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How to Write a Conclusion for Research Papers (with Examples)

The conclusion of a research paper is a crucial section that plays a significant role in the overall impact and effectiveness of your research paper. However, this is also the section that typically receives less attention compared to the introduction and the body of the paper. The conclusion serves to provide a concise summary of the key findings, their significance, their implications, and a sense of closure to the study. Discussing how can the findings be applied in real-world scenarios or inform policy, practice, or decision-making is especially valuable to practitioners and policymakers. The research paper conclusion also provides researchers with clear insights and valuable information for their own work, which they can then build on and contribute to the advancement of knowledge in the field.

The research paper conclusion should explain the significance of your findings within the broader context of your field. It restates how your results contribute to the existing body of knowledge and whether they confirm or challenge existing theories or hypotheses. Also, by identifying unanswered questions or areas requiring further investigation, your awareness of the broader research landscape can be demonstrated.

Remember to tailor the research paper conclusion to the specific needs and interests of your intended audience, which may include researchers, practitioners, policymakers, or a combination of these.

Table of Contents

What is a conclusion in a research paper, summarizing conclusion, editorial conclusion, externalizing conclusion, importance of a good research paper conclusion, how to write a conclusion for your research paper, research paper conclusion examples.

• How to write a research paper conclusion with Paperpal? 

Frequently Asked Questions

A conclusion in a research paper is the final section where you summarize and wrap up your research, presenting the key findings and insights derived from your study. The research paper conclusion is not the place to introduce new information or data that was not discussed in the main body of the paper. When working on how to conclude a research paper, remember to stick to summarizing and interpreting existing content. The research paper conclusion serves the following purposes: 1

• Warn readers of the possible consequences of not attending to the problem.
• Recommend specific course(s) of action.
• Restate key ideas to drive home the ultimate point of your research paper.
• Provide a “take-home” message that you want the readers to remember about your study.

Types of conclusions for research papers

In research papers, the conclusion provides closure to the reader. The type of research paper conclusion you choose depends on the nature of your study, your goals, and your target audience. I provide you with three common types of conclusions:

A summarizing conclusion is the most common type of conclusion in research papers. It involves summarizing the main points, reiterating the research question, and restating the significance of the findings. This common type of research paper conclusion is used across different disciplines.

An editorial conclusion is less common but can be used in research papers that are focused on proposing or advocating for a particular viewpoint or policy. It involves presenting a strong editorial or opinion based on the research findings and offering recommendations or calls to action.

An externalizing conclusion is a type of conclusion that extends the research beyond the scope of the paper by suggesting potential future research directions or discussing the broader implications of the findings. This type of conclusion is often used in more theoretical or exploratory research papers.

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The conclusion in a research paper serves several important purposes:

• Offers Implications and Recommendations : Your research paper conclusion is an excellent place to discuss the broader implications of your research and suggest potential areas for further study. It’s also an opportunity to offer practical recommendations based on your findings.
• Provides Closure : A good research paper conclusion provides a sense of closure to your paper. It should leave the reader with a feeling that they have reached the end of a well-structured and thought-provoking research project.
• Leaves a Lasting Impression : Writing a well-crafted research paper conclusion leaves a lasting impression on your readers. It’s your final opportunity to leave them with a new idea, a call to action, or a memorable quote.

Writing a strong conclusion for your research paper is essential to leave a lasting impression on your readers. Here’s a step-by-step process to help you create and know what to put in the conclusion of a research paper: 2

• Research Statement : Begin your research paper conclusion by restating your research statement. This reminds the reader of the main point you’ve been trying to prove throughout your paper. Keep it concise and clear.
• Key Points : Summarize the main arguments and key points you’ve made in your paper. Avoid introducing new information in the research paper conclusion. Instead, provide a concise overview of what you’ve discussed in the body of your paper.
• Address the Research Questions : If your research paper is based on specific research questions or hypotheses, briefly address whether you’ve answered them or achieved your research goals. Discuss the significance of your findings in this context.
• Significance : Highlight the importance of your research and its relevance in the broader context. Explain why your findings matter and how they contribute to the existing knowledge in your field.
• Implications : Explore the practical or theoretical implications of your research. How might your findings impact future research, policy, or real-world applications? Consider the “so what?” question.
• Future Research : Offer suggestions for future research in your area. What questions or aspects remain unanswered or warrant further investigation? This shows that your work opens the door for future exploration.
• Closing Thought : Conclude your research paper conclusion with a thought-provoking or memorable statement. This can leave a lasting impression on your readers and wrap up your paper effectively. Avoid introducing new information or arguments here.
• Proofread and Revise : Carefully proofread your conclusion for grammar, spelling, and clarity. Ensure that your ideas flow smoothly and that your conclusion is coherent and well-structured.

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Remember that a well-crafted research paper conclusion is a reflection of the strength of your research and your ability to communicate its significance effectively. It should leave a lasting impression on your readers and tie together all the threads of your paper. Now you know how to start the conclusion of a research paper and what elements to include to make it impactful, let’s look at a research paper conclusion sample.

How to write a research paper conclusion with Paperpal?

A research paper conclusion is not just a summary of your study, but a synthesis of the key findings that ties the research together and places it in a broader context. A research paper conclusion should be concise, typically around one paragraph in length. However, some complex topics may require a longer conclusion to ensure the reader is left with a clear understanding of the study’s significance. Paperpal, an AI writing assistant trusted by over 800,000 academics globally, can help you write a well-structured conclusion for your research paper. 

• Sign Up or Log In: Create a new Paperpal account or login with your details.  
• Navigate to Features : Once logged in, head over to the features’ side navigation pane. Click on Templates and you’ll find a suite of generative AI features to help you write better, faster.  
• Generate an outline: Under Templates, select ‘Outlines’. Choose ‘Research article’ as your document type.  
• Select your section: Since you’re focusing on the conclusion, select this section when prompted.  
• Choose your field of study: Identifying your field of study allows Paperpal to provide more targeted suggestions, ensuring the relevance of your conclusion to your specific area of research. 
• Provide a brief description of your study: Enter details about your research topic and findings. This information helps Paperpal generate a tailored outline that aligns with your paper’s content. 
• Generate the conclusion outline: After entering all necessary details, click on ‘generate’. Paperpal will then create a structured outline for your conclusion, to help you start writing and build upon the outline.  
• Write your conclusion: Use the generated outline to build your conclusion. The outline serves as a guide, ensuring you cover all critical aspects of a strong conclusion, from summarizing key findings to highlighting the research’s implications. 
• Refine and enhance: Paperpal’s ‘Make Academic’ feature can be particularly useful in the final stages. Select any paragraph of your conclusion and use this feature to elevate the academic tone, ensuring your writing is aligned to the academic journal standards. 

By following these steps, Paperpal not only simplifies the process of writing a research paper conclusion but also ensures it is impactful, concise, and aligned with academic standards. Sign up with Paperpal today and write your research paper conclusion 2x faster .  

The research paper conclusion is a crucial part of your paper as it provides the final opportunity to leave a strong impression on your readers. In the research paper conclusion, summarize the main points of your research paper by restating your research statement, highlighting the most important findings, addressing the research questions or objectives, explaining the broader context of the study, discussing the significance of your findings, providing recommendations if applicable, and emphasizing the takeaway message. The main purpose of the conclusion is to remind the reader of the main point or argument of your paper and to provide a clear and concise summary of the key findings and their implications. All these elements should feature on your list of what to put in the conclusion of a research paper to create a strong final statement for your work.

A strong conclusion is a critical component of a research paper, as it provides an opportunity to wrap up your arguments, reiterate your main points, and leave a lasting impression on your readers. Here are the key elements of a strong research paper conclusion: 1. Conciseness : A research paper conclusion should be concise and to the point. It should not introduce new information or ideas that were not discussed in the body of the paper. 2. Summarization : The research paper conclusion should be comprehensive enough to give the reader a clear understanding of the research’s main contributions. 3 . Relevance : Ensure that the information included in the research paper conclusion is directly relevant to the research paper’s main topic and objectives; avoid unnecessary details. 4 . Connection to the Introduction : A well-structured research paper conclusion often revisits the key points made in the introduction and shows how the research has addressed the initial questions or objectives. 5. Emphasis : Highlight the significance and implications of your research. Why is your study important? What are the broader implications or applications of your findings? 6 . Call to Action : Include a call to action or a recommendation for future research or action based on your findings.

The length of a research paper conclusion can vary depending on several factors, including the overall length of the paper, the complexity of the research, and the specific journal requirements. While there is no strict rule for the length of a conclusion, but it’s generally advisable to keep it relatively short. A typical research paper conclusion might be around 5-10% of the paper’s total length. For example, if your paper is 10 pages long, the conclusion might be roughly half a page to one page in length.

In general, you do not need to include citations in the research paper conclusion. Citations are typically reserved for the body of the paper to support your arguments and provide evidence for your claims. However, there may be some exceptions to this rule: 1. If you are drawing a direct quote or paraphrasing a specific source in your research paper conclusion, you should include a citation to give proper credit to the original author. 2. If your conclusion refers to or discusses specific research, data, or sources that are crucial to the overall argument, citations can be included to reinforce your conclusion’s validity.

The conclusion of a research paper serves several important purposes: 1. Summarize the Key Points 2. Reinforce the Main Argument 3. Provide Closure 4. Offer Insights or Implications 5. Engage the Reader. 6. Reflect on Limitations

Remember that the primary purpose of the research paper conclusion is to leave a lasting impression on the reader, reinforcing the key points and providing closure to your research. It’s often the last part of the paper that the reader will see, so it should be strong and well-crafted.

• Makar, G., Foltz, C., Lendner, M., & Vaccaro, A. R. (2018). How to write effective discussion and conclusion sections. Clinical spine surgery, 31(8), 345-346.
• Bunton, D. (2005). The structure of PhD conclusion chapters.  Journal of English for academic purposes ,  4 (3), 207-224.

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Organizing Your Social Sciences Research Paper

• 9. The Conclusion
• Purpose of Guide
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The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research. For most college-level research papers, two or three well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in describing the key findings and their significance.

Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.

Importance of a Good Conclusion

A well-written conclusion provides you with important opportunities to demonstrate to the reader your understanding of the research problem. These include:

• Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
• Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize  your answer to the "So What?" question by placing the study within the context of how your research advances past research about the topic.
• Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [first identified in your literature review section] has been addressed by your research and why this contribution is significant.
• Demonstrating the importance of your ideas . Don't be shy. The conclusion offers an opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
• Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.

Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Structure and Writing Style

I.  General Rules

The general function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Do this by clearly summarizing the context, background, and necessity of pursuing the research problem you investigated in relation to an issue, controversy, or a gap found in the literature. However, make sure that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your paper.

When writing the conclusion to your paper, follow these general rules:

• Present your conclusions in clear, concise language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., what were the unique, new, or crucial contributions your study made to the overall research about your topic?].
• Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
• Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem but that further investigations should take place beyond the scope of your investigation.

Consider the following points to help ensure your conclusion is presented well:

• If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
• If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data [this is opposite of the introduction, which begins with general discussion of the context and ends with a detailed description of the research problem]. 

The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way. If asked to think introspectively about the topics, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.

II.  Developing a Compelling Conclusion

Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following:

• If your essay deals with a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively.
• Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge leading to positive change.
• Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good source would be from your literature review].
• Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
• Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
• If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
• Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results from your study to recast it in new or important ways.
• Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.

III. Problems to Avoid

Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .

Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move from a specific discussion [your research problem] back to a general discussion framed around the implications and significance of your findings [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific analysis and discussion, conclude with a broad summary of the study's implications and significance].

Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study. They should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use negative results as an opportunity to explain their possible significance and/or how they may form the basis for future research.

Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long.

Failure to match the objectives of your research Often research objectives in the social and behavioral sciences change while the research is being carried out. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority as a researcher by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader about the study's validity and realiability.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining that they are reaching the end of your paper. You'll irritate your readers if you belabor the obvious.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper. This why the conclusion rarely has citations to sources. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you’ve presented, and position your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights to that scholarship.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.

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In a short paper—even a research paper—you don’t need to provide an exhaustive summary as part of your conclusion. But you do need to make some kind of transition between your final body paragraph and your concluding paragraph. This may come in the form of a few sentences of summary. Or it may come in the form of a sentence that brings your readers back to your thesis or main idea and reminds your readers where you began and how far you have traveled.

So, for example, in a paper about the relationship between ADHD and rejection sensitivity, Vanessa Roser begins by introducing readers to the fact that researchers have studied the relationship between the two conditions and then provides her explanation of that relationship. Here’s her thesis: “While socialization may indeed be an important factor in RS, I argue that individuals with ADHD may also possess a neurological predisposition to RS that is exacerbated by the differing executive and emotional regulation characteristic of ADHD.”

In her final paragraph, Roser reminds us of where she started by echoing her thesis: “This literature demonstrates that, as with many other conditions, ADHD and RS share a delicately intertwined pattern of neurological similarities that is rooted in the innate biology of an individual’s mind, a connection that cannot be explained in full by the behavioral mediation hypothesis.”  

Highlight the “so what”  

At the beginning of your paper, you explain to your readers what’s at stake—why they should care about the argument you’re making. In your conclusion, you can bring readers back to those stakes by reminding them why your argument is important in the first place. You can also draft a few sentences that put those stakes into a new or broader context.

In the conclusion to her paper about ADHD and RS, Roser echoes the stakes she established in her introduction—that research into connections between ADHD and RS has led to contradictory results, raising questions about the “behavioral mediation hypothesis.”

She writes, “as with many other conditions, ADHD and RS share a delicately intertwined pattern of neurological similarities that is rooted in the innate biology of an individual’s mind, a connection that cannot be explained in full by the behavioral mediation hypothesis.”  

Leave your readers with the “now what”  

After the “what” and the “so what,” you should leave your reader with some final thoughts. If you have written a strong introduction, your readers will know why you have been arguing what you have been arguing—and why they should care. And if you’ve made a good case for your thesis, then your readers should be in a position to see things in a new way, understand new questions, or be ready for something that they weren’t ready for before they read your paper.

In her conclusion, Roser offers two “now what” statements. First, she explains that it is important to recognize that the flawed behavioral mediation hypothesis “seems to place a degree of fault on the individual. It implies that individuals with ADHD must have elicited such frequent or intense rejection by virtue of their inadequate social skills, erasing the possibility that they may simply possess a natural sensitivity to emotion.” She then highlights the broader implications for treatment of people with ADHD, noting that recognizing the actual connection between rejection sensitivity and ADHD “has profound implications for understanding how individuals with ADHD might best be treated in educational settings, by counselors, family, peers, or even society as a whole.”

To find your own “now what” for your essay’s conclusion, try asking yourself these questions:

• What can my readers now understand, see in a new light, or grapple with that they would not have understood in the same way before reading my paper? Are we a step closer to understanding a larger phenomenon or to understanding why what was at stake is so important?  
• What questions can I now raise that would not have made sense at the beginning of my paper? Questions for further research? Other ways that this topic could be approached?  
• Are there other applications for my research? Could my questions be asked about different data in a different context? Could I use my methods to answer a different question?  
• What action should be taken in light of this argument? What action do I predict will be taken or could lead to a solution?  
• What larger context might my argument be a part of?  

What to avoid in your conclusion  

• a complete restatement of all that you have said in your paper.  
• a substantial counterargument that you do not have space to refute; you should introduce counterarguments before your conclusion.  
• an apology for what you have not said. If you need to explain the scope of your paper, you should do this sooner—but don’t apologize for what you have not discussed in your paper.  
• fake transitions like “in conclusion” that are followed by sentences that aren’t actually conclusions. (“In conclusion, I have now demonstrated that my thesis is correct.”)
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How to Write a Conclusion for a Research Paper

3-minute read

• 29th August 2023

If you’re writing a research paper, the conclusion is your opportunity to summarize your findings and leave a lasting impression on your readers. In this post, we’ll take you through how to write an effective conclusion for a research paper and how you can:

·   Reword your thesis statement

·   Highlight the significance of your research

·   Discuss limitations

·   Connect to the introduction

·   End with a thought-provoking statement

Rewording Your Thesis Statement

Begin your conclusion by restating your thesis statement in a way that is slightly different from the wording used in the introduction. Avoid presenting new information or evidence in your conclusion. Just summarize the main points and arguments of your essay and keep this part as concise as possible. Remember that you’ve already covered the in-depth analyses and investigations in the main body paragraphs of your essay, so it’s not necessary to restate these details in the conclusion.

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Highlighting the Significance of Your Research

The conclusion is a good place to emphasize the implications of your research . Avoid ambiguous or vague language such as “I think” or “maybe,” which could weaken your position. Clearly explain why your research is significant and how it contributes to the broader field of study.

Here’s an example from a (fictional) study on the impact of social media on mental health:

Discussing Limitations

Although it’s important to emphasize the significance of your study, you can also use the conclusion to briefly address any limitations you discovered while conducting your research, such as time constraints or a shortage of resources. Doing this demonstrates a balanced and honest approach to your research.

Connecting to the Introduction

In your conclusion, you can circle back to your introduction , perhaps by referring to a quote or anecdote you discussed earlier. If you end your paper on a similar note to how you began it, you will create a sense of cohesion for the reader and remind them of the meaning and significance of your research.

Ending With a Thought-Provoking Statement

Consider ending your paper with a thought-provoking and memorable statement that relates to the impact of your research questions or hypothesis. This statement can be a call to action, a philosophical question, or a prediction for the future (positive or negative). Here’s an example that uses the same topic as above (social media and mental health):

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Home » Research Paper Conclusion – Writing Guide and Examples

Research Paper Conclusion – Writing Guide and Examples

Table of Contents

Research Paper Conclusion

Definition:

A research paper conclusion is the final section of a research paper that summarizes the key findings, significance, and implications of the research. It is the writer’s opportunity to synthesize the information presented in the paper, draw conclusions, and make recommendations for future research or actions.

The conclusion should provide a clear and concise summary of the research paper, reiterating the research question or problem, the main results, and the significance of the findings. It should also discuss the limitations of the study and suggest areas for further research.

Parts of Research Paper Conclusion

The parts of a research paper conclusion typically include:

Restatement of the Thesis

The conclusion should begin by restating the thesis statement from the introduction in a different way. This helps to remind the reader of the main argument or purpose of the research.

Summary of Key Findings

The conclusion should summarize the main findings of the research, highlighting the most important results and conclusions. This section should be brief and to the point.

Implications and Significance

In this section, the researcher should explain the implications and significance of the research findings. This may include discussing the potential impact on the field or industry, highlighting new insights or knowledge gained, or pointing out areas for future research.

Limitations and Recommendations

It is important to acknowledge any limitations or weaknesses of the research and to make recommendations for how these could be addressed in future studies. This shows that the researcher is aware of the potential limitations of their work and is committed to improving the quality of research in their field.

Concluding Statement

The conclusion should end with a strong concluding statement that leaves a lasting impression on the reader. This could be a call to action, a recommendation for further research, or a final thought on the topic.

How to Write Research Paper Conclusion

Here are some steps you can follow to write an effective research paper conclusion:

• Restate the research problem or question: Begin by restating the research problem or question that you aimed to answer in your research. This will remind the reader of the purpose of your study.
• Summarize the main points: Summarize the key findings and results of your research. This can be done by highlighting the most important aspects of your research and the evidence that supports them.
• Discuss the implications: Discuss the implications of your findings for the research area and any potential applications of your research. You should also mention any limitations of your research that may affect the interpretation of your findings.
• Provide a conclusion : Provide a concise conclusion that summarizes the main points of your paper and emphasizes the significance of your research. This should be a strong and clear statement that leaves a lasting impression on the reader.
• Offer suggestions for future research: Lastly, offer suggestions for future research that could build on your findings and contribute to further advancements in the field.

Remember that the conclusion should be brief and to the point, while still effectively summarizing the key findings and implications of your research.

Example of Research Paper Conclusion

Here’s an example of a research paper conclusion:

Conclusion :

In conclusion, our study aimed to investigate the relationship between social media use and mental health among college students. Our findings suggest that there is a significant association between social media use and increased levels of anxiety and depression among college students. This highlights the need for increased awareness and education about the potential negative effects of social media use on mental health, particularly among college students.

Despite the limitations of our study, such as the small sample size and self-reported data, our findings have important implications for future research and practice. Future studies should aim to replicate our findings in larger, more diverse samples, and investigate the potential mechanisms underlying the association between social media use and mental health. In addition, interventions should be developed to promote healthy social media use among college students, such as mindfulness-based approaches and social media detox programs.

Overall, our study contributes to the growing body of research on the impact of social media on mental health, and highlights the importance of addressing this issue in the context of higher education. By raising awareness and promoting healthy social media use among college students, we can help to reduce the negative impact of social media on mental health and improve the well-being of young adults.

Purpose of Research Paper Conclusion

The purpose of a research paper conclusion is to provide a summary and synthesis of the key findings, significance, and implications of the research presented in the paper. The conclusion serves as the final opportunity for the writer to convey their message and leave a lasting impression on the reader.

The conclusion should restate the research problem or question, summarize the main results of the research, and explain their significance. It should also acknowledge the limitations of the study and suggest areas for future research or action.

Overall, the purpose of the conclusion is to provide a sense of closure to the research paper and to emphasize the importance of the research and its potential impact. It should leave the reader with a clear understanding of the main findings and why they matter. The conclusion serves as the writer’s opportunity to showcase their contribution to the field and to inspire further research and action.

When to Write Research Paper Conclusion

The conclusion of a research paper should be written after the body of the paper has been completed. It should not be written until the writer has thoroughly analyzed and interpreted their findings and has written a complete and cohesive discussion of the research.

Before writing the conclusion, the writer should review their research paper and consider the key points that they want to convey to the reader. They should also review the research question, hypotheses, and methodology to ensure that they have addressed all of the necessary components of the research.

Once the writer has a clear understanding of the main findings and their significance, they can begin writing the conclusion. The conclusion should be written in a clear and concise manner, and should reiterate the main points of the research while also providing insights and recommendations for future research or action.

Characteristics of Research Paper Conclusion

The characteristics of a research paper conclusion include:

• Clear and concise: The conclusion should be written in a clear and concise manner, summarizing the key findings and their significance.
• Comprehensive: The conclusion should address all of the main points of the research paper, including the research question or problem, the methodology, the main results, and their implications.
• Future-oriented : The conclusion should provide insights and recommendations for future research or action, based on the findings of the research.
• Impressive : The conclusion should leave a lasting impression on the reader, emphasizing the importance of the research and its potential impact.
• Objective : The conclusion should be based on the evidence presented in the research paper, and should avoid personal biases or opinions.
• Unique : The conclusion should be unique to the research paper and should not simply repeat information from the introduction or body of the paper.

Advantages of Research Paper Conclusion

The advantages of a research paper conclusion include:

• Summarizing the key findings : The conclusion provides a summary of the main findings of the research, making it easier for the reader to understand the key points of the study.
• Emphasizing the significance of the research: The conclusion emphasizes the importance of the research and its potential impact, making it more likely that readers will take the research seriously and consider its implications.
• Providing recommendations for future research or action : The conclusion suggests practical recommendations for future research or action, based on the findings of the study.
• Providing closure to the research paper : The conclusion provides a sense of closure to the research paper, tying together the different sections of the paper and leaving a lasting impression on the reader.
• Demonstrating the writer’s contribution to the field : The conclusion provides the writer with an opportunity to showcase their contribution to the field and to inspire further research and action.

Limitations of Research Paper Conclusion

While the conclusion of a research paper has many advantages, it also has some limitations that should be considered, including:

• I nability to address all aspects of the research: Due to the limited space available in the conclusion, it may not be possible to address all aspects of the research in detail.
• Subjectivity : While the conclusion should be objective, it may be influenced by the writer’s personal biases or opinions.
• Lack of new information: The conclusion should not introduce new information that has not been discussed in the body of the research paper.
• Lack of generalizability: The conclusions drawn from the research may not be applicable to other contexts or populations, limiting the generalizability of the study.
• Misinterpretation by the reader: The reader may misinterpret the conclusions drawn from the research, leading to a misunderstanding of the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Conclusions

What this handout is about.

This handout will explain the functions of conclusions, offer strategies for writing effective ones, help you evaluate conclusions you’ve drafted, and suggest approaches to avoid.

About conclusions

Introductions and conclusions can be difficult to write, but they’re worth investing time in. They can have a significant influence on a reader’s experience of your paper.

Just as your introduction acts as a bridge that transports your readers from their own lives into the “place” of your analysis, your conclusion can provide a bridge to help your readers make the transition back to their daily lives. Such a conclusion will help them see why all your analysis and information should matter to them after they put the paper down.

