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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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• 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

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The Quintessence of Basic and Clinical Research and Scientific Publishing pp 717–731 Cite as

How to Present Results in a Research Paper

• Aparna Mukherjee 4 ,
• Gunjan Kumar 4 &
• Rakesh Lodha 5  
• First Online: 01 October 2023

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The results section is the core of a research manuscript where the study data and analyses are presented in an organized, uncluttered manner such that the reader can easily understand and interpret the findings. This section is completely factual; there is no place for opinions or explanations from the authors. The results should correspond to the objectives of the study in an orderly manner. Self-explanatory tables and figures add value to this section and make data presentation more convenient and appealing. The results presented in this section should have a link with both the preceding methods section and the following discussion section. A well-written, articulate results section lends clarity and credibility to the research paper and the study as a whole. This chapter provides an overview and important pointers to effective drafting of the results section in a research manuscript and also in theses.

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Acknowledgments

The book chapter is derived in part from our article “Mukherjee A, Lodha R. Writing the Results. Indian Pediatr. 2016 May 8;53(5):409-15.” We thank the Editor-in-Chief of the journal “Indian Pediatrics” for the permission for the same.

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Mukherjee, A., Kumar, G., Lodha, R. (2023). How to Present Results in a Research Paper. In: Jagadeesh, G., Balakumar, P., Senatore, F. (eds) The Quintessence of Basic and Clinical Research and Scientific Publishing. Springer, Singapore. https://doi.org/10.1007/978-981-99-1284-1_44

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Table of Contents

At its core, a research paper aims to fill a gap in the research on a given topic. As a result, the results section of the paper, which describes the key findings of the study, is often considered the core of the paper. This is the section that gets the most attention from reviewers, peers, students, and any news organization reporting on your findings. Writing a clear, concise, and logical results section is, therefore, one of the most important parts of preparing your manuscript.

Difference between results and discussion

Before delving into how to write the results section, it is important to first understand the difference between the results and discussion sections. The results section needs to detail the findings of the study. The aim of this section is not to draw connections between the different findings or to compare it to previous findings in literature—that is the purview of the discussion section. Unlike the discussion section, which can touch upon the hypothetical, the results section needs to focus on the purely factual. In some cases, it may even be preferable to club these two sections together into a single section. For example, while writing  a review article, it can be worthwhile to club these two sections together, as the main results in this case are the conclusions that can be drawn from the literature.

Structure of the results section

Although the main purpose of the results section in a research paper is to report the findings, it is necessary to present an introduction and repeat the research question. This establishes a connection to the previous section of the paper and creates a smooth flow of information.

Next, the results section needs to communicate the findings of your research in a systematic manner. The section needs to be organized such that the primary research question is addressed first, then the secondary research questions. If the research addresses multiple questions, the results section must individually connect with each of the questions. This ensures clarity and minimizes confusion while reading.

Consider representing your results visually. For example, graphs, tables, and other figures can help illustrate the findings of your paper, especially if there is a large amount of data in the results.

Remember, an appealing results section can help peer reviewers better understand the merits of your research, thereby increasing your chances of publication.

Practical guidance for writing an effective results section for a research paper

• Always use simple and clear language. Avoid the use of uncertain or out-of-focus expressions.
• The findings of the study must be expressed in an objective and unbiased manner. While it is acceptable to correlate certain findings in the discussion section, it is best to avoid overinterpreting the results.
• If the research addresses more than one hypothesis, use sub-sections to describe the results. This prevents confusion and promotes understanding.
• Ensure that negative results are included in this section, even if they do not support the research hypothesis.
• Wherever possible, use illustrations like tables, figures, charts, or other visual representations to showcase the results of your research paper. Mention these illustrations in the text, but do not repeat the information that they convey.
• For statistical data, it is adequate to highlight the tests and explain their results. The initial or raw data should not be mentioned in the results section of a research paper.

The results section of a research paper is usually the most impactful section because it draws the greatest attention. Regardless of the subject of your research paper, a well-written results section is capable of generating interest in your research.

