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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.

Align your conclusion’s tone with the rest of your research paper. Start Writing with Paperpal Now!  

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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• 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 The Conclusion Chapter

The what, why & how explained simply (with examples).

By: Jenna Crossley (PhD Cand). Reviewed By: Dr. Eunice Rautenbach | September 2021

So, you’ve wrapped up your results and discussion chapters, and you’re finally on the home stretch – the conclusion chapter . In this post, we’ll discuss everything you need to know to craft a high-quality conclusion chapter for your dissertation or thesis project.

Overview: Dissertation Conclusion Chapter

• What the thesis/dissertation conclusion chapter is
• What to include in your conclusion chapter
• How to structure and write up your conclusion chapter
• A few tips  to help you ace the chapter

What exactly is the conclusion chapter?

The conclusion chapter is typically the final major chapter of a dissertation or thesis. As such, it serves as a concluding summary of your research findings and wraps up the document. While some publications such as journal articles and research reports combine the discussion and conclusion sections, these are typically separate chapters in a dissertation or thesis. As always, be sure to check what your university’s structural preference is before you start writing up these chapters.

So, what’s the difference between the discussion and the conclusion chapter?

Well, the two chapters are quite similar , as they both discuss the key findings of the study. However, the conclusion chapter is typically more general and high-level in nature. In your discussion chapter, you’ll typically discuss the intricate details of your study, but in your conclusion chapter, you’ll take a   broader perspective, reporting on the main research outcomes and how these addressed your research aim (or aims) .

A core function of the conclusion chapter is to synthesise all major points covered in your study and to tell the reader what they should take away from your work. Basically, you need to tell them what you found , why it’s valuable , how it can be applied , and what further research can be done.

Whatever you do, don’t just copy and paste what you’ve written in your discussion chapter! The conclusion chapter should not be a simple rehash of the discussion chapter. While the two chapters are similar, they have distinctly different functions.  

What should I include in the conclusion chapter?

To understand what needs to go into your conclusion chapter, it’s useful to understand what the chapter needs to achieve. In general, a good dissertation conclusion chapter should achieve the following:

• Summarise the key findings of the study
• Explicitly answer the research question(s) and address the research aims
• Inform the reader of the study’s main contributions
• Discuss any limitations or weaknesses of the study
• Present recommendations for future research

Therefore, your conclusion chapter needs to cover these core components. Importantly, you need to be careful not to include any new findings or data points. Your conclusion chapter should be based purely on data and analysis findings that you’ve already presented in the earlier chapters. If there’s a new point you want to introduce, you’ll need to go back to your results and discussion chapters to weave the foundation in there.

In many cases, readers will jump from the introduction chapter directly to the conclusions chapter to get a quick overview of the study’s purpose and key findings. Therefore, when you write up your conclusion chapter, it’s useful to assume that the reader hasn’t consumed the inner chapters of your dissertation or thesis. In other words, craft your conclusion chapter such that there’s a strong connection and smooth flow between the introduction and conclusion chapters, even though they’re on opposite ends of your document.

Need a helping hand?

How to write the conclusion chapter

Now that you have a clearer view of what the conclusion chapter is about, let’s break down the structure of this chapter so that you can get writing. Keep in mind that this is merely a typical structure – it’s not set in stone or universal. Some universities will prefer that you cover some of these points in the discussion chapter , or that you cover the points at different levels in different chapters.

Step 1: Craft a brief introduction section

As with all chapters in your dissertation or thesis, the conclusions chapter needs to start with a brief introduction. In this introductory section, you’ll want to tell the reader what they can expect to find in the chapter, and in what order . Here’s an example of what this might look like:

This chapter will conclude the study by summarising the key research findings in relation to the research aims and questions and discussing the value and contribution thereof. It will also review the limitations of the study and propose opportunities for future research.

Importantly, the objective here is just to give the reader a taste of what’s to come (a roadmap of sorts), not a summary of the chapter. So, keep it short and sweet – a paragraph or two should be ample.

Step 2: Discuss the overall findings in relation to the research aims

The next step in writing your conclusions chapter is to discuss the overall findings of your study , as they relate to the research aims and research questions . You would have likely covered similar ground in the discussion chapter, so it’s important to zoom out a little bit here and focus on the broader findings – specifically, how these help address the research aims .

In practical terms, it’s useful to start this section by reminding your reader of your research aims and research questions, so that the findings are well contextualised. In this section, phrases such as, “This study aimed to…” and “the results indicate that…” will likely come in handy. For example, you could say something like the following:

This study aimed to investigate the feeding habits of the naked mole-rat. The results indicate that naked mole rats feed on underground roots and tubers. Further findings show that these creatures eat only a part of the plant, leaving essential parts to ensure long-term food stability.

Be careful not to make overly bold claims here. Avoid claims such as “this study proves that” or “the findings disprove existing the existing theory”. It’s seldom the case that a single study can prove or disprove something. Typically, this is achieved by a broader body of research, not a single study – especially not a dissertation or thesis which will inherently have significant  limitations . We’ll discuss those limitations a little later.

Step 3: Discuss how your study contributes to the field

Next, you’ll need to discuss how your research has contributed to the field – both in terms of theory and practice . This involves talking about what you achieved in your study, highlighting why this is important and valuable, and how it can be used or applied.

In this section you’ll want to:

• Mention any research outputs created as a result of your study (e.g., articles, publications, etc.)
• Inform the reader on just how your research solves your research problem , and why that matters
• Reflect on gaps in the existing research and discuss how your study contributes towards addressing these gaps
• Discuss your study in relation to relevant theories . For example, does it confirm these theories or constructively challenge them?
• Discuss how your research findings can be applied in the real world . For example, what specific actions can practitioners take, based on your findings?

Be careful to strike a careful balance between being firm but humble in your arguments here. It’s unlikely that your one study will fundamentally change paradigms or shake up the discipline, so making claims to this effect will be frowned upon . At the same time though, you need to present your arguments with confidence, firmly asserting the contribution your research has made, however small that contribution may be. Simply put, you need to keep it balanced .

Step 4: Reflect on the limitations of your study

Now that you’ve pumped your research up, the next step is to critically reflect on the limitations and potential shortcomings of your study. You may have already covered this in the discussion chapter, depending on your university’s structural preferences, so be careful not to repeat yourself unnecessarily.

There are many potential limitations that can apply to any given study. Some common ones include:

• Sampling issues that reduce the generalisability of the findings (e.g., non-probability sampling )
• Insufficient sample size (e.g., not getting enough survey responses ) or limited data access
• Low-resolution data collection or analysis techniques
• Researcher bias or lack of experience
• Lack of access to research equipment
• Time constraints that limit the methodology (e.g. cross-sectional vs longitudinal time horizon)
• Budget constraints that limit various aspects of the study

Discussing the limitations of your research may feel self-defeating (no one wants to highlight their weaknesses, right), but it’s a critical component of high-quality research. It’s important to appreciate that all studies have limitations (even well-funded studies by expert researchers) – therefore acknowledging these limitations adds credibility to your research by showing that you understand the limitations of your research design .

That being said, keep an eye on your wording and make sure that you don’t undermine your research . It’s important to strike a balance between recognising the limitations, but also highlighting the value of your research despite those limitations. Show the reader that you understand the limitations, that these were justified given your constraints, and that you know how they can be improved upon – this will get you marks.

Next, you’ll need to make recommendations for future studies. This will largely be built on the limitations you just discussed. For example, if one of your study’s weaknesses was related to a specific data collection or analysis method, you can make a recommendation that future researchers undertake similar research using a more sophisticated method.

Another potential source of future research recommendations is any data points or analysis findings that were interesting or surprising , but not directly related to your study’s research aims and research questions. So, if you observed anything that “stood out” in your analysis, but you didn’t explore it in your discussion (due to a lack of relevance to your research aims), you can earmark that for further exploration in this section.

Essentially, this section is an opportunity to outline how other researchers can build on your study to take the research further and help develop the body of knowledge. So, think carefully about the new questions that your study has raised, and clearly outline these for future researchers to pick up on.

Step 6: Wrap up with a closing summary

Quick tips for a top-notch conclusion chapter

Now that we’ve covered the what , why and how of the conclusion chapter, here are some quick tips and suggestions to help you craft a rock-solid conclusion.

• Don’t ramble . The conclusion chapter usually consumes 5-7% of the total word count (although this will vary between universities), so you need to be concise. Edit this chapter thoroughly with a focus on brevity and clarity.
• Be very careful about the claims you make in terms of your study’s contribution. Nothing will make the marker’s eyes roll back faster than exaggerated or unfounded claims. Be humble but firm in your claim-making.
• Use clear and simple language that can be easily understood by an intelligent layman. Remember that not every reader will be an expert in your field, so it’s important to make your writing accessible. Bear in mind that no one knows your research better than you do, so it’s important to spell things out clearly for readers.

Hopefully, this post has given you some direction and confidence to take on the conclusion chapter of your dissertation or thesis with confidence. If you’re still feeling a little shaky and need a helping hand, consider booking a free initial consultation with a friendly Grad Coach to discuss how we can help you with hands-on, private coaching.

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17 Comments

Really you team are doing great!

Your guide on writing the concluding chapter of a research is really informative especially to the beginners who really do not know where to start. Im now ready to start. Keep it up guys

Really your team are doing great!

Very helpful guidelines, timely saved. Thanks so much for the tips.

This post was very helpful and informative. Thank you team.

A very enjoyable, understandable and crisp presentation on how to write a conclusion chapter. I thoroughly enjoyed it. Thanks Jenna.

This was a very helpful article which really gave me practical pointers for my concluding chapter. Keep doing what you are doing! It meant a lot to me to be able to have this guide. Thank you so much.

Nice content dealing with the conclusion chapter, it’s a relief after the streneous task of completing discussion part.Thanks for valuable guidance

Thanks for your guidance

I get all my doubts clarified regarding the conclusion chapter. It’s really amazing. Many thanks.

Very helpful tips. Thanks so much for the guidance

Thank you very much for this piece. It offers a very helpful starting point in writing the conclusion chapter of my thesis.

It’s awesome! Most useful and timely too. Thanks a million times

Bundle of thanks for your guidance. It was greatly helpful.

Wonderful, clear, practical guidance. So grateful to read this as I conclude my research. Thank you.

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• Writing Tips

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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How to write a strong conclusion for your research paper

Last updated

17 February 2024

Reviewed by

Writing a research paper is a chance to share your knowledge and hypothesis. It's an opportunity to demonstrate your many hours of research and prove your ability to write convincingly.

Ideally, by the end of your research paper, you'll have brought your readers on a journey to reach the conclusions you've pre-determined. However, if you don't stick the landing with a good conclusion, you'll risk losing your reader’s trust.

Writing a strong conclusion for your research paper involves a few important steps, including restating the thesis and summing up everything properly.

Find out what to include and what to avoid, so you can effectively demonstrate your understanding of the topic and prove your expertise.

• Why is a good conclusion important?

A good conclusion can cement your paper in the reader’s mind. Making a strong impression in your introduction can draw your readers in, but it's the conclusion that will inspire them.

• What to include in a research paper conclusion

There are a few specifics you should include in your research paper conclusion. Offer your readers some sense of urgency or consequence by pointing out why they should care about the topic you have covered. Discuss any common problems associated with your topic and provide suggestions as to how these problems can be solved or addressed.

The conclusion should include a restatement of your initial thesis. Thesis statements are strengthened after you’ve presented supporting evidence (as you will have done in the paper), so make a point to reintroduce it at the end.

Finally, recap the main points of your research paper, highlighting the key takeaways you want readers to remember. If you've made multiple points throughout the paper, refer to the ones with the strongest supporting evidence.

• Steps for writing a research paper conclusion

Many writers find the conclusion the most challenging part of any research project . By following these three steps, you'll be prepared to write a conclusion that is effective and concise.

• Step 1: Restate the problem

Always begin by restating the research problem in the conclusion of a research paper. This serves to remind the reader of your hypothesis and refresh them on the main point of the paper. 

When restating the problem, take care to avoid using exactly the same words you employed earlier in the paper.

• Step 2: Sum up the paper

After you've restated the problem, sum up the paper by revealing your overall findings. The method for this differs slightly, depending on whether you're crafting an argumentative paper or an empirical paper.

Argumentative paper: Restate your thesis and arguments

Argumentative papers involve introducing a thesis statement early on. In crafting the conclusion for an argumentative paper, always restate the thesis, outlining the way you've developed it throughout the entire paper.

It might be appropriate to mention any counterarguments in the conclusion, so you can demonstrate how your thesis is correct or how the data best supports your main points.

Empirical paper: Summarize research findings

Empirical papers break down a series of research questions. In your conclusion, discuss the findings your research revealed, including any information that surprised you.

Be clear about the conclusions you reached, and explain whether or not you expected to arrive at these particular ones.

• Step 3: Discuss the implications of your research

Argumentative papers and empirical papers also differ in this part of a research paper conclusion. Here are some tips on crafting conclusions for argumentative and empirical papers.

