research methodology limitations example

How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

See our "Privacy Policy"

Ensure your structure and ideas are consistent and clearly communicated

Pair your Premium Editing with our add-on service Presubmission Review for an overall assessment of your manuscript.

21 Research Limitations Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

Learn about our Editorial Process

Research limitations refer to the potential weaknesses inherent in a study. All studies have limitations of some sort, meaning declaring limitations doesn’t necessarily need to be a bad thing, so long as your declaration of limitations is well thought-out and explained.

Rarely is a study perfect. Researchers have to make trade-offs when developing their studies, which are often based upon practical considerations such as time and monetary constraints, weighing the breadth of participants against the depth of insight, and choosing one methodology or another.

In research, studies can have limitations such as limited scope, researcher subjectivity, and lack of available research tools.

Acknowledging the limitations of your study should be seen as a strength. It demonstrates your willingness for transparency, humility, and submission to the scientific method and can bolster the integrity of the study. It can also inform future research direction.

Typically, scholars will explore the limitations of their study in either their methodology section, their conclusion section, or both.

Research Limitations Examples

Qualitative and quantitative research offer different perspectives and methods in exploring phenomena, each with its own strengths and limitations. So, I’ve split the limitations examples sections into qualitative and quantitative below.

Qualitative Research Limitations

Qualitative research seeks to understand phenomena in-depth and in context. It focuses on the ‘why’ and ‘how’ questions.

It’s often used to explore new or complex issues, and it provides rich, detailed insights into participants’ experiences, behaviors, and attitudes. However, these strengths also create certain limitations, as explained below.

1. Subjectivity

Qualitative research often requires the researcher to interpret subjective data. One researcher may examine a text and identify different themes or concepts as more dominant than others.

Close qualitative readings of texts are necessarily subjective – and while this may be a limitation, qualitative researchers argue this is the best way to deeply understand everything in context.

Suggested Solution and Response: To minimize subjectivity bias, you could consider cross-checking your own readings of themes and data against other scholars’ readings and interpretations. This may involve giving the raw data to a supervisor or colleague and asking them to code the data separately, then coming together to compare and contrast results.

2. Researcher Bias

The concept of researcher bias is related to, but slightly different from, subjectivity.

Researcher bias refers to the perspectives and opinions you bring with you when doing your research.

For example, a researcher who is explicitly of a certain philosophical or political persuasion may bring that persuasion to bear when interpreting data.

In many scholarly traditions, we will attempt to minimize researcher bias through the utilization of clear procedures that are set out in advance or through the use of statistical analysis tools.

However, in other traditions, such as in postmodern feminist research , declaration of bias is expected, and acknowledgment of bias is seen as a positive because, in those traditions, it is believed that bias cannot be eliminated from research, so instead, it is a matter of integrity to present it upfront.

Suggested Solution and Response: Acknowledge the potential for researcher bias and, depending on your theoretical framework , accept this, or identify procedures you have taken to seek a closer approximation to objectivity in your coding and analysis.

3. Generalizability

If you’re struggling to find a limitation to discuss in your own qualitative research study, then this one is for you: all qualitative research, of all persuasions and perspectives, cannot be generalized.

This is a core feature that sets qualitative data and quantitative data apart.

The point of qualitative data is to select case studies and similarly small corpora and dig deep through in-depth analysis and thick description of data.

Often, this will also mean that you have a non-randomized sample size.

While this is a positive – you’re going to get some really deep, contextualized, interesting insights – it also means that the findings may not be generalizable to a larger population that may not be representative of the small group of people in your study.

Suggested Solution and Response: Suggest future studies that take a quantitative approach to the question.

4. The Hawthorne Effect

The Hawthorne effect refers to the phenomenon where research participants change their ‘observed behavior’ when they’re aware that they are being observed.

This effect was first identified by Elton Mayo who conducted studies of the effects of various factors ton workers’ productivity. He noticed that no matter what he did – turning up the lights, turning down the lights, etc. – there was an increase in worker outputs compared to prior to the study taking place.

Mayo realized that the mere act of observing the workers made them work harder – his observation was what was changing behavior.

So, if you’re looking for a potential limitation to name for your observational research study , highlight the possible impact of the Hawthorne effect (and how you could reduce your footprint or visibility in order to decrease its likelihood).

Suggested Solution and Response: Highlight ways you have attempted to reduce your footprint while in the field, and guarantee anonymity to your research participants.

5. Replicability

Quantitative research has a great benefit in that the studies are replicable – a researcher can get a similar sample size, duplicate the variables, and re-test a study. But you can’t do that in qualitative research.

Qualitative research relies heavily on context – a specific case study or specific variables that make a certain instance worthy of analysis. As a result, it’s often difficult to re-enter the same setting with the same variables and repeat the study.

Furthermore, the individual researcher’s interpretation is more influential in qualitative research, meaning even if a new researcher enters an environment and makes observations, their observations may be different because subjectivity comes into play much more. This doesn’t make the research bad necessarily (great insights can be made in qualitative research), but it certainly does demonstrate a weakness of qualitative research.

6. Limited Scope

“Limited scope” is perhaps one of the most common limitations listed by researchers – and while this is often a catch-all way of saying, “well, I’m not studying that in this study”, it’s also a valid point.

No study can explore everything related to a topic. At some point, we have to make decisions about what’s included in the study and what is excluded from the study.

So, you could say that a limitation of your study is that it doesn’t look at an extra variable or concept that’s certainly worthy of study but will have to be explored in your next project because this project has a clearly and narrowly defined goal.

Suggested Solution and Response: Be clear about what’s in and out of the study when writing your research question.

7. Time Constraints

This is also a catch-all claim you can make about your research project: that you would have included more people in the study, looked at more variables, and so on. But you’ve got to submit this thing by the end of next semester! You’ve got time constraints.

And time constraints are a recognized reality in all research.

But this means you’ll need to explain how time has limited your decisions. As with “limited scope”, this may mean that you had to study a smaller group of subjects, limit the amount of time you spent in the field, and so forth.

Suggested Solution and Response: Suggest future studies that will build on your current work, possibly as a PhD project.

8. Resource Intensiveness

Qualitative research can be expensive due to the cost of transcription, the involvement of trained researchers, and potential travel for interviews or observations.

So, resource intensiveness is similar to the time constraints concept. If you don’t have the funds, you have to make decisions about which tools to use, which statistical software to employ, and how many research assistants you can dedicate to the study.

Suggested Solution and Response: Suggest future studies that will gain more funding on the back of this ‘ exploratory study ‘.

9. Coding Difficulties

Data analysis in qualitative research often involves coding, which can be subjective and complex, especially when dealing with ambiguous or contradicting data.

After naming this as a limitation in your research, it’s important to explain how you’ve attempted to address this. Some ways to ‘limit the limitation’ include:

• Triangulation: Have 2 other researchers code the data as well and cross-check your results with theirs to identify outliers that may need to be re-examined, debated with the other researchers, or removed altogether.
• Procedure: Use a clear coding procedure to demonstrate reliability in your coding process. I personally use the thematic network analysis method outlined in this academic article by Attride-Stirling (2001).

Suggested Solution and Response: Triangulate your coding findings with colleagues, and follow a thematic network analysis procedure.

10. Risk of Non-Responsiveness

There is always a risk in research that research participants will be unwilling or uncomfortable sharing their genuine thoughts and feelings in the study.

This is particularly true when you’re conducting research on sensitive topics, politicized topics, or topics where the participant is expressing vulnerability .

This is similar to the Hawthorne effect (aka participant bias), where participants change their behaviors in your presence; but it goes a step further, where participants actively hide their true thoughts and feelings from you.

Suggested Solution and Response: One way to manage this is to try to include a wider group of people with the expectation that there will be non-responsiveness from some participants.

11. Risk of Attrition

Attrition refers to the process of losing research participants throughout the study.

This occurs most commonly in longitudinal studies , where a researcher must return to conduct their analysis over spaced periods of time, often over a period of years.

Things happen to people over time – they move overseas, their life experiences change, they get sick, change their minds, and even die. The more time that passes, the greater the risk of attrition.

Suggested Solution and Response: One way to manage this is to try to include a wider group of people with the expectation that there will be attrition over time.

12. Difficulty in Maintaining Confidentiality and Anonymity

Given the detailed nature of qualitative data , ensuring participant anonymity can be challenging.

If you have a sensitive topic in a specific case study, even anonymizing research participants sometimes isn’t enough. People might be able to induce who you’re talking about.

Sometimes, this will mean you have to exclude some interesting data that you collected from your final report. Confidentiality and anonymity come before your findings in research ethics – and this is a necessary limiting factor.

Suggested Solution and Response: Highlight the efforts you have taken to anonymize data, and accept that confidentiality and accountability place extremely important constraints on academic research.

13. Difficulty in Finding Research Participants

A study that looks at a very specific phenomenon or even a specific set of cases within a phenomenon means that the pool of potential research participants can be very low.

Compile on top of this the fact that many people you approach may choose not to participate, and you could end up with a very small corpus of subjects to explore. This may limit your ability to make complete findings, even in a quantitative sense.

You may need to therefore limit your research question and objectives to something more realistic.

Suggested Solution and Response: Highlight that this is going to limit the study’s generalizability significantly.

14. Ethical Limitations

Ethical limitations refer to the things you cannot do based on ethical concerns identified either by yourself or your institution’s ethics review board.

This might include threats to the physical or psychological well-being of your research subjects, the potential of releasing data that could harm a person’s reputation, and so on.

Furthermore, even if your study follows all expected standards of ethics, you still, as an ethical researcher, need to allow a research participant to pull out at any point in time, after which you cannot use their data, which demonstrates an overlap between ethical constraints and participant attrition.

Suggested Solution and Response: Highlight that these ethical limitations are inevitable but important to sustain the integrity of the research.

For more on Qualitative Research, Explore my Qualitative Research Guide

Quantitative Research Limitations

Quantitative research focuses on quantifiable data and statistical, mathematical, or computational techniques. It’s often used to test hypotheses, assess relationships and causality, and generalize findings across larger populations.

Quantitative research is widely respected for its ability to provide reliable, measurable, and generalizable data (if done well!). Its structured methodology has strengths over qualitative research, such as the fact it allows for replication of the study, which underpins the validity of the research.

However, this approach is not without it limitations, explained below.

1. Over-Simplification

Quantitative research is powerful because it allows you to measure and analyze data in a systematic and standardized way. However, one of its limitations is that it can sometimes simplify complex phenomena or situations.

In other words, it might miss the subtleties or nuances of the research subject.

For example, if you’re studying why people choose a particular diet, a quantitative study might identify factors like age, income, or health status. But it might miss other aspects, such as cultural influences or personal beliefs, that can also significantly impact dietary choices.

When writing about this limitation, you can say that your quantitative approach, while providing precise measurements and comparisons, may not capture the full complexity of your subjects of study.

Suggested Solution and Response: Suggest a follow-up case study using the same research participants in order to gain additional context and depth.

2. Lack of Context

Another potential issue with quantitative research is that it often focuses on numbers and statistics at the expense of context or qualitative information.

Let’s say you’re studying the effect of classroom size on student performance. You might find that students in smaller classes generally perform better. However, this doesn’t take into account other variables, like teaching style , student motivation, or family support.

When describing this limitation, you might say, “Although our research provides important insights into the relationship between class size and student performance, it does not incorporate the impact of other potentially influential variables. Future research could benefit from a mixed-methods approach that combines quantitative analysis with qualitative insights.”

3. Applicability to Real-World Settings

Oftentimes, experimental research takes place in controlled environments to limit the influence of outside factors.

This control is great for isolation and understanding the specific phenomenon but can limit the applicability or “external validity” of the research to real-world settings.

For example, if you conduct a lab experiment to see how sleep deprivation impacts cognitive performance, the sterile, controlled lab environment might not reflect real-world conditions where people are dealing with multiple stressors.

Therefore, when explaining the limitations of your quantitative study in your methodology section, you could state:

“While our findings provide valuable information about [topic], the controlled conditions of the experiment may not accurately represent real-world scenarios where extraneous variables will exist. As such, the direct applicability of our results to broader contexts may be limited.”

Suggested Solution and Response: Suggest future studies that will engage in real-world observational research, such as ethnographic research.

4. Limited Flexibility

Once a quantitative study is underway, it can be challenging to make changes to it. This is because, unlike in grounded research, you’re putting in place your study in advance, and you can’t make changes part-way through.

Your study design, data collection methods, and analysis techniques need to be decided upon before you start collecting data.

For example, if you are conducting a survey on the impact of social media on teenage mental health, and halfway through, you realize that you should have included a question about their screen time, it’s generally too late to add it.

When discussing this limitation, you could write something like, “The structured nature of our quantitative approach allows for consistent data collection and analysis but also limits our flexibility to adapt and modify the research process in response to emerging insights and ideas.”

Suggested Solution and Response: Suggest future studies that will use mixed-methods or qualitative research methods to gain additional depth of insight.

5. Risk of Survey Error

Surveys are a common tool in quantitative research, but they carry risks of error.

There can be measurement errors (if a question is misunderstood), coverage errors (if some groups aren’t adequately represented), non-response errors (if certain people don’t respond), and sampling errors (if your sample isn’t representative of the population).

For instance, if you’re surveying college students about their study habits , but only daytime students respond because you conduct the survey during the day, your results will be skewed.

In discussing this limitation, you might say, “Despite our best efforts to develop a comprehensive survey, there remains a risk of survey error, including measurement, coverage, non-response, and sampling errors. These could potentially impact the reliability and generalizability of our findings.”

Suggested Solution and Response: Suggest future studies that will use other survey tools to compare and contrast results.

6. Limited Ability to Probe Answers

With quantitative research, you typically can’t ask follow-up questions or delve deeper into participants’ responses like you could in a qualitative interview.

For instance, imagine you are surveying 500 students about study habits in a questionnaire. A respondent might indicate that they study for two hours each night. You might want to follow up by asking them to elaborate on what those study sessions involve or how effective they feel their habits are.

However, quantitative research generally disallows this in the way a qualitative semi-structured interview could.

When discussing this limitation, you might write, “Given the structured nature of our survey, our ability to probe deeper into individual responses is limited. This means we may not fully understand the context or reasoning behind the responses, potentially limiting the depth of our findings.”

Suggested Solution and Response: Suggest future studies that engage in mixed-method or qualitative methodologies to address the issue from another angle.

7. Reliance on Instruments for Data Collection

In quantitative research, the collection of data heavily relies on instruments like questionnaires, surveys, or machines.

The limitation here is that the data you get is only as good as the instrument you’re using. If the instrument isn’t designed or calibrated well, your data can be flawed.

For instance, if you’re using a questionnaire to study customer satisfaction and the questions are vague, confusing, or biased, the responses may not accurately reflect the customers’ true feelings.

When discussing this limitation, you could say, “Our study depends on the use of questionnaires for data collection. Although we have put significant effort into designing and testing the instrument, it’s possible that inaccuracies or misunderstandings could potentially affect the validity of the data collected.”

Suggested Solution and Response: Suggest future studies that will use different instruments but examine the same variables to triangulate results.

8. Time and Resource Constraints (Specific to Quantitative Research)

Quantitative research can be time-consuming and resource-intensive, especially when dealing with large samples.

It often involves systematic sampling, rigorous design, and sometimes complex statistical analysis.

If resources and time are limited, it can restrict the scale of your research, the techniques you can employ, or the extent of your data analysis.

For example, you may want to conduct a nationwide survey on public opinion about a certain policy. However, due to limited resources, you might only be able to survey people in one city.

When writing about this limitation, you could say, “Given the scope of our research and the resources available, we are limited to conducting our survey within one city, which may not fully represent the nationwide public opinion. Hence, the generalizability of the results may be limited.”

Suggested Solution and Response: Suggest future studies that will have more funding or longer timeframes.

How to Discuss Your Research Limitations

1. in your research proposal and methodology section.

In the research proposal, which will become the methodology section of your dissertation, I would recommend taking the four following steps, in order:

• Be Explicit about your Scope – If you limit the scope of your study in your research question, aims, and objectives, then you can set yourself up well later in the methodology to say that certain questions are “outside the scope of the study.” For example, you may identify the fact that the study doesn’t address a certain variable, but you can follow up by stating that the research question is specifically focused on the variable that you are examining, so this limitation would need to be looked at in future studies.
• Acknowledge the Limitation – Acknowledging the limitations of your study demonstrates reflexivity and humility and can make your research more reliable and valid. It also pre-empts questions the people grading your paper may have, so instead of them down-grading you for your limitations; they will congratulate you on explaining the limitations and how you have addressed them!
• Explain your Decisions – You may have chosen your approach (despite its limitations) for a very specific reason. This might be because your approach remains, on balance, the best one to answer your research question. Or, it might be because of time and monetary constraints that are outside of your control.
• Highlight the Strengths of your Approach – Conclude your limitations section by strongly demonstrating that, despite limitations, you’ve worked hard to minimize the effects of the limitations and that you have chosen your specific approach and methodology because it’s also got some terrific strengths. Name the strengths.

Overall, you’ll want to acknowledge your own limitations but also explain that the limitations don’t detract from the value of your study as it stands.

2. In the Conclusion Section or Chapter

In the conclusion of your study, it is generally expected that you return to a discussion of the study’s limitations. Here, I recommend the following steps:

• Acknowledge issues faced – After completing your study, you will be increasingly aware of issues you may have faced that, if you re-did the study, you may have addressed earlier in order to avoid those issues. Acknowledge these issues as limitations, and frame them as recommendations for subsequent studies.
• Suggest further research – Scholarly research aims to fill gaps in the current literature and knowledge. Having established your expertise through your study, suggest lines of inquiry for future researchers. You could state that your study had certain limitations, and “future studies” can address those limitations.
• Suggest a mixed methods approach – Qualitative and quantitative research each have pros and cons. So, note those ‘cons’ of your approach, then say the next study should approach the topic using the opposite methodology or could approach it using a mixed-methods approach that could achieve the benefits of quantitative studies with the nuanced insights of associated qualitative insights as part of an in-study case-study.

Overall, be clear about both your limitations and how those limitations can inform future studies.

In sum, each type of research method has its own strengths and limitations. Qualitative research excels in exploring depth, context, and complexity, while quantitative research excels in examining breadth, generalizability, and quantifiable measures. Despite their individual limitations, each method contributes unique and valuable insights, and researchers often use them together to provide a more comprehensive understanding of the phenomenon being studied.

Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research , 1 (3), 385-405. ( Source )

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J., & Williams, R. A. (2021).  SAGE research methods foundations . London: Sage Publications.

Clark, T., Foster, L., Bryman, A., & Sloan, L. (2021).  Bryman’s social research methods . Oxford: Oxford University Press.

Köhler, T., Smith, A., & Bhakoo, V. (2022). Templates in qualitative research methods: Origins, limitations, and new directions.  Organizational Research Methods ,  25 (2), 183-210. ( Source )

Lenger, A. (2019). The rejection of qualitative research methods in economics.  Journal of Economic Issues ,  53 (4), 946-965. ( Source )

Taherdoost, H. (2022). What are different research approaches? Comprehensive review of qualitative, quantitative, and mixed method research, their applications, types, and limitations.  Journal of Management Science & Engineering Research ,  5 (1), 53-63. ( Source )

Walliman, N. (2021).  Research methods: The basics . New York: Routledge.

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 101 Class Group Name Ideas (for School Students)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 19 Top Cognitive Psychology Theories (Explained)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 119 Bloom’s Taxonomy Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ All 6 Levels of Understanding (on Bloom’s Taxonomy)

Leave a Comment Cancel Reply

Your email address will not be published. Required fields are marked *

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Limitations of the Study
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. Study limitations are the constraints placed on the ability to generalize from the results, to further describe applications to practice, and/or related to the utility of findings that are the result of the ways in which you initially chose to design the study or the method used to establish internal and external validity or the result of unanticipated challenges that emerged during the study.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Theofanidis, Dimitrios and Antigoni Fountouki. "Limitations and Delimitations in the Research Process." Perioperative Nursing 7 (September-December 2018): 155-163. .

Importance of...

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and have your grade lowered because you appeared to have ignored them or didn't realize they existed.

Keep in mind that acknowledgment of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgment of a study's limitations also provides you with opportunities to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and discuss how they possibly impacted your results. Note that descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is generally less relevant in qualitative research if explained in the context of the research problem.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but provide cogent reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe a need for future research based on designing a different method for gathering data.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian! In cases when a librarian has confirmed that there is little or no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design ]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to the accuracy of what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency, but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, data, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this needs to be described. Also, include an explanation why being denied or limited access did not prevent you from following through on your study.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, event, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. NOTE :   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias. For example, if a previous study only used boys to examine how music education supports effective math skills, describe how your research expands the study to include girls.
• Fluency in a language -- if your research focuses , for example, on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic or to speak with these students in their primary language. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods. Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings!

After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitations of your study. Inflating the importance of your study's findings could be perceived by your readers as an attempt hide its flaws or encourage a biased interpretation of the results. A small measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated. Or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may very well be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Lewis, George H. and Jonathan F. Lewis. “The Dog in the Night-Time: Negative Evidence in Social Research.” The British Journal of Sociology 31 (December 1980): 544-558.

Yet Another Writing Tip

Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgment about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Boddy, Clive Roland. "Sample Size for Qualitative Research." Qualitative Market Research: An International Journal 19 (2016): 426-432; Huberman, A. Michael and Matthew B. Miles. "Data Management and Analysis Methods." In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444; Blaikie, Norman. "Confounding Issues Related to Determining Sample Size in Qualitative Research." International Journal of Social Research Methodology 21 (2018): 635-641; Oppong, Steward Harrison. "The Problem of Sampling in qualitative Research." Asian Journal of Management Sciences and Education 2 (2013): 202-210.

• << Previous: 8. The Discussion
• Next: 9. The Conclusion >>
• Last Updated: Jun 18, 2024 10:45 AM
• URL: https://libguides.usc.edu/writingguide

• Affiliate Program

• UNITED STATES
• 台灣 (TAIWAN)
• TÜRKIYE (TURKEY)
• Academic Editing Services
• - Research Paper
• - Journal Manuscript
• - Dissertation
• - College & University Assignments
• Admissions Editing Services
• - Application Essay
• - Personal Statement
• - Recommendation Letter
• - Cover Letter
• - CV/Resume
• Business Editing Services
• - Business Documents
• - Report & Brochure
• - Website & Blog
• Writer Editing Services
• - Script & Screenplay
• Our Editors
• Client Reviews
• Editing & Proofreading Prices
• Wordvice Points
• Partner Discount
• Plagiarism Checker

APA Citation Generator

MLA Citation Generator

Chicago Citation Generator

Vancouver Citation Generator

• - APA Style
• - MLA Style
• - Chicago Style
• - Vancouver Style
• Writing & Editing Guide
• Academic Resources
• Admissions Resources

How to Present the Limitations of the Study Examples

What are the limitations of a study?

The limitations of a study are the elements of methodology or study design that impact the interpretation of your research results. The limitations essentially detail any flaws or shortcomings in your study. Study limitations can exist due to constraints on research design, methodology, materials, etc., and these factors may impact the findings of your study. However, researchers are often reluctant to discuss the limitations of their study in their papers, feeling that bringing up limitations may undermine its research value in the eyes of readers and reviewers.

In spite of the impact it might have (and perhaps because of it) you should clearly acknowledge any limitations in your research paper in order to show readers—whether journal editors, other researchers, or the general public—that you are aware of these limitations and to explain how they affect the conclusions that can be drawn from the research.

In this article, we provide some guidelines for writing about research limitations, show examples of some frequently seen study limitations, and recommend techniques for presenting this information. And after you have finished drafting and have received manuscript editing for your work, you still might want to follow this up with academic editing before submitting your work to your target journal.

Why do I need to include limitations of research in my paper?

Although limitations address the potential weaknesses of a study, writing about them toward the end of your paper actually strengthens your study by identifying any problems before other researchers or reviewers find them.

Furthermore, pointing out study limitations shows that you’ve considered the impact of research weakness thoroughly and have an in-depth understanding of your research topic. Since all studies face limitations, being honest and detailing these limitations will impress researchers and reviewers more than ignoring them.

Where should I put the limitations of the study in my paper?

Some limitations might be evident to researchers before the start of the study, while others might become clear while you are conducting the research. Whether these limitations are anticipated or not, and whether they are due to research design or to methodology, they should be clearly identified and discussed in the discussion section —the final section of your paper. Most journals now require you to include a discussion of potential limitations of your work, and many journals now ask you to place this “limitations section” at the very end of your article. 

Some journals ask you to also discuss the strengths of your work in this section, and some allow you to freely choose where to include that information in your discussion section—make sure to always check the author instructions of your target journal before you finalize a manuscript and submit it for peer review .

Limitations of the Study Examples

There are several reasons why limitations of research might exist. The two main categories of limitations are those that result from the methodology and those that result from issues with the researcher(s).

Common Methodological Limitations of Studies

Limitations of research due to methodological problems can be addressed by clearly and directly identifying the potential problem and suggesting ways in which this could have been addressed—and SHOULD be addressed in future studies. The following are some major potential methodological issues that can impact the conclusions researchers can draw from the research.

Issues with research samples and selection

Sampling errors occur when a probability sampling method is used to select a sample, but that sample does not reflect the general population or appropriate population concerned. This results in limitations of your study known as “sample bias” or “selection bias.”

For example, if you conducted a survey to obtain your research results, your samples (participants) were asked to respond to the survey questions. However, you might have had limited ability to gain access to the appropriate type or geographic scope of participants. In this case, the people who responded to your survey questions may not truly be a random sample.

Insufficient sample size for statistical measurements

When conducting a study, it is important to have a sufficient sample size in order to draw valid conclusions. The larger the sample, the more precise your results will be. If your sample size is too small, it will be difficult to identify significant relationships in the data.

Normally, statistical tests require a larger sample size to ensure that the sample is considered representative of a population and that the statistical result can be generalized to a larger population. It is a good idea to understand how to choose an appropriate sample size before you conduct your research by using scientific calculation tools—in fact, many journals now require such estimation to be included in every manuscript that is sent out for review.

Lack of previous research studies on the topic

Citing and referencing prior research studies constitutes the basis of the literature review for your thesis or study, and these prior studies provide the theoretical foundations for the research question you are investigating. However, depending on the scope of your research topic, prior research studies that are relevant to your thesis might be limited.

When there is very little or no prior research on a specific topic, you may need to develop an entirely new research typology. In this case, discovering a limitation can be considered an important opportunity to identify literature gaps and to present the need for further development in the area of study.

Methods/instruments/techniques used to collect the data

After you complete your analysis of the research findings (in the discussion section), you might realize that the manner in which you have collected the data or the ways in which you have measured variables has limited your ability to conduct a thorough analysis of the results.

For example, you might realize that you should have addressed your survey questions from another viable perspective, or that you were not able to include an important question in the survey. In these cases, you should acknowledge the deficiency or deficiencies by stating a need for future researchers to revise their specific methods for collecting data that includes these missing elements.

Common Limitations of the Researcher(s)

Study limitations that arise from situations relating to the researcher or researchers (whether the direct fault of the individuals or not) should also be addressed and dealt with, and remedies to decrease these limitations—both hypothetically in your study, and practically in future studies—should be proposed.

Limited access to data

If your research involved surveying certain people or organizations, you might have faced the problem of having limited access to these respondents. Due to this limited access, you might need to redesign or restructure your research in a different way. In this case, explain the reasons for limited access and be sure that your finding is still reliable and valid despite this limitation.

Time constraints

Just as students have deadlines to turn in their class papers, academic researchers might also have to meet deadlines for submitting a manuscript to a journal or face other time constraints related to their research (e.g., participants are only available during a certain period; funding runs out; collaborators move to a new institution). The time available to study a research problem and to measure change over time might be constrained by such practical issues. If time constraints negatively impacted your study in any way, acknowledge this impact by mentioning a need for a future study (e.g., a longitudinal study) to answer this research problem.

Conflicts arising from cultural bias and other personal issues

Researchers might hold biased views due to their cultural backgrounds or perspectives of certain phenomena, and this can affect a study’s legitimacy. Also, it is possible that researchers will have biases toward data and results that only support their hypotheses or arguments. In order to avoid these problems, the author(s) of a study should examine whether the way the research problem was stated and the data-gathering process was carried out appropriately.

Steps for Organizing Your Study Limitations Section

When you discuss the limitations of your study, don’t simply list and describe your limitations—explain how these limitations have influenced your research findings. There might be multiple limitations in your study, but you only need to point out and explain those that directly relate to and impact how you address your research questions.

We suggest that you divide your limitations section into three steps: (1) identify the study limitations; (2) explain how they impact your study in detail; and (3) propose a direction for future studies and present alternatives. By following this sequence when discussing your study’s limitations, you will be able to clearly demonstrate your study’s weakness without undermining the quality and integrity of your research.

Step 1. Identify the limitation(s) of the study

• This part should comprise around 10%-20% of your discussion of study limitations.

The first step is to identify the particular limitation(s) that affected your study. There are many possible limitations of research that can affect your study, but you don’t need to write a long review of all possible study limitations. A 200-500 word critique is an appropriate length for a research limitations section. In the beginning of this section, identify what limitations your study has faced and how important these limitations are.

You only need to identify limitations that had the greatest potential impact on: (1) the quality of your findings, and (2) your ability to answer your research question.

Step 2. Explain these study limitations in detail

• This part should comprise around 60-70% of your discussion of limitations.

After identifying your research limitations, it’s time to explain the nature of the limitations and how they potentially impacted your study. For example, when you conduct quantitative research, a lack of probability sampling is an important issue that you should mention. On the other hand, when you conduct qualitative research, the inability to generalize the research findings could be an issue that deserves mention.

Explain the role these limitations played on the results and implications of the research and justify the choice you made in using this “limiting” methodology or other action in your research. Also, make sure that these limitations didn’t undermine the quality of your dissertation .

Step 3. Propose a direction for future studies and present alternatives (optional)

• This part should comprise around 10-20% of your discussion of limitations.

After acknowledging the limitations of the research, you need to discuss some possible ways to overcome these limitations in future studies. One way to do this is to present alternative methodologies and ways to avoid issues with, or “fill in the gaps of” the limitations of this study you have presented.  Discuss both the pros and cons of these alternatives and clearly explain why researchers should choose these approaches.

Make sure you are current on approaches used by prior studies and the impacts they have had on their findings. Cite review articles or scientific bodies that have recommended these approaches and why. This might be evidence in support of the approach you chose, or it might be the reason you consider your choices to be included as limitations. This process can act as a justification for your approach and a defense of your decision to take it while acknowledging the feasibility of other approaches.

P hrases and Tips for Introducing Your Study Limitations in the Discussion Section

The following phrases are frequently used to introduce the limitations of the study:

• “There may be some possible limitations in this study.”
• “The findings of this study have to be seen in light of some limitations.”
•  “The first is the…The second limitation concerns the…”
•  “The empirical results reported herein should be considered in the light of some limitations.”
• “This research, however, is subject to several limitations.”
• “The primary limitation to the generalization of these results is…”
• “Nonetheless, these results must be interpreted with caution and a number of limitations should be borne in mind.”
• “As with the majority of studies, the design of the current study is subject to limitations.”
• “There are two major limitations in this study that could be addressed in future research. First, the study focused on …. Second ….”

For more articles on research writing and the journal submissions and publication process, visit Wordvice’s Academic Resources page.

And be sure to receive professional English editing and proofreading services , including paper editing services , for your journal manuscript before submitting it to journal editors.

Wordvice Resources

Proofreading & Editing Guide

Writing the Results Section for a Research Paper

How to Write a Literature Review

Research Writing Tips: How to Draft a Powerful Discussion Section

How to Captivate Journal Readers with a Strong Introduction

Tips That Will Make Your Abstract a Success!

APA In-Text Citation Guide for Research Writing

Additional Resources

• Diving Deeper into Limitations and Delimitations (PhD student)
• Organizing Your Social Sciences Research Paper: Limitations of the Study (USC Library)
• Research Limitations (Research Methodology)
• How to Present Limitations and Alternatives (UMASS)

Article References

Pearson-Stuttard, J., Kypridemos, C., Collins, B., Mozaffarian, D., Huang, Y., Bandosz, P.,…Micha, R. (2018). Estimating the health and economic effects of the proposed US Food and Drug Administration voluntary sodium reformulation: Microsimulation cost-effectiveness analysis. PLOS. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002551

Xu, W.L, Pedersen, N.L., Keller, L., Kalpouzos, G., Wang, H.X., Graff, C,. Fratiglioni, L. (2015). HHEX_23 AA Genotype Exacerbates Effect of Diabetes on Dementia and Alzheimer Disease: A Population-Based Longitudinal Study. PLOS. Retrieved from https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001853

What are the limitations in research and how to write them?

Learn about the potential limitations in research and how to appropriately address them in order to deliver honest and ethical research.

It is fairly uncommon for researchers to stumble into the term research limitations when working on their research paper. Limitations in research can arise owing to constraints on design, methods, materials, and so on, and these aspects, unfortunately, may have an influence on your subject’s findings.

In this Mind The Graph’s article, we’ll discuss some recommendations for writing limitations in research , provide examples of various common types of limitations, and suggest how to properly present this information.

What are the limitations in research?

The limitations in research are the constraints in design, methods or even researchers’ limitations that affect and influence the interpretation of your research’s ultimate findings. These are limitations on the generalization and usability of findings that emerge from the design of the research and/or the method employed to ensure validity both internally and externally. 

Researchers are usually cautious to acknowledge the limitations of their research in their publications for fear of undermining the research’s scientific validity. No research is faultless or covers every possible angle. As a result, addressing the constraints of your research exhibits honesty and integrity .

Why should include limitations of research in my paper?

Though limitations tackle potential flaws in research, commenting on them at the conclusion of your paper, by demonstrating that you are aware of these limitations and explaining how they impact the conclusions that may be taken from the research, improves your research by disclosing any issues before other researchers or reviewers do . 