For detailed information and assistance on writing the results of a research paper, refer to Elsevier Author Services.

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How to Write an Effective Results Section

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• 1 Rothman Orthopaedics Institute, Philadelphia, PA.
• PMID: 31145152
• DOI: 10.1097/BSD.0000000000000845

Developing a well-written research paper is an important step in completing a scientific study. This paper is where the principle investigator and co-authors report the purpose, methods, findings, and conclusions of the study. A key element of writing a research paper is to clearly and objectively report the study's findings in the Results section. The Results section is where the authors inform the readers about the findings from the statistical analysis of the data collected to operationalize the study hypothesis, optimally adding novel information to the collective knowledge on the subject matter. By utilizing clear, concise, and well-organized writing techniques and visual aids in the reporting of the data, the author is able to construct a case for the research question at hand even without interpreting the data.

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Writing a scientific paper.

• Writing a lab report
• INTRODUCTION

Writing a "good" results section

Figures and Captions in Lab Reports

"Results Checklist" from: How to Write a Good Scientific Paper. Chris A. Mack. SPIE. 2018.

Additional tips for results sections.

• LITERATURE CITED
• Bibliography of guides to scientific writing and presenting
• Peer Review
• Presentations
• Lab Report Writing Guides on the Web

This is the core of the paper. Don't start the results sections with methods you left out of the Materials and Methods section. You need to give an overall description of the experiments and present the data you found.

• Factual statements supported by evidence. Short and sweet without excess words
• Present representative data rather than endlessly repetitive data
• Discuss variables only if they had an effect (positive or negative)
• Use meaningful statistics
• Avoid redundancy. If it is in the tables or captions you may not need to repeat it

A short article by Dr. Brett Couch and Dr. Deena Wassenberg, Biology Program, University of Minnesota

• Present the results of the paper, in logical order, using tables and graphs as necessary.
• Explain the results and show how they help to answer the research questions posed in the Introduction. Evidence does not explain itself; the results must be presented and then explained. 
• Avoid: presenting results that are never discussed;  presenting results in chronological order rather than logical order; ignoring results that do not support the conclusions; 
• Number tables and figures separately beginning with 1 (i.e. Table 1, Table 2, Figure 1, etc.).
• Do not attempt to evaluate the results in this section. Report only what you found; hold all discussion of the significance of the results for the Discussion section.
• It is not necessary to describe every step of your statistical analyses. Scientists understand all about null hypotheses, rejection rules, and so forth and do not need to be reminded of them. Just say something like, "Honeybees did not use the flowers in proportion to their availability (X2 = 7.9, p<0.05, d.f.= 4, chi-square test)." Likewise, cite tables and figures without describing in detail how the data were manipulated. Explanations of this sort should appear in a legend or caption written on the same page as the figure or table.
• You must refer in the text to each figure or table you include in your paper.
• Tables generally should report summary-level data, such as means ± standard deviations, rather than all your raw data.  A long list of all your individual observations will mean much less than a few concise, easy-to-read tables or figures that bring out the main findings of your study.  
• Only use a figure (graph) when the data lend themselves to a good visual representation.  Avoid using figures that show too many variables or trends at once, because they can be hard to understand.

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Introduction, Methods and Results

Introduction.

The Introduction should provide readers with the background information needed to understand your study, and the reasons why you conducted your experiments. The Introduction should answer the question: what question/problem was studied?

While writing the background, make sure your citations are:

• Well balanced:  If experiments have found conflicting results on a question, have you cited studies with both kinds of results?
• Current:  Every field is different, but you should aim to cite references that are not more than 10 years old if possible. Although be sure to cite the first discovery or mention in the literature even if it older than 10 years.
• Relevant:  This is the most important requirement. The studies you cite should be strongly related to your research question.

TIP: Do not write a literature review in your Introduction, but do cite reviews where readers can find more information if they want it.