Your conclusion is your chance to have the last word on the subject. The conclusion allows you to have the final say on the issues you have raised in your paper, to synthesize your thoughts, to demonstrate the importance of your ideas, and to propel your reader to a new view of the subject. It is also your opportunity to make a good final impression and to end on a positive note.

Your conclusion can go beyond the confines of the assignment. The conclusion pushes beyond the boundaries of the prompt and allows you to consider broader issues, make new connections, and elaborate on the significance of your findings.

Your conclusion should make your readers glad they read your paper. Your conclusion gives your reader something to take away that will help them see things differently or appreciate your topic in personally relevant ways. It can suggest broader implications that will not only interest your reader, but also enrich your reader’s life in some way. It is your gift to the reader.

Strategies for writing an effective conclusion

One or more of the following strategies may help you write an effective conclusion:

• Play the “So What” Game. If you’re stuck and feel like your conclusion isn’t saying anything new or interesting, ask a friend to read it with you. Whenever you make a statement from your conclusion, ask the friend to say, “So what?” or “Why should anybody care?” Then ponder that question and answer it. Here’s how it might go: You: Basically, I’m just saying that education was important to Douglass. Friend: So what? You: Well, it was important because it was a key to him feeling like a free and equal citizen. Friend: Why should anybody care? You: That’s important because plantation owners tried to keep slaves from being educated so that they could maintain control. When Douglass obtained an education, he undermined that control personally. You can also use this strategy on your own, asking yourself “So What?” as you develop your ideas or your draft.
• Return to the theme or themes in the introduction. This strategy brings the reader full circle. For example, if you begin by describing a scenario, you can end with the same scenario as proof that your essay is helpful in creating a new understanding. You may also refer to the introductory paragraph by using key words or parallel concepts and images that you also used in the introduction.
• Synthesize, don’t summarize. Include a brief summary of the paper’s main points, but don’t simply repeat things that were in your paper. Instead, show your reader how the points you made and the support and examples you used fit together. Pull it all together.
• Include a provocative insight or quotation from the research or reading you did for your paper.
• Propose a course of action, a solution to an issue, or questions for further study. This can redirect your reader’s thought process and help them to apply your info and ideas to their own life or to see the broader implications.
• Point to broader implications. For example, if your paper examines the Greensboro sit-ins or another event in the Civil Rights Movement, you could point out its impact on the Civil Rights Movement as a whole. A paper about the style of writer Virginia Woolf could point to her influence on other writers or on later feminists.

Strategies to avoid

• Beginning with an unnecessary, overused phrase such as “in conclusion,” “in summary,” or “in closing.” Although these phrases can work in speeches, they come across as wooden and trite in writing.
• Stating the thesis for the very first time in the conclusion.
• Introducing a new idea or subtopic in your conclusion.
• Ending with a rephrased thesis statement without any substantive changes.
• Making sentimental, emotional appeals that are out of character with the rest of an analytical paper.
• Including evidence (quotations, statistics, etc.) that should be in the body of the paper.

Four kinds of ineffective conclusions

• The “That’s My Story and I’m Sticking to It” Conclusion. This conclusion just restates the thesis and is usually painfully short. It does not push the ideas forward. People write this kind of conclusion when they can’t think of anything else to say. Example: In conclusion, Frederick Douglass was, as we have seen, a pioneer in American education, proving that education was a major force for social change with regard to slavery.
• The “Sherlock Holmes” Conclusion. Sometimes writers will state the thesis for the very first time in the conclusion. You might be tempted to use this strategy if you don’t want to give everything away too early in your paper. You may think it would be more dramatic to keep the reader in the dark until the end and then “wow” them with your main idea, as in a Sherlock Holmes mystery. The reader, however, does not expect a mystery, but an analytical discussion of your topic in an academic style, with the main argument (thesis) stated up front. Example: (After a paper that lists numerous incidents from the book but never says what these incidents reveal about Douglass and his views on education): So, as the evidence above demonstrates, Douglass saw education as a way to undermine the slaveholders’ power and also an important step toward freedom.
• The “America the Beautiful”/”I Am Woman”/”We Shall Overcome” Conclusion. This kind of conclusion usually draws on emotion to make its appeal, but while this emotion and even sentimentality may be very heartfelt, it is usually out of character with the rest of an analytical paper. A more sophisticated commentary, rather than emotional praise, would be a more fitting tribute to the topic. Example: Because of the efforts of fine Americans like Frederick Douglass, countless others have seen the shining beacon of light that is education. His example was a torch that lit the way for others. Frederick Douglass was truly an American hero.
• The “Grab Bag” Conclusion. This kind of conclusion includes extra information that the writer found or thought of but couldn’t integrate into the main paper. You may find it hard to leave out details that you discovered after hours of research and thought, but adding random facts and bits of evidence at the end of an otherwise-well-organized essay can just create confusion. Example: In addition to being an educational pioneer, Frederick Douglass provides an interesting case study for masculinity in the American South. He also offers historians an interesting glimpse into slave resistance when he confronts Covey, the overseer. His relationships with female relatives reveal the importance of family in the slave community.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Douglass, Frederick. 1995. Narrative of the Life of Frederick Douglass, an American Slave, Written by Himself. New York: Dover.

Hamilton College. n.d. “Conclusions.” Writing Center. Accessed June 14, 2019. https://www.hamilton.edu//academics/centers/writing/writing-resources/conclusions .

Holewa, Randa. 2004. “Strategies for Writing a Conclusion.” LEO: Literacy Education Online. Last updated February 19, 2004. https://leo.stcloudstate.edu/acadwrite/conclude.html.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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• How to Write Discussions and Conclusions

The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.

What makes an effective discussion?

When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.

A successful discussion section puts your findings in context. It should include:

• the results of your research,
• a discussion of related research, and
• a comparison between your results and initial hypothesis.

Tip: Not all journals share the same naming conventions.

You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.

Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts. 

Questions to ask yourself:

• Was my hypothesis correct?
• If my hypothesis is partially correct or entirely different, what can be learned from the results? 
• How do the conclusions reshape or add onto the existing knowledge in the field? What does previous research say about the topic? 
• Why are the results important or relevant to your audience? Do they add further evidence to a scientific consensus or disprove prior studies? 
• How can future research build on these observations? What are the key experiments that must be done? 
• What is the “take-home” message you want your reader to leave with?

How to structure a discussion

Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:

Writing Tips

While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results! 

• Read the journal’s guidelines on the discussion and conclusion sections. If possible, learn about the guidelines before writing the discussion to ensure you’re writing to meet their expectations. 
• Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. 
• Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and limitations of the research. 
• State whether the results prove or disprove your hypothesis. If your hypothesis was disproved, what might be the reasons? 
• Introduce new or expanded ways to think about the research question. Indicate what next steps can be taken to further pursue any unresolved questions. 
• If dealing with a contemporary or ongoing problem, such as climate change, discuss possible consequences if the problem is avoided. 
• Be concise. Adding unnecessary detail can distract from the main findings. 

Don’t

• Rewrite your abstract. Statements with “we investigated” or “we studied” generally do not belong in the discussion. 
• Include new arguments or evidence not previously discussed. Necessary information and evidence should be introduced in the main body of the paper. 
• Apologize. Even if your research contains significant limitations, don’t undermine your authority by including statements that doubt your methodology or execution. 
• Shy away from speaking on limitations or negative results. Including limitations and negative results will give readers a complete understanding of the presented research. Potential limitations include sources of potential bias, threats to internal or external validity, barriers to implementing an intervention and other issues inherent to the study design. 
• Overstate the importance of your findings. Making grand statements about how a study will fully resolve large questions can lead readers to doubt the success of the research. 

Snippets of Effective Discussions:

Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach

Identifying reliable indicators of fitness in polar bears

• How to Write a Great Title
• How to Write an Abstract
• How to Write Your Methods
• How to Report Statistics
• How to Edit Your Work

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The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

How to Write a Conclusion for a Research Paper

By the time you write the conclusion, you should have pointed out in the body of your research paper why your topic is important to the reader, and you should have presented the reader with all your arguments. It is critical that you do not introduce new information or ideas in your conclusion. If you find that you have not yet made the arguments you wished to make or pointed out evidence you feel is crucial to your reader’s understanding of your subject, you are not yet ready to write the conclusion; add another body paragraph before writing the conclusion.

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Your research paper should have a strong, succinct concluding section, where you draw together your findings. Think of it as a conclusion, not a summary. The difference is that you are reaching overall judgments about your topic, not summarizing everything you wrote about it. How to write a conclusion for a research paper? The focus should be on:

• Saying what your research has found, what the findings mean, and how well they support the argument of your thesis statement.
• Establishing the limits of your argument: How widely does it apply? What are the strengths and weaknesses of your method? How clear-cut are your findings?
• Explaining how your findings and argument fit into your field, relating them to answers others have given and to the existing literature.

You may also want to add some concise comments about possible future developments or what kind of research should come next, but don’t lay it on too thick. The place of honor goes to your own explanation. Don’t spend too much of your final section criticizing others. Don’t introduce any big new topics or ideas. You certainly don’t expect to see new characters in the last scene of a movie. For the same reasons, you shouldn’t find any big new topics being introduced in the last paragraphs of a research paper.

Your concluding statement should focus on what your findings mean. How do you interpret them? Are they just as easily explained by alternative theories or other perspectives? Here, you are returning to the questions that first animated you and answering them, based on your research. You not only want to give the answers; you also want to explain their significance. What do they mean for policy, theory, literary interpretation, moral action, or whatever? You are answering the old, hard question: “So what?”

Be wary of overreaching. You really need to do two things at the same time: explain the significance of your findings and stake out their limits. You may have a hunch that your findings apply widely but, as a social scientist, you need to assess whether you can say so confidently, based on your current research. Your reader needs to know: “Do these findings apply to all college students, to all adults, or only to white mice?” White mice don’t come up much in the humanities, but the reader still wants to know how far your approach reaches. Does your analysis apply only to this novel or this writer, or could it apply to a whole literary genre?

Make it a priority to discuss these conclusions with your professor or adviser. The main danger here is that students finally reach this final section with only a week or two left before the due date. They don’t have enough time to work through their conclusions and revise them. That leaves the research paper weakest at the end, precisely where it should be strongest, nailing down the most significant points.

Begin discussing your major findings with your adviser while you are still writing the heart of the research paper. Of course, your conclusions will be tentative at that stage, but it helps to begin talking about them. As always, a little writing helps. You could simply list your main findings or write out a few paragraphs about them. Either would serve as a launching pad for meetings with your adviser. You will find these discussions also shed light on the research that leads to these findings. That, in turn, will strengthen your middle sections. Later, when you draft the conclusion, review your notes on these talks and the short documents you wrote for them. They will serve as prewriting for the final section.

The opening sentence of the conclusion should flow smoothly and logically from the transition sentence in the previous paragraph and lead the reader to reflect on your thesis. A good conclusion however, does not simply restate the thesis. You want to remind the reader of the thesis in your conclusion but reword it in a stronger fashion so that it is interesting and memorable to your audience.After reminding the reader of the thesis, the conclusion should then reflect on the topics in the body of the paper and summarize the key findings of your research. If you are writing a persuasive paper, it should summarize your key arguments and logically point your readers to the conclusion you wish them to reach.

Phrases for Conclusions of Research Papers

• All this requires us to (propose the next action or an alternative idea).
• Altogether, these findings indicate (point out the logical result).
• Finally, it is important to note (make your strongest point and follow with a recommendation).
• In conclusion (restate your thesis with greater emphasis).
• It is evident that (point out the logical result or obvious next action).
• In light of the evidence, (restate your thesis with greater emphasis).
• In short, (summarize your findings).
• It should be evident that we need to (propose the next action or an alternative idea).
• In summary, (summarize your findings).
• Looking ahead, it is obvious that (propose the next action or an alternative idea).
• My conclusion is (restate your thesis with greater emphasis).
• One last word must be said. (Follow with your opinion and propose a next action.)
• One concludes that (give your opinion).
• Overall, (summarize your findings).
• Reflecting on these facts,we can see that …
• The evidence presented above shows that (give your opinion).
• The reader can conclude (make the point you wish to make).
• These facts and observations support the idea that (offer a theory).
• This analysis reveals (state your findings).
• To conclude, (give an opinion based on the findings presented in the paper).
• To sum up this discussion, (summarize your findings).
• To summarize, (summarize your findings).
• We arrive at the following conclusion: (give an opinion based on the findings presented in the paper).
• We cannot ignore the fact that (state an important concern and follow with a call to action).
• We can postulate (give your opinion or offer a theory).
• We come to the conclusion that (give your opinion or offer a theory).
• We can now present the theory that (give your opinion or offer a theory).

Examples of Strong Conclusions

As an example of how to end your research paper, let’s turn again to John Dower’s splendid book on postwar Japan, Embracing Defeat: Japan in the Wake of World War II . In the final pages, Dower pulls together his findings on war-ravaged Japan and its efforts to rebuild. He then judges the legacies of that period: its continuing impact on the country’s social, political, and economic life. Some insights are unexpected, at least to me. He argues that Japan has pursued trade protection as the only acceptable avenue for its persistent nationalism. America’s overwhelming power and Japan’s self-imposed restraints—the intertwined subjects of the book—blocked any political or military expression of Japan’s nationalist sentiment. Those avenues were simply too dangerous, he says, while economic nationalism was not. Dower ends with these paragraphs:

The Japanese economists and bureaucrats who drafted the informal 1946 blueprint for a planned economy were admirably clear on these objectives [of “demilitarization and democratization”]. They sought rapid recovery and maximum economic growth, of course—but they were just as concerned with achieving economic demilitarization and economic democracy. . . . Japan became wealthy. The standard of living rose impressively at every level of society. Income distribution was far more equitable than in the United States. Job security was assured. Growth was achieved without inordinate dependence on a military-industrial complex or a thriving trade in armaments. These are hardly trivial ideas, but they are now being discarded along with all the deservedly bankrupt aspects of the postwar system. The lessons and legacies of defeat have been many and varied indeed; and their end is not yet in sight. (John W. Dower, Embracing Defeat: Japan in the Wake of World War II . New York: W. W. Norton, 1999, pp. 563–64)

Remember the anecdotal opening of Herbert’s book Impressionism: Art, Leisure, and Parisian Society , with Henry Tuckerman’s 1867 arrival in a much-changed Paris? (see research paper introduction examples) Herbert strikes a completely different tone in his conclusion. It synthesizes the art history he has presented, offers a large judgment about where Impressionism fits among art movements, and suggests why exhibitions of Monet, Manet, and Renoir are still so popular. He manages to do all that in a few well-crafted sentences:

Although we credit [Impressionism] with being the gateway to modern art, we also treat it as the last of the great Western styles based upon a perception of harmony with natural vision. That harmony, long since lost to us in this century of urbanization, industrialization, and world wars, remains a longed-for idea, so we look back to Impressionism as the painting of a golden era. We flock into exhibitions of paintings that represent cafes, boating, promenading, and peaceful landscapes precisely because of our yearning for less troubled times. The only history that we feel deeply is the kind that is useful to us. Impressionism still looms large at the end of the twentieth century because we use its leisure-time subjects and its brilliantly colored surfaces to construct a desirable history. (Herbert, Impressionism , p. 306)

Robert Dallek offers similarly accessible, powerful judgments in his conclusion to Flawed Giant: Lyndon Johnson and His Times, 1961–1973 :

[Johnson’s] presidency was a story of great achievement and terrible failure, of lasting gains and unforgettable losses. . . . In a not so distant future, when coming generations have no direct experience of the man and the passions of the sixties are muted, Johnson will probably be remembered as a President who faithfully reflected the country’s greatness and limitations—a man notable for his successes and failures, for his triumphs and tragedy. Only one thing seems certain: Lyndon Johnson will not join the many obscure—almost nameless, faceless—Presidents whose terms of office register on most Americans as blank slates. He will not be forgotten. (Robert Dallek, Flawed Giant: Lyndon Johnson and His Times, 1961–1973 . New York: Oxford University Press, 1998, p. 628)

Some writers not only synthesize their findings or compare them to others; they use the conclusion to say what their work means for appropriate methods or subject matter in their field. That is what Robert Bruegmann does in his final statement in The Architects and the City: Holabird & Roche of Chicago, 1880–1918 . His conclusion goes beyond saying that this was a great architectural firm or that it designed buildings of lasting importance. Bruegmann tells us that Holabird & Roche helped shape modern Chicago and that its work, properly studied, helps us understand “the city as the ultimate human artifact”:

Traditional architectural history has tended to see the city less as a process than as a product, a collection of high art architectural objects in a setting dominated by mundane buildings of little interest. This tended to perpetuate a destructive and divisive attitude about the built environment, suggesting that only a few buildings are worthy of careful study and preservation while all others are mere backdrop. I hope that these explorations in the work of Holabird & Roche have shed light on parts of the city rarely visited by the architectural historian and on some little explored aspects of its history. If so, perhaps it has achieved its most basic goal: providing an insight into the city as the ultimate human artifact, our most complex and prodigious social creation, and the most tangible result of the actions over time of all its citizens. (Robert Bruegmann, The Architects and the City: Holabird & Roche of Chicago, 1880–1918 . Chicago: University of Chicago Press, 1997, p. 443)

These are powerful conclusions, ending major works of scholarship on a high note. What concluding paragraphs should never do is gaze off into the sunset, offer vague homilies, or claim you have found the meaning of human existence. Be concrete. Stick to your topic. Make sure your research paper conclusions stand on solid ground. Avoid vague platitudes in your conclusion. Your goal should be reaching strong, sound judgments, firmly grounded in your readings and research. Better to claim too little than too much. Best of all, claim what you’ve earned the right to say: what your research really means.

Having finished the main parts of a research paper you can write an abstract.

Back to  How To Write A Research Paper .

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How to Write a Conclusion for a Research Paper

Last Updated: May 8, 2024 Approved

This article was co-authored by Christopher Taylor, PhD . Christopher Taylor is an Adjunct Assistant Professor of English at Austin Community College in Texas. He received his PhD in English Literature and Medieval Studies from the University of Texas at Austin in 2014. wikiHow marks an article as reader-approved once it receives enough positive feedback. This article received 42 testimonials and 83% of readers who voted found it helpful, earning it our reader-approved status. This article has been viewed 2,260,216 times.

The conclusion of a research paper needs to summarize the content and purpose of the paper without seeming too wooden or dry. Every basic conclusion must share several key elements, but there are also several tactics you can play around with to craft a more effective conclusion and several you should avoid to prevent yourself from weakening your paper's conclusion. Here are some writing tips to keep in mind when creating a conclusion for your next research paper.

Sample Conclusions

Writing a basic conclusion.

• Do not spend a great amount of time or space restating your topic.
• A good research paper will make the importance of your topic apparent, so you do not need to write an elaborate defense of your topic in the conclusion.
• Usually a single sentence is all you need to restate your topic.
• An example would be if you were writing a paper on the epidemiology of infectious disease, you might say something like "Tuberculosis is a widespread infectious disease that affects millions of people worldwide every year."
• Yet another example from the humanities would be a paper about the Italian Renaissance: "The Italian Renaissance was an explosion of art and ideas centered around artists, writers, and thinkers in Florence."

• A thesis is a narrowed, focused view on the topic at hand.
• This statement should be rephrased from the thesis you included in your introduction. It should not be identical or too similar to the sentence you originally used.
• Try re-wording your thesis statement in a way that complements your summary of the topic of your paper in your first sentence of your conclusion.
• An example of a good thesis statement, going back to the paper on tuberculosis, would be "Tuberculosis is a widespread disease that affects millions of people worldwide every year. Due to the alarming rate of the spread of tuberculosis, particularly in poor countries, medical professionals are implementing new strategies for the diagnosis, treatment, and containment of this disease ."

• A good way to go about this is to re-read the topic sentence of each major paragraph or section in the body of your paper.
• Find a way to briefly restate each point mentioned in each topic sentence in your conclusion. Do not repeat any of the supporting details used within your body paragraphs.
• Under most circumstances, you should avoid writing new information in your conclusion. This is especially true if the information is vital to the argument or research presented in your paper.
• For example, in the TB paper you could summarize the information. "Tuberculosis is a widespread disease that affects millions of people worldwide. Due to the alarming rate of the spread of tuberculosis, particularly in poor countries, medical professionals are implementing new strategies for the diagnosis, treatment, and containment of this disease. In developing countries, such as those in Africa and Southeast Asia, the rate of TB infections is soaring. Crowded conditions, poor sanitation, and lack of access to medical care are all compounding factors in the spread of the disease. Medical experts, such as those from the World Health Organization are now starting campaigns to go into communities in developing countries and provide diagnostic testing and treatments. However, the treatments for TB are very harsh and have many side effects. This leads to patient non-compliance and spread of multi-drug resistant strains of the disease."

• Note that this is not needed for all research papers.
• If you already fully explained what the points in your paper mean or why they are significant, you do not need to go into them in much detail in your conclusion. Simply restating your thesis or the significance of your topic should suffice.
• It is always best practice to address important issues and fully explain your points in the body of your paper. The point of a conclusion to a research paper is to summarize your argument for the reader and, perhaps, to call the reader to action if needed.

• Note that a call for action is not essential to all conclusions. A research paper on literary criticism, for instance, is less likely to need a call for action than a paper on the effect that television has on toddlers and young children.
• A paper that is more likely to call readers to action is one that addresses a public or scientific need. Let's go back to our example of tuberculosis. This is a very serious disease that is spreading quickly and with antibiotic-resistant forms.
• A call to action in this research paper would be a follow-up statement that might be along the lines of "Despite new efforts to diagnose and contain the disease, more research is needed to develop new antibiotics that will treat the most resistant strains of tuberculosis and ease the side effects of current treatments."

• For example, if you are writing a history paper, then you might discuss how the historical topic you discussed matters today. If you are writing about a foreign country, then you might use the conclusion to discuss how the information you shared may help readers understand their own country.

Making Your Conclusion as Effective as Possible

• Since this sort of conclusion is so basic, you must aim to synthesize the information rather than merely summarizing it.
• Instead of merely repeating things you already said, rephrase your thesis and supporting points in a way that ties them all together.
• By doing so, you make your research paper seem like a "complete thought" rather than a collection of random and vaguely related ideas.

• Ask a question in your introduction. In your conclusion, restate the question and provide a direct answer.
• Write an anecdote or story in your introduction but do not share the ending. Instead, write the conclusion to the anecdote in the conclusion of your paper.
• For example, if you wanted to get more creative and put a more humanistic spin on a paper on tuberculosis, you might start your introduction with a story about a person with the disease, and refer to that story in your conclusion. For example, you could say something like this before you re-state your thesis in your conclusion: "Patient X was unable to complete the treatment for tuberculosis due to severe side effects and unfortunately succumbed to the disease."
• Use the same concepts and images introduced in your introduction in your conclusion. The images may or may not appear at other points throughout the research paper.

• Include enough information about your topic to back the statement up but do not get too carried away with excess detail.
• If your research did not provide you with a clear-cut answer to a question posed in your thesis, do not be afraid to indicate as much.
• Restate your initial hypothesis and indicate whether you still believe it or if the research you performed has begun swaying your opinion.
• Indicate that an answer may still exist and that further research could shed more light on the topic at hand.

• This may not be appropriate for all types of research papers. Most research papers, such as one on effective treatment for diseases, will have the information to make the case for a particular argument already in the paper.
• A good example of a paper that might ask a question of the reader in the ending is one about a social issue, such as poverty or government policy.
• Ask a question that will directly get at the heart or purpose of the paper. This question is often the same question, or some version of it, that you may have started with when you began your research.
• Make sure that the question can be answered by the evidence presented in your paper.
• If desired you can briefly summarize the answer after stating the question. You could also leave the question hanging for the reader to answer, though.

• Even without a call to action, you can still make a recommendation to your reader.
• For instance, if you are writing about a topic like third-world poverty, you can various ways for the reader to assist in the problem without necessarily calling for more research.
• Another example would be, in a paper about treatment for drug-resistant tuberculosis, you could suggest donating to the World Health Organization or research foundations that are developing new treatments for the disease.

Avoiding Common Pitfalls

• These sayings usually sound stiff, unnatural, or trite when used in writing.
• Moreover, using a phrase like "in conclusion" to begin your conclusion is a little too straightforward and tends to lead to a weak conclusion. A strong conclusion can stand on its own without being labeled as such.

