limitations of a research study examples

21 Research Limitations Examples

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.

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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]

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Home » Limitations in Research – Types, Examples and Writing Guide

Limitations in Research – Types, Examples and Writing Guide

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Limitations in Research

Limitations in research refer to the factors that may affect the results, conclusions , and generalizability of a study. These limitations can arise from various sources, such as the design of the study, the sampling methods used, the measurement tools employed, and the limitations of the data analysis techniques.

Types of Limitations in Research

Types of Limitations in Research are as follows:

Sample Size Limitations

This refers to the size of the group of people or subjects that are being studied. If the sample size is too small, then the results may not be representative of the population being studied. This can lead to a lack of generalizability of the results.

Time Limitations

Time limitations can be a constraint on the research process . This could mean that the study is unable to be conducted for a long enough period of time to observe the long-term effects of an intervention, or to collect enough data to draw accurate conclusions.

Selection Bias

This refers to a type of bias that can occur when the selection of participants in a study is not random. This can lead to a biased sample that is not representative of the population being studied.

Confounding Variables

Confounding variables are factors that can influence the outcome of a study, but are not being measured or controlled for. These can lead to inaccurate conclusions or a lack of clarity in the results.

Measurement Error

This refers to inaccuracies in the measurement of variables, such as using a faulty instrument or scale. This can lead to inaccurate results or a lack of validity in the study.

Ethical Limitations

Ethical limitations refer to the ethical constraints placed on research studies. For example, certain studies may not be allowed to be conducted due to ethical concerns, such as studies that involve harm to participants.

Examples of Limitations in Research

Some Examples of Limitations in Research are as follows:

Research Title: “The Effectiveness of Machine Learning Algorithms in Predicting Customer Behavior”

Limitations:

• The study only considered a limited number of machine learning algorithms and did not explore the effectiveness of other algorithms.
• The study used a specific dataset, which may not be representative of all customer behaviors or demographics.
• The study did not consider the potential ethical implications of using machine learning algorithms in predicting customer behavior.

Research Title: “The Impact of Online Learning on Student Performance in Computer Science Courses”

• The study was conducted during the COVID-19 pandemic, which may have affected the results due to the unique circumstances of remote learning.
• The study only included students from a single university, which may limit the generalizability of the findings to other institutions.
• The study did not consider the impact of individual differences, such as prior knowledge or motivation, on student performance in online learning environments.

Research Title: “The Effect of Gamification on User Engagement in Mobile Health Applications”

• The study only tested a specific gamification strategy and did not explore the effectiveness of other gamification techniques.
• The study relied on self-reported measures of user engagement, which may be subject to social desirability bias or measurement errors.
• The study only included a specific demographic group (e.g., young adults) and may not be generalizable to other populations with different preferences or needs.

How to Write Limitations in Research

When writing about the limitations of a research study, it is important to be honest and clear about the potential weaknesses of your work. Here are some tips for writing about limitations in research:

• Identify the limitations: Start by identifying the potential limitations of your research. These may include sample size, selection bias, measurement error, or other issues that could affect the validity and reliability of your findings.
• Be honest and objective: When describing the limitations of your research, be honest and objective. Do not try to minimize or downplay the limitations, but also do not exaggerate them. Be clear and concise in your description of the limitations.
• Provide context: It is important to provide context for the limitations of your research. For example, if your sample size was small, explain why this was the case and how it may have affected your results. Providing context can help readers understand the limitations in a broader context.
• Discuss implications : Discuss the implications of the limitations for your research findings. For example, if there was a selection bias in your sample, explain how this may have affected the generalizability of your findings. This can help readers understand the limitations in terms of their impact on the overall validity of your research.
• Provide suggestions for future research : Finally, provide suggestions for future research that can address the limitations of your study. This can help readers understand how your research fits into the broader field and can provide a roadmap for future studies.

Purpose of Limitations in Research

There are several purposes of limitations in research. Here are some of the most important ones:

• To acknowledge the boundaries of the study : Limitations help to define the scope of the research project and set realistic expectations for the findings. They can help to clarify what the study is not intended to address.
• To identify potential sources of bias: Limitations can help researchers identify potential sources of bias in their research design, data collection, or analysis. This can help to improve the validity and reliability of the findings.
• To provide opportunities for future research: Limitations can highlight areas for future research and suggest avenues for further exploration. This can help to advance knowledge in a particular field.
• To demonstrate transparency and accountability: By acknowledging the limitations of their research, researchers can demonstrate transparency and accountability to their readers, peers, and funders. This can help to build trust and credibility in the research community.
• To encourage critical thinking: Limitations can encourage readers to critically evaluate the study’s findings and consider alternative explanations or interpretations. This can help to promote a more nuanced and sophisticated understanding of the topic under investigation.

When to Write Limitations in Research

Limitations should be included in research when they help to provide a more complete understanding of the study’s results and implications. A limitation is any factor that could potentially impact the accuracy, reliability, or generalizability of the study’s findings.

It is important to identify and discuss limitations in research because doing so helps to ensure that the results are interpreted appropriately and that any conclusions drawn are supported by the available evidence. Limitations can also suggest areas for future research, highlight potential biases or confounding factors that may have affected the results, and provide context for the study’s findings.

Generally, limitations should be discussed in the conclusion section of a research paper or thesis, although they may also be mentioned in other sections, such as the introduction or methods. The specific limitations that are discussed will depend on the nature of the study, the research question being investigated, and the data that was collected.

Examples of limitations that might be discussed in research include sample size limitations, data collection methods, the validity and reliability of measures used, and potential biases or confounding factors that could have affected the results. It is important to note that limitations should not be used as a justification for poor research design or methodology, but rather as a way to enhance the understanding and interpretation of the study’s findings.

Importance of Limitations in Research

Here are some reasons why limitations are important in research:

• Enhances the credibility of research: Limitations highlight the potential weaknesses and threats to validity, which helps readers to understand the scope and boundaries of the study. This improves the credibility of research by acknowledging its limitations and providing a clear picture of what can and cannot be concluded from the study.
• Facilitates replication: By highlighting the limitations, researchers can provide detailed information about the study’s methodology, data collection, and analysis. This information helps other researchers to replicate the study and test the validity of the findings, which enhances the reliability of research.
• Guides future research : Limitations provide insights into areas for future research by identifying gaps or areas that require further investigation. This can help researchers to design more comprehensive and effective studies that build on existing knowledge.
• Provides a balanced view: Limitations help to provide a balanced view of the research by highlighting both strengths and weaknesses. This ensures that readers have a clear understanding of the study’s limitations and can make informed decisions about the generalizability and applicability of the findings.

Advantages of Limitations in Research

Here are some potential advantages of limitations in research:

• Focus : Limitations can help researchers focus their study on a specific area or population, which can make the research more relevant and useful.
• Realism : Limitations can make a study more realistic by reflecting the practical constraints and challenges of conducting research in the real world.
• Innovation : Limitations can spur researchers to be more innovative and creative in their research design and methodology, as they search for ways to work around the limitations.
• Rigor : Limitations can actually increase the rigor and credibility of a study, as researchers are forced to carefully consider the potential sources of bias and error, and address them to the best of their abilities.
• Generalizability : Limitations can actually improve the generalizability of a study by ensuring that it is not overly focused on a specific sample or situation, and that the results can be applied more broadly.

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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.

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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.

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How to present limitations in research

Last updated

30 January 2024

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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.

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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.

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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.

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How to Identify Limitations in Research

4-minute read

• 7th March 2022

Whether you’re a veteran researcher with years of experience under your belt or a novice to the field that’s feeling overwhelmed with where to start, you must understand that every study has its limitations. These are restrictions that arise from the study’s design, or the methodology implemented during the testing phase. Unfortunately, research limitations will always exist due to the subjective nature of testing a hypothesis. We’ve compiled some helpful information below on how to identify and accept research limitations and use them to your advantage. Essentially, we’ll show you how to make lemonade (a brilliant piece of academic work ) from the lemons you receive (the constraints your study reveals).

Research Limitations

So, let’s dive straight in, shall we? It’s always beneficial (and good practice) to disclose your research limitations . A common thought is that divulging these shortcomings will undermine the credibility and quality of your research. However, this is certainly not the case— stating the facts upfront not only reinforces your reputation as a researcher but also lets the assessor or reader know that you’re confident and transparent about the results and relevance of your study, despite these constraints.

Additionally, it creates a gap for more research opportunities, where you can analyze these limitations and determine how to incorporate or address them in a new batch of tests or create a new hypothesis altogether. Another bonus is that it helps readers to understand the optimum conditions for how to apply the results of your testing. This is a win-win, making for a far more persuasive research paper .

Now that you know why you should clarify your research limitations, let’s focus on which ones take precedence and should be disclosed. Any given research project can be vulnerable to various hindrances, so how do you identify them and single out the most significant ones to discuss? Well, that depends entirely on the nature of your study. You’ll need to comb through your research approach, methodology, testing processes, and expected results to identify the type of limitations your study may be exposed to. It’s worth noting that this understanding can only offer a broad idea of the possible restrictions you’ll face and may potentially change throughout the study.

We’ve compiled a list of the most common types of research limitations that you may encounter so you can adequately prepare for them and remain vigilant during each stage of your study.

Sample Size:

It’s critical that you choose a sample size that accurately represents the population you wish to test your theory on. If a sample is too small, the results cannot reliably be generalized across a large population.

Methodology:

The method you choose before you commence testing might seem effective in theory, but too many stumbling blocks during the testing phase can influence the accuracy and reliability of the results.

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Collection of Data:

The methods you utilize to obtain your research—surveys, emails, in-person interviews, phone calls—will directly influence the type of results your study yields.

Age of Data:

The nature of the information—and how far back it goes—affects the type of assumptions you can make. Extrapolating older data for a current hypothesis can significantly change the outcome of your testing.

Time Constraints:

Working within the deadline of when you need to submit your findings will determine the extent of your research and testing and, therefore, can heavily impact your results. Limited time frames for testing might mean not achieving the scope of results you were originally looking for.

Limited Budget:

Your study may require equipment and other resources that can become extremely costly. Budget constraints may mean you cannot acquire advanced software, programs, or travel to multiple destinations to interview participants. All of these factors can substantially influence your results.

So, now that you know how to determine your research limitations and the types you might experience, where should you document it? It’s commonly disclosed at the beginning of your discussion section , so the reader understands the shortcomings of your study before digging into the juicy bit—your findings. Alternatively, you can detail the constraints faced at the end of the discussion section to emphasize the requirements for the completion of further studies.

We hope this post will prepare you for some of the pitfalls you may encounter when conducting and documenting your research. Once you have a first draft ready, consider submitting a free sample to us for proofreading to ensure that your writing is concise and error-free and your results—despite their limitations— shine through.

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Limitations in Medical Research: Recognition, Influence, and Warning

Douglas e. ott.

Mercer University, Macon, Georgia, USA.

Background:

As the number of limitations increases in a medical research article, their consequences multiply and the validity of findings decreases. How often do limitations occur in a medical article? What are the implications of limitation interaction? How often are the conclusions hedged in their explanation?

To identify the number, type, and frequency of limitations and words used to describe conclusion(s) in medical research articles.

Search, analysis, and evaluation of open access research articles from 2021 and 2022 from the Journal of the Society of Laparoscopic and Robotic Surgery and 2022 Surgical Endoscopy for type(s) of limitation(s) admitted to by author(s) and the number of times they occurred. Limitations not admitted to were found, obvious, and not claimed. An automated text analysis was performed for hedging words in conclusion statements. A limitation index score is proposed to gauge the validity of statements and conclusions as the number of limitations increases.

A total of 298 articles were reviewed and analyzed, finding 1,764 limitations. Four articles had no limitations. The average was between 3.7% and 6.9% per article. Hedging, weasel words and words of estimative probability description was found in 95.6% of the conclusions.

Conclusions:

Limitations and their number matter. The greater the number of limitations and ramifications of their effects, the more outcomes and conclusions are affected. Wording ambiguity using hedging or weasel words shows that limitations affect the uncertainty of claims. The limitation index scoring method shows the diminished validity of finding(s) and conclusion(s).

INTRODUCTION

As the number of limitations in a medical research article increases, does their influence have a more significant effect than each one considered separately, making the findings and conclusions less reliable and valid? Limitations are known variables that influence data collection and findings and compromise outcomes, conclusions, and inferences. A large body of work recognizes the effect(s) and consequence(s) of limitations. 1 – 77 Other than the ones known to the author(s), unknown and unrecognized limitations influence research credibility. This study and analysis aim to determine how frequently and what limitations are found in peer-reviewed open-access medical articles for laparoscopic/endoscopic surgeons.

This research is about limitations, how often they occur and explained and/or justified. Failure to disclose limitations in medical writing limits proper decision-making and understanding of the material presented. All articles have limitations and constraints. Not acknowledging limitations is a lack of candor, ignorance, or a deliberate omission. To reduce the suspicion of invalid conclusions limitations and their effects must be acknowledged and explained. This allows for a clearer more focused assessment of the article’s subject matter without explaining its findings and conclusions using hedging and words of estimative probability. 78 , 79

An evaluation of open access research/meta-analysis/case series/methodologies/review articles published in the Journal of the Society of Laparoendoscopic and Robotic Surgery ( JSLS ) for 2021 and 2022 (129) and commentary/guidelines/new technology/practice guidelines/review/SAGES Masters Program articles in Surgical Endoscopy ( Surg Endosc ) for 2022 (169) totaling 298 were read and evaluated by automated text analysis for limitations admitted to by the paper’s authors using such words as “limitations,” “limits,” “shortcomings,” “inadequacies,” “flaws,” “weaknesses,” “constraints,” “deficiencies,” “problems,” and “drawbacks” in the search. Limitations not mentioned were found by reading the paper and assigning type and frequency. The number of hedging and weasel words used to describe the conclusion or validate findings was determined by reading the article and adding them up.

For JSLS , there were 129 articles having 63 different types of limitations. Authors claimed 476, and an additional 32 were found within the article, totaling 508 limitations (93.7% admitted to and 6.3% discovered that were not mentioned). This was a 3.9 limitation average per article. No article said it was free of limitations. The ten most frequent limitations and their rate of occurrence are in Table 1 . The total number of limitations, frequency, and visual depictions are seen in Figures 1A and ​ and 1B 1B .

( A ) Visual depiction of the ranked frequency of limitations for JSLS articles reviewed.

The Ten Most Frequent Limitations Found in JSLS and Surg Endosc Articles

There were 169 articles for Surg Endosc , with 78 different named limitations the authors claimed for a total of 1,162. An additional 94 limitations were found in the articles, totaling 1,256, or 7.4 per article. The authors explicitly stated 92.5% of the limitations, and an additional 7.5% of additional limitations were found within the article. Five claimed zero limitations (5/169 = 3%). The ten most frequent limitations and their rate of occurrence are in Table 1 . The total number of limitations and frequency is shown in Figures 1A and ​ and 1B 1B .

Conclusions were described in hedged, weasel words or words of estimative probability 95.6% of the time (285/298).

A research hypothesis aims to test the idea about expected relationships between variables or to explain an occurrence. The assessment of a hypothesis with limitations embedded in the method reaches a conclusion that is inherently flawed. What is compromised by the limitation(s)? The result is an inferential study in the presence of uncertainty. As the number of limitations increases, the validity of information decreases due to the proliferation of uncertain information. Information gathered and conclusions made in the presence of limitations can be functionally unsound. Hypothesis testing of spurious conditions with limitations and then claiming a conclusion is not a reliable method for generating factual evidence. The authors’ reliance on limitation gathered “evidence” data and asserting that this is valid is spurious reasoning. The bridge between theory and evidence is not through limitations that unquestionably accept findings. A range of conclusion possibilities exists being some percent closer to either more correct or incorrect. Relying on leveraging the pursuit of “fact” in the presence of limitations as the safeguard is akin to the fox watching the hen house. Acknowledgment of the uncertainty limitations create in research and discounting the finding’s reliability would give more credibility to the effort. Shortcomings and widespread misuses of research limitation justifications make findings suspect and falsely justified in many instances.

The JSLS instructions to authors say that in the discussion section of the paper the author(s) must “Comment on any methodological weaknesses of the study” ( http://jsls.sls.org/guidelines-for-authors/ ). In their instructions for authors, Surg Endosc says that in the discussion of the paper, “A paragraph discussing study limitations is required” ( https://www.springer.com/journal/464/submission-guidelines ). A comment for a written article about a limitation should express an opinion or reaction. A paragraph discussing limitations, especially, if there is more than one, requires just that: a paragraph and discussion. These requirements were not met or enforced by JSLS 86% (111/129) of the time and 92.3% (156/169) for Surg Endosc . This is an error in peer reviewing, not adhering to established research publication best practices, and the journals needing to adhere to their guidelines. The International Committee of Medical Journal Editors, uniform requirements for manuscripts recommends that authors “State the limitations of your study, and explore the implications of your findings for future research and for clinical practice or policy. Discuss the influence or association of variables, such as sex and/or gender, on your findings, where appropriate, and the limitations of the data.” It also says, “describe new or substantially modified methods, give reasons for using them, and evaluate their limitations” and “Include in the Discussion section the implications of the findings and their limitations, including implications for future research” and “give references to established methods, including statistical methods (see below); provide references and brief descriptions for methods that have been published but are not well known; describe new or substantially modified methods, give reasons for using them, and evaluate their limitations.” 65 “Reporting guidelines (e.g., CONSORT, 1 ARRIVE 2 ) have been proposed to promote the transparency and accuracy of reporting for biomedical studies, and they often include discussion of limitations as a checklist item. Although such guidelines have been endorsed by high-profile biomedical journals, and compliance with them is associated with improved reporting quality, 3 adherence remains suboptimal.” 4 , 5

Limitations start in the methodologic design phase of research. They require troubleshooting evaluations from the start to consider what limitations exist, what is known and unknown, where, and how to overcome them, and how they will affect the reasonableness and assessment of possible conclusions. A named limitation represents a category with numerous components. Each factor has a unique effect on findings and collectively influences conclusion assessment. Even a single limitation can compromise the study’s implementation and adversely influence research parameters, resulting in diminished value of the findings, outcomes, and conclusions. This becomes more problematic as the number of limitations and their components increase. Any limitation influences a research paper. It is unknown how much and to what extent any limitation affects other limitations, but it does create a cascading domino effect of ever-increasing interactions that compromise findings and conclusions. Considering “research” as a system, it has sensitivity and initial conditions (methodology, data collection, analysis, etc.). The slightest alteration of a study due to limitations can profoundly impact all aspects of the study. The presence and influence of limitations introduce a range of unpredictable influences on findings, results, and conclusions.

Researchers and readers need to pay attention to and discount the effects limitations have on the validity of findings. Richard Feynman said in “Cargo cult science” “the first principle is that you must not fool yourself and you are the easiest person to fool.” 73 We strongly believe our own nonsense or wrong-headed reasoning. Buddhist philosophers say we are attached to our ignorance. Researchers are not critical enough about how they fool themselves regarding their findings with known limitations and then pass them on to readers. The competence of findings with known limitations results in suspect conclusions.