Additionally, emphasizing research constraints implies that you have thoroughly investigated the ramifications of research shortcomings and have a thorough understanding of your research problem. 

Limits exist in any research; being honest about them and explaining them would impress researchers and reviewers more than disregarding them. 

Remember that acknowledging a research’s shortcomings offers a chance to provide ideas for future research, but be careful to describe how your study may help to concentrate on these outstanding problems.

Possible limitations examples

Here are some limitations connected to methodology and the research procedure that you may need to explain and discuss in connection to your findings.

Methodological limitations

Sample size.

The number of units of analysis used in your study is determined by the sort of research issue being investigated. It is important to note that if your sample is too small, finding significant connections in the data will be challenging, as statistical tests typically require a larger sample size to ensure a fair representation and this can be limiting. 

Lack of available or reliable data

A lack of data or trustworthy data will almost certainly necessitate limiting the scope of your research or the size of your sample, or it can be a substantial impediment to identifying a pattern and a relevant connection.

Lack of prior research on the subject

Citing previous research papers forms the basis of your literature review and aids in comprehending the research subject you are researching. Yet there may be little if any, past research on your issue.

The measure used to collect data

After finishing your analysis of the findings, you realize that the method you used to collect data limited your capacity to undertake a comprehensive evaluation of the findings. Recognize the flaw by mentioning that future researchers should change the specific approach for data collection.

Issues with research samples and selection

Sampling inaccuracies arise when a probability sampling method is employed to choose a sample, but that sample does not accurately represent the overall population or the relevant group. As a result, your study suffers from “sampling bias” or “selection bias.”

Limitations of the research

When your research requires polling certain persons or a specific group, you may have encountered the issue of limited access to these interviewees. Because of the limited access, you may need to reorganize or rearrange your research. In this scenario, explain why access is restricted and ensure that your findings are still trustworthy and valid despite the constraint.

Time constraints

Practical difficulties may limit the amount of time available to explore a research issue and monitor changes as they occur. If time restrictions have any detrimental influence on your research, recognize this impact by expressing the necessity for a future investigation.

Due to their cultural origins or opinions on observed events, researchers may carry biased opinions, which can influence the credibility of a research. Furthermore, researchers may exhibit biases toward data and conclusions that only support their hypotheses or arguments.

The structure of the limitations section 

The limitations of your research are usually stated at the beginning of the discussion section of your paper so that the reader is aware of and comprehends the limitations prior to actually reading the rest of your findings, or they are stated at the end of the discussion section as an acknowledgment of the need for further research.

The ideal way is to divide your limitations section into three steps: 

1. Identify the research constraints; 

2. Describe in great detail how they affect your research; 

3. Mention the opportunity for future investigations and give possibilities. 

By following this method while addressing the constraints of your research, you will be able to effectively highlight your research’s shortcomings without jeopardizing the quality and integrity of your research.

Present your research or paper in an innovative way

If you want your readers to be engaged and participate in your research, try Mind The Graph tool to add visual assets to your content. Infographics may improve comprehension and are easy to read, just as the Mind The Graph tool is simple to use and offers a variety of templates from which you can select the one that best suits your information.

Subscribe to our newsletter

Exclusive high quality content about effective visual communication in science.

About Jessica Abbadia

Jessica Abbadia is a lawyer that has been working in Digital Marketing since 2020, improving organic performance for apps and websites in various regions through ASO and SEO. Currently developing scientific and intellectual knowledge for the community's benefit. Jessica is an animal rights activist who enjoys reading and drinking strong coffee.

Content tags

How to present limitations in research

Last updated

30 January 2024

Reviewed by

Short on time? Get an AI generated summary of this article instead

Limitations don’t invalidate or diminish your results, but it’s best to acknowledge them. This will enable you to address any questions your study failed to answer because of them.

In this guide, learn how to recognize, present, and overcome limitations in research.

• What is a research limitation?

Research limitations are weaknesses in your research design or execution that may have impacted outcomes and conclusions. Uncovering limitations doesn’t necessarily indicate poor research design—it just means you encountered challenges you couldn’t have anticipated that limited your research efforts.

Does basic research have limitations?

Basic research aims to provide more information about your research topic . It requires the same standard research methodology and data collection efforts as any other research type, and it can also have limitations.

• Common research limitations

Researchers encounter common limitations when embarking on a study. Limitations can occur in relation to the methods you apply or the research process you design. They could also be connected to you as the researcher.

Methodology limitations

Not having access to data or reliable information can impact the methods used to facilitate your research. A lack of data or reliability may limit the parameters of your study area and the extent of your exploration.

Your sample size may also be affected because you won’t have any direction on how big or small it should be and who or what you should include. Having too few participants won’t adequately represent the population or groups of people needed to draw meaningful conclusions.

Research process limitations

The study’s design can impose constraints on the process. For example, as you’re conducting the research, issues may arise that don’t conform to the data collection methodology you developed. You may not realize until well into the process that you should have incorporated more specific questions or comprehensive experiments to generate the data you need to have confidence in your results.

Constraints on resources can also have an impact. Being limited on participants or participation incentives may limit your sample sizes. Insufficient tools, equipment, and materials to conduct a thorough study may also be a factor.

Common researcher limitations

Here are some of the common researcher limitations you may encounter:

Time: some research areas require multi-year longitudinal approaches, but you might not be able to dedicate that much time. Imagine you want to measure how much memory a person loses as they age. This may involve conducting multiple tests on a sample of participants over 20–30 years, which may be impossible.

Bias: researchers can consciously or unconsciously apply bias to their research. Biases can contribute to relying on research sources and methodologies that will only support your beliefs about the research you’re embarking on. You might also omit relevant issues or participants from the scope of your study because of your biases.

Limited access to data : you may need to pay to access specific databases or journals that would be helpful to your research process. You might also need to gain information from certain people or organizations but have limited access to them. These cases require readjusting your process and explaining why your findings are still reliable.

• Why is it important to identify limitations?

Identifying limitations adds credibility to research and provides a deeper understanding of how you arrived at your conclusions.

Constraints may have prevented you from collecting specific data or information you hoped would prove or disprove your hypothesis or provide a more comprehensive understanding of your research topic.

However, identifying the limitations contributing to your conclusions can inspire further research efforts that help gather more substantial information and data.

• Where to put limitations in a research paper

A research paper is broken up into different sections that appear in the following order:

Introduction

Methodology

The discussion portion of your paper explores your findings and puts them in the context of the overall research. Either place research limitations at the beginning of the discussion section before the analysis of your findings or at the end of the section to indicate that further research needs to be pursued.

What not to include in the limitations section

Evidence that doesn’t support your hypothesis is not a limitation, so you shouldn’t include it in the limitation section. Don’t just list limitations and their degree of severity without further explanation.

• How to present limitations

You’ll want to present the limitations of your study in a way that doesn’t diminish the validity of your research and leave the reader wondering if your results and conclusions have been compromised.

Include only the limitations that directly relate to and impact how you addressed your research questions. Following a specific format enables the reader to develop an understanding of the weaknesses within the context of your findings without doubting the quality and integrity of your research.

Identify the limitations specific to your study

You don’t have to identify every possible limitation that might have occurred during your research process. Only identify those that may have influenced the quality of your findings and your ability to answer your research question.

Explain study limitations in detail

This explanation should be the most significant portion of your limitation section.

Link each limitation with an interpretation and appraisal of their impact on the study. You’ll have to evaluate and explain whether the error, method, or validity issues influenced the study’s outcome and how.

Propose a direction for future studies and present alternatives

In this section, suggest how researchers can avoid the pitfalls you experienced during your research process.

If an issue with methodology was a limitation, propose alternate methods that may help with a smoother and more conclusive research project . Discuss the pros and cons of your alternate recommendation.

Describe steps taken to minimize each limitation

You probably took steps to try to address or mitigate limitations when you noticed them throughout the course of your research project. Describe these steps in the limitation section.

• Limitation example

“Approaches like stem cell transplantation and vaccination in AD [Alzheimer’s disease] work on a cellular or molecular level in the laboratory. However, translation into clinical settings will remain a challenge for the next decade.”

The authors are saying that even though these methods showed promise in helping people with memory loss when conducted in the lab (in other words, using animal studies), more studies are needed. These may be controlled clinical trials, for example. 

However, the short life span of stem cells outside the lab and the vaccination’s severe inflammatory side effects are limitations. Researchers won’t be able to conduct clinical trials until these issues are overcome.

• How to overcome limitations in research

You’ve already started on the road to overcoming limitations in research by acknowledging that they exist. However, you need to ensure readers don’t mistake weaknesses for errors within your research design.

To do this, you’ll need to justify and explain your rationale for the methods, research design, and analysis tools you chose and how you noticed they may have presented limitations.

Your readers need to know that even when limitations presented themselves, you followed best practices and the ethical standards of your field. You didn’t violate any rules and regulations during your research process.

You’ll also want to reinforce the validity of your conclusions and results with multiple sources, methods, and perspectives. This prevents readers from assuming your findings were derived from a single or biased source.

• Learning and improving starts with limitations in research

Dealing with limitations with transparency and integrity helps identify areas for future improvements and developments. It’s a learning process, providing valuable insights into how you can improve methodologies, expand sample sizes, or explore alternate approaches to further support the validity of your findings.

Should you be using a customer insights hub?

Do you want to discover previous research faster?

Do you share your research findings with others?

Do you analyze research data?

Start for free today, add your research, and get to key insights faster

Editor’s picks

Last updated: 18 April 2023

Last updated: 27 February 2023

Last updated: 6 February 2023

Last updated: 6 October 2023

Last updated: 5 February 2023

Last updated: 16 April 2023

Last updated: 7 March 2023

Last updated: 9 March 2023

Last updated: 12 December 2023

Last updated: 11 March 2024

Last updated: 6 March 2024

Last updated: 5 March 2024

Last updated: 13 May 2024

Latest articles

Related topics, .css-je19u9{-webkit-align-items:flex-end;-webkit-box-align:flex-end;-ms-flex-align:flex-end;align-items:flex-end;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-box-flex-wrap:wrap;-webkit-flex-wrap:wrap;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;row-gap:0;text-align:center;max-width:671px;}@media (max-width: 1079px){.css-je19u9{max-width:400px;}.css-je19u9>span{white-space:pre;}}@media (max-width: 799px){.css-je19u9{max-width:400px;}.css-je19u9>span{white-space:pre;}} decide what to .css-1kiodld{max-height:56px;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}@media (max-width: 1079px){.css-1kiodld{display:none;}} build next, decide what to build next.

Users report unexpectedly high data usage, especially during streaming sessions.

Users find it hard to navigate from the home page to relevant playlists in the app.

It would be great to have a sleep timer feature, especially for bedtime listening.

I need better filters to find the songs or artists I’m looking for.

Log in or sign up

Get started for free

Research Limitations: A Comprehensive Guide

Embarking on a research journey is an exciting endeavor, but every study has its boundaries and constraints. Understanding and transparently acknowledging these limitations is a crucial aspect of scholarly work. In this guide, we'll explore the concept of research limitations, why they matter, and how to effectively address and navigate them in your academic endeavors.

1. Defining Research Limitations:

• Definition: Research limitations are the constraints or shortcomings that affect the scope, applicability, and generalizability of a study.
• Inherent in Research: Every research project, regardless of its scale or significance, possesses limitations.

2. Types of Research Limitations:

• Methodological Limitations: Constraints related to the research design, data collection methods, or analytical techniques.
• Sampling Limitations: Issues associated with the representativeness or size of the study sample.
• Contextual Limitations: Restrictions stemming from the specific time, place, or cultural context of the study.
• Resource Limitations: Constraints related to time, budget, or access to necessary resources.

3. Why Acknowledge Limitations?

• Transparency: Acknowledging limitations demonstrates transparency and honesty in your research.
• Robustness of Findings: Recognizing limitations adds nuance to your findings, making them more robust.
• Future Research Directions: Addressing limitations provides a foundation for future researchers to build upon.

4. Identifying Research Limitations:

• Reflect on Methodology: Consider the strengths and weaknesses of your research design, data collection methods, and analysis.
• Examine Sample Characteristics: Evaluate the representativeness and size of your study sample.
• Consider External Factors: Assess external factors that may impact the generalizability of your findings.

5. How to Address Limitations:

• In the Methodology Section: Clearly articulate limitations in the methodology section of your research paper.
• Offer Solutions: If possible, propose ways to mitigate or address identified limitations.
• Future Research Suggestions: Use limitations as a springboard to suggest areas for future research.

6. Common Phrases to Express Limitations:

• "This study is not without limitations."
• "One limitation of our research is..."
• "It is important to acknowledge the constraints of this study, including..."

7. Examples of Addressing Limitations:

• Example 1 (Methodological): "While our survey provided valuable insights, the reliance on self-reported data introduces the possibility of response bias."
• Example 2 (Sampling): "The small sample size of our study limits the generalizability of our findings to a broader population."
• Example 3 (Resource): "Due to budget constraints, our research was limited to a single geographical location, potentially impacting the external validity."

8. Balancing Strengths and Limitations:

• Emphasize Contributions: Highlight the contributions and strengths of your research alongside the limitations.
• Maintain a Positive Tone: Discuss limitations objectively without undermining the significance of your study.

9. Feedback and Peer Review:

• Seek Feedback: Share your research with peers or mentors to gain valuable insights.
• Peer Review: Embrace the feedback received during the peer-review process to enhance the robustness of your work.

10. Continuous Reflection:

• Throughout the Research Process: Continuously reflect on potential limitations during the entire research process.
• Adjust as Needed: Be willing to adjust your approach as you encounter unforeseen challenges.

Conclusion:

Understanding and effectively addressing research limitations is a hallmark of rigorous and responsible scholarship. By openly acknowledging these constraints, you not only enhance the credibility of your work but also contribute to the broader academic discourse. Embrace the nuances of your research journey, navigate its limitations thoughtfully, and pave the way for future investigations.

Related Guides

• How to Write an Essay Outline: A Step-by-Step Guide
• Your Ultimate Guide to In-text Citation
• Research Methods : A Comprehensive Guide
• How to Write a Thesis Statement?
• The Art of Wringing a Research Conclusion
• Analyze and Discuss Your Research Findings Like a Pro

Research Limitations

It is for sure that your research will have some limitations and it is normal. However, it is critically important for you to be striving to minimize the range of scope of limitations throughout the research process.  Also, you need to provide the acknowledgement of your research limitations in conclusions chapter honestly.

It is always better to identify and acknowledge shortcomings of your work, rather than to leave them pointed out to your by your dissertation assessor. While discussing your research limitations, don’t just provide the list and description of shortcomings of your work. It is also important for you to explain how these limitations have impacted your research findings.

Your research may have multiple limitations, but you need to discuss only those limitations that directly relate to your research problems. For example, if conducting a meta-analysis of the secondary data has not been stated as your research objective, no need to mention it as your research limitation.

Research limitations in a typical dissertation may relate to the following points:

1. Formulation of research aims and objectives . You might have formulated research aims and objectives too broadly. You can specify in which ways the formulation of research aims and objectives could be narrowed so that the level of focus of the study could be increased.

2. Implementation of data collection method . Because you do not have an extensive experience in primary data collection (otherwise you would not be reading this book), there is a great chance that the nature of implementation of data collection method is flawed.

3. Sample size. Sample size depends on the nature of the research problem. If sample size is too small, statistical tests would not be able to identify significant relationships within data set. You can state that basing your study in larger sample size could have generated more accurate results. The importance of sample size is greater in quantitative studies compared to qualitative studies.

4. Lack of previous studies in the research area . Literature review is an important part of any research, because it helps to identify the scope of works that have been done so far in research area. Literature review findings are used as the foundation for the researcher to be built upon to achieve her research objectives.

However, there may be little, if any, prior research on your topic if you have focused on the most contemporary and evolving research problem or too narrow research problem. For example, if you have chosen to explore the role of Bitcoins as the future currency, you may not be able to find tons of scholarly paper addressing the research problem, because Bitcoins are only a recent phenomenon.

5. Scope of discussions . You can include this point as a limitation of your research regardless of the choice of the research area. Because (most likely) you don’t have many years of experience of conducing researches and producing academic papers of such a large size individually, the scope and depth of discussions in your paper is compromised in many levels compared to the works of experienced scholars.

You can discuss certain points from your research limitations as the suggestion for further research at conclusions chapter of your dissertation.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

Writing Limitations of Research Study — 4 Reasons Why It Is Important!

It is not unusual for researchers to come across the term limitations of research during their academic paper writing. More often this is interpreted as something terrible. However, when it comes to research study, limitations can help structure the research study better. Therefore, do not underestimate significance of limitations of research study.

Allow us to take you through the context of how to evaluate the limits of your research and conclude an impactful relevance to your results.

Table of Contents

What Are the Limitations of a Research Study?

Every research has its limit and these limitations arise due to restrictions in methodology or research design.  This could impact your entire research or the research paper you wish to publish. Unfortunately, most researchers choose not to discuss their limitations of research fearing it will affect the value of their article in the eyes of readers.

However, it is very important to discuss your study limitations and show it to your target audience (other researchers, journal editors, peer reviewers etc.). It is very important that you provide an explanation of how your research limitations may affect the conclusions and opinions drawn from your research. Moreover, when as an author you state the limitations of research, it shows that you have investigated all the weaknesses of your study and have a deep understanding of the subject. Being honest could impress your readers and mark your study as a sincere effort in research.

Why and Where Should You Include the Research Limitations?

The main goal of your research is to address your research objectives. Conduct experiments, get results and explain those results, and finally justify your research question . It is best to mention the limitations of research in the discussion paragraph of your research article.

At the very beginning of this paragraph, immediately after highlighting the strengths of the research methodology, you should write down your limitations. You can discuss specific points from your research limitations as suggestions for further research in the conclusion of your thesis.

1. Common Limitations of the Researchers

Limitations that are related to the researcher must be mentioned. This will help you gain transparency with your readers. Furthermore, you could provide suggestions on decreasing these limitations in you and your future studies.

2. Limited Access to Information

Your work may involve some institutions and individuals in research, and sometimes you may have problems accessing these institutions. Therefore, you need to redesign and rewrite your work. You must explain your readers the reason for limited access.

3. Limited Time

All researchers are bound by their deadlines when it comes to completing their studies. Sometimes, time constraints can affect your research negatively. However, the best practice is to acknowledge it and mention a requirement for future study to solve the research problem in a better way.

4. Conflict over Biased Views and Personal Issues

Biased views can affect the research. In fact, researchers end up choosing only those results and data that support their main argument, keeping aside the other loose ends of the research.

Types of Limitations of Research

Before beginning your research study, know that there are certain limitations to what you are testing or possible research results. There are different types that researchers may encounter, and they all have unique characteristics, such as:

1. Research Design Limitations

Certain restrictions on your research or available procedures may affect your final results or research outputs. You may have formulated research goals and objectives too broadly. However, this can help you understand how you can narrow down the formulation of research goals and objectives, thereby increasing the focus of your study.

2. Impact Limitations

Even if your research has excellent statistics and a strong design, it can suffer from the influence of the following factors:

• Presence of increasing findings as researched
• Being population specific
• A strong regional focus.

3. Data or statistical limitations

In some cases, it is impossible to collect sufficient data for research or very difficult to get access to the data. This could lead to incomplete conclusion to your study. Moreover, this insufficiency in data could be the outcome of your study design. The unclear, shabby research outline could produce more problems in interpreting your findings.

How to Correctly Structure Your Research Limitations?

There are strict guidelines for narrowing down research questions, wherein you could justify and explain potential weaknesses of your academic paper. You could go through these basic steps to get a well-structured clarity of research limitations:

• Declare that you wish to identify your limitations of research and explain their importance,
• Provide the necessary depth, explain their nature, and justify your study choices.
• Write how you are suggesting that it is possible to overcome them in the future.

In this section, your readers will see that you are aware of the potential weaknesses in your business, understand them and offer effective solutions, and it will positively strengthen your article as you clarify all limitations of research to your target audience.

Know that you cannot be perfect and there is no individual without flaws. You could use the limitations of research as a great opportunity to take on a new challenge and improve the future of research. In a typical academic paper, research limitations may relate to:

1. Formulating your goals and objectives

If you formulate goals and objectives too broadly, your work will have some shortcomings. In this case, specify effective methods or ways to narrow down the formula of goals and aim to increase your level of study focus.

2. Application of your data collection methods in research

If you do not have experience in primary data collection, there is a risk that there will be flaws in the implementation of your methods. It is necessary to accept this, and learn and educate yourself to understand data collection methods.

3. Sample sizes

This depends on the nature of problem you choose. Sample size is of a greater importance in quantitative studies as opposed to qualitative ones. If your sample size is too small, statistical tests cannot identify significant relationships or connections within a given data set.

You could point out that other researchers should base the same study on a larger sample size to get more accurate results.

4. The absence of previous studies in the field you have chosen

Writing a literature review is an important step in any scientific study because it helps researchers determine the scope of current work in the chosen field. It is a major foundation for any researcher who must use them to achieve a set of specific goals or objectives.

However, if you are focused on the most current and evolving research problem or a very narrow research problem, there may be very little prior research on your topic. For example, if you chose to explore the role of Bitcoin as the currency of the future, you may not find tons of scientific papers addressing the research problem as Bitcoins are only a new phenomenon.

It is important that you learn to identify research limitations examples at each step. Whatever field you choose, feel free to add the shortcoming of your work. This is mainly because you do not have many years of experience writing scientific papers or completing complex work. Therefore, the depth and scope of your discussions may be compromised at different levels compared to academics with a lot of expertise. Include specific points from limitations of research. Use them as suggestions for the future.

Have you ever faced a challenge of writing the limitations of research study in your paper? How did you overcome it? What ways did you follow? Were they beneficial? Let us know in the comments below!

Frequently Asked Questions

Setting limitations in our study helps to clarify the outcomes drawn from our research and enhance understanding of the subject. Moreover, it shows that the author has investigated all the weaknesses in the study.

Scope is the range and limitations of a research project which are set to define the boundaries of a project. Limitations are the impacts on the overall study due to the constraints on the research design.

Limitation in research is an impact of a constraint on the research design in the overall study. They are the flaws or weaknesses in the study, which may influence the outcome of the research.

1. Limitations in research can be written as follows: Formulate your goals and objectives 2. Analyze the chosen data collection method and the sample sizes 3. Identify your limitations of research and explain their importance 4. Provide the necessary depth, explain their nature, and justify your study choices 5. Write how you are suggesting that it is possible to overcome them in the future

Excellent article ,,,it has helped me big

This is very helpful information. It has given me an insight on how to go about my study limitations.

Good comments and helpful

the topic is well covered

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Publishing Research
• Trending Now
• Understanding Ethics

Understanding the Impact of Retractions on Research Integrity – A global study

As we reach the midway point of 2024, ‘Research Integrity’ remains one of the hot…

• Diversity and Inclusion

The Silent Struggle: Confronting gender bias in science funding

In the 1990s, Dr. Katalin Kariko’s pioneering mRNA research seemed destined for obscurity, doomed by…

• Promoting Research

Plain Language Summary — Communicating your research to bridge the academic-lay gap

Science can be complex, but does that mean it should not be accessible to the…

Addressing Barriers in Academia: Navigating unconscious biases in the Ph.D. journey

In the journey of academia, a Ph.D. marks a transitional phase, like that of a…

• Manuscripts & Grants
• Reporting Research

Unraveling Research Population and Sample: Understanding their role in statistical inference

Research population and sample serve as the cornerstones of any scientific inquiry. They hold the…

Research Problem Statement — Find out how to write an impactful one!

How to Develop a Good Research Question? — Types & Examples

5 Effective Ways to Avoid Ghostwriting for Busy Researchers

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What would be most effective in reducing research misconduct?

Stating the Obvious: Writing Assumptions, Limitations, and Delimitations

During the process of writing your thesis or dissertation, you might suddenly realize that your research has inherent flaws. Don’t worry! Virtually all projects contain restrictions to your research. However, being able to recognize and accurately describe these problems is the difference between a true researcher and a grade-school kid with a science-fair project. Concerns with truthful responding, access to participants, and survey instruments are just a few of examples of restrictions on your research. In the following sections, the differences among delimitations, limitations, and assumptions of a dissertation will be clarified.

Delimitations

Delimitations are the definitions you set as the boundaries of your own thesis or dissertation, so delimitations are in your control. Delimitations are set so that your goals do not become impossibly large to complete. Examples of delimitations include objectives, research questions, variables, theoretical objectives that you have adopted, and populations chosen as targets to study. When you are stating your delimitations, clearly inform readers why you chose this course of study. The answer might simply be that you were curious about the topic and/or wanted to improve standards of a professional field by revealing certain findings. In any case, you should clearly list the other options available and the reasons why you did not choose these options immediately after you list your delimitations. You might have avoided these options for reasons of practicality, interest, or relativity to the study at hand. For example, you might have only studied Hispanic mothers because they have the highest rate of obese babies. Delimitations are often strongly related to your theory and research questions. If you were researching whether there are different parenting styles between unmarried Asian, Caucasian, African American, and Hispanic women, then a delimitation of your study would be the inclusion of only participants with those demographics and the exclusion of participants from other demographics such as men, married women, and all other ethnicities of single women (inclusion and exclusion criteria). A further delimitation might be that you only included closed-ended Likert scale responses in the survey, rather than including additional open-ended responses, which might make some people more willing to take and complete your survey. Remember that delimitations are not good or bad. They are simply a detailed description of the scope of interest for your study as it relates to the research design. Don’t forget to describe the philosophical framework you used throughout your study, which also delimits your study.

Limitations

Limitations of a dissertation are potential weaknesses in your study that are mostly out of your control, given limited funding, choice of research design, statistical model constraints, or other factors. In addition, a limitation is a restriction on your study that cannot be reasonably dismissed and can affect your design and results. Do not worry about limitations because limitations affect virtually all research projects, as well as most things in life. Even when you are going to your favorite restaurant, you are limited by the menu choices. If you went to a restaurant that had a menu that you were craving, you might not receive the service, price, or location that makes you enjoy your favorite restaurant. If you studied participants’ responses to a survey, you might be limited in your abilities to gain the exact type or geographic scope of participants you wanted. The people whom you managed to get to take your survey may not truly be a random sample, which is also a limitation. If you used a common test for data findings, your results are limited by the reliability of the test. If your study was limited to a certain amount of time, your results are affected by the operations of society during that time period (e.g., economy, social trends). It is important for you to remember that limitations of a dissertation are often not something that can be solved by the researcher. Also, remember that whatever limits you also limits other researchers, whether they are the largest medical research companies or consumer habits corporations. Certain kinds of limitations are often associated with the analytical approach you take in your research, too. For example, some qualitative methods like heuristics or phenomenology do not lend themselves well to replicability. Also, most of the commonly used quantitative statistical models can only determine correlation, but not causation.

Assumptions

Assumptions are things that are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis. In other words, any scholar reading your paper will assume that certain aspects of your study is true given your population, statistical test, research design, or other delimitations. For example, if you tell your friend that your favorite restaurant is an Italian place, your friend will assume that you don’t go there for the sushi. It’s assumed that you go there to eat Italian food. Because most assumptions are not discussed in-text, assumptions that are discussed in-text are discussed in the context of the limitations of your study, which is typically in the discussion section. This is important, because both assumptions and limitations affect the inferences you can draw from your study. One of the more common assumptions made in survey research is the assumption of honesty and truthful responses. However, for certain sensitive questions this assumption may be more difficult to accept, in which case it would be described as a limitation of the study. For example, asking people to report their criminal behavior in a survey may not be as reliable as asking people to report their eating habits. It is important to remember that your limitations and assumptions should not contradict one another. For instance, if you state that generalizability is a limitation of your study given that your sample was limited to one city in the United States, then you should not claim generalizability to the United States population as an assumption of your study. Statistical models in quantitative research designs are accompanied with assumptions as well, some more strict than others. These assumptions generally refer to the characteristics of the data, such as distributions, correlational trends, and variable type, just to name a few. Violating these assumptions can lead to drastically invalid results, though this often depends on sample size and other considerations.

Click here to cancel reply.

You must be logged in to post a comment.

Copyright © 2024 PhDStudent.com. All rights reserved. Designed by Divergent Web Solutions, LLC .

Organizing Academic Research Papers: Limitations of the Study

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

The limitations of the study are those characteristics of design or methodology that impacted or influenced the application or interpretation of the results of your study. They are the constraints on generalizability and utility of findings that are the result of the ways in which you chose to design the study and/or the method used to establish internal and external validity.

Importance of...

Always acknowledge a study's limitations. It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor and be graded down because you appear to have ignored them.

Keep in mind that acknowledgement of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgement of a study's limitations also provides you with an opportunity to demonstrate to your professor that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitiations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the findings and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in your paper.

Here are examples of limitations you may need to describe and to discuss how they possibly impacted your findings. Descriptions of limitations should be stated in the past tense.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but to offer reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe the need for future research.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, consult with a librarian! In cases when a librarian has confirmed that there is a lack of prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design]. Note that this limitation can serve as an important opportunity to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need in future research to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing self-reported data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to take what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data contain several potential sources of bias that should be noted as limitations: (1) selective memory (remembering or not remembering experiences or events that occurred at some point in the past); (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, or documents and, for whatever reason, access is denied or otherwise limited, the reasons for this need to be described.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single research problem, the time available to investigate a research problem and to measure change or stability within a sample is constrained by the due date of your assignment. Be sure to choose a topic that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, or thing is viewed or shown in a consistently inaccurate way. It is usually negative, though one can have a positive bias as well. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places and how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. Note that if you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating bias.
• Fluency in a language -- if your research focuses on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students, for example, and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic. This deficiency should be acknowledged.

Brutus, Stéphane et al. Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations. Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods . Powerpoint Presentation. Regent University of Science and Technology.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as a pilot study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in later studies.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study  is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to reframe your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to  the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't ask a particular question in a survey that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in any future study. A underlying goal of scholarly research is not only to prove what works, but to demonstrate what doesn't work or what needs further clarification.

Brutus, Stéphane et al. Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations. Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. Limitations are not Properly Acknowledged in the Scientific Literature. Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed . January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings! After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitiations of your study. Inflating of the importance of your study's findings in an attempt hide its flaws is a big turn off to your readers. A measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated, or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Yet Another Writing Tip

A Note about Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgement about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Huberman, A. Michael and Matthew B. Miles. Data Management and Analysis Methods. In Handbook of Qualitative Research. Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444.

• << Previous: 8. The Discussion
• Next: 9. The Conclusion >>
• Last Updated: Jul 18, 2023 11:58 AM
• URL: https://library.sacredheart.edu/c.php?g=29803
• QuickSearch
• Library Catalog
• Databases A-Z
• Publication Finder
• Course Reserves
• Citation Linker
• Digital Commons
• Our Website

Research Support

• Ask a Librarian
• Appointments
• Interlibrary Loan (ILL)
• Research Guides
• Databases by Subject
• Citation Help

Using the Library

• Reserve a Group Study Room
• Renew Books
• Honors Study Rooms
• Off-Campus Access
• Library Policies
• Library Technology

User Information

• Grad Students
• Online Students
• COVID-19 Updates
• Staff Directory
• News & Announcements
• Library Newsletter

My Accounts

• Interlibrary Loan
• Staff Site Login

FIND US ON  

CPS Online Graduate Studies Research Paper (UNH Manchester Library): Limitations of the Study

• Overview of the Research Process for Capstone Projects
• Types of Research Design
• Selecting a Research Problem
• The Title of Your Research Paper
• Before You Begin Writing
• 7 Parts of the Research Paper
• Background Information
• Quanitative and Qualitative Methods
• Qualitative Methods
• Quanitative Methods
• Resources to Help You With the Literature Review
• Non-Textual Elements

Limitations of the Study

• Format of Capstone Research Projects at GSC
• Editing and Proofreading Your Paper
• Acknowledgements
• UNH Scholar's Repository

The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. They are the constraints on generalizability, applications to practice, and/or utility of findings that are the result of the ways in which you initially chose to design the study and/or the method used to establish internal and external validity.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67.

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and be graded down because you appear to have ignored them.

Keep in mind that acknowledgement of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgement of a study's limitations also provides you with an opportunity to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but to also confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and to discuss how they possibly impacted your results. Descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is less relevant in qualitative research.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but to offer reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe the need for future research.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian. In cases when a librarian has confirmed that there is no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to take what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this need to be described.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is pretty much constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support for your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation.

NOTE:   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias.

• Fluency in a language -- if your research focuses on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students, for example, and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods . Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section. If you determine that your study is seriously flawed due to important limitations, such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study. But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic. If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study. When discussing the limitations of your research, be sure to: Describe each limitation in detailed but concise terms; Explain why each limitation exists; Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible]; Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and, If appropriate, describe how these limitations could point to the need for further research. Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification. Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed . January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion . The Writing Lab and The OWL. Purdue University.

• << Previous: The Discussion
• Next: Conclusion >>
• Last Updated: Nov 6, 2023 1:43 PM
• URL: https://libraryguides.unh.edu/cpsonlinegradpaper

What Is Research Methodology? A Plain-Language Explanation & Definition (With Examples)

By Derek Jansen (MBA)  and Kerryn Warren (PhD) | June 2020 (Last updated April 2023)

If you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

Moving on to the quantitative side of things, popular data analysis methods in this type of research include:

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

Again, the choice of which data collection method to use depends on your overall research aims and objectives , as well as practicalities and resource constraints. In the video below, we explain some core concepts central to quantitative analysis.

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

You Might Also Like:

199 Comments

Thank you for this simple yet comprehensive and easy to digest presentation. God Bless!

You’re most welcome, Leo. Best of luck with your research!

I found it very useful. many thanks

This is really directional. A make-easy research knowledge.

Thank you for this, I think will help my research proposal

Thanks for good interpretation,well understood.