• Always state the main argument or thesis in the introduction. A research paper is an analytical discussion of an academic topic, not a mystery novel.
• A good, effective research paper will allow your reader to follow your main argument from start to finish.
• This is why it is best practice to start your paper with an introduction that states your main argument and to end the paper with a conclusion that re-states your thesis for re-iteration.

• All significant information should be introduced in the body of the paper.
• Supporting evidence expands the topic of your paper by making it appear more detailed. A conclusion should narrow the topic to a more general point.
• A conclusion should only summarize what you have already stated in the body of your paper.
• You may suggest further research or a call to action, but you should not bring in any new evidence or facts in the conclusion.

• Most often, a shift in tone occurs when a research paper with an academic tone gives an emotional or sentimental conclusion.
• Even if the topic of the paper is of personal significance for you, you should not indicate as much in your paper.
• If you want to give your paper a more humanistic slant, you could start and end your paper with a story or anecdote that would give your topic more personal meaning to the reader.
• This tone should be consistent throughout the paper, however.

• Apologetic statements include phrases like "I may not be an expert" or "This is only my opinion."
• Statements like this can usually be avoided by refraining from writing in the first-person.
• Avoid any statements in the first-person. First-person is generally considered to be informal and does not fit with the formal tone of a research paper.

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• ↑ http://owl.english.purdue.edu/owl/resource/724/04/
• ↑ http://www.crlsresearchguide.org/18_Writing_Conclusion.asp
• ↑ http://writing.wisc.edu/Handbook/PlanResearchPaper.html#conclusion
• ↑ http://writingcenter.unc.edu/handouts/conclusions/
• ↑ http://writing2.richmond.edu/writing/wweb/conclude.html

About This Article

To write a conclusion for a research paper, start by restating your thesis statement to remind your readers what your main topic is and bring everything full circle. Then, briefly summarize all of the main points you made throughout your paper, which will help remind your readers of everything they learned. You might also want to include a call to action if you think more research or work needs to be done on your topic by writing something like, "Despite efforts to contain the disease, more research is needed to develop antibiotics." Finally, end your conclusion by explaining the broader context of your topic and why your readers should care about it, which will help them understand why your topic is relevant and important. For tips from our Academic co-author, like how to avoid common pitfalls when writing your conclusion, scroll down! Did this summary help you? Yes No

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Writing a Paper: Conclusions

Writing a conclusion.

A conclusion is an important part of the paper; it provides closure for the reader while reminding the reader of the contents and importance of the paper. It accomplishes this by stepping back from the specifics in order to view the bigger picture of the document. In other words, it is reminding the reader of the main argument. For most course papers, it is usually one paragraph that simply and succinctly restates the main ideas and arguments, pulling everything together to help clarify the thesis of the paper. A conclusion does not introduce new ideas; instead, it should clarify the intent and importance of the paper. It can also suggest possible future research on the topic.

An Easy Checklist for Writing a Conclusion

It is important to remind the reader of the thesis of the paper so he is reminded of the argument and solutions you proposed.

Think of the main points as puzzle pieces, and the conclusion is where they all fit together to create a bigger picture. The reader should walk away with the bigger picture in mind.

Make sure that the paper places its findings in the context of real social change.

Make sure the reader has a distinct sense that the paper has come to an end. It is important to not leave the reader hanging. (You don’t want her to have flip-the-page syndrome, where the reader turns the page, expecting the paper to continue. The paper should naturally come to an end.)

No new ideas should be introduced in the conclusion. It is simply a review of the material that is already present in the paper. The only new idea would be the suggesting of a direction for future research.

Conclusion Example

As addressed in my analysis of recent research, the advantages of a later starting time for high school students significantly outweigh the disadvantages. A later starting time would allow teens more time to sleep--something that is important for their physical and mental health--and ultimately improve their academic performance and behavior. The added transportation costs that result from this change can be absorbed through energy savings. The beneficial effects on the students’ academic performance and behavior validate this decision, but its effect on student motivation is still unknown. I would encourage an in-depth look at the reactions of students to such a change. This sort of study would help determine the actual effects of a later start time on the time management and sleep habits of students.

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Organizing Academic Research Papers: 9. The Conclusion

• 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 conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of your points or a re-statement of your research problem but a synthesis of key points. For most essays, one well-developed paragraph is sufficient for a conclusion, although in some cases, a two-or-three paragraph conclusion may be required.

Importance of a Good Conclusion

A well-written conclusion provides you with several important opportunities to demonstrate your overall understanding of the research problem to the reader. These include:

• Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key points in your analysis or findings.
• Summarizing your thoughts and conveying the larger implications of your study . The conclusion is an opportunity to succinctly answer the "so what?" question by placing the study within the context of past research about the topic you've investigated.
• Demonstrating the importance of your ideas . Don't be shy. The conclusion offers you a chance to elaborate on the significance of your findings.
• Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing/contextualizing the research problem based on the results of your study.

Conclusions . The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion . San Francisco Edit, 2003-2008.

Structure and Writing Style

https://writing.wisc.edu/wp-content/uploads/sites/535/2018/07/conclusions_uwmadison_writingcenter_aug2012.pdf I.  General Rules

When writing the conclusion to your paper, follow these general rules:

• State your conclusions in clear, simple language.
• Do not simply reiterate your results or the discussion.
• Indicate opportunities for future research, as long as you haven't already done so in the discussion section of your paper.

The function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Make sure, however, that your conclusion is not simply a repetitive summary of the findings because this reduces the impact of the argument(s) you have developed in your essay.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or point of your paper is complex, you may need to summarize the argument for your reader.
• If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data.

The conclusion also provides a place for you to persuasively and succinctly restate your research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented, or on the essay's central research problem. However, the nature of being introspective about the research you have done will depend on the topic and whether your professor wants you to express your observations in this way.

NOTE : Don't delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply not to guess at possible outcomes.

II.  Developing a Compelling Conclusion

Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following.

• If your essay deals with a contemporary problem, warn readers of the possible consequences of not attending to the problem.
• Recommend a specific course or courses of action.
• Cite a relevant quotation or expert opinion to lend authority to the conclusion you have reached [a good place to look is research from your literature review].
• Restate a key statistic, fact, or visual image to drive home the ultimate point of your paper.
• If your discipline encourages personal reflection, illustrate your concluding point with a relevant narrative drawn from your own life experiences.
• Return to an anecdote, an example, or a quotation that you introduced in your introduction, but add further insight that is derived from the findings of your study; use your interpretation of results to reframe it in new ways.
• Provide a "take-home" message in the form of a strong, succient statement that you want the reader to remember about your study.

III. Problems to Avoid Failure to be concise The conclusion section should be concise and to the point. Conclusions that are too long often have unnecessary detail. The conclusion section is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, etc. that you make. Failure to comment on larger, more significant issues In the introduction, your task was to move from general [the field of study] to specific [your research problem]. However, in the conclusion, your task is to move from specific [your research problem] back to general [your field, i.e., how your research contributes new understanding or fills an important gap in the literature]. In other words, the conclusion is where you place your research within a larger context. Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. Problems, drawbacks, and challenges encountered during your study should be included as a way of qualifying your overall conclusions. If you encountered negative results [findings that are validated outside the research context in which they were generated], you must report them in the results section of your paper. In the conclusion, use the negative results as an opportunity to explain how they provide information on which future research can be based. Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits back into your field of study [and possibly the world at large], you need to summarize it briefly and directly. Often this element of your conclusion is only a few sentences long. Failure to match the objectives of your research Often research objectives change while the research is being carried out. This is not a problem unless you forget to go back and refine your original objectives in your introduction, as these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you now know a good deal about it, perhaps even more than your professor! Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts!  Don't undermine your authority by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches...."

Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions . The Writing Center. University of North Carolina; Conclusions . The Writing Lab and The OWL. Purdue University; Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions . The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count . The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Tips for Writing a Good Conclusion . Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion . San Francisco Edit, 2003-2008; Writing Conclusions . Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization . Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining to read, when an essay is about to end. You'll irritate your readers if you belabor the obvious.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your Conclusion that was never referenced anywhere else in the paper. If you have new information to present, add it to the Discussion or other appropriate section of the paper.  Note that, although no actual new information is introduced, the conclusion is where you offer your most "original" contributions in the paper; it's where you describe the value of your research, demonstrate your understanding of the material that you’ve presented, and locate your findings within the larger context of scholarship on the topic.

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How to Write a Conclusion for a Research Paper

Find out which type of conclusion best suits your research, how to write it step-by-step, and common mistakes to avoid.

When writing a research paper, it can be challenging to make your point after providing an extensive amount of information. For this reason, a well-organized conclusion is essential. 

A research paper’s conclusion should be a brief summary of the paper’s substance and objectives; what you present in your research paper can gain impact by having a strong conclusion section.

In this Mind The Graph article, you will learn how to write a conclusion for a research report in a way that inspires action and helps the readers to better understand your research paper. This article will provide you the definition and some broad principles before providing step-by-step guidance.

What is a conclusion for a research paper and why is it important?

A conclusion is where you summarize the main points and, if appropriate, make new research suggestions. It is not merely a summary of the key points discussed or a rehash of your research question.

The reader is expected to comprehend from the article’s conclusion why your study should be significant to them after reading it. A conclusion of one or two well-developed paragraphs is appropriate for the majority of research papers; however, in a few unusual cases, more paragraphs may be required to highlight significant findings and their importance.

Just as the introduction is responsible for giving the reader a first impression on the subject, the conclusion is the chance to make a final impression by summarizing major information of your research paper and, most often, giving a different point of view on significant implications.

Adding a strong conclusion to your research paper is important because it’s a possibility to give the reader the comprehension of your research topic. Given that the reader is now fully informed on the subject, the conclusion also gives you a chance to restate the research problem effectively and concisely.

Examples of conclusions for a research paper

Now that you are aware of what a conclusion is and its significance for a research paper, it is time to provide you with some excellent samples of well-structured conclusions so you may get knowledge about the type of conclusion you can use for your research paper.

Argumentative Research Paper Conclusion

The most convincing arguments from your research paper should be added to the conclusion if you want to compose a strong argumentative conclusion.

Additionally, if your thesis statement expresses your perspective on the subject, you should think about restarting it as well as including any other pertinent information.

Example: As a result of the sixth extinction, which is currently affecting Earth, many species are vanishing every day. There are at least three strategies that people could employ to keep them from going extinct entirely in the ensuing fifty years. More recycling options, innovative plastic production techniques, and species preservation could save lives.

Analytical Research Paper Conclusion

The first thing you should do is reiterate your thesis and list the main elements of your arguments.

There should undoubtedly be a spotlight on a bigger context in the analytical research paper conclusion, which is the key distinction between it and other types of conclusions. It means you can add some meaning to the findings.

Example: Elon Musk has revolutionized the way we drive, pay for things, and even fly. His innovations are solely motivated by the desire to simplify things, but they inevitably alter the course of history. When Musk was a student, he had his first idea for PayPal, which is now among the most widely used methods of online payment. Likewise with Tesla automobiles.

Comparative Research Paper Conclusion

The conclusion of a comparative essay should be deeply analytical. To clearly express your conclusions, you must be very thorough when reviewing the data. Furthermore, the sources must be reliable.

A paraphrased thesis statement and a few sentences describing the significance of your study research are also required, as per normal.

Example: Gas-powered vehicles are ineffective and inefficient compared to electric vehicles. Not only do they emit fewer pollutants, but the drivers also get there more quickly. Additionally, gas cars cost more to maintain. Everything stems from the details of the far more straightforward engines used in electric cars.

How to write a conclusion for a research paper

In this section, you will learn how to write a conclusion for a research paper effectively and properly. These few easy steps will enable you to write the most convincing conclusion to your research paper.

1. Remember about the main topic

The statement must be written clearly and concisely to be effective, just one sentence. Remember that your conclusion should be concise and precise, expressing only the most important elements.

2. Reaffirm your thesis

Restate the research paper’s thesis after that. This can be done by going back to the original thesis that you presented in the research’s introduction. The thesis statement in your conclusion must be expressed differently from how it was in the introduction. This section can also be written effectively in a single sentence.

3. Sum important points in a summary

It’s time to make a list of the important arguments in your research paper. This phase can be made simpler by reading over your research and emphasizing only the main ideas and evidence.

Remember that the conclusion should not contain any new information. Focus only on the concepts you cover in your paper’s main body as a result. And also, keep in mind that this brief summary reminds your readers of the importance of the topic you are researching.

4. Emphasize the importance

At this stage, you can genuinely express a few words about how significant your arguments are. A succinct but impactful sentence can successfully achieve its aim. You could also attempt to examine this circumstance from a wider perspective.

Give an example of how your discoveries have affected a certain field. It would be beneficial if you made an effort to answer the question, “So what?” if there was any ambiguity.

5. Finish up your argument

As you wrap up your conclusion, consider posing a question or a call to action that will encourage readers to consider your point of view even further. This sentence can also answer any queries that were not addressed in the paper’s body paragraphs.

In addition, if there is an unresolved question in the main body, this is a fantastic area to comment on.

Common mistakes you should avoid

After learning the fundamentals of producing a strong research paper conclusion, it’s time to learn the common mistakes to avoid.

• Weak conclusion: If your ending is weak, readers will feel dissatisfied and disappointed. Writing ambiguous closing lines for essays also lowers the quality of the paper and the capacity of your arguments to support your main topic.
• Abrupt conclusion: Your research has to be an expression of your writing as a whole, not just a section. Therefore, make sure your thoughts are fully stated.
• Adding new information: Only your research should only be summarized in the conclusion. As the conclusion cannot contain extra information, make sure to offer all of your conclusions and supporting evidence in the body paragraphs.
• Absence of focus: A conclusion needs to be concise and well-focused. Avoid concluding the research with inane or superfluous details.
• Absurd length: Research must be of a proper length—neither too long nor too short. If you write more than is necessary, you can miss the point, which is to revisit the paper’s argument straightforwardly. Additionally, if you write too little, your readers will think you’re being negligent. It should be written in at least one or two whole paragraphs.

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How to Write a Conclusion for a Research Paper

When you're wrapping up a research paper, the conclusion is like the grand finale of a fireworks show – it's your chance to leave a lasting impression. In this article, we'll break down the steps to help you write a winning research paper conclusion that not only recaps your main points but also ties everything together. Consider it the "So what?" moment – why should people care about your research? Our professional essay writers will guide you through making your conclusion strong, clear, and something that sticks with your readers long after they've put down your paper. So, let's dive in and ensure your research ends on a high note!

What Is a Conclusion in a Research Paper

In a research paper, the conclusion serves as the final segment, where you summarize the main points and findings of your study. It's not just a repetition of what you've already said but rather a chance to tie everything together and highlight the significance of your research. As you learn how to start a research paper , a good conclusion also often discusses the implications of your findings, suggests potential areas for further research, and leaves the reader with a lasting impression of the importance and relevance of your work in the broader context of the field. Essentially, it's your last opportunity to make a strong impact and leave your readers with a clear understanding of the significance of your research. Here’s a research paper conclusion example:

In conclusion, this research paper has navigated the intricacies of sustainable urban development, shedding light on the pivotal role of community engagement and innovative planning strategies. Through applying qualitative and quantitative research methods, we've uncovered valuable insights into the challenges and opportunities inherent in fostering environmentally friendly urban spaces. The implications of these findings extend beyond the confines of this study, emphasizing the imperative for continued exploration in the realms of urban planning and environmental sustainability. By emphasizing both the practical applications and theoretical contributions, this research underscores the significance of community involvement and forward-thinking strategies in shaping the future of urban landscapes. As cities evolve, incorporating these insights into planning and development practices will create resilient and harmonious urban environments.

Conclusion Outline for Research Paper

This outline for a research paper conclusion provides a structured framework to ensure that your ending effectively summarizes the key elements of your research paper and leaves a lasting impression on your readers. Adjust the content based on the specific requirements and focus of your research.

Restate the Thesis Statement

• Briefly restate the main thesis or research question.
• Emphasize the core objective or purpose of the study.

Summarize Key Findings

• Recap the main points and key findings from each section of the paper.
• Provide a concise overview of the research journey.

Discuss Implications

• Explore the broader implications of the research findings.
• Discuss how the results contribute to the existing body of knowledge in the field.

Address Limitations

• Acknowledge any limitations or constraints encountered during the research process.
• Explain how these limitations may impact the interpretation of the findings.

Suggest Areas for Future Research

• Propose potential directions for future studies related to the topic.
• Identify gaps in the current research that warrant further exploration.

Reaffirm Significance

• Reaffirm the importance and relevance of the research in the broader context.
• Highlight the practical applications or real-world implications of the study.

Concluding Statement

• Craft a strong, memorable closing statement that leaves a lasting impression.
• Sum up the overall impact of the research and its potential contribution to the field.

Study the full guide on how to make a research paper outline here, which will also specify the conclusion writing specifics to improve your general prowess.

Tips on How to Make a Conclusion in Research

Here are key considerations regarding a conclusion for research paper to not only recap the primary ideas in your work but also delve deeper to earn a higher grade:

• Provide a concise recap of your main research outcomes.
• Remind readers of your research goals and their accomplishments.
• Stick to summarizing existing content; refrain from adding new details.
• Emphasize why your research matters and its broader implications.
• Clearly explain the practical or theoretical impact of your findings.
• Prompt readers to reflect on how your research influences their perspective.
• Briefly discuss the robustness of your research methods.
• End with a suggestion for future research or a practical application.
• Transparently address any constraints or biases in your study.
• End on a powerful note, leaving a memorable impression on your readers.

For your inspiration, we’ve also prepared this research proposal example APA , which dwells on another important aspect of research writing.

How to Write a Research Paper Conclusion

As you finish your research paper, the conclusion takes center stage. In this section, we've got five practical tips for writing a conclusion for a research paper. We'll guide you through summarizing your key findings, revisiting your research goals, discussing the bigger picture, addressing any limitations, and ending on a powerful note. Think of it as your roadmap to creating a conclusion that not only wraps up your research but also leaves a lasting impact on your readers. Let's dive in and make sure your conclusion stands out for all the right reasons!

Synthesize Core Discoveries. Initiate your conclusion by synthesizing the essential discoveries of your research. Offer a succinct recapitulation of the primary points and outcomes you have elucidated in your paper. This aids in reinforcing the gravity of your work and reiterates the pivotal information you have presented.

Revisit Research Objectives. Revisit the research objectives or questions you outlined at the beginning of your paper. Assess whether you have successfully addressed these objectives and if your findings align with the initial goals of your research. This reflection helps tie your conclusion back to the purpose of your study.

Discuss Implications and Contributions. Discuss the broader implications of your research and its potential contributions to the field. Consider how your findings might impact future research, applications, or understanding of the subject matter. This demonstrates the significance of your work and places it within a larger context.

Address Limitations and Future Research. Acknowledge any limitations in your study, such as constraints in data collection or potential biases. Briefly discuss how these limitations might have affected your results. Additionally, suggest areas for future research that could build upon your work, addressing any unanswered questions or unexplored aspects. This demonstrates a thoughtful approach to your research.

End with a Strong Conclusion Statement. Conclude your research paper with a strong and memorable statement that reinforces the key message you want readers to take away. This could be a call to action, a proposal for further investigation, or a reflection on the broader significance of your findings. Leave your readers with a lasting impression that emphasizes the importance of your research. Remember that you can buy a research paper anytime if you lack time or get stuck in writer’s block.

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Stylistic Devices to Use in a Conclusion

Discover distinctive stylistic insights that you can apply when writing a conclusion for a research paper:

• Rhetorical Questions. When using rhetorical questions, strategically place them to engage readers' minds. For instance, you might pose a question that prompts reflection on the broader implications of your findings, leaving your audience with something to ponder.
• Powerful Language. Incorporate strong language to convey a sense of conviction and importance. Choose words that resonate with the overall tone of your research and amplify the significance of your conclusions. This adds weight to your key messages.
• Repetitions. Repetitions can be employed to reinforce essential ideas. Reiterate key phrases or concepts in a way that emphasizes their importance without sounding redundant. This technique serves to drive home your main points.
• Anecdotes. Integrating anecdotes into your conclusion can provide a human touch. Share a brief and relevant story that connects with your research, making the information more relatable and memorable for your audience.
• Vivid Imagery. Lastly, use vivid imagery to paint a picture in the minds of your readers. Appeal to their senses by describing scenarios or outcomes related to your research. This creates a more immersive and lasting impression.

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How to Make a Conclusion Logically Appealing

Knowing how to write a conclusion for a research paper that is logically appealing is important for leaving a lasting impression on your readers. Here are some tips to achieve this:

Logical Sequencing

• Present your conclusion in a structured manner, following the natural flow of your paper. Readers should effortlessly follow your thought process, making your conclusion more accessible and persuasive.

Reinforce Main Arguments

• Emphasize the core arguments and findings from your research. By reinforcing key points, you solidify your stance and provide a logical culmination to your paper.

Address Counterarguments

• Acknowledge and address potential counterarguments or limitations in your research. Demonstrate intellectual honesty and strengthen your conclusion by preemptively addressing potential doubts.

Connect with Introduction

• Revisit themes or concepts introduced in your introduction to create a cohesive narrative, allowing readers to trace the logical progression of your research from start to finish.

Propose Actionable Insights

• Suggest practical applications or recommendations based on your findings. This will add a forward-looking dimension, making your conclusion more relevant and compelling.

Highlight Significance

• Clearly articulate the broader implications of your research to convey the importance of your work and its potential impact on the field, making your conclusion logically compelling.

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Avoid These Things When Writing a Research Paper Conclusion

As you write your conclusion of research paper, there’s a list of things professional writers don’t recommend doing. Consider these issues carefully:

• Repetition of Exact Phrases
• Repetitively using the same phrases or sentences from the main body. Repetition can make your conclusion seem redundant and less engaging.
• Overly Lengthy Summaries
• Providing excessively detailed summaries of each section of your paper. Readers may lose interest if the conclusion becomes too long and detailed.
• Unclear Connection to the Introduction
• Failing to connect the conclusion back to the introduction. A lack of continuity may make the paper feel disjointed.
• Adding New Arguments or Ideas
• Introducing new arguments or ideas that were not addressed in the body. This can confuse the reader and disrupt the coherence of your paper.
• Overuse of Complex Jargon
• Using excessively complex or technical language without clarification. Clear communication is essential in the conclusion, ensuring broad understanding.
• Apologizing or Undermining Confidence
• Apologizing for limitations or expressing doubt about your work. Maintain a confident tone; if limitations exist, present them objectively without undermining your research.
• Sweeping Generalizations
• Making overly broad or unsupported generalizations. Such statements can weaken the credibility of your conclusion.
• Neglecting the Significance
• Failing to emphasize the broader significance of your research. Readers need to understand why your findings matter in a larger context.
• Abrupt Endings
• Concluding abruptly without a strong closing statement. A powerful ending leaves a lasting impression; avoid a sudden or weak conclusion.

Research Paper Conclusion Example

That covers the essential aspects of summarizing a research paper. The only remaining step is to review the conclusion examples for research paper provided by our team.

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Final Thoughts

In conclusion, the knowledge of how to write the conclusion of a research paper is pivotal for presenting your findings and leaving a lasting impression on your readers. By summarizing the key points, reiterating the significance of your research, and offering avenues for future exploration, you can create a conclusion that not only reinforces the value of your study but also encourages further academic discourse. Remember to balance brevity and completeness, ensuring your conclusion is concise yet comprehensive. Emphasizing the practical implications of your research and connecting it to the broader academic landscape will help solidify the impact of your work. Pay someone to write a research paper if you are having a hard time finishing your coursework on time.

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How To Write A Conclusion For A Research Paper?

What should the conclusion of a research paper contain, how to start a conclusion paragraph for a research paper.

Daniel Parker

is a seasoned educational writer focusing on scholarship guidance, research papers, and various forms of academic essays including reflective and narrative essays. His expertise also extends to detailed case studies. A scholar with a background in English Literature and Education, Daniel’s work on EssayPro blog aims to support students in achieving academic excellence and securing scholarships. His hobbies include reading classic literature and participating in academic forums.

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Human evolution

Human evolution is the lengthy process of change by which people originated from apelike ancestors. Scientific evidence shows that the physical and behavioral traits shared by all people originated from apelike ancestors and evolved over a period of approximately six million years.

One of the earliest defining human traits, bipedalism -- the ability to walk on two legs -- evolved over 4 million years ago. Other important human characteristics -- such as a large and complex brain, the ability to make and use tools, and the capacity for language -- developed more recently. Many advanced traits -- including complex symbolic expression, art, and elaborate cultural diversity -- emerged mainly during the past 100,000 years.