Once you have provided background material and stated the problem or question for your study, tell the reader the purpose of your study. Usually the reason is to fill a gap in the knowledge or to answer a previously unanswered question. For example, if a drug is known to work well in one population, but has never been tested in a different population, the purpose of a study could be to test the efficacy and safety of the drug in the second population.

The final thing to include at the end of your Introduction is a clear and exact statement of your study aims. You might also explain in a sentence or two how you conducted the study.

Materials and Methods

This section provides the reader with all the details of how you conducted your study. You should:

• Use  subheadings  to separate different methodologies
• Describe what you did in the  past tense
• Describe new methods in enough detail that another researcher can reproduce your experiment
• Describe established methods briefly, and simply cite a reference where readers can find more detail
• State  all  statistical tests and parameters

TIP: Check the ‘Instructions for Authors’ for your target journal to see how manuscripts should present the Materials and Methods. Also, as another guide, look at previously published papers in the journal or sample reports on the journal website.

In the Results section, simply state what you found, but  do not interpret the results or discuss their implications.

• As in the Materials and Methods section, use subheadings  to separate the results of different experiments.
• Results should be presented in a  logical order . In general this will be in order of importance, not necessarily the order in which the experiments were performed. Use the  past tense  to describe your results; however, refer to figures and tables in the present tense.
• Do not duplicate data  among figures, tables, and text. A common mistake is to re-state much of the data from a table in the text of the manuscript. Instead, use the text to summarize what the reader will find in the table, or mention one or two of the most important data points. It is usually much easier to read data in a table than in the text.
• Include  the results of statistical analyses  in the text, usually by providing p values wherever statistically significant differences are described.

TIP: There is a famous saying in English: “A picture is worth a thousand words.” This means that, sometimes, an image can explain your findings far better than text could. So make good use of figures and tables in your manuscript! However, avoid including redundant figures and tables (e.g. two showing the same thing in a different format), or using figures and tables where it would be better to just include the information in the text (e.g. where there is not enough data for a table or figure).

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How to Write an APA Results Section

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Verywell / Nusha Ashjaee 

What to Include in an APA Results Section

• Justify Claims
• Summarize Results

Report All Relevant Results

• Report Statistical Findings

Include Tables and Figures

What not to include in an apa results section.

Psychology papers generally follow a specific structure. One important section of a paper is known as the results section. An APA results section of a psychology paper summarizes the data that was collected and the statistical analyses that were performed. The goal of this section is to report the results of your study or experiment without any type of subjective interpretation.

At a Glance

The results section is a vital part of an APA paper that summarizes a study's findings and statistical analysis. This section often includes descriptive text, tables, and figures to help summarize the findings. The focus is purely on summarizing and presenting the findings and should not include any interpretation, since you'll cover that in the subsequent discussion section.

This article covers how to write an APA results section, including what to include and what to avoid.

The results section is the third section of a psychology paper. It will appear after the introduction and methods sections and before the discussion section.

The results section should include:

• A summary of the research findings.
• Information about participant flow, recruitment, retention, and attrition. If some participants started the study and later left or failed to complete the study, then this should be described. 
• Information about any reasons why some data might have been excluded from the study. 
• Statistical information including samples sizes and statistical tests that were used. It should report standard deviations, p-values, and other measures of interest.

Results Should Justify Your Claims

Report data in order to sufficiently justify your conclusions. Since you'll be talking about your own interpretation of the results in the discussion section, you need to be sure that the information reported in the results section justifies your claims.

When you start writing your discussion section, you can then look back on your results to ensure that all the data you need are there to fully support your conclusions. Be sure not to make claims in your discussion section that are not supported by the findings described in your results section.

Summarize Your Results

Remember, you are summarizing the results of your psychological study, not reporting them in full detail. The results section should be a relatively brief overview of your findings, not a complete presentation of every single number and calculation.

If you choose, you can create a supplemental online archive where other researchers can access the raw data if they choose.

How long should a results section be?