Authors should not ask for dismissal, disregard, or indulgence of their limitations. They should be thoughtful and reflective about the implications and uncertainty the limitations create 67 ; their uncertainties, blind spots, and impact on the research’s relevance. A meaningful presentation of study limitations should describe the limitation, explain its effect, provide possible alternative approaches, and describe steps taken to mitigate the limitation. This was largely absent from the articles reviewed.

Authors use synonyms and phrases describing limitations that hide, deflect, downplay, and divert attention from them, i.e., some drawbacks of the study are …, weaknesses of the study are…, shortcomings are…, and disadvantages of the study are…. They then say their finding(s) lack(s) generalizability, meaning the findings only apply to the study participants or that care, sometimes extreme, must be taken in interpreting the results. Which limitation components are they referring to? Are the authors aware of the extent of their limitations, or are they using convenient phrases to highlight the existence of limitations without detailing their defects?

Limitations negatively weigh on both data and conclusions yet no literature exists to provide a quantifiable measure of this effect. The only acknowledgment is that limitations affect research data and conclusions. The adverse effects of limitations are both specific and contextual to each research article and is part of the parameters that affect research. All the limitations are expressed in words, excuses, and a litany of mea culpas asking for forgiveness and without explaining the extent or magnitude of their impact. It is left to the writer and reader to figure out. It is not known what value writers put on their limitations in the 298 articles reviewed from JSLS and Surg Endosc . Listing limitations without comment and effect on the findings and conclusions is a compromising red flag. Therefore, a limitation scoring method was developed and is proposed to assess the level of suspicion generated by the number of limitations.

It is doubtful that a medical research article is so well designed and executed that there are no limitations. This is doubtful since there are unknown unknowns. This study showed that authors need to acknowledge all the limitations when they are known. They acknowledge the ones they know but do not consider other possibilities. There are the known known limitations; the ones the author(s) are aware of and can be measured, some explained, most not. The known unknowns: limitations authors are aware of but cannot explain or quantify. The unknown unknown limitations: the ones authors are not aware of and have unknown influence(s), i.e., the things they do not know they do not know. These are blind spots (not knowing what they do not know or black swan events). And the unknown knowns; the limitations authors may be aware of but have not disclosed, thoroughly reported, understood, or addressed. They are unexpected and not considered. See Table 2 . 74

Limitations of Known and Unknowns as They Apply to Limitations

It is possible that authors did not identify, want to identify, or acknowledge potential limitations or were unaware of what limitations existed. Cumulative complexity is the result of the presence of multiple limitations because of the accumulation and interaction of limitations and their components. Just mentioning a limitation category and not the specific parts that are the limitation(s) is not enough. Authors telling readers of their known research limitations is a caution to discount the findings and conclusions. At what point does the caution for each limitation, its ramifications, and consequences become a warning? When does the piling up of mistakes, bad and missing data, biases, small sample size, lack of generalizability, confounding factors, etc., reach a point when the findings become s uninterpretable and meaningless? “Caution” indicates a level of potential hazard; a warning is more dire and consequential. Authors use the word “caution” not “warning” to describe their conclusions. There is a point when the number of limitations and their cumulative effects surpasses the point where a caution statement is no longer applicable, and a warning statement is required. This is the reason for establishing a limitations risk score.

Limitations put medical research articles at risk. The accumulation of limitations (variables having additional limitation components) are gaps and flaws diluting the probability of validity. There is currently no assessment method for evaluating the effect(s) of limitations on research outcomes other than awareness that there is an effect. Authors make statements warning that their results may not be reliable or generalizable, and need more research and larger numbers. Just because the weight effect of any given limitation is not known, explained, or how it discounts findings does not negate a causation effect on data, its analysis, and conclusions. Limitation variables and the ramifications of their effects have consequences. The relationship is not zero effect and accumulates with each added limitation.

As a result of this research, a limitation index score (LIS) system and assessment tool were developed. This limitation risk assessment tool gives a scores assessment of the relative validity of conclusions in a medical article having limitations. The adoption of the LIS scoring assessment tool for authors, researchers, editors, reviewers, and readers is a step toward understanding the effects of limitations and their causal relationships to findings and conclusions. The objective is cleaner, tighter methodologies, and better data assessment, to achieve more reliable findings. Adjustments to research conclusions in the presence of limitations are necessary. The degree of modification depends on context. The cumulative effect of this burden must be acknowledged by a tangible reduction and questioning of the legitimacy of statements made under these circumstances. The description calculating the LIS score is detailed in Appendix 1 .

A limitation word or phrase is not one limitation; it is a group of limitations under the heading of that word or phrase having many additional possible components just as an individual named influence. For instance, when an admission of selection bias is noted, the authors do not explain if it was an exclusion criterion, self-selection, nonresponsiveness, lost to follow-up, recruitment error, how it affects external validity, lack of randomization, etc., or any of the least 263 types of known biases causing systematic distortions of the truth whether unintentional or wanton. 40 , 76 Which forms of selection bias are they identifying? 63 Limitations have branches that introduce additional limitations influencing the study’s ability to reach a useful conclusion. Authors rarely tell you the effect consequences and extent limitations have on their study, findings, and conclusions.

This is a sample of limitations and a few of their component variables under the rubric of a single word or phrase. See Table 3 .

A Limitation Word or Phrase is a Limitation Having Additional Components That Are Additional Limitations. When an Author Uses the Limitation Composite Word or Phrase, They Leave out Which One of Its Components is Contributory to the Research Limitations. Each Limitation Interacts with Other Limitations, Creating a Cluster of Cross Complexities of Data, Findings, and Conclusions That Are Tainted and Negatively Affect Findings and Conclusions

Limitations rarely occur alone. If you see one there are many you do not see or appreciate. Limitation s components interact with their own and other limitations, leading to complex connections interacting and discounting the reliability of findings. By how much is context dependent: but it is not zero. Limitations are variables influencing outcomes. As the number of limitations increases, the reliability of the conclusions decreases. How many variables (limitations) does it take to nullify the claims of the findings? The weight and influence of each limitation, its aggregate components, and interconnectedness have an unknown magnitude and effect. The result is a disorderly concoction of hearsay explanations. Table 4 is an example of just two single explanation limitations and some of their components illustrating the complex compounding of their effects on each other.

An Example of Interactions between Only Two Limitations and Some of Their Components Causes 16 Interactions

The novelty of this paper on limitations in medical science is not the identification of research article limitations or their number or frequency; it is the recognition of the multiplier effect(s) limitations and the influence they have on diminishing any conclusion(s) the paper makes. It is possible that limitations contribute to the inability of studies to replicate and why so many are one-time occurrences. Therefore, the generalizability statement that should be given to all readers is BEWARE THERE IS A REDUCTION EFFECT ON THE CONCLUSIONS IN THIS ARTICLE BECAUSE OF ITS LIMITATIONS.

Journals accept studies done with too many limitations, creating forking path situations resulting in an enormous number of possible associations of individual data points as multiple comparisons. 79 The result is confusion, a muddled mess caused by interactions of limitations undermining the ability to make valid inferences. Authors know and acknowledge but rarely explain them or their influence. They also use incomplete and biased databases, biased methods, small sample sizes, and not eliminating confounders, etc., but persist in doing research with these circumstances. Why is that? Is it because when limitations are acknowledged, authors feel justified in their conclusions? It wasn’t my poor research design; it was the limitation(s). How do peer reviewers score and analyze these papers without a method to discount the findings and conclusions in the presence of limitations? What are the calculus editors use to justify papers with multiple limitations, reaching compromised or spurious conclusions? How much caution or warning should a journal say must be taken in interpreting article results? How much? Which results? When? Under what circumstance(s)?

Since a critical component of research is its limitations, the quality and rigor of research are largely defined by, 75 these constraints making it imperative that limitations be exposed and explained. All studies have limitations admitted to or not, and these limitations influence outcomes and conclusions. Unfortunately, they are given insufficient attention, accompanied by feeble excuses, but they all matter. The degrees of freedom of each limitation influence every other limitation, magnifying their ramifications and confusion. Limitations of a scientific article must put the findings in context so the reader can judge the validity and strength of the conclusions. While authors acknowledge the limitations of their study, they influence its legitimacy.

Not only are limitations not properly acknowledged in the scientific literature, 8 but their implications, magnitude, and how they affect a conclusion are not explained or appreciated. Authors work at claiming their work and methods “overcome,” “avoid,” or “circumvent” limitations. Limitations are explained away as “Failure to prove a difference does not prove lack of a difference.” 60 Sample size, bias, confounders, bad data, etc. are not what they seem and do not sully the results. The implication is “trust me.” But that’s not science. Limitations create cognitive distortions and framing (misperception of reality) for the authors and readers. Data in studies with limitations is data having limitations. It was real but tainted.

Limitations are not a trivial aspect of research. It is a tangible something, positive or negative, put into a data set to be analyzed and used to reach a conclusion. How did these extra somethings, known unknowns, not knowns, and unknown knowns, affect the validity of the data set and conclusions? Research presented with the vagaries of explicit limitations is intensified by additional limitations and their component effects on top of the first limitation s , quickly diluting any conclusion making its dependability questionable.

This study’s analysis of limitations in medical articles averaged 3.9% per article for JSLS and 7.4% for Surg Endosc . Authors admit to some and are aware of limitations, but not all of them and discount or leave out others. Limitations were often presented with misleading and hedging language. Authors do not give weight or suggest the percent discount limitations have on the reliance of conclusion(s). Since limitations influence findings, reliability, generalizability, and validity without knowing the magnitude of each and their context, the best that can be said about the conclusions is that they are specific to the study described, context-driven, and suspect.

Limitations mean something is missing, added, incorrect, unseen, unaware of, fabricated, or unknown; circumstances that confuse, confound, and compromise findings and information to the extent that a notice is necessary. All medical articles should have this statement, “Any conclusion drawn from this medical study should be interpreted considering its limitations. Readers should exercise caution, use critical judgement, and consult other sources before accepting these findings. Findings may not be generalizable regardless of sample size, composition, representative data points, and subject groups. Methodologic, analytic, and data collection may have introduced biases or limitations that can affect the accuracy of the results. Controlling for confounding variables, known and unknown, may have influenced the data and/or observations. The accuracy and completeness of the data used to draw a conclusion may not be reliable. The study was specific to time, place, persons, and prevailing circumstances. The weight of each of these factors is unknown to us. Their effect may be limited or compounded and diminish the validity of the proposed conclusions.”

This study and findings are limited and constrained by the limitations of the articles reviewed. They have known and unknown limitations not accounted for, missing data, small sample size, incongruous populations, internal and external validity concerns, confounders, and more. See Tables 2 and ​ and 3 . 3 . Some of these are correctible by the author’s awareness of the consequences of limitations, making plans to address them in the methodology phase of hypothesis assessment and performance of the research to diminish their effects.

Limitations in research articles are expected, but they can be reduced in their effect so that conclusions are closer to being valid. Limitations introduce elements of ignorance and suspicion. They need to be explained so their influence on the believability of the study and its conclusions is closer to meeting construct, content, face, and criterion validity. As the number of limitations increases, common sense, skepticism, study component acceptability, and understanding the ramifications of each limitation are necessary to accept, discount, or reject the author’s findings. As the number of hedging and weasel words used to explain conclusion(s) increases, believability decreases, and raises suspicion regarding claims. Establishing a systematic limitation scoring index limitations for authors, editors, reviewers, and readers and recognizing their cumulative effects will result in a clearer understanding of research content and legitimacy.

How to calculate the Limitation Index Score (LIS). See Tables 5 – 5 . Each limitation admitted to by authors in the article equals (=) one (1) point. Limitations may be generally stated by the author as a broad category, but can have multiple components, such as a retrospective study with these limitation components: 1. data or recall not accurate, 2. data missing, 3. selection bias not controlled, 4. confounders not controlled, 5. no randomization, 6. no blinding, 7. difficult to establish cause and effect, and 8. cannot draw a conclusion of causation. For each component, no matter how many are not explained and corrected, add an additional one (1) point to the score. See Table 2 .

The Limitation Scoring Index is a Numeric Limitation Risk Assessment Score to Rank Risk Categories and Discounting Probability of Validity and Conclusions. The More Limitations in a Study, the Greater the Risk of Unreliable Findings and Conclusions

Limitations May Be Generally Stated by the Author but Have Multiple Components, Such as a Retrospective Study Having Disadvantage Components of 1. Data or Recall Not Accurate, 2. Data Missing, 3. Selection Bias Not Controlled, 4. Confounders Not Controlled, 5. No Randomization, 6. No Blinding, 7 Difficult to Establish Cause and Effect, 8. Results Are Hypothesis Generating, and 9. Cannot Draw a Conclusion of Causation. For Each Component, Not Explained and Corrected, Add an Additional One (1) Point Is Added to the Score. Extra Blanks Are for Additional Limitations

An Automatic 2 Points is Added for Meta-Analysis Studies Since They Have All the Retrospective Detrimental Components. 44 Data from Insurance, State, National, Medicare, and Medicaid, Because of Incorrect Coding, Over Reporting, and Under-Reporting, Etc. Each Component of the Limitation Adds One Additional Point. For Surveys and Questionnaires Add One Additional Point for Each Bias. Extra Blanks Are for Additional Limitations

Automatic Five (5) Points for Manufacturer and User Facility Device Experience (MAUDE) Database Articles. The FDA Access Data Site Says Submissions Can Be “Incomplete, Inaccurate, Untimely, Unverified, or Biased” and “the Incidence or Prevalence of an Event Cannot Be Determined from This Reporting System Alone Due to Under-Reporting of Events, Inaccuracies in Reports, Lack of Verification That the Device Caused the Reported Event, and Lack of Information” and “DR Data Alone Cannot Be Used to Establish Rates of Events, Evaluate a Change in Event Rates over Time or Compare Event Rates between Devices. The Number of Reports Cannot Be Interpreted or Used in Isolation to Reach Conclusions” 80

Total Limitation Index Score

Each limitation not admitted to = two (2) points. A meta-analysis study gets an automatic 2 points since they are retrospective and have detrimental components that should be added to the 2 points. Data from insurance, state, national, Medicare, and Medicaid, because of incorrect coding, over-reporting, and underreporting, etc., score 2 points, and each component adds one additional point. Surveys and questionnaires get 2 points, and add one additional point for each bias. See Table 3 .

Manufacturer and User Facility Device Experience (MAUDE) database articles receive an automatic five (5) points. The FDA access data site says, submissions can be “incomplete, inaccurate, untimely, unverified, or biased” and “the incidence or prevalence of an event cannot be determined from this reporting system alone due to underreporting of events, inaccuracies in reports, lack of verification that the device caused the reported event, and lack of information” and “MDR data alone cannot be used to establish rates of events, evaluate a change in event rates over time or compare event rates between devices. The number of reports cannot be interpreted or used in isolation to reach conclusions.” 80 See Table 4 . Add one additional point for each additional limitation noted in the article.

Add one additional point for each additional limitation and one point for each of its components. Extra blanks are for additional

limitations and their component scores.

Funding sources: none.

Disclosure: none.

Conflict of interests: none.

Acknowledgments: Author would like to thank Lynda Davis for her help with data collection.

References:

All references have been archived at https://archive.org/web/

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

Scientific Research and Methodology : An introduction to quantitative research and statistics

9 research design limitations.

So far, you have learnt to ask a RQ and designs studies. In this chapter , you will learn to identify:

• limitations to internally valid.
• limitations to externally valid.
• limitations to ecologically valid.

9.1 Introduction

The type of study and the research design determine how the results of the study should be interpreted. Ideally, a study would be perfectly externally and internally valid; in practice this is very difficult to achieve. Practically every study has limitations. The results of a study should be interpreted in light of these limitations. Limitations are not necessarily problems .

Limitations generally can be discussed through three components:

• Internal validity (Sect. 6.1 ): Discuss any limitations to internal validity due to the research design (such as identifying possible confounding variables). This is related to the effectiveness of the study within the sample (Sect. 9.2 ).
• External validity (Sect. 5.1 ): Discuss how well the sample represents the intended population. This is related to the generalisability of the study to the intended population (Sect. 9.3 ).
• Ecological validity : Discuss how well the study methods, materials and context approximate the real situation being studied. This is related to the practicality of the results to real life (Sect. 9.4 ).

Some of these limitations are imposed by the type of study. All these issues should be addressed when considering the study limitations.

Almost every study has limitations. Identifying potential limitations, and discussing the likely impact they have on the interpretation of the study results, is important and ethical.

Example 9.1 Delarue et al. ( 2019 ) discuss studies where subjects rate the taste of new food products. They note that taste-testing studies should (p. 78):

... allow generalizing the conclusions obtained with a consumer sample [...] to the general targeted population [i.e., external validity]... tests should be reliable in terms of accuracy and replicability [i.e., internal validity].

However, even with good internal and external validity, these studies often result in a 'high rate of failures of new launched products'. That is, the studies do not replicate the real world, and so lack ecological validity .

9.2 Limitations: internal validity

Internal validity refers to the extent to which a cause-and-effect relationship can be established in a study, eliminating other possible explanations (Sect. 6.1 ). A discussion of the limitations of internal validity should cover, as appropriate: possible confounding variables; the impact of the Hawthorne, observer, placebo and carry-over effects; the impact of any other design decisions.

If any of these issues are likely to compromise internal validity, the implications on the interpretation of the results should be discussed. For example, if the participants were not blinded, this should be clearly stated, and the conclusion should indicate that the individuals in the study may have behaved differently than usual.

Example 9.2 (Study limitations) Axmann et al. ( 2020 ) randomly allocated Ugandan farmers to receive, or not receive, hybrid maize seeds. One potential threat to internal validity was that farmers receiving the hybrid seeds could share their seeds with their neighbours.

Hence, the researchers contacted the \(75\) farmers allocated to receive the hybrid seeds; none of the contacted farmers reported selling or giving seeds to other farmers. This extra step increased the internal validity of the study.

Maximizing internal validity in observational studies is more difficult than in experimental studies (e.g., random allocation is not possible). The internal validity of experimental studies involving people is often compromised because people must be informed that they are participating in a study.

Example 9.3 (Internal validity) In a study of the hand-hygiene practices of paramedics ( Barr et al. 2017 ) , self -reported hand-hygiene practices were very different than what was reported by peers . That is, how people self-report their behaviours may not align with how they actually behave, which influenced the internal validity of the study.

A study evaluated using a new therapy on elderly men, and listed some limitations of their study:

... the researcher was not blinded and had prior knowledge of the research aims, disease status, and intervention. As such, these could all have influenced data recording [...] The potential of reporting bias and observer bias could be reduced by implementing blinding in future studies. --- Kabata-Piżuch et al. ( 2021 ) , p. 10

9.3 Limitations: external validity

External validity refers to the ability to generalise the findings made from the sample to the entire intended population (Sect.  5.1 ). For a study to be externally valid, it must first be internally valid: if the study of not effective in the sample studied (i.e., internally valid), the results may not apply to the intended population either.