Good morning sorry I want to the search topic

Thank u more

Thank you, your explanation is simple and very helpful.

Very educative a.nd exciting platform. A bigger thank you and I’ll like to always be with you

That’s the best analysis

So simple yet so insightful. Thank you.

This really easy to read as it is self-explanatory. Very much appreciated…

Thanks for this. It’s so helpful and explicit. For those elements highlighted in orange, they were good sources of referrals for concepts I didn’t understand. A million thanks for this.

Good morning, I have been reading your research lessons through out a period of times. They are important, impressive and clear. Want to subscribe and be and be active with you.

Thankyou So much Sir Derek…

Good morning thanks so much for the on line lectures am a student of university of Makeni.select a research topic and deliberate on it so that we’ll continue to understand more.sorry that’s a suggestion.

Beautiful presentation. I love it.

please provide a research mehodology example for zoology

It’s very educative and well explained

Thanks for the concise and informative data.

This is really good for students to be safe and well understand that research is all about

Thank you so much Derek sir🖤🙏🤗

Very simple and reliable

This is really helpful. Thanks alot. God bless you.

very useful, Thank you very much..

thanks a lot its really useful

in a nutshell..thank you!

Thanks for updating my understanding on this aspect of my Thesis writing.

thank you so much my through this video am competently going to do a good job my thesis

Thanks a lot. Very simple to understand. I appreciate 🙏

Very simple but yet insightful Thank you

This has been an eye opening experience. Thank you grad coach team.

Very useful message for research scholars

Really very helpful thank you

yes you are right and i’m left

Research methodology with a simplest way i have never seen before this article.

wow thank u so much

Good morning thanks so much for the on line lectures am a student of university of Makeni.select a research topic and deliberate on is so that we will continue to understand more.sorry that’s a suggestion.

Very precise and informative.

Thanks for simplifying these terms for us, really appreciate it.

Thanks this has really helped me. It is very easy to understand.

I found the notes and the presentation assisting and opening my understanding on research methodology

Good presentation

Im so glad you clarified my misconceptions. Im now ready to fry my onions. Thank you so much. God bless

Thank you a lot.

thanks for the easy way of learning and desirable presentation.

Thanks a lot. I am inspired

Well written

I am writing a APA Format paper . I using questionnaire with 120 STDs teacher for my participant. Can you write me mthology for this research. Send it through email sent. Just need a sample as an example please. My topic is ” impacts of overcrowding on students learning

Thanks for your comment.

We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

All the best with your research.

Thank you so much for this!! God Bless

Thank you. Explicit explanation

Thank you, Derek and Kerryn, for making this simple to understand. I’m currently at the inception stage of my research.

Thnks a lot , this was very usefull on my assignment

excellent explanation

I’m currently working on my master’s thesis, thanks for this! I’m certain that I will use Qualitative methodology.

Thanks a lot for this concise piece, it was quite relieving and helpful. God bless you BIG…

I am currently doing my dissertation proposal and I am sure that I will do quantitative research. Thank you very much it was extremely helpful.

Very interesting and informative yet I would like to know about examples of Research Questions as well, if possible.

I’m about to submit a research presentation, I have come to understand from your simplification on understanding research methodology. My research will be mixed methodology, qualitative as well as quantitative. So aim and objective of mixed method would be both exploratory and confirmatory. Thanks you very much for your guidance.

OMG thanks for that, you’re a life saver. You covered all the points I needed. Thank you so much ❤️ ❤️ ❤️

Thank you immensely for this simple, easy to comprehend explanation of data collection methods. I have been stuck here for months 😩. Glad I found your piece. Super insightful.

I’m going to write synopsis which will be quantitative research method and I don’t know how to frame my topic, can I kindly get some ideas..

Thanks for this, I was really struggling.

This was really informative I was struggling but this helped me.

Thanks a lot for this information, simple and straightforward. I’m a last year student from the University of South Africa UNISA South Africa.

its very much informative and understandable. I have enlightened.

An interesting nice exploration of a topic.

Thank you. Accurate and simple🥰

This article was really helpful, it helped me understanding the basic concepts of the topic Research Methodology. The examples were very clear, and easy to understand. I would like to visit this website again. Thank you so much for such a great explanation of the subject.

Thanks dude

Thank you Doctor Derek for this wonderful piece, please help to provide your details for reference purpose. God bless.

Many compliments to you

Great work , thank you very much for the simple explanation

Thank you. I had to give a presentation on this topic. I have looked everywhere on the internet but this is the best and simple explanation.

thank you, its very informative.

Well explained. Now I know my research methodology will be qualitative and exploratory. Thank you so much, keep up the good work

Well explained, thank you very much.

This is good explanation, I have understood the different methods of research. Thanks a lot.

Great work…very well explanation

Thanks Derek. Kerryn was just fantastic!

Great to hear that, Hyacinth. Best of luck with your research!

Its a good templates very attractive and important to PhD students and lectuter

Thanks for the feedback, Matobela. Good luck with your research methodology.

Thank you. This is really helpful.

You’re very welcome, Elie. Good luck with your research methodology.

Well explained thanks

This is a very helpful site especially for young researchers at college. It provides sufficient information to guide students and equip them with the necessary foundation to ask any other questions aimed at deepening their understanding.

Thanks for the kind words, Edward. Good luck with your research!

Thank you. I have learned a lot.

Great to hear that, Ngwisa. Good luck with your research methodology!

Thank you for keeping your presentation simples and short and covering key information for research methodology. My key takeaway: Start with defining your research objective the other will depend on the aims of your research question.

My name is Zanele I would like to be assisted with my research , and the topic is shortage of nursing staff globally want are the causes , effects on health, patients and community and also globally

Thanks for making it simple and clear. It greatly helped in understanding research methodology. Regards.

This is well simplified and straight to the point

Thank you Dr

I was given an assignment to research 2 publications and describe their research methodology? I don’t know how to start this task can someone help me?

Sure. You’re welcome to book an initial consultation with one of our Research Coaches to discuss how we can assist – https://gradcoach.com/book/new/ .

Thanks a lot I am relieved of a heavy burden.keep up with the good work

I’m very much grateful Dr Derek. I’m planning to pursue one of the careers that really needs one to be very much eager to know. There’s a lot of research to do and everything, but since I’ve gotten this information I will use it to the best of my potential.

Thank you so much, words are not enough to explain how helpful this session has been for me!

Thanks this has thought me alot.

Very concise and helpful. Thanks a lot

Thank Derek. This is very helpful. Your step by step explanation has made it easier for me to understand different concepts. Now i can get on with my research.

I wish i had come across this sooner. So simple but yet insightful

really nice explanation thank you so much

I’m so grateful finding this site, it’s really helpful…….every term well explained and provide accurate understanding especially to student going into an in-depth research for the very first time, even though my lecturer already explained this topic to the class, I think I got the clear and efficient explanation here, much thanks to the author.

It is very helpful material

I would like to be assisted with my research topic : Literature Review and research methodologies. My topic is : what is the relationship between unemployment and economic growth?

Its really nice and good for us.

THANKS SO MUCH FOR EXPLANATION, ITS VERY CLEAR TO ME WHAT I WILL BE DOING FROM NOW .GREAT READS.

Short but sweet.Thank you

Informative article. Thanks for your detailed information.

I’m currently working on my Ph.D. thesis. Thanks a lot, Derek and Kerryn, Well-organized sequences, facilitate the readers’ following.

great article for someone who does not have any background can even understand

I am a bit confused about research design and methodology. Are they the same? If not, what are the differences and how are they related?

Thanks in advance.

concise and informative.

Thank you very much

How can we site this article is Harvard style?

Very well written piece that afforded better understanding of the concept. Thank you!

Am a new researcher trying to learn how best to write a research proposal. I find your article spot on and want to download the free template but finding difficulties. Can u kindly send it to my email, the free download entitled, “Free Download: Research Proposal Template (with Examples)”.

Thank too much

Thank you very much for your comprehensive explanation about research methodology so I like to thank you again for giving us such great things.

Good very well explained.Thanks for sharing it.

Thank u sir, it is really a good guideline.

so helpful thank you very much.

Thanks for the video it was very explanatory and detailed, easy to comprehend and follow up. please, keep it up the good work

It was very helpful, a well-written document with precise information.

how do i reference this?

MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

Your explanation is easily understood. Thank you

Very help article. Now I can go my methodology chapter in my thesis with ease

I feel guided ,Thank you

This simplification is very helpful. It is simple but very educative, thanks ever so much

The write up is informative and educative. It is an academic intellectual representation that every good researcher can find useful. Thanks

Wow, this is wonderful long live.

Nice initiative

thank you the video was helpful to me.

Thank you very much for your simple and clear explanations I’m really satisfied by the way you did it By now, I think I can realize a very good article by following your fastidious indications May God bless you

Thanks very much, it was very concise and informational for a beginner like me to gain an insight into what i am about to undertake. I really appreciate.

very informative sir, it is amazing to understand the meaning of question hidden behind that, and simple language is used other than legislature to understand easily. stay happy.

This one is really amazing. All content in your youtube channel is a very helpful guide for doing research. Thanks, GradCoach.

research methodologies

Please send me more information concerning dissertation research.

Nice piece of knowledge shared….. #Thump_UP

This is amazing, it has said it all. Thanks to Gradcoach

This is wonderful,very elaborate and clear.I hope to reach out for your assistance in my research very soon.

This is the answer I am searching about…

realy thanks a lot

Thank you very much for this awesome, to the point and inclusive article.

Thank you very much I need validity and reliability explanation I have exams

Thank you for a well explained piece. This will help me going forward.

Very simple and well detailed Many thanks

This is so very simple yet so very effective and comprehensive. An Excellent piece of work.

I wish I saw this earlier on! Great insights for a beginner(researcher) like me. Thanks a mil!

Thank you very much, for such a simplified, clear and practical step by step both for academic students and general research work. Holistic, effective to use and easy to read step by step. One can easily apply the steps in practical terms and produce a quality document/up-to standard

Thanks for simplifying these terms for us, really appreciated.

Thanks for a great work. well understood .

This was very helpful. It was simple but profound and very easy to understand. Thank you so much!

Great and amazing research guidelines. Best site for learning research

hello sir/ma’am, i didn’t find yet that what type of research methodology i am using. because i am writing my report on CSR and collect all my data from websites and articles so which type of methodology i should write in dissertation report. please help me. i am from India.

how does this really work?

perfect content, thanks a lot

As a researcher, I commend you for the detailed and simplified information on the topic in question. I would like to remain in touch for the sharing of research ideas on other topics. Thank you

Impressive. Thank you, Grad Coach 😍

Thank you Grad Coach for this piece of information. I have at least learned about the different types of research methodologies.

Very useful content with easy way

Thank you very much for the presentation. I am an MPH student with the Adventist University of Africa. I have successfully completed my theory and starting on my research this July. My topic is “Factors associated with Dental Caries in (one District) in Botswana. I need help on how to go about this quantitative research

I am so grateful to run across something that was sooo helpful. I have been on my doctorate journey for quite some time. Your breakdown on methodology helped me to refresh my intent. Thank you.

thanks so much for this good lecture. student from university of science and technology, Wudil. Kano Nigeria.

It’s profound easy to understand I appreciate

Thanks a lot for sharing superb information in a detailed but concise manner. It was really helpful and helped a lot in getting into my own research methodology.

Comment * thanks very much

This was sooo helpful for me thank you so much i didn’t even know what i had to write thank you!

You’re most welcome 🙂

Simple and good. Very much helpful. Thank you so much.

This is very good work. I have benefited.

Thank you so much for sharing

This is powerful thank you so much guys

I am nkasa lizwi doing my research proposal on honors with the university of Walter Sisulu Komani I m on part 3 now can you assist me.my topic is: transitional challenges faced by educators in intermediate phase in the Alfred Nzo District.

Appreciate the presentation. Very useful step-by-step guidelines to follow.

I appreciate sir

wow! This is super insightful for me. Thank you!

Indeed this material is very helpful! Kudos writers/authors.

I want to say thank you very much, I got a lot of info and knowledge. Be blessed.

I want present a seminar paper on Optimisation of Deep learning-based models on vulnerability detection in digital transactions.

Need assistance

Dear Sir, I want to be assisted on my research on Sanitation and Water management in emergencies areas.

I am deeply grateful for the knowledge gained. I will be getting in touch shortly as I want to be assisted in my ongoing research.

The information shared is informative, crisp and clear. Kudos Team! And thanks a lot!

hello i want to study

Hello!! Grad coach teams. I am extremely happy in your tutorial or consultation. i am really benefited all material and briefing. Thank you very much for your generous helps. Please keep it up. If you add in your briefing, references for further reading, it will be very nice.

All I have to say is, thank u gyz.

Good, l thanks

thank you, it is very useful

Trackbacks/Pingbacks

• What Is A Literature Review (In A Dissertation Or Thesis) - Grad Coach - […] the literature review is to inform the choice of methodology for your own research. As we’ve discussed on the Grad Coach blog,…
• Free Download: Research Proposal Template (With Examples) - Grad Coach - […] Research design (methodology) […]
• Dissertation vs Thesis: What's the difference? - Grad Coach - […] and thesis writing on a daily basis – everything from how to find a good research topic to which…

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

Get science-backed answers as you write with Paperpal's Research feature

What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

Writing the methods section of a research paper? Let Paperpal help you achieve perfection

Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

Let Paperpal help you write the perfect research methods section. Start now!

What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

Got writer’s block? Kickstart your research paper writing with Paperpal now!

How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

Streamline Your Research Paper Writing Process with Paperpal

The methods section is a critical part of the research papers, allowing researchers to use this to understand your findings and replicate your work when pursuing their own research. However, it is usually also the most difficult section to write. This is where Paperpal can help you overcome the writer’s block and create the first draft in minutes with Paperpal Copilot, its secure generative AI feature suite.  

With Paperpal you can get research advice, write and refine your work, rephrase and verify the writing, and ensure submission readiness, all in one place. Here’s how you can use Paperpal to develop the first draft of your methods section.  

• Generate an outline: Input some details about your research to instantly generate an outline for your methods section 
• Develop the section: Use the outline and suggested sentence templates to expand your ideas and develop the first draft.  
• P araph ras e and trim : Get clear, concise academic text with paraphrasing that conveys your work effectively and word reduction to fix redundancies. 
• Choose the right words: Enhance text by choosing contextual synonyms based on how the words have been used in previously published work.  
• Check and verify text : Make sure the generated text showcases your methods correctly, has all the right citations, and is original and authentic. .   

You can repeat this process to develop each section of your research manuscript, including the title, abstract and keywords. Ready to write your research papers faster, better, and without the stress? Sign up for Paperpal and start writing today!

Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

Accelerate your research paper writing with Paperpal. Try for free now!

• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

Paperpal is a comprehensive AI writing toolkit that helps students and researchers achieve 2x the writing in half the time. It leverages 21+ years of STM experience and insights from millions of research articles to provide in-depth academic writing, language editing, and submission readiness support to help you write better, faster.  

Get accurate academic translations, rewriting support, grammar checks, vocabulary suggestions, and generative AI assistance that delivers human precision at machine speed. Try for free or upgrade to Paperpal Prime starting at US$19 a month to access premium features, including consistency, plagiarism, and 30+ submission readiness checks to help you succeed.  

Experience the future of academic writing – Sign up to Paperpal and start writing for free!  

Related Reads:

• Dangling Modifiers and How to Avoid Them in Your Writing 
• Webinar: How to Use Generative AI Tools Ethically in Your Academic Writing
• Research Outlines: How to Write An Introduction Section in Minutes with Paperpal Copilot
• How to Paraphrase Research Papers Effectively

Language and Grammar Rules for Academic Writing

Climatic vs. climactic: difference and examples, you may also like, how to structure an essay, leveraging generative ai to enhance student understanding of..., how to write a good hook for essays,..., addressing peer review feedback and mastering manuscript revisions..., how paperpal can boost comprehension and foster interdisciplinary..., what is the importance of a concept paper..., how to write the first draft of a..., mla works cited page: format, template & examples, how to ace grant writing for research funding..., powerful academic phrases to improve your essay writing .

CRO Platform

Test your insights. Run experiments. Win. Or learn. And then win.

eCommerce Customer Analytics Platform

Acquisition matters. But retention matters more. Understand, monitor & nurture the best customers.

• Case Studies
• Ebooks, Tools, Templates
• Digital Marketing Glossary
• eCommerce Growth Stories
• eCommerce Growth Show
• Help & Technical Documentation

CRO Guide   >  Chapter 3.1

Qualitative Research: Definition, Methodology, Limitation & Examples

Qualitative research is a method focused on understanding human behavior and experiences through non-numerical data. Examples of qualitative research include:

• One-on-one interviews,
• Focus groups, Ethnographic research,
• Case studies,
• Record keeping,
• Qualitative observations

In this article, we’ll provide tips and tricks on how to use qualitative research to better understand your audience through real world examples and improve your ROI. We’ll also learn the difference between qualitative and quantitative data.

Table of Contents

Marketers often seek to understand their customers deeply. Qualitative research methods such as face-to-face interviews, focus groups, and qualitative observations can provide valuable insights into your products, your market, and your customers’ opinions and motivations. Understanding these nuances can significantly enhance marketing strategies and overall customer satisfaction.

What is Qualitative Research

Qualitative research is a market research method that focuses on obtaining data through open-ended and conversational communication. This method focuses on the “why” rather than the “what” people think about you. Thus, qualitative research seeks to uncover the underlying motivations, attitudes, and beliefs that drive people’s actions. 

Let’s say you have an online shop catering to a general audience. You do a demographic analysis and you find out that most of your customers are male. Naturally, you will want to find out why women are not buying from you. And that’s what qualitative research will help you find out.

In the case of your online shop, qualitative research would involve reaching out to female non-customers through methods such as in-depth interviews or focus groups. These interactions provide a platform for women to express their thoughts, feelings, and concerns regarding your products or brand. Through qualitative analysis, you can uncover valuable insights into factors such as product preferences, user experience, brand perception, and barriers to purchase.

Types of Qualitative Research Methods

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience regarding a particular topic.

The most frequently used qualitative analysis methods are one-on-one interviews, focus groups, ethnographic research, case study research, record keeping, and qualitative observation.

1. One-on-one interviews

Conducting one-on-one interviews is one of the most common qualitative research methods. One of the advantages of this method is that it provides a great opportunity to gather precise data about what people think and their motivations.

Spending time talking to customers not only helps marketers understand who their clients are, but also helps with customer care: clients love hearing from brands. This strengthens the relationship between a brand and its clients and paves the way for customer testimonials.

• A company might conduct interviews to understand why a product failed to meet sales expectations.
• A researcher might use interviews to gather personal stories about experiences with healthcare.

These interviews can be performed face-to-face or on the phone and usually last between half an hour to over two hours. 

When a one-on-one interview is conducted face-to-face, it also gives the marketer the opportunity to read the body language of the respondent and match the responses.

2. Focus groups

Focus groups gather a small number of people to discuss and provide feedback on a particular subject. The ideal size of a focus group is usually between five and eight participants. The size of focus groups should reflect the participants’ familiarity with the topic. For less important topics or when participants have little experience, a group of 10 can be effective. For more critical topics or when participants are more knowledgeable, a smaller group of five to six is preferable for deeper discussions.

The main goal of a focus group is to find answers to the “why”, “what”, and “how” questions. This method is highly effective in exploring people’s feelings and ideas in a social setting, where group dynamics can bring out insights that might not emerge in one-on-one situations.

• A focus group could be used to test reactions to a new product concept.
• Marketers might use focus groups to see how different demographic groups react to an advertising campaign.

One advantage that focus groups have is that the marketer doesn’t necessarily have to interact with the group in person. Nowadays focus groups can be sent as online qualitative surveys on various devices.

Focus groups are an expensive option compared to the other qualitative research methods, which is why they are typically used to explain complex processes.

3. Ethnographic research

Ethnographic research is the most in-depth observational method that studies individuals in their naturally occurring environment.

This method aims at understanding the cultures, challenges, motivations, and settings that occur.

• A study of workplace culture within a tech startup.
• Observational research in a remote village to understand local traditions.

Ethnographic research requires the marketer to adapt to the target audiences’ environments (a different organization, a different city, or even a remote location), which is why geographical constraints can be an issue while collecting data.

This type of research can last from a few days to a few years. It’s challenging and time-consuming and solely depends on the expertise of the marketer to be able to analyze, observe, and infer the data.

4. Case study research

The case study method has grown into a valuable qualitative research method. This type of research method is usually used in education or social sciences. It involves a comprehensive examination of a single instance or event, providing detailed insights into complex issues in real-life contexts.  

• Analyzing a single school’s innovative teaching method.
• A detailed study of a patient’s medical treatment over several years.

Case study research may seem difficult to operate, but it’s actually one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

Record keeping is similar to going to the library: you go over books or any other reference material to collect relevant data. This method uses already existing reliable documents and similar sources of information as a data source.

• Historical research using old newspapers and letters.
• A study on policy changes over the years by examining government records.

This method is useful for constructing a historical context around a research topic or verifying other findings with documented evidence.

6. Qualitative observation

Qualitative observation is a method that uses subjective methodologies to gather systematic information or data. This method deals with the five major sensory organs and their functioning, sight, smell, touch, taste, and hearing.

• Sight : Observing the way customers visually interact with product displays in a store to understand their browsing behaviors and preferences.
• Smell : Noting reactions of consumers to different scents in a fragrance shop to study the impact of olfactory elements on product preference.
• Touch : Watching how individuals interact with different materials in a clothing store to assess the importance of texture in fabric selection.
• Taste : Evaluating reactions of participants in a taste test to identify flavor profiles that appeal to different demographic groups.
• Hearing : Documenting responses to changes in background music within a retail environment to determine its effect on shopping behavior and mood.

Below we are also providing real-life examples of qualitative research that demonstrate practical applications across various contexts:

Qualitative Research Real World Examples

Let’s explore some examples of how qualitative research can be applied in different contexts.

1. Online grocery shop with a predominantly male audience

Method used: one-on-one interviews.

Let’s go back to one of the previous examples. You have an online grocery shop. By nature, it addresses a general audience, but after you do a demographic analysis you find out that most of your customers are male.

One good method to determine why women are not buying from you is to hold one-on-one interviews with potential customers in the category.

Interviewing a sample of potential female customers should reveal why they don’t find your store appealing. The reasons could range from not stocking enough products for women to perhaps the store’s emphasis on heavy-duty tools and automotive products, for example. These insights can guide adjustments in inventory and marketing strategies.

2. Software company launching a new product

Method used: focus groups.

Focus groups are great for establishing product-market fit.

Let’s assume you are a software company that wants to launch a new product and you hold a focus group with 12 people. Although getting their feedback regarding users’ experience with the product is a good thing, this sample is too small to define how the entire market will react to your product.

So what you can do instead is holding multiple focus groups in 20 different geographic regions. Each region should be hosting a group of 12 for each market segment; you can even segment your audience based on age. This would be a better way to establish credibility in the feedback you receive.

3. Alan Pushkin’s “God’s Choice: The Total World of a Fundamentalist Christian School”

Method used: ethnographic research.

Moving from a fictional example to a real-life one, let’s analyze Alan Peshkin’s 1986 book “God’s Choice: The Total World of a Fundamentalist Christian School”.

Peshkin studied the culture of Bethany Baptist Academy by interviewing the students, parents, teachers, and members of the community alike, and spending eighteen months observing them to provide a comprehensive and in-depth analysis of Christian schooling as an alternative to public education.

The study highlights the school’s unified purpose, rigorous academic environment, and strong community support while also pointing out its lack of cultural diversity and openness to differing viewpoints. These insights are crucial for understanding how such educational settings operate and what they offer to students.

Even after discovering all this, Peshkin still presented the school in a positive light and stated that public schools have much to learn from such schools.

Peshkin’s in-depth research represents a qualitative study that uses observations and unstructured interviews, without any assumptions or hypotheses. He utilizes descriptive or non-quantifiable data on Bethany Baptist Academy specifically, without attempting to generalize the findings to other Christian schools.

4. Understanding buyers’ trends

Method used: record keeping.

Another way marketers can use quality research is to understand buyers’ trends. To do this, marketers need to look at historical data for both their company and their industry and identify where buyers are purchasing items in higher volumes.

For example, electronics distributors know that the holiday season is a peak market for sales while life insurance agents find that spring and summer wedding months are good seasons for targeting new clients.

5. Determining products/services missing from the market

Conducting your own research isn’t always necessary. If there are significant breakthroughs in your industry, you can use industry data and adapt it to your marketing needs.

The influx of hacking and hijacking of cloud-based information has made Internet security a topic of many industry reports lately. A software company could use these reports to better understand the problems its clients are facing.

As a result, the company can provide solutions prospects already know they need.

Real-time Customer Lifetime Value (CLV) Benchmark Report

See where your business stands compared to 1,000+ e-stores in different industries.

Qualitative Research Approaches

Once the marketer has decided that their research questions will provide data that is qualitative in nature, the next step is to choose the appropriate qualitative approach.

The approach chosen will take into account the purpose of the research, the role of the researcher, the data collected, the method of data analysis , and how the results will be presented. The most common approaches include:

• Narrative : This method focuses on individual life stories to understand personal experiences and journeys. It examines how people structure their stories and the themes within them to explore human existence. For example, a narrative study might look at cancer survivors to understand their resilience and coping strategies.
• Phenomenology : attempts to understand or explain life experiences or phenomena; It aims to reveal the depth of human consciousness and perception, such as by studying the daily lives of those with chronic illnesses.
• Grounded theory : investigates the process, action, or interaction with the goal of developing a theory “grounded” in observations and empirical data. 
• Ethnography : describes and interprets an ethnic, cultural, or social group;
• Case study : examines episodic events in a definable framework, develops in-depth analyses of single or multiple cases, and generally explains “how”. An example might be studying a community health program to evaluate its success and impact.

How to Analyze Qualitative Data

Analyzing qualitative data involves interpreting non-numerical data to uncover patterns, themes, and deeper insights. This process is typically more subjective and requires a systematic approach to ensure reliability and validity. 

1. Data Collection

Ensure that your data collection methods (e.g., interviews, focus groups, observations) are well-documented and comprehensive. This step is crucial because the quality and depth of the data collected will significantly influence the analysis.

2. Data Preparation

Once collected, the data needs to be organized. Transcribe audio and video recordings, and gather all notes and documents. Ensure that all data is anonymized to protect participant confidentiality where necessary.

3. Familiarization

Immerse yourself in the data by reading through the materials multiple times. This helps you get a general sense of the information and begin identifying patterns or recurring themes.

Develop a coding system to tag data with labels that summarize and account for each piece of information. Codes can be words, phrases, or acronyms that represent how these segments relate to your research questions.

• Descriptive Coding : Summarize the primary topic of the data.
• In Vivo Coding : Use language and terms used by the participants themselves.
• Process Coding : Use gerunds (“-ing” words) to label the processes at play.
• Emotion Coding : Identify and record the emotions conveyed or experienced.

5. Thematic Development

Group codes into themes that represent larger patterns in the data. These themes should relate directly to the research questions and form a coherent narrative about the findings.

6. Interpreting the Data

Interpret the data by constructing a logical narrative. This involves piecing together the themes to explain larger insights about the data. Link the results back to your research objectives and existing literature to bolster your interpretations.

7. Validation

Check the reliability and validity of your findings by reviewing if the interpretations are supported by the data. This may involve revisiting the data multiple times or discussing the findings with colleagues or participants for validation.

8. Reporting

Finally, present the findings in a clear and organized manner. Use direct quotes and detailed descriptions to illustrate the themes and insights. The report should communicate the narrative you’ve built from your data, clearly linking your findings to your research questions.

Limitations of qualitative research

The disadvantages of qualitative research are quite unique. The techniques of the data collector and their own unique observations can alter the information in subtle ways. That being said, these are the qualitative research’s limitations:

1. It’s a time-consuming process

The main drawback of qualitative study is that the process is time-consuming. Another problem is that the interpretations are limited. Personal experience and knowledge influence observations and conclusions.

Thus, qualitative research might take several weeks or months. Also, since this process delves into personal interaction for data collection, discussions often tend to deviate from the main issue to be studied.

2. You can’t verify the results of qualitative research

Because qualitative research is open-ended, participants have more control over the content of the data collected. So the marketer is not able to verify the results objectively against the scenarios stated by the respondents. For example, in a focus group discussing a new product, participants might express their feelings about the design and functionality. However, these opinions are influenced by individual tastes and experiences, making it difficult to ascertain a universally applicable conclusion from these discussions.

3. It’s a labor-intensive approach

Qualitative research requires a labor-intensive analysis process such as categorization, recording, etc. Similarly, qualitative research requires well-experienced marketers to obtain the needed data from a group of respondents.

4. It’s difficult to investigate causality

Qualitative research requires thoughtful planning to ensure the obtained results are accurate. There is no way to analyze qualitative data mathematically. This type of research is based more on opinion and judgment rather than results. Because all qualitative studies are unique they are difficult to replicate.

5. Qualitative research is not statistically representative

Because qualitative research is a perspective-based method of research, the responses given are not measured.

Comparisons can be made and this can lead toward duplication, but for the most part, quantitative data is required for circumstances that need statistical representation and that is not part of the qualitative research process.

While doing a qualitative study, it’s important to cross-reference the data obtained with the quantitative data. By continuously surveying prospects and customers marketers can build a stronger database of useful information.

Quantitative vs. Qualitative Research

Image source

Quantitative and qualitative research are two distinct methodologies used in the field of market research, each offering unique insights and approaches to understanding consumer behavior and preferences.

As we already defined, qualitative analysis seeks to explore the deeper meanings, perceptions, and motivations behind human behavior through non-numerical data. On the other hand, quantitative research focuses on collecting and analyzing numerical data to identify patterns, trends, and statistical relationships.  

Let’s explore their key differences: 

Nature of Data:

• Quantitative research : Involves numerical data that can be measured and analyzed statistically.
• Qualitative research : Focuses on non-numerical data, such as words, images, and observations, to capture subjective experiences and meanings.

Research Questions:

• Quantitative research : Typically addresses questions related to “how many,” “how much,” or “to what extent,” aiming to quantify relationships and patterns.
• Qualitative research: Explores questions related to “why” and “how,” aiming to understand the underlying motivations, beliefs, and perceptions of individuals.

Data Collection Methods:

• Quantitative research : Relies on structured surveys, experiments, or observations with predefined variables and measures.
• Qualitative research : Utilizes open-ended interviews, focus groups, participant observations, and textual analysis to gather rich, contextually nuanced data.

Analysis Techniques:

• Quantitative research: Involves statistical analysis to identify correlations, associations, or differences between variables.
• Qualitative research: Employs thematic analysis, coding, and interpretation to uncover patterns, themes, and insights within qualitative data.

Do Conversion Rate Optimization the Right way.

Explore helps you make the most out of your CRO efforts through advanced A/B testing, surveys, advanced segmentation and optimised customer journeys.

If you haven’t subscribed yet to our newsletter, now is your chance!

Like what you’re reading?

Join the informed ecommerce crowd.

We will never bug you with irrelevant info.

By clicking the Button, you confirm that you agree with our Terms and Conditions .

Continue your Conversion Rate Optimization Journey

• Last modified: January 3, 2023
• Conversion Rate Optimization , User Research

Valentin Radu

We’re a team of people that want to empower marketers around the world to create marketing campaigns that matter to consumers in a smart way. Meet us at the intersection of creativity, integrity, and development, and let us show you how to optimize your marketing.

Our Software

• > Book a Demo
• > Partner Program
• > Affiliate Program
• Blog Sitemap

How to Determine the Scope of Research | Examples & Tips

Introduction

What is the scope of a study, what is a research scope example, what is the purpose of the research scope, what considerations are relevant to the research scope, how do i write the scope in a report.

The scope of a research project is one of the more important yet sometimes understated aspects of a study. The scope of the study explains what the researchers are examining and what environment they are studying.

This article explains the general purpose of the research scope, how it informs the broader study at hand, and how it can be incorporated in a research paper to establish the necessary transparency and rigor for your research audience.

Scientific knowledge very rarely, if ever, produces universal axioms. The boiling point of water changes depending on the amount of pressure in the air and, by extension, the altitude you are at relative to sea level when you boil water. What looks like polite behavior in a given culture may look rude in another. The definition of beauty is bound to change as people get older.

Similarly, research findings that aren't contextualized are less persuasive. If you are reading a study that looks at interactional patterns between parents and their children, it's important to have a clear sense of the theoretical lens , data collection , and analysis in order to determine the extent to which the findings are applicable across contexts.

In a nutshell, the scope tells you what the researchers are looking at and are not looking at. It provides the context necessary to understand the research, how it was conducted, and what findings it generated.

Conversely, establishing the bounds of the scope also clarify what research inquiries are not addressed in the study, ensuring that the study's argumentation is clearly grounded in the theory, data, and analysis.

Let's imagine an example of a research study examining best practices for mental health. The research design centers on a survey study with a target population of college students with part-time jobs in addition to their coursework.

The researchers can focus on any number of things affecting mental health, including lifestyle factors such as sleep, socioeconomic factors such as income, and even influences further afield like the political alignment of friends and family.

Certainly, any of these things can have a profound impact on one's mental health. But when there are so many things to examine, it's necessary to narrow down what the research project at hand should examine.

The scope of the study can come down to any number of things, including the researchers' interest, the current state of theoretical development on the subject of mental health, and the design of the study, particularly how the data is collected. It might even boil down to influences like geographical location, which can determine the kind of research participants involved in the study.

All of these factors can inform an explicit description of the scope, which might look like this if found in the methodology section of a paper:

"In this study, the researchers focused on surveying college students over four months, roughly the same time frame as a semester at a university in the United States. Surveys were distributed to all college students, but this paper will narrow the data analysis to those students who reported having part-time jobs. This refined lens aligns with our interest in examining work-related factors contributing to negative mental health outcomes, as established in previous studies."