Argumentative paper: Powerful closing statement

In an argumentative paper, you'll have spent a great deal of time expressing the opinions you formed after doing a significant amount of research. Make a strong closing statement in your argumentative paper's conclusion to share the significance of your work.

You can outline the next steps through a bold call to action, or restate how powerful your ideas turned out to be.

Empirical paper: Directions for future research

Empirical papers are broader in scope. They usually cover a variety of aspects and can include several points of view.

To write a good conclusion for an empirical paper, suggest the type of research that could be done in the future, including methods for further investigation or outlining ways other researchers might proceed.

If you feel your research had any limitations, even if they were outside your control, you could mention these in your conclusion.

After you finish outlining your conclusion, ask someone to read it and offer feedback. In any research project you're especially close to, it can be hard to identify problem areas. Having a close friend or someone whose opinion you value read the research paper and provide honest feedback can be invaluable. Take note of any suggested edits and consider incorporating them into your paper if they make sense.

• Things to avoid in a research paper conclusion

Keep these aspects to avoid in mind as you're writing your conclusion and refer to them after you've created an outline.

Dry summary

Writing a memorable, succinct conclusion is arguably more important than a strong introduction. Take care to avoid just rephrasing your main points, and don't fall into the trap of repeating dry facts or citations.

You can provide a new perspective for your readers to think about or contextualize your research. Either way, make the conclusion vibrant and interesting, rather than a rote recitation of your research paper’s highlights.

Clichéd or generic phrasing

Your research paper conclusion should feel fresh and inspiring. Avoid generic phrases like "to sum up" or "in conclusion." These phrases tend to be overused, especially in an academic context and might turn your readers off.

The conclusion also isn't the time to introduce colloquial phrases or informal language. Retain a professional, confident tone consistent throughout your paper’s conclusion so it feels exciting and bold.

New data or evidence

While you should present strong data throughout your paper, the conclusion isn't the place to introduce new evidence. This is because readers are engaged in actively learning as they read through the body of your paper.

By the time they reach the conclusion, they will have formed an opinion one way or the other (hopefully in your favor!). Introducing new evidence in the conclusion will only serve to surprise or frustrate your reader.

Ignoring contradictory evidence

If your research reveals contradictory evidence, don't ignore it in the conclusion. This will damage your credibility as an expert and might even serve to highlight the contradictions.

Be as transparent as possible and admit to any shortcomings in your research, but don't dwell on them for too long.

Ambiguous or unclear resolutions

The point of a research paper conclusion is to provide closure and bring all your ideas together. You should wrap up any arguments you introduced in the paper and tie up any loose ends, while demonstrating why your research and data are strong.

Use direct language in your conclusion and avoid ambiguity. Even if some of the data and sources you cite are inconclusive or contradictory, note this in your conclusion to come across as confident and trustworthy.

• Examples of research paper conclusions

Your research paper should provide a compelling close to the paper as a whole, highlighting your research and hard work. While the conclusion should represent your unique style, these examples offer a starting point:

Ultimately, the data we examined all point to the same conclusion: Encouraging a good work-life balance improves employee productivity and benefits the company overall. The research suggests that when employees feel their personal lives are valued and respected by their employers, they are more likely to be productive when at work. In addition, company turnover tends to be reduced when employees have a balance between their personal and professional lives. While additional research is required to establish ways companies can support employees in creating a stronger work-life balance, it's clear the need is there.

Social media is a primary method of communication among young people. As we've seen in the data presented, most young people in high school use a variety of social media applications at least every hour, including Instagram and Facebook. While social media is an avenue for connection with peers, research increasingly suggests that social media use correlates with body image issues. Young girls with lower self-esteem tend to use social media more often than those who don't log onto social media apps every day. As new applications continue to gain popularity, and as more high school students are given smartphones, more research will be required to measure the effects of prolonged social media use.

What are the different kinds of research paper conclusions?

There are no formal types of research paper conclusions. Ultimately, the conclusion depends on the outline of your paper and the type of research you’re presenting. While some experts note that research papers can end with a new perspective or commentary, most papers should conclude with a combination of both. The most important aspect of a good research paper conclusion is that it accurately represents the body of the paper.

Can I present new arguments in my research paper conclusion?

Research paper conclusions are not the place to introduce new data or arguments. The body of your paper is where you should share research and insights, where the reader is actively absorbing the content. By the time a reader reaches the conclusion of the research paper, they should have formed their opinion. Introducing new arguments in the conclusion can take a reader by surprise, and not in a positive way. It might also serve to frustrate readers.

How long should a research paper conclusion be?

There's no set length for a research paper conclusion. However, it's a good idea not to run on too long, since conclusions are supposed to be succinct. A good rule of thumb is to keep your conclusion around 5 to 10 percent of the paper's total length. If your paper is 10 pages, try to keep your conclusion under one page.

What should I include in a research paper conclusion?

A good research paper conclusion should always include a sense of urgency, so the reader can see how and why the topic should matter to them. You can also note some recommended actions to help fix the problem and some obstacles they might encounter. A conclusion should also remind the reader of the thesis statement, along with the main points you covered in the paper. At the end of the conclusion, add a powerful closing statement that helps cement the paper in the mind of the reader.

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

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

The results section is where you report the findings of your study based upon the methodology [or methodologies] you applied to gather information. The results section should state the findings of the research arranged in a logical sequence without bias or interpretation. A section describing results should be particularly detailed if your paper includes data generated from your own research.

Annesley, Thomas M. "Show Your Cards: The Results Section and the Poker Game." Clinical Chemistry 56 (July 2010): 1066-1070.

Importance of a Good Results Section

When formulating the results section, it's important to remember that the results of a study do not prove anything . Findings can only confirm or reject the hypothesis underpinning your study. However, the act of articulating the results helps you to understand the problem from within, to break it into pieces, and to view the research problem from various perspectives.

The page length of this section is set by the amount and types of data to be reported . Be concise. Use non-textual elements appropriately, such as figures and tables, to present findings more effectively. In deciding what data to describe in your results section, you must clearly distinguish information that would normally be included in a research paper from any raw data or other content that could be included as an appendix. In general, raw data that has not been summarized should not be included in the main text of your paper unless requested to do so by your professor.

Avoid providing data that is not critical to answering the research question . The background information you described in the introduction section should provide the reader with any additional context or explanation needed to understand the results. A good strategy is to always re-read the background section of your paper after you have written up your results to ensure that the reader has enough context to understand the results [and, later, how you interpreted the results in the discussion section of your paper that follows].

Bavdekar, Sandeep B. and Sneha Chandak. "Results: Unraveling the Findings." Journal of the Association of Physicians of India 63 (September 2015): 44-46; Brett, Paul. "A Genre Analysis of the Results Section of Sociology Articles." English for Specific Speakers 13 (1994): 47-59; Go to English for Specific Purposes on ScienceDirect;Burton, Neil et al. Doing Your Education Research Project . Los Angeles, CA: SAGE, 2008; Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Kretchmer, Paul. Twelve Steps to Writing an Effective Results Section. San Francisco Edit; "Reporting Findings." In Making Sense of Social Research Malcolm Williams, editor. (London;: SAGE Publications, 2003) pp. 188-207.

Structure and Writing Style

I.  Organization and Approach

For most research papers in the social and behavioral sciences, there are two possible ways of organizing the results . Both approaches are appropriate in how you report your findings, but use only one approach.

• Present a synopsis of the results followed by an explanation of key findings . This approach can be used to highlight important findings. For example, you may have noticed an unusual correlation between two variables during the analysis of your findings. It is appropriate to highlight this finding in the results section. However, speculating as to why this correlation exists and offering a hypothesis about what may be happening belongs in the discussion section of your paper.
• Present a result and then explain it, before presenting the next result then explaining it, and so on, then end with an overall synopsis . This is the preferred approach if you have multiple results of equal significance. It is more common in longer papers because it helps the reader to better understand each finding. In this model, it is helpful to provide a brief conclusion that ties each of the findings together and provides a narrative bridge to the discussion section of the your paper.

NOTE :   Just as the literature review should be arranged under conceptual categories rather than systematically describing each source, you should also organize your findings under key themes related to addressing the research problem. This can be done under either format noted above [i.e., a thorough explanation of the key results or a sequential, thematic description and explanation of each finding].

II.  Content

In general, the content of your results section should include the following:

• Introductory context for understanding the results by restating the research problem underpinning your study . This is useful in re-orientating the reader's focus back to the research problem after having read a review of the literature and your explanation of the methods used for gathering and analyzing information.
• Inclusion of non-textual elements, such as, figures, charts, photos, maps, tables, etc. to further illustrate key findings, if appropriate . Rather than relying entirely on descriptive text, consider how your findings can be presented visually. This is a helpful way of condensing a lot of data into one place that can then be referred to in the text. Consider referring to appendices if there is a lot of non-textual elements.
• A systematic description of your results, highlighting for the reader observations that are most relevant to the topic under investigation . Not all results that emerge from the methodology used to gather information may be related to answering the " So What? " question. Do not confuse observations with interpretations; observations in this context refers to highlighting important findings you discovered through a process of reviewing prior literature and gathering data.
• The page length of your results section is guided by the amount and types of data to be reported . However, focus on findings that are important and related to addressing the research problem. It is not uncommon to have unanticipated results that are not relevant to answering the research question. This is not to say that you don't acknowledge tangential findings and, in fact, can be referred to as areas for further research in the conclusion of your paper. However, spending time in the results section describing tangential findings clutters your overall results section and distracts the reader.
• A short paragraph that concludes the results section by synthesizing the key findings of the study . Highlight the most important findings you want readers to remember as they transition into the discussion section. This is particularly important if, for example, there are many results to report, the findings are complicated or unanticipated, or they are impactful or actionable in some way [i.e., able to be pursued in a feasible way applied to practice].

NOTE:   Always use the past tense when referring to your study's findings. Reference to findings should always be described as having already happened because the method used to gather the information has been completed.

III.  Problems to Avoid

When writing the results section, avoid doing the following :

• Discussing or interpreting your results . Save this for the discussion section of your paper, although where appropriate, you should compare or contrast specific results to those found in other studies [e.g., "Similar to the work of Smith [1990], one of the findings of this study is the strong correlation between motivation and academic achievement...."].
• Reporting background information or attempting to explain your findings. This should have been done in your introduction section, but don't panic! Often the results of a study point to the need for additional background information or to explain the topic further, so don't think you did something wrong. Writing up research is rarely a linear process. Always revise your introduction as needed.
• Ignoring negative results . A negative result generally refers to a finding that does not support the underlying assumptions of your study. Do not ignore them. Document these findings and then state in your discussion section why you believe a negative result emerged from your study. Note that negative results, and how you handle them, can give you an opportunity to write a more engaging discussion section, therefore, don't be hesitant to highlight them.
• Including raw data or intermediate calculations . Ask your professor if you need to include any raw data generated by your study, such as transcripts from interviews or data files. If raw data is to be included, place it in an appendix or set of appendices that are referred to in the text.
• Be as factual and concise as possible in reporting your findings . Do not use phrases that are vague or non-specific, such as, "appeared to be greater than other variables..." or "demonstrates promising trends that...." Subjective modifiers should be explained in the discussion section of the paper [i.e., why did one variable appear greater? Or, how does the finding demonstrate a promising trend?].
• Presenting the same data or repeating the same information more than once . If you want to highlight a particular finding, it is appropriate to do so in the results section. However, you should emphasize its significance in relation to addressing the research problem in the discussion section. Do not repeat it in your results section because you can do that in the conclusion of your paper.
• Confusing figures with tables . Be sure to properly label any non-textual elements in your paper. Don't call a chart an illustration or a figure a table. If you are not sure, go here .

Annesley, Thomas M. "Show Your Cards: The Results Section and the Poker Game." Clinical Chemistry 56 (July 2010): 1066-1070; Bavdekar, Sandeep B. and Sneha Chandak. "Results: Unraveling the Findings." Journal of the Association of Physicians of India 63 (September 2015): 44-46; Burton, Neil et al. Doing Your Education Research Project . Los Angeles, CA: SAGE, 2008;  Caprette, David R. Writing Research Papers. Experimental Biosciences Resources. Rice University; Hancock, Dawson R. and Bob Algozzine. Doing Case Study Research: A Practical Guide for Beginning Researchers . 2nd ed. New York: Teachers College Press, 2011; Introduction to Nursing Research: Reporting Research Findings. Nursing Research: Open Access Nursing Research and Review Articles. (January 4, 2012); Kretchmer, Paul. Twelve Steps to Writing an Effective Results Section. San Francisco Edit ; Ng, K. H. and W. C. Peh. "Writing the Results." Singapore Medical Journal 49 (2008): 967-968; Reporting Research Findings. Wilder Research, in partnership with the Minnesota Department of Human Services. (February 2009); Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Schafer, Mickey S. Writing the Results. Thesis Writing in the Sciences. Course Syllabus. University of Florida.