Humans are primates. Physical and genetic similarities show that the modern human species, Homo sapiens , has a very close relationship to another group of primate species, the apes. Humans and the great apes (large apes) of Africa -- chimpanzees (including bonobos, or so-called “pygmy chimpanzees”) and gorillas -- share a common ancestor that lived between 8 and 6 million years ago. Humans first evolved in Africa, and much of human evolution occurred on that continent. The fossils of early humans who lived between 6 and 2 million years ago come entirely from Africa.

Most scientists currently recognize some 15 to 20 different species of early humans. Scientists do not all agree, however, about how these species are related or which ones simply died out. Many early human species -- certainly the majority of them – left no living descendants. Scientists also debate over how to identify and classify particular species of early humans, and about what factors influenced the evolution and extinction of each species.

Early humans first migrated out of Africa into Asia probably between 2 million and 1.8 million years ago. They entered Europe somewhat later, between 1.5 million and 1 million years. Species of modern humans populated many parts of the world much later. For instance, people first came to Australia probably within the past 60,000 years and to the Americas within the past 30,000 years or so. The beginnings of agriculture and the rise of the first civilizations occurred within the past 12,000 years.

Paleoanthropology

Paleoanthropology is the scientific study of human evolution. Paleoanthropology is a subfield of anthropology, the study of human culture, society, and biology. The field involves an understanding of the similarities and differences between humans and other species in their genes, body form, physiology, and behavior. Paleoanthropologists search for the roots of human physical traits and behavior. They seek to discover how evolution has shaped the potentials, tendencies, and limitations of all people. For many people, paleoanthropology is an exciting scientific field because it investigates the origin, over millions of years, of the universal and defining traits of our species. However, some people find the concept of human evolution troubling because it can seem not to fit with religious and other traditional beliefs about how people, other living things, and the world came to be. Nevertheless, many people have come to reconcile their beliefs with the scientific evidence.

Early human fossils and archeological remains offer the most important clues about this ancient past. These remains include bones, tools and any other evidence (such as footprints, evidence of hearths, or butchery marks on animal bones) left by earlier people. Usually, the remains were buried and preserved naturally. They are then found either on the surface (exposed by rain, rivers, and wind erosion) or by digging in the ground. By studying fossilized bones, scientists learn about the physical appearance of earlier humans and how it changed. Bone size, shape, and markings left by muscles tell us how those predecessors moved around, held tools, and how the size of their brains changed over a long time. Archeological evidence refers to the things earlier people made and the places where scientists find them. By studying this type of evidence, archeologists can understand how early humans made and used tools and lived in their environments.

The process of evolution

The process of evolution involves a series of natural changes that cause species (populations of different organisms) to arise, adapt to the environment, and become extinct. All species or organisms have originated through the process of biological evolution. In animals that reproduce sexually, including humans, the term species refers to a group whose adult members regularly interbreed, resulting in fertile offspring -- that is, offspring themselves capable of reproducing. Scientists classify each species with a unique, two-part scientific name. In this system, modern humans are classified as Homo sapiens .

Evolution occurs when there is change in the genetic material -- the chemical molecule, DNA -- which is inherited from the parents, and especially in the proportions of different genes in a population. Genes represent the segments of DNA that provide the chemical code for producing proteins. Information contained in the DNA can change by a process known as mutation. The way particular genes are expressed – that is, how they influence the body or behavior of an organism -- can also change. Genes affect how the body and behavior of an organism develop during its life, and this is why genetically inherited characteristics can influence the likelihood of an organism’s survival and reproduction.

Evolution does not change any single individual. Instead, it changes the inherited means of growth and development that typify a population (a group of individuals of the same species living in a particular habitat). Parents pass adaptive genetic changes to their offspring, and ultimately these changes become common throughout a population. As a result, the offspring inherit those genetic characteristics that enhance their chances of survival and ability to give birth, which may work well until the environment changes. Over time, genetic change can alter a species' overall way of life, such as what it eats, how it grows, and where it can live. Human evolution took place as new genetic variations in early ancestor populations favored new abilities to adapt to environmental change and so altered the human way of life.

Dr. Rick Potts provides a video short introduction to some of the evidence for human evolution, in the form of fossils and artifacts.

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• Members Thoughts on Science, Religion & Human Origins (video)
• Science, Religion, Evolution and Creationism: Primer
• The Evolution of Religious Belief: Seeking Deep Evolutionary Roots
• Laboring for Science, Laboring for Souls:  Obstacles and Approaches to Teaching and Learning Evolution in the Southeastern United States
• Public Event : Religious Audiences and the Topic of Evolution: Lessons from the Classroom (video)
• Evolution and the Anthropocene: Science, Religion, and the Human Future
• Imagining the Human Future: Ethics for the Anthropocene
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How to Write a Dissertation Conclusion | Checklist and Examples

Published on 9 September 2022 by Tegan George and Shona McCombes. Revised on 10 October 2022.

The conclusion is the very last part of your thesis or dissertation . It should be concise and engaging, leaving your reader with a clear understanding of your main findings, as well as the answer to your research question .

In it, you should:

• Clearly state the answer to your main research question
• Summarise and reflect on your research process
• Make recommendations for future work on your topic
• Show what new knowledge you have contributed to your field
• Wrap up your thesis or dissertation

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Table of contents

Discussion vs. conclusion, how long should your conclusion be, step 1: answer your research question, step 2: summarise and reflect on your research, step 3: make future recommendations, step 4: emphasise your contributions to your field, step 5: wrap up your thesis or dissertation, full conclusion example, conclusion checklist, frequently asked questions about conclusion sections.

While your conclusion contains similar elements to your discussion section , they are not the same thing.

Your conclusion should be shorter and more general than your discussion. Instead of repeating literature from your literature review , discussing specific research results , or interpreting your data in detail, concentrate on making broad statements that sum up the most important insights of your research.

As a rule of thumb, your conclusion should not introduce new data, interpretations, or arguments.

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Depending on whether you are writing a thesis or dissertation, your length will vary. Generally, a conclusion should make up around 5–7% of your overall word count.

An empirical scientific study will often have a short conclusion, concisely stating the main findings and recommendations for future research. A humanities topic or systematic review , on the other hand, might require more space to conclude its analysis, tying all the previous sections together in an overall argument.

Your conclusion should begin with the main question that your thesis or dissertation aimed to address. This is your final chance to show that you’ve done what you set out to do, so make sure to formulate a clear, concise answer.

• Don’t repeat a list of all the results that you already discussed
• Do synthesise them into a final takeaway that the reader will remember.

An empirical thesis or dissertation conclusion may begin like this:

A case study –based thesis or dissertation conclusion may begin like this:

In the second example, the research aim is not directly restated, but rather added implicitly to the statement. To avoid repeating yourself, it is helpful to reformulate your aims and questions into an overall statement of what you did and how you did it.

Your conclusion is an opportunity to remind your reader why you took the approach you did, what you expected to find, and how well the results matched your expectations.

To avoid repetition , consider writing more reflectively here, rather than just writing a summary of each preceding section. Consider mentioning the effectiveness of your methodology , or perhaps any new questions or unexpected insights that arose in the process.

You can also mention any limitations of your research, but only if you haven’t already included these in the discussion. Don’t dwell on them at length, though – focus on the positives of your work.

• While x limits the generalisability of the results, this approach provides new insight into y .
• This research clearly illustrates x , but it also raises the question of y .

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You may already have made a few recommendations for future research in your discussion section, but the conclusion is a good place to elaborate and look ahead, considering the implications of your findings in both theoretical and practical terms.

• Based on these conclusions, practitioners should consider …
• To better understand the implications of these results, future studies could address …
• Further research is needed to determine the causes of/effects of/relationship between …

When making recommendations for further research, be sure not to undermine your own work. Relatedly, while future studies might confirm, build on, or enrich your conclusions, they shouldn’t be required for your argument to feel complete. Your work should stand alone on its own merits.

Just as you should avoid too much self-criticism, you should also avoid exaggerating the applicability of your research. If you’re making recommendations for policy, business, or other practical implementations, it’s generally best to frame them as ‘shoulds’ rather than ‘musts’. All in all, the purpose of academic research is to inform, explain, and explore – not to demand.

Make sure your reader is left with a strong impression of what your research has contributed to the state of your field.

Some strategies to achieve this include:

• Returning to your problem statement to explain how your research helps solve the problem
• Referring back to the literature review and showing how you have addressed a gap in knowledge
• Discussing how your findings confirm or challenge an existing theory or assumption

Again, avoid simply repeating what you’ve already covered in the discussion in your conclusion. Instead, pick out the most important points and sum them up succinctly, situating your project in a broader context.

The end is near! Once you’ve finished writing your conclusion, it’s time to wrap up your thesis or dissertation with a few final steps:

• It’s a good idea to write your abstract next, while the research is still fresh in your mind.
• Next, make sure your reference list is complete and correctly formatted. To speed up the process, you can use our free APA citation generator .
• Once you’ve added any appendices , you can create a table of contents and title page .
• Finally, read through the whole document again to make sure your thesis is clearly written and free from language errors. You can proofread it yourself , ask a friend, or consider Scribbr’s proofreading and editing service .

Here is an example of how you can write your conclusion section. Notice how it includes everything mentioned above:

V. Conclusion

The current research aimed to identify acoustic speech characteristics which mark the beginning of an exacerbation in COPD patients.

The central questions for this research were as follows: 1. Which acoustic measures extracted from read speech differ between COPD speakers in stable condition and healthy speakers? 2. In what ways does the speech of COPD patients during an exacerbation differ from speech of COPD patients during stable periods?

All recordings were aligned using a script. Subsequently, they were manually annotated to indicate respiratory actions such as inhaling and exhaling. The recordings of 9 stable COPD patients reading aloud were then compared with the recordings of 5 healthy control subjects reading aloud. The results showed a significant effect of condition on the number of in- and exhalations per syllable, the number of non-linguistic in- and exhalations per syllable, and the ratio of voiced and silence intervals. The number of in- and exhalations per syllable and the number of non-linguistic in- and exhalations per syllable were higher for COPD patients than for healthy controls, which confirmed both hypotheses.

However, the higher ratio of voiced and silence intervals for COPD patients compared to healthy controls was not in line with the hypotheses. This unpredicted result might have been caused by the different reading materials or recording procedures for both groups, or by a difference in reading skills. Moreover, there was a trend regarding the effect of condition on the number of syllables per breath group. The number of syllables per breath group was higher for healthy controls than for COPD patients, which was in line with the hypothesis. There was no effect of condition on pitch, intensity, center of gravity, pitch variability, speaking rate, or articulation rate.

This research has shown that the speech of COPD patients in exacerbation differs from the speech of COPD patients in stable condition. This might have potential for the detection of exacerbations. However, sustained vowels rarely occur in spontaneous speech. Therefore, the last two outcome measures might have greater potential for the detection of beginning exacerbations, but further research on the different outcome measures and their potential for the detection of exacerbations is needed due to the limitations of the current study.

Checklist: Conclusion

I have clearly and concisely answered the main research question .

I have summarized my overall argument or key takeaways.

I have mentioned any important limitations of the research.

I have given relevant recommendations .

I have clearly explained what my research has contributed to my field.

I have  not introduced any new data or arguments.

You've written a great conclusion! Use the other checklists to further improve your dissertation.

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

While it may be tempting to present new arguments or evidence in your thesis or disseration conclusion , especially if you have a particularly striking argument you’d like to finish your analysis with, you shouldn’t. Theses and dissertations follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the discussion section and results section .) The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

For a stronger dissertation conclusion , avoid including:

• Generic concluding phrases (e.g. “In conclusion…”)
• Weak statements that undermine your argument (e.g. “There are good points on both sides of this issue.”)

Your conclusion should leave the reader with a strong, decisive impression of your work.

The conclusion of your thesis or dissertation shouldn’t take up more than 5-7% of your overall word count.

The conclusion of your thesis or dissertation should include the following:

• A restatement of your research question
• A summary of your key arguments and/or results
• A short discussion of the implications of your research

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How to Write a Whitepaper: The Ultimate Guide for Marketers

A whitepaper is an in-depth, persuasive, and informational document that presents a problem and provides a solution. You can use white papers in content marketing to generate interest, establish thought leadership, and influence the decision-making process of potential customers.

Typically ranging from 2,500 to 5,000 words , a well-researched and engaging whitepaper allows you to explore a topic in-depth. It is meant to educate your audience about an issue they are facing and subtly guide them towards your product or service as the ideal solution.

In this comprehensive guide, we will walk you through the methodology and process of planning, researching, writing, formatting, and promoting a white paper that sets you apart as a thought leader in your industry. You will learn how to write a whitepaper by choosing the right topic, crafting a compelling argument, presenting your ideas with clarity, and leveraging your whitepaper to achieve your sales and marketing goals.

Understanding the Purpose and Types of Whitepapers

The primary goal of a whitepaper is to build trust with your audience and provide an in-depth report or guide that demonstrates your company's expertise in the field.

There are several common types of white papers, each serving a unique purpose. Some whitepapers focus on explaining the technical information of a product or service , while others present a business case for adopting a particular solution . Regardless of the specific type, all whitepapers should aim to inform and persuade the reader, rather than serve as a direct sales pitch.

By educating the reader about a specific challenge they face and offering a thoughtful solution to a problem, whitepapers can help establish your company as a trusted authority . This trust is essential for building long-term relationships with your target audience and promote a product or service.

When crafting a whitepaper, it's crucial to keep the purpose of a white paper in mind: to provide value to the reader. While the ultimate goal may be to generate leads or drive sales, the whitepaper itself should focus on delivering helpful, relevant information that addresses the reader's needs and concerns.

Planning and Preparing to Write Your Whitepaper

Writing a whitepaper requires careful planning and preparation to ensure it effectively addresses your potential customers' needs and positions your business as a thought leader. Here's a step-by-step process for writing a whitepaper that resonates with your target audience:

• Define your target audience and their pain points . Understand who will be reading your whitepaper and what challenges they face. Identifying their needs allows you to tailor your content to provide the most relevant and valuable information.
• Choose a specific topic that addresses your audience's needs. Select a whitepaper topic that directly relates to your potential customers' pain points and showcases your unique expertise. A focused, relevant topic will capture your readers' attention and demonstrate how your business can solve their problems.
• Conduct thorough research using credible sources. A compelling whitepaper needs to provide original research, data, and insights. Gather facts and evidence from reputable industry sources, case studies, and your own research findings to support your whitepaper's claims and solutions.
• Create a detailed outline to organize your whitepaper's contents. Structure your whitepaper with a clear introduction, problem statement, background information, proposed solution, and conclusion. A well-organized outline ensures your whitepaper flows logically and keeps readers engaged from start to finish.

What elements should include a Whitepaper?

Here is a summary of the key elements and format that a good whitepaper should include:

• Attention-grabbing title that clearly states the problem or topic the whitepaper covers
• Subtitle providing more context
• Company name and logo
• Publication date
• Name(s) of author(s)

Abstract or Executive Summary 

• Concise overview of the whitepaper's contents 
• Direct statements of the whitepaper's position or argument to engage the reader
• Enough detail to satisfy an executive while encouraging further reading

Table of Contents

• Organized outline of the whitepaper's sections and subsections

Introduction

• Hook to grab the reader's attention 
• Definition of the issue or problem and relevant background information
• Establishes the author's credibility and common ground with the audience

Problem Statement

• Thorough explanation of the specific problem the whitepaper addresses
• Entirely from the perspective of the target audience
• Supported by facts, statistics and examples illustrating the problem's impact

Proposed Solution

• Detailed description of the proposed solution to the stated problem
• Makes a persuasive, evidence-based argument for the solution
• Addresses potential objections and alternative solutions
• Includes supporting visuals like charts, graphs, and infographics
• Summarizes the whitepaper's key points and takeaways 
• Reiterates the importance and value of the proposed solution
• Includes a specific call-to-action for readers
• Citations for all research, statistics, and information sources used

Designing Your Whitepaper for Maximum Engagement

The design and layout of your whitepaper play a crucial role in its readability and overall impact. A well-designed whitepaper not only looks professional but also makes the content more accessible and engaging for the reader. You can find different whitepaper examples  and templates in websites like Venngage .

Incorporate visual elements like images, charts, and infographics to break up the text and illustrate key points. These elements can help make complex information more digestible and engaging for your audience.

However, avoid turning your whitepaper into a slick sales brochure . While visual elements are important, ensure that each page has more text than visuals to maintain the whitepaper's informative purpose.

Optimize your whitepaper design for multiple devices, as readers may access it on desktops, tablets, or smartphones. Use a responsive layout that adapts to different screen sizes, making it easy to read and navigate.

Remember, a well-designed whitepaper enhances the reading experience, making it more likely that your audience will engage with and share your content.

Promoting Your Whitepaper for Lead Generation

Once you've created a compelling whitepaper, it's time to promote it as part of your content marketing strategy . A well-crafted whitepaper can be a powerful lead magnet, helping you generate interest and capture valuable contact information from potential customers.

To maximize the impact of your whitepaper, create a dedicated landing page to host it. This page should highlight the potential benefits of your whitepaper and include a lead generation form to collect visitor details in exchange for the download.

Leverage your whitepaper across multiple channels to reach a wider audience. Share snippets and links to your whitepaper on social media platforms like LinkedIn, Twitter, and Facebook[16][19]. Incorporate it into your email marketing campaigns, targeting relevant segments of your subscriber list.

Don't let your whitepaper be a one-and-done piece of content. Repurpose the valuable information into various content formats to extend its reach. Transform key sections into blog posts, create engaging videos that summarize the main points, or develop a slide presentation to share on platforms like SlideShare.

A whitepaper is just one type of content in your marketing arsenal. Combine it with other lead generation tactics like eBooks, webinars, and email courses to create a comprehensive content marketing strategy that drives results.

Measuring the Success and ROI of Your Whitepaper

Tracking the performance of your whitepaper is crucial for understanding its impact and optimizing your content marketing strategy. By monitoring key metrics, you can gauge the effectiveness of your whitepaper and make data-driven decisions to improve its ROI.

One essential metric to track is the number of downloads your whitepaper receives. This indicates the level of interest and engagement from your target audience. Additionally, keep a close eye on the leads generated from your whitepaper, as this directly ties to its potential for driving conversions and revenue.

To gain deeper insights into reader engagement, analyze data such as time spent reading, scroll depth, and click-through rates on links within your whitepaper . This information can help you identify areas for improvement and optimize your content to better resonate with your audience.

Gathering feedback from readers is another valuable way to measure the success of your whitepaper. Surveys, comments, and social media mentions can provide qualitative data on how well your content is received and what improvements can be made.

By consistently tracking and analyzing these metrics, you can continually refine your whitepaper marketing strategy to maximize its impact and ROI. Use the insights gained to optimize your content, distribution channels, and promotional efforts, ensuring that your whitepaper remains a valuable asset in your content marketing arsenal.

Conclusion: How to write a Whitepaper

Writing a whitepaper may seem daunting, but by following the key steps and best practices outlined in this guide, you can create a valuable asset for your content marketing strategy. To recap, start by choosing a relevant topic, understanding your audience, and conducting thorough research. Then, craft a compelling outline, write engaging content, and enhance your whitepaper with visuals and a professional design.

Remember, whitepapers are powerful tools for establishing thought leadership, generating leads, and educating your target audience. Investing time and effort into whitepaper writing can differentiate your brand and provide immense value to your readers.

Don't let the process overwhelm you – break it down into manageable steps and leverage the expertise of your team or external resources when needed. With practice and persistence, you'll soon be creating whitepapers that resonate with your audience and drive results for your business.

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• Open access
• Published: 27 May 2024

Optimizing double-layered convolutional neural networks for efficient lung cancer classification through hyperparameter optimization and advanced image pre-processing techniques

• M. Mohamed Musthafa 1 ,
• I. Manimozhi 2 ,
• T. R. Mahesh 3 &
• Suresh Guluwadi 4  

BMC Medical Informatics and Decision Making volume  24 , Article number:  142 ( 2024 ) Cite this article

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Metrics details

Lung cancer remains a leading cause of cancer-related mortality globally, with prognosis significantly dependent on early-stage detection. Traditional diagnostic methods, though effective, often face challenges regarding accuracy, early detection, and scalability, being invasive, time-consuming, and prone to ambiguous interpretations. This study proposes an advanced machine learning model designed to enhance lung cancer stage classification using CT scan images, aiming to overcome these limitations by offering a faster, non-invasive, and reliable diagnostic tool. Utilizing the IQ-OTHNCCD lung cancer dataset, comprising CT scans from various stages of lung cancer and healthy individuals, we performed extensive preprocessing including resizing, normalization, and Gaussian blurring. A Convolutional Neural Network (CNN) was then trained on this preprocessed data, and class imbalance was addressed using Synthetic Minority Over-sampling Technique (SMOTE). The model’s performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and ROC curve analysis. The results demonstrated a classification accuracy of 99.64%, with precision, recall, and F1-score values exceeding 98% across all categories. SMOTE significantly enhanced the model’s ability to classify underrepresented classes, contributing to the robustness of the diagnostic tool. These findings underscore the potential of machine learning in transforming lung cancer diagnostics, providing high accuracy in stage classification, which could facilitate early detection and tailored treatment strategies, ultimately improving patient outcomes.

Peer Review reports

Introduction

Lung cancer stands as a formidable global health challenge, consistently ranking as one of the leading causes of cancer-related mortality worldwide. It is characterized by the uncontrolled growth of abnormal cells in one or both lungs, typically in the cells lining the air passages. Unlike normal cells, these cancerous cells do not develop into healthy lung tissue; instead, they divide rapidly and form tumors that disrupt the lung’s primary function: oxygen exchange.

The global impact of lung cancer is staggering, with millions of new cases diagnosed annually. Its high mortality rate is primarily due to late-stage detection, where the cancer has progressed to an advanced stage or metastasized to other body parts, significantly diminishing the effectiveness of treatment modalities. Thus, early and accurate diagnosis of lung cancer is paramount in improving patient prognoses, extending survival rates, and enhancing the quality of life for affected individuals.

The primary cause of lung cancer is cigarette smoking, which exposes the lungs to carcinogenic substances that can damage the cells’ DNA and lead to cancer. Other risk factors for lung cancer include exposure to secondhand smoke, radon gas, asbestos, air pollution, and a family history of lung cancer.

Symptoms of lung cancer can vary but may include persistent coughing, chest pain, shortness of breath, hoarseness, coughing up blood, unexplained weight loss, and fatigue. However, lung cancer may not cause symptoms in its initial stages, which is why early detection through screening is crucial for improving outcomes.

Diagnosis of lung cancer typically involves imaging tests such as chest X-rays, CT scans, and PET scans to visualize the lungs and detect any abnormalities. A biopsy, where a small sample of lung tissue is taken and examined under a microscope, is usually needed to confirm the diagnosis.

Treatment options for lung cancer depend on several factors, including the type and stage of the cancer, as well as the patient’s overall health and preferences. Treatment may include surgery to remove the tumor, chemotherapy, radiation therapy, targeted therapy, immunotherapy, or a combination of these approaches.

Lung cancer is a critical condition that necessitates immediate medical care. Detecting it early, along with improvements in treatment methods, has enhanced the prognosis for numerous patients. However, the most effective strategy to avoid lung cancer is to stop smoking and minimize contact with additional risk elements. Figure  1 displays some example images of lung cancer tests.

Sample images of lung cancer

Current diagnostic techniques for lung cancer involve various approaches, such as biopsies, CT scans, chest X-rays, PET scans, and MRI, among others [ 1 ]. While these methods are invaluable in the diagnostic process, they come with certain limitations. For instance, biopsies, while definitive, are invasive and carry risks of complications. Less invasive imaging methods such as X-rays or CT scans might produce false positives or negatives, potentially causing unwarranted stress or delays in treatment.

Moreover, the interpretation of these diagnostic tests heavily relies on the expertise of the clinician, introducing a degree of subjectivity and potential for human error. There’s also the challenge of early-stage lung cancer, which often presents very subtle changes not always detectable with conventional imaging techniques [ 2 ].

This context highlights the critical need for advanced diagnostic tools capable of overcoming these challenges. This study aims to address these issues by developing a machine learning model using Convolutional Neural Networks (CNNs) to enhance the precision and effectiveness of lung cancer stage classification from CT scans. By automating and refining the diagnostic process, the proposed model seeks to mitigate the limitations of traditional methods, offering a faster, non-invasive, and more reliable diagnostic alternative.