The above example of a study's scope highlights what the researchers focused on during the study and while analyzing the data. The researchers chose to study a narrow subset of their data to generate insights most applicable to their research interests. The researchers might also analyze the proportion of students that reported having part-time jobs to give a broader description of the study body, but they clearly focus on understanding the mental health of students with part-time jobs.

Moreover, the narrow scope allows the researchers to focus on a small number of elements in the relationship between mental health and work, which allows the researchers to make deeper contributions to this specific part of the conversation around students' mental health.

Defining the scope of the study benefits both the researcher and their audience. Ultimately, establishing transparency in a research project focuses the data collection and analysis processes and makes the findings more compelling and persuasive.

Describing the scope can clarify what specific concepts should be used and examined during the course of the study. A good scope can keep the researcher focused on what data to collect and what ancillary developments, however interesting or useful, should be discarded or left to another study. Setting a clear scope can greatly help researchers maintain a coherent fit between their research question, collected data, and ultimate findings. Journal editors and reviewers often reject papers for publication because of a lack of fit between these important elements, which highlights the value of a clear research scope for conducting rigorous research.

In logistical terms, a well-defined scope also ensures the feasibility of a study by limiting the researcher's lens to a small but manageable set of factors to observe and analyze during the course of the study. Conversely, an unfocused study makes the collection of data a significant challenge when the researcher is left to document as much as possible, potentially gathering all kinds of data that may not be relevant to a given research question , while not gathering enough of the appropriate data that can address a research inquiry.

The research audience also requires an understanding of the scope of the study to determine the relevance of the findings to their own research inquiry. Readers of research bring their own assumptions and preconceived notions about what to look at in a given context. A well-written scope, on the other hand, gives readers clear guidance on what to look for in the study's analysis and findings.

From start to finish, make ATLAS.ti your research solution

Make the most of your qualitative data with ATLAS.ti. Get started by downloading a free trial.

Besides the research area being studied, the scope of a study has a clear description of most of the following aspects. Understanding what makes rigorous research and what readers of research look for in a well-crafted study will be useful for describing the scope of a research project.

Target population

The kind of research participants you are including in a study informs what theories are relevant and how the study should be designed. Are you researching children, young adults, or older professionals? Do they belong to a specific culture or community? Are they connected or related to each other in some way or do they just happen to belong to the same demographic?

Because qualitative, social science research seldom yields universal theories, it's important to narrow the scope of a study down to a specific set of the population. The more specific the scope, the more that the findings and resulting theoretical developments can be appropriately contextualized and thus inform how other researchers can build on those insights.

Geographical location

The geographical location covered by the study provides a necessary context for any study in the social sciences. Even if you narrow the targeted population to a specific demographic, what is true for that population in one country or region may not be true for another.

As a result, a scope that describes the location of the study explains where the findings are most relevant and where they might be relevant for further study.

Data collection

If you are conducting observational or ethnographic research , it may seem like you are facing a firehose when it comes to collecting data. Even interviews , focus groups , and surveys can provide a torrent of data, much of which may not be relevant to your inquiry if the study design isn't refined.

Without a sufficiently defined scope that identifies what aspects of the world you are looking at, the data you collect may become unmanageable at best. When crafting your study, develop the scope to determine the specific topics and aspects worth exploring.

In academic publishing , reviewers and editors need a clear understanding of the scope of the study in a manuscript when evaluating the research. Despite its importance, however, the scope doesn't necessarily have its own explicit section in a research paper.

That said, you can describe the study's scope in key areas of your research writing. Here are some of the important sections in a typical research paper for academic writing where a description of the scope is key.

Literature review

Any study disseminated for academic publishing requires a thorough understanding of the current research and existing theories that are relevant to your study. In turn, the literature review also defines the aspects of the phenomenon or concepts that you can study for the purpose of theoretical development.

Rely on the key theories in the literature review to define a useful scope that identifies key aspects of the theoretical framework that will inform the data collection and analysis .

Problem statement

A well-crafted problem statement generally sets the stage for what knowledge is missing and what novel and interesting insights can be uncovered in new research. As a result, a clear understanding of the research scope helps define the problem that a new research project seeks to address.

When incorporating a problem statement in your research paper, be sure to explicitly detail the rationale for problematizing the phenomenon you are researching.

Research question

Research questions define the relationships between the relevant concepts or phenomena being explored, and thus provide evidence of a scope that has been thoughtfully planned. Use the wording of your research question to highlight what is the central focus and, thus, the scope of the study.

At minimum, the scope of the study should narrow the focus of data collection and data analysis to the study of certain concepts relevant to addressing the given research question. Qualitative research methods can often result in open-ended data collection that can yield many insights, only a few of which may directly address the research inquiry.

Narrowing the collection of data to a set of relevant criteria can help the researcher avoid any unnecessary rabbit holes that might complicate the later analysis with irrelevant information.

Limitations

Research scope and limitations go hand in hand because, together, they define what is studied within a research project and what is not. Moreover, a good description of the study's scope can also provide direction, by way of the description of limitations, about what inquiries other researchers could pursue next.

Bring clarity to your research with ATLAS.ti

Turn data into insights with our powerful data analysis platform. Download a free trial of ATLAS.ti today.

Data Analysis in Research

Ai generator.

Data analysis in research involves systematically applying statistical and logical techniques to describe, illustrate, condense, and evaluate data. It is a crucial step that enables researchers to identify patterns, relationships, and trends within the data, transforming raw information into valuable insights. Through methods such as descriptive statistics, inferential statistics, and qualitative analysis, researchers can interpret their findings, draw conclusions, and support decision-making processes. An effective data analysis plan and robust methodology ensure the accuracy and reliability of research outcomes, ultimately contributing to the advancement of knowledge across various fields.

What is Data Analysis in Research?

Data analysis in research involves using statistical and logical techniques to describe, summarize, and compare collected data. This includes inspecting, cleaning, transforming, and modeling data to find useful information and support decision-making. Quantitative data provides measurable insights, and a solid research design ensures accuracy and reliability. This process helps validate hypotheses, identify patterns, and make informed conclusions, making it a crucial step in the scientific method.

Examples of Data analysis in Research

• Survey Analysis : Researchers collect survey responses from a sample population to gauge opinions, behaviors, or characteristics. Using descriptive statistics, they summarize the data through means, medians, and modes, and then inferential statistics to generalize findings to a larger population.
• Experimental Analysis : In scientific experiments, researchers manipulate one or more variables to observe the effect on a dependent variable. Data is analyzed using methods such as ANOVA or regression analysis to determine if changes in the independent variable(s) significantly affect the dependent variable.
• Content Analysis : Qualitative research often involves analyzing textual data, such as interview transcripts or open-ended survey responses. Researchers code the data to identify recurring themes, patterns, and categories, providing a deeper understanding of the subject matter.
• Correlation Studies : Researchers explore the relationship between two or more variables using correlation coefficients. For example, a study might examine the correlation between hours of study and academic performance to identify if there is a significant positive relationship.
• Longitudinal Analysis : This type of analysis involves collecting data from the same subjects over a period of time. Researchers analyze this data to observe changes and developments, such as studying the long-term effects of a specific educational intervention on student achievement.
• Meta-Analysis : By combining data from multiple studies, researchers perform a meta-analysis to increase the overall sample size and enhance the reliability of findings. This method helps in synthesizing research results to draw broader conclusions about a particular topic or intervention.

Data analysis in Qualitative Research

Data analysis in qualitative research involves systematically examining non-numeric data, such as interviews, observations, and textual materials, to identify patterns, themes, and meanings. Here are some key steps and methods used in qualitative data analysis:

• Coding : Researchers categorize the data by assigning labels or codes to specific segments of the text. These codes represent themes or concepts relevant to the research question.
• Thematic Analysis : This method involves identifying and analyzing patterns or themes within the data. Researchers review coded data to find recurring topics and construct a coherent narrative around these themes.
• Content Analysis : A systematic approach to categorize verbal or behavioral data to classify, summarize, and tabulate the data. This method often involves counting the frequency of specific words or phrases.
• Narrative Analysis : Researchers focus on the stories and experiences shared by participants, analyzing the structure, content, and context of the narratives to understand how individuals make sense of their experiences.
• Grounded Theory : This method involves generating a theory based on the data collected. Researchers collect and analyze data simultaneously, continually refining and adjusting their theoretical framework as new data emerges.
• Discourse Analysis : Examining language use and communication patterns within the data, researchers analyze how language constructs social realities and power relationships.
• Case Study Analysis : An in-depth analysis of a single case or multiple cases, exploring the complexities and unique aspects of each case to gain a deeper understanding of the phenomenon under study.

Data analysis in Quantitative Research

Data analysis in quantitative research involves the systematic application of statistical techniques to numerical data to identify patterns, relationships, and trends. Here are some common methods used in quantitative data analysis:

• Descriptive Statistics : This includes measures such as mean, median, mode, standard deviation, and range, which summarize and describe the main features of a data set.
• Inferential Statistics : Techniques like t-tests, chi-square tests, and ANOVA (Analysis of Variance) are used to make inferences or generalizations about a population based on a sample.
• Regression Analysis : This method examines the relationship between dependent and independent variables. Simple linear regression analyzes the relationship between two variables, while multiple regression examines the relationship between one dependent variable and several independent variables.
• Correlation Analysis : Researchers use correlation coefficients to measure the strength and direction of the relationship between two variables.
• Factor Analysis : This technique is used to identify underlying relationships between variables by grouping them into factors based on their correlations.
• Cluster Analysis : A method used to group a set of objects or cases into clusters, where objects in the same cluster are more similar to each other than to those in other clusters.
• Hypothesis Testing : This involves testing an assumption or hypothesis about a population parameter. Common tests include z-tests, t-tests, and chi-square tests, which help determine if there is enough evidence to reject the null hypothesis.
• Time Series Analysis : This method analyzes data points collected or recorded at specific time intervals to identify trends, cycles, and seasonal variations.
• Multivariate Analysis : Techniques like MANOVA (Multivariate Analysis of Variance) and PCA (Principal Component Analysis) are used to analyze data that involves multiple variables to understand their effect and relationships.
• Structural Equation Modeling (SEM) : A multivariate statistical analysis technique that is used to analyze structural relationships. This method is a combination of factor analysis and multiple regression analysis and is used to analyze the structural relationship between measured variables and latent constructs.

Data analysis in Research Methodology

Data analysis in research methodology involves the process of systematically applying statistical and logical techniques to describe, condense, recap, and evaluate data. Here are the key components and methods involved:

• Data Preparation : This step includes collecting, cleaning, and organizing raw data. Researchers ensure data quality by handling missing values, removing duplicates, and correcting errors.
• Descriptive Analysis : Researchers use descriptive statistics to summarize the basic features of the data. This includes measures such as mean, median, mode, standard deviation, and graphical representations like histograms and pie charts.
• Inferential Analysis : This involves using statistical tests to make inferences about the population from which the sample was drawn. Common techniques include t-tests, chi-square tests, ANOVA, and regression analysis.
• Qualitative Data Analysis : For non-numeric data, researchers employ methods like coding, thematic analysis, content analysis, narrative analysis, and discourse analysis to identify patterns and themes.
• Quantitative Data Analysis : For numeric data, researchers apply statistical methods such as correlation, regression, factor analysis, cluster analysis, and time series analysis to identify relationships and trends.
• Hypothesis Testing : Researchers test hypotheses using statistical methods to determine whether there is enough evidence to reject the null hypothesis. This involves calculating p-values and confidence intervals.
• Data Interpretation : This step involves interpreting the results of the data analysis. Researchers draw conclusions based on the statistical findings and relate them back to the research questions and objectives.
• Validation and Reliability : Ensuring the validity and reliability of the analysis is crucial. Researchers check for consistency in the results and use methods like cross-validation and reliability testing to confirm their findings.
• Visualization : Effective data visualization techniques, such as charts, graphs, and plots, are used to present the data in a clear and understandable manner, aiding in the interpretation and communication of results.
• Reporting : The final step involves reporting the results in a structured format, often including an introduction, methodology, results, discussion, and conclusion. This report should clearly convey the findings and their implications for the research question.

Types of Data analysis in Research

• Purpose : To summarize and describe the main features of a dataset.
• Methods : Mean, median, mode, standard deviation, frequency distributions, and graphical representations like histograms and pie charts.
• Example : Calculating the average test scores of students in a class.
• Purpose : To make inferences or generalizations about a population based on a sample.
• Methods : T-tests, chi-square tests, ANOVA (Analysis of Variance), regression analysis, and confidence intervals.
• Example : Testing whether a new teaching method significantly affects student performance compared to a traditional method.
• Purpose : To analyze data sets to find patterns, anomalies, and test hypotheses.
• Methods : Visualization techniques like box plots, scatter plots, and heat maps; summary statistics.
• Example : Visualizing the relationship between hours of study and exam scores using a scatter plot.
• Purpose : To make predictions about future outcomes based on historical data.
• Methods : Regression analysis, machine learning algorithms (e.g., decision trees, neural networks), and time series analysis.
• Example : Predicting student graduation rates based on their academic performance and demographic data.
• Purpose : To provide recommendations for decision-making based on data analysis.
• Methods : Optimization algorithms, simulation, and decision analysis.
• Example : Suggesting the best course of action for improving student retention rates based on various predictive factors.
• Purpose : To identify and understand cause-and-effect relationships.
• Methods : Controlled experiments, regression analysis, path analysis, and structural equation modeling (SEM).
• Example : Determining the impact of a specific intervention, like a new curriculum, on student learning outcomes.
• Purpose : To understand the specific mechanisms through which variables affect one another.
• Methods : Detailed modeling and simulation, often used in scientific research to understand biological or physical processes.
• Example : Studying how a specific drug interacts with biological pathways to affect patient health.

How to write Data analysis in Research

Data analysis is crucial for interpreting collected data and drawing meaningful conclusions. Follow these steps to write an effective data analysis section in your research.

1. Prepare Your Data

Ensure your data is clean and organized:

• Remove duplicates and irrelevant data.
• Check for errors and correct them.
• Categorize data if necessary.

2. Choose the Right Analysis Method

Select a method that fits your data type and research question:

• Quantitative Data : Use statistical analysis such as t-tests, ANOVA, regression analysis.
• Qualitative Data : Use thematic analysis, content analysis, or narrative analysis.

3. Describe Your Analytical Techniques

Clearly explain the methods you used:

• Software and Tools : Mention any software (e.g., SPSS, NVivo) used.
• Statistical Tests : Detail the statistical tests applied, such as chi-square tests or correlation analysis.
• Qualitative Techniques : Describe coding and theme identification processes.

4. Present Your Findings

Organize your findings logically:

• Use Tables and Figures : Display data in tables, graphs, and charts for clarity.
• Summarize Key Results : Highlight the most significant findings.
• Include Relevant Statistics : Report p-values, confidence intervals, means, and standard deviations.

5. Interpret the Results

Explain what your findings mean in the context of your research:

• Compare with Hypotheses : State whether the results support your hypotheses.
• Relate to Literature : Compare your results with previous studies.
• Discuss Implications : Explain the significance of your findings.

6. Discuss Limitations

Acknowledge any limitations in your data or analysis:

• Sample Size : Note if the sample size was small.
• Biases : Mention any potential biases in data collection.
• External Factors : Discuss any factors that might have influenced the results.

7. Conclude with a Summary

Wrap up your data analysis section:

• Restate Key Findings : Briefly summarize the main results.
• Future Research : Suggest areas for further investigation.

Importance of Data analysis in Research

Data analysis is a fundamental component of the research process. Here are five key points highlighting its importance:

• Enhances Accuracy and Reliability Data analysis ensures that research findings are accurate and reliable. By using statistical techniques, researchers can minimize errors and biases, ensuring that the results are dependable.
• Facilitates Informed Decision-Making Through data analysis, researchers can make informed decisions based on empirical evidence. This is crucial in fields like healthcare, business, and social sciences, where decisions impact policies, strategies, and outcomes.
• Identifies Trends and Patterns Analyzing data helps researchers uncover trends and patterns that might not be immediately visible. These insights can lead to new hypotheses and areas of study, advancing knowledge in the field.
• Supports Hypothesis Testing Data analysis is vital for testing hypotheses. Researchers can use statistical methods to determine whether their hypotheses are supported or refuted, which is essential for validating theories and advancing scientific understanding.
• Provides a Basis for Predictions By analyzing current and historical data, researchers can develop models that predict future outcomes. This predictive capability is valuable in numerous fields, including economics, climate science, and public health.

FAQ’s

What is the difference between qualitative and quantitative data analysis.

Qualitative analysis focuses on non-numerical data to understand concepts, while quantitative analysis deals with numerical data to identify patterns and relationships.

What is descriptive statistics?

Descriptive statistics summarize and describe the features of a data set, including measures like mean, median, mode, and standard deviation.

What is inferential statistics?

Inferential statistics use sample data to make generalizations about a larger population, often through hypothesis testing and confidence intervals.

What is regression analysis?

Regression analysis examines the relationship between dependent and independent variables, helping to predict outcomes and understand variable impacts.

What is the role of software in data analysis?

Software like SPSS, R, and Excel facilitate data analysis by providing tools for statistical calculations, visualization, and data management.

What are data visualization techniques?

Data visualization techniques include charts, graphs, and maps, which help in presenting data insights clearly and effectively.

What is data cleaning?

Data cleaning involves removing errors, inconsistencies, and missing values from a data set to ensure accuracy and reliability in analysis.

What is the significance of sample size in data analysis?

Sample size affects the accuracy and generalizability of results; larger samples generally provide more reliable insights.

How does correlation differ from causation?

Correlation indicates a relationship between variables, while causation implies one variable directly affects the other.

What are the ethical considerations in data analysis?

Ethical considerations include ensuring data privacy, obtaining informed consent, and avoiding data manipulation or misrepresentation.

Text prompt

• Instructive
• Professional

10 Examples of Public speaking

20 Examples of Gas lighting

Research Trends in STEM Clubs: A Content Analysis

• Open access
• Published: 25 June 2024

Cite this article

You have full access to this open access article

• Rabia Nur Öndeş   ORCID: orcid.org/0000-0002-9787-4382 1  

55 Accesses

Explore all metrics

To identify the research trends in studies related to STEM Clubs, 56 publications that met the inclusion and extraction criteria were identified from the online databases ERIC and WoS in this study. These studies were analysed by using the descriptive content analysis research method based on the Paper Classification Form (PCF), which includes publishing years, keywords, research methods, sample levels and sizes, data collection tools, data analysis methods, durations, purposes, and findings. The findings showed that, the keywords in the studies were used under six different categories: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). Case studies were frequently employed, with middle school students serving as the main participants in sample groups ranging from 11–15, 16–20, and 201–250. Surveys, questionnaires, and observations were the primary methods of data collection, and descriptive analysis was commonly used for data analysis. STEM Clubs had sessions ranging from 2 to 16 weeks, with each session commonly lasting 60 to 120 min. The study purposes mainly focused on four themes: the impact of participation on various aspects such as attitudes towards STEM disciplines, career paths, STEM major selection, and academic achievement; the development and implementation of a sample STEM Club program, including challenges and limitations; the examination of students' experiences, perceptions, and factors influencing their involvement and choice of STEM majors; the identification of some aspects such as attitudinal effects and non-academic skills; and the comparison of STEM experiences between in-school and out-of-school settings. The study results mainly focused on three themes: the increase in various aspects such as academic achievement, STEM major choice, engagement in STEM clubs, identity, interest in STEM, collaboration-communication skills; the design of STEM Clubs, including sample implementations, design principles, challenges, and factors affecting their success and sustainability; and the identification of factors influencing participation, motivation, and barriers. Overall, this study provides a comprehensive understanding of STEM Clubs, leading the way for more targeted and informed future research endeavours.

Similar content being viewed by others

Measuring the effect of sustainability programs on interest in STEM disciplines: a pre-post survey study of the student green team internship program

Effects of Out-of-School STEM Learning Environments on Student Interest: a Critical Systematic Literature Review

Which role models are effective for which students? A systematic review and four recommendations for maximizing the effectiveness of role models in STEM

Avoid common mistakes on your manuscript.

Introduction

Worldwide, STEM education, which integrates the disciplines of science, technology, engineering, and math, is gaining popularity in K-12 settings due to its capacity to enhance 21st-century skills such as adaptability, problem-solving, and creative thinking (National Research Council [NRC], 2015 ). In STEM lessons, students are frequently guided by the engineering design process, which involves identifying problems or technical challenges and creating and developing solutions. Furthermore, higher achievement in STEM education has been linked to increased enrolment in post-secondary STEM fields, offering students greater opportunities to pursue careers in these domains (Merrill & Daugherty, 2010 ). However, STEM activities require dedicated time and the restructuring of integrated curricula, necessitating careful organization of lessons. Recognizing the complexity of developing 21st-century STEM proficiency, schools are not expected to tackle this challenge alone. In addition to regular STEM classes, there exists a diverse range of extended education programs, activities, and out-of-school learning environments (Baran et al., 2016 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ). In this paper, out-of-school learning environments, informal learning environments, extended education, and afterschool programs were used synonymously. It is worth noting that the literature lacks a universally accepted definition for out-of-school learning environments, leading to the use of various interchangeable terms (Donnelly et al., 2019 ). Some of these terms include informal learning environments, extended education, afterschool programs, all-day school, extracurricular activities, out-of-school time learning, extended schools, expanded learning, and leisure-time activities. These terms refer to optional programs and clubs offered by schools that exist outside of the standard academic curriculum (Baran et al., 2016 ; Cooper, 2011 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ).

Out-of-school learning, in contrast to traditional in-school learning, offers greater flexibility in terms of time and space, as it is not bound by the constraints of the school schedule, national or state standards, and standardized tests (Cooper, 2011 ). Out-of-school learning experiences typically involve collaborative engagement, the use of tools, and immersion in authentic environments, while school environments often emphasize individual performance, independent thinking, symbolic representations, and the acquisition of generalized skills and knowledge (Resnick, 1987 ). They encompass everyday activities such as family discussions, pursuing hobbies, and engaging in daily conversations, as well as designed environments like museums, science centres, and afterschool programs (Civil, 2007 ; Hein, 2009 ). On the other hand, extended education refers to intentionally structured learning and development programs and activities that are not part of regular classes. These programs are typically offered before and after school, as well as at locations outside the school (Bae, 2018 ). As a result, out-of-school learning environments encompass a wide range of experiences, including social, cultural, and technical excursions around the school, field studies at museums, zoos, nature centres, aquariums, and planetariums, project-based learning, sports activities, nature training, and club activities (Civil, 2007 ; Donnelly et al., 2019 ; Hein, 2009 ). At this point, STEM clubs are a specialized type of extracurricular activity that engage students in hands-on projects, experiments, and learning experiences related to scientific, technological, engineering, and mathematical disciplines. STEM Clubs, described as flexible learning environments unconstrained by time or location, offer an effective approach to conducting STEM studies outside of school (Blanchard et al., 2017 ; Cooper, 2011 ; Dabney et al., 2012 ).

Out-of-school learning environments, extended education or afterschool programs, hold tremendous potential for enhancing student learning and providing them with a diverse and enriching educational experience (Robelen, 2011 ). Extensive research supports the notion that these alternative educational programs not only contribute to students' academic growth but also foster their social, emotional, and intellectual development (NRC, 2015 ). Studies have consistently shown that after-school programs play a vital role in boosting students' achievement levels (Casing & Casing, 2024 ; Pastchal-Temple, 2012 ; Shernoff & Vandell, 2007 ), and contributing to positive emotional development, including improved self-esteem, positive attitudes, and enhanced social behaviour (Afterschool Alliance, 2015 ; Durlak & Weissberg, 2007 ; Lauer et al., 2006 ; Little et al., 2008 ). Moreover, engaging in various activities within these programs allows students to develop meaningful connections, expand their social networks, enhance leadership skills (Lipscomb et al., 2017 ), and cultivate cooperation, effective communication, and innovative problem-solving abilities (Mahoney et al., 2007 ).

Implementing STEM activities in out-of-school learning environments not only supports students in making career choices and fostering meaningful learning and interest in science, but also facilitates deep learning experiences (Bybee, 2001 ; Dabney et al., 2012 ; Sahin et al., 2018 ). Furthermore, STEM Clubs enhance students' emotional skills, such as a sense of belonging and peer-to-peer communication, while also fostering 21st-century skills, facilitating the acquisition of current content, and promoting career awareness and interest in STEM professions (Blanchard et al., 2017 ). In summary, engaging in STEM activities through social club activities not only addresses time constraints but also complements formal education and contributes to students' overall development. Hence, STEM Clubs, which are part of extended education, can be defined as dynamic and flexible learning environments that provide an effective approach to conducting STEM studies beyond traditional classroom settings. These clubs offer flexibility in terms of time and location, with intentionally structured programs and activities that take place outside of regular classes. They provide students with unique opportunities to explore and deepen their understanding of STEM subjects through collaborative engagement, hands-on use of tools, and immersive experiences in authentic environments (Bae, 2018 ; Blanchard, et al., 2017 ; Bybee, 2001 ; Cooper, 2011 ; Dabney et al., 2012 ). STEM Clubs have gained immense popularity worldwide, providing students with invaluable opportunities to explore and cultivate their interests and knowledge in these crucial fields (Adams et al., 2014 ; Bell et al., 2009 ). According to America After 3PM, nearly 75% of afterschool program participants, around 5,740,836 children, have access to STEM learning opportunities (Afterschool Alliance, 2015 ).

STEM Clubs as after-school programs come in various forms and provide diverse tutoring and instructional opportunities. For instance, the Boys and Girls Club of America (BGCA) operates in numerous cities across the United States, annually serving 4.73 million students (Boys and Girls Club of America, 2019 ). This program offers students the chance to engage in activities like sports, art, dance, field trips, and addresses the underrepresentation of African Americans in STEM. Another example is the Science Club for Girls (SCFG), established by concerned parents in Cambridge to address gender inequity in math, science, and technology courses and careers. SCFG brings together girls from grades K–7 through free after-school or weekend clubs, science explorations during vacations, and community science fairs, with approximately 800 to 1,000 students participating each year. The primary goal of these clubs is to increase STEM literacy and self-confidence among K–12 girls from underrepresented groups in these fields. More examples can be found in the literature, such as the St. Jude STEM Club (SJSC), where students conducted a 10-week paediatric cancer research project using accurate data (Ayers et al., 2020 ), and After School Matters, based in Chicago, offers project-based learning that enhances students' soft skills and culminates in producing a final project based on their activities (Hirsch, 2011 ).

The Purpose of The Study

The literature on STEM Clubs indicates a diverse range of such clubs located worldwide, catering to different student groups, operating on varying schedules, implementing diverse activities, and employing various strategies, methodologies, experiments, and assessments (Ayers et al., 2020 ; Blanchard et al., 2017 ; Boys and Girls Club of America, 2019 ; Hirsch, 2011 ; Sahin et al., 2018 ). However, it was previously unknown which specific sample groups were most commonly studied, which analytical methods were used frequently, and which results were primarily reported, even though the overall topic of STEM Clubs has gained significant attention. Therefore, organizing and categorizing this expansive body of literature is necessary to gain deeper insights into the current state of knowledge and practices in STEM Clubs. By systematically reviewing and synthesizing the diverse range of studies on this topic, we can develop a clearer understanding of the focus areas, methodologies, and key findings that have emerged from the existing research (Fraenkel et al., 2012 ). At this point, using a content analysis method is appropriate for this purpose because this method is particularly useful for examining trends and patterns in documents (Stemler, 2000 ). Similarly, some previous research on STEM education has conducted content analyses to examine existing studies and construct holistic patterns to understand trends (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ). However, there is a lack of content analysis specifically focused on studies of STEM Clubs in the literature and showing the trends in this topic. Analysing research trends in STEM Clubs can help build upon existing knowledge, identify gaps, explore emerging topics, and highlight successful methodologies and strategies (Fraenkel et al., 2012 ; Noris et al., 2023 ; Stemler, 2000 ). This information can be valuable for researchers, educators, and policymakers to stay up-to-date and make informed decisions regarding curriculum design (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ), the development of effective STEM Club programs, resource allocation, and policy formulation (Blanchard et al., 2017 ; Cooper, 2011 ; Dabney et al., 2012 ). Therefore, the identification of research trends in STEM Clubs was the aim of this study.

To identify research trends, studies commonly analysed documents by considering the dimensions of articles such as keywords, publishing years, research designs, purposes, sample levels, sample sizes, data collection tools, data analysis methods, and findings (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Sozbilir et al., 2012 ). Using these dimensions as a framework is a useful and common approach in content analysis because this framework allows researchers to systematically examine the key aspects of existing studies and uncover patterns, relationships, and trends within the research data (Sozbilir et al., 2012 ). Hence, since the aim of this study is to identify and analyse research trends in STEM Clubs, it focused on publishing years, keywords, research designs, purposes, sample levels, sample sizes, data collection tools, data analysis methods, and findings of the studies on STEM Clubs.

As a conclusion, the main problem of this study is “What are the characteristics of the studies on STEM Clubs?”. The following sub-questions are addressed in this study:

What is the distribution of studies on STEM Clubs by year?

What are the frequently used keywords in studies on STEM Clubs?

What are the commonly employed research designs in studies on STEM Clubs?

What are the typical purposes explored in studies on STEM Clubs?

What are the commonly observed sample levels in studies on STEM Clubs?

What are the commonly observed sample sizes in studies on STEM Clubs?

What are the commonly utilized data collection tools in studies on STEM Clubs?

What are the commonly utilized data analysis methods in studies on STEM Clubs?

What are the typical durations reported in studies on STEM Clubs?

What are the commonly reported findings in studies on STEM Clubs?

In this study, the descriptive content analysis research method was employed, which allows for a systematic and objective examination of the content within articles, and description of the general trends and research results in a particular subject matter (Lin et al., 2014 ; Suri & Clarke, 2009 ; Sozbilir et al., 2012 ; Stemler, 2000 ). Given the aim of examining research trends in STEM Clubs, the utilization of this method was appropriate, as it provides a structured approach to identify patterns and trends (Gay et al., 2012 ). To implement the content analysis method, this study followed the three main phases proposed by Elo and Kyngäs ( 2008 ): preparation, organizing, and reporting. In the preparation phase, the unit of analysis, such as a word or theme, is selected as the starting point. So, in this study, the topic of STEM Clubs was carefully selected. During the organizing process, the researcher strives to make sense of the data and to learn "what is going on" and obtain a sense of the whole. So, in this study, during the analysis process, the content analysis framework (sample levels, sample sizes, data collection tools, research designs, etc.) was used to question the collected studies. Finally, in the reporting phase, the analyses are presented in a meaningful and coherent manner. So, the analyses were presented meaningfully with visual representations such as tables, graphs, etc. By adopting the content analysis research method and following the suggested phases, this study aimed to gain insights into research trends in STEM Clubs, identify recurring themes, and provide a comprehensive analysis of the collected data.

Search and Selection Process

The online databases ERIC and Web of Science were searched using keywords derived from a database thesaurus. These databases were chosen because of their widespread recognition and respect in the fields of education and academic research, and they offer a substantial amount of high-quality, peer-reviewed literature. The search process involved several steps. Firstly, titles, abstracts, and keywords were searched using Boolean operators for the keywords "STEM Clubs," "STEAM Clubs," "science-technology-engineering-mathematics clubs," "after school STEM program" and "extracurricular STEM activities" in the databases (criterion-1). Secondly, studies were collected beginning from November to the end of December 2023. So, the studies published until the end of December 2023 were included in the search, without a specific starting date restriction (criterion-2). Thirdly, the search was limited to scientific journal articles, book chapters, proceedings, and theses, excluding publications such as practices, letters to editors, corrections, and (guest) editorials (criterion-3). Fourthly, studies published in languages other than English were excluded, focusing exclusively on English language publications (criterion-4). Fifthly, duplicate articles found in both databases were identified and removed. Next, the author read the contents of all the studies, including those without full articles, with a particular focus on the abstract sections. After that, studies related to after school program and extracurricular activities that did not specifically involve the terms STEM or clubs were excluded, even though “extracurricular STEM activities” and “after school STEM program” were used in the search process, and there were studies related to after school program or extracurricular activities but not STEM (criterion-5). Additionally, studies conducted in formal and informal settings within STEM clubs were included, while studies conducted in settings such as museums or trips were excluded (criterion-6). Because STEM Clubs are a subset of informal STEM education settings, which also include museums and field trips, the main focus of this study is to show the trends specifically related to STEM Clubs. Moreover, studies focusing solely on technology without incorporating other STEM components were also excluded (criterion-7). Finally, 56 publications that met the inclusion and extraction criteria were identified. These publications comprised two dissertations, seven proceedings, and 47 articles from 36 different journals. By applying these criteria, the search process aimed to ensure the inclusion of relevant studies while excluding those that did not meet the specified criteria as shown in Fig.  1 .

Flowchart of article process selection

Data Analysing Process

Two different approaches were followed in the content analysis process of this study. In the first part, deductive content analysis was used, and a priori coding was conducted as the categories were established prior to the analysis. The categorization matrix was created based on the Paper Classification Form (PCF) developed by Sozbilir et al. ( 2012 ). The coding scheme devised consisted of eight classification groups for the sections of publication years, keywords, research designs, sample levels, sample sizes, data collection tools, data analysis methods, and durations, with sub-categories for each section. For example, under the research designs section, the sub-categories included qualitative and quantitative methods, case study, design-case study, comparative-case study, ethnographic study, phenomenological study, survey study, experimental study, mixed and longitudinal study, and literature review study. These sub-categories were identified prior to the analysis. Coding was then applied to the data using spreadsheets in the Excel program, based on the categorization matrix. Frequencies for the codes and categories created were calculated and presented in the findings section with tables. Line charts were used for the publication years section, while word clouds, which visually represent word frequency, were used for the keywords section. Word clouds display the most frequently used words in different sizes and colours based on their frequencies (DePaolo & Wilkinson, 2014 ). So, in this part, the analysis was certain since the studies mostly provided related information in their contents.