Writing Tip

Why Don't I Just Combine the Results Section with the Discussion Section?

It's not unusual to find articles in scholarly social science journals where the author(s) have combined a description of the findings with a discussion about their significance and implications. You could do this. However, if you are inexperienced writing research papers, consider creating two distinct sections for each section in your paper as a way to better organize your thoughts and, by extension, your paper. Think of the results section as the place where you report what your study found; think of the discussion section as the place where you interpret the information and answer the "So What?" question. As you become more skilled writing research papers, you can consider melding the results of your study with a discussion of its implications.

Driscoll, Dana Lynn and Aleksandra Kasztalska. Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

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• Last Updated: May 7, 2024 9:40 AM
• URL: https://libguides.usc.edu/writingguide

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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Home » Research Results Section – Writing Guide and Examples

Research Results Section – Writing Guide and Examples

Table of Contents

Research Results

Research results refer to the findings and conclusions derived from a systematic investigation or study conducted to answer a specific question or hypothesis. These results are typically presented in a written report or paper and can include various forms of data such as numerical data, qualitative data, statistics, charts, graphs, and visual aids.

Results Section in Research

The results section of the research paper presents the findings of the study. It is the part of the paper where the researcher reports the data collected during the study and analyzes it to draw conclusions.

In the results section, the researcher should describe the data that was collected, the statistical analysis performed, and the findings of the study. It is important to be objective and not interpret the data in this section. Instead, the researcher should report the data as accurately and objectively as possible.

Structure of Research Results Section

The structure of the research results section can vary depending on the type of research conducted, but in general, it should contain the following components:

• Introduction: The introduction should provide an overview of the study, its aims, and its research questions. It should also briefly explain the methodology used to conduct the study.
• Data presentation : This section presents the data collected during the study. It may include tables, graphs, or other visual aids to help readers better understand the data. The data presented should be organized in a logical and coherent way, with headings and subheadings used to help guide the reader.
• Data analysis: In this section, the data presented in the previous section are analyzed and interpreted. The statistical tests used to analyze the data should be clearly explained, and the results of the tests should be presented in a way that is easy to understand.
• Discussion of results : This section should provide an interpretation of the results of the study, including a discussion of any unexpected findings. The discussion should also address the study’s research questions and explain how the results contribute to the field of study.
• Limitations: This section should acknowledge any limitations of the study, such as sample size, data collection methods, or other factors that may have influenced the results.
• Conclusions: The conclusions should summarize the main findings of the study and provide a final interpretation of the results. The conclusions should also address the study’s research questions and explain how the results contribute to the field of study.
• Recommendations : This section may provide recommendations for future research based on the study’s findings. It may also suggest practical applications for the study’s results in real-world settings.

Outline of Research Results Section

The following is an outline of the key components typically included in the Results section:

I. Introduction

• A brief overview of the research objectives and hypotheses
• A statement of the research question

II. Descriptive statistics

• Summary statistics (e.g., mean, standard deviation) for each variable analyzed
• Frequencies and percentages for categorical variables

III. Inferential statistics

• Results of statistical analyses, including tests of hypotheses
• Tables or figures to display statistical results

IV. Effect sizes and confidence intervals

• Effect sizes (e.g., Cohen’s d, odds ratio) to quantify the strength of the relationship between variables
• Confidence intervals to estimate the range of plausible values for the effect size

V. Subgroup analyses

• Results of analyses that examined differences between subgroups (e.g., by gender, age, treatment group)

VI. Limitations and assumptions

• Discussion of any limitations of the study and potential sources of bias
• Assumptions made in the statistical analyses

VII. Conclusions

• A summary of the key findings and their implications
• A statement of whether the hypotheses were supported or not
• Suggestions for future research

Example of Research Results Section

An Example of a Research Results Section could be:

• This study sought to examine the relationship between sleep quality and academic performance in college students.
• Hypothesis : College students who report better sleep quality will have higher GPAs than those who report poor sleep quality.
• Methodology : Participants completed a survey about their sleep habits and academic performance.

II. Participants

• Participants were college students (N=200) from a mid-sized public university in the United States.
• The sample was evenly split by gender (50% female, 50% male) and predominantly white (85%).
• Participants were recruited through flyers and online advertisements.

III. Results

• Participants who reported better sleep quality had significantly higher GPAs (M=3.5, SD=0.5) than those who reported poor sleep quality (M=2.9, SD=0.6).
• See Table 1 for a summary of the results.
• Participants who reported consistent sleep schedules had higher GPAs than those with irregular sleep schedules.

IV. Discussion

• The results support the hypothesis that better sleep quality is associated with higher academic performance in college students.
• These findings have implications for college students, as prioritizing sleep could lead to better academic outcomes.
• Limitations of the study include self-reported data and the lack of control for other variables that could impact academic performance.

V. Conclusion

• College students who prioritize sleep may see a positive impact on their academic performance.
• These findings highlight the importance of sleep in academic success.
• Future research could explore interventions to improve sleep quality in college students.

Example of Research Results in Research Paper :

Our study aimed to compare the performance of three different machine learning algorithms (Random Forest, Support Vector Machine, and Neural Network) in predicting customer churn in a telecommunications company. We collected a dataset of 10,000 customer records, with 20 predictor variables and a binary churn outcome variable.

Our analysis revealed that all three algorithms performed well in predicting customer churn, with an overall accuracy of 85%. However, the Random Forest algorithm showed the highest accuracy (88%), followed by the Support Vector Machine (86%) and the Neural Network (84%).

Furthermore, we found that the most important predictor variables for customer churn were monthly charges, contract type, and tenure. Random Forest identified monthly charges as the most important variable, while Support Vector Machine and Neural Network identified contract type as the most important.

Overall, our results suggest that machine learning algorithms can be effective in predicting customer churn in a telecommunications company, and that Random Forest is the most accurate algorithm for this task.

Example 3 :

Title : The Impact of Social Media on Body Image and Self-Esteem

Abstract : This study aimed to investigate the relationship between social media use, body image, and self-esteem among young adults. A total of 200 participants were recruited from a university and completed self-report measures of social media use, body image satisfaction, and self-esteem.

Results: The results showed that social media use was significantly associated with body image dissatisfaction and lower self-esteem. Specifically, participants who reported spending more time on social media platforms had lower levels of body image satisfaction and self-esteem compared to those who reported less social media use. Moreover, the study found that comparing oneself to others on social media was a significant predictor of body image dissatisfaction and lower self-esteem.

Conclusion : These results suggest that social media use can have negative effects on body image satisfaction and self-esteem among young adults. It is important for individuals to be mindful of their social media use and to recognize the potential negative impact it can have on their mental health. Furthermore, interventions aimed at promoting positive body image and self-esteem should take into account the role of social media in shaping these attitudes and behaviors.

Importance of Research Results

Research results are important for several reasons, including:

• Advancing knowledge: Research results can contribute to the advancement of knowledge in a particular field, whether it be in science, technology, medicine, social sciences, or humanities.
• Developing theories: Research results can help to develop or modify existing theories and create new ones.
• Improving practices: Research results can inform and improve practices in various fields, such as education, healthcare, business, and public policy.
• Identifying problems and solutions: Research results can identify problems and provide solutions to complex issues in society, including issues related to health, environment, social justice, and economics.
• Validating claims : Research results can validate or refute claims made by individuals or groups in society, such as politicians, corporations, or activists.
• Providing evidence: Research results can provide evidence to support decision-making, policy-making, and resource allocation in various fields.

How to Write Results in A Research Paper

Here are some general guidelines on how to write results in a research paper:

• Organize the results section: Start by organizing the results section in a logical and coherent manner. Divide the section into subsections if necessary, based on the research questions or hypotheses.
• Present the findings: Present the findings in a clear and concise manner. Use tables, graphs, and figures to illustrate the data and make the presentation more engaging.
• Describe the data: Describe the data in detail, including the sample size, response rate, and any missing data. Provide relevant descriptive statistics such as means, standard deviations, and ranges.
• Interpret the findings: Interpret the findings in light of the research questions or hypotheses. Discuss the implications of the findings and the extent to which they support or contradict existing theories or previous research.
• Discuss the limitations : Discuss the limitations of the study, including any potential sources of bias or confounding factors that may have affected the results.
• Compare the results : Compare the results with those of previous studies or theoretical predictions. Discuss any similarities, differences, or inconsistencies.
• Avoid redundancy: Avoid repeating information that has already been presented in the introduction or methods sections. Instead, focus on presenting new and relevant information.
• Be objective: Be objective in presenting the results, avoiding any personal biases or interpretations.

When to Write Research Results

Here are situations When to Write Research Results”

• After conducting research on the chosen topic and obtaining relevant data, organize the findings in a structured format that accurately represents the information gathered.
• Once the data has been analyzed and interpreted, and conclusions have been drawn, begin the writing process.
• Before starting to write, ensure that the research results adhere to the guidelines and requirements of the intended audience, such as a scientific journal or academic conference.
• Begin by writing an abstract that briefly summarizes the research question, methodology, findings, and conclusions.
• Follow the abstract with an introduction that provides context for the research, explains its significance, and outlines the research question and objectives.
• The next section should be a literature review that provides an overview of existing research on the topic and highlights the gaps in knowledge that the current research seeks to address.
• The methodology section should provide a detailed explanation of the research design, including the sample size, data collection methods, and analytical techniques used.
• Present the research results in a clear and concise manner, using graphs, tables, and figures to illustrate the findings.
• Discuss the implications of the research results, including how they contribute to the existing body of knowledge on the topic and what further research is needed.
• Conclude the paper by summarizing the main findings, reiterating the significance of the research, and offering suggestions for future research.

Purpose of Research Results

The purposes of Research Results are as follows:

• Informing policy and practice: Research results can provide evidence-based information to inform policy decisions, such as in the fields of healthcare, education, and environmental regulation. They can also inform best practices in fields such as business, engineering, and social work.
• Addressing societal problems : Research results can be used to help address societal problems, such as reducing poverty, improving public health, and promoting social justice.
• Generating economic benefits : Research results can lead to the development of new products, services, and technologies that can create economic value and improve quality of life.
• Supporting academic and professional development : Research results can be used to support academic and professional development by providing opportunities for students, researchers, and practitioners to learn about new findings and methodologies in their field.
• Enhancing public understanding: Research results can help to educate the public about important issues and promote scientific literacy, leading to more informed decision-making and better public policy.
• Evaluating interventions: Research results can be used to evaluate the effectiveness of interventions, such as treatments, educational programs, and social policies. This can help to identify areas where improvements are needed and guide future interventions.
• Contributing to scientific progress: Research results can contribute to the advancement of science by providing new insights and discoveries that can lead to new theories, methods, and techniques.
• Informing decision-making : Research results can provide decision-makers with the information they need to make informed decisions. This can include decision-making at the individual, organizational, or governmental levels.
• Fostering collaboration : Research results can facilitate collaboration between researchers and practitioners, leading to new partnerships, interdisciplinary approaches, and innovative solutions to complex problems.

Advantages of Research Results

Some Advantages of Research Results are as follows:

• Improved decision-making: Research results can help inform decision-making in various fields, including medicine, business, and government. For example, research on the effectiveness of different treatments for a particular disease can help doctors make informed decisions about the best course of treatment for their patients.
• Innovation : Research results can lead to the development of new technologies, products, and services. For example, research on renewable energy sources can lead to the development of new and more efficient ways to harness renewable energy.
• Economic benefits: Research results can stimulate economic growth by providing new opportunities for businesses and entrepreneurs. For example, research on new materials or manufacturing techniques can lead to the development of new products and processes that can create new jobs and boost economic activity.
• Improved quality of life: Research results can contribute to improving the quality of life for individuals and society as a whole. For example, research on the causes of a particular disease can lead to the development of new treatments and cures, improving the health and well-being of millions of people.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Write a Research Paper Conclusion Section

What is a conclusion in a research paper?

The conclusion in a research paper is the final paragraph or two in a research paper. In scientific papers, the conclusion usually follows the Discussion section , summarizing the importance of the findings and reminding the reader why the work presented in the paper is relevant.

However, it can be a bit confusing to distinguish the conclusion section/paragraph from a summary or a repetition of your findings, your own opinion, or the statement of the implications of your work. In fact, the conclusion should contain a bit of all of these other parts but go beyond it—but not too far beyond! 

The structure and content of the conclusion section can also vary depending on whether you are writing a research manuscript or an essay. This article will explain how to write a good conclusion section, what exactly it should (and should not) contain, how it should be structured, and what you should avoid when writing it.  

Table of Contents:

What does a good conclusion section do, what to include in a research paper conclusion.

• Conclusion in an Essay
• Research Paper Conclusion 
• Conclusion Paragraph Outline and Example
• What Not to Do When Writing a Conclusion

The conclusion of a research paper has several key objectives. It should:

• Restate your research problem addressed in the introduction section
• Summarize your main arguments, important findings, and broader implications
• Synthesize key takeaways from your study

The specific content in the conclusion depends on whether your paper presents the results of original scientific research or constructs an argument through engagement with previously published sources.