External validity refers to how well the sample is likely to represent the intended population in the RQ.

If the population is Iowans, then the study is externally valid if the sample is representative of Iowans The results do not have to apply to people in the rest of the United States (though this can be commented on, too). The intended population is Iowans .

External validity depends on how the sample was obtained. Results from random samples (Sects.  5.5 to  5.9 ) are likely to generalise to the population and be externally valid. (The analyses in this book assume all samples are simple random samples .) Furthermore, results from approximately representative samples (Sect.  5.10 ) may generalise to the population and be externally valid if those in the study are not obviously different than those not in the study.

Example 9.4 (External validity) A New Zealand study ( Gammon et al. 2012 ) identified (for well-documented reasons) a population of interest: 'women of South Asian origin living in New Zealand' (p. 21). The women in the sample were 'women of South Asian origin [...] recruited using a convenience sample method throughout Auckland' (p. 21).

The results may not generalise to the intended population ( all women of South Asian origin living in New Zealand) because all the women in the sample came from Auckland, and the sample was not a random sample from this population anyway. The study was still useful however!

Example 9.5 (Using biochar) Farrar et al. ( 2018 ) studied growing ginger using biochar on one farm at Mt Mellum, Australia. The results may only generalise to growing ginger at Mt Mellum, but since ginger is usually grown in similar types of climates and soils, the results may apply to other ginger farms also.

9.4 Limitations: ecological validity

The likely practicality of the study results in the real world should also be discussed. This is called ecological validity .

Definition 9.1 (Ecological validity) A study is ecologically valid if the study methods, materials and context closely approximate the real situation of interest.

Studies don't need to be ecologically valid to be useful; much can be learnt under special conditions, as long as the potential limitations are understood when applying the results to the real world. The ecological validity of experimental studies may be compromised because the experimental conditions are sometimes artificially controlled (for good reason).

Example 9.6 (Ecological validity) Consider a study to determine the proportion of people that buy coffee in a reusable cup. People could be asked about their behaviour. This study may not be ecologically valid, as how people act may not align with how they say they will act.

An alternative study could watch people buy coffees at various coffee shops, and record what people do in practice. This second study is more likely to be ecologically valid , as real-world behaviour is observed.

A study observed the effect of using high-mounted rear brake lights ( Kahane and Hertz 1998 ) , which are now commonplace. The American study showed that such lights reduced rear-end collisions by about \(50\) %. However, after making these lights mandatory, rear-end collisions reduced by only \(5\) %. Why?

9.5 Limitations: study types

Experimental studies, in general, have higher internal validity than observational studies, since more of the research design in under the control of the researchers; for example, random allocation of treatments is possible to minimise confounding.

Only well-conducted experimental studies can show cause-and-effect relationships.

However, experimental studies may suffer from poor ecological validity; for instance, laboratory experiments are often conducted under controlled temperature and humidity. Many experiments also require that people be told about being in a study (due to ethics), and so internal validity may be comprised (the Hawthorne effect).

Example 9.7 (Retrofitting) giandomenico2022systematic studied retro-fitting houses with energy-saving devices, and found large discrepancies in savings for observational studies ( \(12.2\) %) and experimental studies ( \(6.2\) %). The authors say that 'this finding reinforces the importance of using study designs with high internal validity to evaluate program savings' (p. 692).

9.6 Chapter summary

The limitations in a study need to be identified, and may be related to:

• internal validity (effectiveness): how well the study is conducted within the sample, isolating the relationship of interest.
• external validity (generalisability): how well the sample results are likely to apply to the intended population.
• ecological validity (practicality): how well the results may apply to the real-world situation.

Many of the limitations are a results of the type of study.

9.7 Quick review questions

Are the following statements true or false ?

• When interpreting the results of a study, the steps taken to maximize internal validity should be evaluated TRUE FALSE
• If studies are not externally valid, then they are not useful. TRUE FALSE
• When interpreting the results of a study, the steps taken to maximize external validity do not need to be evaluated TRUE FALSE
• When interpreting the results of a study, ecological validity is about the impact of the study on the environment. TRUE FALSE

9.8 Exercises

Answers to odd-numbered exercises are available in App.  E .

Exercise 9.1 A research study examined how people can save energy through lighting choices ( Gentile 2022 ) . The study states (p. 9) that the results 'are limited to the specific study and cannot be easily projected to other similar settings'.

What type of validity is being discussed here?

Exercise 9.2 Fill the blanks with the correct word: internal , external or ecological .

When interpreting the results of studies, we consider the practicality ( internal external ecological validity), the generalizability ( internal external ecological validity) and the effectiveness ( internal external ecological validity).

Exercise 9.3 A student project asked if 'the percentage of word retention higher in male students than female students?' When discussing external validity , the students stated:

We cannot say whether or not the general public have better or worse word retention compared to the students that we will be studying.

Why is the statement not relevant in a discussion of external validity?

Exercise 9.4 Yeh et al. ( 2018 ) conducted an experimental study to 'determine if using a parachute prevents death or major traumatic injury when jumping from an aircraft'.

The researchers randomised \(23\) volunteers into one of two groups: wearing a parachute, or wearing an empty backpack. The response variable was a measurement of death or major traumatic injury upon landing. From the study, death or major injury was the same in both groups (0% for each group). However, the study used 'small stationary aircraft on the ground, suggesting cautious extrapolation to high altitude jumps' (p. 1).

Comment on the internal, external and ecological validity.

Exercise 9.5 A study examined how well hospital patients sleep at night ( Delaney et al. 2018 ) . The researchers state that 'convenience sampling was used to recruit patients' (p. 2). Later, the researchers state (p. 7):

... while most healthy individuals sleep primarily or exclusively at night, it is important to consider that patients requiring hospitalization will likely require some daytime nap periods. This study looks at sleep only in the night-time period \(22\) : \(00\) -- \(07\) : \(00\) h, without the context of daytime sleep considered.

Discuss these issues using the language introduced in this chapter.

Exercise 9.6 Botelho et al. ( 2019 ) examined the food choices made when subjects were asked to shop for ingredients to make a last-minute meal. Half were told to prepare a 'healthy meal', and the other half told just to prepare a 'meal'. The authors stated (p. 436):

Another limitation is that results report findings from a simulated purchase. As participants did not have to pay for their selection, actual choices could be different. Participants may also have not behaved in their usual manner since they were taking part in a research study, a situation known as the Hawthorne effect.

What type of limitation is being discussed?

Exercise 9.7 Johnson et al. ( 2018 ) studied the use of over-the-counter menthol cough-drops in people with a cough. One conclusion from the observational study of \(548\) people was that, taking 'too many cough drops [...] may actually make coughs more severe', as one author explained in an interview about the study Critique this statement.

• The role of limitations in research: why they are important
• How to Organize Limitations of a Research Study

What are the Limitations of a Study (Research)?

Why and where to include limitations in my research paper, common limitations of the researchers.

• Limited Access to Information

Time Limits

Conflicts on biased views and personal issues, different types, 1. research design limitations, 2. impact limitations, 3. data or statistical limitations, how to structure your research limitations correctly, how to set your research limitations, formulation of your objectives and aims, implementation of your data collection methods, what are sample sizes, lacking previous studies in the same field, scope of discussions, concluding thoughts.

When completing a study or any other important work, there are different details that you should include to present its comprehensive and clear description. Sometimes you might even need to hire a thesis writer to help you with the whole writing process. Don’t underrate the section with limitations in research . It plays a big role in the entire process. Some students find it difficult to write this part, while others are reluctant to include it in their academic papers. Don’t underestimate the significance of limitations in research to provide readers with an accurate context of your work and enough data to evaluate the impact and relevance of your results. What is the best way to go about them? Keep reading to find out more.

Every research has its limitations. These limitations can appear due to constraints on methodology or research design. Needless to say, this may impact your whole study or research paper. Most researchers prefer to not discuss their study limitations because they think it may decrease the value of their paper in the eyes of the audience.

Remember that it’s quite important to show your study limitations to your audience (other researchers, editors of journals, and public readers). You need to notice that you know about these limitations and about the impact they may have. It’s important to give an explanation of how your research limitations can affect the conclusions and thoughts drawn from your research. 

In this guide, you can read useful tips on how to write limitations on your future research. Read great techniques on making a proper limitations section and see examples to make sure you have got an idea of writing your qualitative research limitations. You need to understand that even if limitations show the weaknesses of your future research, including them in your study can make your paper strengthen because you show all the problems before your readers will discover them by themselves. 

Apart from this, when the author points out the study limitations, it means that you have researched all the weak sides of your study and you understand the topic deeply. Needless to say, all the studies have their limitations even if you know how to make research design properly. When you’re honest with your readers, it can impress people much better than ignoring limitations at all.

Every research has certain limitations, and it’s completely normal, but you need to minimize their range of scope in the process. Provide your acknowledgment of them in the conclusion. Identify and understand potential shortcomings in your work.

When discussing limitations in research, explain how they impact your findings because creating their short list or description isn’t enough. Your research may have many limitations. Your basic goal is to discuss the ones that relate to the research questions that you choose for a specific academic assignment.

Limitations of your qualitative research can become clear to your readers even before they start to read your study. Sometimes, people can see the limitations only when they have viewed the whole document. You have to present your study limitations clearly in the Discussion section of a researh paper . This is the final part of your work where it’s logical to place the limitations section. You should write the limitations at the very beginning of this paragraph, just after you have highlighted the strong sides of the research methodology. When you discuss the limitations before the findings are analyzed, it will help to see how to qualify and apply these findings in future research.   

Limitations related to the researcher must also be written and shown to readers. You have to provide suggestions on decreasing these limitations in both your and future studies.

Limited Access to Information 

Your study may involve some organizations and people in the research, and sometimes you may get problems with access to these organizations. Due to this, you need to redesign and rewrite your study. You need to explain the cause of limited access to your readers.

Needless to say, all the researchers have their deadlines when they need to complete their studies. Sometimes, time constraints can affect your research negatively. If this happened, you need to acknowledge it and mention a need for future research to solve the main problem. 

Some researchers can have biased views because of their cultural background or personal views. Needless to say, it can affect the research. Apart from this, researchers with biased views can choose only those results and data that support their main arguments. If you want to avoid this problem, pay your attention to the problem statement and proper data gathering.

Before you start your study or work, keep in mind that there are specific limitations to what you test or possible research results. What are their types? There are different types that students may encounter and they all have unique features, including:

• Research design limitations,
• Impact limitations,
• Data or statistical limitations.

Specific constraints on your population research or available procedures may affect the final outcomes or results that you obtain.

Even if your research has excellent stats and a strong design, it may suffer from the impact of such factors as:

• The field is conductive to incremental findings,
• Being too population-specific.
• A strong regional focus.

In some cases, it’s impossible to collect enough data or enrollment is very difficult, and all that under-powers your research results. They may stem from your study design. They produce more issues in interpreting your findings.

There are strict rules to structure this section of your academic paper where you need to justify and explain its potential weaknesses. Take these basic steps to end up with a well-structured section:

• Announce to identify your research limitations and explain their importance,
• Reflect to provide the necessary depth, explain their nature, and justify your study choices,
• Look forward to suggest how it’s possible to overcome them in the future.

They walk your readers through this section. You need them to make it clear to your target audience that you recognize potential weaknesses in your work, understand them, and can point effective solutions.

No one is perfect. It means that your work isn’t beyond possible flaws, but you need to use them as a great opportunity to overcome new challenges and improve your knowledge. In a typical academic paper, research limitations can relate to these points:

• Formulation of your objectives and aims,
• Implementation of your data collection methods,
• Sample sizes,
• Lack of previous studies in your chosen area,
• The scope of discussions.

Learn to determine them in each one.

Your work has certain shortcomings if you formulate objectives and aims in a very broad manner. What to do in this case? Specify effective methods or ways to narrow your formulation of objectives and aims to increase the level of your study focus.

If you don’t have a lot of experience in collecting primary data, there’s a certain risk that the implementation of your methods has flaws. It’s necessary to acknowledge that.

They depend on the nature of your chosen problem and their significance is bigger in quantitative studies, unlike the qualitative ones. If your sample size is very small, statistical tests will fail to identify important relationships or connections within a particular data set. How to solve this problem? State that other researchers need to base the same study on a larger sample size to end up with more accurate results. To find more information on how to identify a resesrch problem , check our guide. 

Writing a literature review is a key step in any scientific work because it helps students determine the scope of existing studies in the chosen area. Why should you use the literature review findings? They are a basic foundation for any researcher who must use them to achieve a set of specific objectives or aims. What if there are no previous works? You may face this challenge if you choose an evolving or current problem for your study or if it’s very narrow.

Feel free to include this point as a shortcoming of your work, no matter what your chosen area is. Why? The main reason is that you don’t have long years of experience in writing scientific papers or completing complex studies. That’s why the depth and scope of your discussions can be compromised in different levels compared to scholars with a lot of expertise. Include certain points from limitations in research. Use them as suggestions for the future.

Any research suffers from specific limitations that range from common flaws to serious problems in design or methodology dissertation has. The ability to set these shortcomings plays a huge role in writing a successful academic paper and earning good grades. What if you lack it? Turn to our professional thesis writers and get their expert consultation on thesis or research paper.

What comes first, the research design or research problem selection? Read on this guide from our dissertation writing service if you are struggling to answer this question. Any research paper is based on the hypothesis, datum, and methodology. These things though are not written down in the instruct...

The methodology is an important part of your dissertation. It describes a broad philosophical underpinning to your chosen research methods, either quantitative or qualitative, to explain to readers your approach better. Make sure that you’re clear about an academic basis for your choice of research ...

Students have to complete different writing assignments, and some of them are utterly complex. Every assignment has the central idea or problem, which is supposed to be discussed and analyzed during the entire work. It’s called a thesis statement. The main objective of the statement is to explain to...

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.

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Research Implications & Recommendations

A Plain-Language Explainer With Examples + FREE Template

By: Derek Jansen (MBA) | Reviewers: Dr Eunice Rautenbach | May 2024

The research implications and recommendations are closely related but distinctly different concepts that often trip students up. Here, we’ll unpack them using plain language and loads of examples , so that you can approach your project with confidence.

Overview: Implications & Recommendations

• What are research implications ?
• What are research recommendations ?
• Examples of implications and recommendations
• The “ Big 3 ” categories
• How to write the implications and recommendations
• Template sentences for both sections
• Key takeaways

Implications & Recommendations 101

Let’s start with the basics and define our terms.

At the simplest level, research implications refer to the possible effects or outcomes of a study’s findings. More specifically, they answer the question, “ What do these findings mean?” . In other words, the implications section is where you discuss the broader impact of your study’s findings on theory, practice and future research.

This discussion leads us to the recommendations section , which is where you’ll propose specific actions based on your study’s findings and answer the question, “ What should be done next?” . In other words, the recommendations are practical steps that stakeholders can take to address the key issues identified by your study.

In a nutshell, then, the research implications discuss the broader impact and significance of a study’s findings, while recommendations provide specific actions to take, based on those findings. So, while both of these components are deeply rooted in the findings of the study, they serve different functions within the write up.

Need a helping hand?

Examples: Implications & Recommendations

The distinction between research implications and research recommendations might still feel a bit conceptual, so let’s look at one or two practical examples:

Let’s assume that your study finds that interactive learning methods significantly improve student engagement compared to traditional lectures. In this case, one of your recommendations could be that schools incorporate more interactive learning techniques into their curriculums to enhance student engagement.

Let’s imagine that your study finds that patients who receive personalised care plans have better health outcomes than those with standard care plans. One of your recommendations might be that healthcare providers develop and implement personalised care plans for their patients.

Now, these are admittedly quite simplistic examples, but they demonstrate the difference (and connection ) between the research implications and the recommendations. Simply put, the implications are about the impact of the findings, while the recommendations are about proposed actions, based on the findings.

The “Big 3” Categories

Now that we’ve defined our terms, let’s dig a little deeper into the implications – specifically, the different types or categories of research implications that exist.

Broadly speaking, implications can be divided into three categories – theoretical implications, practical implications and implications for future research .

Theoretical implications relate to how your study’s findings contribute to or challenge existing theories. For example, if a study on social behaviour uncovers new patterns, it might suggest that modifications to current psychological theories are necessary.

Practical implications , on the other hand, focus on how your study’s findings can be applied in real-world settings. For example, if your study demonstrated the effectiveness of a new teaching method, this would imply that educators should consider adopting this method to improve learning outcomes.

Practical implications can also involve policy reconsiderations . For example, if a study reveals significant health benefits from a particular diet, an implication might be that public health guidelines be re-evaluated.

Last but not least, there are the implications for future research . As the name suggests, this category of implications highlights the research gaps or new questions raised by your study. For example, if your study finds mixed results regarding a relationship between two variables, it might imply the need for further investigation to clarify these findings.

To recap then, the three types of implications are the theoretical, the practical and the implications on future research. Regardless of the category, these implications feed into and shape the recommendations , laying the foundation for the actions you’ll propose.

How To Write The  Sections

Now that we’ve laid the foundations, it’s time to explore how to write up the implications and recommendations sections respectively.

Let’s start with the “ where ” before digging into the “ how ”. Typically, the implications will feature in the discussion section of your document, while the recommendations will be located in the conclusion . That said, layouts can vary between disciplines and institutions, so be sure to check with your university what their preferences are.

For the implications section, a common approach is to structure the write-up based on the three categories we looked at earlier – theoretical, practical and future research implications. In practical terms, this discussion will usually follow a fairly formulaic sentence structure – for example:

This research provides new insights into [theoretical aspect], indicating that…

The study’s outcomes highlight the potential benefits of adopting [specific practice] in..

This study raises several questions that warrant further investigation, such as…

Moving onto the recommendations section, you could again structure your recommendations using the three categories. Alternatively, you could structure the discussion per stakeholder group – for example, policymakers, organisations, researchers, etc.

Again, you’ll likely use a fairly formulaic sentence structure for this section. Here are some examples for your inspiration: 

Based on the findings, [specific group] should consider adopting [new method] to improve…

To address the issues identified, it is recommended that legislation should be introduced to…

Researchers should consider examining [specific variable] to build on the current study’s findings.

Remember, you can grab a copy of our tried and tested templates for both the discussion and conclusion sections over on the Grad Coach blog. You can find the links to those, as well as loads of other free resources, in the description 🙂

FAQs: Implications & Recommendations

How do i determine the implications of my study.

To do this, you’ll need to consider how your findings address gaps in the existing literature, how they could influence theory, practice, or policy, and the potential societal or economic impacts.

When thinking about your findings, it’s also a good idea to revisit your introduction chapter, where you would have discussed the potential significance of your study more broadly. This section can help spark some additional ideas about what your findings mean in relation to your original research aims. 