In the second part, open coding and the creation of categories and abstraction phases were followed for the purposes and findings sections. Firstly, the stated purposes and findings of the studies were written as text. The written text was then carefully reviewed, and any necessary terms were written down in the margins to describe all aspects of the content. Following this open coding, the lists of categories were grouped under higher order headings, taking into consideration their similarities or dissimilarities. Each category was named using content-characteristic words. The abstraction process was repeated to the extent that was reasonable and possible. In this coding process, two individuals independently reviewed ten studies, considering the coding scheme for the first part and conducting open coding for the second part. They then compared their notes and resolved any differences that emerged during their initial checklists. Inter-rater reliability was calculated as 0.84 using Cohen's kappa analysis. Once coding reliability was ensured, the remaining articles were independently coded by the author. After completing the coding process, consensus was reached through discussions regarding any disagreements among the researchers regarding the codes, as well as the codes and categories constructed for the purpose and findings sections. At this point, there were mostly agreements in the coding process since the studies had already clearly stated their key characteristics, such as research design, sample size, sample level, and data collection tools. Additionally, when coding the studies' stated purposes and results, the researchers closely referred to the original sentences in the studies, which led to a high level of consistency in the coded content between the two raters.

Studies related to the STEM Clubs were initially conducted in 2009 (Fig.  2 ). The noticeable increase in the number of studies conducted each year is remarkable. It can be seen that the majority of the 47 articles that were examined (56 articles) were published after 2015, despite a decrease in the year 2018. Additionally, it was observed that the articles were most frequently published (8) in the years 2019 and 2022, least frequently (1) in the years 2009, 2010, and 2014, and there were no publications in 2012.

Number of articles by years

Word clouds were utilized to present the most frequently used keywords in the articles, as shown in Fig.  3 . However, due to the lack of reported keywords in the ERIC database, only 30 articles were included for these analyses. The keywords that exist in these studies were represented in a word cloud in Fig.  3 . The most frequently appearing keywords, such as "STEM," "education" and "learning" were identified. Additionally, by using a content analysis method, these keywords were categorized into six different groups: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables) in Table  1 .

Word cloud of the keywords used in articles

The purposes of the identified studies identified were classified into six main themes: “effects of participation in STEM Clubs on” (25), “evolution of a sample program for STEM Clubs and its implementation” (25), “examination of” (11), “identification of” (3), “comparison of in-school and out-school STEM experiences” (2) and “others” (6). Table 2 presents the distribution of the articles’ purposes based on the classification regarding these themes. Therefore, it can be seen that purposes of “effects of participation in STEM Clubs on,” and “evolution of a sample program for STEM Clubs and its implementation” were given the highest and equal consideration, while the purposes related to "identification of" (3) and "comparison of in-school and out-of-school STEM experiences" (2) were given the least consideration among them.

Within the theme of "effects of participation in STEM Clubs on" there are 11 categories. The aims of the studies in this section are to examine the effect of participation in STEM Clubs on various aspects such as attitudes towards STEM disciplines or career paths, STEM major choice/career aspiration, achievement in math, science, STEM disciplines, or content knowledge, perception of scientists, strategies used, value of clubs, STEM career paths, enjoyment of physics, use of complex and scientific language, interest in STEM, creativity, critical thinking about STEM texts, images of mathematics, or climate-change beliefs/literacy. It is evident that the majority of research in this section focuses on the effects of participation in STEM Clubs on STEM major choice/career aspiration (5), achievement (4), perception of something (4), and interest in STEM (3).

Within the theme of "evolution of a sample program for STEM Clubs and its implementation" there are three categories: development of program/curriculum/activity (14), identification of program's challenges and limitations (3), and implementation of program/activity (8). The studies in this section aim to develop a sample program for STEM Clubs and describe its implementation. It can be seen that the most preferred purpose among them is the development of program/curriculum/activity (14), while the least preferred purpose is the identification of program's challenges and limitations (3). In addition, studies that focus on the development of the program, curriculum, or activity were classified under the "general" category (10). Sub-categories were created for studies specifically expressing the development of the program with a focus on a particular area, such as the maker movement or Arduino-assisted robotics and coding. Similarly, studies that explicitly mentioned the development of the program based on presented ideas and experiences formed another sub-category. Furthermore, the category related to the implementation of program/activity was divided into eight sub-categories, each indicating the specific centre of implementation, such as problem-based learning-centred and representation of blacks-centred.

The theme of "examination of" refers to studies that aim to examine certain aspects, such as the experiences and perceptions of students (7) and the factors influencing specific subjects (4). Studies focusing on examining the experiences and perceptions of students were labelled as "general" (4), while studies exploring their experiences and perceptions regarding specific content, such as influences and challenges to participation in STEM clubs (2) and assessment (1), were labelled accordingly. Additionally, studies that focused on examining factors affecting the choice of STEM majors (2), participation in STEM clubs (1), and motivation to develop interest in STEM (1) were categorized in line with their respective focuses. As shown in Table  2 , it is evident that studies focusing on examining the experiences and perceptions of students (7) were more frequently conducted compared to studies focusing on examining the factors affecting specific subjects (4).

The theme of "identification of" refers to studies that aim to identify certain aspects, such as the types of attitudinal effects (1), types of changes in affect toward engineering (1), and non-academic skills (1). Additionally, the theme of "comparison of in-school and out-of-school STEM experiences" (2) refers to studies that aim to compare STEM experiences within school and outside of school. Lastly, studies that did not fit into the aforementioned categories were included in the "others" theme (6) as no clear connection could be identified among them.

Research Designs

The research designs employed in the examined articles were identified as follows: qualitative methods (36), including case study (20), design-case study (6), comparative-case study (4), ethnographic study (2), phenomenological study (2), and survey study (2); quantitative methods (7), including survey study (4) and experimental study (3); mixed methods and longitudinal studies (10); and literature review (3), as illustrated in Table  3 . It can be observed that among these methods, case study was the most commonly utilized. Furthermore, it is evident that quantitative methods (7) and literature reviews (3) were employed less frequently compared to qualitative (36) and mixed methods (10). Additionally, survey studies were utilized in both quantitative and qualitative studies.

Sample Levels

The frequencies and percentages of sample levels in the examined articles are presented in Table  4 . The studies involved participants at different educational levels, including elementary school (8), middle school (23), high school (14), pre-service teachers or undergraduate students (6), teachers (4), parents (3), and others (1). It is apparent that middle school students (23) were the most commonly utilized sample among them, while high school students (14) were more frequently chosen compared to elementary school students (8). It should be noted that while grade levels were specified for both elementary and middle school students, separate grade levels were not identified for high school students in these studies. Additionally, studies that involved mixed groups were labelled as 3-5th and 6-8th grades. However, when the mixed groups included participants from different educational levels such as elementary, middle, or high school, teachers, parents, etc., they were counted as separate levels. Furthermore, the studies conducted with participants such as pre-service teachers, undergraduates, teachers, and parents were less frequently employed compared to K-12 students.

Sample Sizes

The frequencies of sample sizes in the examined articles are presented in Table  5 . It was observed that in 15 studies, the number of sample sizes was not provided. The intervals for the sample size were not equally separated; instead, they were arranged with intervals of 5, 10, 50, and 100. This choice was made to allow for a more detailed analysis of smaller samples, as smaller intervals can provide a more granular examination of data instead of cumulative amounts. The analysis reveals that the studies primarily prioritized sample groups with 11–15 (f:8) participants, followed by groups of 16–20 (f:4) and 201–250 (f:4). Additionally, it is evident that sample sizes of 6–10, 21–25, 41–50, 50–100, and more than 2000 (f:1) were the least commonly studied.

Data Collection Tools

The frequencies and percentages of data collection tools in the examined articles are presented in Table  6 . The analysis reveals that the studies primarily employed survey or questionnaires (31.6%) and observations (30.5%) as data collection methods, followed by interviews (15.8%), documents (13.7%), tests (4.2%), and field notes (4.2%). Regarding survey/questionnaires, Likert-type scales (f:23) were more commonly employed compared to open-ended questions (f:7). Tests were predominantly used as achievement tests (f:2) and assessments (f:2), representing the least preferred data collection tools. Furthermore, the table illustrates that multiple data collection tools were frequently employed, as the total number of tools (95) is nearly twice the number of studies (56).

Data Analysing Methods

The frequencies and percentages of data analysing methods in the examined articles are presented in Table  7 . The table reveals that the studies predominantly employed descriptive analysis (f:33, 41.25%), followed by inferential statistics (f:16, 20%), descriptive statistics (f:15, 18.75%), content analysis (f:14, 17.5%), and the constant-comparative method (f:2, 2.5%). It is notable that qualitative methods (f:49, 61.25%) were preferred more frequently than quantitative methods (f:31, 38.75%) in the examined studies related to STEM Clubs. Within the qualitative methods, descriptive analysis (f:33) was utilized nearly twice as often as content analysis (f:14), while within the quantitative methods, descriptive statistics (f:15) and inferential statistics (f:16), including t-tests, ANOVA, regression, and other methods, were used with comparable frequency.

The durations of STEM Clubs in the examined studies are presented in Table  8 . Based on the analysis, there are more studies (f:37) that do not state the duration of STEM Clubs than studies (f:19) that do provide information on the durations. Additionally, among the studies that do state the durations, there is no common period of time for STEM Clubs, as they were implemented for varying numbers of weeks and sessions, with session durations ranging from several minutes. Therefore, it can be observed that STEM Clubs were conducted over the course of 3 semesters (academic year and summer), 5 months, 2 to 16 weeks, with session durations ranging from 60 to 120 min. Furthermore, the durations of "3 semesters," "10 weeks with 90-min sessions per week," and "unknown weeks with 60-min sessions per week" were used more than once in the studies.

The content analysis of the findings of the identified examined articles are presented by their frequencies in Table  9 . Although the studies cover a diverse range of topics, the analysis indicates that the results can be broadly classified into three themes, namely, the "development of or increase in certain aspects" (f:68), "design of STEM Clubs" (f:17), and "identification of various aspects" (f:16). Based on the analysis, the findings in the studies are associated with the development of certain aspects such as skills or the increase in specific outcomes like academic achievement. Furthermore, the studies explore the design of STEM Clubs through the description of specific cases, such as sample implementations and challenges. Additionally, the studies focus on the identification of various aspects, such as factors and perceptions.

It is evident from the findings that the studies predominantly yield results related to the development of or increase in certain aspects (f:68). Within this theme, the most commonly observed result is the development of STEM or academic achievement or STEM competency (f:11). This is followed by an increase in STEM major choice or career aspiration (f:9), an increase in engagement or participation in STEM clubs (f:5), the development of identity including STEM, science, engineering, under-representative groups (f:5), the development of interest in STEM (f:4), an increase in enjoyment (f:4), and the development of collaboration, leadership, or communication skills (f:4). Furthermore, it can be observed that there are some results, such as the development of critical thinking, perseverance and the teachers’ profession, that were yielded less frequently (f:1). The results of 16 studies were found with a frequency of 1.

Within the design of STEM Clubs, the sample implementation or design model for different purposes such as the usage of robotic program or students with disabilities (f:7), design principles or ideas for STEM clubs, activities or curriculum (f:4), challenges or factors effecting STEM Clubs success and sustainability (f:3) were presented as a result. Additionally, the comparison was made between in-school and out-of-school learning environments (f:3), highlighting the contradictions of STEM clubs and science classes, as well as the differences in STEM activities and continues-discontinues learning experiences in mathematics. Within the identification of various aspects, the most commonly gathered result was the identification of factors affecting participation or motivation to STEM clubs (f:5). This was followed by the identification of barriers to participation (f:2). The identification of other aspects, such as parents' roles and perspectives on STEM, was comparatively less frequent.

Considering the wide variety of STEM Clubs found in different regions around the world, this study aimed to investigate the current state of research on STEM Clubs. It is not surprising to observe an increase in the number of studies conducted on STEM Clubs over the years. This can be attributed to the overall growth in research on STEM education (Zhan et al., 2022 ), as STEM education often includes activities and after-school programs as integral components (Blanchard et al., 2017 ). Identifying relevant keywords and incorporating them into a search strategy is crucial for conducting a comprehensive and rigorous systematic review (Corrin et al., 2022 ). To gain a broader understanding of keyword usage in the context of STEM Clubs, a word cloud analysis was performed (McNaught & Lam, 2010 ). Additionally, based on the content analysis method, six different categories for keywords were immerged: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). The analysis revealed that the keyword "STEM" was used most frequently in the studies examined. This may be because authors want their studies to be easily found and widely searchable by others, so they use "STEM" as a general term for their studies (Corrin et al., 2022 ). Similarly, the frequent use of keywords like "education" and "learning" from the "core elements of education" category could be attributed to authors' desire to use broad, searchable terms to make their studies more discoverable (Corrin et al., 2022 ). Additionally, it was observed that from the STEM components, only "science" and "engineering" were used as keywords, while "mathematics" and "technology" were not present. This finding aligns with claims in the literature that mathematics is often underemphasized in STEM integration (Fitzallen, 2015 ; Maass et al., 2019 ; Stohlmann, 2018 ). Although the specific term "technology" did not appear in the word cloud, technology-related keywords such as "arduino," "robots," "coding," and "innovative" were present. Furthermore, the analysis revealed that authors preferred to use keywords related to their sample populations, such as "middle (school students)," "elementary (students)," "high school students," or "teachers." Additionally, keywords describing learning experiences, such as "extracurricular," "informal," "afterschool," "out-of-school," "social," "clubs," and "practice" were commonly used. This preference may stem from the fact that STEM clubs are often part of informal learning environments, out-of-school programs, or afterschool activities, and these concepts are closely related to each other (Baran et al., 2016 ; Cooper, 2011 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ). Moreover, the analysis showed that keywords related to psychosocial factors (variables), such as "disabilities," "skills," "interest," "attainment," "enactment," "expectancy-value," "self-efficacy," "engagement," "motivation," "career," "gender," "cognitive," and "identity" were also prevalent. This suggests that the articles investigated the effects of STEM club practices on these psychosocial variables. To sum up, by using these keywords, researchers can gain valuable insights and effectively search for relevant articles related to STEM clubs, enabling them to locate appropriate resources for their research (Corrin et al., 2022 ).

The popularity of case studies as a research design, based on the analysis, can be attributed to the fact that studies on STEM Clubs were conducted in diverse learning environments, highlighting sample implementation designs (Adams et al., 2014 ; Bell et al., 2009 ; Robelen, 2011 ). At this point, case studies offer the opportunity to present practical applications and real-world examples (Hamilton & Corbett-Whittier, 2012 ), which is highly valuable in the context of STEM Clubs. Additionally, the observation that quantitative methods were not as commonly utilized as qualitative methods in studies related to STEM Clubs contrasts with the predominant reliance on quantitative methods in STEM education research (Aslam et al., 2022 ; Irwanto et al., 2022 ; Lin et al., 2019 ). This suggests a lack of quantitative studies specifically focused on STEM Clubs, indicating a need for more research in this area employing quantitative approaches. Therefore, it is important to prioritize and conduct additional quantitative studies to further enhance our understanding of STEM Clubs and their impact. In studies on STEM Club, there is a higher frequency of research involving K-12 students, particularly middle school students, parallel to some studies on literature (Aslam et al., 2022 ), compared to other groups such as pre-service teachers, undergraduate students, teachers, and parents. This can be attributed to the fact that STEM Clubs are designed for K-12 students, and middle school is a crucial period for introducing them to STEM concepts and careers. Middle school students are developmentally ready for hands-on and inquiry-based learning, commonly used in STEM education. Additionally, time constraints, especially for high school students preparing for university, may limit their involvement in extensive STEM activities. Furthermore, STEM Clubs were primarily employed with sample groups ranging from 11–15, 16–20, and 201–250 participants. The preference for 11–20 participants, rather than less than 10, may be attributed to the collaborative nature of STEM activities, which often require a larger team for effective teamwork and group dynamics (Magaji et al., 2022 ). Utilizing small groups as samples can result in the case study research design being the most frequently employed approach due to its compatibility with smaller sample sizes. On the other hand, the inclusion of larger groups (201–250) is suitable for survey studies, as this number can represent the total student population attending STEM Clubs throughout a semester with multiple sessions (Boys & Girls Club of America, 2019 ).

According to studies on STEM Clubs, surveys or questionnaires and observations were predominantly used as data collection methods. This preference can be attributed to the fact that surveys or questionnaires allow researchers to gather data on diverse aspects, including students' attitudes, perceptions, and experiences related to STEM Clubs, facilitating generalization and comparison (McLafferty, 2016 ). Furthermore, observations were frequently employed because they can offer a deeper understanding of the lived experiences and actual practices within STEM Clubs (Baker, 2006 ). Along with data collection tools, descriptive analysis was predominantly utilized in studies on STEM Clubs, with quantitative methods including descriptive statistics and inferential statistics being used to a similar extent. The preference for descriptive analysis may arise from its effectiveness in describing activities, experiences, and practices within STEM Clubs. Given the predominance of case study research in the analysed studies, it is not surprising to observe a high frequency of descriptive statistics in the findings. On the other hand, the extensive use of quantitative analysing methods can be attributed to the need for statistical analysis of surveys and questionnaires (Young, 2015 ). Consequently, future studies on STEM Clubs could benefit from considering the use of tests and field notes as additional data collection tools, along with surveys, observations and interviews. Additionally, the development of tests specifically designed to assess aspects related to STEM could provide valuable insights (Capraro & Corlu, 2013 ; Grangeat et al., 2021 ). Moreover, increasing the utilization of content analysis and constant comparative analysis methods could further enhance the depth and richness of data analysis in STEM Club research (White & Marsh, 2006 ). In the studies on STEM Clubs, the duration and scheduling of the clubs varied considerably. While there was no common period of time for STEM Clubs, they were implemented for different numbers of weeks and sessions, with session durations ranging from several minutes to 60 to 120 min. However, it was observed that STEM Clubs were predominantly conducted over the course of three semesters, including the academic year and summer, or for durations of 2 to 16 weeks. This scheduling pattern can be attributed to the fact that STEM Clubs were often implemented as after-school programs, and they were designed to align with the academic semesters and summer school periods to effectively reach students. Additionally, the number of weeks in these studies may have been arranged according to the duration of academic semesters, although some studies were conducted for less than a semester (Gutierrez, 2016 ). The most common use of multiple sessions with a time range of 60 to 120 min can be attributed to the nature of the activities involved in STEM Clubs. These activities often require more time than regular class hours, and splitting them into separate sessions allows students to effectively concentrate on their work and engage in more in-depth learning experiences (Vennix et al., 2017 ).

The purposes of the studies on STEM Clubs were mostly related to effects of participation in STEM Clubs on various aspects such as attitudes towards STEM disciplines or career paths, STEM major choice/career aspiration, achievement etc., evolution of a sample program for STEM Clubs and its implementation including the development of program/activity, identification of program's challenges and limitations, and implementation of it, followed by the examination of certain aspects such as the experiences and perceptions of students and the factors influencing specific subjects, identification of such as the types of attitudinal effects and non-academic skills, and comparison of in-school and out-school STEM experiences. Therefore, the results of the studies parallel to the purposes were mostly related to development of or increase in certain aspects such as STEM or academic achievement or STEM competency STEM major choice or career aspiration engagement or participation in STEM Clubs, identity, interest in STEM, enjoyment, collaboration, communication skills, critical thinking, the design of STEM Clubs including the sample implementation or design model for different purposes such as the usage of robotic program or students with disabilities, design principles or ideas for STEM clubs or activities, challenges or factors effecting STEM Clubs success and sustainability, and the comparison between in-school and out-of-school learning environments. Also, they are related to the identification of various aspects such as factors affecting participation or motivation to STEM clubs, barriers to participation. At this point, it is evident that these identified categories align with the findings of studies in the literature. These studies claim that after-school programs, such as STEM Clubs, have positive impacts on students' achievement levels (NRC, 2015 ; Kazu & Kurtoglu Yalcin, 2021 ; Shernoff & Vandell, 2007 ), communication, and innovative problem-solving abilities (Mahoney et al., 2007 ), leadership skills (Lipscomb et al., 2017 ), career decision-making (Bybee, 2001 ; Dabney et al., 2012 ; Sahin et al., 2018 ; Tai et al., 2006 ), creativity (Wan et al., 2023 ), 21st-century skills (Hirsch, 2011 ; Zeng et al., 2018 ), interest in STEM professions (Blanchard et al., 2017 ; Chittum et al., 2017 ; Wang et al., 2011 ), and knowledge in STEM fields (Adams et al., 2014 ; Bell et al., 2009 ). Furthermore, it can be inferred that the studies on STEM Clubs paid significant attention to the design descriptions of programs or activities (Nation et al., 2019 ). This may be because there is a need for studies that focus on designing program models for different cases (Calabrese Barton & Tan, 2018 ; Estrada et al., 2016 ). These studies can serve as examples and provide guidance for the development of STEM clubs in various settings. By creating sample models, researchers can contribute to the improvement and expansion of STEM clubs across different environments (Cakir & Guven, 2019 ; Estrada et al., 2016 ).

In conclusion, as the studies on the trends in STEM education (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ), the analysis of prevailing research trends specifically in STEM Clubs, which are implemented in diverse environments with varying methods and purposes, can provide a comprehensive understanding of these clubs as a whole.

It can also serve as a valuable resource for guiding future investigations in this field. By identifying common approaches and identifying gaps in methods and results, a holistic perspective on STEM Clubs can be achieved, leading to a more informed and targeted direction for future research endeavours.

Recommendations

Future research on STEM Clubs should consider the trends identified in the study and address methodological gaps. For instance, there is a lack of research in this area that employs quantitative approaches. Therefore, it is important for future studies to incorporate quantitative methods to enhance the understanding of STEM Clubs and their impact. This includes exploring underrepresented populations, investigating the long-term impacts of STEM Clubs, and examining the effectiveness of specific pedagogical approaches or interventions within these clubs. Researchers should conduct an analysis to identify common approaches used in STEM Clubs across different settings. This analysis can help uncover effective strategies, best practices, and successful models that can be replicated or adapted in various contexts. By undertaking these efforts, researchers can contribute to a more comprehensive understanding of STEM Clubs, leading to advancements in the field of STEM education.

Limitations

It is important to consider the limitations of the study when interpreting its findings. The study's findings are based on the literature selected from two databases, which may introduce biases and limitations. Additionally, the study's findings are constrained by the timeframe of the literature review, and new studies may have emerged since the cut-off date, potentially impacting the representation and generalizability of the research trends identified. Another limitation lies in the construction of categories during the coding process. The coding scheme used may not have fully captured or represented all relevant terms or concepts. Some relevant terms may have been inadequately represented or identified using different words or phrases, potentially introducing limitations to the analysis. While efforts were made to ensure validity and reliability, there is still a possibility of unintended biases or inconsistencies in the categorization process.

Data Availability

The datasets (documents, excel analysis) utilized in this article are available upon request from the corresponding author.

Adams, J. D., Gupta, P., & Cotumaccio, A. (2014). A museum program enhances girls’ STEM interest, motivation and persistence. Afterschool Matters, 12 , 14–20.

Google Scholar  

Afterschool Alliance (2015).  Full STEM ahead: Afterschool programs step up as key partners in STEM education . Retrieved November 2023 from http://www.afterschoolalliance.org/AA3PM/

Aslam, S., Saleem, A., Kennedy, T. J., Kumar, T., Parveen, K., Akram, H., & Zhang, B. (2022). Identifying the research and trends in STEM education in Pakistan: A systematic literature review. SAGE Open, 12 (3), 21582440221118544.

Article   Google Scholar  

Ayers, K. A., Wade-Jaimes, K., Wang, L., Pennella, R. A., & Pounds, S. B. (2020). The St. Jude STEM clubs: An after-school STEM club for upper elementary school students in Memphis, TN. Journal of STEM Outreach, 3 (1), 1–26. https://doi.org/10.15695/jstem/v3i1.13

Bae, S. H. (2018). Concepts, models, and research of extended education. International Journal for Research on Extended Education, 6 (2), 153–165.

Baker, L. (2006). Observation: A complex research method. Library Trends, 55 (1), 171–189.

Baran, E., Bilici, S. C., Mesutoglu, C., & Ocak, C. (2016). Moving STEM beyond schools: Students’ perceptions about an out-of-school STEM education program. International Journal of Education in Mathematics, Science and Technology, 4 (1), 9–19. https://doi.org/10.18404/ijemst.71338

Bell, P., Lewenstein, B., Shouse, A. W., & Feder, M. A. (2009). Learning science in informal environments: People, places and pursuits . National Research Council of the National Academies.

Blanchard, M. R., Hoyle, K. S., & Gutierrez, K. S. (2017). How to start a STEM club. Science Scope, 41 (3), 88–94.

Boys and Girls Club of America (2019). Annual report . Retrieved November 2023 from https://www.bgca.org/about-us/annual-report

Bozkurt, A., Ucar, H., Durak, G., & Idin, S. (2019). The current state of the art in STEM research: A systematic review study. Cypriot Journal of Educational Science,  14 (3), 374–383. https://doi.org/10.18844/cjes.v14i3.3447

Bybee, R. W. (2001). Achieving scientific literacy: Strategies for ensuring that free choice science education complements national formal science education efforts. In J. H. Falk (Ed.), Free choice education: How we learn science outside of school (pp. 44–63). Teachers College Press.

Cakir, N. K., & Guven, G. (2019). Arduino-assisted robotic and coding applications in science teaching: Pulsimeter activity in compliance with the 5E learning model. Science Activities, 56 (2), 42–51.

Calabrese Barton, A., & Tan, E. (2018). A longitudinal study of equity-oriented STEM-rich making among youth from historically marginalized communities. American Educational Research Journal, 55 (4), 761–800.

Capraro, R. M., & Corlu, M. S. (2013). Changing views on assessment for STEM project-based learning. In R. M. Capraro, M. M. Capraro, & J. R. Morgan (Eds.),  STEM project-based learning (pp. 109–118). Brill.

Chapter   Google Scholar  

Casing, P. I., & Casing, L. M. R. (2024). Fostering students’ mathematics achievement through after-school program in the 21st century. Online Submission, 12 (3), 118–122.

Chittum, J. R., Jones, B. D., Akalin, S., & Schram, A. B. (2017). The effects of an afterschool STEM program on students’ motivation and engagement. International Journal of STEM Education, 4 , 1–16.

Chomphuphra, P., Chaipidech, P., & Yuenyong, C. (2019). Trends and research issues of STEM education: A review of academic publications from 2007 to 2017. Journal of Physics: Conference Series, 1340 (1), 012069.

Civil, M. (2007). Building on community knowledge: An avenue to equity in mathematics education. In N. S. Nasir & P. Cobb (Eds.), Improving access to mathematics: Diversity and equity in the classroom (pp. 105–117). Teachers College.

Cooper, S. (2011). An exploration of the potential for mathematical experiences in informal learning environments. Visitor Studies, 14 (1), 48–65. https://doi.org/10.1080/10645578.2011.557628

Corrin, L., Thompson, K., Hwang, G. J., & Lodge, J. M. (2022). The importance of choosing the right keywords for educational technology publications. Australasian Journal of Educational Technology, 38 (2), 1–8.

Dabney, K. P., Tai, R. H., Almarode, J. T., Miller-Friedmann, J. L., Sonnert, G., Sadler, P. M., & Hazari, Z. (2012). Out-of-school time science activities and their association with a career interest in STEM. International Journal of Science Education, Part B, 2 (1), 63–79. https://doi.org/10.1080/21548455.2011.629455

DePaolo, C. A., & Wilkinson, K. (2014). Get your head into the clouds: Using word clouds for analyzing qualitative assessment data. TechTrends, 58 , 38–44. https://doi.org/10.1007/s11528-014-0750-9

Donnelly, M., ažetić, P., Sandoval-Hernandez, A., Kumar, K., & Whewall, S. (2019). An unequal playing field-extra-curricular activities, soft skills and social mobility . Social Mobility Commission.

Durlak, J. A., & Weissberg, R. P. (2007). The impact of after-school programs that promote personal and social skills. Collaborative for Academic, Social, and Emotional Learning (CASEL). Retrieved from www.casel.org

Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62 (1), 107–115.

Estrada, M., Burnett, M., Campbell, A. G., Campbell, P. B., Denetclaw, W. F., Gutiérrez, C. G., Hurtado, S., John, G. H., Matsui, J., McGee, R., Okpodu, C. M, Robinson, T. J., Summers, M. F., Werner-Washburne, M., & Zavala, M. (2016). Improving underrepresented minority student persistence in STEM. CBE—Life Sciences Education , 15 (3), es5.

Fitzallen, N. (2015). STEM Education: What does mathematics have to offer? In M. Marshman, V. Geiger, & A. Bennison (Eds.), Mathematics education in the margins. Proceedings of The 38th Annual Conference of the Mathematics Education Research Group of Australasia (pp. 237–244). MERGA.

Fraenkel, J., Wallen, N., & Hyun, H. (2012). How to design and evaluate research in education (10th ed.). McGraw-Hill Education.

Gay, L. R., Mills, G. E., & Airasian, P. W. (2012). Educational research: competencies for analysis and applications (10th ed.). Pearson.

Grangeat, M., Harrison, C., & Dolin, J. (2021). Exploring assessment in STEM inquiry learning classrooms. International Journal of Science Education, 43 (3), 345–361.

Gutierrez, K. S. (2016). Investigating the climate change beliefs, knowledge, behaviors, and cultural worldviews of rural middle school students and their families during an out-of-school intervention: A mixed-methods study (Publication No. 11320) [Doctoral dissertation, North Carolina State University]. NC State University Libraries.

Hamilton, L., & Corbett-Whittier, C. (2012). Using case study in education research . Sage.

Hein, G. (2009). Learning science in informal environments: People, places, and pursuits. Museums & Social Issues, 4 (1), 113–124.

Hirsch, B. (2011). Learning and development in after-school programs. Phi Delta Kappan, 92 (5), 66–69. https://doi.org/10.1177/2F003172171109200516

Irwanto, I., Saputro, A. D., Widiyanti, W., Ramadhan, M. F., & Lukman, I. R. (2022). Research trends in STEM education from 2011 to 2020: A systematic review of publications in selected journals. International Journal of Interactive Mobile Technologies (iJIM), 16 (5), 19–32.

Kalkan, C., & Eroglu, S. (2017). Designing sample activities based on STEM materials for gifted/talented students in support education rooms. Journal of Gifted Education and Creativity , 4 (2), 36–46. Retrieved November 2023 from  https://dergipark.org.tr/tr/pub/jgedc/issue/38702/449432

Kazu, I. Y., & Kurtoglu Yalcin, C. (2021). The effect of STEM education on academic performance: A meta-analysis study. Turkish Online Journal of Educational Technology-TOJET, 20 (4), 101–116.

Lauer, P. A., Akiba, M., Wilkerson, S. B., Apthorp, H. S., Snow, D., & Martin-Glenn, M. L. (2006). Out-of-school-time programs: A meta-analysis of effects for at-risk students. Review of Educa- Tional Research, 76 (2), 275–313.

Li, Y., Wang, K., Xiao, Y., & Froyd, J. E. (2020). Research and trends in STEM education: A systematic review of journal publications. International Journal of STEM Education, 7 (1), 1–16.

Lin, T. C., Lin, T. J., & Tsai, C. C. (2014). Research trends in science education from 2008 to 2012: A systematic content analysis of publications in selected journals. International Journal of Science Education, 36 (8), 1346–1372.

Lin, T. J., Lin, T. C., Potvin, P., & Tsai, C. C. (2019). Research trends in science education from 2013 to 2017: A systematic content analysis of publications in selected journals. International Journal of Science Education, 41 (3), 367–387.

Lipscomb, S., Haimson, J., Liu, A. Y., Burghardt, J., Johnson, D. R., & Thurlow, M. L. (2017). Preparing for life after high school: The characteristics and experiences of youth in special education. Findings from the National Longitudinal Transition Study 2012. Volume 2: Comparisons across disability groups: Full report (Report No. NCEE 2017–4018). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance.

Little, P., Wimer, C., & Weiss, H. B. (2008). After school programs in the 21st century: Their poten- tial and what it takes to achieve it. Issues and Opportunities in out-of-School Time Evaluation, 10 , 1–12.

Maass, K., Geiger, V., Ariza, M. R., & Goos, M. (2019). The role of mathematics in interdisciplinary STEM education. ZDM, 51 , 869–884. https://doi.org/10.1007/s11858-019-01100-5

Magaji, A., Ade-Ojo, G., & Bijlhout, D. (2022). The impact of after school science club on the learning progress and attainment of students. International Journal of Instruction, 15 (3), 171–190.

Mahoney, J. L., Parente, M. E., & Lord, H. (2007). After-school program engagement: Links to child competence and program quality and content. The Elementary School Journal, 107 (4), 385–404.

Martín-Páez, T., Aguilera, D., Perales-Palacios, F. J., & Vílchez-González, J. M. (2019). What are we talking about when we talk about STEM education? A Review of Literature. Science Education, 103 (4), 799–822.

McLafferty, S. (2016). Conducting questionnaire surveys. Key Methods in Geography, 3 , 129–142.

McNaught, C., & Lam, P. (2010). Using Wordle as a supplementary research tool. Qualitative Report, 15 (3), 630–643.

Merrill, C., & Daugherty, J. (2010). STEM education and leadership: A mathematics and science partnership approach. Journal of Technology Education, 21 (2), 21–34.

Nation, J. M., Harlow, D., Arya, D. J., & Longtin, M. (2019). Being and becoming scientists: Design-based STEM programming for girls. Afterschool Matters, 29 , 36–44.

National Research Council, Division of Behavioral, Board on Science Education, & Committee on Successful Out-of-School STEM Learning (2015). Identifying and supporting productive STEM programs in out-of-school settings . National Academies Press.