You presented your general field of study to the reader in the introduction section, by moving from general information (the background of your work, often combined with a literature review ) to the rationale of your study and then to the specific problem or topic you addressed, formulated in the form of the statement of the problem in research or the thesis statement in an essay.

In the conclusion section, in contrast, your task is to move from your specific findings or arguments back to a more general depiction of how your research contributes to the readers’ understanding of a certain concept or helps solve a practical problem, or fills an important gap in the literature. The content of your conclusion section depends on the type of research you are doing and what type of paper you are writing. But whatever the outcome of your work is, the conclusion is where you briefly summarize it and place it within a larger context. It could be called the “take-home message” of the entire paper.

What to summarize in the conclusion

Your conclusion section needs to contain a very brief summary of your work , a very brief summary of the main findings of your work, and a mention of anything else that seems relevant when you now look at your work from a bigger perspective, even if it was not initially listed as one of your main research questions. This could be a limitation, for example, a problem with the design of your experiment that either needs to be considered when drawing any conclusions or that led you to ask a different question and therefore draw different conclusions at the end of your study (compared to when you started out).

Once you have reminded the reader of what you did and what you found, you need to go beyond that and also provide either your own opinion on why your work is relevant (and for whom, and how) or theoretical or practical implications of the study , or make a specific call for action if there is one to be made.   

How to Write an Essay Conclusion

Academic essays follow quite different structures than their counterparts in STEM and the natural sciences. Humanities papers often have conclusion sections that are much longer and contain more detail than scientific papers. There are three main types of academic essay conclusions.

Summarizing conclusion

The most typical conclusion at the end of an analytical/explanatory/argumentative essay is a summarizing conclusion . This is, as the name suggests, a clear summary of the main points of your topic and thesis. Since you might have gone through a number of different arguments or subtopics in the main part of your essay, you need to remind the reader again what those were, how they fit into each other, and how they helped you develop or corroborate your hypothesis.

For an essay that analyzes how recruiters can hire the best candidates in the shortest time or on “how starving yourself will increase your lifespan, according to science”, a summary of all the points you discussed might be all you need. Note that you should not exactly repeat what you said earlier, but rather highlight the essential details and present those to your reader in a different way. 

Externalizing conclusion

If you think that just reminding the reader of your main points is not enough, you can opt for an externalizing conclusion instead, that presents new points that were not presented in the paper so far. These new points can be additional facts and information or they can be ideas that are relevant to the topic and have not been mentioned before.

Such a conclusion can stimulate your readers to think about your topic or the implications of your analysis in a whole new way. For example, at the end of a historical analysis of a specific event or development, you could direct your reader’s attention to some current events that were not the topic of your essay but that provide a different context for your findings.

Editorial conclusion

In an editorial conclusion , another common type of conclusion that you will find at the end of papers and essays, you do not add new information but instead present your own experiences or opinions on the topic to round everything up. What makes this type of conclusion interesting is that you can choose to agree or disagree with the information you presented in your paper so far. For example, if you have collected and analyzed information on how a specific diet helps people lose weight, you can nevertheless have your doubts on the sustainability of that diet or its practicability in real life—if such arguments were not included in your original thesis and have therefore not been covered in the main part of your paper, the conclusion section is the place where you can get your opinion across.    

How to Conclude an Empirical Research Paper

An empirical research paper is usually more concise and succinct than an essay, because, if it is written well, it focuses on one specific question, describes the method that was used to answer that one question, describes and explains the results, and guides the reader in a logical way from the introduction to the discussion without going on tangents or digging into not absolutely relevant topics.

Summarize the findings

In a scientific paper, you should include a summary of the findings. Don’t go into great detail here (you will have presented your in-depth  results  and  discussion  already), but do clearly express the answers to the  research questions  you investigated.

Describe your main findings, even if they weren’t necessarily the ones anticipated, and explain the conclusion they led you to. Explain these findings in as few words as possible.

Instead of beginning with “ In conclusion, in this study, we investigated the effect of stress on the brain using fMRI …”, you should try to find a way to incorporate the repetition of the essential (and only the essential) details into the summary of the key points. “ The findings of this fMRI study on the effect of stress on the brain suggest that …” or “ While it has been known for a long time that stress has an effect on the brain, the findings of this fMRI study show that, surprisingly… ” would be better ways to start a conclusion. 

You should also not bring up new ideas or present new facts in the conclusion of a research paper, but stick to the background information you have presented earlier, to the findings you have already discussed, and the limitations and implications you have already described. The one thing you can add here is a practical recommendation that you haven’t clearly stated before—but even that one needs to follow logically from everything you have already discussed in the discussion section.

Discuss the implications

After summing up your key arguments or findings, conclude the paper by stating the broader implications of the research , whether in methods , approach, or findings. Express practical or theoretical takeaways from your paper. This often looks like a “call to action” or a final “sales pitch” that puts an exclamation point on your paper.

If your research topic is more theoretical in nature, your closing statement should express the significance of your argument—for example, in proposing a new understanding of a topic or laying the groundwork for future research.

Future research example

Future research into education standards should focus on establishing a more detailed picture of how novel pedagogical approaches impact young people’s ability to absorb new and difficult concepts. Moreover, observational studies are needed to gain more insight into how specific teaching models affect the retention of relationships and facts—for instance, how inquiry-based learning and its emphasis on lateral thinking can be used as a jumping-off point for more holistic classroom approaches.

Research Conclusion Example and Outline

Let’s revisit the study on the effect of stress on the brain we mentioned before and see what the common structure for a conclusion paragraph looks like, in three steps. Following these simple steps will make it easy for you to wrap everything up in one short paragraph that contains all the essential information: 

One: Short summary of what you did, but integrated into the summary of your findings:

While it has been known for a long time that stress has an effect on the brain, the findings of this fMRI study in 25 university students going through mid-term exams show that, surprisingly, one’s attitude to the experienced stress significantly modulates the brain’s response to it. 

Note that you don’t need to repeat any methodological or technical details here—the reader has been presented with all of these before, they have read your results section and the discussion of your results, and even (hopefully!) a discussion of the limitations and strengths of your paper. The only thing you need to remind them of here is the essential outcome of your work. 

Two: Add implications, and don’t forget to specify who this might be relevant for: 

Students could be considered a specific subsample of the general population, but earlier research shows that the effect that exam stress has on their physical and mental health is comparable to the effects of other types of stress on individuals of other ages and occupations. Further research into practical ways of modulating not only one’s mental stress response but potentially also one’s brain activity (e.g., via neurofeedback training) are warranted.

This is a “research implication”, and it is nicely combined with a mention of a potential limitation of the study (the student sample) that turns out not to be a limitation after all (because earlier research suggests we can generalize to other populations). If there already is a lot of research on neurofeedback for stress control, by the way, then this should have been discussed in your discussion section earlier and you wouldn’t say such studies are “warranted” here but rather specify how your findings could inspire specific future experiments or how they should be implemented in existing applications. 

Three: The most important thing is that your conclusion paragraph accurately reflects the content of your paper. Compare it to your research paper title , your research paper abstract , and to your journal submission cover letter , in case you already have one—if these do not all tell the same story, then you need to go back to your paper, start again from the introduction section, and find out where you lost the logical thread. As always, consistency is key.    

Problems to Avoid When Writing a Conclusion 

• Do not suddenly introduce new information that has never been mentioned before (unless you are writing an essay and opting for an externalizing conclusion, see above). The conclusion section is not where you want to surprise your readers, but the take-home message of what you have already presented.
• Do not simply copy your abstract, the conclusion section of your abstract, or the first sentence of your introduction, and put it at the end of the discussion section. Even if these parts of your paper cover the same points, they should not be identical.
• Do not start the conclusion with “In conclusion”. If it has its own section heading, that is redundant, and if it is the last paragraph of the discussion section, it is inelegant and also not really necessary. The reader expects you to wrap your work up in the last paragraph, so you don’t have to announce that. Just look at the above example to see how to start a conclusion in a natural way.
• Do not forget what your research objectives were and how you initially formulated the statement of the problem in your introduction section. If your story/approach/conclusions changed because of methodological issues or information you were not aware of when you started, then make sure you go back to the beginning and adapt your entire story (not just the ending). 

Consider Receiving Academic Editing Services

When you have arrived at the conclusion of your paper, you might want to head over to Wordvice AI’s AI Writing Assistant to receive a free grammar check for any academic content. 

After drafting, you can also receive English editing and proofreading services , including paper editing services for your journal manuscript. If you need advice on how to write the other parts of your research paper , or on how to make a research paper outline if you are struggling with putting everything you did together, then head over to the Wordvice academic resources pages , where we have a lot more articles and videos for you.

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• Efficacy of psilocybin...

Efficacy of psilocybin for treating symptoms of depression: systematic review and meta-analysis

Linked editorial.

Psilocybin for depression

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This article has a correction. Please see:

• EXPRESSION OF CONCERN: Efficacy of psilocybin for treating symptoms of depression: systematic review and meta-analysis - May 04, 2024
• Athina-Marina Metaxa , masters graduate researcher 1 ,
• Mike Clarke , professor 2
• 1 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
• 2 Northern Ireland Methodology Hub, Centre for Public Health, ICS-A Royal Hospitals, Belfast, Ireland, UK
• Correspondence to: A-M Metaxa athina.metaxa{at}hmc.ox.ac.uk (or @Athina_Metaxa12 on X)
• Accepted 6 March 2024

Objective To determine the efficacy of psilocybin as an antidepressant compared with placebo or non-psychoactive drugs.

Design Systematic review and meta-analysis.

Data sources Five electronic databases of published literature (Cochrane Central Register of Controlled Trials, Medline, Embase, Science Citation Index and Conference Proceedings Citation Index, and PsycInfo) and four databases of unpublished and international literature (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, ProQuest Dissertations and Theses Global, and PsycEXTRA), and handsearching of reference lists, conference proceedings, and abstracts.

Data synthesis and study quality Information on potential treatment effect moderators was extracted, including depression type (primary or secondary), previous use of psychedelics, psilocybin dosage, type of outcome measure (clinician rated or self-reported), and personal characteristics (eg, age, sex). Data were synthesised using a random effects meta-analysis model, and observed heterogeneity and the effect of covariates were investigated with subgroup analyses and metaregression. Hedges’ g was used as a measure of treatment effect size, to account for small sample effects and substantial differences between the included studies’ sample sizes. Study quality was appraised using Cochrane’s Risk of Bias 2 tool, and the quality of the aggregated evidence was evaluated using GRADE guidelines.

Eligibility criteria Randomised trials in which psilocybin was administered as a standalone treatment for adults with clinically significant symptoms of depression and change in symptoms was measured using a validated clinician rated or self-report scale. Studies with directive psychotherapy were included if the psychotherapeutic component was present in both experimental and control conditions. Participants with depression regardless of comorbidities (eg, cancer) were eligible.

Results Meta-analysis on 436 participants (228 female participants), average age 36-60 years, from seven of the nine included studies showed a significant benefit of psilocybin (Hedges’ g=1.64, 95% confidence interval (CI) 0.55 to 2.73, P<0.001) on change in depression scores compared with comparator treatment. Subgroup analyses and metaregressions indicated that having secondary depression (Hedges’ g=3.25, 95% CI 0.97 to 5.53), being assessed with self-report depression scales such as the Beck depression inventory (3.25, 0.97 to 5.53), and older age and previous use of psychedelics (metaregression coefficient 0.16, 95% CI 0.08 to 0.24 and 4.2, 1.5 to 6.9, respectively) were correlated with greater improvements in symptoms. All studies had a low risk of bias, but the change from baseline metric was associated with high heterogeneity and a statistically significant risk of small study bias, resulting in a low certainty of evidence rating.

Conclusion Treatment effects of psilocybin were significantly larger among patients with secondary depression, when self-report scales were used to measure symptoms of depression, and when participants had previously used psychedelics. Further research is thus required to delineate the influence of expectancy effects, moderating factors, and treatment delivery on the efficacy of psilocybin as an antidepressant.

Systematic review registration PROSPERO CRD42023388065.