The length of your results section will vary depending on the nature of your paper and the complexity of your research. In most cases, this will be the shortest section of your paper.

Just as the results section of your psychology paper should sufficiently justify your claims, it should also provide an accurate look at what you found in your study. Be sure to mention all relevant information.

Don't omit findings simply because they failed to support your predictions.

Your hypothesis may have expected more statistically significant results or your study didn't support your hypothesis , but that doesn't mean that the conclusions you reach are not useful. Provide data about what you found in your results section, then save your interpretation for what the results might mean in the discussion section.

While your study might not have supported your original predictions, your finding can provide important inspiration for future explorations into a topic.

How is the results section different from the discussion section?

The results section provides the results of your study or experiment. The goal of the section is to report what happened and the statistical analyses you performed. The discussion section is where you will examine what these results mean and whether they support or fail to support your hypothesis.

Report Your Statistical Findings

Always assume that your readers have a solid understanding of statistical concepts. There's no need to explain what a t-test is or how a one-way ANOVA works. Your responsibility is to report the results of your study, not to teach your readers how to analyze or interpret statistics.

Include Effect Sizes

The Publication Manual of the American Psychological Association recommends including effect sizes in your results section so that readers can appreciate the importance of your study's findings.

Your results section should include both text and illustrations. Presenting data in this way makes it easier for readers to quickly look at your results.

Structure your results section around tables or figures that summarize the results of your statistical analysis. In many cases, the easiest way to accomplish this is to first create your tables and figures and then organize them in a logical way. Next, write the summary text to support your illustrative materials.

Only include tables and figures if you are going to talk about them in the body text of your results section.

In addition to knowing what you should include in the results section of your psychology paper, it's also important to be aware of things that you should avoid putting in this section:

Cause-and-Effect Conclusions

Don't draw cause-effect conclusions. Avoid making any claims suggesting that your result "proves" that something is true. 

Interpretations

Present the data without editorializing it. Save your comments and interpretations for the discussion section of your paper. 

Statistics Without Context

Don't include statistics without narration. The results section should not be a numbers dump. Instead, you should sequentially narrate what these numbers mean.

Don't include the raw data in the results section. The results section should be a concise presentation of the results. If there is raw data that would be useful, include it in the appendix .

Don't only rely on descriptive text. Use tables and figures to present these findings when appropriate. This makes the results section easier to read and can convey a great deal of information quickly.

Repeated Data

Don't present the same data twice in your illustrative materials. If you have already presented some data in a table, don't present it again in a figure. If you have presented data in a figure, don't present it again in a table.

All of Your Findings

Don't feel like you have to include everything. If data is irrelevant to the research question, don't include it in the results section.

But Don't Skip Relevant Data

Don't leave out results because they don't support your claims. Even if your data does not support your hypothesis, including it in your findings is essential if it's relevant.

More Tips for Writing a Results Section

If you are struggling, there are a few things to remember that might help:

• Use the past tense . The results section should be written in the past tense.
• Be concise and objective . You will have the opportunity to give your own interpretations of the results in the discussion section.
• Use APA format . As you are writing your results section, keep a style guide on hand. The Publication Manual of the American Psychological Association is the official source for APA style.
• Visit your library . Read some journal articles that are on your topic. Pay attention to how the authors present the results of their research.
• Get a second opinion . If possible, take your paper to your school's writing lab for additional assistance.

What This Means For You

Remember, the results section of your paper is all about providing the data from your study. This section is often the shortest part of your paper, and in most cases, the most clinical.

Be sure not to include any subjective interpretation of the results. Simply relay the data in the most objective and straightforward way possible. You can then provide your own analysis of what these results mean in the discussion section of your paper.

Bavdekar SB, Chandak S. Results: Unraveling the findings . J Assoc Physicians India . 2015 Sep;63(9):44-6. PMID:27608866.

Snyder N, Foltz C, Lendner M, Vaccaro AR. How to write an effective results section .  Clin Spine Surg . 2019;32(7):295-296. doi:10.1097/BSD.0000000000000845

American Psychological Association.  Publication Manual of the American Psychological Association  (7th ed.). Washington DC: The American Psychological Association; 2019.