The impact of this study is significant: the model’s high accuracy in classifying lung cancer stages promises to revolutionize clinical diagnostics, facilitating early detection and enabling tailored treatment strategies. This advancement has the potential to improve patient outcomes by allowing for timely intervention and more effective management of lung cancer, ultimately contributing to reduced mortality rates and enhanced patient care.

The objective of this research paper is to:

Develop a machine learning model utilizing Convolutional Neural Networks (CNNs) for lung cancer stage classification based on CT scans.

Bridge existing diagnostic deficiencies by providing clinicians with a tool for expedited and precise decision-making in lung cancer management.

Contribute to improved patient outcomes through enhanced diagnostic accuracy and early detection capabilities.

The paper is organized as follows: Initially, the Literature Review explores existing research on lung cancer diagnostics, highlighting advancements and limitations, and sets the foundation for the proposed methodology. Subsequently, the Materials and methods section describes the dataset, preprocessing steps, model architecture, training process, and evaluation metrics in detail. The Results section then presents the study’s findings, including model performance metrics and comparative analysis with existing methods. This is followed by the Discussion, which interprets the results, discusses implications for clinical practice, addresses limitations, and suggests future research directions. Finally, the Conclusion summarizes the main findings and their relevance within the broader scope of lung cancer diagnostics, supported by a comprehensive list of References to provide credit and enable readers to explore the research background further.

Through this structured approach, the paper aims to contribute meaningful insights to the field of medical imaging and machine learning, offering a novel tool for the early and accurate diagnosis of lung cancer.

Literature review

The literature surrounding lung cancer diagnostics encompasses various methodologies, ranging from traditional imaging techniques to more advanced approaches such as machine learning. This review aims to explore existing research in this area, highlighting both the advancements made and the limitations faced, ultimately setting the foundation for the proposed machine learning-based methodology.

Diagnosis of lung cancer using CT scans

The utilization of Computed Tomography (CT) scans in lung cancer diagnosis has been a cornerstone in the medical field, offering high-resolution images that are pivotal for detecting and monitoring various stages of lung tumors [ 3 ]. Over the years, numerous studies have underscored the importance of CT scans in identifying nodules that could potentially be malignant, with a particular focus on low-dose CT scans, which have become a standard in screening programs, especially for high-risk populations. Such studies underscore the superior sensitivity of CT scans in identifying early-stage lung cancer, a significant advancement over other imaging methods like chest X-rays, which may overlook smaller, subtler lesions.

Despite the advancements, the interpretation of CT scans remains a significant challenge. Radiologists need to discern between benign and malignant nodules, an endeavor complicated by the presence of various artifacts and benign conditions like scars or inflammatory diseases, which can mimic the appearance of cancerous nodules [ 4 , 5 ].

Machine learning approaches in lung cancer detection and classification

The integration of machine learning, particularly deep learning techniques, into the analysis of CT images has established a groundbreaking paradigm in the identification and classification of lung cancer. Convolutional Neural Networks (CNNs) are spearheading this transformation by providing a framework for automated extraction and categorization of features directly from the images. This advancement marks a substantial stride in augmenting the accuracy and effectiveness of lung cancer diagnostics, thus facilitating more precise and timely interventions.

Binary classification models

Early studies primarily focused on binary classification, distinguishing between malignant and non-malignant nodules. CNNs, through their layered architecture, have demonstrated the ability to learn complex patterns in imaging data, surpassing traditional computer vision techniques in accuracy and reliability [ 6 , 7 ].

Multi-class classification models

Recent advancements have moved towards more nuanced multi-class classification models that categorize nodules into various cancer stages or types. This granularity is crucial for treatment planning and prognosis, offering a more detailed understanding of the disease’s progression [ 8 ].

Transfer learning

Given the challenges of assembling large annotated medical imaging datasets, transfer learning has become a popular approach. Models pre-trained on vast, non-medical image datasets are fine-tuned on smaller medical imaging datasets, leveraging learned features to improve performance in the medical domain [ 9 ].

Data augmentation

To address the issue of restricted training data, strategies such as rotation, scaling, and flipping are commonly employed for data augmentation, effectively expanding the training dataset artificially. These methods bolster the model’s resilience and its ability to generalize from a limited number of examples [ 10 ].

Segmentation models

Deep learning models extend their utility beyond mere classification; they are also employed in segmentation tasks, delineating the precise boundaries of nodules, which is vital for assessing tumor size and growth over time. U-Net, a type of CNN, is particularly noted for its effectiveness in medical image segmentation [ 11 ].

In Table 1  a few of the studies which have been done in this field are given.

Gaps in current research

Despite significant advancements in lung cancer diagnostics, several critical gaps remain in the current research landscape. Many existing models are trained on datasets lacking diversity in demographics, scanner types, and image acquisition parameters, which can limit their generalizability across different populations and clinical settings. This limitation underscores the need for more comprehensive and diverse datasets to enhance the robustness of diagnostic models. Additionally, the “black box” nature of deep learning models poses a challenge for clinical adoption, as there is a growing demand for models that not only predict accurately but also provide insights into the reasoning behind their predictions. This issue of interpretability is crucial for gaining the trust of clinicians and integrating these models into clinical workflows effectively. Furthermore, the transition from research to clinical practice is slow, with models requiring not just technological solutions but also addressing regulatory, ethical, and practical considerations to facilitate their integration into routine medical care. Another critical gap is the need for models capable of longitudinal analysis, which can analyze changes in lung nodules over time, providing a dynamic assessment that aligns more closely with clinical needs. Addressing these gaps, this study introduces a comprehensive CNN model trained on a diverse and extensive dataset, encompassing various stages of lung cancer. The model is designed for multi-class classification, offering detailed insights critical for personalized treatment strategies. Emphasis is placed on the interpretability of the model, aiming to provide clinicians with understandable and actionable information. By demonstrating the model’s effectiveness in a clinical setting, this research contributes to the ongoing effort to integrate advanced machine learning techniques into the realm of lung cancer diagnosis and treatment.

Addressing these gaps, this study introduces a comprehensive CNN model trained on a diverse and extensive dataset, encompassing various stages of lung cancer. The model is designed for multi-class classification, offering detailed insights critical for personalized treatment strategies. Emphasis is placed on the interpretability of the model, aiming to provide clinicians with understandable and actionable information. By demonstrating the model’s effectiveness in a clinical setting, this research contributes to the ongoing effort to integrate advanced machine learning techniques into the realm of lung cancer diagnosis and treatment.

Materials and methods

This section delineates the comprehensive methodology employed to construct and validate a convolutional neural network (CNN) model for the classification of lung cancer stages using the IQ-OTHNCCD lung cancer dataset. The approach encompasses dataset acquisition, application of preprocessing methodologies, formulation of the model architecture, delineation of training procedures, and determination of evaluation metrics to ensure a comprehensive and reliable analysis. The workflow of the proposed model is visually depicted in Fig.  2 .

Workflow of the proposed model

Dataset description and preprocessing

The IQ-OTHNCCD lung cancer dataset, integral to this study, is painstakingly curated to facilitate the creation and validation of machine learning models aimed at identifying and classifying lung cancer stages. This dataset encompasses a vast collection of CT scan images essential for advancing diagnostic capabilities in the field of lung cancer.

This dataset comprises CT scan images, comprising a diverse and comprehensive range of cases, covering various stages of lung cancer, including benign, malignant, and normal cases. This diversity is essential for training robust models capable of generalizing well across the spectrum of lung cancer manifestations, enabling effective diagnostic applications. In Table 2  a brief description of the dataset has been given.

Based on Table  2 , to provide visual insights of the data Fig.  3 delves into the same aspects.

Dataset description

Annotating and labeling each image meticulously, medical professionals from the Iraq-Oncology Teaching Hospital/National Center for Cancer Diseases have ensured the dataset’s reliability. Annotations categorize images into one of three classes: benign, malignant, or normal. Such granular labeling establishes a solid ground truth essential for training and assessing the model, enhancing the dataset’s utility in research and clinical applications.

Characterized by high quality and consistency, the CT scans adhere to standardized imaging protocols, guaranteeing reliability and accuracy. However, variations in image dimensions necessitate preprocessing to standardize inputs for neural networks. These steps ensure that the model processes uniform data, enhancing its performance and generalizability across diverse datasets. The images of the dataset ratio are checked using Eq.  1 .

Preprocessing steps are pivotal in preparing data for effective model training, including:

Resizing: Resizing images to a uniform dimension ensures consistency in input size for CNNs, optimizing model performance.

Normalization: Normalizing pixel values to a scale of 0 to 1 expedites model convergence during training, facilitating efficient learning. It is achieved using Eq.  2 .

Augmentation: Utilizing data augmentation methods like rotation, flipping, and scaling improves the model’s robustness and helps prevent overfitting by effectively enlarging the dataset size.

Splitting: Partitioning the dataset into training, validation, and test sets is crucial for facilitating effective model training and evaluation, thereby ensuring the model’s ability to generalize and perform accurately on unseen data.

In this process, CNN is trained using the preprocessed dataset to adeptly extract features from CT scan images and accurately classify the stages of lung cancer. The dataset’s diversity and quality are pivotal in enabling the model to learn nuanced features and patterns associated with various lung cancer stages, underscoring its significance in advancing diagnostic accuracy and efficiency.

The IQ-OTHNCCD lung cancer dataset serves as the cornerstone for developing machine learning models that enhance early detection and classification of lung cancer. Through meticulous curation and rigorous preprocessing, this dataset showcases the transformative potential of AI in healthcare, underscoring its role in improving diagnostic accuracy and efficiency.

• Image preprocessing

The preprocessing of images stands as a pivotal stage in the pipeline of developing a machine learning model, especially when handling medical imaging data like the IQ-OTHNCCD lung cancer dataset. This procedure comprises several crucial steps, each tailored to convert the raw CT scan images into a format conducive to effective analysis by a convolutional neural network (CNN).

Initially, image resizing is conducted. Given the inherent variability in the dimensions of CT scans, it is imperative to standardize the size of all images to ensure consistent input to the CNN. Resizing is performed while preserving the aspect ratio to avoid distortion, typically scaling down to a fixed size (e.g., 256 × 256 pixels). This uniformity is vital for the neural network to process and glean insights from the data effectively, as it necessitates a consistent input size [ 21 ].

Some pre-processed images to enhance the accessibility has been provided in Fig.  4 .

Pre-processed images

Following resizing, normalization of pixel values is performed. CT scans, by nature, contain a wide range of pixel intensities, which can adversely affect the training process of a CNN due to the varying scales of image brightness and contrast. Normalization is a crucial preprocessing step in image analysis that adjusts the pixel values to fall within a specific range, commonly 0 to 1 or -1 to 1. This adjustment is typically achieved by dividing the pixel values by the maximum possible value, which is 255 for 8-bit images. Such a normalization process ensures that the model can train faster and more efficiently. This step ensures that the model trains faster and more effectively, as small, standardized values facilitate quicker convergence during the optimization process.

Gaussian blur is then applied as an additional preprocessing step. This technique, which employs a Gaussian kernel to smooth the image, is instrumental in reducing image noise and mitigating the effects of minor variations and artifacts in the scans. By doing so, the model’s focus is directed toward the salient features relevant to lung cancer classification, rather than being distracted by irrelevant noise or details. Gaussian blur operates by convolving the image with a Gaussian function, effectively averaging the pixel values within a specified radius. This process smoothens the image, reducing high-frequency components and noise, which can otherwise lead to overfitting or distraction during the training of the CNN.

In the context of lung cancer CT scans, Gaussian blur helps to highlight the important structural elements of the lungs and nodules while suppressing irrelevant details that could complicate the model’s learning process. By smoothing the images, Gaussian blur enhances the model’s ability to generalize by focusing on the more significant, lower-frequency features of the image, such as the shape and size of nodules, rather than being confounded by small variations or noise. This is particularly beneficial in medical imaging, where the presence of noise and artifacts can obscure critical diagnostic features.

The application of Gaussian blur can also aid in generalizing the model, preventing overfitting to the high-frequency noise present in the training set. It is achieved using Eq.  3 and the SMOTE ratio through Eq.  4 .

These are the preprocessing steps collectively enhance the quality and consistency of the input data, enabling the CNN to focus on learning meaningful, discriminative features from the CT images [ 22 ]. By ensuring that the images are appropriately resized, normalized, and filtered, the model is better equipped to identify the subtle nuances associated with different stages of lung cancer, thereby improving its diagnostic accuracy and reliability. Through meticulous image preprocessing, the foundation is laid for developing a robust machine learning model capable of contributing significantly to the field of medical imaging and diagnostics.

Deep learning model

The model architecture utilized in this study is a Convolutional Neural Network (CNN), renowned for its effectiveness in various image analysis tasks, notably in the domain of medical image processing. In this study, we utilized a Convolutional Neural Network (CNN) architecture, known for its effectiveness in analyzing images, particularly in medical contexts like lung cancer diagnosis from CT scans. Let’s break down how it works in simpler terms. First, the input layer takes in images resized to a standard size of 256 × 256 pixels, in black and white. This consistency helps the CNN learn efficiently. Then comes the first convolutional layer, where the model looks for basic patterns like edges and textures using small 3 × 3 filters. After that, a process called max pooling reduces the image’s size, focusing on the most important features. This step helps the model generalize better and ignore noise. We repeat this process with another convolutional layer to capture more complex patterns. The flattened layer turns the extracted features into a format the model can understand. Next, a fully connected layer reasons based on these features, helping with the final classification. The output layer then gives probabilities for each class (benign, malignant, or normal). Throughout training, we used the Adam optimizer to adjust learning rates and manage gradients effectively. Additionally, we applied a technique called SMOTE to balance our dataset, ensuring the model learned from all classes equally. By carefully designing our CNN architecture and incorporating these steps, we aimed to create a model that can accurately classify lung cancer stages from CT scans.

Input layer : The input layer accepts images resized to 256 × 256 pixels, maintaining a single channel (grayscale), resulting in an input shape of (256, 256, 1).

First convolutional layer : This layer consists of 64 filters of size 3 × 3, using a ReLU (Rectified Linear Unit) activation function. The choice of 64 filters is aimed at capturing a broad array of features from the input image, while the 3 × 3 filter size is standard for capturing spatial relationships in the image data. The equation involved are given in Eqs.  5 and 6 .

First max pooling layer : Following the convolutional layer, the model incorporates a max pooling layer with a 2 × 2 pool size. This layer serves to decrease the spatial dimensions of the feature maps, which not only helps in reducing the computational load but also enhances the model’s generalization capabilities. By focusing on the most prominent features, max pooling ensures that the model does not overfit to the noise in the training data. It is done using Eq.  7 .

Second convolutional layer : Another set of 64 filters is applied, like the first convolutional layer, to further refine the feature extraction. This layer also uses a 3 × 3 kernel and is followed by a ReLU activation. It is achieved using Eqs.  8 and 9 .

Second max pooling layer : This layer additionally decreases the size of the feature maps, aiding in the prevention of overfitting and lessening the computational burden.

Flattening : The feature maps are flattened into a single vector to prepare for the fully connected layers, facilitating the transition from convolutional layers to dense layers.

Fully connected layer : A dense layer with 16 neurons is used, providing a high-level reasoning based on the extracted features. This layer utilizes a linear activation function to allow for a range of linear responses. The equations helping in this are given in Eqs.  10 and 11 .

Output layer : The final layer of the model contains three neurons, each representing one of the classes: benign, malignant, and normal. It uses a SoftMax activation function, which is selected because it provides a probability distribution across these three classes, making it . involved are given in Eqs.  12 and 13 .

Optimizer : The Adam optimizer is used due to its effectiveness in managing sparse gradients and its ability to adapt learning rates, which enhance the convergence speed during training. The equation involved in this is given in Eq.  14 .

CNN is chosen for its proven efficacy in image classification tasks, particularly its ability to learn hierarchical patterns in data. In medical imaging, CNNs have demonstrated success in identifying subtle patterns that are indicative of various pathologies, making them ideal for this application. The sequential model with convolutional layers followed by pooling layers allows for the extraction and down sampling of features, which is critical for capturing relevant information from medical images.

The Synthetic Minority Over-Sampling Technique (SMOTE) represents an innovative strategy devised to address the issue of class imbalance within the dataset. Class imbalance poses a substantial risk of biasing the model’s performance, particularly in medical datasets where one class may be underrepresented. SMOTE functions by creating synthetic samples within the feature space of the minority class, drawing inspiration from the feature space of its nearest neighbors. This process aids in rectifying class imbalances and ensuring more equitable representation during model training.

Filter mapping of a sample image is shown in Fig.  5 to make it more sound about the interoperability of the model.

In this research:

Application of SMOTE : SMOTE is applied only to the training data to prevent information leakage and to promote robust generalization on unseen data. It balances the dataset by augmenting the minority classes, ensuring that the model does not become biased toward the majority class.

Impact on model performance : By addressing the class imbalance, SMOTE helps in improving the model’s sensitivity towards the minority class, which is crucial in medical diagnostics, as overlooking a positive case can have serious implications.

Considerations : While SMOTE can significantly improve model performance in cases of class imbalance, it’s essential to monitor for overfitting, as the synthetic samples may cause the model to overgeneralize from the minority class.

The algorithm for the proposed model is presented in Algorithm 1.

Algorithm 1: Proposed algorithm for the methodology

As per the algorithm in the initial convolutional layers of the model, two sets of convolutional layers followed by max-pooling layers play a pivotal role in feature detection. Utilizing a standard 3 × 3 kernel size allows the model to discern small, localized features within CT scan images. By stacking these convolutional layers before applying max pooling, the model effectively captures intricate patterns such as edges, textures, and shapes, crucial for distinguishing between benign, malignant, and normal lung tissue. The ReLU activation function is employed in these convolutional layers due to its effectiveness in introducing non-linearity, enabling the model to learn complex patterns efficiently. Additionally, max pooling is utilized to downsample the feature maps, reducing computational load and enhancing robustness to image variations, thereby improving translational invariance. Following feature extraction, the model flattens the output and transitions to dense layers, condensing learned information into abstract representations. The final layer consists of three neurons, representing the three classes under consideration, employing the SoftMax activation function to transform logits into probabilities, thereby providing insights into the model’s confidence regarding each class. Throughout the compilation and training phases, the Adam optimizer and sparse categorical crossentropy loss function, as depicted by Eq.  15 , are chosen due to their adaptive learning rate features and appropriateness for classification objectives. Validation on an independent dataset is crucial for detecting overfitting and refining hyperparameters.

In the training phase, SMOTE is strategically applied to create a balanced dataset representative of all classes, crucial for generalizing well across various lung tissue conditions, especially in medical datasets where class imbalance may exist.

Training and validation

Throughout the training and validation phases of the deep learning model, meticulous steps are taken to ensure that the model not only learns effectively from the training data but also demonstrates robust generalization capabilities when presented with new, unseen data. This phase plays a pivotal role in evaluating the model’s proficiency in accurately classifying lung cancer stages from CT scans.

The training process initiates with the segmentation of the dataset into distinct training and validation subsets. This segmentation is performed in a stratified manner to guarantee that each subset encompasses a balanced representation of the various classes. Such stratification is essential for maintaining consistency and mitigating biases, particularly in light of the class imbalance addressed by SMOTE during training. Approximately 80% of the data is allocated for training purposes, while the remaining 20% is reserved for validation.

Subsequent to the data segmentation, the training commences with the utilization of a batch size of 8. The selection of a smaller batch size is deliberate, aiming to facilitate more precise and nuanced updates to the model’s weights during each iteration, thereby potentially enhancing generalization. Nonetheless, it is imperative to strike a balance between this granularity and computational efficiency, as smaller batch sizes may prolong the training duration.

The number of epochs is predetermined to be 12, indicating the total number of complete passes that the learning algorithm will undertake across the entire training dataset. This choice represents a delicate balance between underfitting and overfitting; insufficient epochs may hinder the model’s learning process, whereas excessive epochs may result in the model memorizing the training data, consequently impairing its ability to generalize effectively. The progression of training and validation loss and accuracy across epochs is visualized in Fig.  6 .

Training and validation loss and accuracy

During training, the model’s performance is continuously evaluated using a comprehensive set of performance metrics assessed against the validation set. These metrics encompass accuracy, precision, recall, and F1-score, all of which are instrumental in comprehending the model’s strengths and weaknesses in classifying each lung cancer stage. Accuracy furnishes a broad overview of the model’s overall performance, while precision and recall delve deeper into its class-specific performance, a critical consideration in medical diagnostics where false negatives and false positives carry significant consequences. The F1-score serves to harmonize precision and recall, furnishing a unified metric to gauge the model’s equilibrium between these two facets.

Moreover, the validation process incorporates a confusion matrix and ROC curves to furnish a more granular analysis of the model’s performance across diverse thresholds and classes. The confusion matrix delineates the model’s true positives, false positives, false negatives, and true negatives, offering a snapshot of its classification capabilities. Meanwhile, ROC curves and the corresponding AUC (Area Under the Curve) provide insights into the model’s capacity to discriminate between classes at varying threshold settings, a crucial consideration for refining the model’s decision boundary.

In our quest to maximize the performance of our Convolutional Neural Network (CNN) model for lung cancer classification, we meticulously fine-tuned several critical hyperparameters that play pivotal roles in shaping the learning process and ultimately, the model’s accuracy. Specifically, we focused on optimizing the learning rate, batch size, number of filters in each convolutional layer, filter size, and dropout rate. Firstly, we delved into exploring a spectrum of learning rates to pinpoint the optimal value that ensures swift convergence towards the minimum of the loss function without overshooting. Next, we scrutinized various batch sizes to strike a delicate balance between training time and the stability of the gradient descent process. Moving forward, we embarked on an exploration of different combinations of the number of filters and filter sizes in the convolutional layers, aiming to unearth the configuration most adept at extracting salient features from the intricate CT scan images. Additionally, to combat overfitting and foster model robustness, we meticulously optimized the dropout rate, discerning the precise proportion of neurons to deactivate during training. Our methodology embraced a meticulous grid search strategy, systematically traversing through predefined sets of values for each hyperparameter while evaluating the model’s performance using cross-validation. This exhaustive search enabled us to pinpoint the hyperparameter combination that not only elevated the model’s classification accuracy but also bolstered its generalization capabilities. Subsequently, the efficacy of the selected hyperparameters was meticulously validated using a distinct validation set, underscoring the robustness and reliability of our chosen parameters. Through this systematic and rigorous approach to hyperparameter tuning, we achieved remarkable strides in fortifying the performance and stability of our lung cancer classification model, thereby augmenting its potential for real-world clinical applications.

The training and validation phases operate iteratively, with refinements made to the model’s architecture, hyperparameters, or training methodology based on the validation outcomes. This iterative refinement persists until the model achieves a satisfactory equilibrium of accuracy, generalizability, and robustness, thereby ensuring its efficacy and reliability in clinical settings for lung cancer stage classification.

Statistical methods

In the analysis of the IQ-OTH/NCCD lung cancer dataset, various statistical and machine learning techniques were employed to ensure a comprehensive evaluation of the data. The primary focus was on classification metrics to assess the performance of the predictive models.

Confusion matrix : The confusion matrix serves as a pivotal component in our analysis, furnishing a visual representation of the model’s performance. It succinctly presents the counts of true positives, true negatives, false positives, and false negatives, thereby offering a lucid comprehension of the model’s classification accuracy and any instances of misclassification.

Accuracy : The accuracy metric was calculated by dividing the number of correctly predicted observations by the total number of observations, providing a straightforward measure for assessing the model’s overall performance. However, relying solely on accuracy can be deceptive, particularly in datasets with imbalanced class distributions. Therefore, it is imperative to incorporate additional metrics for a more comprehensive evaluation. It is achieved by Eq.  16 .

Precision (positive predictive value) : Precision was utilized to assess the accuracy of positive predictions, quantified as the ratio of true positives to the sum of true positives and false positives. This metric bears significant relevance in scenarios where the repercussions of false positives are considerable. It is achieved by Eq.  17 .

Recall (sensitivity or true positive rate) : Recall assesses the model’s ability to detect positive instances, calculated as the ratio of true positives to the sum of true positives and false negatives. This metric holds particular importance in medical diagnostics, where failing to identify a positive case can lead to severe consequences. It is achieved by Eq.  18 .

F1-score : The F1-score, which is the harmonic mean of precision and recall, was used to provide a balance between the two metrics, particularly valuable in situations of class imbalance. It is a more robust measure than accuracy in scenarios where false negatives and false positives have different implications. It is achieved by Eq.  19 .

Cohen’s kappa : The Cohen’s Kappa statistic was applied to assess the agreement between observed and predicted classifications, accounting for chance agreement. This statistic offers a nuanced understanding of the model’s performance, which is particularly valuable in scenarios involving imbalanced datasets. It is achieved by Eq.  20 .

Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) : MSE (Mean Squared Error) and RMSE (Root Mean Squared Error) were calculated to evaluate the average squared difference and the square root of the average squared differences, respectively, between predicted and actual classification categories. These metrics are instrumental in understanding the variance of prediction errors. MSE and RMSE are achieved using Eqs.  21 and 22 , respectively.

Mean Absolute Error (MAE) : MAE (Mean Absolute Error) measures the average magnitude of errors in a set of predictions, regardless of their direction. It is a linear score, meaning that all individual differences are equally weighted in the average. It is achieved using Eq.  23 .

Receiver Operating Characteristic (ROC) Curve and Area Under the Curve (AUC) : The ROC curve graphically illustrates the diagnostic ability of the model by plotting the true positive rate against the false positive rate at various threshold settings. The AUC (Area Under the Curve) provides a single scalar value summarizing the overall performance of the model across all possible classification thresholds. It is achieved using Eq.  24 .

F2-score : The F2-score was calculated to weigh recall higher than precision, useful in scenarios where missing positive predictions is more detrimental than making false positives. It is achieved using Eq.  25 .

These statistical methods and metrics provided a multifaceted evaluation of the model’s performance, ensuring a robust analysis of the predictive capabilities and reliability in classifying the cases within the IQ-OTH/NCCD lung cancer dataset.

The evaluation of the IQ-OTH/NCCD lung cancer dataset through our predictive model yielded detailed insights across various statistical metrics, showcasing the model’s efficacy in classifying lung cancer stages. Here we delve into a comprehensive analysis of each metric:

Confusion matrix : The confusion matrix offered a detailed perspective on the model’s classification performance, unveiling a notable count of true positives and true negatives, reflecting precise predictions. Notably, there were minimal occurrences of false positives and false negatives, underscoring the model’s accuracy in discerning between benign, malignant, and normal cases. The same is visualized in Fig.  7 .

Confusion matrix

Accuracy : The overall model accuracy was noted at 99.64%, highlighting the model’s robust capacity to accurately identify and classify instances within the dataset. This exceptional accuracy rate underscores the model’s reliability in clinical diagnostic settings, establishing a solid basis for subsequent validation and potential clinical implementation. To provide visual insight of this Fig.  8 gives truly classified instances.

Correctly classified instances

Precision : The precision metric provided valuable insights into the model’s predictive reliability. It attained a precision of 96.77% for benign cases, signifying a high probability that a case predicted as benign is indeed benign. Moreover, for malignant and normal cases, the precision reached 100%, demonstrating the model’s outstanding ability to predict these categories accurately without any false positives.

Recall : The recall scores were equally remarkable, achieving 100% for both benign and malignant cases, and 99.04% for normal cases. These findings underscore the model’s sensitivity and its capability to accurately detect all true positive cases, thereby mitigating the risk of false negatives as a pivotal consideration in medical diagnostics.

F1-score : The F1-scores, which strike a balance between precision and recall, were 98.36% for benign, 100% for malignant, and 99.52% for normal cases. These scores signify the model’s balanced performance, guaranteeing both the accuracy of positive predictions and the reduction of false negatives. To enhance the visualization of the classification report, Table  3 provides a statistical representation.

Based on Table 3 a heatmap to visualize the same detail is provided in Fig.  9 for better insights.

Classification report

Cohen’s kappa : With a Cohen’s Kappa score of 0.9938, the model exhibited perfect agreement with the actual classifications, surpassing the performance expected by chance alone. This underscores an elevated level of consistency in the model’s predictions, thus reinforcing its reliability.

Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) : The model reported an MSE of 0.0145 and an RMSE of 0.1206, indicating minimal variance and bias in the prediction errors. These low values suggest that the model’s predictions are consistently close to the actual values, enhancing trust in its predictive power.

Mean Absolute Error (MAE) : With an MAE of 0.0073, the model exhibited minimal average error magnitude in its predictions, signifying high predictive accuracy. This metric further reinforces the model’s suitability for clinical settings where precision is crucial. To visualize the error metrics, a bar chart is given in Fig.  10 .

Error metrics barh chart

Receiver Operating Characteristic (ROC) Curve and Area Under the Curve (AUC) : The ROC curves and corresponding AUC values were exceptional, achieving AUCs of 1.00 for malignant, benign, and normal cases. These results indicate the model’s outstanding discrimination ability between different classes across various threshold settings. The roc-auc curve is provided in Fig.  11 .

F2-score : The F2-score of 0.9964, which places more emphasis on recall, indicates the model’s strong ability to identify positive cases. This is particularly important in the medical field, where failing to detect a condition could have profound consequences. The visual representation of performance score is given in Fig.  12 .

Performance scores

The detailed results across these metrics provide a comprehensive picture of the model’s performance, highlighting its precision, reliability, and robustness in classifying lung cancer stages from the IQ-OTH/NCCD dataset. The findings demonstrate the model’s potential as a diagnostic tool, supporting its further investigation and potential integration into clinical practice.

The analysis of the IQ-OTH/NCCD lung cancer dataset with our model reveals a groundbreaking level of performance in medical image classification. With an accuracy of 99.64% and exceptional precision and recall metrics across the three categories (benign, malignant, and normal), the model emerges as a highly reliable diagnostic aid. The significance of these results extends beyond the high metric scores; it lies in the model’s capability to accurately distinguish between benign and malignant cases, a critical aspect for patient management and treatment planning.

The high F1-score underscores the model’s balanced consideration of precision and recall, thereby minimizing the risk of misdiagnosis. Additionally, the emphasis on recall in the F2-score holds particular significance in the medical domain, where overlooking a positive case (false negative) can have more severe consequences than erroneously identifying a case as positive (false positive). The comparison between the baseline models and proposed model has been given in Table  4 .

In the realm of lung cancer detection, many existing models focus predominantly on binary classification, often neglecting the nuanced differentiation between benign and malignant cases [ 37 ]. Our model’s tri-classification capability sets a new benchmark, offering a more detailed diagnostic tool compared to the binary classifiers. When juxtaposed with existing methods, our model’s performance underscores its advanced detection capabilities, potentially offering a more nuanced and informative diagnostic perspective than currently available tools.

For clinical practice, the integration of such a high-performing model could revolutionize lung cancer diagnostics [ 22 , 38 ]. It can augment radiologists’ capabilities, reducing diagnostic time and increasing throughput. The ability to accurately classify lung nodules as benign, malignant, or normal could significantly reduce unnecessary interventions, minimizing patient exposure to invasive procedures and associated risks. Additionally, it can streamline the patient pathway, ensuring rapid treatment initiation for malignant cases and appropriate follow-up for benign conditions [ 39 , 40 ].

While the results are promising, the study’s limitations warrant consideration. The model’s training on a dataset from a specific demographic and geographic area raises questions about its applicability to broader populations. Additionally, the model’s performance in a controlled study environment might not fully translate to the diverse and unpredictable nature of clinical settings. The black-box nature of deep learning models also poses a challenge in clinical contexts, where understanding the rationale behind a diagnosis is as crucial as the diagnosis itself [ 41 ]. To make it more clear in Fig.  13 some misclassified instances has been shown.

Misclassified instances

When evaluating our CNN model’s performance on the lung cancer dataset, we noticed some errors in classification. These mistakes can happen for various reasons. Firstly, some features in the CT scans may look similar between benign and malignant nodules, making it hard for the model to tell them apart. Also, noise and artifacts in the scans can confuse the model by hiding important details. Even though we tried to balance the classes, rare cases could still be challenging for the model to recognize. Plus, early-stage cancer might look very similar to normal tissue, making it tricky for the model to spot. Differences in how scans are taken can also affect the model’s understanding, leading to errors. Lastly, if the model learns too much from the training data, it might not perform well on new, unseen images. To fix these issues, we’re planning to use better techniques for preparing the data, like removing noise more effectively and making the model more flexible to different imaging conditions. We also aim to combine multiple models and use more diverse data to improve accuracy. By addressing these challenges, we hope to make our model better at classifying lung cancer stages.

While the IQ-OTHNCCD lung cancer dataset has been instrumental in developing and validating our model, it is important to recognize its limitations, particularly concerning demographic and geographic diversity. The dataset predominantly represents a specific population, which may not capture the full spectrum of variations seen in global populations. This limitation poses challenges for the model’s generalizability, as differences in demographics, such as age, ethnicity, and underlying health conditions, can influence the presentation of lung cancer in CT scans.

To address these limitations, future research should focus on expanding the dataset to include a more diverse range of CT scan images from various demographic groups and geographic regions. This expansion can be facilitated through collaborations with international medical institutions and accessing publicly available medical imaging repositories. Additionally, incorporating advanced data augmentation techniques that simulate variations in demographic characteristics, such as age and gender, can further enhance the dataset’s diversity. By broadening the dataset, we aim to improve the model’s robustness and ensure its applicability across different populations, ultimately enhancing the utility and reliability of our diagnostic tool in diverse clinical settings. This approach will contribute to developing a more inclusive and universally applicable model for lung cancer diagnosis.

Sensitivity analysis of precision, recall, and F1-score

In our endeavor to comprehensively assess the performance of our Convolutional Neural Network (CNN) model for lung cancer diagnosis, we conducted a sensitivity analysis focusing on precision, recall, and the F1-score. Precision sensitivity involved systematically adjusting the threshold values used for classification to observe its impact on false positive rates and the model’s conservatism in identifying positive cases. As precision increased, indicating a more stringent classification approach, false positives decreased, but the risk of false negatives rose, necessitating a delicate balance in medical diagnostics. Conversely, recall sensitivity entailed modifying the model’s sensitivity to detect positive cases, thereby influencing its ability to minimize false negatives. Heightened recall improved the identification of true positives, crucial for early diagnosis and treatment, albeit with potential increases in false positives, mandating cautious management. Additionally, analyzing the F1-score, a harmonic mean of precision and recall, elucidated its role in balancing false positives and false negatives. Optimizing for a high F1-score underscored a balanced approach, ensuring robust performance across both precision and recall metrics. Overall, the sensitivity analysis underscored the significance of striking a delicate balance between precision, recall, and the F1-score to optimize the model’s performance in clinical settings. By navigating and managing these trade-offs effectively, we can bolster the reliability and efficacy of our model in diagnosing lung cancer, thereby contributing to improved patient outcomes.

Regulatory considerations for clinical application

Implementing machine learning models in clinical settings involves navigating a complex landscape of regulatory requirements to ensure patient safety, data security, and efficacy. One of the primary regulatory hurdles is obtaining approval from medical device regulatory bodies such as the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), or other relevant national authorities. These regulatory agencies require extensive validation studies to demonstrate the model’s accuracy, reliability, and safety in diagnosing lung cancer. This involves rigorous testing on diverse datasets to ensure the model’s generalizability and performance across different patient populations and clinical scenarios.

Additionally, regulatory guidelines mandate that machine learning models used in healthcare must provide a level of interpretability and transparency. Clinicians need to understand the decision-making process of the model to trust and effectively integrate it into clinical workflows. This requirement for explainability poses a challenge for deep learning models, which are often considered “black boxes.” Therefore, developing methods to elucidate the model’s reasoning, such as feature importance analysis or visual explanations, is crucial for meeting regulatory standards.

Data privacy and security are also significant regulatory concerns, particularly with the implementation of regulations like the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States. Ensuring that patient data is anonymized, securely stored, and used ethically is essential for compliance. This includes implementing robust data encryption, access controls, and audit trails to protect sensitive health information from unauthorized access and breaches.

Moreover, post-market surveillance is a critical component of regulatory compliance, requiring continuous monitoring of the model’s performance in real-world clinical settings. This involves tracking the model’s diagnostic accuracy, identifying potential biases, and updating the model as needed to maintain its efficacy and safety over time. Establishing a framework for ongoing evaluation and improvement is essential to meet regulatory requirements and ensure the model’s long-term success in clinical applications.

Addressing these regulatory hurdles necessitates close collaboration between developers, healthcare providers, and regulatory bodies to ensure that machine learning models are safe, effective, and aligned with clinical needs. By adhering to these regulatory frameworks, we can facilitate the successful integration of advanced diagnostic tools into healthcare, ultimately enhancing patient outcomes and advancing the field of medical diagnostics.

Future research directions should focus on external validation of the model across various populations and healthcare settings to ascertain its universality and robustness. Integrating multimodal data, encompassing patient history, genetic information, and other diagnostic results, could enhance the model’s diagnostic precision. Addressing the interpretability of deep learning models could foster greater trust and integration into clinical decision-making processes. Additionally, prospective studies assessing the model’s impact on clinical outcomes, patient satisfaction, and healthcare efficiency would provide invaluable insights into its practical benefits and potential areas for improvement.

This study presented a comprehensive analysis of the IQ-OTH/NCCD lung cancer dataset using a sophisticated machine learning model, which demonstrated exceptional performance in classifying lung cancer stages. Key findings include a near-perfect accuracy rate of 99.64%, alongside impressive precision and recall metrics across benign, malignant, and normal case classifications. The model’s balanced F1-score and the emphasis on recall in the F2-score further highlight its diagnostic precision and sensitivity. These results signify a substantial advancement in the model’s ability to differentiate between nuanced lung cancer stages, providing a critical tool for early and accurate diagnosis.

The implications of these discoveries on the field of lung cancer diagnostics are profound. The model’s precision in classifying lung cancer stages holds the promise of substantially enhancing diagnostic protocols, thereby refining the accuracy and efficiency of lung cancer detection. This advancement has the potential to facilitate earlier treatment interventions, potentially enhancing patient outcomes and survival rates. Moreover, the model’s capability to differentiate between benign and malignant nodules could mitigate the need for unnecessary invasive procedures, consequently reducing patient risk and healthcare expenditures.

Future research should focus on external validation of the model to ensure its effectiveness across diverse populations and clinical settings. The exploration of model interpretability is crucial for clinical adoption, where understanding the basis for diagnostic decisions is essential. Additionally, integrating the model with other diagnostic data and clinical workflows could enhance its utility and impact.

Prospective studies are needed to evaluate the model’s real-world clinical impact, particularly its ability to improve patient outcomes, streamline diagnostic pathways, and reduce healthcare costs. The potential for the model to be adapted or extended to other types of cancers or medical imaging modalities also represents an exciting avenue for future research.

This study highlights the potential of advanced machine learning models to transform lung cancer diagnostics, providing a more precise, effective, and nuanced approach to detecting and classifying lung cancer. The ongoing advancement and incorporation of such models into clinical settings hold the promise of catalyzing substantial progress in patient care and outcomes within the field of oncology.

Availability of data and materials

Data used for the findings are publicly available at https://www.kaggle.com/datasets/hamdallak/the-iqothnccd-lung-cancer-dataset .

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Al-Ameen Engineering College (Autonomous), Erode, Tamil Nadu, India

M. Mohamed Musthafa

Department of Computer science and Engineering, East Point College of Engineering & Technology, Bangalore, India

I. Manimozhi

Department of Computer Science and Engineering, JAIN (Deemed-to-be University), Bengaluru, 562112, India

T. R. Mahesh

Adama Science and Technology University, Adama, 302120, Ethiopia

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Contributions

M.M.M took care of the review of literature and methodology. M.T.R has done the formal analysis, data collection and investigation. I.M has done the initial drafting and statistical analysis. S.G has supervised the overall project. All the authors of the article have read and approved the final article.

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Correspondence to Suresh Guluwadi .

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Musthafa, M.M., Manimozhi, I., Mahesh, T.R. et al. Optimizing double-layered convolutional neural networks for efficient lung cancer classification through hyperparameter optimization and advanced image pre-processing techniques. BMC Med Inform Decis Mak 24 , 142 (2024). https://doi.org/10.1186/s12911-024-02553-9

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Primary Market Research: Everything You Need to Know

P rimary market research supports businesses in gaining first-hand insights and information, which isn't already available about the market in which they operate. 

This supports decision-making and the growth of the business. Understanding your customers is key to business success, and primary market research is the most effective way to gain these insights. 

This guide will explore what is primary market research, the essentials of primary market research, its distinct advantages, methods and practical steps for conducting your own research.

Dive in to make informed decisions that drive growth.

What is Primary Market Research?

Primary market research is data that you gather from various techniques and sources, but it's all for a specific research purpose.

It involves the collection of new data and information that isn't already available for the business, typically conducted for a number of purposes including: identifying customer needs, identifying gaps in the market, reducing risk, and ultimately making better decisions.

The significance of primary market research lies in its ability to provide tailored insights and direct feedback from the target audience, which are essential for informed decision-making and strategic planning.

By engaging directly with the market, businesses can ensure that their decisions are based on up-to-date and relevant information, making their actions more effective and their strategies more aligned with consumer demands.

Importance of Primary Market Research

Primary market research offers the ability to design quantitative and qualitative questions tailored precisely to your needs.

It allows businesses to gather unique data, which can serve as a competitive edge and influence key strategic decisions. As highlighted, the main benefit is that it's research that is very focused on a particular research objective and it tends to be pretty up-to-date because the research data is gathered for that specific research objective.

This tailored and current data helps businesses minimize risks and make more informed decisions that are crucial for their growth and adaptation in a competitive market.

Primary vs. Secondary Market Research

Primary market research involves collecting data that has not been previously gathered, providing fresh insights directly tailored to the company's specific needs.

Secondary market research, on the other hand, involves utilizing data that was originally collected by others and already exists. For example, looking at industry sales and financial reports would be considered a secondary source.

The choice between these depends on the needs and resources of the business.

Primary research is vital when fresh, specific insights are needed, and secondary research is useful for broad, initial understandings, often at a lower cost and effort.

Before conducting primary research, you might want to see what secondary research is available to determine if the investment in primary research is justified.

Methods of Primary Market Research

Primary market research encompasses 5 main methods:

Surveys, whether conducted online or offline, are a popular method for gathering feedback. It's crucial to use a mixture of open and closed questions aimed at collecting information to ensure a comprehensive understanding. One effective strategy is making personality quizzes , which can be particularly engaging and insightful.

Best practices include keeping surveys concise to maintain participant engagement and ensuring a balanced number of questions to avoid respondent fatigue while still gathering sufficient data for analysis.

Focus Groups

Focus groups involve organizing five to ten people in a room, asking them questions about your product or a prospective product for the future. The benefits of this method include gaining deep insights through discussion and interaction, which can be more nuanced than those obtained via surveys.

However, the limitations include the potential for groupthink influencing individual opinions and the higher cost and logistical complexity of organizing these sessions.

In-Depth Interviews (IDIs)

In-depth interviews are one-on-one sessions that allow for a thorough exploration of individual opinions and experiences. Techniques for conducting effective IDIs include preparing a guide with open-ended questions to encourage detailed responses and actively listening to capture nuanced insights.

These interviews are invaluable for gathering detailed data but require skilled interviewers to manage the conversation and extract pertinent information.

Intercept Surveys

Intercept surveys are typically conducted in public places where researchers directly approach people to solicit immediate feedback on specific topics.

These are useful for collecting quick, on-the-spot impressions but can be challenging to implement due to the need for immediate participant engagement and the potential for bias in the responses collected in such a rushed environment.

In-Home Usage Tests (IHUTs)

IHUTs involve providing a product to consumers to use in their own homes, gathering authentic feedback on its usage in a real-world setting. Steps for conducting IHUTs include selecting appropriate participants, providing clear instructions for usage, and collecting feedback systematically.

This method offers the advantage of observing how a product is used in daily life, providing insights that can significantly enhance product development.

Step-by-Step Guide to Conducting Primary Market Research

Conducting effective primary market research involves several crucial steps, each designed to ensure that the data collected is both relevant and actionable.

Step 1: Define Objectives

The first step is to set clear, actionable goals which involve identifying what you want to achieve with the research. Objectives should be specific and directly related to the business challenges or opportunities you are addressing. This clarity ensures that the subsequent steps in the research process are aligned and focused on delivering the necessary insights.

Step 2: Choose the Right Method

Selecting the appropriate research method is crucial and should be based on the objectives you have set. For instance, if detailed, qualitative insights are needed, focus groups or in-depth interviews might be the best approach. Conversely, for broader quantitative data, surveys might be more appropriate. Each method has its strengths and should be chosen to best meet the research objectives.

Step 3: Design and Prepare

This stage involves developing questions and selecting participants. The design of the questions is critical as they must be structured to elicit clear, meaningful answers that directly address the research objectives. Selecting the right participants is equally important to ensure that the data collected is representative of the broader target audience.

Step 4: Collect Data

Data collection can be performed using a variety of techniques and tools depending on the chosen method. Whether through online surveys, face-to-face interviews, or observational studies, it's vital to collect data in a manner that minimizes bias and maximizes response rates and the quality of information received.

Step 5: Analyze Data

Once data is collected, it needs to be analyzed to extract meaningful insights. This can involve statistical analysis for quantitative data or content analysis for qualitative data. The aim is to interpret the data in a way that provides clear answers to the research questions posed at the outset.

Step 6: Report and Apply Findings

The final step in conducting primary market research is effectively reporting and applying the findings. This involves presenting findings and integrating them into business strategy. It's crucial to prepare reports that are both comprehensive and understandable, ensuring that key insights are accessible to all relevant stakeholders.

These findings should then be used to inform strategic decisions, such as entering new markets, adjusting marketing strategies, or improving products and services. Successfully applying research findings can lead to significant competitive advantages and better alignment with consumer needs and market trends.

Advantages and Disadvantages of Primary Market Research

Primary market research provides several significant advantages. One of the most crucial is data ownership, which gives businesses exclusive access to information that competitors cannot easily acquire.

This data is not only relevant but also extremely targeted, allowing businesses to gain deep insights into specific consumer behaviors and preferences. The targeted approach of primary research ensures that the data collected is directly applicable to the specific research objectives, leading to more effective decision-making and strategy development.

As noted, this method provides businesses with the ability to design questions tailored precisely to your needs, which in turn enhances the relevance and applicability of the research findings.

Disadvantages

Despite its many benefits, primary market research also comes with significant disadvantages, primarily related to its cost, time consumption, and the intensive resources required.

Conducting this type of research is often seriously time-consuming and involves considerable expense, not only in terms of financial outlay but also the human resources needed to design, execute, and analyze the research.

This method often requires a considerable investment in both staffing and technology, especially when handling large data sets or conducting detailed qualitative research.

Furthermore, the risk of research bias and the potential for non-representative sampling can further complicate the process, requiring additional controls and oversight to ensure validity and reliability of the research outcomes.

Best Practices for Primary Market Research

To maximize the effectiveness of primary market research, it's essential to follow several best practices. First, ensure that the research objectives are clearly defined and aligned with the strategic goals of the business.

This alignment helps in designing focused and relevant research tools and methodologies. Additionally, choosing the right sample size and demographic is crucial for obtaining representative and unbiased data. It's also important to use a mix of qualitative and quantitative methods to capture a broad spectrum of insights.

A common pitfall to avoid is the lack of thorough preparation, which can lead to poorly designed research that does not fully address the research questions. Also, avoid leading questions in surveys and interviews, which can introduce bias and affect the integrity of the data.

Ensuring respondent anonymity and confidentiality can improve the quality and honesty of the feedback received. Lastly, regularly review and adapt research methods to keep up with changes in the market and technology, thereby maintaining the relevance and accuracy of the data collected.

When to Hire a Primary Market Research Vendor

Outsourcing primary market research can be beneficial in several situations, particularly when the in-house team lacks the necessary expertise or resources to conduct comprehensive research.

Hiring a vendor is also advisable when the research requires extensive geographic reach or specialized knowledge that only professionals might possess.

When choosing a reliable vendor, it is crucial to assess their expertise and experience in your specific industry. Look for vendors with a proven track record of conducting effective research and those who can provide detailed case studies or references.

It's also important to evaluate the transparency of their research process and ensure they adhere to ethical standards and data protection laws.

Lastly, clear communication about goals, expectations, and research methodologies is essential to ensure that the vendor's approach aligns with your business needs and objectives

Business Applications of Primary Market Research

Primary market research is utilized across various industries to enhance product development, marketing strategies, and customer service.

In product development, businesses use primary research to test and trial new products or services before they are launched onto the market. This allows them to gather feedback and make necessary adjustments, reducing the risk of market failure.

For example, in the food industry, test marketing is often conducted in smaller geographical areas to gauge consumer response before a nationwide rollout.

In marketing, primary research helps companies understand consumer behavior and preferences, enabling them to tailor their advertising and promotional strategies.