Should I discuss both positive and negative implications?

Absolutely. You’ll need to discuss both the positive and negative implications to provide a balanced view of how your findings affect the field and any limitations or potential downsides.

Can my research implications be speculative?

Yes and no. While implications are somewhat more speculative than recommendations and can suggest potential future outcomes, they should be grounded in your data and analysis. So, be careful to avoid overly speculative claims.

How do I formulate recommendations?

Ideally, you should base your recommendations on the limitations and implications of your study’s findings. So, consider what further research is needed, how policies could be adapted, or how practices could be improved – and make proposals in this respect.

How specific should my recommendations be?

Your recommendations should be as specific as possible, providing clear guidance on what actions or research should be taken next. As mentioned earlier, the implications can be relatively broad, but the recommendations should be very specific and actionable. Ideally, you should apply the SMART framework to your recommendations.

Can I recommend future research in my recommendations?

Absolutely. Highlighting areas where further research is needed is a key aspect of the recommendations section. Naturally, these recommendations should link to the respective section of your implications (i.e., implications for future research).

Wrapping Up: Key Takeaways

We’ve covered quite a bit of ground here, so let’s quickly recap.

• Research implications refer to the possible effects or outcomes of a study’s findings.
• The recommendations section, on the other hand, is where you’ll propose specific actions based on those findings.
• You can structure your implications section based on the three overarching categories – theoretical, practical and future research implications.
• You can carry this structure through to the recommendations as well, or you can group your recommendations by stakeholder.

Remember to grab a copy of our tried and tested free dissertation template, which covers both the implications and recommendations sections. If you’d like 1:1 help with your research project, be sure to check out our private coaching service, where we hold your hand throughout the research journey, step by step.

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• Getting started
• Criteria for a problem formulation
• Find who and what you are looking for
• Too broad, too narrow, or o.k.?
• Test your knowledge
• Lesson 5: Meeting your supervisor
• Getting started: summary
• Literature search
• Searching for articles
• Searching for Data
• Databases provided by your library
• Other useful search tools
• Free text, truncating and exact phrase
• Combining search terms – Boolean operators
• Keep track of your search strategies
• Problems finding your search terms?
• Different sources, different evaluations
• Extract by relevance
• Lesson 4: Obtaining literature
• Literature search: summary
• Research methods
• Combining qualitative and quantitative methods
• Collecting data
• Analysing data

Strengths and limitations

• Explanatory, analytical and experimental studies
• The Nature of Secondary Data
• How to Conduct a Systematic Review
• Directional Policy Research
• Strategic Policy Research
• Operational Policy Research
• Conducting Research Evaluation
• Research Methods: Summary
• Project management
• Project budgeting
• Data management plan
• Quality Control
• Project control
• Project management: Summary
• Writing process
• Title page, abstract, foreword, abbreviations, table of contents
• Introduction, methods, results
• Discussion, conclusions, recomendations, references, appendices, layout
• Use citations correctly
• Use references correctly
• Bibliographic software
• Writing process – summary
• Research methods /
• Lesson 1: Qualitative and quan… /

Quantitative method Quantitive data are pieces of information that can be counted and which are usually gathered by surveys from large numbers of respondents randomly selected for inclusion. Secondary data such as census data, government statistics, health system metrics, etc. are often included in quantitative research. Quantitative data is analysed using statistical methods. Quantitative approaches are best used to answer what, when and who questions and are not well suited to how and why questions.

Qualitative method Qualitative data are usually gathered by observation, interviews or focus groups, but may also be gathered from written documents and through case studies.  In qualitative research there is less emphasis on counting numbers of people who think or behave in certain ways and more emphasis on explaining why people think and behave in certain ways.  Participants in qualitative studies often involve smaller numbers of tools include and utilizes open-ended questionnaires interview guides.  This type of research is best used to answer how and why questions and is not well suited to generalisable what, when and who questions.

Learn more about using quantitative and qualitative approaches in various study types in the next lesson.

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Limitations and Weaknesses of Quantitative Research

• Post author: Edeh Samuel Chukwuemeka ACMC
• Post published: August 16, 2021
• Post category: Scholarly Articles

Limitations and Weaknesses of Quantitative Research: Research entails the collection of materials for  academic or other purposes. It is a process of gathering information and data to solve or existing problem or prevent future problems. Research works can be done via two methods. Qualitative research or quantitative research.

Qualitative research involves the carrying out of research by gathering non-numerical data. For example, gathering of video evidence, texts or messages for analysis. On the other hand, quantitative research is the process where by numerical data are collected and analyzed. It is effectively used to find patterns and averages as well as generalising a finding or result to a wider population. Quantitative research is mostly used in natural and social sciences such as biology, psychology, economics, among others.

Quantitative research could be carried out using any four methods of researching which are descriptive research, correlational research, experimental research or survey research. In descriptive, one seeks to know the ‘what’ of a thing rather than the ‘why’ of such thing. It tries to describe the various components of an information.

Correlational research involves the research between two variables to ascertain the relationship between the variables. It understudies the impact of one variable on the other. On the other hand, an experimental research is one that uses scientific methods to establish the relationship between groups of variables. That is, it tries to establish a cause-effect relationship between the various variables under study.

Recommended: How to become a good researcher: 5 qualities you need to have.

Finally, the survey research which is most widely used involves the preparation of set questionnaires, interviews and polls to which answers are provided by a segment of the target population and then, conclusions are drawn from such answers given. Survey research studies the relationship between various variables in a given research.

One of the major benefit of  quantitative research method is that it makes one arrive at a well considered conclusion since samples are collected from those who are directly affected by the research. The data collected are majorly converted to a numerical form which aids in statistical analysis. Also, quantitative research is more convenient for projects with scientific and social science inclinations.

Also see: Advantages and Disadvantages of quantitative and qualitative Research

Weaknesses of Quantitative Research

Notwithstanding the benefits of quantitative research, the research method has its own weaknesses and limitations. This is because the method is not applicable and convenient in all cases of research. Thus, using a quantitative research method in a research where qualitative research method should be used will not produce the needed result.

To this end, some of the weaknesses and limitations of quantitative research are highlighted below.

1. It Requires a Large Number of Respondents: In the course of carrying out a quantitative research, recourse has to be made to a large number of respondents. This is because you are sampling a section of a population to get their views, which views will be seen as that of the general population. In doing this, a huge number of respondents have to be consulted so as to get a fair view or percentage of the target population.

For example, if one wishes to carry out a quantitative research in Nigeria as to her acceptance of a policy of the government, one will need to consult wider. This is because Nigeria has a population of over 200 million people and the opinions of a few thousands cannot pass out as that of 200 million people. In the light of this, more respondents will be required to be interviewed so as to enable one get a fair view of the population.

Large number of respondents is thus, one of the weaknesses or limitations of quantitative research as a small sampling of a section of the target population might not be of much help to the research.

2. It is time consuming: Unlike qualitative research which has to do with analysis of already prepared data, quantitative research demands that you source for and collate the data yourself while converting such data collected into a numerical form for proper analysis. This process is time consuming. Again, the task of sending out questionnaires to respondents and waiting for answers to such questionnaires might be time consuming as most respondents will reply late or may not even reply at all.

Great patience is therefore needed in carrying out a quantitative research. It is therefore not always a good method of research in cases of urgencies as the time to get responses might take too long.

Also see: Major characteristics of customary laws

3. It requires huge resources: Quantitative research requires huge investment of time, money and energy. It is time consuming just as it also involve huge financial commitments.

In carrying out quantitative research, one needs to get your questions prepared, sent out and also followed up to ensure that such is answered. Also, some respondents might demand to be paid before giving their inputs to such a research. An example is the trending online surveys in which the target respondents are paid for every survey they carry out for a researcher.

4. Difficulty in Analyzing the Data Collected: Data are collected from respondents and then converted into statistics. This usually poses as a limitation to a researcher who is not an expert in statistics. Analysis of collected data is also demanding and time consuming. A researcher needs to make such information collected into numerical data and correlate them with the larger population. Where this is not properly done, it means that the outcome might be false or misleading.

Also, due to the fact that a researcher might not have control over the environment he is researching in, as any such environment is susceptible to change at any point in time, the outcome of his research might be inconsistent.

Recommended: Problems and criticism of democracy

5. Outcomes of quantitative research is usually limited: In quantitative research, the outcomes are usually limited. This is because the outcome is usually based on what the researcher wants. This limited outcome is due to the structured pattern of the questionnaires. Questionnaires usually have close ended questions which gives a respondent little or no opportunity of explanations. Thus, the answers provided are limited to the questions asked and nothing more.

6. Data outcomes are usually generalised : As noted earlier, quantitative research is usually conducted on a section of a target population and not on the whole population. The outcome of this research is then generalised as the view of the entire population. What this portends is that the views of  few respondents in that research is seen as that of the general populace. Such views from them might be biased or insincere, yet they are seen as that of the entire population.

In the light of this, the fallacy of hasty generalisation is prone to be committed in a quantitative research. Generalisation of the views of a section of the population might not be the best as their views may be biased.

Recommended: Advantages and Disadvantages of Capitalism

In conclusion, quantitative research is a veritable means of conducting research especially in the fields of natural sciences and social sciences. This is because it mostly has a one on one interaction between the researcher and the various respondents as it majorly studies behavior. This advantage notwithstanding, the research method has its own  limitations and weaknesses. These limitations and weaknesses often times affect the quality of a research which is done using the quantitative method of research.

Edeh Samuel Chukwuemeka, ACMC, is a lawyer and a certified mediator/conciliator in Nigeria. He is also a developer with knowledge in various programming languages. Samuel is determined to leverage his skills in technology, SEO, and legal practice to revolutionize the legal profession worldwide by creating web and mobile applications that simplify legal research. Sam is also passionate about educating and providing valuable information to people.

Limitations that Hinder the Successful Application of a Knowledge Management Model in Research Centers in a Higher Education Institution

• Conference paper
• First Online: 13 May 2024
• Cite this conference paper

• Verónica Martínez-Lazcano   ORCID: orcid.org/0000-0003-2172-4000 14 ,
• Claudia Isabel Martínez-Alcalá   ORCID: orcid.org/0000-0003-0847-5150 15 ,
• Iliana Castillo-Pérez   ORCID: orcid.org/0000-0002-8130-9231 14 &
• Edgar Alexander Prieto-Barboza   ORCID: orcid.org/0000-0003-4817-5195 16  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 987))

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Knowledge management plays an important role in both organizations and higher education institutions, as they generate knowledge and through the implementation of a knowledge management model, it allows new knowledge to be generated. However, there are organizational and technological limitations or difficulties that may arise during the application of a knowledge management model in research centers of higher education institutions. The methodology of this research consisted of the application of a questionnaire with predefined questions using a Likert scale. The reliability analysis of the instrument was carried out using Cronbach’s alpha coefficient applied to the identified limiting factors, obtaining a value of 0.93. In this study, seven organizational and technological limitations that arise during the application of a knowledge management model in higher education institutions were analyzed. The results identified areas of opportunity in five of the seven limitations to successfully implement a knowledge management model in research centers of higher education institutions.

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Verónica Martínez-Lazcano & Iliana Castillo-Pérez

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Gintautas Dzemyda

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Institute of Information Technology, Lodz University of Technology, Łódz, Poland

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Martínez-Lazcano, V., Martínez-Alcalá, C.I., Castillo-Pérez, I., Prieto-Barboza, E.A. (2024). Limitations that Hinder the Successful Application of a Knowledge Management Model in Research Centers in a Higher Education Institution. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Poniszewska-Marańda, A. (eds) Good Practices and New Perspectives in Information Systems and Technologies. WorldCIST 2024. Lecture Notes in Networks and Systems, vol 987. Springer, Cham. https://doi.org/10.1007/978-3-031-60221-4_4

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Procrastination, depression and anxiety symptoms in university students: a three-wave longitudinal study on the mediating role of perceived stress

• Anna Jochmann 1 ,
• Burkhard Gusy 1 ,
• Tino Lesener 1 &
• Christine Wolter 1  

BMC Psychology volume  12 , Article number:  276 ( 2024 ) Cite this article

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It is generally assumed that procrastination leads to negative consequences. However, evidence for negative consequences of procrastination is still limited and it is also unclear by which mechanisms they are mediated. Therefore, the aim of our study was to examine the harmful consequences of procrastination on students’ stress and mental health. We selected the procrastination-health model as our theoretical foundation and tried to evaluate the model’s assumption that trait procrastination leads to (chronic) disease via (chronic) stress in a temporal perspective. We chose depression and anxiety symptoms as indicators for (chronic) disease and hypothesized that procrastination leads to perceived stress over time, that perceived stress leads to depression and anxiety symptoms over time, and that procrastination leads to depression and anxiety symptoms over time, mediated by perceived stress.

To examine these relationships properly, we collected longitudinal data from 392 university students at three occasions over a one-year period and analyzed the data using autoregressive time-lagged panel models.

Procrastination did lead to depression and anxiety symptoms over time. However, perceived stress was not a mediator of this effect. Procrastination did not lead to perceived stress over time, nor did perceived stress lead to depression and anxiety symptoms over time.

Conclusions

We could not confirm that trait procrastination leads to (chronic) disease via (chronic) stress, as assumed in the procrastination-health model. Nonetheless, our study demonstrated that procrastination can have a detrimental effect on mental health. Further health outcomes and possible mediators should be explored in future studies.

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Introduction

“Due tomorrow? Do tomorrow.”, might be said by someone who has a tendency to postpone tasks until the last minute. But can we enjoy today knowing about the unfinished task and tomorrow’s deadline? Or do we feel guilty for postponing a task yet again? Do we get stressed out because we have little time left to complete it? Almost everyone has procrastinated at some point when it came to completing unpleasant tasks, such as mowing the lawn, doing the taxes, or preparing for exams. Some tend to procrastinate more frequently and in all areas of life, while others are less inclined to do so. Procrastination is common across a wide range of nationalities, as well as socioeconomic and educational backgrounds [ 1 ]. Over the last fifteen years, there has been a massive increase in research on procrastination [ 2 ]. Oftentimes, research focuses on better understanding the phenomenon of procrastination and finding out why someone procrastinates in order to be able to intervene. Similarly, the internet is filled with self-help guides that promise a way to overcome procrastination. But why do people seek help for their procrastination? Until now, not much research has been conducted on the negative consequences procrastination could have on health and well-being. Therefore, in the following article we examine the effect of procrastination on mental health over time and stress as a possible facilitator of this relationship on the basis of the procrastination-health model by Sirois et al. [ 3 ].

Procrastination and its negative consequences

Procrastination can be defined as the tendency to voluntarily and irrationally delay intended activities despite expecting negative consequences as a result of the delay [ 4 , 5 ]. It has been observed in a variety of groups across the lifespan, such as students, teachers, and workers [ 1 ]. For example, some students tend to regularly delay preparing for exams and writing essays until the last minute, even if this results in time pressure or lower grades. Procrastination must be distinguished from strategic delay [ 4 , 6 ]. Delaying a task is considered strategic when other tasks are more important or when more resources are needed before the task can be completed. While strategic delay is viewed as functional and adaptive, procrastination is classified as dysfunctional. Procrastination is predominantly viewed as the result of a self-regulatory failure [ 7 ]. It can be understood as a trait, that is, as a cross-situational and time-stable behavioral disposition [ 8 ]. Thus, it is assumed that procrastinators chronically delay tasks that they experience as unpleasant or difficult [ 9 ]. Approximately 20 to 30% of adults have been found to procrastinate chronically [ 10 , 11 , 12 ]. Prevalence estimates for students are similar [ 13 ]. It is believed that students do not procrastinate more often than other groups. However, it is easy to examine procrastination in students because working on study tasks requires a high degree of self-organization and time management [ 14 ].

It is generally assumed that procrastination leads to negative consequences [ 4 ]. Negative consequences are even part of the definition of procrastination. Research indicates that procrastination is linked to lower academic performance [ 15 ], health impairment (e.g., stress [ 16 ], physical symptoms [ 17 ], depression and anxiety symptoms [ 18 ]), and poor health-related behavior (e.g., heavier alcohol consumption [ 19 ]). However, most studies targeting consequences of procrastination are cross-sectional [ 4 ]. For that reason, it often remains unclear whether an examined outcome is a consequence or an antecedent of procrastination, or whether a reciprocal relationship between procrastination and the examined outcome can be assumed. Additionally, regarding negative consequences of procrastination on health, it is still largely unknown by which mechanisms they are mediated. Uncovering such mediators would be helpful in developing interventions that can prevent negative health consequences of procrastination.

The procrastination-health model

The first and only model that exclusively focuses on the effect of procrastination on health and the mediators of this effect is the procrastination-health model [ 3 , 9 , 17 ]. Sirois [ 9 ] postulates three pathways: An immediate effect of trait procrastination on (chronic) disease and two mediated pathways (see Fig.  1 ).

Adopted from the procrastination-health model by Sirois [ 9 ]

The immediate effect is not further explained. Research suggests that procrastination creates negative feelings, such as shame, guilt, regret, and anger [ 20 , 21 , 22 ]. The described feelings could have a detrimental effect on mental health [ 23 , 24 , 25 ].

The first mediated pathway leads from trait procrastination to (chronic) disease via (chronic) stress. Sirois [ 9 ] assumes that procrastination creates stress because procrastinators are constantly aware of the fact that they still have many tasks to complete. Stress activates the hypothalamic-pituitary-adrenocortical (HPA) system, increases autonomic nervous system arousal, and weakens the immune system, which in turn contributes to the development of diseases. Sirois [ 9 ] distinguishes between short-term and long-term effects of procrastination on health mediated by stress. She believes that, in the short term, single incidents of procrastination cause acute stress, which leads to acute health problems, such as infections or headaches. In the long term, chronic procrastination, as you would expect with trait procrastination, causes chronic stress, which leads to chronic diseases over time. There is some evidence in support of the stress-related pathway, particularly regarding short-term effects [ 3 , 17 , 26 , 27 , 28 ]. However, as we mentioned above, most of these studies are cross-sectional. Therefore, the causal direction of these effects remains unclear. To our knowledge, long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress have not yet been investigated.

The second mediated pathway leads from trait procrastination to (chronic) disease via poor health-related behavior. According to Sirois [ 9 ], procrastinators form lower intentions to carry out health-promoting behavior or to refrain from health-damaging behavior because they have a low self-efficacy of being able to care for their own health. In addition, they lack the far-sighted view that the effects of health-related behavior only become apparent in the long term. For the same reason, Sirois [ 9 ] believes that there are no short-term, but only long-term effects of procrastination on health mediated by poor health-related behavior. For example, an unhealthy diet leads to diabetes over time. The findings of studies examining the behavioral pathway are inconclusive [ 3 , 17 , 26 , 28 ]. Furthermore, since most of these studies are cross-sectional, they are not suitable for uncovering long-term effects of trait procrastination on (chronic) disease mediated by poor health-related behavior.