Noris, M., Saputro, S., & Ulimaz, A. (2023). STEM research trends from 2013 to 2022: A systematic literature review. International Journal of Technology in Education (IJTE), 6 (2), 224–237. https://doi.org/10.46328/ijte.390

Pastchal-Temple, A. S. (2012). The effect of regular participation in an after-school program on student achievement, attendance, and behavior (Publication No. 4368) [Doctoral dissertation, Mississippi State University]. Mississippi State University Libraries.

Resnick, L. B. (1987). Education and learning to think . National Academy Press.

Robelen, E. (2011). New STEM schools target underrepresented groups. Education Week, 31 (1), 18–19.

Sahin, A., Ekmekci, A., & Waxman, H. C. (2018). Collective effects of individual, behavioral, and contextual factors on high school students’ future STEM career plans. International Journal of Science and Mathematics Education, 16 , 69–89.

Schweingruber, H., Pearson, G., & Honey, M. (Eds.). (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research . National Academies Press.

Shernoff, D. J., & Vandell, D. L. (2007). Engagement in after school program activities: Quality of experience from the perspective of participants. Journal of Youth Adolescence, 36 , 891–903.

Stemler, S. (2000). An overview of content analysis. Practical Assessment, Research & Evaluation, 7 (17), 1–6. https://doi.org/10.7275/z6fm-2e34

Stohlmann, M. (2018). A vision for future work to focus on the “m” in integrated STEM. School Science and Mathematics, 118 (7), 310–319. https://doi.org/10.1111/ssm.12301

Sozbilir, M., Kutu, H., & Yasar, M. D. (2012). Science education research in Turkey: A content analysis of selected features of papers published. In J. Dillon & D. Jorde (Eds.), The world of science education: Handbook of research in Europe (pp. 1–35). Sense publishers.

Suri, H., & Clarke, D. (2009). Advancements in research systhesis methods: From a methodologically inclusive perspective. Review of Educational Research, 79 (1), 395–430.

Tai, R. H., Qi Liu, C., Maltese, A. V., & Fan, X. (2006). Planning early for careers in science. Science, 312 (5777), 1143–1144.

Vennix, J., Den Brok, P., & Taconis, R. (2017). Perceptions of STEM-based outreach learning activities in secondary education. Learning Environments Research, 20 , 21–46.

Wan, Z. H., So, W. M. W., & Zhan, Y. (2023). Investigating the effects of design-based STEM learning on primary students’ STEM creativity and epistemic beliefs. International Journal of Science and Mathematics Education, 21 (Suppl. 1), 87–108.

Wang, H. H., Moore, T. J., Roehrig, G. H., & Park, M. S. (2011). STEM integration: Teacher perceptions and practice. Journal of Pre-College Engineering Education Research, 1 (2), 1–13.

White, M. D., & Marsh, E. E. (2006). Content analysis: A flexible methodology. Library Trends, 55 (1), 22–45.

Young, T. J. (2015). Questionnaires and surveys. In Z. Hua (Ed.), Research methods in intercultural communication: A practical guide (pp. 163–180). John Wiley & Sons. https://doi.org/10.1002/9781119166283.ch11

Zeng, Z., Yao, J., Gu, H., & Przybylski, R. (2018). A meta-analysis on the effects of STEM education on students’ abilities. Science Insights Education Frontiers, 1 (1), 3–16.

Zhan, Z., Shen, W., Xu, Z., Niu, S., & You, G. (2022). A bibliometric analysis of the global landscape on STEM education (2004–2021): Towards global distribution, subject integration, and research trends. Asia Pacific Journal of Innovation and Entrepreneurship, 16 (2), 171–203.

Download references

Open access funding provided by the Scientific and Technological Research Council of Türkiye (TÜBİTAK). There was no external funding received for the research conducted in this article.

Author information

Authors and affiliations.

Department of Industrial Engineering, Istanbul Aydin University, Istanbul, Turkey

Rabia Nur Öndeş

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Rabia Nur Öndeş .

Ethics declarations

Ethical approval and consent.

This is a review study and no ethical approval is required.

Competing Interests

The authors have no competing interests to declare that are relevant to the content of this article.

No potential conflict of interest was reported by the author.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Öndeş, R.N. Research Trends in STEM Clubs: A Content Analysis. Int J of Sci and Math Educ (2024). https://doi.org/10.1007/s10763-024-10477-z

Download citation

Received : 19 January 2024

Accepted : 10 June 2024

Published : 25 June 2024

DOI : https://doi.org/10.1007/s10763-024-10477-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Research Trends
• Content Analysis
• After-school Program
• Extracurricular Activities
• Find a journal
• Publish with us
• Track your research

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

The molecular mechanisms and therapeutic potential of cranberry, d-mannose, and flavonoids against infectious diseases: the example of urinary tract infections.

1. Introduction

2. the need for and examples of alternative treatments in the treatment of infectious diseases, 3. literature search methodology, 4. the potential of flavonoids in the management of infectious diseases and their underlying molecular mechanisms, 4.1. the antibacterial impact of flavonoids and their underlying mechanism, 4.2. the synergistic effect of flavonoids with antibiotics in the fight against antimicrobial resistance, 4.3. clinical trials of flavonoids in infectious diseases, 4.4. limitations and bioavailability of flavonoids, 5. natural products for the management of urinary tract infections, 5.1. cranberry products, 5.2. d-mannose, 6. natural compounds as antibiotic-sparing agents in the era of amr, 7. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Bennett, J.E.; Dolin, E.; Blaser, M.J. Mandell, Douglas, and Bennett’s Principles and Practice of Infectious Diseases , 9th ed.; Elsevier: Philadelphia, PA, USA, 2019. [ Google Scholar ]
• Magiorakos, A.-P.; Srinivasan, A.; Carey, R.B.; Carmeli, Y.; Falagas, M.E.; Giske, C.G.; Harbarth, S.; Hindler, J.F.; Kahlmeter, G.; Olsson-Liljequist, B.; et al. Multidrug-Resistant, Extensively Drug-Resistant and Pandrug-Resistant Bacteria: An International Expert Proposal for Interim Standard Definitions for Acquired Resistance. Clin. Microbiol. Infect. Off. Publ. Eur. Soc. Clin. Microbiol. Infect. Dis. 2012 , 18 , 268–281. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Antimicrobial Resistance Collaborators. Global Burden of Bacterial Antimicrobial Resistance in 2019: A Systematic Analysis. Lancet 2022 , 399 , 629–655. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ioannou, P.; Baliou, S.; Samonis, G. Bacteriophages in Infectious Diseases and Beyond—A Narrative Review. Antibiotics 2023 , 12 , 1012. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ioannou, P.; Baliou, S.; Kofteridis, D.P. Antimicrobial Peptides in Infectious Diseases and Beyond—A Narrative Review. Life 2023 , 13 , 1651. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ioannou, P.; Baliou, S.; Samonis, G. Nanotechnology in the Diagnosis and Treatment of Antibiotic-Resistant Infections. Antibiotics 2024 , 13 , 121. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Konesan, J.; Liu, L.; Mansfield, K.J. The Clinical Trial Outcomes of Cranberry, D-Mannose and NSAIDs in the Prevention or Management of Uncomplicated Urinary Tract Infections in Women: A Systematic Review. Pathogens 2022 , 11 , 1471. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Farha, M.A.; Brown, E.D. Strategies for Target Identification of Antimicrobial Natural Products. Nat. Prod. Rep. 2016 , 33 , 668–680. [ Google Scholar ] [ CrossRef ]
• Kwok, M.; McGeorge, S.; Mayer-Coverdale, J.; Graves, B.; Paterson, D.L.; Harris, P.N.A.; Esler, R.; Dowling, C.; Britton, S.; Roberts, M.J. Guideline of Guidelines: Management of Recurrent Urinary Tract Infections in Women. BJU Int. 2022 , 130 (Suppl. S3), 11–22. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Cerini, P.; Meduri, F.R.; Tomassetti, F.; Polidori, I.; Brugneti, M.; Nicolai, E.; Bernardini, S.; Pieri, M.; Broccolo, F. Trends in Antibiotic Resistance of Nosocomial and Community-Acquired Infections in Italy. Antibiotics 2023 , 12 , 651. [ Google Scholar ] [ CrossRef ]
• Salam, M.A.; Al-Amin, M.Y.; Salam, M.T.; Pawar, J.S.; Akhter, N.; Rabaan, A.A.; Alqumber, M.A.A. Antimicrobial Resistance: A Growing Serious Threat for Global Public Health. Healthcare 2023 , 11 , 1946. [ Google Scholar ] [ CrossRef ]
• O’Neill, J. Review on Antimicrobial Resistance. Tackling Drug-Resistant Infections Globally. 2016. Available online: https://amr-review.org/sites/default/files/160525_Final%20paper_with%20cover.pdf (accessed on 29 May 2024).
• Cosgrove, S.E.; Sakoulas, G.; Perencevich, E.N.; Schwaber, M.J.; Karchmer, A.W.; Carmeli, Y. Comparison of Mortality Associated with Methicillin-Resistant and Methicillin-Susceptible Staphylococcus Aureus Bacteremia: A Meta-Analysis. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2003 , 36 , 53–59. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Seung, K.J.; Keshavjee, S.; Rich, M.L. Multidrug-Resistant Tuberculosis and Extensively Drug-Resistant Tuberculosis. Cold Spring Harb. Perspect. Med. 2015 , 5 , a017863. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bryce, A.; Hay, A.D.; Lane, I.F.; Thornton, H.V.; Wootton, M.; Costelloe, C. Global Prevalence of Antibiotic Resistance in Paediatric Urinary Tract Infections Caused by Escherichia Coli and Association with Routine Use of Antibiotics in Primary Care: Systematic Review and Meta-Analysis. BMJ 2016 , 352 , i939. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Johnson, J.R.; Johnston, B.; Clabots, C.; Kuskowski, M.A.; Castanheira, M. Escherichia Coli Sequence Type ST131 as the Major Cause of Serious Multidrug-Resistant E. Coli Infections in the United States. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2010 , 51 , 286–294. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ioannou, P.; Plexousaki, M.; Dimogerontas, K.; Aftzi, V.; Drougkaki, M.; Konidaki, M.; Paschalidis, K.; Maraki, S.; Kofteridis, D.P. Characteristics of Urinary Tract Infections in Older Patients in a Tertiary Hospital in Greece. Geriatr. Gerontol. Int. 2020 , 20 , 1228–1233. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Dejonckheere, Y.; Desmet, S.; Knops, N. A Study of the 20-Year Evolution of Antimicrobial Resistance Patterns of Pediatric Urinary Tract Infections in a Single Center. Eur. J. Pediatr. 2022 , 181 , 3271–3281. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Sanchez, G.V.; Baird, A.M.G.; Karlowsky, J.A.; Master, R.N.; Bordon, J.M. Nitrofurantoin Retains Antimicrobial Activity against Multidrug-Resistant Urinary Escherichia Coli from US Outpatients. J. Antimicrob. Chemother. 2014 , 69 , 3259–3262. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Poudel, A.N.; Zhu, S.; Cooper, N.; Little, P.; Tarrant, C.; Hickman, M.; Yao, G. The Economic Burden of Antibiotic Resistance: A Systematic Review and Meta-Analysis. PLoS ONE 2023 , 18 , e0285170. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Meek, R.W.; Vyas, H.; Piddock, L.J.V. Nonmedical Uses of Antibiotics: Time to Restrict Their Use? PLoS Biol. 2015 , 13 , e1002266. [ Google Scholar ] [ CrossRef ]
• Sihra, N.; Goodman, A.; Zakri, R.; Sahai, A.; Malde, S. Nonantibiotic Prevention and Management of Recurrent Urinary Tract Infection. Nat. Rev. Urol. 2018 , 15 , 750–776. [ Google Scholar ] [ CrossRef ]
• Bishop, E.J.; Tiruvoipati, R. Management of Clostridioides Difficile Infection in Adults and Challenges in Clinical Practice: Review and Comparison of Current IDSA/SHEA, ESCMID and ASID Guidelines. J. Antimicrob. Chemother. 2022 , 78 , 21–30. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lou, J.; Cui, S.; Huang, N.; Jin, G.; Chen, C.; Fan, Y.; Zhang, C.; Li, J. Efficacy of Probiotics or Synbiotics in Critically Ill Patients: A Systematic Review and Meta-Analysis. Clin. Nutr. ESPEN 2024 , 59 , 48–62. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Yenet, A.; Nibret, G.; Tegegne, B.A. Challenges to the Availability and Affordability of Essential Medicines in African Countries: A Scoping Review. Clin. Outcomes Res. 2023 , 15 , 443–458. [ Google Scholar ] [ CrossRef ]
• Kováč, J.; Slobodníková, L.; Trajčíková, E.; Rendeková, K.; Mučaji, P.; Sychrová, A.; Bittner Fialová, S. Therapeutic Potential of Flavonoids and Tannins in Management of Oral Infectious Diseases—A Review. Molecules 2022 , 28 , 158. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Górniak, I.; Bartoszewski, R.; Króliczewski, J. Comprehensive Review of Antimicrobial Activities of Plant Flavonoids. Phytochem. Rev. 2019 , 18 , 241–272. [ Google Scholar ] [ CrossRef ]
• Fernández-Rojas, B.; Gutiérrez-Venegas, G. Flavonoids Exert Multiple Periodontic Benefits Including Anti-Inflammatory, Periodontal Ligament-Supporting, and Alveolar Bone-Preserving Effects. Life Sci. 2018 , 209 , 435–454. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Justesen, U.; Knuthsen, P. Composition of Flavonoids in Fresh Herbs and Calculation of Flavonoid Intake by Use of Herbs in Traditional Danish Dishes. Food Chem. 2001 , 73 , 245–250. [ Google Scholar ] [ CrossRef ]
• Roy, A.; Khan, A.; Ahmad, I.; Alghamdi, S.; Rajab, B.S.; Babalghith, A.O.; Alshahrani, M.Y.; Islam, S.; Islam, M.R. Flavonoids a Bioactive Compound from Medicinal Plants and Its Therapeutic Applications. BioMed Res. Int. 2022 , 2022 , 5445291. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Chagas, M.D.S.S.; Behrens, M.D.; Moragas-Tellis, C.J.; Penedo, G.X.M.; Silva, A.R.; Gonçalves-de-Albuquerque, C.F. Flavonols and Flavones as Potential Anti-Inflammatory, Antioxidant, and Antibacterial Compounds. Oxid. Med. Cell. Longev. 2022 , 2022 , 9966750. [ Google Scholar ] [ CrossRef ]
• Wittayathanarattana, T.; Wanichananan, P.; Supaibulwatana, K.; Goto, E. Enhancement of Bioactive Compounds in Baby Leaf Amaranthus Tricolor L. Using Short-Term Application of UV-B Irradiation. Plant Physiol. Biochem. 2022 , 182 , 202–215. [ Google Scholar ] [ CrossRef ]
• Ferreyra, M.L.F.; Serra, P.; Casati, P. Recent Advances on the Roles of Flavonoids as Plant Protective Molecules after UV and High Light Exposure. Physiol. Plant. 2021 , 173 , 736–749. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Dias, M.C.; Pinto, D.C.G.A.; Silva, A.M.S. Plant Flavonoids: Chemical Characteristics and Biological Activity. Mol. Basel Switz. 2021 , 26 , 5377. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Miean, K.H.; Mohamed, S. Flavonoid (Myricetin, Quercetin, Kaempferol, Luteolin, and Apigenin) Content of Edible Tropical Plants. J. Agric. Food Chem. 2001 , 49 , 3106–3112. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hytti, M.; Piippo, N.; Korhonen, E.; Honkakoski, P.; Kaarniranta, K.; Kauppinen, A. Fisetin and Luteolin Protect Human Retinal Pigment Epithelial Cells from Oxidative Stress-Induced Cell Death and Regulate Inflammation. Sci. Rep. 2015 , 5 , 17645. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Franza, L.; Carusi, V.; Nucera, E.; Pandolfi, F. Luteolin, Inflammation and Cancer: Special Emphasis on Gut Microbiota. BioFactors 2021 , 47 , 181–189. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Jan, A.T.; Kamli, M.R.; Murtaza, I.; Singh, J.B.; Ali, A.; Haq, Q.M.R. Dietary Flavonoid Quercetin and Associated Health Benefits—An Overview. Food Rev. Int. 2010 , 26 , 302–317. [ Google Scholar ] [ CrossRef ]
• Shu, Y.; Liu, Y.; Li, L.; Feng, J.; Lou, B.; Zhou, X.; Wu, H. Antibacterial Activity of Quercetin on Oral Infectious Pathogens. Afr. J. Microbiol. Res. 2011 , 5 , 5358–5361. [ Google Scholar ] [ CrossRef ]
• Shalini, V.; Bhaskar, S.; Kumar, K.S.; Mohanlal, S.; Jayalekshmy, A.; Helen, A. Molecular Mechanisms of Anti-Inflammatory Action of the Flavonoid, Tricin from Njavara Rice ( Oryza sativa L.) in Human Peripheral Blood Mononuclear Cells: Possible Role in the Inflammatory Signaling. Int. Immunopharmacol. 2012 , 14 , 32–38. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Abdallah, H.M.; Almowallad, F.M.; Esmat, A.; Shehata, I.A.; Abdel-Sattar, E.A. Anti-Inflammatory Activity of Flavonoids from Chrozophora tinctoria . Phytochem. Lett. 2015 , 13 , 74–80. [ Google Scholar ] [ CrossRef ]
• Fu, Y.; Chen, J.; Li, Y.-J.; Zheng, Y.-F.; Li, P. Antioxidant and Anti-Inflammatory Activities of Six Flavonoids Separated from Licorice. Food Chem. 2013 , 141 , 1063–1071. [ Google Scholar ] [ CrossRef ]
• Das, T.; Mukherjee, S.; Chaudhuri, K. Effect of Quercetin on Vibrio Cholerae Induced Nuclear Factor-κB Activation and Interleukin-8 Expression in Intestinal Epithelial Cells. Microbes Infect. 2012 , 14 , 690–695. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Li, B.Q.; Fu, T.; Dongyan, Y.; Mikovits, J.A.; Ruscetti, F.W.; Wang, J.M. Flavonoid Baicalin Inhibits HIV-1 Infection at the Level of Viral Entry. Biochem. Biophys. Res. Commun. 2000 , 276 , 534–538. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ono, K.; Nakane, H.; Fukushima, M.; Chermann, J.C.; Barré-Sinoussi, F. Inhibition of Reverse Transcriptase Activity by a Flavonoid Compound, 5,6,7-Trihydroxyflavone. Biochem. Biophys. Res. Commun. 1989 , 160 , 982–987. [ Google Scholar ] [ CrossRef ]
• Khazeei Tabari, M.A.; Iranpanah, A.; Bahramsoltani, R.; Rahimi, R. Flavonoids as Promising Antiviral Agents against SARS-CoV-2 Infection: A Mechanistic Review. Molecules 2021 , 26 , 3900. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Liu, A.-L.; Wang, H.-D.; Lee, S.M.; Wang, Y.-T.; Du, G.-H. Structure-Activity Relationship of Flavonoids as Influenza Virus Neuraminidase Inhibitors and Their in Vitro Anti-Viral Activities. Bioorg. Med. Chem. 2008 , 16 , 7141–7147. [ Google Scholar ] [ CrossRef ]
• Clementi, N.; Scagnolari, C.; D’Amore, A.; Palombi, F.; Criscuolo, E.; Frasca, F.; Pierangeli, A.; Mancini, N.; Antonelli, G.; Clementi, M.; et al. Naringenin Is a Powerful Inhibitor of SARS-CoV-2 Infection in Vitro. Pharmacol. Res. 2021 , 163 , 105255. [ Google Scholar ] [ CrossRef ]
• Martínez-Castillo, M.; Pacheco-Yepez, J.; Flores-Huerta, N.; Guzmán-Téllez, P.; Jarillo-Luna, R.A.; Cárdenas-Jaramillo, L.M.; Campos-Rodríguez, R.; Shibayama, M. Flavonoids as a Natural Treatment Against Entamoeba Histolytica. Front. Cell. Infect. Microbiol. 2018 , 8 , 209. [ Google Scholar ] [ CrossRef ]
• Dsouza, D.; Nanjaiah, L. Antibacterial Activity of 3,3′,4′-Trihydroxyflavone from Justicia wynaadensis against Diabetic Wound and Urinary Tract Infection. Braz. J. Microbiol. Publ. Braz. Soc. Microbiol. 2018 , 49 , 152–161. [ Google Scholar ] [ CrossRef ]
• Somerville, V.S.; Braakhuis, A.J.; Hopkins, W.G. Effect of Flavonoids on Upper Respiratory Tract Infections and Immune Function: A Systematic Review and Meta-Analysis. Adv. Nutr. 2016 , 7 , 488–497. [ Google Scholar ] [ CrossRef ]
• Xie, Y.; Yang, W.; Tang, F.; Chen, X.; Ren, L. Antibacterial Activities of Flavonoids: Structure-Activity Relationship and Mechanism. Curr. Med. Chem. 2014 , 22 , 132–149. [ Google Scholar ] [ CrossRef ]
• Cascioferro, S.; Totsika, M.; Schillaci, D. Sortase A: An Ideal Target for Anti-Virulence Drug Development. Microb. Pathog. 2014 , 77 , 105–112. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Tsuchiya, H. Membrane Interactions of Phytochemicals as Their Molecular Mechanism Applicable to the Discovery of Drug Leads from Plants. Molecules 2015 , 20 , 18923–18966. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Reygaert, W.C. The Antimicrobial Possibilities of Green Tea. Front. Microbiol. 2014 , 5 , 434. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Sanver, D.; Murray, B.S.; Sadeghpour, A.; Rappolt, M.; Nelson, A.L. Experimental Modeling of Flavonoid-Biomembrane Interactions. Langmuir ACS J. Surf. Colloids 2016 , 32 , 13234–13243. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fathima, A.; Rao, J.R. Selective Toxicity of Catechin-a Natural Flavonoid towards Bacteria. Appl. Microbiol. Biotechnol. 2016 , 100 , 6395–6402. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Nagle, D.G.; Ferreira, D.; Zhou, Y.-D. Epigallocatechin-3-Gallate (EGCG): Chemical and Biomedical Perspectives. Phytochemistry 2006 , 67 , 1849–1855. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kong, M.; Xie, K.; Lv, M.; Li, J.; Yao, J.; Yan, K.; Wu, X.; Xu, Y.; Ye, D. Anti-Inflammatory Phytochemicals for the Treatment of Diabetes and Its Complications: Lessons Learned and Future Promise. Biomed. Pharmacother. Biomed. Pharmacother. 2021 , 133 , 110975. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ravindranath, M.H.; Saravanan, T.S.; Monteclaro, C.C.; Presser, N.; Ye, X.; Selvan, S.R.; Brosman, S. Epicatechins Purified from Green Tea (Camellia Sinensis) Differentially Suppress Growth of Gender-Dependent Human Cancer Cell Lines. Evid. Based Complement. Altern. Med. ECAM 2006 , 3 , 237–247. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ikigai, H.; Nakae, T.; Hara, Y.; Shimamura, T. Bactericidal Catechins Damage the Lipid Bilayer. Biochim. Biophys. Acta 1993 , 1147 , 132–136. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Budzyńska, A.; Rózalski, M.; Karolczak, W.; Wieckowska-Szakiel, M.; Sadowska, B.; Rózalska, B. Synthetic 3-Arylideneflavanones as Inhibitors of the Initial Stages of Biofilm Formation by Staphylococcus Aureus and Enterococcus Faecalis. Z. Naturforschung C J. Biosci. 2011 , 66 , 104–114. [ Google Scholar ] [ CrossRef ]
• Cushnie, T.P.T.; Lamb, A.J. Antimicrobial Activity of Flavonoids. Int. J. Antimicrob. Agents 2005 , 26 , 343–356. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Yan, Y.; Xia, X.; Fatima, A.; Zhang, L.; Yuan, G.; Lian, F.; Wang, Y. Antibacterial Activity and Mechanisms of Plant Flavonoids against Gram-Negative Bacteria Based on the Antibacterial Statistical Model. Pharmaceuticals 2024 , 17 , 292. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Haraguchi, H.; Tanimoto, K.; Tamura, Y.; Mizutani, K.; Kinoshita, T. Mode of Antibacterial Action of Retrochalcones from Glycyrrhiza Inflata. Phytochemistry 1998 , 48 , 125–129. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gledhill, J.R.; Montgomery, M.G.; Leslie, A.G.W.; Walker, J.E. Mechanism of Inhibition of Bovine F1-ATPase by Resveratrol and Related Polyphenols. Proc. Natl. Acad. Sci. USA 2007 , 104 , 13632–13637. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Chinnam, N.; Dadi, P.K.; Sabri, S.A.; Ahmad, M.; Kabir, M.A.; Ahmad, Z. Dietary Bioflavonoids Inhibit Escherichia Coli ATP Synthase in a Differential Manner. Int. J. Biol. Macromol. 2010 , 46 , 478–486. [ Google Scholar ] [ CrossRef ]
• Plaper, A.; Golob, M.; Hafner, I.; Oblak, M.; Solmajer, T.; Jerala, R. Characterization of Quercetin Binding Site on DNA Gyrase. Biochem. Biophys. Res. Commun. 2003 , 306 , 530–536. [ Google Scholar ] [ CrossRef ]
• Wu, D.; Kong, Y.; Han, C.; Chen, J.; Hu, L.; Jiang, H.; Shen, X. D-Alanine:D-Alanine Ligase as a New Target for the Flavonoids Quercetin and Apigenin. Int. J. Antimicrob. Agents 2008 , 32 , 421–426. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Breidenstein, E.B.M.; de la Fuente-Núñez, C.; Hancock, R.E.W. Pseudomonas Aeruginosa: All Roads Lead to Resistance. Trends Microbiol. 2011 , 19 , 419–426. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Sarbu, L.G.; Bahrin, L.G.; Babii, C.; Stefan, M.; Birsa, M.L. Synthetic Flavonoids with Antimicrobial Activity: A Review. J. Appl. Microbiol. 2019 , 127 , 1282–1290. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Wrońska, N.; Szlaur, M.; Zawadzka, K.; Lisowska, K. The Synergistic Effect of Triterpenoids and Flavonoids-New Approaches for Treating Bacterial Infections? Molecules 2022 , 27 , 847. [ Google Scholar ] [ CrossRef ]
• Gregoire, S.; Singh, A.P.; Vorsa, N.; Koo, H. Influence of Cranberry Phenolics on Glucan Synthesis by Glucosyltransferases and Streptococcus Mutans Acidogenicity. J. Appl. Microbiol. 2007 , 103 , 1960–1968. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gutiérrez-Venegas, G.; Gómez-Mora, J.A.; Meraz-Rodríguez, M.A.; Flores-Sánchez, M.A.; Ortiz-Miranda, L.F. Effect of Flavonoids on Antimicrobial Activity of Microorganisms Present in Dental Plaque. Heliyon 2019 , 5 , e03013. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Srivastava, D.; Yadav, A.; Naqvi, S.; Awasthi, H.; Fatima, Z. Efficacy of Flavonoids in Combating Fluconazole Resistant Oral Candidiasis. Curr. Pharm. Des. 2022 , 28 , 1703–1713. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Smiljković, M.; Kostić, M.; Stojković, D.; Glamočlija, J.; Soković, M. Could Flavonoids Compete with Synthetic Azoles in Diminishing Candida Albicans Infections? A Comparative Review Based on In Vitro Studies. Curr. Med. Chem. 2019 , 26 , 2536–2554. [ Google Scholar ] [ CrossRef ]
• Srinivas, N.R. Combination of Flavonoids with Azole Drugs for Fungal Infections: Key Pharmacokinetic Challenges. Future Microbiol. 2019 , 14 , 733–738. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• da Silva, C.R.; de Andrade Neto, J.B.; de Sousa Campos, R.; Figueiredo, N.S.; Sampaio, L.S.; Magalhães, H.I.F.; Cavalcanti, B.C.; Gaspar, D.M.; de Andrade, G.M.; Lima, I.S.P.; et al. Synergistic Effect of the Flavonoid Catechin, Quercetin, or Epigallocatechin Gallate with Fluconazole Induces Apoptosis in Candida Tropicalis Resistant to Fluconazole. Antimicrob. Agents Chemother. 2014 , 58 , 1468–1478. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kohanski, M.A.; Dwyer, D.J.; Hayete, B.; Lawrence, C.A.; Collins, J.J. A Common Mechanism of Cellular Death Induced by Bactericidal Antibiotics. Cell 2007 , 130 , 797–810. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Palacios, P.; Gutkind, G.; Rondina, R.V.; de Torres, R.; Coussio, J.D. Genus Baccharis. II. Antimicrobial Activity of B. Crispa and B. Notosergila. Planta Med. 1983 , 49 , 128. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Oksüz, S.; Ayyildiz, H.; Johansson, C. 6-Methoxylated and C-Glycosyl Flavonoids from Centaurea Species. J. Nat. Prod. 1984 , 47 , 902–903. [ Google Scholar ] [ CrossRef ]
• Basile, A.; Giordano, S.; López-Sáez, J.A.; Cobianchi, R.C. Antibacterial Activity of Pure Flavonoids Isolated from Mosses. Phytochemistry 1999 , 52 , 1479–1482. [ Google Scholar ] [ CrossRef ]
• Basile, A.; Sorbo, S.; Giordano, S.; Ricciardi, L.; Ferrara, S.; Montesano, D.; Castaldo Cobianchi, R.; Vuotto, M.L.; Ferrara, L. Antibacterial and Allelopathic Activity of Extract from Castanea Sativa Leaves. Fitoterapia 2000 , 71 (Suppl. 1), S110–S116. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Basile, A.; Conte, B.; Rigano, D.; Senatore, F.; Sorbo, S. Antibacterial and Antifungal Properties of Acetonic Extract of Feijoa sellowiana Fruits and Its Effect on Helicobacter pylori Growth. J. Med. Food 2010 , 13 , 189–195. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bakar, N.S.; Zin, N.M.; Basri, D.F. Synergy of Flavone with Vancomycin and Oxacillin against Vancomycin-Intermediate Staphyloccus aureus . Pak. J. Pharm. Sci. 2012 , 25 , 633–638. [ Google Scholar ]
• Akilandeswari, K.; Ruckmani, K. Synergistic Antibacterial Effect of Apigenin with β-Lactam Antibiotics and Modulation of Bacterial Resistance by a Possible Membrane Effect against Methicillin Resistant Staphylococcus aureus . Cell. Mol. Biol. 2016 , 62 , 74–82. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Usman Amin, M.; Khurram, M.; Khan, T.A.; Faidah, H.S.; Ullah Shah, Z.; Ur Rahman, S.; Haseeb, A.; Ilyas, M.; Ullah, N.; Umar Khayam, S.M.; et al. Effects of Luteolin and Quercetin in Combination with Some Conventional Antibiotics against Methicillin-Resistant Staphylococcus aureus . Int. J. Mol. Sci. 2016 , 17 , 1947. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lopes, L.A.A.; Dos Santos Rodrigues, J.B.; Magnani, M.; de Souza, E.L.; de Siqueira-Júnior, J.P. Inhibitory Effects of Flavonoids on Biofilm Formation by Staphylococcus aureus That Overexpresses Efflux Protein Genes. Microb. Pathog. 2017 , 107 , 193–197. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Pepeljnjak, S.; Kosalec, I. Galangin Expresses Bactericidal Activity against Multiple-Resistant Bacteria: MRSA, Enterococcus Spp. and Pseudomonas Aeruginosa. FEMS Microbiol. Lett. 2004 , 240 , 111–116. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Siriwong, S.; Thumanu, K.; Hengpratom, T.; Eumkeb, G. Synergy and Mode of Action of Ceftazidime plus Quercetin or Luteolin on Streptococcus pyogenes . Evid. Based Complement. Altern. Med. 2015 , 2015 , 759459. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Eumkeb, G.; Sakdarat, S.; Siriwong, S. Reversing β-Lactam Antibiotic Resistance of Staphylococcus Aureus with Galangin from Alpinia Officinarum Hance and Synergism with Ceftazidime. Phytomedicine Int. J. Phytother. Phytopharm. 2010 , 18 , 40–45. [ Google Scholar ] [ CrossRef ]
• Wang, S.-Y.; Sun, Z.-L.; Liu, T.; Gibbons, S.; Zhang, W.-J.; Qing, M. Flavonoids from Sophora moorcroftiana and Their Synergistic Antibacterial Effects on MRSA. Phytother. Res. 2014 , 28 , 1071–1076. [ Google Scholar ] [ CrossRef ]
• Navrátilová, A.; Nešuta, O.; Vančatová, I.; Čížek, A.; Varela, M.R.E.; López-Abán, J.; Villa-Pulgarin, J.A.; Mollinedo, F.; Muro, A.; Žemličková, H.; et al. C-Geranylated Flavonoids from Paulownia Tomentosa Fruits with Antimicrobial Potential and Synergistic Activity with Antibiotics. Pharm. Biol. 2016 , 54 , 1398–1407. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Yao, J.; Zhang, Y.; Wang, X.-Z.; Zhao, J.; Yang, Z.-J.; Lin, Y.-P.; Sun, L.; Lu, Q.-Y.; Fan, G.-J. Flavonoids for Treating Viral Acute Respiratory Tract Infections: A Systematic Review and Meta-Analysis of 30 Randomized Controlled Trials. Front. Public Health 2022 , 10 , 814669. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• El-Shiekh, R.A.; Elhemely, M.A.; Naguib, I.A.; Bukhari, S.I.; Elshimy, R. Luteolin 4′-Neohesperidoside Inhibits Clinically Isolated Resistant Bacteria In Vitro and In Vivo. Molecules 2023 , 28 , 2609. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Manach, C.; Williamson, G.; Morand, C.; Scalbert, A.; Rémésy, C. Bioavailability and Bioefficacy of Polyphenols in Humans. I. Review of 97 Bioavailability Studies. Am. J. Clin. Nutr. 2005 , 81 , 230S–242S. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Thilakarathna, S.H.; Rupasinghe, H.P.V. Flavonoid Bioavailability and Attempts for Bioavailability Enhancement. Nutrients 2013 , 5 , 3367–3387. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Shen, Q.; Li, X.; Li, W.; Zhao, X. Enhanced Intestinal Absorption of Daidzein by Borneol/Menthol Eutectic Mixture and Microemulsion. AAPS PharmSciTech 2011 , 12 , 1044–1049. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zhang, Z.; Huang, Y.; Gao, F.; Gao, Z.; Bu, H.; Gu, W.; Li, Y. A Self-Assembled Nanodelivery System Enhances the Oral Bioavailability of Daidzein: In Vitro Characteristics and in Vivo Performance. Nanomedicine 2011 , 6 , 1365–1379. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Nielsen, I.L.F.; Chee, W.S.S.; Poulsen, L.; Offord-Cavin, E.; Rasmussen, S.E.; Frederiksen, H.; Enslen, M.; Barron, D.; Horcajada, M.-N.; Williamson, G. Bioavailability Is Improved by Enzymatic Modification of the Citrus Flavonoid Hesperidin in Humans: A Randomized, Double-Blind, Crossover Trial. J. Nutr. 2006 , 136 , 404–408. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Cao, H.; Jing, X.; Wu, D.; Shi, Y. Methylation of Genistein and Kaempferol Improves Their Affinities for Proteins. Int. J. Food Sci. Nutr. 2013 , 64 , 437–443. [ Google Scholar ] [ CrossRef ]
• Foxman, B. Recurring Urinary Tract Infection: Incidence and Risk Factors. Am. J. Public Health 1990 , 80 , 331–333. [ Google Scholar ] [ CrossRef ]
• Foxman, B.; Gillespie, B.; Koopman, J.; Zhang, L.; Palin, K.; Tallman, P.; Marsh, J.V.; Spear, S.; Sobel, J.D.; Marty, M.J.; et al. Risk Factors for Second Urinary Tract Infection among College Women. Am. J. Epidemiol. 2000 , 151 , 1194–1205. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hooton, T.M.; Scholes, D.; Hughes, J.P.; Winter, C.; Roberts, P.L.; Stapleton, A.E.; Stergachis, A.; Stamm, W.E. A Prospective Study of Risk Factors for Symptomatic Urinary Tract Infection in Young Women. N. Engl. J. Med. 1996 , 335 , 468–474. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fihn, S.D.; Boyko, E.J.; Normand, E.H.; Chen, C.L.; Grafton, J.R.; Hunt, M.; Yarbro, P.; Scholes, D.; Stergachis, A. Association between Use of Spermicide-Coated Condoms and Escherichia Coli Urinary Tract Infection in Young Women. Am. J. Epidemiol. 1996 , 144 , 512–520. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fihn, S.D.; Boyko, E.J.; Chen, C.L.; Normand, E.H.; Yarbro, P.; Scholes, D. Use of Spermicide-Coated Condoms and Other Risk Factors for Urinary Tract Infection Caused by Staphylococcus Saprophyticus. Arch. Intern. Med. 1998 , 158 , 281–287. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Scholes, D.; Hooton, T.M.; Roberts, P.L.; Stapleton, A.E.; Gupta, K.; Stamm, W.E. Risk Factors for Recurrent Urinary Tract Infection in Young Women. J. Infect. Dis. 2000 , 182 , 1177–1182. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hooton, T.M.; Stapleton, A.E.; Roberts, P.L.; Winter, C.; Scholes, D.; Bavendam, T.; Stamm, W.E. Perineal Anatomy and Urine-Voiding Characteristics of Young Women with and without Recurrent Urinary Tract Infections. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 1999 , 29 , 1600–1601. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Schaeffer, A.J.; Jones, J.M.; Dunn, J.K. Association of in Vitro Escherichia Coli Adherence to Vaginal and Buccal Epithelial Cells with Susceptibility of Women to Recurrent Urinary-Tract Infections. N. Engl. J. Med. 1981 , 304 , 1062–1066. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Källenius, G.; Winberg, J. Bacterial Adherence to Periurethral Epithelial Cells in Girls Prone to Urinary-Tract Infections. Lancet 1978 , 2 , 540–543. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fowler, J.E.; Stamey, T.A. Studies of Introital Colonization in Women with Recurrent Urinary Infections. VII. The Role of Bacterial Adherence. J. Urol. 1977 , 117 , 472–476. [ Google Scholar ] [ CrossRef ]
• Stapleton, A.; Nudelman, E.; Clausen, H.; Hakomori, S.; Stamm, W.E. Binding of Uropathogenic Escherichia Coli R45 to Glycolipids Extracted from Vaginal Epithelial Cells Is Dependent on Histo-Blood Group Secretor Status. J. Clin. Investig. 1992 , 90 , 965–972. [ Google Scholar ] [ CrossRef ]
• Lomberg, H.; Cedergren, B.; Leffler, H.; Nilsson, B.; Carlström, A.S.; Svanborg-Edén, C. Influence of Blood Group on the Availability of Receptors for Attachment of Uropathogenic Escherichia Coli. Infect. Immun. 1986 , 51 , 919–926. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bixler, B.R.; Anger, J.T. Updates to Recurrent Uncomplicated Urinary Tract Infections in Women: AUA/CUA/SUFU Guideline. J. Urol. 2022 , 208 , 754–756. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Cymbal, M.; Chatterjee, A.; Baggott, B.; Auron, M. Management of Clostridioides Difficile Infection: Diagnosis, Treatment, and Future Perspectives. Am. J. Med. 2024 , 137 , 571–576. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Tacconelli, E.; De Angelis, G.; Cataldo, M.A.; Mantengoli, E.; Spanu, T.; Pan, A.; Corti, G.; Radice, A.; Stolzuoli, L.; Antinori, S.; et al. Antibiotic Usage and Risk of Colonization and Infection with Antibiotic-Resistant Bacteria: A Hospital Population-Based Study. Antimicrob. Agents Chemother. 2009 , 53 , 4264–4269. [ Google Scholar ] [ CrossRef ]
• Duarte, S.; Gregoire, S.; Singh, A.P.; Vorsa, N.; Schaich, K.; Bowen, W.H.; Koo, H. Inhibitory Effects of Cranberry Polyphenols on Formation and Acidogenicity of Streptococcus Mutans Biofilms. FEMS Microbiol. Lett. 2006 , 257 , 50–56. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Guay, D.R.P. Cranberry and Urinary Tract Infections. Drugs 2009 , 69 , 775–807. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hisano, M.; Bruschini, H.; Nicodemo, A.C.; Srougi, M. Cranberries and Lower Urinary Tract Infection Prevention. Clinics 2012 , 67 , 661–668. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lynch, D.M. Cranberry for Prevention of Urinary Tract Infections. Am. Fam. Physician 2004 , 70 , 2175–2177. [ Google Scholar ]
• Beachey, E.H. Bacterial Adherence: Adhesin-Receptor Interactions Mediating the Attachment of Bacteria to Mucosal Surface. J. Infect. Dis. 1981 , 143 , 325–345. [ Google Scholar ] [ CrossRef ]
• Zafriri, D.; Ofek, I.; Adar, R.; Pocino, M.; Sharon, N. Inhibitory Activity of Cranberry Juice on Adherence of Type 1 and Type P Fimbriated Escherichia Coli to Eucaryotic Cells. Antimicrob. Agents Chemother. 1989 , 33 , 92–98. [ Google Scholar ] [ CrossRef ]
• Howell, A.B.; Reed, J.D.; Krueger, C.G.; Winterbottom, R.; Cunningham, D.G.; Leahy, M. A-Type Cranberry Proanthocyanidins and Uropathogenic Bacterial Anti-Adhesion Activity. Phytochemistry 2005 , 66 , 2281–2291. [ Google Scholar ] [ CrossRef ]
• Liu, Y.; Black, M.A.; Caron, L.; Camesano, T.A. Role of Cranberry Juice on Molecular-Scale Surface Characteristics and Adhesion Behavior of Escherichia Coli. Biotechnol. Bioeng. 2006 , 93 , 297–305. [ Google Scholar ] [ CrossRef ]
• Ren, D.; Zuo, R.; González Barrios, A.F.; Bedzyk, L.A.; Eldridge, G.R.; Pasmore, M.E.; Wood, T.K. Differential Gene Expression for Investigation of Escherichia Coli Biofilm Inhibition by Plant Extract Ursolic Acid. Appl. Environ. Microbiol. 2005 , 71 , 4022–4034. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Grace, M.H.; Massey, A.R.; Mbeunkui, F.; Yousef, G.G.; Lila, M.A. Comparison of Health-Relevant Flavonoids in Commonly Consumed Cranberry Products. J. Food Sci. 2012 , 77 , H176–H183. [ Google Scholar ] [ CrossRef ]
• Howell, A.B.; Foxman, B. Cranberry Juice and Adhesion of Antibiotic-Resistant Uropathogens. JAMA 2002 , 287 , 3082–3083. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Avorn, J.; Monane, M.; Gurwitz, J.H.; Glynn, R.J.; Choodnovskiy, I.; Lipsitz, L.A. Reduction of Bacteriuria and Pyuria after Ingestion of Cranberry Juice. JAMA 1994 , 271 , 751–754. [ Google Scholar ] [ CrossRef ]
• Howell, A.B.; Botto, H.; Combescure, C.; Blanc-Potard, A.-B.; Gausa, L.; Matsumoto, T.; Tenke, P.; Sotto, A.; Lavigne, J.-P. Dosage Effect on Uropathogenic Escherichia Coli Anti-Adhesion Activity in Urine Following Consumption of Cranberry Powder Standardized for Proanthocyanidin Content: A Multicentric Randomized Double Blind Study. BMC Infect. Dis. 2010 , 10 , 94. [ Google Scholar ] [ CrossRef ]
• Beerepoot, M.; Geerlings, S. Non-Antibiotic Prophylaxis for Urinary Tract Infections. Pathogens 2016 , 5 , 36. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Luís, Â.; Domingues, F.; Pereira, L. Can Cranberries Contribute to Reduce the Incidence of Urinary Tract Infections? A Systematic Review with Meta-Analysis and Trial Sequential Analysis of Clinical Trials. J. Urol. 2017 , 198 , 614–621. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Jepson, R.G.; Williams, G.; Craig, J.C. Cranberries for Preventing Urinary Tract Infections. Cochrane Database Syst. Rev. 2012 , 10 , CD001321. [ Google Scholar ] [ CrossRef ]
• Gbinigie, O.A.; Spencer, E.A.; Heneghan, C.J.; Lee, J.J.; Butler, C.C. Cranberry Extract for Symptoms of Acute, Uncomplicated Urinary Tract Infection: A Systematic Review. Antibiotics 2020 , 10 , 12. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fu, Z.; Liska, D.; Talan, D.; Chung, M. Cranberry Reduces the Risk of Urinary Tract Infection Recurrence in Otherwise Healthy Women: A Systematic Review and Meta-Analysis. J. Nutr. 2017 , 147 , 2282–2288. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Koradia, P.; Kapadia, S.; Trivedi, Y.; Chanchu, G.; Harper, A. Probiotic and Cranberry Supplementation for Preventing Recurrent Uncomplicated Urinary Tract Infections in Premenopausal Women: A Controlled Pilot Study. Expert Rev. Anti Infect. Ther. 2019 , 17 , 733–740. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Stapleton, A.E.; Dziura, J.; Hooton, T.M.; Cox, M.E.; Yarova-Yarovaya, Y.; Chen, S.; Gupta, K. Recurrent Urinary Tract Infection and Urinary Escherichia Coli in Women Ingesting Cranberry Juice Daily: A Randomized Controlled Trial. Mayo Clin. Proc. 2012 , 87 , 143–150. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Barbosa-Cesnik, C.; Brown, M.B.; Buxton, M.; Zhang, L.; DeBusscher, J.; Foxman, B. Cranberry Juice Fails to Prevent Recurrent Urinary Tract Infection: Results from a Randomized Placebo-Controlled Trial. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2011 , 52 , 23–30. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Maki, K.C.; Kaspar, K.L.; Khoo, C.; Derrig, L.H.; Schild, A.L.; Gupta, K. Consumption of a Cranberry Juice Beverage Lowered the Number of Clinical Urinary Tract Infection Episodes in Women with a Recent History of Urinary Tract Infection. Am. J. Clin. Nutr. 2016 , 103 , 1434–1442. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bruyère, F.; Azzouzi, A.R.; Lavigne, J.-P.; Droupy, S.; Coloby, P.; Game, X.; Karsenty, G.; Issartel, B.; Ruffion, A.; Misrai, V.; et al. A Multicenter, Randomized, Placebo-Controlled Study Evaluating the Efficacy of a Combination of Propolis and Cranberry (Vaccinium Macrocarpon) (DUAB ® ) in Preventing Low Urinary Tract Infection Recurrence in Women Complaining of Recurrent Cystitis. Urol. Int. 2019 , 103 , 41–48. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Vostalova, J.; Vidlar, A.; Simanek, V.; Galandakova, A.; Kosina, P.; Vacek, J.; Vrbkova, J.; Zimmermann, B.F.; Ulrichova, J.; Student, V. Are High Proanthocyanidins Key to Cranberry Efficacy in the Prevention of Recurrent Urinary Tract Infection? Phytother. Res. PTR 2015 , 29 , 1559–1567. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ledda, A.; Bottari, A.; Luzzi, R.; Belcaro, G.; Hu, S.; Dugall, M.; Hosoi, M.; Ippolito, E.; Corsi, M.; Gizzi, G.; et al. Cranberry Supplementation in the Prevention of Non-Severe Lower Urinary Tract Infections: A Pilot Study. Eur. Rev. Med. Pharmacol. Sci. 2015 , 19 , 77–80. [ Google Scholar ]
• Kontiokari, T.; Sundqvist, K.; Nuutinen, M.; Pokka, T.; Koskela, M.; Uhari, M. Randomised Trial of Cranberry-Lingonberry Juice and Lactobacillus GG Drink for the Prevention of Urinary Tract Infections in Women. BMJ 2001 , 322 , 1571. [ Google Scholar ] [ CrossRef ]
• Stothers, L. A Randomized Trial to Evaluate Effectiveness and Cost Effectiveness of Naturopathic Cranberry Products as Prophylaxis against Urinary Tract Infection in Women. Can. J. Urol. 2002 , 9 , 1558–1562. [ Google Scholar ] [ PubMed ]
• Beerepoot, M.A.J.; ter Riet, G.; Nys, S.; van der Wal, W.M.; de Borgie, C.A.J.M.; de Reijke, T.M.; Prins, J.M.; Koeijers, J.; Verbon, A.; Stobberingh, E.; et al. Cranberries vs Antibiotics to Prevent Urinary Tract Infections: A Randomized Double-Blind Noninferiority Trial in Premenopausal Women. Arch. Intern. Med. 2011 , 171 , 1270–1278. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Babar, A.; Moore, L.; Leblanc, V.; Dudonné, S.; Desjardins, Y.; Lemieux, S.; Bochard, V.; Guyonnet, D.; Dodin, S. High Dose versus Low Dose Standardized Cranberry Proanthocyanidin Extract for the Prevention of Recurrent Urinary Tract Infection in Healthy Women: A Double-Blind Randomized Controlled Trial. BMC Urol. 2021 , 21 , 44. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Davis, J.A.; Freeze, H.H. Studies of Mannose Metabolism and Effects of Long-Term Mannose Ingestion in the Mouse. Biochim. Biophys. Acta 2001 , 1528 , 116–126. [ Google Scholar ] [ CrossRef ]
• Fronzes, R.; Remaut, H.; Waksman, G. Architectures and Biogenesis of Non-Flagellar Protein Appendages in Gram-Negative Bacteria. EMBO J. 2008 , 27 , 2271–2280. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Choudhury, D.; Thompson, A.; Stojanoff, V.; Langermann, S.; Pinkner, J.; Hultgren, S.J.; Knight, S.D. X-ray Structure of the FimC-FimH Chaperone-Adhesin Complex from Uropathogenic Escherichia coli . Science 1999 , 285 , 1061–1066. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zhou, G.; Mo, W.J.; Sebbel, P.; Min, G.; Neubert, T.A.; Glockshuber, R.; Wu, X.R.; Sun, T.T.; Kong, X.P. Uroplakin Ia Is the Urothelial Receptor for Uropathogenic Escherichia coli : Evidence from in Vitro FimH Binding. J. Cell Sci. 2001 , 114 , 4095–4103. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Pak, J.; Pu, Y.; Zhang, Z.T.; Hasty, D.L.; Wu, X.R. Tamm-Horsfall Protein Binds to Type 1 Fimbriated Escherichia coli and Prevents E. coli from Binding to Uroplakin Ia and Ib Receptors. J. Biol. Chem. 2001 , 276 , 9924–9930. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Eto, D.S.; Jones, T.A.; Sundsbak, J.L.; Mulvey, M.A. Integrin-Mediated Host Cell Invasion by Type 1-Piliated Uropathogenic Escherichia Coli. PLoS Pathog. 2007 , 3 , e100. [ Google Scholar ] [ CrossRef ]
• Mydock-McGrane, L.K.; Cusumano, Z.T.; Janetka, J.W. Mannose-Derived FimH Antagonists: A Promising Anti-Virulence Therapeutic Strategy for Urinary Tract Infections and Crohn’s Disease. Expert Opin. Ther. Pat. 2016 , 26 , 175–197. [ Google Scholar ] [ CrossRef ]
• Michaels, E.K.; Chmiel, J.S.; Plotkin, B.J.; Schaeffer, A.J. Effect of D-Mannose and D-Glucose on Escherichia Coli Bacteriuria in Rats. Urol. Res. 1983 , 11 , 97–102. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Schaeffer, A.J.; Chmiel, J.S.; Duncan, J.L.; Falkowski, W.S. Mannose-Sensitive Adherence of Escherichia Coli to Epithelial Cells from Women with Recurrent Urinary Tract Infections. J. Urol. 1984 , 131 , 906–910. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Spaulding, C.N.; Klein, R.D.; Ruer, S.; Kau, A.L.; Schreiber, H.L.; Cusumano, Z.T.; Dodson, K.W.; Pinkner, J.S.; Fremont, D.H.; Janetka, J.W.; et al. Selective Depletion of Uropathogenic E. Coli from the Gut by a FimH Antagonist. Nature 2017 , 546 , 528–532. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Mydock-McGrane, L.K.; Hannan, T.J.; Janetka, J.W. Rational Design Strategies for FimH Antagonists: New Drugs on the Horizon for Urinary Tract Infection and Crohn’s Disease. Expert Opin. Drug Discov. 2017 , 12 , 711–731. [ Google Scholar ] [ CrossRef ]
• Lenger, S.M.; Bradley, M.S.; Thomas, D.A.; Bertolet, M.H.; Lowder, J.L.; Sutcliffe, S. D-Mannose vs Other Agents for Recurrent Urinary Tract Infection Prevention in Adult Women: A Systematic Review and Meta-Analysis. Am. J. Obstet. Gynecol. 2020 , 223 , 265.e1–265.e13. [ Google Scholar ] [ CrossRef ]
• Kyriakides, R.; Jones, P.; Somani, B.K. Role of D-Mannose in the Prevention of Recurrent Urinary Tract Infections: Evidence from a Systematic Review of the Literature. Eur. Urol. Focus 2021 , 7 , 1166–1169. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Parazzini, F.; Ricci, E.; Fedele, F.; Chiaffarino, F.; Esposito, G.; Cipriani, S. Systematic Review of the Effect of D-Mannose with or without Other Drugs in the Treatment of Symptoms of Urinary Tract Infections/Cystitis (Review). Biomed. Rep. 2022 , 17 , 69. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kranjčec, B.; Papeš, D.; Altarac, S. D-Mannose Powder for Prophylaxis of Recurrent Urinary Tract Infections in Women: A Randomized Clinical Trial. World J. Urol. 2014 , 32 , 79–84. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Porru, D.; Parmigiani, A.; Tinelli, C.; Barletta, D.; Choussos, D.; Di Franco, C.; Bobbi, V.; Bassi, S.; Miller, O.; Gardella, B.; et al. Oral D-Mannose in Recurrent Urinary Tract Infections in Women: A Pilot Study. J. Clin. Urol. 2014 , 7 , 208–213. [ Google Scholar ] [ CrossRef ]
• Cooper, T.E.; Teng, C.; Howell, M.; Teixeira-Pinto, A.; Jaure, A.; Wong, G. D-Mannose for Preventing and Treating Urinary Tract Infections. Cochrane Database Syst. Rev. 2022 , 8 , CD013608. [ Google Scholar ] [ CrossRef ]
• Fish, D.N.; Piscitelli, S.C.; Danziger, L.H. Development of Resistance during Antimicrobial Therapy: A Review of Antibiotic Classes and Patient Characteristics in 173 Studies. Pharmacotherapy 1995 , 15 , 279–291. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Baraz, A.; Chowers, M.; Nevo, D.; Obolski, U. The Time-Varying Association between Previous Antibiotic Use and Antibiotic Resistance. Clin. Microbiol. Infect. Off. Publ. Eur. Soc. Clin. Microbiol. Infect. Dis. 2023 , 29 , 390.e1–390.e4. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kawalec, A.; Józefiak, J.; Kiliś-Pstrusińska, K. Urinary Tract Infection and Antimicrobial Resistance Patterns: 5-Year Experience in a Tertiary Pediatric Nephrology Center in the Southwestern Region of Poland. Antibiotics 2023 , 12 , 1454. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Parry, C.M.; Taylor, A.; Williams, R.; Lally, H.; Corbett, H.J. Antimicrobial Resistance of Breakthrough Urinary Tract Infections in Young Children Receiving Continual Antibiotic Prophylaxis. Eur. J. Pediatr. 2023 , 182 , 4087–4093. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Alsubaie, S.S.; Barry, M.A. Current Status of Long-Term Antibiotic Prophylaxis for Urinary Tract Infections in Children: An Antibiotic Stewardship Challenge. Kidney Res. Clin. Pract. 2019 , 38 , 441–454. [ Google Scholar ] [ CrossRef ]
• Pothoven, R. Management of Urinary Tract Infections in the Era of Antimicrobial Resistance. Drug Target Insights 2023 , 17 , 126–137. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Share and Cite