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Introduction

Depression affects an estimated 300 million people around the world, an increase of nearly 20% over the past decade. 1 Worldwide, depression is also the leading cause of disability. 2

Drugs for depression are widely available but these seem to have limited efficacy, can have serious adverse effects, and are associated with low patient adherence. 3 4 Importantly, the treatment effects of antidepressant drugs do not appear until 4-7 weeks after the start of treatment, and remission of symptoms can take months. 4 5 Additionally, the likelihood of relapse is high, with 40-60% of people with depression experiencing a further depressive episode, and the chance of relapse increasing with each subsequent episode. 6 7

Since the early 2000s, the naturally occurring serotonergic hallucinogen psilocybin, found in several species of mushrooms, has been widely discussed as a potential treatment for depression. 8 9 Psilocybin’s mechanism of action differs from that of classic selective serotonin reuptake inhibitors (SSRIs) and might improve the treatment response rate, decrease time to improvement of symptoms, and prevent relapse post-remission. Moreover, more recent assessments of harm have consistently reported that psilocybin generally has low addictive potential and toxicity and that it can be administered safely under clinical supervision. 10

The renewed interest in psilocybin’s antidepressive effects led to several clinical trials on treatment resistant depression, 11 12 major depressive disorder, 13 and depression related to physical illness. 14 15 16 17 These trials mostly reported positive efficacy findings, showing reductions in symptoms of depression within a few hours to a few days after one dose or two doses of psilocybin. 11 12 13 16 17 18 These studies reported only minimal adverse effects, however, and drug harm assessments in healthy volunteers indicated that psilocybin does not induce physiological toxicity, is not addictive, and does not lead to withdrawal. 19 20 Nevertheless, these findings should be interpreted with caution owing to the small sample sizes and open label design of some of these studies. 11 21

Several systematic reviews and meta-analyses since the early 2000s have investigated the use of psilocybin to treat symptoms of depression. Most found encouraging results, but as well as people with depression some included healthy volunteers, 22 and most combined data from studies of multiple serotonergic psychedelics, 23 24 25 even though each compound has unique neurobiological effects and mechanisms of action. 26 27 28 Furthermore, many systematic reviews included non-randomised studies and studies in which psilocybin was tested in conjunction with psychotherapeutic interventions, 25 29 30 31 32 which made it difficult to distinguish psilocybin’s treatment effects. Most systematic reviews and meta-analyses did not consider the impact of factors that could act as moderators to psilocybin’s effects, such as type of depression (primary or secondary), previous use of psychedelics, psilocybin dosage, type of outcome measure (clinician rated or self-reported), and personal characteristics (eg, age, sex). 25 26 29 30 31 32 Lastly, systematic reviews did not consider grey literature, 33 34 which might have led to a substantial overestimation of psilocybin’s efficacy as a treatment for depression. In this review we focused on randomised trials that contained an unconfounded evaluation of psilocybin in adults with symptoms of depression, regardless of country and language of publication.

In this systematic review and meta-analysis of indexed and non-indexed randomised trials we investigated the efficacy of psilocybin to treat symptoms of depression compared with placebo or non-psychoactive drugs. The protocol was registered in the International Prospective Register of Systematic Reviews (see supplementary Appendix A). The study overall did not deviate from the pre-registered protocol; one clarification was made to highlight that any non-psychedelic comparator was eligible for inclusion, including placebo, niacin, micro doses of psychedelics, and drugs that are considered the standard of care in depression (eg, SSRIs).

Inclusion and exclusion criteria

Double blind and open label randomised trials with a crossover or parallel design were eligible for inclusion. We considered only studies in humans and with a control condition, which could include any type of non -active comparator, such as placebo, niacin, or micro doses of psychedelics.

Eligible studies were those that included adults (≥18 years) with clinically significant symptoms of depression, evaluated using a clinically validated tool for depression and mood disorder outcomes. Such tools included the Beck depression inventory, Hamilton depression rating scale, Montgomery-Åsberg depression rating scale, profile of mood states, and quick inventory of depressive symptomatology. Studies of participants with symptoms of depression and comorbidities (eg, cancer) were also eligible. We excluded studies of healthy participants (without depressive symptomatology).

Eligible studies investigated the effect of psilocybin as a standalone treatment on symptoms of depression. Studies with an active psilocybin condition that involved micro dosing (ie, psilocybin <100 μg/kg, according to the commonly accepted convention 22 35 ) were excluded. We included studies with directive psychotherapy if the psychotherapeutic component was present in both the experimental and the control conditions, so that the effects of psilocybin could be distinguished from those of psychotherapy. Studies involving group therapy were also excluded. Any non-psychedelic comparator was eligible for inclusion, including placebo, niacin, and micro doses of psychedelics.

Changes in symptoms, measured by validated clinician rated or self-report scales, such as the Beck depression inventory, Hamilton depression rating scale, Montgomery-Åsberg depression rating scale, profile of mood states, and quick inventory of depressive symptomatology were considered. We excluded outcomes that were measured less than three hours after psilocybin had been administered because any reported changes could be attributed to the transient cognitive and affective effects of the substance being administered. Aside from this, outcomes were included irrespective of the time point at which measurements were taken.

Search strategy

We searched major electronic databases and trial registries of psychological and medical research, with no limits on the publication date. Databases were the Cochrane Central Register of Controlled Trials via the Cochrane Library, Embase via Ovid, Medline via Ovid, Science Citation Index and Conference Proceedings Citation Index-Science via Web of Science, and PsycInfo via Ovid. A search through multiple databases was necessary because each database includes unique journals. Supplementary Appendix B shows the search syntax used for the Cochrane Central Register of Controlled Trials, which was slightly modified to comply with the syntactic rules of the other databases.

Unpublished and grey literature were sought through registries of past and ongoing trials, databases of conference proceedings, government reports, theses, dissertations, and grant registries (eg, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, ProQuest Dissertations and Theses Global, and PsycEXTRA). The references and bibliographies of eligible studies were checked for relevant publications. The original search was done in January 2023 and updated search was performed on 10 August 2023.

Data collection, extraction, and management

The results of the literature search were imported to the Endnote X9 reference management software, and the references were imported to the Covidence platform after removal of duplicates. Two reviewers (AM and DT) independently screened the title and abstract of each reference and then screened the full text of potentially eligible references. Any disagreements about eligibility were resolved through discussion. If information was insufficient to determine eligibility, the study’s authors were contacted. The reviewers were not blinded to the studies’ authors, institutions, or journal of publication.

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram shows the study selection process and reasons for excluding studies that were considered eligible for full text screening. 36

Critical appraisal of individual studies and of aggregated evidence

The methodological quality of eligible studies was assessed using the Cochrane Risk of Bias 2 tool (RoB 2) for assessing risk of bias in randomised trials. 37 In addition to the criteria specified by RoB 2, we considered the potential impact of industry funding and conflicts of interest. The overall methodological quality of the aggregated evidence was evaluated using GRADE (Grading of Recommendations, Assessment, Development and Evaluation). 38

If we found evidence of heterogeneity among the trials, then small study biases, such as publication bias, were assessed using a funnel plot and asymmetry tests (eg, Egger’s test). 39

We used a template for data extraction (see supplementary Appendix C) and summarised the extracted data in tabular form, outlining personal characteristics (age, sex, previous use of psychedelics), methodology (study design, dosage), and outcome related characteristics (mean change from baseline score on a depression questionnaire, response rates, and remission rates) of the included studies. Response conventionally refers to a 50% decrease in symptom severity based on scores on a depression rating scale, whereas remission scores are specific to a questionnaire (eg, score of ≤5 on the quick inventory of depressive symptomatology, score of ≤10 on the Montgomery-Åsberg depression rating scale, 50% or greater reduction in symptoms, score of ≤7 on the Hamilton depression rating scale, or score of ≤12 on the Beck depression inventory). Across depression scales, higher scores signify more severe symptoms of depression.

Continuous data synthesis

From each study we extracted the baseline and post-intervention means and standard deviations (SDs) of the scores between comparison groups for the depression questionnaires and calculated the mean differences and SDs of change. If means and SDs were not available for the included studies, we extracted the values from available graphs and charts using the Web Plot Digitizer application ( https://automeris.io/WebPlotDigitizer/ ). If it was not possible to calculate SDs from the graphs or charts, we generated values by converting standard errors (SEs) or confidence intervals (CIs), depending on availability, using formulas in the Cochrane Handbook (section 7.7.3.2). 40

Standardised mean differences were calculated for each study. We chose these rather than weighted mean differences because, although all the studies measured depression as the primary outcome, they did so with different questionnaires that score depression based on slightly different items. 41 If we had used weighted mean differences, any variability among studies would be assumed to reflect actual methodological or population differences and not differences in how the outcome was measured, which could be misleading. 40

The Hedges’ g effect size estimate was used because it tends to produce less biased results for studies with smaller samples (<20 participants) and when sample sizes differ substantially between studies, in contrast with Cohen’s d. 42 According to the Cochrane Handbook, the Hedges’ g effect size measure is synonymous with the standardised mean difference, 40 and the terms may be used interchangeably. Thus, a Hedges’ g of 0.2, 0.5, 0.8, or 1.2 corresponds to a small, medium, large, or very large effect, respectively. 40

Owing to variation in the participants’ personal characteristics, psilocybin dosage, type of depression investigated (primary or secondary), and type of comparators, we used a random effects model with a Hartung-Knapp-Sidik-Jonkman modification. 43 This model also allowed for heterogeneity and within study variability to be incorporated into the weighting of the results of the included studies. 44 Lastly, this model could help to generalise the findings beyond the studies and patient populations included, making the meta-analysis more clinically useful. 45 We chose the Hartung-Knapp-Sidik-Jonkman adjustment in favour of more widely used random effects models (eg, DerSimonian and Laird) because it allows for better control of type 1 errors, especially for studies with smaller samples, and provides a better estimation of between study variance by accounting for small sample sizes. 46 47

For studies in which multiple treatment groups were compared with a single placebo group, we split the placebo group to avoid multiplicity. 48 Similarly, if studies included multiple primary outcomes (eg, change in depression at three weeks and at six weeks), we split the treatment groups to account for overlapping participants. 40

Prediction intervals (PIs) were calculated and reported to show the expected effect range of a similar future study, in a different setting. In a random effects model, within study measures of variability, such as CIs, can only show the range in which the average effect size could lie, but they are not informative about the range of potential treatment effects given the heterogeneity between studies. 49 Thus, we used PIs as an indication of variation between studies.

Heterogeneity and sensitivity analysis

Statistical heterogeneity was tested using the χ 2 test (significance level P<0.1) and I 2 statistic, and heterogeneity among included studies was evaluated visually and displayed graphically using a forest plot. If substantial or considerable heterogeneity was found (I 2 ≥50% or P<0.1), 50 we considered the study design and characteristics of the included studies. Sources of heterogeneity were explored by subgroup analysis, and the potential effects on the results are discussed.

Planned sensitivity analyses to assess the effect of unpublished studies and studies at high risk of bias were not done because all included studies had been published and none were assessed as high risk of bias. Exclusion sensitivity plots were used to display graphically the impact of individual studies and to determine which studies had a particularly large influence on the results of the meta-analysis. All sensitivity analyses were carried out with Stata 16 software.

Subgroup analysis

To reduce the risk of errors caused by multiplicity and to avoid data fishing, we planned subgroup analyses a priori and limited to: (1) patient characteristics, including age and sex; (2) comorbidities, such as a serious physical condition (previous research indicates that the effects of psilocybin may be less strong for such participants, compared with participants with no comorbidities) 33 ; (3) number of doses and amount of psilocybin administered, because some previous meta-analyses found that a higher number of doses and a higher dose of psilocybin both predicted a greater reduction in symptoms of depression, 34 whereas others reported the opposite 33 ; (4) psilocybin administered alongside psychotherapeutic guidance or as a standalone treatment; (5) severity of depressive symptoms (clinical v subclinical symptomatology); (6) clinician versus patient rated scales; and (7) high versus low quality studies, as determined by RoB 2 assessment scores.

Metaregression

Given that enough studies were identified (≥10 distinct observations according to the Cochrane Handbook’s suggestion 40 ), we performed metaregression to investigate whether covariates, or potential effect modifiers, explained any of the statistical heterogeneity. The metaregression analysis was carried out using Stata 16 software.

Random effects metaregression analyses were used to determine whether continuous variables such as participants’ age, percentage of female participants, and percentage of participants who had previously used psychedelics modified the effect estimate, all of which have been implicated in differentially affecting the efficacy of psychedelics in modifying mood. 51 We chose this approach in favour of converting these continuous variables into categorical variables and conducting subgroup analyses for two primary reasons; firstly, the loss of any data and subsequent loss of statistical power would increase the risk of spurious significant associations, 51 and, secondly, no cut-offs have been agreed for these factors in literature on psychedelic interventions for mood disorders, 52 making any such divisions arbitrary and difficult to reconcile with the findings of other studies. The analyses were based on within study averages, in the absence of individual data points for each participant, with the potential for the results to be affected by aggregate bias, compromising their validity and generalisability. 53 Furthermore, a group level analysis may not be able to detect distinct interactions between the effect modifiers and participant subgroups, resulting in ecological bias. 54 As a result, this analysis should be considered exploratory.

Sensitivity analysis

A sensitivity analysis was performed to determine if choice of analysis method affected the primary findings of meta-analysis. Specifically, we reanalysed the data on change in depression score using a random effects Dersimonian and Laird model without the Hartung-Knapp-Sidik-Jonkman modification and compared the results with those of the originally used model. This comparison is particularly important in the presence of substantial heterogeneity and the potential of small study effects to influence the intervention effect estimate. 55

Patient and public involvement

Research on novel depression treatments is of great interest to both patients and the public. Although patients and members of the public were not directly involved in the planning or writing of this manuscript owing to a lack of available funding for recruitment and researcher training, patients and members of the public read the manuscript after submission.