The automotive industry provides a notable example, as seen with Chrysler Plymouth in the 1950s, which used focus groups to understand buyer preferences, leading to targeted advertising that significantly boosted sales.

Customer service also benefits greatly from primary research. Companies like Sky use surveys post-interaction to assess customer satisfaction and areas for improvement.

These insights help businesses refine their service offerings and enhance customer experience, ultimately contributing to customer retention and loyalty.

Primary market research is indispensable for businesses seeking to understand their market deeply and make informed decisions.

It provides targeted, up-to-date information that can significantly impact product development, marketing strategies, and customer service. By employing best practices and choosing the right methods, companies can avoid common pitfalls and maximize the effectiveness of their research efforts.

Ultimately, the thoughtful implementation of primary market research is crucial for maintaining competitive advantage and achieving sustainable growth.

Collagen is the most abundant protein in the body. Its fiber-like structure is used to make connective tissue. Like the name implies, this type of tissue connects other tissues and is a major component of bone, skin, muscles, tendons, and cartilage. It helps to make tissues strong and resilient, able to withstand stretching.

In food, collagen is naturally found only in animal flesh like meat and fish that contain connective tissue. However, a variety of both animal and plant foods contain materials for collagen production in our own bodies.

Our bodies gradually make less collagen as we age, but collagen production drops most quickly due to excess sun exposure, smoking, excess alcohol, and lack of sleep and exercise . With aging, collagen in the deep skin layers changes from a tightly organized network of fibers to an unorganized maze. [1] Environmental exposures can damage collagen fibers reducing their thickness and strength, leading to wrinkles on the skin’s surface.

Collagen Supplementation

Despite its abundance in our bodies, collagen has become a top-selling supplement purported to improve hair, skin, and nails—key components of the fountain of youth. The idea of popping a pill that doesn’t have side effects and may reverse the signs of aging is attractive to many. According to Google Trends, online searches for collagen have steadily increased since 2014.

Collagen first appeared as an ingredient in skin creams and serums. However, its effectiveness as a topical application was doubted even by dermatologists, as collagen is not naturally found on the skin’s surface but in the deeper layers. Collagen fibers are too large to permeate the skin’s outer layers, and research has not supported that shorter chains of collagen, called peptides, are more successful at this feat.

Oral collagen supplements in the form of pills, powders, and certain foods are believed to be more effectively absorbed by the body and have skyrocketed in popularity among consumers. They may be sold as collagen peptides or hydrolyzed collagen, which are broken down forms of collagen that are more easily absorbed. Collagen supplements contain amino acids, the building blocks of protein , and some may also contain additional nutrients related to healthy skin and hair like vitamin C , biotin , or zinc .

What does the research say on collagen supplements?

Most research on collagen supplements is related to joint and skin health. Human studies are lacking but some randomized controlled trials have found that collagen supplements improve skin elasticity. [3,4] Other trials have found that the supplements can improve joint mobility and decrease joint pain such as with osteoarthritis or in athletes. [5] Collagen comprises about 60% of cartilage, a very firm tissue that surrounds bones and cushions them from the shock of high-impact movements; so a breakdown in collagen could lead to a loss of cartilage and joint problems.

However, potential conflicts of interest exist in this area because most if not all of the research on collagen supplements are funded or partially funded by related industries that could benefit from a positive study result, or one or more of the study authors have ties to those industries. This makes it difficult to determine how effective collagen supplements truly are and if they are worth their often hefty price.

A downside of collagen supplements is the unknown of what exactly it contains or if the supplement will do what the label promotes. There are also concerns of collagen supplements containing heavy metals. In the U.S., the Food and Drug Administration does not review supplements for safety or effectiveness before they are sold to consumers.

Another potential downside is that taking a collagen supplement can become an excuse to not practice healthy behaviors that can protect against collagen decline, such as getting enough sleep and stopping smoking.

That said, the available research has not shown negative side effects in people given collagen supplements. [3,4]

Can You Eat Collagen?

Food containing collagen

• There are foods rich in collagen, specifically tough cuts of meat full of connective tissue like pot roast, brisket, and chuck steak. However, a high intake of red meat is not recommended as part of a long-term healthy and environmentally sustainable diet . Collagen is also found in the bones and skin of fresh and saltwater fish. [2]
• Bone broth, a trending food featured prominently in soup aisles, is promoted as a health food rich in collagen. The process involves simmering animal bones in water and a small amount of vinegar (to help dissolve the bone and release collagen and minerals) anywhere from 4 to 24 hours. However, the amount of amino acids will vary among batches depending on the types of bones used, how long they are cooked, and the amount of processing (e.g., if it is a packaged/canned version).
• Gelatin is a form of collagen made by boiling animal bones, cartilage, and skin for several hours and then allowing the liquid to cool and set. The breakdown of these connective tissues produces gelatin. Collagen and its derivative, gelatin, are promoted on certain eating plans such as the paleo diet .

Foods to boost collagen production

• Several high-protein foods are believed to nurture collagen production because they contain the amino acids that make collagen—glycine, proline, and hydroxyproline. [6] These include fish, poultry, meat, eggs , dairy , legumes , and soy .
• Collagen production also requires nutrients like zinc that is found in shellfish, legumes, meats, nuts , seeds, and whole grains ; and vitamin C from citrus fruits, berries, leafy greens, bell peppers, and tomatoes.

Is bone broth healthy?

In reality, bone broth contains only small amounts of minerals naturally found in bone including calcium , magnesium , potassium , iron , phosphorus , sodium , and copper. The amount of protein , obtained from the gelatin, varies from 5-10 grams per cup.

There is some concern that bone broth contains toxic metals like lead. One small study found that bone broth made from chicken bones contained three times the lead as chicken broth made with the meat only. [7] However the amount of lead in the bone broth per serving was still less than half the amount permitted by the Environmental Protection Agency in drinking water. A different study found that bone broth, both homemade and commercially produced, contained low levels (<5% RDA) of calcium and magnesium as well as heavy metals like lead and cadmium. [9] The study noted that various factors can affect the amount of protein and minerals extracted in bone broth: the amount of acidity, cooking time, cooking temperature, and type of animal bone used. Therefore it is likely that the nutritional value of bone broths will vary widely.

Healthy Lifestyle Habits That May Help  

Along with a healthy and balanced diet , here are some habits that may help protect your body’s natural collagen:

• Wear sunscreen or limit the amount of time spent in direct sunlight (10-20 minutes in direct midday sunlight 3-4 times a week provides adequate vitamin D for most people).
• Get adequate sleep . For the average person, this means 7-9 hours a night.
• Avoid smoking or secondhand smoke.
• Control stress . Chronically high cortisol levels can decrease collagen production.
• Although the exact connection between exercise and skin quality is unclear, some studies have found that exercise slows down cell activity involved with aging skin. [10]  

Bottom Line

At this time, non-industry funded research on collagen supplements is lacking. Natural collagen production is supported through a healthy and balanced diet by eating enough protein foods , whole grains , fruits, and vegetables and reducing lifestyle risk factors.

• Rinnerhaler M, Bischof J, Streubel MK, Trost A, Richter K. Oxidative Stress in Aging Human Skin. Biomolecules . 2015 Apr 21;5(2):545-89.
• Avila Rodríguez MI, Rodriguez Barroso LG, Sánchez ML. Collagen: A review on its sources and potential cosmetic applications. Journal of Cosmetic Dermatology . 2018 Feb;17(1):20-6.
• Proksch E, Segger D, Degwert J, Schunck M, Zague V, Oesser S. Oral supplementation of specific collagen peptides has beneficial effects on human skin physiology: a double-blind, placebo-controlled study. Skin pharmacology and physiology . 2014;27(1):47-55.
• Kim DU, Chung HC, Choi J, Sakai Y, Lee BY. Oral intake of low-molecular-weight collagen peptide improves hydration, elasticity, and wrinkling in human skin: a randomized, double-blind, placebo-controlled study. Nutrients . 2018 Jul;10(7):826.
• Bello AE, Oesser S. Collagen hydrolysate for the treatment of osteoarthritis and other joint disorders: a review of the literature. Current medical research and opinion . 2006 Nov 1;22(11):2221-32.
• Lodish H, Berk A, Zipursky SL, et al. Molecular Cell Biology . New York: W. H. Freeman; 2000.
• Monro JA, Leon R, Puri BK. The risk of lead contamination in bone broth diets. Medical hypotheses . 2013 Apr 1;80(4):389-90.
• Global Market Insights. Worldwide Broth Market . Feb 26, 2018.
• Hsu DJ, Lee CW, Tsai WC, Chien YC. Essential and toxic metals in animal bone broths. Food & nutrition research . 2017 Jan 1;61(1):1347478.
• Crane JD, MacNeil LG, Lally JS, Ford RJ, Bujak AL, Brar IK, Kemp BE, Raha S, Steinberg GR, Tarnopolsky MA. Exercise‐stimulated interleukin‐15 is controlled by AMPK and regulates skin metabolism and aging. Aging cell . 2015 Aug;14(4):625-34.

Last reviewed May 2021

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Main article content, influence of physical activity on health-related fitness in young adults: an observational research, karampreet kour buttar, sudhanshu kacker.

Background : Health-related fitness directly depends on the level of physical activity (PA) of the individual. Inactivity contributes to around 3.3% of all deaths, making the lack of exercise and sedentary lifestyles among the young generation a current source of concern. There is a paucity of research on the association between PA and health-related physical fitness among young people. In the perspective of this, the objective of this research was to find out the effect of PA levels on physical fitness in healthy adults. Methodology : A total of 419 students between the ages of 18 and 25 participated in this cross-sectional survey. The “Global Physical Activity Questionnaire (GPAQ)” was used to evaluate the PA. Their body fat percentage was measured using a skin fold caliper, followed by measurement of VO2max using a gas analyzer and hand grip strength and endurance assessment with the help of a computerized dynamometer. For statistical analysis, Karl Pearson's correlation coefficients and the ANOVA test were utilized. Results: PA was positively correlated with VO2 max (r=0.429), and handgrip strength (r=0.408) while negatively correlated with body fat % (r=-.315). VO2 max, body fat, and hand grip strength differ significantly amongst participants having different physical activity levels. (p-value =<0.05) Conclusion: This research concludes that PA is associated with physical fitness. PA will lead to a definite improvement in overall physical fitness. With the help of the results of this study, young adults can be motivated for physical fitness.

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Journal Identifiers

This paper is in the following e-collection/theme issue:

Published on 31.5.2024 in Vol 26 (2024)

This is a member publication of University of Oxford (Jisc)

How Informal Carers Support Video Consulting in Physiotherapy, Heart Failure, and Cancer: Qualitative Study Using Linguistic Ethnography

Authors of this article:

Original Paper

• Lucas Martinus Seuren 1, 2 , PhD   ; 
• Sara Shaw 1 , PhD  

1 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom

2 Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada

Corresponding Author:

Lucas Martinus Seuren, PhD

Nuffield Department of Primary Care Health Sciences

University of Oxford

Radcliffe Observatory Quarter

Woodstock Road

Oxford, OX2 6GG

United Kingdom

Phone: 1 4372607372

Email: [email protected]

Background: Informal carers play an important role in the everyday care of patients and the delivery of health care services. They aid patients in transportation to and from appointments, and they provide assistance during the appointments (eg, answering questions on the patient’s behalf). Video consultations are often seen as a way of providing patients with easier access to care. However, few studies have considered how this affects the role of informal carers and how they are needed to make video consultations safe and feasible.

Objective: This study aims to identify how informal carers, usually friends or family who provide unpaid assistance, support patients and clinicians during video consultations.

Methods: We conducted an in-depth analysis of the communication in a sample of video consultations drawn from 7 clinical settings across 4 National Health Service Trusts in the United Kingdom. The data set consisted of 52 video consultation recordings (of patients with diabetes, gestational diabetes, cancer, heart failure, orthopedic problems, long-term pain, and neuromuscular rehabilitation) and interviews with all participants involved in these consultations. Using Linguistic Ethnography, which embeds detailed analysis of verbal and nonverbal communication in the context of the interaction, we examined the interactional, technological, and clinical work carers did to facilitate video consultations and help patients and clinicians overcome challenges of the remote and video-mediated context.

Results: Most patients (40/52, 77%) participated in the video consultation without support from an informal carer. Only 23% (12/52) of the consultations involved an informal carer. In addition to facilitating the clinical interaction (eg, answering questions on behalf of the patient), we identified 3 types of work that informal carers did: facilitating the use of technology; addressing problems when the patient could not hear or understand the clinician; and assisting with physical examinations, acting as the eyes, ears, and hands of the clinician. Carers often stayed in the background, monitoring the consultation to identify situations where they might be needed. In doing so, copresent carers reassured patients and helped them conduct the activities that make up a consultation. However, carers did not necessarily help patients solve all the challenges of a video consultation (eg, aiming the camera while laying hands on the patient during an examination). We compared cases where an informal carer was copresent with cases where the patient was alone, which showed that carers provided an important safety net, particularly for patients who were frail and experienced mobility difficulties.

Conclusions: Informal carers play a critical role in making video consultations safe and feasible, particularly for patients with limited technological experience or complex needs. Guidance and research on video consulting need to consider the availability and work done by informal carers and how they can be supported in providing patients access to digital health care services.

Introduction

Video consulting has become an established health care service model since the outbreak of the COVID-19 pandemic [ 1 ]. Video consultations have been shown to be safe and effective in a range of clinical settings [ 2 - 6 ]. Patients and clinicians have largely reported positive experiences, particularly in secondary and tertiary care [ 7 - 10 ], with some patients even preferring video consultations over face-to-face consultations, especially for follow-up appointments and where a trusted relationship with the provider is already in place [ 11 ]. Given the policy push for remote health care services to continue beyond the COVID-19 pandemic [ 12 - 14 ], it is clear that video consulting is here to stay. However, significant concerns remain around when video consulting is feasible and appropriate (eg, for which patients and in which clinical settings) [ 15 - 17 ]. Some patients still do not have access to the necessary technology (ie, smartphone, tablet, or computer and high-quality internet) [ 18 , 19 ] and they may also lack the experience, confidence, or ability to use it for a medical consultation [ 20 - 22 ]. In these situations, carers, either professional or informal (eg, family and friends), can provide assistance [ 23 , 24 ].

There is extensive literature on video consulting, documenting the benefits and challenges for patients and clinicians [ 5 ]. However, very few studies address how informal carers participate in video consultations [ 25 , 26 ]. This is surprising, given that informal carers play an important role in patient care. Informal carers, usually family or friends, “[provide] unpaid care and support to a family member, friend or neighbour who is disabled, has an illness or long-term condition, or who needs extra help as they grow older” [ 27 ]. In the United Kingdom, approximately 6 million people provide unpaid care, many of whom play a vital role in coordinating and supporting care received by the person they care for [ 28 , 29 ]. Therefore, it is important to understand the role they play in supporting and delivering video-consulting services.

Contemporary health care systems and policy makers have been pushing a transition to patient-centered or person-centered care, that is, care that is “respectful and responsive to individual preferences, needs and values” [ 30 ]. However, person-centered care has often been taken to only mean patient-centered care. Guidelines do not always address family or carers, and where they do, they merely highlight that practitioners must involve carers in patient care, for example, by asking them to clarify the patient’s wishes [ 31 ]. In other words, the focus in person-centered care is still on the patient. Nevertheless, informal carers play a central role in the delivery of care, supporting patients (to varying degrees and in varying situations) with their needs and care. Carers may deliver up to 90% of the care and support for patients in the community [ 32 ]. Therefore, it is potentially important for guidance on video consultations to take carers, and the support of carers, into account. Given that the work done by carers can cause a significant mental and physical strain [ 33 ], practitioners and policy makers need to consider the preferences, needs, and values of patients and carers.

Health communication research has shown that carers sometimes play an active role in making in-person consultations work: carers may speak on behalf of the patient (eg, to provide additional medical or other information for children or patients who lack capacity), alongside the patient (eg, when planning a next appointment), or with the patient (eg, to help them answer questions about their medication) [ 34 - 36 ]. However, having a carer copresent, that is, physically with the patient in the consultation, can be challenging as patients, clinicians, and carers report that they have trouble managing turn-taking [ 37 ]. This raises questions regarding when the carer is able to talk, what they can talk about, and how they can determine this.

Participation problems may be more pronounced in video consultations. From research outside the health care setting, we know that it can be difficult for carers to facilitate a conversation over video [ 38 ]. The camera restricts the field of view, and generally, only 1 person is visible at a time on each end [ 39 ]. The clinical context adds additional challenges, with participants having to manage new interactional skills (eg, how to begin a video consultation) and accomplish activities that are constrained by the lack of physical copresence (eg, conducting a physical examination) [ 5 , 40 , 41 ].

To date, only 1 study has investigated how the constraints of technology affect communication in health care where informal carers are copresent, focusing on postoperative cancer consultations in the Netherlands and showing that carers often remain offscreen and do not actively participate, and when they do, they mostly talk to the patient [ 42 ]. Several other studies have investigated how professional carers (eg, copresent nurses or primary care physicians) participate in video consultations, with a focus on how these professional Despite their crucial role in health care delivery, informal carers have not yet benefited from the advancements made in this field [ 29 ].

Overall, there is a need to understand how informal carers support video consultations when they are copresent with the patient. This study focuses on how informal carers support patients and clinicians during video consultations. Our focus is on the work (either interactional, clinical, or technological) that informal carers do to make video consultations work to provide key insights into how they affect the feasibility of video consulting. To support our analysis, we compared the consultations where informal carers provided support and the reflections of participants in subsequent interviews with consultations where patients were alone and the reflections of those participants.

Study Design

We conducted a qualitative, multimethods study using Linguistic Ethnography, which combines ethnographic approaches (ie, observation and interviews) with the close inspection of interactional data [ 43 ]. We used ethnography of communication [ 44 ] to guide our understanding of how the context of video consultations (eg, restricted visual field) may shape the ways in which patients, carers, and clinicians communicate over video. We combined this with conversation analysis, an inductive method that investigates the turn-by-turn construction of a conversation, to understand the communication practices (verbal and nonverbal) that make up a video consultation [ 45 ]. Combining these methods enabled us to show how the interactions in video consultations shape, and are shaped by, the wider sociocultural and clinical contexts (eg, established clinical routines, policy, and technology in use) [ 46 ].

For this study, we conducted secondary analysis of qualitative data that were previously collected for 3 separate studies on video consultations in different clinical settings across 4 National Health Service clinics in the United Kingdom (1 in Oxford and 3 in London):

• Supporting Consultations in Remote Physiotherapy (SCiP; 2021-2022) was funded by the National Institute for Health Research to investigate the feasibility and practicalities of video consultations for physiotherapy.
• Virtual Online Consultations: Advantages and Limitations (VOCAL; 2015-2017) was funded by the National Institute for Health Research and investigated (gestational) diabetes and cancer.
• Oxford Telehealth Qualitative Study (OTQS; 2015-2017) was funded by the Wellcome Trust to investigate the feasibility of video consulting in a specialist nurse service for patients with heart failure.

Data were chosen for convenience, having been collected as part of research studies that had already been conducted by members of the larger research team and available for secondary analysis [ 47 , 48 ].

Data Collection

We analyzed all 52 video recordings of video consultations that were recorded across the 3 studies. Data for VOCAL and OTQS were collected from 2015 to 2017 (refer to the study by Shaw et al [ 5 ] for an overview), and data for SCiP were collected from 2021 to 2022 (refer to the study by Seuren et al [ 47 ] for an overview).

In all 3 studies, recruitment was done based on convenience. For VOCAL and OTQS, which took place before the COVID-19 pandemic when video consulting was still relatively unfamiliar, patient participants were recruited in collaboration with clinical staff to ensure that patients were suitable to have a video consultation. The aim was to create a sample with a range of experiences with video consultations, “seeking maximum variety in clinical, ethnic and personal circumstances.” Patients were initially contacted by their clinician, after which the research team sent out an invitation letter [ 5 ]. For SCiP, data collection took place between August 2021 and March 2022, during the COVID-19 pandemic. Initially, clinicians reached out to any patient who had an upcoming appointment by video. Those who showed an interest in the study were subsequently contacted by a member of the research team to explain the details of the study [ 47 ]. For all studies, exclusion criteria were the inability to give informed consent and comorbidity preventing participation. For VOCAL and OTQS, additional exclusion criteria were no 3G internet access at home and lack of familiarity with technology [ 5 ].

Video consultations for VOCAL and OTQS were recorded using small digital camcorders (Sony Handycam DCR-SR72; Sony Corporation) and a handheld iPad (Apple Inc), combined with a commercially available screen-capture software tool (ACA Systems), which was run directly from an encrypted USB memory stick. Whenever feasible, both the patient’s and the clinician’s end of the consultation had been recorded, capturing the consultations and the context in which they took place. The total data set from VOCAL and OTQS consisted of 37 video recordings and transcripts of the video consultations (cancer: 12/37, 32%; diabetes: 12/37, 32%; heart failure: 7/37, 19%; and gestational diabetes: 6/37, 16%), 35 transcripts of semistructured interviews conducted with staff and 26 transcripts of semistructured interviews conducted with patients involved in these consultations ( Table 1 ) [ 5 ].

Video consultations for SCiP were recorded by the clinical team in the 2 National Health Service Trusts using the built-in recording option in Microsoft Teams (Microsoft Corp). The total data set consisted of 15 video recordings and transcripts of video consultations (neuromuscular rehabilitation: 5/15, 33%; long-term pain: 1/15, 7%; and orthopedics: 9/15, 60%), 15 transcripts of semistructured interviews with patients and 7 transcripts of semistructured interviews with clinicians involved in these consultations ( Table 2 ) [ 47 ].

a There was only one participant; hence, there is no IQR.

An initial exploration of the 52 recorded video consultations across all 3 studies showed that informal carers performed a range of seemingly vital tasks in some (but not all) video consultations (12/52, 23%; eg, holding the tablet and laying hands on the patient). This raised questions about the role of carers in video consultations. We collected all instances in our video data where carers were involved at any point during a video consultation and corresponding interview data in which participants in these video consultations reflected on the work carers do. As a routine practice in conversation analysis [ 49 , 50 ], we then built “collections” of similar cases [ 51 ], organizing the data based on the type of work done by carers. To further refine our analysis, we compared our findings with consultations where no carer was present (40/52, 77%), combining researcher observations of potentially risky situations (eg, an older patient nearly fell) with clinician reflections on these consultations to identify cases where the lack of a copresent carer might have negatively affected the quality of care. On the basis of these collections, we then analyzed the qualitative interviews deductively using thematic analysis [ 52 ]. Themes were identified based on our analysis of the consultations and used deductively to analyze the interviews. We examined how participants talked about the 3 key themes, aiming to discern whether participants’ reflections were in line with our findings of the consultations (eg, when and why do patients require assistance with technology) or whether they offered complementary (eg, additional work done by informal carers outside of the consultation) or even contradicting viewpoints (eg, informal carers not being able to offer support). Our analysis focused on the conversation analysis of the consultations, with supporting reflections from the participants.

As all data were selected for convenience, the consultations that involved a carer and those that did not involve a carer were not matched regarding, for example, clinical context, patient demographics, or type of technology used.

We transcribed all video consultations orthographically and subsequently used established conventions for verbal and nonverbal communication [ 53 , 54 ] for the data in our collections. This is a routine practice in conversation analysis and, for this paper, enabled us to track how and why carers assist in video consultations. In the Results section, we present simplified extracts from transcripts, providing orthographic transcripts complemented with notations for silence and overlapping talk to maintain legibility. We added screengrabs to allow readers to appreciate the context of consultations and how participants use their bodies and material objects (eg, how they move and hold a tablet). All interviews were transcribed orthographically. We extracted screengrabs using Adobe Premiere Pro 2023 (Adobe Inc), adding a video filter and facial blur to deidentify participants. Subsequently, we combined these screengrabs with the transcript in Adobe InDesign 2023 (Adobe Inc) and exported these at 600 dots per inch to generate the figures.

Ethical Considerations

All studies received ethics approval for detailed analysis of video recordings of video consultations and audio recordings of interviews. VOCAL was approved by the National Research Ethics Committee London-City Road and Hampstead in December 2014 (14/LO/1883), OTQS by the South Central-Berkshire Research Ethics Committee in September 2015 (15/SC/0553), and SCiP by the East Midland-Nottingham 1 Research Ethics Committee in April 2021 (21/EM/0082). All participating staff and patients provided their informed consent to be audio and video recorded during consultations and interviews and for the data to be used for research purposes, including secondary analysis.