Ioannou, P.; Baliou, S. The Molecular Mechanisms and Therapeutic Potential of Cranberry, D-Mannose, and Flavonoids against Infectious Diseases: The Example of Urinary Tract Infections. Antibiotics 2024 , 13 , 593. https://doi.org/10.3390/antibiotics13070593

Ioannou P, Baliou S. The Molecular Mechanisms and Therapeutic Potential of Cranberry, D-Mannose, and Flavonoids against Infectious Diseases: The Example of Urinary Tract Infections. Antibiotics . 2024; 13(7):593. https://doi.org/10.3390/antibiotics13070593

Ioannou, Petros, and Stella Baliou. 2024. "The Molecular Mechanisms and Therapeutic Potential of Cranberry, D-Mannose, and Flavonoids against Infectious Diseases: The Example of Urinary Tract Infections" Antibiotics 13, no. 7: 593. https://doi.org/10.3390/antibiotics13070593

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

• Privacy Policy

Home » Research Methods – Types, Examples and Guide

Research Methods – Types, Examples and Guide

Table of Contents

Research Methods

Definition:

Research Methods refer to the techniques, procedures, and processes used by researchers to collect , analyze, and interpret data in order to answer research questions or test hypotheses. The methods used in research can vary depending on the research questions, the type of data that is being collected, and the research design.

Types of Research Methods

Types of Research Methods are as follows:

Qualitative research Method

Qualitative research methods are used to collect and analyze non-numerical data. This type of research is useful when the objective is to explore the meaning of phenomena, understand the experiences of individuals, or gain insights into complex social processes. Qualitative research methods include interviews, focus groups, ethnography, and content analysis.

Quantitative Research Method

Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.

Mixed Method Research

Mixed Method Research refers to the combination of both qualitative and quantitative research methods in a single study. This approach aims to overcome the limitations of each individual method and to provide a more comprehensive understanding of the research topic. This approach allows researchers to gather both quantitative data, which is often used to test hypotheses and make generalizations about a population, and qualitative data, which provides a more in-depth understanding of the experiences and perspectives of individuals.

Key Differences Between Research Methods

The following Table shows the key differences between Quantitative, Qualitative and Mixed Research Methods

Examples of Research Methods

Examples of Research Methods are as follows:

Qualitative Research Example:

A researcher wants to study the experience of cancer patients during their treatment. They conduct in-depth interviews with patients to gather data on their emotional state, coping mechanisms, and support systems.

Quantitative Research Example:

A company wants to determine the effectiveness of a new advertisement campaign. They survey a large group of people, asking them to rate their awareness of the product and their likelihood of purchasing it.

Mixed Research Example:

A university wants to evaluate the effectiveness of a new teaching method in improving student performance. They collect both quantitative data (such as test scores) and qualitative data (such as feedback from students and teachers) to get a complete picture of the impact of the new method.

Applications of Research Methods

Research methods are used in various fields to investigate, analyze, and answer research questions. Here are some examples of how research methods are applied in different fields:

• Psychology : Research methods are widely used in psychology to study human behavior, emotions, and mental processes. For example, researchers may use experiments, surveys, and observational studies to understand how people behave in different situations, how they respond to different stimuli, and how their brains process information.
• Sociology : Sociologists use research methods to study social phenomena, such as social inequality, social change, and social relationships. Researchers may use surveys, interviews, and observational studies to collect data on social attitudes, beliefs, and behaviors.
• Medicine : Research methods are essential in medical research to study diseases, test new treatments, and evaluate their effectiveness. Researchers may use clinical trials, case studies, and laboratory experiments to collect data on the efficacy and safety of different medical treatments.
• Education : Research methods are used in education to understand how students learn, how teachers teach, and how educational policies affect student outcomes. Researchers may use surveys, experiments, and observational studies to collect data on student performance, teacher effectiveness, and educational programs.
• Business : Research methods are used in business to understand consumer behavior, market trends, and business strategies. Researchers may use surveys, focus groups, and observational studies to collect data on consumer preferences, market trends, and industry competition.
• Environmental science : Research methods are used in environmental science to study the natural world and its ecosystems. Researchers may use field studies, laboratory experiments, and observational studies to collect data on environmental factors, such as air and water quality, and the impact of human activities on the environment.
• Political science : Research methods are used in political science to study political systems, institutions, and behavior. Researchers may use surveys, experiments, and observational studies to collect data on political attitudes, voting behavior, and the impact of policies on society.

Purpose of Research Methods

Research methods serve several purposes, including:

• Identify research problems: Research methods are used to identify research problems or questions that need to be addressed through empirical investigation.
• Develop hypotheses: Research methods help researchers develop hypotheses, which are tentative explanations for the observed phenomenon or relationship.
• Collect data: Research methods enable researchers to collect data in a systematic and objective way, which is necessary to test hypotheses and draw meaningful conclusions.
• Analyze data: Research methods provide tools and techniques for analyzing data, such as statistical analysis, content analysis, and discourse analysis.
• Test hypotheses: Research methods allow researchers to test hypotheses by examining the relationships between variables in a systematic and controlled manner.
• Draw conclusions : Research methods facilitate the drawing of conclusions based on empirical evidence and help researchers make generalizations about a population based on their sample data.
• Enhance understanding: Research methods contribute to the development of knowledge and enhance our understanding of various phenomena and relationships, which can inform policy, practice, and theory.

When to Use Research Methods

Research methods are used when you need to gather information or data to answer a question or to gain insights into a particular phenomenon.

Here are some situations when research methods may be appropriate:

• To investigate a problem : Research methods can be used to investigate a problem or a research question in a particular field. This can help in identifying the root cause of the problem and developing solutions.
• To gather data: Research methods can be used to collect data on a particular subject. This can be done through surveys, interviews, observations, experiments, and more.
• To evaluate programs : Research methods can be used to evaluate the effectiveness of a program, intervention, or policy. This can help in determining whether the program is meeting its goals and objectives.
• To explore new areas : Research methods can be used to explore new areas of inquiry or to test new hypotheses. This can help in advancing knowledge in a particular field.
• To make informed decisions : Research methods can be used to gather information and data to support informed decision-making. This can be useful in various fields such as healthcare, business, and education.

Advantages of Research Methods

Research methods provide several advantages, including:

• Objectivity : Research methods enable researchers to gather data in a systematic and objective manner, minimizing personal biases and subjectivity. This leads to more reliable and valid results.
• Replicability : A key advantage of research methods is that they allow for replication of studies by other researchers. This helps to confirm the validity of the findings and ensures that the results are not specific to the particular research team.
• Generalizability : Research methods enable researchers to gather data from a representative sample of the population, allowing for generalizability of the findings to a larger population. This increases the external validity of the research.
• Precision : Research methods enable researchers to gather data using standardized procedures, ensuring that the data is accurate and precise. This allows researchers to make accurate predictions and draw meaningful conclusions.
• Efficiency : Research methods enable researchers to gather data efficiently, saving time and resources. This is especially important when studying large populations or complex phenomena.
• Innovation : Research methods enable researchers to develop new techniques and tools for data collection and analysis, leading to innovation and advancement in the field.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Ethnographic Research -Types, Methods and Guide

Correlational Research – Methods, Types and...

Informed Consent in Research – Types, Templates...

Research Objectives – Types, Examples and...

Experimental Design – Types, Methods, Guide

Case Study – Methods, Examples and Guide

• Study protocol
• Open access
• Published: 27 June 2024

Study on the efficiency of virtual reality in the treatment of alcohol use disorder: study protocol for a randomized controlled trial

• Fanny Nègre   ORCID: orcid.org/0009-0008-7020-6748 1 , 2 ,
• Maud Lemercier-Dugarin 3 ,
• Romain Gomet 2 ,
• Antoine Pelissolo 4 , 5 ,
• Eric Malbos 6 , 7 ,
• Lucia Romo 1 , 8 , 9 &
• El-Hadi Zerdazi 2 , 5  

Trials volume  25 , Article number:  417 ( 2024 ) Cite this article

Metrics details

According to the World Health Organization, alcohol is a major global public health problem, leading to a significant increase in illness and death. To treat alcohol use disorders, new therapeutic tools are being promoted, among which virtual reality (VR) shows promise. Previous research has demonstrated the efficacy of VR in reducing alcohol cravings in patients, but there is a lack of data on its effectiveness in maintaining abstinence or reducing consumption in recently abstinent individuals.

The E-Reva study aims to compare the efficacy of a treatment strategy combining virtual reality cue exposure therapy (VR-CET) and cognitive behavioral therapy (CBT) with conventional CBT in reducing alcohol consumption and craving in patients with alcohol use disorder (AUD). In addition to this primary objective, the study will compare the effects of VR-CET combined with CBT on anxiety, depression, rumination, and feelings of self-efficacy versus conventional CBT.

This prospective randomized controlled trial will be conducted over 8 months in four addiction departments in France. It includes two parallel groups: i) the VR-CET + CBT group, and ii) the CBT-only group, which serves as a control group.

Participants will be recruited by the investigating doctor in the addiction centers. The sample will consist of 156 patients diagnosed with AUD and abstinent for at least 15 days.

Both treatment groups will participate in four group CBT sessions followed by four individual sessions: i) the VR-CET group will be exposed to virtual environments associated with alcohol-related stimuli, ii) the CBT-only group will receive traditional CBT sessions. After completion of the 8 sessions, patients will be followed up for 6 months. The primary outcome is the cumulative number of standard drinks consumed at 8 months, assessed using the TLFB method.

Despite the promise of VR-CET to reduce the desire to drink, the effect on alcohol consumption remains uncertain in the existing literature. Our protocol aims to address the limitations of previous research by increasing sample size, targeting consumption reduction, and incorporating neutral environments. E-Reva aims to enrich the literature on the use of VR in the treatment of AUD and open new perspectives for future interventions.

Trial registration

ClinicalTrials.gov ID NCT06104176, Registered 2023/11/13 ( https://clinicaltrials.gov/study/NCT06104176?id=NCT06104176&rank=1 ).

N° IDRCB: 2022-A02797-36.

Protocol version 1.0, 12/05/2023.

Peer Review reports

Introduction

Responsible for nearly 3.3 million deaths per year, alcohol has been a worldwide public health problem for years [ 1 , 2 ]. The ethanol (ethyl alcohol) in alcohol is responsible for numerous disorders: cognitive and behavioral disorders, certain types of cancer, cardiovascular disease, higher risk of cirrhosis and pancreatitis, and trauma from violence and road or work accidents [ 3 ]. Excessive alcohol consumption therefore induces neurobiological and behavioral changes, creating a breeding ground for the development of alcohol use disorder (AUD). According to the 5th version of the Diagnostic and Statistical Manual of Mental Disorders, AUD is defined as "a set of behavioral, cognitive, and physiological phenomena that result in progressive disinvestment from other activities" [ 4 ]. Despite the harmful physical and emotional effects of excessive alcohol use, many people find it difficult to reduce or maintain abstinence over the long term [ 5 ].

Craving is defined as "a compelling need to consume the substance" that can lead to compulsive substance seeking and consumption-related behaviors. Craving elicits psychophysiological, emotional, cognitive, and behavioral responses that follow a subjective perception of the urge to drink alcohol [ 6 ]. Craving is a key element in the development and maintenance of excessive drinking and AUD [ 7 , 8 ].

Treatment for AUD is based on a multidimensional approach that includes pharmaceutical, behavioral, and psychosocial interventions [ 7 ]. These treatments aim to address loss of control over use, reduce negative emotions and hyperreactivity to stress, and/or reduce craving [ 9 ]. Among these interventions, several meta-analyses conclude that CBTs are effective in treating addictive disorders, have few contraindications, and are easy to implement [ 10 , 11 ].