Figure 1 presents the flow of studies through the systematic review and meta-analysis. 56 A total of 4884 titles were retrieved from the five databases of published literature, and a further 368 titles were identified from the databases of unpublished and international literature in February 2023. After the removal of duplicate records, we screened the abstracts and titles of 875 reports. A further 12 studies were added after handsearching of reference lists and conference proceedings and abstracts. Overall, nine studies totalling 436 participants were eligible. The average age of the participants ranged from 36-60 years. During an updated search on 10 August 2023, no further studies were identified.

Flow of studies in systematic review and meta-analysis

After screening of the title and abstract, 61 titles remained for full text review. Native speakers helped to translate papers in languages other than English. The most common reasons for exclusion were the inclusion of healthy volunteers, absence of control groups, and use of a survey based design rather than an experimental design. After full text screening, nine studies were eligible for inclusion, and 15 clinical trials prospectively registered or underway as of August 2023 were noted for potential future inclusion in an update of this review (see supplementary Appendix D).

We sent requests for further information to the authors of studies by Griffiths et al, 57 Barrett, 58 and Benville et al, 59 because these studies appeared to meet the inclusion criteria but were only provided as summary abstracts online. A potentially eligible poster presentation from the 58th annual meeting of the American College of Neuropsychopharmacology was identified but the lead author (Griffiths) clarified that all information from the presentation was included in the studies by Davis et al 13 and Gukasyan et al 60 ; both of which we had already deemed ineligible.

Barrett 58 reported the effects of psilocybin on the cognitive flexibility and verbal reasoning of a subset of patients with major depressive disorder from Griffith et al’s trial, 61 compared with a waitlist group, but when contacted, Barrett explained that the results were published in the study by Doss et al, 62 which we had already screened and judged ineligible (see supplementary Appendix E). Benville et al’s study 59 presented a follow-up of Ross et al’s study 17 on a subset of patients with cancer and high suicidal ideation and desire for hastened death at baseline. Measures of antidepressant effects of psilocybin treatment compared with niacin were taken before and after treatment crossover, but detailed results are not reported. Table 1 describes the characteristics of the included studies and table 2 lists the main findings of the studies.

Characteristics of included studies

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Main findings of included studies

Side effects and adverse events

Side effects reported in the included studies were minor and transient (eg, short term increases in blood pressure, headache, and anxiety), and none were coded as serious. Cahart-Harris et al noted one instance of abnormal dreams and insomnia. 63 This side effect profile is consistent with findings from other meta-analyses. 30 68 Owing to the different scales and methods used to catalogue side effects and adverse events across trials, it was not possible to combine these data quantitatively (see supplementary Appendix F).

Risk of bias

The Cochrane RoB 2 tools were used to evaluate the included studies ( table 3 ). RoB 2 for randomised trials was used for the five reports of parallel randomised trials (Carhart-Harris et al 63 and its secondary analysis Barba et al, 64 Goodwin et al 18 and its secondary analysis Goodwin et al, 65 and von Rotz et al 66 ) and RoB 2 for crossover trials was used for the four reports of crossover randomised trials (Griffiths et al, 14 Grob et al, 15 and Ross et al 17 and its follow-up Ross et al 67 ). Supplementary Appendix G provides a detailed explanation of the assessment of the included studies.

Summary risk of bias assessment of included studies, based on domains in Cochrane Risk of Bias 2 tool

Quality of included studies

Confidence in the quality of the evidence for the meta-analysis was assessed using GRADE, 38 through the GRADEpro GDT software program. Figure 2 shows the results of this assessment, along with our summary of findings.

GRADE assessment outputs for outcomes investigated in meta-analysis (change in depression scores and response and remission rates). The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). BDI=Beck depression inventory; CI=confidence interval; GRADE=Grading of Recommendations, Assessment, Development and Evaluation; HADS-D=hospital anxiety and depression scale; HAM-D=Hamilton depression rating scale; MADRS=Montgomery-Åsberg depression rating scale; QIDS=quick inventory of depressive symptomatology; RCT=randomised controlled trial; SD=standard deviation

Meta-analyses

Continuous data, change in depression scores —Using a Hartung-Knapp-Sidik-Jonkman modified random effects meta-analysis, change in depression scores was significantly greater after treatment with psilocybin compared with active placebo. The overall Hedges’ g (1.64, 95% CI 0.55 to 2.73) indicated a large effect size favouring psilocybin ( fig 3 ). PIs were, however, wide and crossed the line of no difference (95% CI −1.72 to 5.03), indicating that there could be settings or populations in which psilocybin intervention would be less efficacious.

Forest plot for overall change in depression scores from before to after treatment. CI=confidence interval; DL=DerSimonian and Laird; HKSJ=Hartung-Knapp-Sidik-Jonkman

Exploring publication bias in continuous data —We used Egger’s test and a funnel plot to examine the possibility of small study biases, such as publication bias. Statistical significance of Egger’s test for small study effects, along with the asymmetry in the funnel plot ( fig 4 ), indicates the presence of bias against smaller studies with non-significant results, suggesting that the pooled intervention effect estimate is likely to be overestimated. 69 An alternative explanation, however, is that smaller studies conducted at the early stages of a new psychotherapeutic intervention tend to include more high risk or responsive participants, and psychotherapeutic interventions tend to be delivered more effectively in smaller trials; both of these factors can exaggerate treatment effects, resulting in funnel plot asymmetry. 70 Also, because of the relatively small number of included studies and the considerable heterogeneity observed, test power may be insufficient to distinguish real asymmetry from chance. 71 Thus, this analysis should be considered exploratory.

Funnel plot assessing publication bias among studies measuring change in depression scores from before to after treatment. CI=confidence interval; θ IV =estimated effect size under inverse variance random effects model

Dichotomous data

We extracted response and remission rates for each group when reported directly, or imputed information when presented graphically. Two studies did not measure response or remission and thus did not contribute data for this part of the analysis. 15 18 The random effects model with a Hartung-Knapp-Sidik-Jonkman modification was used to allow for heterogeneity to be incorporated into the weighting of the included studies’ results, and to provide a better estimation of between study variance accounting for small sample sizes.

Response rate —Overall, the likelihood of psilocybin intervention leading to treatment response was about two times greater (risk ratio 2.02, 95% CI 1.33 to 3.07) than with placebo. Despite the use of different scales to measure response, the heterogeneity between studies was not significant (I 2 =25.7%, P=0.23). PIs were, however, wide and crossed the line of no difference (−0.94 to 3.88), indicating that there could be settings or populations in which psilocybin intervention would be less efficacious.

Remission rate —Overall, the likelihood of psilocybin intervention leading to remission of depression was nearly three times greater than with placebo (risk ratio 2.71, 95% CI 1.75 to 4.20). Despite the use of different scales to measure response, no statistical heterogeneity was found between studies (I 2 =0.0%, P=0.53). PIs were, however, wide and crossed the line of no difference (0.87 to 2.32), indicating that there could be settings or populations in which psilocybin intervention would be less efficacious.

Exploring publication bias in response and remission rates data —We used Egger’s test and a funnel plot to examine whether response and remission estimates were affected by small study biases. The result for Egger’s test was non-significant (P>0.05) for both response and remission estimates, and no substantial asymmetry was observed in the funnel plots, providing no indication for the presence of bias against smaller studies with non-significant results.

Heterogeneity: subgroup analyses and metaregression

Heterogeneity was considerable across studies exploring changes in depression scores (I 2 =89.7%, P<0.005), triggering subgroup analyses to explore contributory factors. Table 4 and table 5 present the results of the heterogeneity analyses (subgroup analyses and metaregression, respectively). Also see supplementary Appendix H for a more detailed description and graphical representation of these results.

Subgroup analyses to explore potential causes of heterogeneity among included studies

Metaregression analyses to explore potential causes of heterogeneity among included studies

Cumulative meta-analyses

We used cumulative meta-analyses to investigate how the overall estimates of the outcomes of interest changed as each study was added in chronological order 72 ; change in depression scores and likelihood of treatment response both increased as the percentage of participants with past use of psychedelics increased across studies, as expected based on the metaregression analysis (see supplementary Appendix I). No other significant time related patterns were found.

We reanalysed the data for change in depression scores using a random effects Dersimonian and Laird model without the Hartung-Knapp-Sidik-Jonkman modification and compared the results with those of the original model. All comparisons found to be significant using the Dersimonian and Laird model with the Hartung-Knapp-Sidik-Jonkman adjustment were also significant without the Hartung-Knapp-Sidik-Jonkman adjustment, and confidence intervals were only slightly narrower. Thus, small study effects do not appear to have played a major role in the treatment effect estimate.

Additionally, to estimate the accuracy and robustness of the estimated treatment effect, we excluded studies from the meta-analysis one by one; no important differences in the treatment effect, significance, and heterogeneity levels were observed after the exclusion of any study (see supplementary Appendix J).

In our meta-analysis we found that psilocybin use showed a significant benefit on change in depression scores compared with placebo. This is consistent with other recent meta-analyses and trials of psilocybin as a standalone treatment for depression 73 74 or in combination with psychological support. 24 25 29 30 31 32 68 75 This review adds to those finding by exploring the considerable heterogeneity across the studies, with subsequent subgroup analyses showing that the type of depression (primary or secondary) and the depression scale used (Montgomery-Åsberg depression rating scale, quick inventory of depressive symptomatology, or Beck depression inventory) had a significant differential effect on the outcome. High between study heterogeneity has been identified by some other meta-analyses of psilocybin (eg, Goldberg et al 29 ), with a higher treatment effect in studies with patients with comorbid life threatening conditions compared with patients with primary depression. 22 Although possible explanations, including personal factors (eg, patients with life threatening conditions being older) or depression related factors (eg, secondary depression being more severe than primary depression) could be considered, these hypotheses are not supported by baseline data (ie, patients with secondary depression do not differ substantially in age or symptom severity from patients with primary depression). The differential effects from assessment scales used have not been examined in other meta-analyses of psilocybin, but this review’s finding that studies using the Beck depression inventory showed a higher treatment effect than those using the Montgomery-Åsberg depression rating scale and quick inventory of depressive symptomatology is consistent with studies in the psychological literature that have shown larger treatment effects when self-report scales are used (eg, Beck depression inventory). 76 77 This finding may be because clinicians tend to overestimate the severity of depression symptoms at baseline assessments, leading to less pronounced differences between before and after treatment identified in clinician assessed scales (eg, Montgomery-Åsberg depression rating scale, quick inventory of depressive symptomatology). 78

Metaregression analyses further showed that a higher average age and a higher percentage of participants with past use of psychedelics both correlated with a greater improvement in depression scores with psilocybin use and explained a substantial amount of between study variability. However, the cumulative meta-analysis showed that the effects of age might be largely an artefact of the inclusion of one specific study, and alternative explanations are worth considering. For instance, Studerus et al 79 identified participants’ age as the only personal variable significantly associated with psilocybin response, with older participants reporting a higher “blissful state” experience. This might be because of older people’s increased experience in managing negative emotions and the decrease in 5-hydroxytryptamine type 2A receptor density associated with older age. 80 Furthermore, Rootman et al 81 reported that the cognitive performance of older participants (>55 years) improved significantly more than that of younger participants after micro dosing with psilocybin. Therefore, the higher decrease in depressive symptoms associated with older age could be attributed to a decrease in cognitive difficulties experienced by older participants.

Interestingly, a clear pattern emerged for past use of psychedelics—the higher the proportion of study participants who had used psychedelics in the past, the higher the post-psilocybin treatment effect observed. Past use of psychedelics has been proposed to create an expectancy bias among participants and amplify the positive effects of psilocybin 82 83 84 ; however, this important finding has not been examined in other meta-analyses and may highlight the role of expectancy in psilocybin research.

Limitations of this study

Generalisability of the findings of this meta-analysis was limited by the lack of racial and ethnic diversity in the included studies—more than 90% of participants were white across all included trials, resulting in a homogeneous sample that is not representative of the general population. Moreover, it was not possible to distinguish between subgroups of participants who had never used psilocybin and those who had taken psilocybin more than a year before the start of the trial, as these data were not provided in the included studies. Such a distinction would be important, as the effects of psilocybin on mood may wane within a year after being administered. 21 85 Also, how psychological support was conceptualised was inconsistent within studies of psilocybin interventions; many studies failed to clearly describe the type of psychological support participants received, and others used methods ranging from directive guidance throughout the treatment session to passive encouragement or reassurance (eg, Griffiths et al, 14 Carhart-Harris et al 63 ). The included studies also did not gather evidence on participants’ previous experiences with treatment approaches, which could influence their response to the trials’ intervention. Thus, differences between participant subgroups related to past use of psilocybin or psychotherapy may be substantial and could help interpret this study’s findings more accurately. Lastly, the use of graphical extraction software to estimate the findings of studies where exact numerical data were not available (eg, Goodwin et al, 18 Grob et al 15 ), may have affected the robustness of the analyses.