Purdue Online Writing Lab. APA sample paper: Experimental psychology .

Berkeley University. Reviewing test results .

Tuncel A, Atan A. How to clearly articulate results and construct tables and figures in a scientific paper ? Turk J Urol . 2013;39(Suppl 1):16-19. doi:10.5152/tud.2013.048

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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How to Write the Results/Findings Section in Research

What is the research paper Results section and what does it do?

The Results section of a scientific research paper represents the core findings of a study derived from the methods applied to gather and analyze information. It presents these findings in a logical sequence without bias or interpretation from the author, setting up the reader for later interpretation and evaluation in the Discussion section. A major purpose of the Results section is to break down the data into sentences that show its significance to the research question(s).

The Results section appears third in the section sequence in most scientific papers. It follows the presentation of the Methods and Materials and is presented before the Discussion section —although the Results and Discussion are presented together in many journals. This section answers the basic question “What did you find in your research?”

What is included in the Results section?

The Results section should include the findings of your study and ONLY the findings of your study. The findings include:

• Data presented in tables, charts, graphs, and other figures (may be placed into the text or on separate pages at the end of the manuscript)
• A contextual analysis of this data explaining its meaning in sentence form
• All data that corresponds to the central research question(s)
• All secondary findings (secondary outcomes, subgroup analyses, etc.)

If the scope of the study is broad, or if you studied a variety of variables, or if the methodology used yields a wide range of different results, the author should present only those results that are most relevant to the research question stated in the Introduction section .

As a general rule, any information that does not present the direct findings or outcome of the study should be left out of this section. Unless the journal requests that authors combine the Results and Discussion sections, explanations and interpretations should be omitted from the Results.

How are the results organized?

The best way to organize your Results section is “logically.” One logical and clear method of organizing research results is to provide them alongside the research questions—within each research question, present the type of data that addresses that research question.

Let’s look at an example. Your research question is based on a survey among patients who were treated at a hospital and received postoperative care. Let’s say your first research question is:

“What do hospital patients over age 55 think about postoperative care?”

This can actually be represented as a heading within your Results section, though it might be presented as a statement rather than a question:

Attitudes towards postoperative care in patients over the age of 55

Now present the results that address this specific research question first. In this case, perhaps a table illustrating data from a survey. Likert items can be included in this example. Tables can also present standard deviations, probabilities, correlation matrices, etc.

Following this, present a content analysis, in words, of one end of the spectrum of the survey or data table. In our example case, start with the POSITIVE survey responses regarding postoperative care, using descriptive phrases. For example:

“Sixty-five percent of patients over 55 responded positively to the question “ Are you satisfied with your hospital’s postoperative care ?” (Fig. 2)

Include other results such as subcategory analyses. The amount of textual description used will depend on how much interpretation of tables and figures is necessary and how many examples the reader needs in order to understand the significance of your research findings.

Next, present a content analysis of another part of the spectrum of the same research question, perhaps the NEGATIVE or NEUTRAL responses to the survey. For instance:

  “As Figure 1 shows, 15 out of 60 patients in Group A responded negatively to Question 2.”

After you have assessed the data in one figure and explained it sufficiently, move on to your next research question. For example:

  “How does patient satisfaction correspond to in-hospital improvements made to postoperative care?”

This kind of data may be presented through a figure or set of figures (for instance, a paired T-test table).

Explain the data you present, here in a table, with a concise content analysis:

“The p-value for the comparison between the before and after groups of patients was .03% (Fig. 2), indicating that the greater the dissatisfaction among patients, the more frequent the improvements that were made to postoperative care.”