In summary, previous research on the two mediated pathways of the procrastination-health model mainly found support for the role of (chronic) stress in the relationship between trait procrastination and (chronic) disease. However, only short-term effects have been investigated so far. Moreover, longitudinal studies are needed to be able to assess the causal direction of the relationship between trait procrastination, (chronic) stress, and (chronic) disease. Consequently, our study is the first to examine long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress, using a longitudinal design. (Chronic) disease could be measured by a variety of different indicators (e.g., physical symptoms, diabetes, or coronary heart disease). We choose depression and anxiety symptoms as indicators for (chronic) disease because they signal mental health complaints before they manifest as (chronic) diseases. Additionally, depression and anxiety symptoms are two of the most common mental health complaints among students [ 29 , 30 ] and procrastination has been shown to be a significant predictor of depression and anxiety symptoms [ 18 , 31 , 32 , 33 , 34 ]. Until now, the stress-related pathway of the procrastination-health model with depression and anxiety symptoms as the health outcome has only been analyzed in one cross-sectional study that confirmed the predictions of the model [ 35 ].

The aim of our study is to evaluate some of the key assumptions of the procrastination-health model, particularly the relationships between trait procrastination, (chronic) stress, and (chronic) disease over time, surveyed in the following analysis using depression and anxiety symptoms.

In line with the key assumptions of the procrastination-health model, we postulate (see Fig.  2 ):

Procrastination leads to perceived stress over time.

Perceived stress leads to depression and anxiety symptoms over time.

Procrastination leads to depression and anxiety symptoms over time, mediated by perceived stress.

The section of the procrastination-health model we examined

Materials and methods

Our study was part of a health monitoring at a large German university Footnote 1 . Ethical approval for our study was granted by the Ethics Committee of the university’s Department of Education and Psychology. We collected the initial data in 2019. Two occasions followed, each at an interval of six months. In January 2019, we sent out 33,267 invitations to student e-mail addresses. Before beginning the survey, students provided their written informed consent to participate in our study. 3,420 students took part at the first occasion (T1; 10% response rate). Of these, 862 participated at the second (T2) and 392 at the third occasion (T3). In order to test whether dropout was selective, we compared sociodemographic and study specific characteristics (age, gender, academic semester, number of assessments/exams) as well as behavior and health-related variables (procrastination, perceived stress, depression and anxiety symptoms) between the participants of the first wave ( n  = 3,420) and those who participated three times ( n  = 392). Results from independent-samples t-tests and chi-square analysis showed no significant differences regarding sociodemographic and study specific characteristics (see Additional file 1: Table S1 and S2 ). Regarding behavior and health-related variables, independent-samples t-tests revealed a significant difference in procrastination between the two groups ( t (3,409) = 2.08, p  < .05). The mean score of procrastination was lower in the group that participated in all three waves.

The mean age of the longitudinal respondents was 24.1 years ( SD  = 5.5 years), the youngest participants were 17 years old, the oldest one was 59 years old. The majority of participants was female (74.0%), 7 participants identified neither as male nor as female (1.8%). The respondents were on average enrolled in the third year of studying ( M  = 3.9; SD  = 2.3). On average, the students worked about 31.2 h ( SD  = 14.1) per week for their studies, and an additional 8.5 h ( SD  = 8.5) for their (part-time) jobs. The average income was €851 ( SD  = 406), and 4.9% of the students had at least one child. The students were mostly enrolled in philosophy and humanities (16.5%), education and psychology (15.8%), biology, chemistry, and pharmacy (12.5%), political and social sciences (10.6%), veterinary medicine (8.9%), and mathematics and computer science (7.7%).

We only used established and well evaluated instruments for our analyses.

• Procrastination

We adopted the short form of the Procrastination Questionnaire for Students (PFS-4) [ 36 ] to measure procrastination. The PFS-4 assesses procrastination at university as a largely stable behavioral disposition across situations, that is, as a trait. The questionnaire consists of four items (e.g., I put off starting tasks until the last moment.). Each item was rated on a 5-point scale ((almost) never = 1 to (almost) always = 5) for the last two weeks. All items were averaged, with higher scores indicating a greater tendency to procrastinate. The PFS-4 has been proven to be reliable and valid, showing very high correlations with other established trait procrastination scales, for example, with the German short form of the General Procrastination Scale [ 37 , 38 ]. We also proved the scale to be one-dimensional in a factor analysis, with a Cronbach’s alpha of 0.90.

Perceived stress

The Heidelberger Stress Index (HEI-STRESS) [ 39 ] is a three-item measure of current perceived stress due to studying as well as in life in general. For the first item, respondents enter a number between 0 (not stressed at all) and 100 (completely stressed) to indicate how stressed their studies have made them feel over the last four weeks. For the second and third item, respondents rate on a 5-point scale how often they feel “stressed and tense” and as how stressful they would describe their life at the moment. We transformed the second and third item to match the range of the first item before we averaged all items into a single score with higher values indicating greater perceived stress. We proved the scale to be one-dimensional and Cronbach’s alpha for our study was 0.86.

Depression and anxiety symptoms

We used the Patient Health Questionnaire-4 (PHQ-4) [ 40 ], a short form of the Patient Health Questionnaire [ 41 ] with four items, to measure depression and anxiety symptoms. The PHQ-4 contains two items from the Patient Health Questionnaire-2 (PHQ-2) [ 42 ] and the Generalized Anxiety Disorder Scale-2 (GAD-2) [ 43 ], respectively. It is a well-established screening scale designed to assess the core criteria of major depressive disorder (PHQ-2) and generalized anxiety disorder (GAD-2) according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). However, it was shown that the GAD-2 is also appropriate for screening other anxiety disorders. According to Kroenke et al. [ 40 ], the PHQ-4 can be used to assess a person’s symptom burden and impairment. We asked the participants to rate how often they have been bothered over the last two weeks by problems, such as “Little interest or pleasure in doing things”. Response options were 0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day. Calculated as the sum of the four items, the total scores range from 0 to 12 with higher scores indicating more frequent depression and anxiety symptoms. The total scores can be categorized as none-to-minimal (0–2), mild (3–5), moderate (6–8), and severe (9–12) depression and anxiety symptoms. The PHQ-4 was shown to be reliable and valid [ 40 , 44 , 45 ]. We also proved the scale to be one-dimensional in a factor analysis, with a Cronbach’s alpha of 0.86.

Data analysis

To test our hypotheses, we performed structural equation modelling (SEM) using R (Version 4.1.1) with the package lavaan. All items were standardized ( M  = 0, SD  = 1). Due to the non-normality of some study variables and a sufficiently large sample size of N near to 400 [ 46 ], we used robust maximum likelihood estimation (MLR) for all model estimations. As recommended by Hu and Bentler [ 47 ], we assessed the models’ goodness of fit by chi-square test statistic, root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), Tucker-Lewis index (TLI), and comparative fit index (CFI). A non-significant chi-square indicates good model fit. Since chi-square is sensitive to sample size, we also evaluated fit indices less sensitive to the number of observations. RMSEA and SRMR values of 0.05 or lower as well as TLI and CFI values of 0.97 or higher indicate good model fit. RMSEA values of 0.08 or lower, SRMR values of 0.10 or lower, as well as TLI and CFI values of 0.95 or higher indicate acceptable model fit [ 48 , 49 ]. First, we conducted confirmatory factor analysis for the first occasion, defining three factors that correspond to the measures of procrastination, perceived stress, and depression and anxiety symptoms. Next, we tested for measurements invariance over time and specified the measurement model, before testing our hypotheses.

Measurement invariance over time

To test for measurement invariance over time, we defined one latent variable for each of the three occasions, corresponding to the measures of procrastination, perceived stress, and depression and anxiety symptoms, respectively. As recommended by Geiser and colleagues [ 50 ], the links between indicators and factors (i.e., factor loadings and intercepts) should be equal over measurement occasions; therefore, we added indicator specific factors. A first and least stringent step of testing measurement invariance is configural invariance (M CI ). It was examined whether the included constructs (procrastination, perceived stress, depression and anxiety symptoms) have the same pattern of free and fixed loadings over time. This means that the assignment of the indicators to the three latent factors over time is supported by the underlying data. If configural invariance was supported, restrictions for the next step of testing measurement invariance (metric or weak invariance; M MI ) were added. This means that each item contributes to the latent construct to a similar degree over time. Metric invariance was tested by constraining the factor loadings of the constructs over time. The next step of testing measurement invariance (scalar or strong invariance; M SI ) consisted of checking whether mean differences in the latent construct capture all mean differences in the shared variance of the items. Scalar invariance was tested by constraining the item intercepts over time. The constraints applied in the metric invariance model were retained [ 51 ]. For the last step of testing measurement invariance (residual or strict invariance; M RI ), the residual variables were also set equal over time. If residual invariance is supported, differences in the observed variables can exclusively be attributed to differences in the variances of the latent variables.

We used the Satorra-Bentler chi-square difference test to evaluate the superiority of a more stringent model [ 52 ]. We assumed the model with the largest number of invariance restrictions – which still has an acceptable fit and no substantial deterioration of the chi-square value – to be the final model [ 53 ]. Following previous recommendations, we considered a decrease in CFI of 0.01 and an increase in RMSEA of 0.015 as unacceptable to establish measurement invariance [ 54 ]. If a more stringent model had a significant worse chi-square value, but the model fit was still acceptable and the deterioration in model fit fell within the change criteria recommended for CFI and RMSEA values, we still considered the more stringent model to be superior.

Hypotheses testing

As recommended by Dormann et al. [ 55 ], we applied autoregressive time-lagged panel models to test our hypotheses. In the first step, we specified a model (M 0 ) that only included the stabilities of the three variables (procrastination, perceived stress, depression and anxiety symptoms) over time. In the next step (M 1 ), we added the time-lagged effects from procrastination (T1) to perceived stress (T2) and from procrastination (T2) to perceived stress (T3) as well as from perceived stress (T1) to depression and anxiety symptoms (T2) and from perceived stress (T2) to depression and anxiety symptoms (T3). Additionally, we included a direct path from procrastination (T1) to depression and anxiety symptoms (T3). If this path becomes significant, we can assume a partial mediation [ 55 ]. Otherwise, we can assume a full mediation. We compared these nested models using the Satorra-Bentler chi-square difference test and the Akaike information criterion (AIC). The chi-square difference value should either be non-significant, indicating that the proposed model including our hypotheses (M 1 ) does not have a significant worse model fit than the model including only stabilities (M 0 ), or, if significant, it should be in the direction that M 1 fits the data better than M 0 . Regarding the AIC, M 1 should have a lower value than M 0 .

Table  1 displays the means, standard deviations, internal consistencies (Cronbach’s alpha), and stabilities (correlations) of all study variables. The alpha values of procrastination, perceived stress, and depression and anxiety symptoms are classified as good (> 0.80) [ 56 ]. The correlation matrix of the manifest variables used for the analyses can be found in the Additional file 1: Table  S3 .

We observed the highest test-retest reliabilities for procrastination ( r  ≥ .74). The test-retest reliabilities for depression and anxiety symptoms ( r  ≥ .64) and for perceived stress ( r  ≥ .54) were a bit lower (see Table  1 ). The pattern of correlations shows a medium to large but positive relationship between procrastination and depression and anxiety symptoms [ 57 , 58 ]. The association between procrastination and perceived stress was small, the one between perceived stress and depression and anxiety symptoms very large (see Table  1 ).

Confirmatory factor analysis showed an acceptable to good fit (x 2 (41) = 118.618, p  < .001; SRMR = 0.042; RMSEA = 0.071; TLI = 0.95; CFI = 0.97). When testing for measurement invariance over time for each construct, the residual invariance models with indicator specific factors provided good fit to the data (M RI ; see Table  2 ), suggesting that differences in the observed variables can exclusively be attributed to differences of the latent variables. We then specified and tested the measurement model of the latent constructs prior to model testing based on the items of procrastination, perceived stress, and depression and anxiety symptoms. The measurement model fitted the data well (M M ; see Table  3 ). All items loaded solidly on their respective factors (0.791 ≤ β ≤ 0.987; p  < .001).

To test our hypotheses, we analyzed the two models described in the methods section.

The fit of the stability model (M 0 ) was acceptable (see Table  3 ). Procrastination was stable over time, with stabilities above 0.82. The stabilities of perceived stress as well as depression and anxiety symptoms were somewhat lower, ranging from 0.559 (T1 -> T2) to 0.696 (T2 -> T3) for perceived stress and from 0.713 (T2 -> T3) to 0.770 (T1 -> T2) for depression and anxiety symptoms, respectively.

The autoregressive mediation model (M 1 ) fitted the data significantly better than M 0 . The direct path from procrastination (T1) to depression and anxiety symptoms (T3) was significant (β = 0.16; p  < .001), however, none of the mediated paths (from procrastination (T1) to perceived stress (T2) and from perceived stress (T2) to depression and anxiety symptoms (T3)) proved to be substantial. Also, the time-lagged paths from perceived stress (T1) to depression and anxiety symptoms (T2) and from procrastination (T2) to perceived stress (T3) were not substantial either (see Fig.  3 ).

To examine whether the hypothesized effects would occur over a one-year period rather than a six-months period, we specified an additional model with paths from procrastination (T1) to perceived stress (T3) and from perceived stress (T1) to depression and anxiety symptoms (T3), also including the stabilities of the three constructs as in the stability model M 0 . The model showed an acceptable fit (χ 2 (486) = 831.281, p  < .001; RMSEA = 0.048; SRMR = 0.091; TLI = 0.95; CFI = 0.95), but neither of the two paths were significant.

Therefore, our hypotheses, that procrastination leads to perceived stress over time (H1) and that perceived stress leads to depression and anxiety symptoms over time (H2) must be rejected. We could only partially confirm our third hypothesis, that procrastination leads to depression and anxiety over time, mediated by perceived stress (H3), since procrastination did lead to depression and anxiety symptoms over time. However, this effect was not mediated by perceived stress.

Results of the estimated model including all hypotheses (M 1 ). Note Non-significant paths are dotted. T1 = time 1; T2 = time 2; T3 = time 3. *** p  < .001

To sum up, we tried to examine the harmful consequences of procrastination on students’ stress and mental health. Hence, we selected the procrastination-health model by Sirois [ 9 ] as a theoretical foundation and tried to evaluate some of its key assumptions in a temporal perspective. The author assumes that trait procrastination leads to (chronic) disease via (chronic) stress. We chose depression and anxiety symptoms as indicators for (chronic) disease and postulated, in line with the key assumptions of the procrastination-health model, that procrastination leads to perceived stress over time (H1), that perceived stress leads to depression and anxiety symptoms over time (H2), and that procrastination leads to depression and anxiety symptoms over time, mediated by perceived stress (H3). To examine these relationships properly, we collected longitudinal data from students at three occasions over a one-year period and analyzed the data using autoregressive time-lagged panel models. Our first and second hypotheses had to be rejected: Procrastination did not lead to perceived stress over time, and perceived stress did not lead to depression and anxiety symptoms over time. However, procrastination did lead to depression and anxiety symptoms over time – which is in line with our third hypothesis – but perceived stress was not a mediator of this effect. Therefore, we could only partially confirm our third hypothesis.

Our results contradict previous studies on the stress-related pathway of the procrastination-health model, which consistently found support for the role of (chronic) stress in the relationship between trait procrastination and (chronic) disease. Since most of these studies were cross-sectional, though, the causal direction of these effects remained uncertain. There are two longitudinal studies that confirm the stress-related pathway of the procrastination-health model [ 27 , 28 ], but both studies examined short-term effects (≤ 3 months), whereas we focused on more long-term effects. Therefore, the divergent findings may indicate that there are short-term, but no long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress.

Our results especially raise the question whether trait procrastination leads to (chronic) stress in the long term. Looking at previous longitudinal studies on the effect of procrastination on stress, the following stands out: At shorter study periods of two weeks [ 27 ] and four weeks [ 28 ], the effect of procrastination on stress appears to be present. At longer study periods of seven weeks [ 59 ], three months [ 28 ], six months, and twelve months, as in our study, the effect of procrastination on stress does not appear to be present. There is one longitudinal study in which procrastination was a significant predictor of stress symptoms nine months later [ 34 ]. The results of this study should be interpreted with caution, though, because the outbreak of the COVID-19 pandemic fell within the study period, which could have contributed to increased stress symptoms [ 60 ]. Unfortunately, Johansson et al. [ 34 ] did not report whether average stress symptoms increased during their study. In one of the two studies conducted by Fincham and May [ 59 ], the COVID-19 pandemic outbreak also fell within their seven-week study period. However, they reported that in their study, average stress symptoms did not increase from baseline to follow-up. Taken together, the findings suggest that procrastination can cause acute stress in the short term, for example during times when many tasks need to be completed, such as at the end of a semester, but that procrastination does not lead to chronic stress over time. It seems possible that students are able to recover during the semester from the stress their procrastination caused at the end of the previous semester. Because of their procrastination, they may also have more time to engage in relaxing activities, which could further mitigate the effect of procrastination on stress. Our conclusions are supported by an early and well-known longitudinal study by Tice and Baumeister [ 61 ], which compared procrastinating and non-procrastinating students with regard to their health. They found that procrastinators experienced less stress than their non-procrastinating peers at the beginning of the semester, but more at the end of the semester. Additionally, our conclusions are in line with an interview study in which university students were asked about the consequences of their procrastination [ 62 ]. The students reported that, due to their procrastination, they experience high levels of stress during periods with heavy workloads (e.g., before deadlines or exams). However, the stress does not last, instead, it is relieved immediately after these periods.

Even though research indicates, in line with the assumptions of the procrastination-health model, that stress is a risk factor for physical and mental disorders [ 63 , 64 , 65 , 66 ], perceived stress did not have a significant effect on depression and anxiety symptoms in our study. The relationship between stress and mental health is complex, as people respond to stress in many different ways. While some develop stress-related mental disorders, others experience mild psychological symptoms or no symptoms at all [ 67 ]. This can be explained with the help of vulnerability-stress models. According to vulnerability-stress models, mental illnesses emerge from an interaction of vulnerabilities (e.g., genetic factors, difficult family backgrounds, or weak coping abilities) and stress (e.g., minor or major life events or daily hassles) [ 68 , 69 ]. The stress perceived by the students in our sample may not be sufficient enough on its own, without the presence of other risk factors, to cause depression and anxiety symptoms. However, since we did not assess individual vulnerability and stress factors in our study, these considerations are mere speculation.