A common limitation in studies of psilocybin is the likelihood of expectancy effects augmenting the treatment effect observed. Although some studies used low dose psychedelics as comparators to deal with this problem (eg, Carhart-Harris et al, 63 Goodwin et al, 18 Griffiths et al 14 ) or used a niacin placebo that can induce effects similar to those of psilocybin (eg, Grob et al, 15 Ross et al 17 ), the extent to which these methods were effective in blinding participants is not known. Other studies have, however, reported that participants can accurately identify the study groups to which they had been assigned 70-85% of the time, 84 86 indicating a high likelihood of insufficient blinding. This is especially likely for studies in which a high proportion of participants had previously used psilocybin and other hallucinogens, making the identification of the drug’s acute effects easier (eg, Griffiths et al, 14 Grob et al, 15 Ross et al 17 ). Patients also have expectations related to the outcome of their treatment, expecting psilocybin to improve their symptoms of depression, and these positive expectancies are strong predictors of actual treatment effects. 87 88 Importantly, the effect of outcome expectations on treatment effect is particularly strong when patient reported measures are used as primary outcomes, 89 which was the case in several of the included studies (eg, Griffiths et al, 14 Grob et al, 15 Ross et al 17 ). Unfortunately, none of the included studies recorded expectations before treatment, so it is not possible to determine the extent to which this factor affected the findings.

Implications for clinical practice

Although this review’s findings are encouraging for psilocybin’s potential as an effective antidepressant, a few areas about its applicability in clinical practice remain unexplored. Firstly, it is unclear whether the protocols for psilocybin interventions in clinical trials can be reliably and safely implemented in clinical practice. In clinical trials, patients receive psilocybin in a non-traditional medical setting, such as a specially designed living room, while they may be listening to curated calming music and are isolated from most external stimuli by wearing eyeshades and external noise-cancelling earphones. A trained therapist closely supervises these sessions, and the patient usually receives one or more preparatory sessions before the treatment commences. Standardising an intervention setting with so many variables is unlikely to be achievable in routine practice, and consensus is considerably lacking on the psychotherapeutic training and accreditations needed for a therapist to deliver such treatment. 90 The combination of these elements makes this a relatively complex and expensive intervention, which could make it challenging to gain approval from regulatory agencies and to gain reimbursement from insurance companies and others. Within publicly funded healthcare systems, the high cost of treatment may make psilocybin treatment inaccessible. The high cost associated with the intervention also increases the risk that unregulated clinics may attempt to cut costs by making alterations to the protocol and the therapeutic process, 91 92 which could have detrimental effects for patients. 92 93 94 Thus, avoiding the conflation of medical and commercial interests is a primary concern that needs to be dealt with before psilocybin enters mainstream practice.

Implications for future research

More large scale randomised trials with long follow-up are needed to fully understand psilocybin’s treatment potential, and future studies should aim to recruit a more diverse population. Another factor that would make clinical trials more representative of routine practice would be to recruit patients who are currently using or have used commonly prescribed serotonergic antidepressants. Clinical trials tend to exclude such participants because many antidepressants that act on the serotonin system modulate the 5-hydroxytryptamine type 2A receptor that psilocybin primarily acts upon, with prolonged use of tricyclic antidepressants associated with more intense psychedelic experiences and use of monoamine oxidase inhibitors or SSRIs inducing weaker responses to psychedelics. 95 96 97 Investigating psilocybin in such patients would, however, provide valuable insight on how psilocybin interacts with commonly prescribed drugs for depression and would help inform clinical practice.

Minimising the influence of expectancy effects is another core problem for future studies. One strategy would be to include expectancy measures and explore the level of expectancy as a covariate in statistical analysis. Researchers should also test the effectiveness of condition masking. Another proposed solution would be to adopt a 2×2 balanced placebo design, where both the drug (psilocybin or placebo) and the instructions given to participants (told they have received psilocybin or told they have received placebo) are crossed. 98 Alternatively, clinical trials could adopt a three arm design that includes both an inactive placebo (eg, saline) and active placebo (eg, niacin, lower psylocibin dose), 98 allowing for the effects of psilocybin to be separated from those of the placebo.

Overall, future studies should explore psilocybin’s exact mechanism of treatment effectiveness and outline how its physiological effects, mystical experiences, dosage, treatment setting, psychological support, and relationship with the therapist all interact to produce a synergistic antidepressant effect. Although this may be difficult to achieve using an explanatory randomised trial design, pragmatic clinical trial designs may be better suited to psilocybin research, as their primary objective is to achieve high external validity and generalisability. Such studies may include multiple alternative treatments rather than simply an active and placebo treatment comparison (eg, psilocybin v SSRI v serotonin-noradrenaline reuptake inhibitor), and participants would be recruited from broader clinical populations. 99 100 Although such studies are usually conducted after a drug’s launch, 100 earlier use of such designs could help assess the clinical effectiveness of psilocybin more robustly and broaden patient access to a novel type of antidepressant treatment.

Conclusions

This review’s findings on psilocybin’s efficacy in reducing symptoms of depression are encouraging for its use in clinical practice as a drug intervention for patients with primary or secondary depression, particularly when combined with psychological support and administered in a supervised clinical environment. However, the highly standardised treatment setting, high cost, and lack of regulatory guidelines and legal safeguards associated with psilocybin treatment need to be dealt with before it can be established in clinical practice.

What is already known on this topic

Recent research on treatments for depression has focused on psychedelic agents that could have strong antidepressant effects without the drawbacks of classic antidepressants; psilocybin being one such substance

Over the past decade, several clinical trials, meta-analyses, and systematic reviews have investigated the use of psilocybin for symptoms of depression, and most have found that psilocybin can have antidepressant effects

Studies published to date have not investigated factors that may moderate psilocybin’s effects, including type of depression, past use of psychedelics, dosage, outcome measures, and publication biases

What this study adds

This review showed a significantly greater efficacy of psilocybin among patients with secondary depression, patients with past use of psychedelics, older patients, and studies using self-report measures for symptoms of depression

Efficacy did not appear to be homogeneous across patient types—for example, those with depression and a life threatening illness appeared to benefit more from treatment

Further research is needed to clarify the factors that maximise psilocybin’s treatment potential for symptoms of depression

Ethics statements

Ethical approval.

This study was approved by the ethics committee of the University of Oxford Nuffield Department of Medicine, which waived the need for ethical approval and the need to obtain consent for the collection, analysis, and publication of the retrospectively obtained anonymised data for this non-interventional study.

Data availability statement

The relevant aggregated data and statistical code will be made available on reasonable request to the corresponding author.

Acknowledgments

We thank DT who acted as an independent secondary reviewer during the study selection and data review process.

Contributors: AMM contributed to the design and implementation of the research, analysis of the results, and writing of the manuscript. MC was involved in planning and supervising the work and contributed to the writing of the manuscript. AMM and MC are the guarantors. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: None received.

Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: no support from any organisation for the submitted work; AMM is employed by IDEA Pharma, which does consultancy work for pharmaceutical companies developing drugs for physical and mental health conditions; MC was the supervisor for AMM’s University of Oxford MSc dissertation, which forms the basis for this paper; no other relationships or activities that could appear to have influenced the submitted work.

Transparency: The corresponding author (AMM) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as registered have been explained.

Dissemination to participants and related patient and public communities: To disseminate our findings and increase the impact of our research, we plan on writing several social media posts and blog posts outlining the main conclusions of our paper. These will include blog posts on the websites of the University of Oxford’s Department of Primary Care Health Sciences and Department for Continuing Education, as well as print publications, which are likely to reach a wider audience. Furthermore, we plan to present our findings and discuss them with the public in local mental health related events and conferences, which are routinely attended by patient groups and advocacy organisations.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

• ↵ World Health Organization. Depressive Disorder (Depression); 2023. https://www.who.int/news-room/fact-sheets/detail/depression .
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• Open access
• Published: 27 April 2024

Assessing fragility of statistically significant findings from randomized controlled trials assessing pharmacological therapies for opioid use disorders: a systematic review

• Leen Naji   ORCID: orcid.org/0000-0003-0994-1109 1 , 2 , 3 ,
• Brittany Dennis 4 , 5 ,
• Myanca Rodrigues 2 ,
• Monica Bawor 6 ,
• Alannah Hillmer 7 ,
• Caroul Chawar 8 ,
• Eve Deck 9 ,
• Andrew Worster 2 , 4 ,
• James Paul 10 ,
• Lehana Thabane 11 , 2 &
• Zainab Samaan 12 , 2  

Trials volume  25 , Article number:  286 ( 2024 ) Cite this article

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Metrics details

The fragility index is a statistical measure of the robustness or “stability” of a statistically significant result. It has been adapted to assess the robustness of statistically significant outcomes from randomized controlled trials. By hypothetically switching some non-responders to responders, for instance, this metric measures how many individuals would need to have responded for a statistically significant finding to become non-statistically significant. The purpose of this study is to assess the fragility index of randomized controlled trials evaluating opioid substitution and antagonist therapies for opioid use disorder. This will provide an indication as to the robustness of trials in the field and the confidence that should be placed in the trials’ outcomes, potentially identifying ways to improve clinical research in the field. This is especially important as opioid use disorder has become a global epidemic, and the incidence of opioid related fatalities have climbed 500% in the past two decades.

Six databases were searched from inception to September 25, 2021, for randomized controlled trials evaluating opioid substitution and antagonist therapies for opioid use disorder, and meeting the necessary requirements for fragility index calculation. Specifically, we included all parallel arm or two-by-two factorial design RCTs that assessed the effectiveness of any opioid substitution and antagonist therapies using a binary primary outcome and reported a statistically significant result. The fragility index of each study was calculated using methods described by Walsh and colleagues. The risk of bias of included studies was assessed using the Revised Cochrane Risk of Bias tool for randomized trials.

Ten studies with a median sample size of 82.5 (interquartile range (IQR) 58, 179, range 52–226) were eligible for inclusion. Overall risk of bias was deemed to be low in seven studies, have some concerns in two studies, and be high in one study. The median fragility index was 7.5 (IQR 4, 12, range 1–26).

Conclusions

Our results suggest that approximately eight participants are needed to overturn the conclusions of the majority of trials in opioid use disorder. Future work should focus on maximizing transparency in reporting of study results, by reporting confidence intervals, fragility indexes, and emphasizing the clinical relevance of findings.

Trial registration

PROSPERO CRD42013006507. Registered on November 25, 2013.

Peer Review reports

Introduction

Opioid use disorder (OUD) has become a global epidemic, and the incidence of opioid related fatality is unparalleled to the rates observed in North America, having climbed 500% in the past two decades [ 1 , 2 ]. There is a dire need to identify the most effective treatment modality to maintain patient engagement in treatment, mitigate high risk consumption patterns, as well as eliminate overdose risk. Numerous studies have aimed to identify the most effective treatment modality for OUD [ 3 , 4 , 5 ]. Unfortunately, this multifaceted disease is complicated by the interplay between both neurobiological and social factors, impacting our current body of evidence and clinical decision making. Optimal treatment selection is further challenged by the rising number of pharmacological opioid substitution and antagonist therapies (OSAT) [ 6 ]. Despite this growing body of evidence and available therapies, we have yet to arrive to a consensus regarding the best treatment modality given the substantial variability in research findings and directly conflicting results [ 6 , 7 , 8 , 9 ]. More concerning, international clinical practice guidelines rely on out-of-date systematic review evidence to inform guideline development [ 10 ]. In fact, these guidelines make strong recommendations based on a fraction of the available evidence, employing trials with restrictive eligibility criteria which fail to reflect the common OUD patients seen in clinical practice [ 10 ].

A major factor hindering our ability to advance the field of addiction medicine is our failure to apply the necessary critical lens to the growing body of evidence used to inform clinical practice. While distinct concerns exist regarding the external validity of randomized trials in addiction medicine, the robustness of the universally recognized “well designed” trials remains unknown [ 10 ]. The reliability of the results of clinical trials rests on not only the sample size of the study but also the number of outcome events. In fact, a shift in the results of only a few events could in theory render the findings of the trial null, impacting the traditional hypothesis tests above the standard threshold accepted as “statistical significance.” A metric of this fragility was first introduced in 1990, known formally as the fragility index (FI) [ 11 ]. In 2014, it was adapted for use as a tool to assess the robustness of findings from randomized controlled trials (RCTs) [ 12 ]. Briefly, the FI determines the minimum number of participants whose outcome would have to change from non-event to event in order for a statistically significant result to become non-significant. Larger FIs indicate more robust findings [ 11 , 13 ]. Additionally, when the number of study participants lost to follow-up exceeds the FI of the trial, this implies that the outcome of these participants could have significantly altered the statistical significance and final conclusions of the study. The FI has been applied across multiple fields, often yielding similar results such that the change in a small number of outcome events has been powerful enough to overturn the statistical conclusions of many “well-designed” trials [ 13 ].