Patients were initially approached by a member of their clinical care team. After signaling an interest in the study, the patient’s contact information was forwarded to a member of the research team. The author provided the patient with an information sheet to review. After providing an opportunity to ask questions, patients were asked if they wanted to participate, and if they agreed, they were asked to sign the consent form. For VOCAL and OTQS, patients provided consent during an in-person conversation with a member of the research team. For SCiP, to comply with infection control procedures during the COVID-19 pandemic, patients provided verbal consent during a video call. Participants did not receive compensation for participation in any of the 3 studies.

All transcriptions were anonymized by removing identifying data and replacing names with descriptions (eg, NAME, where someone’s name is used). Participants consented to the analysis of the raw (ie, recognizable) video data. For publication, video data were anonymized using a visual filter and blur effect in Adobe Premiere Pro 2023.

Main Findings

Of the 52 video consultations in our data, 12 (23%) involved a copresent carer: 8 (67%) with patients with cancer, 3 (25%) with patients with heart failure, and 1 (8%) with a patient consulting for physiotherapy. None of the patients with gestational diabetes had a copresent carer. In these 12 consultations, we identified three main types of work that carers performed: (1) facilitating the use of the technology, (2) helping the patient hear or understand what the clinician said, and (3) assisting the patient with and performing parts of the physical examination. Carers performed these tasks through the use of verbal and nonverbal communication strategies, as seen in the data extracts, screengrabs, and participants’ reported experiences in the following sections. Furthermore, we found that in 10% (5/52) of the consultations the patient did not have a carer copresent, but either the patient or clinician expressed concerns regarding safety during the consultation (eg, a patient saying, “I’m not sure if I’ll be able to get back up again”) or the clinician, during the interview afterward, commented that they felt they might have put the patient in an unsafe situation.

Facilitating the Use of Technology in Video Consultations

Informal carers facilitated the use of technology for video consultations in 2 ways: they provided patients access to the technology, and their presence and perceived expertise provided patients with confidence and reassurance for using the technology.

In our data, some patients (5/52, 10%) either did not have the technology or had never used it for video chat. Therefore, they relied on carers to set up, and sometimes provide, the technology. This facilitation involved activities such as the carer bringing a tablet for the patient to use, registering a Skype (Skype Technologies) account, adding the clinician as a contact on Skype or FaceTime (Apple Inc), talking to the clinician beforehand regarding any practicalities, and explaining to the patient what to expect from the video consultation. For the patients who lacked experience with video-mediated communication, carers provided a sense of reassurance if something went wrong or if there were difficulties. This was evident both in how the informal carers acted in the consultations and how they discussed their experiences during the interviews. An older patient explained before her oncology consultation that she only agreed to a video consultation if her husband would be there:

First uh, I was a bit uh, I said uh, if he’s here it’s fine. I haven’t got any problem.

Another older patient stated after her heart failure consultation that, while she could learn to use the technology, she relied on her daughter being there and would not have been able to do it on her own:

Patient: that’s what I really think, that for me,... it’s easy. Because I don’t have to sit here and think, what if I do something wrong? Carer: no Patient: for people, old people on their own, entirely different. Carer: yeah. it is entirely different. Patient: And I would not be able to do it on my own. ... I wouldn't have the confidence.

During consultations, we found that carers often facilitated the use of technology while being silent (ie, nonspeaking) and offscreen. This involved carers performing 3 types of background activities that allowed the patient to consult with the clinician via video: they handled the “preopening,” the work people do before they start a video consultation [ 55 ]; they handled the camera allowing the patient and clinician to adequately see each other; and they made sure that the patient and clinician could hear each other.

In 8 (67%) of the 12 consultations, carers took care of the “preopening” [ 55 ]: they set up the technology, logged in, and answered the call from the clinician when using a program such as Skype or FaceTime. Then, the patient took over when the consultation started.

In the example in Figure 1 , the patient had never used FaceTime before and did not own a video communication technology (eg, a smartphone or tablet). The carer brought a tablet with her, signed into FaceTime, and held it ready for use. When the clinician called via video, the carer explained to the patient that they would accept the call (line 1). Then, she swiped to answer, pointed out to the patient when the connection was established (line 7) and answered the video call with a "hello, conveying to the clinician that the connection had been established and they were ready [ 56 ]. The carer stayed out of the frame (refer to screengrab 2 in Figure 1 ) and hence out of the interaction [ 42 , 57 ], allowing the patient to conduct her consultation while still remaining available in the background.

In 7 (58%) of the 12 consultations, carers did additional background work that enabled patients to talk to their clinician. This included making sure that the patient and clinician could adequately see and hear each other, for example, by acting as a cameraperson: positioning the technology and framing the patient throughout the consultation [ 38 ] to maintain a “talking heads” configuration for the patient and clinician [ 39 ], a setup in which both participants are visible from the shoulders up. In 71% (5/7) of these consultations, the carer held a tablet or smartphone, moving this to frame the patient while remaining outside the frame themselves. In 29% (2/7) of these consultations, the patient used a desktop PC, so the carer moved the patient instead of the technology.

In the example in Figure 2 , from the start of an oncology consultation, the patient was at the left edge of the field of view of the camera and only half of her face was visible to the clinician. As soon as the physician told the patient to “move slightly” (line 3), the carer turned toward the patient and began to pull their chair. At the point where the physician completed his request (line 8), the patient was visible in the center of the screen. Our recording of the clinician’s end does not capture the screen. However, on the screen on the patient’s side, we can see that initially only the right half of her face is visible, and the carer then adjusts the chair so that the patient is centered and fully visible.

In 4 (33%) of the 12 consultations, the carers acted as a technological facilitator to ensure the audio and video were working. Carers did most of this work at the start of the consultation. This was the first point where participants could determine whether the sound and video were working. In the example in Figure 3 , the carer answered the clinician’s call when he appeared on screen by saying “hello” (line 1), but the clinician did not respond. The carer treated this silence as indicating a problem: she said “hello” again but this time with a more questioning intonation (a strong rising pitch on the “o”), a typical communication strategy for testing if someone can still hear [ 58 ].

After the clinician had said “hi” (line 4), he asked whether the patient (and carer) could hear him (line 8). The patient and carer confirmed (lines 9-10), and the carer checked whether the clinician could hear them. In other words, before the consultation began, the carer and clinician ensured that the technology was working and that the patient and clinician could see and hear each other. It was only when the physician had confirmed (line 14), that the consultation proceeded in a usual manner. At this point, the carer faded into the background.

Staying largely in the background (and so invisible to the clinician), carers typically maintained an active role, helping to address any problems (eg, lost connection or microphone on mute) that arose during the consultation. In these instances, carers temporarily became active participants while fixing the problem. In the example in Figure 4 , the physician asked the patient “how are you.” However, a technical disruption occurred and his turn was cut off after “ho.” After a few seconds of silence, the physician said, “what happened” (line 3), taking the lack of response by the patient as indicative of a problem. It was the carer who then switched to become an active coparticipant, asking if the physician could hear them (line 5). Once all parties had established that they could see and hear each other, the physician acknowledged (line 13) [ 59 ] and repeated the question.

Overall, carers in our data made video consultations feasible by facilitating the use of technology. Much of this work involved carers moving from being coparticipants to listening in the background, often unobservable to the clinician. They did this either by self-selecting to respond to a clinician’s question ( Figures 3 and 4 ) or by being selected by the clinician to answer a question. After responding, they would visually move out of the screen, or at least, no longer respond or take turns.

Making the Interaction Work in Video Consultations

Patients in our study occasionally had problems with hearing or understanding the clinician (eg, due to soft or distorted sound). Such problems happen routinely in any form of conversation [ 60 ], and people have a large array of repair strategies to fix them [ 61 , 62 ]. Normally, when trouble arises, recipients ask the speaker to repeat or clarify (part of) their turn (eg, by repeating the part of the turn they did hear or using exclamations such as “sorry,” “what,” or “huh” [ 63 - 65 ]). During in-person consultations, if patients have problems, they can ask the clinician to clarify [ 66 ].

In our video consultation data, we found that 25% (3/12) of the patients relied on their carer to help them hear or understand the clinician’s talk (in all 3 consultations, the quality of the call was problematic, eg, low volume and distortions). The example in Figure 5 illustrates how carers perform this type of interactional repair. In lines 1 to 4, the physician checked that the patient had seen one of his registrars the week before at an in-person consultation. At this point, the volume was low, making it hard to hear. Moving into the physician’s turn, the patient started squinting (refer to screengrab 1 in Figure 5 ), indicating she had a problem. When the physician finished his question, the patient remained silent for 700 milliseconds (a substantial amount of time, given the usual response time for face-to-face interaction being 0-200 milliseconds [ 67 ]), indicating difficulty [ 68 ]. Instead of answering, the patient turned to the carer (refer to screengrab 2 in Figure 5 ), softly asking “what?” (indicated with the degree symbols) and expecting the carer to perform an interactional repair on the physician’s question. The carer (offscreen) repeated the physician’s verification question in line 8. Once the patient could answer, she started to nod, turned her gaze toward the physician (line 9), and answered (line 11) loudly, thereby making clear her response was now directed to the physician.

While this was a brief interaction, the carer in this example played a crucial role in the successful communication between the physician and the patient. The patient mobilized the carer to help her hear what the physician said. Akin to an interpreter, the carer “animated” the physician’s talk [ 57 ]. Similar examples using indirect communication (eg, physically turning to the carer when something was unclear) were evident across our data set, where patients sought help from carers to enable repair and continuation of the interaction.

Making Physical Examination Possible in Video Consultations

The final area where carers made a vital contribution to video consultations was during physical examinations. The inability of clinicians to lay hands on the patient is one of the main concerns among clinicians and patients about video consultation [ 69 - 71 ]. Instead, patients have to describe and show their body and, where available, use their own devices such as oximeters (a device that people clip onto their finger to measure their blood oxygen saturation and heart rate) [ 40 , 72 ].

Carers supported remote physical examinations in 8 (67%) of the 12 video consultations in our data. This included helping to make the relevant parts of a patient’s body visible, acting as the clinician’s hands to perform tactile examinations and providing visual assessments, and assisting the patient with operating equipment such as blood pressure meters. Support was typically for patients who were frail, in cases where they were either unable to bend over (eg, due to the nature of their condition) or unable to move their tablet or laptop at the same time as moving their body (a complex sociotechnical task that was particularly challenging for those experiencing chronic illness) [ 72 ].

Figure 6 illustrates how carers can play a vital role in the feasibility of a physical examination. The patient had recently undergone surgery to remove a tumor and had complained to the physician about pain in her abdomen around the scar. The physician asked to examine the scar, requesting her to stand up (lines 1-3). The patient did not respond to this request. Instead, she waited for the carer to help out. After 1.3 seconds of silence, the physician made his request again, but at the same time, the carer said “hold on.” Then, the carer helped the patient lift her sweater and aimed the camera toward the scar, allowing the physician to perform a visual assessment (lines 16-19).

In the example in Figure 6 , the role of the carer was crucial for making the physical examination work. With limited physical capacity (and technological literacy), the patient was unable to hold the tablet and show the clinician her abdomen. It was only with the help of her carer that she could provide a sufficiently clear view for the physician to perform a visual assessment remotely.

At times, clinicians relied on a carer to lay hands on the patient on their behalf during video consultations. In the heart failure consultations—both routine follow-up consultations—the specialist nurse wanted to check whether the patients had fluid build-up (edema) in their legs and ankles by pressing their thumb on the patient’s leg and check whether this leaves an indentation. Carers played a vital role in performing these remote assessments, which involved patients who were frail, with restricted mobility and breathlessness, and for whom moving could cause severe discomfort [ 72 ]. Figure 7 illustrates an example in which the patient had just measured her blood oxygen saturation with an oximeter. Then, the nurse addressed the carer directly, announcing that she wanted to check the patient’s legs (lines 1-4). Depicting how the carer should hold her hand (lines 11-16) [ 72 , 73 ], she explained how to press (lines 18-19). The carer followed these instructions and pressed the patient’s legs several times. Using the camera on the back of the tablet, she not only performed the examination but also did so while simultaneously monitoring what the nurse could see (refer to screengrabs 2 to 4 in Figure 7 ). The carer’s presence meant that the nurse was able to make a good assessment of the patient’s legs, telling the carer that “you’re doing a good job, and I can see it really clearly on the screen.”

In total, 2 (4%) of the 52 cases in our wider data set of video consultations flagged questions regarding the safety of physical assessment where carers were not present. Figure 8 illustrates the example of a neuromuscular physiotherapy consultation with a patient with Charcot-Marie-Tooth disease (a neurological disorder that causes damage to the peripheral nerves leading to muscle weakness and atrophy), who struggled with walking and balance. At one point, the clinician asked the patient to stand up so that she could see her walk while holding onto a wall. The patient had to push herself from the bed, had difficulty standing up without losing her balance, and had to use both hands to help herself. In hindsight, the clinician acknowledged that this may have been too difficult.

We identified a similar case in our heart failure data, where an older patient raised her leg to the camera, allowing her nurse to assess whether there was any swelling ( Figure 9 ). The patient needed to stand and had to hold on to the chair in front of her to maintain her balance, but the uncomfortable position caused abdominal cramps and led her to drop her leg. This raised questions regarding safety while also placing limits on what was only a brief visual assessment.

Furthermore, carers helped some patients (2/12, 10%) operate measuring devices during examination. This was particularly relevant in remote heart failure consultations, in which all 7 patients needed to measure their oxygen saturation, blood pressure, and heart rate. All 7 patients were able to use the oximeter; however, operating a blood pressure meter proved challenging for 2 patients, both experiencing frailty. In both cases, the patient’s carer placed the cuff on their arm, held the monitor up to the screen to display the results, and adjusted positions so that the patient’s blood pressure measurements could be obtained from both sitting and standing positions ( Figure 10 ).

Remote physical examinations are complex sociotechnical tasks, involving (in our data) at least 3 people, multiple devices at both ends of the call, and a series of instructions and interactions conducted over a video consultation [ 72 ]. Hence, while carers were often needed to make physical examinations work, the assistance of a carer did not make them straightforward. In 1 consultation, video largely restricted the examination to a visual inspection. As the carer from Figure 6 reported after the consultation, with an in-person consultation, “[the patient] could probably explain more where it hurts and [the physician] could, you know, feel why it’s, you know, still tender.” Furthermore, doing the examination while making it visible to the clinician can be challenging for the carer [ 72 ]. This was summarized by the carer from Figure 1 as follows:

Well, look at me, fannying about just trying to get a picture of your leg. I mean it’s not a matchstick. I just could not picture. But it’s partly, because I’m holding it and I can’t see what I’m looking at.

Principal Findings

Our findings demonstrate that, for some video consultations with some patients, informal carers play an important role in supporting setting up and running a video consultation. While most patients (40/52, 77%) in our data completed the consultation on their own, informal carers were the linchpin that made the video consultation safe and feasible, especially when the patients lacked technological literacy or experienced high frailty. We demonstrated this using recordings and observations to show 3 types of work that carers perform. First, they help patients use video technology by setting up everything beforehand and acting as technological support, providing patients with the confidence to even commit to using video. Second, where patients struggle to hear or understand the clinician, carers perform the interactional repair work, repeating or clarifying the clinician’s words. Third, where physical assessments are needed, carers can lay hands on the patient’s or the clinician’s behalf or assist the patient with using the technology (either video technology or examination equipment). Even where patients seemed to manage on their own, patients performed maneuvers that put them at risk of falling, and this was not always clear to the remote clinician. Copresent carers provide an important safety net, making video consultations safe and feasible.

Comparison With Previous Research

There is an extensive body of research on the feasibility and acceptability of video consultations [ 6 - 10 ], which indicates that some patients may need assistance from carers [ 74 ]. However, to date, no study has investigated the work informal carers do to support video consultations. A total of 3 health communication studies have used robust methods for analyzing interaction to demonstrate how carers, whether professional or informal, can be involved in a consultation. Two (67%) of these 3 studies documented that nurses and general practitioners play an essential role in making physical examinations work when patients talk to a remote consultant [ 74 , 75 ]. One study on follow-up consultations after surgery showed that informal carers mostly act as bystanders: they remain invisible to the clinician and only occasionally facilitate the consultation [ 42 ].

Our study adds to this growing body of literature, demonstrating that informal carers may take a more active role than that of a bystander: in our data, they are attentive to the interaction, moving into and out of the field of view of the camera as needed; performing a range of technical, interactional, and clinical tasks; and taking a more active role depending on the needs of both the patient and clinician. Discrepancies between our findings and previous studies can be accounted for in many ways. First, as both the 3 previous studies and our study are qualitative in nature, they prioritize analytical depth, which mandates small patient samples that are not necessarily representative, and these are prone to bias in recruitment processes. Second, all studies have taken place in different geographical locations, at different points in time (eg, before or during the COVID-19 pandemic), and in different clinical settings, with patients with different sociodemographic backgrounds. While the methods may be transferable, more research is needed to appreciate to what extent the findings transfer.

The important role of carers is not limited to video consulting. For in-person consultations, research has shown that carers can be actively involved, talking about, alongside, or with the patients, to provide clinicians with relevant information [ 34 - 36 ]. Findings from our study extend this, demonstrating not only the other types of work that carers do to support video consultations but also how the technology shapes this work.

Videoconferencing technologies and the visual angle of webcams are designed for one-to-one conversations [ 39 ]. These aspects of technology add to the complexity of the interactional dynamics that already exist for triadic consultations (ie, involving a patient, clinician, and informal carer), where participants may struggle with turn-taking [ 34 , 35 ]. Because of this added complexity, video consultations have a continuously shifting participation framework (ie, the roles of patient, clinician, and carer as, for example, an active coparticipant of overhearer) [ 57 ], where carers move in and out of a variety of interactional and technical support roles. Depending on the situation (eg, the patient’s capacity and willingness to talk on their own behalf), carers may be expected to be more or less active coparticipants during consultations. Being offscreen makes carers less available for the clinician. They are more likely to act as overhearers [ 42 ], which can be beneficial in cases where patients wish to interact with the clinician themselves, but it may also be detrimental when patients need more continuous support. Therefore, our findings contribute to not only our appreciation of the important role of carers in the delivery of health care services but also the interactional organization of video consultations. Future research should investigate systematically how the affordances of the technology, particularly the camera’s field of view, affect the norms regarding participation, quality of care, and participant satisfaction.

Meaning of the Study

Our findings suggest that when considering the feasibility of video consultations, some important considerations need to be taken into account. Video consulting has often only been considered a suitable service model for patients with technological competence and experience, where the goal of the consultation is expected to be relatively straightforward (eg, sharing test results and routine follow-up). However, our study shows that this unnecessarily limits to application of video for 2 reasons. First, where patients have a lack of experience with or have anxiety around technology, informal carers can help overcome technological or interactional difficulties. Furthermore, they offer reassurance, making patients comfortable with doing a video consultation. Help may not be needed, but where it would be needed, it would be available [ 76 ]. Second, where the goal of the consultation is more complex (eg, involves a physical assessment), video can still be an appropriate option if the patient has adequate support. Assessments in a video consultation often require the patient to move the camera around to frame themselves in a way that they are adequately visible to the clinician while performing movements that may be difficult for them to do safely or using devices that they are not familiar with (eg, oximeters). Copresent carers can overcome some of these challenges, for example, by taking care of the camera or laying hands on the patient, where patients are comfortable with that.

Since the outbreak of the COVID-19 pandemic, video consultations have become a more routinely used service model. While many patients and providers are moving back to in-person delivery of (health) care, hybrid service models that involve remote options, including video consultation, are likely to constitute the new normal. However, despite the routinization of video-consulting services, clinicians still have limited evidence on when they are a feasible and safe option. While the literature is growing quickly and many organizations have proposed guidelines, these often ignore the role of informal carers. Further rollout of this new service model needs to consider not only what patients themselves can do but also what informal carers can do. Given the important role that informal carers have in health care management, particularly for certain groups of patients (eg, young children, patients with high frailty, or patients who lack capacity), it is logical to assume that their role can be transferred to video-consulting models. The additional work for carers will have to be weighed against the potential benefits for each specific clinical context and each individual patient.

The importance of carers for making some video consultations work raises important questions for those providing and supporting services. Not all patients will have access to an informal carer, and those who have may not always want a carer to be present during the consultation. A systematic review found that patients are not necessarily as involved during consultations where they are accompanied by a carer, and while most patients say they appreciate having someone with them, they want to be able to decide whether a carer will be present during the consultation [ 77 ]. Patients should feel comfortable asking for their carer to leave the room at any point during a consultation. However, this might put an unnecessary burden on the patient. It may be necessary for clinicians to create opportunities to talk to the patient privately.

Strengths and Limitations

Physiotherapy consultations in our data set were conducted during the COVID-19 pandemic, with heart failure and diabetes consultations conducted before the pandemic when video consulting was not a routine service model and few patients, carers, or clinicians had experience with it. Given the uptake and learning around video consultations during the COVID-19 pandemic, it is possible that patients involved in heart failure and cancer consultations needed more support with the technology than they would now. The prepandemic data were also likely to involve early-adopter clinicians who were supportive of video consultations as a new service model. Furthermore, participants in our data set used mainly Skype (Microsoft Corporation) and FaceTime (Apple Inc), whereas video consultations now often take place on dedicated platforms such as Teams (Microsoft Corporation), Attend Anywhere, or AccuRx. Some of these platforms affect the opening of video consultations, with patients expected to join a virtual waiting room before joining the consultation with their clinician. In addition, we focused on the positive experiences of patients and carers, without actively considering whether and when clinical staff are receptive to carer involvement. Despite these limitations, we anticipate that many of our findings are transferable to current video-consulting services. Our use of methods focused on interaction and communication has enabled us to demonstrate in detail the active role that carers played in some video consultations. While the exact role of carers may differ during and after the COVID-19 pandemic, it is highly likely that some patients (eg, older patients, those experiencing frailty, or those with multimorbidity) will continue to need assistance.

To our knowledge, this study is the first to use robust methods for analyzing communication in triadic video consultations (ie, among clinician, patient, and informal carer) across multiple clinical settings. Doing so has allowed us to show in detail not only that carers play a vital role in making video consulting work but also how they go about doing this. Our work adds to the existing literature by highlighting the interactional complexity of these consultations, demonstrating the sociotechnical nature of the work undertaken by informal carers, and underscoring the importance of focusing on the microlevel organization of consultations where carers are (and are not) involved [ 46 , 50 ]. Our work was exploratory in nature, relying on secondary analysis; future studies could investigate how the presence of carers affects the overall experience of patients and clinical staff with health care services, the patient-carer relationship, and the health outcomes for patients.

Conclusions

Video consulting remains a viable service option but depends on patient access to technology and their ability to use it. While many patients can manage a video consultation on their own, some (continue to) require assistance. In these circumstances, informal carers can play a unique, and often invisible, role in making video consultations work. To date, research and guidelines have not adequately considered the work of informal carers. This urgently needs addressing, not only to support the policy vision of the spread of video-consulting services but also to make visible and enable the informal carers (and the patients and clinicians they support) in this often vital role.

Acknowledgments

The authors are grateful to Marissa Bird and Joe Wherton for commenting on an earlier draft of this paper. The authors would like to thank Joe Wherton, Chrysanthi Papoutsi, Trish Greenhalgh, Christine A’Court, Gita Ramdharry, Anthony Gilbert, and Jackie Walumbe for their support in collecting the data used in this paper. This project was funded by UK Research and Innovation via the Economic and Social Research Council (ES/V010069/1), Wellcome Trust (WT104830MA), National Institute for Health Research (NIHR) Biomedical Research Centre (BRC-1215-20008), and the NIHR under its Research for Patient Benefit (PB-PG-1216-20012) and Policy Research Programme (grant NIHR202067). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Data Availability

The data sets generated and analyzed during this study are not publicly available due to confidentiality and sensitivity of the material but are available from the corresponding author on reasonable request.

Authors' Contributions

LMS was the principal investigator for this study and led data collection and formal analysis and wrote the first draft of the manuscript. SS provided supervision as a co–principal investigator and supported the review and editing of the manuscript. Both authors were involved in all aspects of the study design and funding acquisition and have reviewed and approved the final manuscript.

Conflicts of Interest

None declared.

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Abbreviations

Edited by T de Azevedo Cardoso; submitted 08.08.23; peer-reviewed by P Traulsen, G Gauhe, T Halkowski, S White; comments to author 06.10.23; revised version received 24.11.23; accepted 19.04.24; published 31.05.24.

©Lucas Martinus Seuren, Sara Shaw. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.05.2024.

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