In our study, procrastination led to depression and anxiety symptoms over time, which is consistent with the procrastination-health model as well as previous cross-sectional and longitudinal evidence [ 18 , 21 , 31 , 32 , 33 , 34 ]. However, it is still unclear by which mechanisms this effect is mediated, as perceived stress did not prove to be a substantial mediator in our study. One possible mechanism would be that procrastination impairs affective well-being [ 70 ] and creates negative feelings, such as shame, guilt, regret, and anger [ 20 , 21 , 22 , 62 , 71 ], which in turn could lead to depression and anxiety symptoms [ 23 , 24 , 25 ]. Other potential mediators of the relationship between procrastination and depression and anxiety symptoms emerge from the behavioral pathway of the procrastination-health model, suggesting that poor health-related behaviors mediate the effect of trait procrastination on (chronic) disease. Although evidence for this is still scarce, the results of one cross-sectional study, for example, indicate that poor sleep quality might mediate the effect of procrastination on depression and anxiety symptoms [ 35 ].

In summary, we found that procrastination leads to depression and anxiety symptoms over time and that perceived stress is not a mediator of this effect. We could not show that procrastination leads to perceived stress over time, nor that perceived stress leads to depression and anxiety symptoms over time. For the most part, the relationships between procrastination, perceived stress, and depression and anxiety symptoms did not match the relationships between trait procrastination, (chronic) stress, and (chronic) disease as assumed in the procrastination-health model. Explanations for this could be that procrastination might only lead to perceived stress in the short term, for example, during preparations for end-of-semester exams, and that perceived stress may not be sufficient enough on its own, without the presence of other risk factors, to cause depression and anxiety symptoms. In conclusion, we could not confirm long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress, as assumed for the stress-related pathway of the procrastination-health model.

Limitations and suggestions for future research

In our study, we tried to draw causal conclusions about the harmful consequences of procrastination on students’ stress and mental health. However, since procrastination is a trait that cannot be manipulated experimentally, we have conducted an observational rather than an experimental study, which makes causal inferences more difficult. Nonetheless, a major strength of our study is that we used a longitudinal design with three waves. This made it possible to draw conclusions about the causal direction of the effects, as in hardly any other study targeting consequences of procrastination on health before [ 4 , 28 , 55 ]. Therefore, we strongly recommend using a similar longitudinal design in future studies on the procrastination-health model or on consequences of procrastination on health in general.

We chose a time lag of six months between each of the three measurement occasions to examine long-term effects of procrastination on depression and anxiety symptoms mediated by perceived stress. However, more than six months may be necessary for the hypothesized effects to occur [ 72 ]. The fact that the temporal stabilities of the examined constructs were moderate or high (0.559 ≤ β ≤ 0.854) [ 73 , 74 ] also suggests that the time lags may have been too short. The larger the time lag, the lower the temporal stabilities, as shown for depression and anxiety symptoms, for example [ 75 ]. High temporal stabilities make it more difficult to detect an effect that actually exists [ 76 ]. Nonetheless, Dormann and Griffin [ 77 ] recommend using shorter time lags of less than one year, even with high stabilities, because of other influential factors, such as unmeasured third variables. Therefore, our time lags of six months seem appropriate.

It should be discussed, though, whether it is possible to detect long-term effects of the stress-related pathway of the procrastination-health model within a total study period of one year. Sirois [ 9 ] distinguishes between short-term and long-term effects of procrastination on health mediated by stress, but does not address how long it might take for long-term effects to occur or when effects can be considered long-term instead of short-term. The fact that an effect of procrastination on stress is evident at shorter study periods of four weeks or less but in most cases not at longer study periods of seven weeks or more, as we mentioned earlier, could indicate that short-term effects occur within the time frame of one to three months, considering the entire stress-related pathway. Hence, it seems appropriate to assume that we have examined rather long-term effects, given our study period of six and twelve months. Nevertheless, it would be beneficial to use varying study periods in future studies, in order to be able to determine when effects can be considered long-term.

Concerning long-term effects of the stress-related pathway, Sirois [ 9 ] assumes that chronic procrastination causes chronic stress, which leads to chronic diseases over time. The term “chronic stress” refers to prolonged stress episodes associated with permanent tension. The instrument we used captures perceived stress over the last four weeks. Even though the perceived stress of the students in our sample was relatively stable (0.559 ≤ β ≤ 0.696), we do not know how much fluctuation occurred between each of the three occasions. However, there is some evidence suggesting that perceived stress is strongly associated with chronic stress [ 78 ]. Thus, it seems acceptable that we used perceived stress as an indicator for chronic stress in our study. For future studies, we still suggest the use of an instrument that can more accurately reflect chronic stress, for example, the Trier Inventory for Chronic Stress (TICS) [ 79 ].

It is also possible that the occasions were inconveniently chosen, as they all took place in a critical academic period near the end of the semester, just before the examination period began. We chose a similar period in the semester for each occasion for the sake of comparability. However, it is possible that, during this preparation periods, stress levels peaked and procrastinators procrastinated less because they had to catch up after delaying their work. This could have introduced bias to the data. Therefore, in future studies, investigation periods should be chosen that are closer to the beginning or in the middle of a semester.

Furthermore, Sirois [ 9 ] did not really explain her understanding of “chronic disease”. However, it seems clear that physical illnesses, such as diabetes or cardiovascular diseases, are meant. Depression and anxiety symptoms, which we chose as indicators for chronic disease, represent mental health complaints that do not have to be at the level of a major depressive disorder or an anxiety disorder, in terms of their quantity, intensity, or duration [ 40 ]. But they can be viewed as precursors to a major depressive disorder or an anxiety disorder. Therefore, given our study period of one year, it seems appropriate to use depression and anxiety symptoms as indicators for chronic disease. At longer study periods, we would expect these mental health complaints to manifest as mental disorders. Moreover, the procrastination-health model was originally designed to be applied to physical diseases [ 3 ]. Perhaps, the model assumptions are more applicable to physical diseases than to mental disorders. By applying parts of the model to mental health complaints, we have taken an important step towards finding out whether the model is applicable to mental disorders as well. Future studies should examine additional long-term health outcomes, both physical and psychological. This would help to determine whether trait procrastination has varying effects on different diseases over time. Furthermore, we suggest including individual vulnerability and stress factors in future studies in order to be able to analyze the effect of (chronic) stress on (chronic) diseases in a more differentiated way.

Regarding our sample, 3,420 students took part at the first occasion, but only 392 participated three times, which results in a dropout rate of 88.5%. At the second and third occasion, invitation e-mails were only sent to participants who had indicated at the previous occasion that they would be willing to participate in a repeat survey and provided their e-mail address. This is probably one of the main reasons for our high dropout rate. Other reasons could be that the students did not receive any incentives for participating in our study and that some may have graduated between the occasions. Selective dropout analysis revealed that the mean score of procrastination was lower in the group that participated in all three waves ( n  = 392) compared to the group that participated in the first wave ( n  = 3,420). One reason for this could be that those who have a higher tendency to procrastinate were more likely to procrastinate on filling out our survey at the second and third occasion. The findings of our dropout analysis should be kept in mind when interpreting our results, as lower levels of procrastination may have eliminated an effect on perceived stress or on depression and anxiety symptoms. Additionally, across all age groups in population-representative samples, the student age group reports having the best subjective health [ 80 ]. Therefore, it is possible that they are more resilient to stress and experience less impairment of well-being than other age groups. Hence, we recommend that future studies focus on other age groups as well.

It is generally assumed that procrastination leads to lower academic performance, health impairment, and poor health-related behavior. However, evidence for negative consequences of procrastination is still limited and it is also unclear by which mechanisms they are mediated. In consequence, the aim of our study was to examine the effect of procrastination on mental health over time and stress as a possible facilitator of this relationship. We selected the procrastination-health model as a theoretical foundation and used the stress-related pathway of the model, assuming that trait procrastination leads to (chronic) disease via (chronic) stress. We chose depression and anxiety symptoms as indicators for (chronic) disease and collected longitudinal data from students at three occasions over a one-year period. This allowed us to draw conclusions about the causal direction of the effects, as in hardly any other study examining consequences of procrastination on (mental) health before. Our results indicate that procrastination leads to depression and anxiety symptoms over time and that perceived stress is not a mediator of this effect. We could not show that procrastination leads to perceived stress over time, nor that perceived stress leads to depression and anxiety symptoms over time. Explanations for this could be that procrastination might only lead to perceived stress in the short term, for example, during preparations for end-of-semester exams, and that perceived stress may not be sufficient on its own, that is, without the presence of other risk factors, to cause depression and anxiety symptoms. Overall, we could not confirm long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress, as assumed for the stress-related pathway of the procrastination-health model. Our study emphasizes the importance of identifying the consequences procrastination can have on health and well-being and determining by which mechanisms they are mediated. Only then will it be possible to develop interventions that can prevent negative health consequences of procrastination. Further health outcomes and possible mediators should be explored in future studies, using a similar longitudinal design.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

University Health Report at Freie Universität Berlin.

Abbreviations

Comparative fit index

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Generalized Anxiety Disorder Scale-2

Heidelberger Stress Index

Hypothalamic-pituitary-adrenocortical

Robust maximum likelihood estimation

Short form of the Procrastination Questionnaire for Students

Patient Health Questionnaire-2

Patient Health Questionnaire-4

Root mean square error of approximation

Structural equation modeling

Standardized root mean square residual

Tucker-Lewis index

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Conceptualization: A.J., B.G., T.L.; methodology: B.G., A.J.; validation: B.G.; formal analysis: A.J., B.G.; investigation: C.W., T.L., B.G.; data curation: C.W., T.L., B.G.; writing–original draft preparation: A.J., B.G.; writing–review and editing: A.J., T.L., B.G., C.W.; visualization: A.J., B.G.; supervision: B.G., T.L.; project administration: C.W., T.L., B.G.; All authors contributed to the article and approved the submitted version.

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Jochmann, A., Gusy, B., Lesener, T. et al. Procrastination, depression and anxiety symptoms in university students: a three-wave longitudinal study on the mediating role of perceived stress. BMC Psychol 12 , 276 (2024). https://doi.org/10.1186/s40359-024-01761-2

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Affiliation Department of Biomedical and Neuromotor Science, Alma Mater Studiorum–University of Bologna, Bologna, Italy

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Affiliation Department of Translational Medicine, University of Eastern Piedmont, (UNIUPO), Novara, Italy

Roles Conceptualization, Data curation, Writing – review & editing

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

Affiliation IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma Neurochirurgia Ipofisi—Pituitary Unit, Bologna, Italy

• Angelo Capodici, 
• Gabriele Mocciaro, 
• Davide Gori, 
• Matthew J. Landry, 
• Alice Masini, 
• Francesco Sanmarchi, 
• Matteo Fiore, 
• Angela Andrea Coa, 
• Gisele Castagna, 

• Published: May 15, 2024
• https://doi.org/10.1371/journal.pone.0300711
• Reader Comments

Cardiovascular diseases (CVDs) and cancer are the two main leading causes of death and disability worldwide. Suboptimal diet, poor in vegetables, fruits, legumes and whole grain, and rich in processed and red meat, refined grains, and added sugars, is a primary modifiable risk factor. Based on health, economic and ethical concerns, plant-based diets have progressively widespread worldwide.

This umbrella review aims at assessing the impact of animal-free and animal-products-free diets (A/APFDs) on the risk factors associated with the development of cardiometabolic diseases, cancer and their related mortalities.

Data sources

PubMed and Scopus were searched for reviews, systematic reviews, and meta-analyses published from 1st January 2000 to 31st June 2023, written in English and involving human subjects of all ages. Primary studies and reviews/meta-analyses based on interventional trials which used A/APFDs as a therapy for people with metabolic diseases were excluded.

Data extraction

The umbrella review approach was applied for data extraction and analysis. The revised AMSTAR-R 11-item tool was applied to assess the quality of reviews/meta-analyses.

Overall, vegetarian and vegan diets are significantly associated with better lipid profile, glycemic control, body weight/BMI, inflammation, and lower risk of ischemic heart disease and cancer. Vegetarian diet is also associated with lower mortality from CVDs. On the other hand, no difference in the risk of developing gestational diabetes and hypertension were reported in pregnant women following vegetarian diets. Study quality was average. A key limitation is represented by the high heterogeneity of the study population in terms of sample size, demography, geographical origin, dietary patterns, and other lifestyle confounders.

Conclusions

Plant-based diets appear beneficial in reducing cardiometabolic risk factors, as well as CVDs, cancer risk and mortality. However, caution should be paid before broadly suggesting the adoption of A/AFPDs since the strength-of-evidence of study results is significantly limited by the large study heterogeneity alongside the potential risks associated with potentially restrictive regimens.

Citation: Capodici A, Mocciaro G, Gori D, Landry MJ, Masini A, Sanmarchi F, et al. (2024) Cardiovascular health and cancer risk associated with plant based diets: An umbrella review. PLoS ONE 19(5): e0300711. https://doi.org/10.1371/journal.pone.0300711

Editor: Melissa Orlandin Premaor, Federal University of Minas Gerais: Universidade Federal de Minas Gerais, BRAZIL

Received: January 8, 2024; Accepted: March 4, 2024; Published: May 15, 2024

Copyright: © 2024 Capodici et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Cardiovascular diseases (CVDs) and cancer currently represent the leading causes of death and disability worldwide. Studies performed on large cohorts worldwide have identified several modifiable and non-modifiable risk factors. Among them, robust evidence supports diet as a major modifiable risk factor [ 1 ].

A suboptimal diet, marked by insufficient consumption of fruits, vegetables, legumes, and whole grains, coupled with an excessive intake of meat (particularly red and processed), salt, refined grains and sugar, has been shown to notably elevate both mortality rates and disability-adjusted life years. Over time, these dietary choices have led to a concerning increase in health-related issues [ 1 , 2 ].

Additionally, the reduction of products of animal origin in favor of vegetarian ones has been suggested to reduce CVD and cancer risk [ 3 , 4 ]. Several major professional and scientific organizations encourage the adoption of vegetarian and vegan diets for the prevention and treatment of a range of chronic metabolic diseases such as atherosclerosis, type 2 diabetes, hypertension and obesity [ 5 , 6 ]. Ethical, environmental, and socio-economic concerns have contributed to the widespread growth of plant-based diets, particularly vegetarian and vegan options [ 7 – 9 ]. 2014 cross-national governmental survey estimated that approximately 75 million people around the globe deliberately followed a vegetarian diet, while an additional 1,45 million were obliged to because of socio-economic factors [ 10 , 11 ].

At the same time, study heterogeneity in terms of plant-based dietary regimens (from limitation of certain types to the total exclusion of animal products), their association with other lifestyle factors, patient demographic and geographical features, associated diseases, as well as study design and duration, significantly limit the assessment of the real benefits associated with animal-free and animal-products-free diets (A/APFDs). Finally, an increasing number of studies have highlighted the potential threatening consequences of chronic vitamin and mineral deficiencies induced by these diets (e.g., megaloblastic anemia due to vitamin B12 deficiency), especially more restrictive ones and in critical periods of life, like pregnancy and early childhood [ 5 ].

Based on these premises, our umbrella review aims at assessing the impact of animal-free and animal-products-free diets (A/APFDs) on the risk factors associated with the development of cardiometabolic diseases, cancer and their related mortalities in both the adult and the pediatric population, as well as pregnant women.

Search strategy

PubMed ( https://pubmed.ncbi.nlm.nih.gov/ ) and Scopus ( https://www.scopus.com/search/form.uri?display=basic#basic ) databases were searched for reviews, systematic reviews and meta-analyses published from 1st January 2000 to 31st June 2023. We considered only articles written in English, involving human subjects, with an available abstract, and answering to the following PICO question: P (population): people of all ages; I (intervention) and C (comparison): people adopting A/APFDs vs. omnivores; O (outcome): impact of A/APFD on health parameters associated with CVDs, metabolic disorders or cancer.

Articles not specifying the type of A/APFD regimen were excluded. If not detailed, the A/APFDs adopted by study participants was defined as “mixed diet”. Vegetarian diets limiting but not completely excluding certain types of meat/fish (i.e. pesco- or pollo-vegetarian diet) were excluded. Studies focusing on subjects with specific nutritional needs (i.e., athletes or military personnel) -except pregnant women-, or with known underlying chronic diseases (i.e., chronic kidney disease), as well as articles focusing on conditions/health parameters related to disorders different from CVDs or cancer, and, finally, reviews/meta-analyses including interventional studies assessing A/APFDs comparing it with pharmacological interventions were excluded.

Ad hoc literature search strings, made of a broad selection of terms related to A/APFDs, including PubMed MeSH-terms, free-text words and their combinations, combined by proper Boolean operators, were created to search PubMed database: ((vegetari* OR vegan OR Diet , Vegetarian[MH] OR fruitar* OR veganism OR raw-food* OR lacto-veget* OR ovo-vege* OR semi-veget* OR plant-based diet* OR vegetable-based diet* OR fruit-based diet* OR root-based diet OR juice-based diet OR non-meat eate* OR non-meat diet*) AND ((review[Publication Type]) OR (meta-analysis[Publication Type]))) AND (("2000/01/01"[Date—Publication] : "2023/06/31"[Date—Publication])) and Scopus database: ALL(vegetari* OR vegan OR Diet , Vegetarian OR fruitar* OR veganism OR raw-food* OR lacto-veget* OR ovo-vege* OR semi-veget* OR plant-based diet* OR vegetable-based diet* OR fruit-based diet* OR root-based diet OR juice-based diet OR non-meat eate* OR non-meat diet) AND SUBJAREA(MEDI OR NURS OR VETE OR DENT OR HEAL OR MULT) PUBYEAR > 1999 AND (LIMIT-TO (DOCTYPE , "re"))

Research design and study classification

An umbrella review approach [ 12 ] was applied to systematically assess the effect of A/APFDs on risk factors related to CVDs, metabolic disorders and cancer as derived from literature reviews, systematic reviews and meta-analyses ( Table 1 ).

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https://doi.org/10.1371/journal.pone.0300711.t001

Study selection

The list of articles identified by literature search was split into 5 equivalent parts, each assigned to a couple of readers (AC, DG, CW, ML, AM, FS, MF, AAC, GC and FG), who independently and blindly read the title and then the abstract of each article to define its pertinence. Papers included in the umbrella review had to focus on one/some of the following A/APFDs: vegans, lacto-vegetarians, ovo-vegetarians, lacto-ovo-vegetarians. No restriction was applied for age, gender, ethnicity, geographical origin, nor socio economic status. Primary studies, reviews/meta-analyses not written in English, or focusing on non-previously mentioned dietary regimens (including the Mediterranean diet) were excluded. Abstract meetings, editorials, letters to the editor, and study protocols were also excluded. To reduce study heterogeneity, at least in terms of dietary regimens, we excluded studies based on vegetarian regimens limiting but not avoiding fish or poultry, and prospective trials directly comparing A/AFPDs to pharmacological interventions.

In case of discordance between readers, we resorted to discussion amongst the authors to resolve it, based on the article’s abstract or, if not decisive, the full text. The study selection process is summarized in Fig 1 .

https://doi.org/10.1371/journal.pone.0300711.g001

This review was registered on PROSPERO (Record ID: 372913 https://www.crd.york.ac.uk /prospero/display_record.php?RecordID=372913 ).