The concerning state of the OUD literature has left us with guidelines which neither acknowledge the lack of external validity and actually go so far as to rank the quality of the evidence as good, despite the concerning limitations we have raised [ 10 ]. Such alarming practices necessitate vigilance on behalf of methodologists and practitioners to be critical and open to a thorough review of the evidence in the field of addiction medicine [ 12 ]. Given the complex nature of OUD treatment and the increasing number of available therapies, concentrated efforts are needed to ensure the reliability and internal validity of the results of clinical trials used to inform guidelines. Application of the FI can serve to provide additional insight into the robustness of the evidence in addiction medicine. The purpose of this study is to assess the fragility of findings of RCTs assessing OSAT for OUD.

Systematic review protocol

We conducted a systematic review of the evidence surrounding OSATs for OUD [ 5 ]. The study protocol was registered with PROSPERO a priori (PROSPERO CRD42013006507). We searched Medline, EMBASE, PubMed, PsycINFO, Web of Science, and Cochrane Library for relevant studies from inception to September 25, 2021. We included all RCTs evaluating the effectiveness of any OSAT for OUD, which met the criteria required for FI calculation. Specifically, we included all parallel arm or two-by-two factorial design RCTs that allocated patients at a 1:1 ratio, assessed the effectiveness of any OSAT using a binary primary or co-primary outcome, and reported this outcome to be statistically significant ( p < 0.05).

All titles, abstracts, and full texts were screened for eligibility by two reviewers independently and in duplicate. Any discrepancies between the two reviewers were discussed for consensus, and a third reviewer was called upon when needed.

Data extraction and risk of bias assessment (ROB)

Two reviewers extracted the following data from the included studies in duplicate and independently using a pilot-tested excel data extraction sheet: sample size, whether a sample size calculation was conducted, statistical test used, primary outcome, number of responders and non-responders in each arm, number lost to follow-up, and the p -value. The 2021 Thomson Reuters Journal Impact Factor for each included study was also recorded. The ROB of included studies for the dichotomous outcome used in the FI calculation was assessed using the Revised Cochrane ROB tool for randomized trials [ 14 ]. Two reviewers independently assessed the included studies based on the following domains for potential ROB: randomization process, deviations from the intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results.

Statistical analyses

Study characteristics were summarized using descriptive statistics. Means and standard deviations (SD), as well as medians and interquartile ranges (IQR: Q 25 , Q 75 ) were used as measures of central tendency for continuous outcomes with normal and skewed distributions, respectively. Frequencies and percentages were used to summarize categorical variables. The FI was calculated using a publicly available free online calculator, using the methods described by Walsh et al. [ 12 , 15 ] In summary, the number of events and non-events in each treatment arm were entered into a two-by-two contingency table for each trial. An event was added to the treatment arm with the smaller number of events, while subtracting a non-event from the same arm, thus keeping the overall sample size the same. Each time this was done, the two-sided p -value for Fisher’s exact test was recalculated. The FI was defined as the number of non-events that needed to be switched to events for the p -value to reach non-statistical significance (i.e., ≥0.05).

We intended to conduct a linear regression and Spearman’s rank correlations to assess the association between FI and journal impact factor, study sample size, and number events. However, we were not powered to do so given the limited number of eligible studies included in this review and thus refrained from conducting any inferential statistics.

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting (see Supplementary Material ) [ 16 ].

Study selection

Our search yielded 13,463 unique studies, of which 104 were RCTs evaluating OSAT for OUD. Among these, ten studies met the criteria required for FI calculation and were included in our analyses. Please refer to Fig. 1 for the search results, study inclusion flow diagram, and Table 1 for details on included studies.

PRISMA flow diagram delineating study selection

Characteristics of included studies

The included studies were published between 1980 and 2018, in eight different journals with a median impact factor of 8.48 (IQR 6.53–56.27, range 3.77–91.25). Four studies reported on a calculated sample size [ 17 , 18 , 19 , 20 ], and only one study specified that reporting guidelines were used [ 21 ]. Treatment retention was the most commonly reported primary outcome ( k = 8). The median sample size of included studies was 82.5 (IQR 58–179, range 52–226).

Overall ROB was deemed to be low in seven studies [ 17 , 19 , 20 , 21 , 22 , 23 , 24 ], have some concerns in two studies [ 18 , 25 ], and be high in one study [ 26 ] due to a high proportion of missing outcome data that was not accounted for in the analyses. We present a breakdown of the ROB assessment of the included studies for the dichotomous outcome of interest in Table 2 .

• Fragility index

The median FI of included studies was 7.5 (IQR 4–12; range 1–26). The FI of individual studies is reported in Table 1 . The number of participants lost to follow-up exceeded the FI in two studies [ 23 , 26 ]. We find that there is a relatively positive correlation between the FI and sample size. However, no clear correlation was appreciated between FI and journal impact factor or number of events.

This is the first study to evaluate the FI in the field of addiction medicine, and more specifically in OUD trials. Among the ten RCTs evaluating the OSAT for OUD, we found that, in some cases, changing the outcome of one or two participants could completely alter the study’s conclusions and render the results statistically non-significant.

We compare our findings to those of Holek et al. , wherein they examined the mean FI across all reviews published in PubMed between 2014 and 2019 that assessed the distribution of FI indices, irrespective of discipline (though none were in addiction medicine) [ 13 ]. Among 24 included reviews with a median sample size of 134 (IQR 82, 207), they found a mean FI of 4 (95% CI 3, 5) [ 13 ]. This is slightly lower than our calculated our median FI of 7.5 (IQR 4–12; range 1–26). It is important to note that half of the reviews included in the study by Holek et al. were conducted in surgical disciplines, which are generally subjected to more limitations to internal and external validity, as it is often not possible to conceal allocation, blind participants, or operators, and the intervention is operator dependent. [ 27 ] To date, no study has directly applied FI to the findings of trials in OUD. In the HIV/AIDS literature, however, a population which is commonly shared with addiction medicine due to the prevalence of the comorbidities coexisting, the median fragility across all trials assessing anti-retroviral therapies ( n = 39) was 6 (IQR = 1, 11) [ 28 ], which is more closely related to our calculated FI. Among the included studies, only 3 were deemed to be at high risk of bias, whereas 13 and 20 studies were deemed to be at low and some risk of bias, respectively.

Loss-to-follow-up plays an important role in the interpretation of the FI. For instance, when the number of study participants lost to follow-up exceeds the FI of the trial, this implies that the outcome of these participants could have significantly altered the statistical significance and final conclusions of the study. While only two of the included studies had an FI that was greater than the total number of participants lost to follow-up [ 23 , 26 ], this metric is less important in our case given the primary outcome assessed by the majority of trials was retention in treatment, rendering loss to follow-up an outcome itself. In our report, we considered participants to be lost to follow-up if they left the study for reasons that were known and not necessarily indicative of treatment failure, such as due to factors beyond the participants, control including incarceration or being transferred to another treatment location.

Findings from our analysis of the literature as well as the application of FI to the existing clinical trials in the field of addiction medicine demonstrates significant concerns regarding the robustness of the evidence. This, in conjunction with the large differences between the clinical population and trial participants of opioid-dependent patients inherent in addiction medicine trials, raises larger concerns as to a growing body of evidence with deficiencies in both internal and external validity. The findings from this study raise important clinical concerns regarding the applicability of the current evidence to treating patients in the context of the opioid epidemic. Are we recommending the appropriate treatments for patients with OUD based on robust and applicable evidence? Are we completing our due diligence and ensuring clinicians and researchers alike understand the critical issues rampant in the literature, including the fragility of the data and misconceptions of p -values? Are we possibly putting our patients at risk employing such treatment based on fragile data? These questions cannot be answered until the appropriate re-evaluation of the evidence takes place employing both the use pragmatic trial designs as well as transparent metrics to reflect the reliability and robustness of the findings.

Strengths and limitations

Our study is strengthened by a comprehensive search strategy, rigorous and systematic screening of studies, and the use of an objective measure to gauge the robustness of studies (i.e., FI). The limitations of this study are inherent in the limitations of the FI. Precisely, that it can only be calculated for RCTs with a 1:1 allocation ratio, a parallel arm or two-by-two factorial design, and a dichotomous primary outcome. As a result, 94 RCTs evaluating OSAT for OUD were excluded for not meeting these criteria (Fig. 1 ). Nonetheless, the FI provides a general sense of the robustness of the available studies, and our data reflect studies published across almost four decades in journals of varying impact factor.

Future direction

This study serves as further evidence for the need of a shift away from p -values [ 29 , 30 ]. Although there is increasingly a shift among statisticians to shift away from relying on statistical significance due to its inability to convey clinical importance [ 31 ], this remains the simplest way and most commonly reported metric in manuscripts. p -values provide a simple statistical measure to confirm or refute a null hypothesis, by providing a measure of how likely the observed result would be if the null hypothesis were true. An arbitrary cutoff of 5% is traditionally used as a threshold for rejecting the null hypothesis. However, a major drawback of the p -value is that it does not take into account the effect size of the outcome measure, such that a small incremental change that may not be clinically significant may still be statistically significant in a large enough trial. Contrastingly, a very large effect size that has biological plausibility, for instance, may not reach statistical significance if the trial size is not large enough [ 29 , 30 ]. This is highly problematic given the common misconceptions surrounding the p -value. Increasing emphasis is being placed on the importance of transparency in outcome reporting, and the reporting of confidence intervals to allow the reader to gauge the uncertainty in the evidence, and make a clinically informed decision about whether a finding is clinically significant or not. It has also been recommended that studies report FI where possible to provide readers with a comprehensible way of gauging the robustness of their findings [ 12 , 13 ]. There is a strive to make all data publicly available, allowing for replication of study findings as well as pooling of data among databases for generating more robust analyses using larger pragmatic samples [ 32 ]. Together, these efforts aim to increase transparency of research and facilitate data sharing to allow for stronger and more robust evidence to be produced, allowing for advancements in evidence-based medicine and improvements in the quality of care delivered to patients.

Our results suggest that approximately eight participants are needed to overturn the conclusions of the majority of trials in addiction medicine. Findings from our analysis of the literature and application of FI to the existing clinical trials in the field of addiction medicine demonstrates significant concerns regarding the overall quality and specifically robustness and stability of the evidence and the conclusions of the trials. Findings from this work raises larger concerns as to a growing body of evidence with deficiencies in both internal and external validity. In order to advance the field of addiction medicine, we must re-evaluate the quality of the evidence and consider employing pragmatic trial designs as well as transparent metrics to reflect the reliability and robustness of the findings. Placing emphasis on clinical relevance and reporting the FI along with confidence intervals may provide researchers, clinicians, and guideline developers with a transparent method to assess the outcomes from clinical trials, ensuring vigilance in decisions regarding management and treatment of patients with substance use disorders.

Availability of data and materials

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

Abbreviations

Interquartile range

• Opioid use disorder

Opioid substitution and antagonist therapies

• Randomized controlled trials

Risk of bias

Standard deviation

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

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Department of Family Medicine, David Braley Health Sciences Centre, McMaster University, 100 Main St W, 3rdFloor, Hamilton, ON, L8P 1H6, Canada

Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada

Leen Naji, Myanca Rodrigues, Andrew Worster, Lehana Thabane & Zainab Samaan

Department of Medicine, Montefiore Medical Center, New York, NY, USA

Department of Medicine, McMaster University, Hamilton, ON, Canada

Brittany Dennis & Andrew Worster

Department of Medicine, University of British Columbia, Vancouver, Canada

Brittany Dennis

Department of Medicine, Imperial College Healthcare NHS Trust, London, UK

Monica Bawor

Department of Psychiatry and Behavaioral Neurosciences, McMaster University, Hamilton, ON, Canada

Alannah Hillmer

Physician Assistant Program, University of Toronto, Toronto, ON, Canada

Caroul Chawar

Department of Family Medicine, Western University, London, ON, Canada

Department of Anesthesia, McMaster University, Hamilton, ON, Canada

Biostatistics Unit, Research Institute at St Joseph’s Healthcare, Hamilton, ON, Canada

Lehana Thabane

Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, ON, Canada

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Contributions

LN, BD, MB, LT, and ZS conceived the research question and protocol. LN, BD, MR, and AH designed the search strategy and ran the literature search. LN, BD, MR, AH, CC, and ED contributed to screening studies for eligibility and data extraction. LN and LT analyzed data. All authors contributed equally to the writing and revision of the manuscript. All authors approved the final version of the manuscript.

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Naji, L., Dennis, B., Rodrigues, M. et al. Assessing fragility of statistically significant findings from randomized controlled trials assessing pharmacological therapies for opioid use disorders: a systematic review. Trials 25 , 286 (2024). https://doi.org/10.1186/s13063-024-08104-x

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Received : 11 December 2022

Accepted : 10 April 2024

Published : 27 April 2024

DOI : https://doi.org/10.1186/s13063-024-08104-x

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