One of the tools used in CBTs is cue exposure therapy (CET), which aims to teach craving self-management techniques through in vivo, in imagination, or multimedia exposure to substance-related stimuli [ 7 , 12 ]. CET is based on the principles of deconditioning a behavior considered maladaptive to replace it with one considered more adaptive, and systematically desensitizing the subject by immersing him or her in the anxiety-provoking environment. Despite its success in treating anxiety disorders, CET has shown limited results in reducing alcohol consumption [ 13 ]. This limited effectiveness appears to be related to the ecological validity of the cues used [ 12 , 13 ]. The in vivo exposures proposed in CET are costly and complex to replicate, as they require specific environments and situations (e.g., bars, nightclubs…). Consequently, exposures are often performed in the laboratory, but these experimental approaches involve artificial behavioral responses to simple stimuli, with constraints on the modification of parameters, context, and available space, which limits the complexity of behavioral interactions [ 8 , 14 ].

Virtual reality exposure therapy (VR-CET) is a new therapeutic exposure technique that uses virtual reality (VR) to allow users to navigate and interact with a computer-generated (and computer-maintained) three-dimensional environment in real time through a headset [ 15 ]. The advantages of this technique are the therapist's control over the exposure, the freedom to stop exposure at any time if necessary, the possibility of adapting the virtual environment to the subject's problems, and better observation of the patient's reactions. All these elements promote greater immersion and interaction of the patient with the virtual environment than, for example, exposure in imagination, another typical technique used in CBT [ 16 ]. Moreover, technological advances in recent years have made it widely available, easily accessible, simpler to use, better tolerated, and increasingly less expensive. Several studies report promising results for VR-CET in the treatment of various mental disorders [ 16 ], including addictive disorders [ 17 ]. The use of virtual reality was motivated by the fact that many patients were reluctant to experience violent anxiety-provoking situations in vivo during CBT sessions [ 18 ]. Thus, the application of VR-CET has been extended to many other specific phobic disorders (acrophobia, arachnophobia, social phobia, claustrophobia, agoraphobia,etc.) and has shown a therapeutic effect superior to no intervention and equivalent to exposure through standard techniques [ 18 , 19 , 20 ]. For people suffering from excessive alcohol consumption, VR-CET has been shown to be effective in inducing and reducing craving [ 21 ]. Despite this promising advance, there remains a gap in the data on the efficacy of VR-CET in maintaining abstinence or reducing alcohol consumption, which remain the primary goals of therapeutic interventions. This raises the need for further studies to shed light on this area of research. The primary objective of this study is to evaluate the efficacy of a treatment strategy combining VR-CET and CBT on reducing the cumulative number of standard drinks (sd) of alcohol at 8 months after enrollment. Secondary objectives are to evaluate the efficacy of the same treatment strategy on reducing alcohol craving, anxiety, depression, and rumination, and on increasing self-efficacy at 8 months. This article describes, in accordance with SPIRIT standards [ 22 ] and following the CONSORT [ 23 ] declaration checklist A prospective, comparative, randomized, open-label, 8-month clinical trial (2 months of therapy followed by 6 months of follow-up) with two parallel groups: i) VR-CET + CBT, ii) CBT alone without exposure (control group). This was a national multicenter study involving four addictology centers. A total of 156 patients diagnosed with AUD according to DSM-5 criteria were included.

Methods/Design

Study setting and population.

Study data will be collected in day hospitals (DH) within the addiction departments of public hospitals. For this research, four centers in the Paris area will be involved in recruiting patients. The four recruiting centers are: 1) Department of Addictions—Hôpital Albert Chenevier—CHU Henri Mondor—APHP – Créteil, 2) Department of Addictions—Hôpital Fernand Widal—Nord—Université de Paris—APHP – Paris, 3) Department of Addictions—Centre hospitalier des Quatre Villes – Sèvres, 4) Department of Addictions—Tolbiac Day Clinic – Paris. Recruitment will be done by the investigating physician at the time of admission to the DH during an individual consultation. If the patient is eligible for the study, the full protocol will be presented and reviewed during an individual consultation at the DH enrollment visit.

The following inclusion criteria apply: i) 18 to 80 years of age at the time of enrolment; ii) patients with a diagnosis of AUD according to DSM-5 criteria (American Psychiatric Association, 2013); iii) patients who had been abstinent for at least 15 days; iv) patients who can speak, understand and read French; v) patients who have signed an informed consent form and who are affiliated to a health insurance plan.

Subjects are not included if they are: i) adults under legal protection or deprived of liberty by judicial or administrative decision; ii) pregnant or breast-feeding women; iii) patients with decompensated psychiatric disorders (psychotic disorders, mood disorders and anxiety disorders); iv) patients relapsing from their AUD; v) patients with severe cognitive impairment as defined by the MOCA Cognitive Assessment Test (score < 10) [ 24 ]; vi) visually impaired patients; vii) patients with contraindications to virtual reality exposure, due to epilepsy or history of photoparoxysmal EEG response, or vestibular disorders; viii) recent cardiovascular accident less than 3 months old, current nausea/vomiting, claustrophobia and moderate or severe myopia (greater than -3. 5 diopters); ix) patients wearing any of the following medical devices (due to the risk of interference with the virtual reality headset): pacemaker, implanted defibrillator or implanted hearing aid (non-implanted prostheses are not contraindicated if the patient agrees to remove them during VR-CET); x) participation in another study or being in the exclusion period after previous research involving human subjects; xi) and patients benefiting from State Medical Assistance (defined as access to healthcare for people in an irregular situation).

Study design and procedure

This study is a multi-center, randomized, controlled trial involving two parallel groups: i) the VR-CET group, which benefits from virtual reality exposure preceded by CBT sessions, and ii) the CBT-only group (control group). Interventions take place over a 2-month (8-week) cycle, with a total of 8 sessions (Cf. Figure  1 ). Both groups receive 4 CBT group sessions in the first month, followed by either 4 supervised individual virtual exposure sessions for the VR-CET group, or 4 additional individual CBT sessions for the CBT-only group. Each session lasts one hour and a half. Once the 8 sessions have been completed (2 months), patients are followed up for 6 months, for a total of 8 months.

Participant timeline

Treatment groups

The first four CBT group sessions focus on understanding the effects of alcohol, assessing motivation to change, behavioral and emotional strategies, cognitive strategies, relapse prevention and assertiveness strategies. These sessions are conducted in a group setting by a trained psychologist and a trainee.

Participants are then randomized into two groups (M1): i) VR-CET + BT group, ii) CBT group only. Allocation is centralized, individualized and randomized according to the following factors: center, presence of pharmacological treatment to maintain alcohol abstinence (2 modalities), history of AUD treatment in the last five years (2 modalities), alcohol consumption goals (2 modalities) and severity of alcohol dependence according to DSM-5 criteria (3 modalities).

CBT treatment group

Individual CBT sessions (sessions 5 to 8 in the control group) are conducted by a CBT-trained investigator and focus on reviewing and adapting the strategies discussed in the group sessions. The sessions last between 30 and 90 min and are designed to develop a list of strategies adapted to the patient's daily life, addressing various environments such as the supermarket, parties, home and exposure to advertising. The patient's desire to drink is regularly assessed using a visual analog scale (VAS).

VR-CET treatment group

For the VR-CET group, individual exposure sessions (sessions 5 to 8) are conducted by an investigator trained in CBT. Prior to the exposure sessions, each patient will establish a hierarchy of four virtual environments: exposure to alcohol advertising, home, supermarket, and parties (cf. Figure  2 ) ranging from the simplest to the hardest. The duration of exposure to each virtual environment varies according to the time needed to reduce the participants’ craving. Participants move on to the next environment when a comfortable level of emotion or craving is reached, and exposure can be repeated if necessary. If craving remains high at the end of a session, it is extended. After exposure, patients benefit from a 5 to 10 min VR relaxation session. Craving is regularly assessed using a VAS before, during and at the end of each session.

Screenshots of the virtual environments utilized in the present study

For the VR-CET group, the virtual reality device is as follows:

An HP reverb G2 virtual reality headset with 2160 × 2160 resolution per eye and position sensor integrated into the headset.

Two motion controllers in the form of joysticks in each hand that locate the position of the thumb, index and middle fingers in contact with the buttons. In addition to walking, the wireless joysticks enable subjects to interact with 3D objects (taking a drink, picking up a bottle, etc.). The subject thus produces equivalent movements in real time and explores synthetic situations visually.

Victus laptop by HP Laptot 16-s0025nf NVIDIA GeForce RTX 4060.

The software exploited to run the virtual reality environments was C2Care. In the alcohol addiction care offering, we have selected 4 environments, following a focus group in 2019, offering distinct scenarios inducing the desire to drink. The environments selected are as follows (Cf. Figure  2 ):

Heading for the metro, where there is a large alcohol advertisement;

Go to the supermarket and pass through the alcohol aisle;

Find yourself alone at home with a bottle of alcohol on the table;

Going to a party.

Criteria for discontinuing or modifying allocated interventions

Participants can end their participation in the research at any time, and the investigator may do so for safety reasons or in the best interest of the participant. Temporary break in participation may occur in cases of persistent psychological distress, trauma during sessions, or discomfort related to virtual reality. Early termination may occur if inclusion criteria are not met. Pregnancy, protective measures, or enrollment in another study will result in definitive dropout. Absence from group sessions (50%) may lead to exclusion.

Evaluation outcomes

Primary outcome.

The primary outcome is the cumulative number of standard drinks consumed (in grams of pure alcohol) at 8 months, as reported by patients. As a reminder, in France, 1 standard drink = 10 g of pure alcohol = 1 unit of alcohol [ 25 ]. Alcohol consumption is estimated retrospectively by patients every month using the Timeline Follow-Back (TLFB) method, a widely used method that has demonstrated good psychometric properties and superiority over free recall [ 26 ]. This method allows retrospective estimation of alcohol consumption over a specified period of up to one year. Estimates of alcohol consumption (in standard drinks) are collected monthly by the research team, either in person or by telephone, to reduce recall bias and improve the performance of this method over time [ 27 ].

Secondary outcomes

Craving is assessed by the Transaddiction Craving Triggers Questionnaire (TCTQ) [ 28 ]. This is an instrument designed to assess what triggers craving. The questionnaire is completed at inclusion, M2, M5, and M8. Craving is also assessed using a VAS (0 to 10) at each exposure session [ 29 ] and on a monthly basis after M2, in the same way as for the primary outcome.

The frequency of hazardous drinking episodes is assessed with the AUDIT-C (Alcohol Use Disorders Identification Test) questionnaire [ 30 ], an abbreviated version of the AUDIT self-report questionnaire [ 31 ] that includes three questions about the patient's alcohol consumption. These data are collected at enrollment and at treatment phases M2, M5, and M8. Finally, reported alcohol consumption is correlated with weekly DH toxicology monitoring, if this is routinely performed at the recruiting centers. Weekly toxicology screenings for ethyl glucuronide (EtG), if performed as part of the routine care at the recruiting centers, will be recorded in the logbook.

Anxiety is assessed by the Generalized Anxiety Disorder-7 (GAD-7) questionnaire [ 32 ]. This instrument is designed to screen for generalized anxiety disorder and may also help to identify panic disorder, social anxiety disorder, and posttraumatic stress disorder. It is administered at inclusion, M2, M5, and M8.

Depression is assessed by the Patient Health Questionnaire-9 (PHQ-9) [ 33 ]. This instrument collects information on the presence and intensity of depressive symptoms. Data is collected at inclusion, M2, M5, and M8.

Self-efficacy is assessed by the Sense of Self-Efficacy Questionnaire, originally developed in German by Matthias Jerusalem and Ralf Schwarzer [ 34 ]. It is administered at inclusion, M2, M5, and M8.

Rumination is assessed by the 15-item Perseverative Thinking Questionnaire (PTQ). This is a widely used self-report measure of repetitive negative thinking [ 35 ]. It is administered at inclusion, M2, M5, and M8.

The state of presence in virtual reality is measured by the QEP questionnaire (Questionnaire sur l'État de Présence) developed by the UQO Cyberpsychology Laboratory (2002) [ 36 , 37 ]. This survey is conducted at M2 for the participants randomly assigned to the VR-CET group.

Cybersickness risk is assessed after each VR-CET session using the Cybermalaise Questionnaire from the UQO Cyberpsychology Laboratory [ 38 ].

All questionnaires are completed by DH patients at inclusion and M2. The scheduled assessments from M3 to M8 are conducted by telephone (Cf. Table 1 ).

Sample size

To determine the number of participants needed for the study, we randomly selected 15 patients with alcohol-related disorders (AUD) who were already being treated at the Albert Chenevier Day Hospital's addiction department. Their cumulative alcohol consumption was monitored at two, five and eight months after admission to estimate the average daily consumption over eight months. The target consumption was calculated on the basis of the recommendations of the European Medicines Agency [ 39 ], aiming at a reduction of at least two risk levels according to the World Health Organization. To achieve a statistical power of 0.8, considering a risk α of 0.05 with a two-sided hypothesis, 65 patients per group are required. Assuming a drop-out rate of 20%, 78 patients per group need to be recruited, for a total of 156 patients for both groups. See Table 2 for recruitment procedure.

Data collection, management, and analysis

Data management.

Data are collected on paper and in an observation notebook (with all questionnaires), then entered by the research team on the secure CleanWEB® platform. This platform enables data to be downloaded, anonymized, stored and randomized.

Statistical methods

The characteristics of all patients will be described globally and according to their randomization group, using the number of patients (%) for qualitative variables and the median [interquartile range] or mean (± standard deviation) for quantitative variables, depending on the normality of their distribution. A patient flow diagram will be generated. Results are reported according to CONSORT recommendations. Tests will be two-tailed, and a significance level of p  < 0.05 will be considered statistically significant. The primary outcome (self-reported cumulative number of standard drinks consumed at 8 months) will be compared between the two groups using Student's t-test for independent samples. Complementary analyses will be conducted using generalized linear regression models adjusted for minimization factors and number of sessions per setting. Given the repeated measurement of outcomes and the multicenter design of the study, additional analysis will be performed including Cox and mixed models. To consider Survival analysis will also be conducted using a linear mixed model. Secondary endpoints will be analyzed using the same methodology as for the primary endpoint, i.e. a comparison of the mean using the usual tests. primary endpoint, i.e. a comparison of means using standard tests at 8 months. Secondary analyses to assess changes in secondary endpoints will be performed using evaluated using linear mixed models.

Methods for accounting for missing, unused, or invalid data

Patients who withdraw consent or discontinue follow-up during the study are not replaced. Missing data will be systematically searched for and checked in the patients' medical records. Analyses may be performed after imputation of missing data. Missing data will be handled using multiple imputation as recommended by the National Research Council Panel on Handling Missing Data in Clinical Trials [ 40 ].

Selection of participants for analyses

The intention-to-treat population will include all patients who signed the informed consent form and were randomized to one of the two study arms and will be analyzed according to the initial randomization group. The per-protocol (PP) population will include patients enrolled in the study without major deviations from the current protocol, including erroneous inclusion of patients, changes or noncompliance with the treatment assigned at randomization. The primary endpoint will be analyzed by ITT and secondarily by PP analyses. PP analyses. Secondary endpoints will be analyzed according to ITT and PP principles to ensure robustness of results.

Data monitoring

Two committees work together to monitor the data and guide the research.

i) The Steering Committee meets quarterly. Its purpose is to define the general organization, determine the methodology, monitor the progress of the research, coordinate information, initially determine the methodology, validate the applications of persons recruited under the protocol, and define any relevant modifications to the protocol necessary for the continuation of the trial. At the end of the meeting, the sponsor will be informed of any decision that requires rapid action by the sponsor.

ii) The Scientific Committee meets quarterly. Its purpose is to define the objectives of the protocol, to draft the protocol and to propose modifications during the research. Decisions taken at these meetings are validated after discussion and majority vote.

All data, documents and reports may be audited without invoking medical confidentiality. Audits can be carried out at any stage of the research process, by independent persons appointed by the sponsor. The aim is to guarantee the quality of the research, the validity of the results, and compliance with applicable laws and regulations.

Ethics and dissemination

Research ethics approval.

This research is conducted in accordance with the World Medical Association's Declaration of Helsinki. The study was approved by the French ethic committee (Comité de Protection des Personnes Sud-Est VI) on 07/07/2023 (National ID 2022-A02797-36). Any substantial modification of the protocol by the coordinating investigator must be approved by the sponsor. Once approved, the sponsor must obtain a favorable opinion from the ethic committee before implementation.

Consent or assent

Patients in addictology DH receive initial information from a trained investigator. Informed consent is obtained by the principal investigator, an attending physician, or a qualified person, with a two- to four-week cooling-off period. The investigator documents participation in the patient's medical record, retains a copy of the consent form, and a tamper-proof envelope is archived by the sponsor at the end of the study. No exclusion period is defined at the end of participation. No anticipated harm or compensation to subjects is foreseen, as the research will be organized as part of their routine care. However, participants in the CBT group will be offered the opportunity to receive virtual reality exposure sessions as part of their routine care once participation in the study has ended.

Confidentiality and access to data

Quality control personnel ensure confidentiality, making data non-identifiable, using initials and a coded ID. The sponsor ensures that each participant has given written consent to access data. APHP Cleanweb® data will be stored on dedicated servers. Physical documents will be kept in a locked cabinet during the research, then archived in accordance with regulations. Documents specific to minimal-risk research will be archived by the investigator and sponsor for 15 years after the end of the research, including sealed envelopes, files, successive versions of the protocol, ethic committee opinions, correspondence, inclusion list, special appendices, final report, and documents relating to data collection. Study results will be communicated to investigators at all centers, to patients and to the scientific community in general. APHP is the owner of the data. Additionally, a contract has been established with the University of Nanterre. This agreement allows for further statistical analyses to be conducted in collaboration with the CLIPSYD laboratory from the Faculty of Psychology at the University of Nanterre, under the direction of Prof. Lucia Romo. For this purpose, pseudonymized research data will be securely transmitted to the team to facilitate these analyses. All data necessary to support the protocol can be provided upon request to APHP.

The present study aims to evaluate the efficacy of VR-CET combined with CBT in the treatment of AUD in recently abstinent individuals. A recent review of the literature highlights the emergence of virtual reality as an innovative and promising tool in the therapeutic landscape [ 21 ]. Studies on the efficacy of VR-CET have mainly focused on craving, with findings such as that exposure to alcohol-related stimuli in virtual reality can increase participants' desire to drink [ 5 ]. In terms of its reduction, VR-CET appears to have positive effects, particularly for individuals with AUD [ 1 , 41 ]. The perceived level of realism of the virtual environment seems to influence this efficacy, with a more pronounced reduction in the desire to drink when the environment is perceived as realistic. About anxiety, the effects of VR-CET were mixed, but integration with CBT resulted in a significant reduction in post-treatment anxiety, although less favorable than in the CBT group alone. About alcohol use, only one study examined this variable and showed that VR-CET had no significant short-term effects [ 42 ]. The systematic review highlighted the lack of longitudinal data to consolidate the efficacy of VR-CET as a therapeutic tool to reduce alcohol consumption Table 2 .

Our protocol aims to address the limitations of previous research by increasing the sample size ( N  = 156), by aiming not only for abstinence but also for a reduction in consumption, which seems more realistic, by having broad inclusion criteria to allow the inclusion of a population as close as possible to clinical reality, integrating sociodemographic questions into our inclusion questionnaire, and considering comorbidities via the MINI questionnaire at inclusion. In addition, we included urinary toxicity test (ethyl glucuronide) during the two months of therapy to objectify alcohol use data. In response to previous criticism regarding the lack of virtual environments with negative connotations, two neutral environments (subway and supermarket) were included to induce a sense of stress.

Despite these improvements, several limitations must be considered. We did not include the multisensory aspect, in particular olfactory stimulation, which could potentially influence perception of the realism of virtual environments. Furthermore, we did not include objective data such as heart rate or urinary toxins about craving and alcohol consumption, only declarative data are collected, leaving a gap in our understanding of physiological responses to alcohol-related stimuli and on subjects' actual consumption.

Despite the limitations of our study, E-Reva contributes to the literature on the use of VR in the treatment of AUD. These findings could potentially open significant horizons for future patient interventions. VR is emerging as an innovative therapeutic resource that provides a unique setting for exposure to alcohol-related environments. Integrating VR into the treatment of AUD requires a thoughtful approach that considers the specific nuances of this disorder. Personalizing interventions based on a thorough understanding of individual patient needs remains critical to maximizing the therapeutic efficacy of VR. Overall, the steady progress of research in this field promises significant advances. These advances will not only strengthen our understanding of the efficacy of VR in the treatment of AUD but will also open new perspectives for innovative therapeutic interventions focused on the specific needs of patients. Thus, VR is emerging as a promising tool to enrich the therapeutic landscape and pave the way for a more targeted and effective approach to the treatment of AUD.

Trials status

The study began enrolling participants in October 2023, and recruitment is scheduled to end in October 2025. Protocol version 1.0, 12/05/2023.

Availability of data and materials

The data sets analyzed in the current study and the statistical code are available from APHP and the principal investigator on reasonable request, as is the full protocol.

Abbreviations

• Alcohol use disorder

Alcohol Use Disorders Identification Test

Cognitive behavioral therapy

Cue exposure therapy

Day hospitals

Diagnostic and Statistical Manual of Mental Disorders

Generalized Anxiety Disorder 7

Per-protocol

Perseverative Thinking Questionnaire

State of Presence Questionnaire

Transaddiction Carving Triggers

Timeline Followback

Visual analog scale

• Virtual reality

Virtual reality cue exposure therapy

Choi YJ, Lee JH. The effect of virtual covert sensitization on reducing alcohol craving in heavy social drinkers. Virtual Reality. 2015;19(2):111–7.

Article   Google Scholar  

World Health Organization. Global status report on alcohol and health 2018. Geneva: World Health Organization; 2018. p. 450.

Burton R, Sheron N. No level of alcohol consumption improves health. The Lancet. 2018;392(10152):987–8.

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). Arlington: Elsevier Masson; 2015.

Ghiţă A, Hernández-Serrano O, Fernández-Ruiz Y, Monras M, Ortega L, Mondon S, et al. Cue-Elicited Anxiety and Alcohol Craving as Indicators of the Validity of ALCO-VR Software: A Virtual Reality Study. J Clin Med. 2019;8(8):1153.

Article   PubMed   PubMed Central   Google Scholar  

Ghiţă A, Hernández-Serrano O, Fernández-Ruiz J, Moreno M, Monras M, Ortega L, et al. Attentional Bias, Alcohol Craving, and Anxiety Implications of the Virtual Reality Cue-Exposure Therapy in Severe Alcohol Use Disorder: A Case Report. Front Psychol. 2021;12: 543586.

Ghiţă A, Gutiérrez-Maldonado J. Applications of virtual reality in individuals with alcohol misuse: A systematic review. Addict Behav. 2018;81:1–11.

Article   PubMed   Google Scholar  

Simon J, Etienne AM, Bouchard S, Quertemont E. Alcohol Craving in Heavy and Occasional Alcohol Drinkers After Cue Exposure in a Virtual Environment: The Role of the Sense of Presence. Frontiers in Human Neuroscience. 2020 [cited 2022 Oct 24];14. Available from: https://www.frontiersin.org/articles/ https://doi.org/10.3389/fnhum.2020.00124 .

Cabrera EA, Wiers CE, Lindgren E, Miller G, Volkow ND, Wang GJ. Neuroimaging the Effectiveness of Substance Use Disorder Treatments. J Neuroimmune Pharmacol. 2016;11(3):408–33.

Magill M, Ray L, Kiluk B, Hoadley A, Bernstein M, Tonigan JS, et al. A meta-analysis of cognitive-behavioral therapy for alcohol or other drug use disorders: Treatment efficacy by contrast condition. J Consult Clin Psychol. 2019;87(12):1093–105.

Magill M, Ray LA. Cognitive-Behavioral Treatment With Adult Alcohol and Illicit Drug Users: A Meta-Analysis of Randomized Controlled Trials. J Stud Alcohol Drugs. 2009;70(4):516–27.

Hernández-Serrano O, Ghiţă A, Fernández-Ruiz J, Monràs M, Gual A, Gacto M, et al. Determinants of Cue-Elicited Alcohol Craving and Perceived Realism in Virtual Reality Environments among Patients with Alcohol Use Disorder. J Clin Med. 2021;10(11):2241.

Trahan MH, Maynard BR, Smith KS, Farina ASJ, Khoo YM. Thérapie d’exposition à la réalité virtuelle sur l’alcool et la nicotine: un examen systématique. Res Soc Work Pract. 2019;29(8):876–91.

Bordnick PS, Traylor A, Copp HL, Graap KM, Carter B, Ferrer M, et al. Assessing reactivity to virtual reality alcohol based cues. Addict Behav. 2008;33(6):743–56.

Bouchard S, Côté S, Richard DCS. Chapter 16 - Virtual reality applications for exposure. In: Richard DCS, Lauterbach D, editors. Handbook of Exposure Therapies [Internet]. Burlington: Academic Press; 2007 [cited 2019 Dec 15]. p. 347–88. Available from: http://www.sciencedirect.com/science/article/pii/B978012587421250017X .

Bohil CJ, Alicea B, Biocca FA. Virtual reality in neuroscience research and therapy. Nat Rev Neurosci. 2011;12(12):752–62.

Article   CAS   PubMed   Google Scholar  

Segawa T, Baudry T, Bourla A, Blanc JV, Peretti CS, Mouchabac S, et al. Virtual Reality (VR) in Assessment and Treatment of Addictive Disorders: A Systematic Review. Frontiers in Neuroscience. 2020 [cited 2022 Mar 3];13. Available from: https://www.frontiersin.org/article/ https://doi.org/10.3389/fnins.2019.01409 .

Malbos E, Boyer L, Lançon C. L’utilisation de la réalité virtuelle dans le traitement des troubles mentaux. La Presse Médicale. 2013;42(11):1442–52.

Bouchard S, Dumoulin S, Robillard G, Guitard T, Klinger É, Forget H, et al. Virtual reality compared with in vivo exposure in the treatment of social anxiety disorder: A three-arm randomised controlled trial. Br J Psychiatry. 2017;210(4):276–83.

Lambrey S, Jouvent R, Allilaire JF, Pélissolo A. Les thérapies utilisant la réalité virtuelle dans les troubles phobiques. Annales Médico-psychologiques, revue psychiatrique. 2010;168(1):44–6.

Nègre F, Lemercier-Dugarin M, Kahn-Lewin C, Gomet R, Zerdazi EHM, Zerhouni O, et al. Virtual reality efficiency as exposure therapy for alcohol use: A systematic literature review. Drug Alcohol Depend. 2023;253: 111027.

Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3):200–7.

Schulz KF, Altman DG, Moher D, CONSORT Group. CONSORT. Statement: updated guidelines for reporting parallel group randomised trials. Trials. 2010;2010(11):32.

Google Scholar  

Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9.

Kalinowski A, Humphreys K. Governmental standard drink definitions and low-risk alcohol consumption guidelines in 37 countries. Addiction. 2016;111(7):1293–8.

Sobell LC, Sobell MB. Timeline Follow-Back : A technique for assessing self-reported alcohol consumption. In: Measuring alcohol consumption : Psychosocial and biochemical methods. Humana Press. 1992. p. 41‑72. Available from: https://doi.org/10.1007/978-1-4612-0357-5 .

Hoeppner BB, Stout RL, Jackson KM, Barnett NP. How good is fine-grained Timeline Follow-back data? Comparing 30-day TLFB and repeated 7-day TLFB alcohol consumption reports on the person and daily level. Addict Behav. 2010;35(12):1138–43.

von Hammerstein C, Cornil A, Rothen S, Romo L, Khazaal Y, Benyamina A, et al. Psychometric properties of the transaddiction craving triggers questionnaire in alcohol use disorder. Int J Methods Psychiatr Res. 2020;29(1): e1815.

Drobes DJ, Thomas SE. Assessing craving for alcohol. Alcohol Res Health. 1999;23(3):179–86.

CAS   PubMed   PubMed Central   Google Scholar  

Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998;158(16):1789–95.

Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption–II. Addiction. 1993;88(6):791–804.

Spitzer RL, Kroenke K, Williams JBW, Löwe B. A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7. Arch Intern Med. 2006;166(10):1092–7.

Kroenke K, Spitzer RL, Williams JBW. The PHQ-9. J Gen Intern Med. 2001;16(9):606–13.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Jerusalem M, Schwarzer R. Self-efficacy as a ressource factor in stress appraisal processes. In: New York: Hemisphere Publishing Corp.; 1992. p. 195–213.

Ehring T, Watkins ER. Repetitive Negative Thinking as a Transdiagnostic Process. Int J Cogn Ther. 2008;1(3):192–205.

Witmer BG, Jerome CJ, Singer MJ. The Factor Structure of the Presence Questionnaire. Presence: Teleoperators and Virtual Environments. 2005;14(3):298–312.

Witmer BG, Singer MJ. Measuring Presence in Virtual Environments: A Presence Questionnaire. Presence: Teleoperators and Virtual Environments. 1998;7(3):225–40.

Kennedy RS, Lane NE, Berbaum KS, Lilienthal MG. Simulator Sickness Questionnaire: An Enhanced Method for Quantifying Simulator Sickness. Int J Aviat Psychol. 1993;3(3):203–20.

European Medicines Agency. Guideline on the development of medicinal products for the treatment of alcohol dependence. ● United Kingdom: European Medicines Agency; 2010 Feb. Available from: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-development-medicinal-products-treatment-alcohol-dependence_en.pdf .

National Research Council (US) Panel on Handling Missing Data in Clinical Trials. The Prevention and Treatment of Missing Data in Clinical Trials [Internet]. Washington (DC): National Academies Press (US); 2010 [cited 2022 Apr 30]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK209904/ .

Hernández-Serrano O, Ghiţă A, Figueras-Puigderrajols N, Fernández-Ruiz J, Monras M, Ortega L, et al. Predictors of Changes in Alcohol Craving Levels during a Virtual Reality Cue Exposure Treatment among Patients with Alcohol Use Disorder. J Clin Med. 2020;9(9):3018.

Pennington DL, Reavis JV, Cano MT, Walker E, Batki SL. The Impact of Exercise and Virtual Reality Executive Function Training on Cognition Among Heavy Drinking Veterans With Traumatic Brain Injury: A Pilot Feasibility Study. Front Behav Neurosci. 2022;16: 802711.

Download references

Acknowledgements

The authors would like to thank: Dr Jean-Baptiste Trabut, head of the Addiction Department at the Albert Chenevier Hospital. The authors would also like to thank the DRCI and URC teams at the Albert Chenevier Hospital: Kaci Lila, Bouaziz Khaled, Kervizic Camille and Guyot France.

This research was supported by the Institut National du Cancer (INCa) and the Institut pour la Recherche en Santé Publique (IRESP) (INCA_16041, INCa/IReSP_16611). The sponsor was Assistance Publique – Hôpitaux de Paris (Délégation à la Recherche Clinique et à l'Innovation). INCa and IRESP play no role in the design of the study, the collection, analysis or interpretation of the data, the drafting of the manuscript or the decision to submit the article for publication.

Author information

Authors and affiliations.

Laboratoire CLIPSYD, Université Paris Nanterre, 92000, Nanterre, France

Fanny Nègre & Lucia Romo

DMU IMPACT, APHP, Hôpitaux Universitaires Henri-Mondor, Hôpital Albert-Chenevier, Service d’addictologie, 94010, Créteil, France

Fanny Nègre, Romain Gomet & El-Hadi Zerdazi

Université de Caen Normandie, LPCN UR, 7452, F-14000, Caen, France

Maud Lemercier-Dugarin

DMU IMPACT, AP-HP, Université Paris-Est-Créteil (UPEC), Hôpitaux Universitaires Henri-MondorService de Psychiatrie, 94000, Créteil, France

Antoine Pelissolo

Université Paris-Est Créteil, INSERM U995, IMRB, Translational Neuropsychiatry Laboratory, 94010, Créteil, France

Antoine Pelissolo & El-Hadi Zerdazi

Psychiatry Service of Pr Lançon, CHU de Sainte Marguerite, Marseille, France

Eric Malbos

Institut Fresnel Aix-Marseille Université, CNRS, Ecole Centrale Marseille, UMR, 72490, Marseille, France

APHP, Hôpital Universitaire Raymond Poincaré, 92380, Garches, France

Université Paris Saclay, INSERM CESP, 1018 UPS, 94807, Villejuif, France

You can also search for this author in PubMed   Google Scholar

Contributions

FN, MLD, E-HZ, RG, AP, EM and LM designed and developed the study. E-HZ took care of the statistical elements and power calculations. The study protocol was drafted by FN, MLD and E-HZ. FN, MLD and LM developed the CBT program. The therapeutic sessions were carried out by FN. The manuscript was written by FN, MLD and E-HZ and critically reviewed by LM, RG, AP and EM. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Fanny Nègre .

Ethics declarations

Ethics approval and consent to participate.

Written, informed consent to participate will be obtained from all participants.

ClinicalTrials.gov ID NCT06104176 / N° IDRCB: 2022-A02797-36 / Protocol version 1.0, 12/05/2023.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary material 1., supplementary material 2., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Nègre, F., Lemercier-Dugarin, M., Gomet, R. et al. Study on the efficiency of virtual reality in the treatment of alcohol use disorder: study protocol for a randomized controlled trial. Trials 25 , 417 (2024). https://doi.org/10.1186/s13063-024-08271-x

Download citation

Received : 08 March 2024

Accepted : 19 June 2024

Published : 27 June 2024

DOI : https://doi.org/10.1186/s13063-024-08271-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

ISSN: 1745-6215

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]