Quality literature analysis

Three raters (AC, DG, FS) independently and blindly assessed the quality of the systematic reviews and meta-analyses using the revised AMSTAR-R 11-item tool, developed by the PEROSH group [ 13 ]. In case of disagreement, the score of each item and the final decision were discussed among the three raters.

Data extraction and reporting

Ten investigators (AC, DG, GM, ML, AM, FS, MF, AAC, GC, FG) independently extracted data from eligible articles. Disagreements in data extraction were resolved by consensus. Using a predefined protocol and a Microsoft Excel sheet, the following data were extracted: first author’s affiliation country; type of review; type of diet; target population; number of aggregated participants; total cholesterol; HDL-cholesterol; LDL-cholesterol; triglycerides; apolipoprotein B; C-Reactive Protein (CRP); Body Mass Index (BMI); body weight; fasting glucose; glycosylated hemoglobin (HbA1c); systolic blood pressure; diastolic blood pressure; cardiac events (type; risk); cardiovascular diseases (type; risk); gestational diabetes; gestational hypertension; cancer (type; risk); death due to CVDs/cancer (risk). Data were reported as mean difference (MD), weighted mean difference (WMD), standardized mean difference (SMD), and 95%CI, while the estimated risk could be reported as relative risk (RR), odds ratio (OR), or hazard ratio (HR), according to the data reported by the study authors. Articles assessing the risk of gestational diabetes and hypertension, as well as risk of low birth weight, and their determinants were examined separately.

Results from studies focusing on both vegetarian and vegan diets were analyzed and reported separately if authors had stratified the results according to the type of diet. On the contrary, if data from vegan and vegetarian subjects were mixed, we arbitrarily considered all of them as “vegetarian”.

Group 1: Cardiovascular endpoints and risk factors

I. total cholesterol (tc)..

Eight studies examined the levels of total serum cholesterol (TC) in vegetarians. Two focused on the general population and included 5,561 [ 14 ] and 576 [ 15 ] respectively, and, based on data meta-analysis, found a significant reduction in TC among vegetarians and people who assumed plant-based proteins (MD: -1.56 mmol/L; 95%CI: −1.73, −1.39; and -0.11 mmol/L; 95%CI: −0.22, −0.01, respectively).

Data were confirmed by Wang et al. (N = 832 total; Ovolacto/lacto-vegetarians: 291) [ 16 ], showing a greater dietary effect in subjects with a BMI ranging from 18.5 to 25 kg/m 2 (mean TC reduction: −0.94 mmol/L; 95%CI: −1.33, −0.55), and from 25 to 30 kg/m 2 (−0.58 mmol/L; 95%CI: −0.89, −0.27), than in those with a BMI >30 kg/m 2 (−0.16 mmol/L; 95%CI: −0.30, −0.01), and by Xu et al. (N = 783) [ 17 ], reporting lower TC in overweight and obese people (WMD: −0.37 mmol/L; 95%CI: −0.52, −0.22) adopting a vegetarian diet.

Another systematic review by Elliott et al., including 27 randomized controlled trials on plant based vs. normal western diets [ 18 ], found lower TC levels in vegetarians. These results were in line with other two descriptive reviews, the first including 2,890 overweight/obese adults [ 19 ], the second 8,969 vegetarian children aged 0–18 years [ 20 ]. Furthermore, a meta-analysis by Liang et al. described significantly lower TC (from -0.36 to -0.24 mmol/L) in people adopting plant based diets vs. people adopting western habitual diets [ 21 ].

Moreover, the review and meta-analysis by Dinu et al. [ 14 ], based on 19 studies for a total of 1,272 adults, reported significantly lower levels of TC among vegans than in omnivores (WMD: −1.72 mmol/L; 95%CI: −1.93, −1.51).

II. High-density lipoprotein cholesterol (HDL-C).

Eight reviews focused on the effects of vegetarian diet on serum high-density lipoprotein cholesterol (HDL-C) levels. Six [ 15 , 17 , 18 , 21 – 23 ] found no significant difference between vegetarians and omnivores, when considering normal weight and overweight/obese people. On the contrary, the study by Dinu et al. [ 14 ], based on 51 studies, for a total of 6,194 vegetarian adults, reported a WMD −0.15 mmol/L (95%CI: −0.19, −0.11). Liang et al. [ 21 ] analyzed 4 studies and reported a pooled estimated MD of −0.10 mmol/L (95%CI: −0.14, −0.05; p<0.001) in vegetarian diet adopters vs. western diets adopters. Finally, Zhang et al. [ 22 ] did not find any statistically significant differences in HDL-C levels when assessing vegetarian diets compared to non-vegetarians; on the same note Dinu et al. [ 14 ], analyzing data from 15 studies, for a total of 1,175 adults, found no significant differences in HDL-C levels between vegans and people following other dietary regimens.

III. Low-density lipoprotein cholesterol (LDL-C).

Ten reviews summarized the effect of vegetarian diets on serum levels of low-density lipoprotein cholesterol (LDL-C). Seven [ 14 – 18 , 21 , 23 ] found significantly lower LDL-C levels associated with vegetarian diet, both in the general population and in diabetic patients. In particular, Elliot et al. [ 18 ], analyzing 43 observational and interventional studies, described lower LDL-C in people adopting plant based diets; a significant difference was reported by the study of Liang et al. [ 21 ] based on 68 studies (MD: -0.29 to -0.17), and similar to data by Lamberg et al. [ 15 ], based on 13 RCTs including for a total of 576 participants (MD: -0.14 mmol/L; 95%CI: -0.25, -0.02). The impact of vegetarian diet appeared even greater in overweight or obese people, according to the analysis by Xu et al. [ 17 ], based on 7 RCTs (N = 783; MD: -0.31 mmol/L; 95%CI: -0.46, -0.16). Two reviews [ 19 , 20 ] reported similar results in overweight/obese patients and children aged 0–18 years, but no meta-analyses were conducted. Wang et al. [ 16 ] reported a MD of −0.34 mmol/L (95%CI: −0.57, −0.11; p<0.001) in the general adult population. Ferdowsian et al. [ 23 ] reported an overall reduction of LDL-C associated with vegetarian diet, but no synthesis analyses were performed. Dinu et al. [ 14 ] analyzed 46 studies encompassing 5,583 vegetarians and found a WMD of -1.18 mmol/L (95%CI: -1.34, -1.01). Finally, Viguiliouk et al. [ 24 ] reported a MD of −0.12 mmol/L (95%CI: −0.20, −0.04) in 6 trials involving 602 diabetic patients.

Four reviews identified a significant reduction in LDL-C in vegans as compared to omnivores [ 14 , 19 , 23 , 25 ]. Benatar et al. [ 25 ] analyzed 31 studies, for a total of 3,355 healthy vegan adults and 53,393 non-vegan controls and found MD of -0.49 mmol/L (95%CI: -0.62, -0.36; p<0.0001). Ferdowsian et al. [ 23 ] reported a reduction of LDL-C in healthy vegans, and Ivanova et al. [ 19 ] in overweight patients, but no meta-analysis was performed. Finally, Dinu et al. [ 14 ] analyzed 13 studies, for a total of 728 healthy vegan adults, and found a significant LDL-C reduction (WMD: −1.27 mmol/L; 95%CI: −1.66, −0.88).

IV. Triglycerides (TG).

Seven systematic reviews [ 14 , 16 – 18 , 20 , 23 , 26 ] analyzed serum triglycerides (TG) in vegetarians vs. omnivores. Specifically, Wang et al. [ 16 ] described no differences between the two, with a pooled estimated effect of 0.04 mmol/L (95%CI: −0.05, 0.13; p = 0.4). Zhang et al. [ 26 ] analyzing 12 studies for a total of 1,300 subjects, found a MD of −1.28 mmol/L (95%CI; −2.14, −0.42). Schürmann et al. and Ferdowsian et al. [ 20 , 23 ] reported lower TG in vegetarians in both children and adults but did not perform data meta-analysis. Dinu et al. [ 14 ] analyzed 55 studies including 4,008 vegetarians and found a WMD of −0.63 mmol/L (95%CI: −0.97, −0.30; p = 0.02). Conversely, in the review by Elliott et al. [ 18 ] no differences were reported in triglycerides. Xu et al. [ 17 ] reported a significant increase of TG (WMD: 0.29 mmol/L; 95%CI: 0.11, 0.47) in vegetarians as compared to meat eaters.

The effect of vegan diet on TG remains debated as one review [ 23 ] reported significative changes in TGs (-0.14 mmol/L, CI -0.24 to -0.05), while another [ 14 ] did not find any differences between vegans and omnivores since, after having analyzed 13 studies for 483 vegans, they reported a WMD of -0.52 mmol/L (95%CI: -1.13; 0.09).

V. C-reactive protein (CRP).

Three studies reported lower C-reactive protein (CRP) levels in normal weight, overweight and obese vegetarians as compared to non-vegetarians. Craddock et al. and Menzel et al. reported a WMD of -0.61 mg/L (95%CI: -0.91, -0.32; p = 0.0001) [ 27 ]; -0.25 mg/L (95%CI: -0.49, 0; p = 0.05) [ 28 ], respectively.

Data derived from the analysis by Menzel et al. [ 28 ] in vegan subjects were in line with previously mentioned studies performed in vegetarians (WMD: -0.54 mg/L; 95%CI: -0.79, -0.28; p<0.0001).

Two reviews [ 29 , 30 ] focused on the effects of mixed vegetarian diets on CRP levels. The first [ 29 ] included 2,689 obese patients and found a WMD of -0.55 mg/L (95%CI: -0.78, -0.32; I 2 = 94.4%), while the other [ 30 ], based on 2,398 normal weight subjects found no significant differences between vegetarians and omnivores in the primary analysis; alas, when considering a minimum duration of two years vegetarianism they described lower CRP levels vs. omnivores (Hedges’ g = -0.29; 95%CI: -0.59, 0.01).

VI. Plant-based diets and lipids.

Three studies [ 23 , 26 , 31 ] assessed the lipid profile in people following plant-based diets (without differentiating among diet subtypes) in comparison with omnivores. All of them found significantly lower levels of TC, HDL-C and LDL-C in subjects following plant-based diets. Specifically, Yokoyama et al. [ 31 ] reported a WMD of −1.62 mmol/L (95%CI: −1.92, −1.32; p< 0.001; I 2 = 81.4) for TC, −1.27 mmol/L (95%CI: −1.55, −0.99; p< 0.001; I 2 = 83.3) for LDL-C, −0.2 mmol/L (95%CI: −0.26, −0.14; p< 0.001; I 2 = 49.7) for HDL-C, and −0.36 mmol/L; 95%CI: −0.78, 0.06; p = 0.092; I 2 = 83.0) for TG when considering observational studies, and of −0.69 mmol/L (95%CI: −0.99, −0.4; p<0.001; I 2 = 54.8) for TC, −0.69 mmol/L (95%CI: −0.98, −0.37; p<0.001; I 2 = 79.2) for LDL-C, −0.19 mmol/L (95%CI: −0.24, −0.14; p<0.001; I 2 = 8.5) for HDL-C, and a non-statistically significant increase of TG based on prospective cohort studies. Additionally, Zhang et al. [ 26 ] in their meta-analysis, including 1,300 subjects, found a SMD of -1.28 mmol/L in TG (95% CI -2.14 to -0.42).

Finally, Picasso et al. [ 32 ] did not find any differences in triglycerides for mixed vegetarian diets (MD: 0.04 mmol/L; 95%CI: -0.09, 0.28), but did find statistically significant differences in HDL-C (MD: -0.05 mmol/L; 95%CI: -0.07, -0.03).

VII. Blood pressure.

A . Systolic blood pressure (SBP) . Various studies found significantly lower mean levels of systolic blood pressure (SBP) levels in vegetarians compared to the general population [ 33 – 36 ]. Specifically, Gibbs et al. [ 33 ] reported a SMD of -5.47 mmHg (95%CI: -7.60, -3.34; p<0.00001) in ovo-lacto-vegetarians, as did Lee et al. [ 34 ] reporting a SMD of -1.75 mmHg (95%CI: -5.38, 1.88; p = 0.05); furthermore, they reported a SBP decreased by -2.66 mmHg (95%CI: -3.76, -1.55), in people adopting generic vegetarian diets. Moreover, Garbett et al. [ 35 ] reported a 33% lower prevalence of hypertension in vegetarians vs. nonvegetarians. On the contrary, Schwingshackl et al. [ 36 ], analyzing data from 67 clinical trials overall including 17,230 pre-hypertensive and hypertensive adult patients with a BMI between 23.6 and 45.4 kg/m 2 , followed for 3 to 48 months, did not find any significant reductions in SBP associated with vegetarian diet.

Four reviews investigated the differences in SBP between vegans and non-vegans. Benatar et al. and Lee et al. [ 25 , 34 ] reported significantly lower mean SBP levels in vegans vs. omnivores (MD: -2.56 mmHg; 95%CI: -4.66, -0.45; and WMD: -3.12 mmHg; 95%CI: -4.54, -1.70; p<0.001, respectively). On the other hand, Gibbs et al. [-1.30 mmHg (95%CI: -3.90,1.29)] and Lopez et al. (-1.33 mmHg; 95%CI: −3.50, 0.84; P = 0.230) [ 33 , 37 ] did not find any significant difference in mean SBP levels between vegans and omnivores.

Both reviews [ 32 , 38 ] focusing on SBP in mixed-plant-based dietary patterns found significantly lower levels in vegetarians than in omnivores. The meta-analysis by Picasso et al. [ 32 ], based on 4 RCTs did not find any differences, alas, analyzing 42 cross sectional studies, they described a MD of -4.18 mmHg (95%CI -5.57, -2.80; p<0.00001), in agreement with Yokoyama et al. [ 38 ], who reported a MD of -4.8 mmHg (95%CI: -6.6, -3.1; p<0.001; I 2 = 0) according to the 7 controlled trials, 6 of which being randomized (311 participants), included in the analysis, and of -6.9 mmHg (95%CI: -9.1, -4.7; p<0.001; I 2 = 91.4) based on the other 32 observational studies (21,604 participants).

B . Diastolic blood pressure (DBP) . Garbett et al. [ 35 ] reported reduced mean diastolic blood pressure (DBP) values in vegetarians vs. omnivores, confirmed by the analysis of Gibbs et al. [ 33 ] (WMD: –2.49 mmHg; 95%CI: –4.17, –0.80; p = 0.004; I 2 = 0%) in ovo-lacto-vegetarians, by Lee et al. [ 34 ] [WMD: -1.69 mmHg (95%CI: -2.97, -0.41; p<0.001)] who included 15 randomized controlled trials (N = 856) performed in vegetarians; and by Yokoyama et al. [ 38 ], who highlighted a MD -2.2 mmHg (95%CI: -3.5, -1.0; p<0.001; I 2 = 0%) and -4.7 mmHg (95%CI: -6.3, -3.1; p<0.001; I 2 = 92.6%) according to data from 7 controlled trials (N = 311) and 32 observational studies (N = 21,604), respectively. Conversely, Schwingshackl et al. [ 36 ] did not find significant differences between vegetarians and non-vegetarians.

Three reviews [ 25 , 34 , 37 ] examined the impact of vegan vs. non-vegan diet on DBP and described statistically significant reductions. Benatar et al. described reduction of DBP, corresponding to a MD of -1.33 mmHg (95%CI: -2.67, -0.02) [ 25 ]. Lee et al. described a reduction in DBP of a WMD of -1.92 mmHg (95%CI: -3.18, -0.66; p<0.001) [ 34 ]. Finally, Lopez et al. [ 37 ] described the same reduction amounting to WMD: -4.10 mmHg (95%CI: -8.14, -0.06).

Four studies agreed upon the lower mean DBP levels in subjects following mixed vegetarian diets as compared to omnivores [ 32 – 34 , 38 ], quantified as MD -3.03 mmHg (95%CI: -4.93, 1.13; p = 0.002) by Picasso et al. [ 32 ], and −2.2 mmHg (95%CI: −3.5, −1.0; p<0.001) and −4.7 mmHg (95%CI: −6.3, −3.1; p <0.001) by the analysis performed on clinical trials and observational studies, respectively, by Yokoyama et al. [ 38 ].

VIII. Body weight and body mass index (BMI).

Berkow et al. [ 39 ] identified 40 observational studies comparing weight status of vegetarians vs. non-vegetarians: 29 reported that weight/BMI of vegetarians of both genders, different ethnicities (i.e., African Americans, Nigerians, Caucasians and Asians), and from widely separated geographic areas, was significantly lower than that of non-vegetarians, while the other 11 did not find significant differences between the two groups. In female vegetarians, weight was 2.9 to 10.6 kg (6% to 17%) and BMI 2.7% to 15.0% lower than female non-vegetarians, while the weight of male vegetarians was 4.6 to 12.6 kg (8% to 17%) lower and the BMI 4.6% to 16.3% lower than that of male non-vegetarians. The review by Schürmann et al. [ 20 ], focusing on 8,969 children aged 0–18 years old found similar body weight in both vegetarian and vegan children as compared to omnivore ones. Dinu et al. [ 14 ] analyzed data from 71 studies (including 57,724 vegetarians and 199,230 omnivores) and identified a WMD BMI of -1.49 kg/m 2 (95%CI: -1,72, -1,25; p<0.0001) in vegetarians when compared to omnivores.

Barnard et al. [ 40 ] found a significant reduction in weight in pure ovolactovegetarians (−2.9 kg; 95% CI −4.1 to −1.6; P<0.0001), compared to non-vegetarians from control groups; furthermore, they found in vegans the mean effect was of -3.2 kg (95% CI: -4.0;-2.4, P: <0.0001); overall they included 490 subjects in their analysis, excluding subjects who did not complete the trials.

Benatar et al. [ 25 ]–including 12,619 vegans and 179,630 omnivores from 40 observation studies–and Dinu et al. [ 14 ]–based on 19 cross sectional studies, for a total of 8,376 vegans and 123,292 omnivores–reported the same exact result, with a mean lower BMI in vegans vs omnivores, equal to -1.72 kg/m 2 (95%CI: -2.30, -1.16) and -1.72 kg/m 2 (95%CI: -2.21,-1.22; p<0.0001), respectively. The meta-analysis by Long et al. [ 41 ], performed on 27 studies, reported a MD of -0.70 kg/m 2 (95%CI: -1.38, -0.01) for BMI in vegans vs. omnivores. A systematic review and meta-analysis by Agnoli et al. [ 42 ] found mean BMI to be lower in subjects adhering to mixed vegetarian diets as compared to omnivores. Additionally, Tran et al. [ 43 ] described weight reductions in clinically healthy patients, as well as in people who underwent vegetarian diets as a prescription, but no meta-analysis was performed.

Finally, Huang et al. [ 44 ] found significant differences in both vegans and vegetarians, who were found to have lost weight after having adopted the diet as a consequence of being assigned to the intervention group in their randomized studies. For vegetarians the WMD was -2.02 kg (95%CI: -2.80 to -1.23), when compared to mixed diets, and for vegans the WMD was -2.52 kg (95%CI: -3.02 to -1.98), when compared to vegetarians.

IX. Glucose metabolism.

Viguiliouk et al. [ 24 ] found a significant reduction in HbA1c (MD: −0.29%; 95%CI: −0.45, −0.12) and fasting glucose (MD: −0.56 mmol/L; 95%CI: −0.99, −0.13) in vegetarians vs. non-vegetarians.

The meta-analysis by Dinu et al. [ 14 ], reported for vegetarians (2256) vs omnivores (2192) WMD: -0.28 mmol/L (95%CI: -0.33, -0.23) in fasting blood glucose.

These findings were confirmed by Picasso et al. [ 32 ] who found a MD of -0.26 mmol/L (95% CI: -0.35, -0.17) in fasting glucose in mixed-vegetarian diets as compared to omnivores.

A meta-analysis by Long et al. [ 41 ], based of 27 cross sectional studies, showed a MD for homeostasis model assessment of insulin resistance -measured as HOMA-IR, a unitless measure ideally less than one- of -0.75 (95%CI: -1.08, -0.42), fasting plasma glucose in vegetarians who adhered also to an exercise intervention as compared to omnivores.

Lee & Park [ 45 ] reported a significantly lower diabetes risk (OR 0.73; 95%CI: 0.61, 0.87; p<0.001) in vegetarians vs. non-vegetarians, being the association stronger in studies conducted in the Western Pacific region and Europe/North America than in those from Southeast Asia.

Regarding vegans, the review by Benatar et al. [ 25 ] determined a mean reduction of 0.23 mmol/L (95%CI: -0.35, -0.10) of fasting blood glucose in vegans (N = 12,619) as compared to omnivores (N = 179,630). The finding was in line with Dinu et al. [ 14 ], who reported a WMD of -0.35 mmol/L (95%CI: -0.69, -0.02; p = 0.04) of fasting blood glucose in vegans (n = 83) than omnivores (n = 125).

A systematic review, finally, including 61 studies [ 42 ] found mean values of fasting plasma glucose, and T2D risk to be lower in subjects following mixed vegetarian diets as compared to omnivores.

X. Cardiovascular events.

Huang et al. [ 46 ] found a significantly lower risk of ischemic heart disease (IHD) (RR: 0.71; 95%CI: 0.56, 0.87), but no significant differences for cerebrovascular mortality between vegetarians and non-vegetarians. The review by Remde et al. [ 47 ] was not conclusive, as only a few studies showed a reduction of the risk of CVDs for vegetarians versus omnivores, while the others did not find any significant results.

Dybvik et al. [ 48 ] based on 13 cohort studies for a total of 844,175 participants (115,392 with CVDs, 30,377 with IHD and 14,419 with stroke) showed that the overall RR for vegetarians vs. nonvegetarians was 0.85 (95%CI: 0.79–0.92, I 2 = 68%; 8 studies) for CVD, 0.79 (95%CI: 0.71–0.88, I 2 = 67%; 8 studies) for IHD, 0.90 (95%CI: 0.77–1.05, I 2 = 61%; 12 studies) for total stroke, while the RR of IHD in vegans vs. omnivores was 0.82 (95%CI: 0.68–1.00, I 2 = 0%; 6 studies).

The meta-analysis by Kwok et al. [ 49 ], based on 8 studies including 183,321 subjects comparing vegetarians versus non-vegetarians. They identified a significant reduction of IHD in the Seventh Day Adventist (SDA) cohort, who primarily follow ovo-lacto-vegetarian diets, while other non-SDA vegetarian diets were associated only with a modest reduction of IHD risk, raising the concern that other lifestyle factors typical of SDA and, thus not generalizable to other groups, play a primary role on outcomes. IHD was significantly reduced in both genders (RR: 0.60; 95%CI: 0.43, 0.83), while the risk of death and cerebrovascular disease and cardiovascular mortality risk reduction was significantly reduced only in men. No significant differences were detected for the risk of cerebrovascular events.

The meta-analysis by Lu et al. [ 50 ] -657,433 participants from cohort studies- reported a lower incidence of total stroke among vegetarians vs. nonvegetarians (HR = 0.66; 95%CI = 0.45–0.95; I 2 = 54%), while no differences were identified for incident stroke.

The descriptive systematic review by Babalola et al. [ 3 ] reported that adherence to a plant-based diet was inversely related to heart failure risk and advantageous for the secondary prevention of CHD, particularly if started from adolescence. Another review by Agnoli et al. [ 42 ], confirmed a lower incidence of CVDs associated with mixed vegetarian diets as compared to omnivorous diets. Finally, Chhabra et al. [ 51 ] found that vegetarian diet, particularly if started in adolescence and associated with vitamin B intake, can reduce the risk of stroke.

Gan et al. [ 52 ] described a lower risk of CVDs (RR 0.84; 95% CI 0.79 to 0.89; p < 0.05) in high, vs. low, adherence plant based diets, but the same association was not confirmed for stroke (RR 0.87; 95% CI: 0.73, 1.03).

Group 2: Pregnancy outcomes

The meta-analysis by Foster et al. [ 53 ], performed on 6 observational studies, found significantly lower zinc levels in vegetarians than in meat eaters (-1.53 ± 0.44 mg/day; p = 0.001), but no association with pregnancy outcomes, specifically no increase in low children birth weight. The finding was confirmed by Tan et al. [ 54 ], who similarly reported no specific risks, but reported that Asian (India/Nepal) vegetarian mothers exhibited increased risks to deliver a baby with Low Birth Weight (RR: 1.33 [95%CI:1.01, 1.76, p =  0.04, I 2 = 0%]; nonetheless, the WMD of neonatal birth weight in five studies they analyzed suggested no difference between vegetarians and omnivores.

To our knowledge, no reviews/meta-analyses have assessed the risk of zinc deficiency and its association with functional outcomes in pregnancy in relation to mixed or vegan diets.

Group 3: Cancer

The meta-analysis by Parra-Soto et al. [ 55 ], based on 409,110 participants from the UK Biobank study (mean follow-up 10.6 years), found a lower risk of liver, pancreatic, lung, prostate, bladder, colorectal, melanoma, kidney, non-Hodgkin lymphoma and lymphatic cancer as well as overall cancer (HR ranging from 0.29 to 0.70) determined by non-adjusted models in vegetarians vs. omnivores; when adjusted for sociodemographic and lifestyle factors, multimorbidity and BMI, the associations remained statistically significant only for prostate cancer (HR 0.57; 95%CI: 0.43, 0.76), colorectal cancer (HR 0.73; 95%CI: 0.54, 0.99), and all cancers combined (HR 0.87; 95%CI 0.79, 0.96). When colorectal cancer was stratified according to subtypes, a lower risk was observed for colon (HR 0.69; 95%CI: 0.48, 0.99) and proximal colon (HR 0.43; 95%CI: 0.22, 0.82), but not for rectal or distal cancer.

Similarly, the analysis by Huang et al. [ 46 ], based on 7 studies for a total of 124,706 subjects, reported a significantly lower overall/total cancer incidence in vegetarians than non-vegetarians (RR 0.82; 95%CI: 0.67, 0.97).

Zhao et al. [ 56 ] found a lower risk of digestive system cancer in plant-based dieters (RR = 0.82, 95%CI: 0.78–0.86; p< 0.001) and in vegans (RR: 0.80; 95%CI: 0.74, 0.86; p<0.001) as compared to meat eaters.

Additionally, DeClercq et al. [ 57 ] reported a decreased risk of overall cancer and colorectal cancer, but inconsistent results for prostate cancer and breast cancer; this was substantiated by Godos et al. [ 58 ] found no significant differences in breast, colorectal, and prostate cancer risk between vegetarians and non-vegetarians.

The umbrella review by Gianfredi et al. [ 59 ], did describe a lower risk of pancreatic cancer associated with vegetarian diets.

Dinu et al. [ 14 ] reported a reduction in the risk of total cancer of 8% in vegetarians, and of 15% in vegans, as compared to omnivores. They described lower risk of cancer among vegetarians (RR 0.92; 95%CI 0.87, 0.98) and vegans (RR: 0.85; 95%CI: 0.75,0.95); nonetheless, they also described non-significant reduced risk of mortality from colorectal, breast, lung and prostate cancers. Regarding the latter, a meta-analysis by Gupta et al. [ 60 ] on prostate cancer risk found a decreased hazard ratio for the incidence of prostate cancer (HR: 0.69; 95%CI: 0.54–0.89, P<0.001) in vegetarians as compared to omnivores from the evidence coming from 3 studies. In the vegan population, similar results were observed from the only included study (HR: 0.65; 95%CI: 0.49–0.85; p<0.001).

Group 4: Death by cardiometabolic diseases and cancer

According to Huang et al. [ 46 ], the mortality from IHD (RR: 0.71; 95%CI: 0.56, 0.87), circulatory diseases (RR: 0.84; 95%CI: 0.54, 1.14) and cerebrovascular diseases (RR: 0.88; 95%CI: 0.70, 1.06) was significantly lower in vegetarians than in non-vegetarians.

The analysis by Dinu et al. [ 14 ] performed on 7 prospective studies, overall including 65,058 vegetarians, reported a 25% reduced mortality risk from ischemic heart diseases (RR 0.75; 95%CI: 0.68, 0.82; p<0.001), but no significant differences were found analyzing 5 cohort studies in terms of mortality from CVDs, cerebrovascular diseases, nor colorectal, breast, prostate, and lung cancer. Regarding vegans, they analyzed 6 cohort studies, and found no differences in all-cause mortality, but significant differences in cancer incidence (RR: 0.85; 95%CI: 0.75, 0.95), indicating a protective effect of vegan diets.

The literature search did not identify studies focusing on mortality risk for cardiometabolic and cancer diseases in vegans.

Quality of the included studies

The quality of the 48 reviews and meta-analyses included in this umbrella review was assessed through the AMSTAR-R tool. Results are reported in S1 Table . Overall, the average quality score was 28, corresponding to mean quality. However, 36 studies (75%) scored between 60% and 90% of the maximum obtainable score, and can, therefore, be considered of good/very good quality. The least satisfied item on the R-AMSTAR grid was #8 -scientific quality of included studies used to draw conclusions-, where as many as 19 studies (39.6%) failed to indicate the use of study-related quality analysis to make recommendations. This finding should be read in conjunction with the missing quality analysis in 15 studies (31.3%)–Item #7 scientific quality of included studies assessed and documented-. Item #10, regarding publication bias, was the second least met item, in which 18 studies (37.5%) did not perform any analysis on this type of bias. 16 studies (33.3%) lacked to indicate careful exclusion of duplicates (Item #2), but also the presence of conflict of interest (Item #11). This point is certainly another important piece to consider in the overall quality assessment of these articles. All these considerations give us a picture of a general low quality of the publications found, lowering the strength of evidence as well as the external validity of the results.

This umbrella review provides an update on the benefits associated with the adoption of A/AFPDs in reducing risk factors associated with the development of cardiometabolic diseases and cancer, considering both the adult and the pediatric population, as well as pregnant women.

Compared to omnivorous regimens, vegetarian and vegan diets appear to significantly improve the metabolic profile through the reduction of total and LDL cholesterol [ 14 – 21 , 23 , 25 ], fasting blood glucose and HbA1c [ 14 , 24 , 25 , 37 , 39 – 41 ], and are associated with lower body weight/BMI, as well as reduced levels of inflammation (evaluated by serum CRP levels [ 27 , 30 ]), while the effect on HDL cholesterol and triglycerides, systolic and diastolic blood pressure levels remains debated. A much more limited body of literature suggested vegetarian, but not vegan diets also reduce ApoB levels further improving the lipid profile [ 61 ].

It should be remarked that, in the majority of the cases, people adopting plant-based diets are more prone to engage in healthy lifestyles that include regular physical activity, reduction/avoidance of sugar-sweetened beverages, alcohol and tobacco, that, in association with previously mentioned modification of diet [ 62 ], lead to the reduction of the risk of ischemic heart disease and related mortality, and, to a lesser extent, of other CVDs.

The adoption of vegan diets is known to increase the risk of vitamin B-12 deficiency and consequent disorders–for which appropriate supplementation was recommended by a 2016 position paper of the Academy of Nutrition and Dietetics’ [ 5 ], but, apparently, does not modify the risk of pregnancy-induced hypertension nor gestational diabetes mellitus [ 53 , 54 ].

The three meta-analyses [ 46 , 55 , 57 ] that analyzed the overall risk of cancer incidence in any form concordantly showed a reduction in risk in vegetarians compared to omnivores. These general results were inconsistent in the stratified analyses for cancer types, which as expected involved smaller numbers of events and wider confidence intervals, especially for less prevalent types of cancers.

The stratified analyses in the different reviews did not show any significant difference for bladder, melanoma, kidney, lymphoma, liver, lung, or breast cancer. Conversely the three meta-analyses that addressed colorectal cancer [ 55 , 57 , 58 ] showed a decrease in risk in two out of three with one not showing a significant difference in vegetarians versus omnivores for the generic colorectal tract.

Interestingly, one review [ 55 ] showed how analysis with even more specific granularity could reveal significant differences in particular subsets of cancers, e.g., distal, and proximal colon. Also, another recent review found significant results for pancreatic cancer [ 59 ].

Our umbrella review seems consistent with other primary evidence that links the consumption of red processed meats to an increased risk of cancers of the gastro-intestinal tract [ 63 ]. The association certainly has two faces, because while a potential risk of cancer given by increased red meat consumption can be observed, the potential protective factor given by increased fruit and vegetable consumption, shown by other previous evidence, must also be considered [ 64 ].

It has also been described that vegetarians, in addition to reduced meat intake, ate less refined grains, added fats, sweets, snacks foods, and caloric beverages than did nonvegetarians and had increased consumption of a wide variety of plant foods [ 65 ]. Such a dietary pattern seems responsible for a reduction of hyperinsulinemia, one of the possible factors for colorectal cancer risk related to diet and food intake [ 66 , 67 ]. In the same manner, some research has suggested that insulin-like growth factors and its binding proteins may relate to cancer risk [ 68 , 69 ]. This dietary pattern should not be regarded as a universal principle, as varying tendencies have been observed among vegetarians and vegans in different studies. This pattern of consumption may potentially negate the anticipated beneficial effects of their diets.

Also, some protective patterns can be attributed to the effects of bioactive compounds of plant foods, these being primary sources of fiber, carotenoids, vitamins, minerals, and other compounds that have been associated with anti-cancer properties [ 70 , 71 ]. The protective patterns are likely attributed to the mechanistic actions of the many bioactives found in plant foods such as fiber, carotenoids, vitamins, and minerals with plausible anti-cancer properties. These ranged from epigenetic mechanisms [ 72 ], to immunoregulation, antioxidant and anti-inflammatory activity [ 73 , 74 ].

Finally, increased adiposity could be another pathway by which food intake is associated with these types of cancers. Since our umbrella review has demonstrated that vegetarian diets are associated with lower BMI, this might be another concurrent factor in the decreased risk for pancreatic and colorectal cancers in vegetarians.

Inflammatory biomarkers and adiposity play pivotal roles in the genesis of prostate cancer [ 75 , 76 ], hence the same etiological pathways might be hypothesized even for the increase of this type of cancer in people adopting an omnivorous diet.

The study presents several noteworthy strengths in its methodological approach and thematic focus. It has employed a rigorous and comprehensive search strategy involving two major databases, PubMed, and Scopus, spanning over two decades of research from 1 st January 2000 to 31 st June 2023, thereby ensuring a robust and exhaustive collection of pertinent literature. By utilizing an umbrella review, the research enables the synthesis of existing systematic reviews and meta-analyses, providing a higher level of evidence and summarizing a vast quantity of information. Furthermore, its alignment with current health concerns, specifically targeting cardiovascular diseases and cancer, makes the study highly relevant to ongoing public health challenges and positions it as a valuable resource for informing preventive measures and dietary guidelines. The deployment of blinded and independent assessments by multiple raters and investigators fortifies the research by minimizing bias and reinforcing the reliability of the selection, quality assessment, and data extraction processes. Quality assessment is standardized using the revised AMSTAR-R 11-item tool, and transparency is fostered through registration on PROSPERO, thus enhancing the credibility of the study. Lastly, the study’s detailed analysis and reporting, particularly the extraction of specific health measures such as cholesterol levels, glucose levels, blood pressure, and cancer risks, contribute to the comprehensiveness of the data synthesis, thereby underlining the overall integrity and significance of the research.

Main limitations to data analysis and interpretation are intrinsic to the original studies and consist in the wide heterogeneity in terms of sample size, demographic features, and geographical origin of included subjects, dietary patterns–not only in terms of quality, but, even more important and often neglected, quantity, distribution during the day, processing, cooking methods–and adherence, and other lifestyle confounders. In this regard, it is worth to mention that the impact of diet per se on the development of complex disorders (i.e. CVDs and cancer) and related mortality is extremely difficult to assess [ 71 ], especially in large populations, characterized by a highly heterogeneous lifestyle. It should also be considered the heterogeneity in dietary and lifestyle habits among countries, according to which the adoption of A/AFPDs could modify significantly habits in some countries, but not in others, and consequently have an extremely different impact on the risk of developing cardiometabolic disorders and cancer [ 25 ]. Furthermore, due to the nature of umbrella reviews, the present work may not include novel associations which were excluded from the analyzed reviews, as the main aim was to summarize secondary studies, such as reviews and meta-analyses. Finally, studies assessing the benefit of A/AFPDs on cancer risk are also limited by the heterogeneity in the timing of oncological evaluation and, therefore, disease progression, as well as in the histological subtypes and previous/concomitant treatments [ 72 – 75 ].

In conclusion, this umbrella review offers valuable insights on the estimated reduction of risk factors for cardiometabolic diseases and cancer, and the CVDs-associated mortality, offered by the adoption of plant-based diets through pleiotropic mechanisms. Through the improvement of glycolipid profile, reduction of body weight/BMI, blood pressure, and systemic inflammation, A/AFPDs significantly reduce the risk of ischemic heart disease, gastrointestinal and prostate cancer, as well as related mortality.

However, data should be taken with caution because of the important methodological limitation associated with the original studies. Moreover, potential risks associated with insufficient intake of vitamin and other elements due to unbalanced and/or extremely restricted dietary regimens, together with specific patient needs should be considered, while promoting research on new and more specific markers (i.e. biochemical, genetic, epigenetic markers; microbiota profile) recently associated with cardiometabolic and cancer risk, before suggesting A/AFPDs on large scale.

Supporting information

S1 table. r-amstar..

https://doi.org/10.1371/journal.pone.0300711.s001

S2 Table. PRISMA 2020 checklist.

https://doi.org/10.1371/journal.pone.0300711.s002

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