Let’s examine another example of a Results section from a study on plant tolerance to heavy metal stress . In the Introduction section, the aims of the study are presented as “determining the physiological and morphological responses of Allium cepa L. towards increased cadmium toxicity” and “evaluating its potential to accumulate the metal and its associated environmental consequences.” The Results section presents data showing how these aims are achieved in tables alongside a content analysis, beginning with an overview of the findings:

“Cadmium caused inhibition of root and leave elongation, with increasing effects at higher exposure doses (Fig. 1a-c).”

The figure containing this data is cited in parentheses. Note that this author has combined three graphs into one single figure. Separating the data into separate graphs focusing on specific aspects makes it easier for the reader to assess the findings, and consolidating this information into one figure saves space and makes it easy to locate the most relevant results.

Following this overall summary, the relevant data in the tables is broken down into greater detail in text form in the Results section.

• “Results on the bio-accumulation of cadmium were found to be the highest (17.5 mg kgG1) in the bulb, when the concentration of cadmium in the solution was 1×10G2 M and lowest (0.11 mg kgG1) in the leaves when the concentration was 1×10G3 M.”

Captioning and Referencing Tables and Figures

Tables and figures are central components of your Results section and you need to carefully think about the most effective way to use graphs and tables to present your findings . Therefore, it is crucial to know how to write strong figure captions and to refer to them within the text of the Results section.

The most important advice one can give here as well as throughout the paper is to check the requirements and standards of the journal to which you are submitting your work. Every journal has its own design and layout standards, which you can find in the author instructions on the target journal’s website. Perusing a journal’s published articles will also give you an idea of the proper number, size, and complexity of your figures.

Regardless of which format you use, the figures should be placed in the order they are referenced in the Results section and be as clear and easy to understand as possible. If there are multiple variables being considered (within one or more research questions), it can be a good idea to split these up into separate figures. Subsequently, these can be referenced and analyzed under separate headings and paragraphs in the text.

To create a caption, consider the research question being asked and change it into a phrase. For instance, if one question is “Which color did participants choose?”, the caption might be “Color choice by participant group.” Or in our last research paper example, where the question was “What is the concentration of cadmium in different parts of the onion after 14 days?” the caption reads:

 “Fig. 1(a-c): Mean concentration of Cd determined in (a) bulbs, (b) leaves, and (c) roots of onions after a 14-day period.”

Steps for Composing the Results Section

Because each study is unique, there is no one-size-fits-all approach when it comes to designing a strategy for structuring and writing the section of a research paper where findings are presented. The content and layout of this section will be determined by the specific area of research, the design of the study and its particular methodologies, and the guidelines of the target journal and its editors. However, the following steps can be used to compose the results of most scientific research studies and are essential for researchers who are new to preparing a manuscript for publication or who need a reminder of how to construct the Results section.

Step 1 : Consult the guidelines or instructions that the target journal or publisher provides authors and read research papers it has published, especially those with similar topics, methods, or results to your study.

• The guidelines will generally outline specific requirements for the results or findings section, and the published articles will provide sound examples of successful approaches.
• Note length limitations on restrictions on content. For instance, while many journals require the Results and Discussion sections to be separate, others do not—qualitative research papers often include results and interpretations in the same section (“Results and Discussion”).
• Reading the aims and scope in the journal’s “ guide for authors ” section and understanding the interests of its readers will be invaluable in preparing to write the Results section.

Step 2 : Consider your research results in relation to the journal’s requirements and catalogue your results.

• Focus on experimental results and other findings that are especially relevant to your research questions and objectives and include them even if they are unexpected or do not support your ideas and hypotheses.
• Catalogue your findings—use subheadings to streamline and clarify your report. This will help you avoid excessive and peripheral details as you write and also help your reader understand and remember your findings. Create appendices that might interest specialists but prove too long or distracting for other readers.
• Decide how you will structure of your results. You might match the order of the research questions and hypotheses to your results, or you could arrange them according to the order presented in the Methods section. A chronological order or even a hierarchy of importance or meaningful grouping of main themes or categories might prove effective. Consider your audience, evidence, and most importantly, the objectives of your research when choosing a structure for presenting your findings.

Step 3 : Design figures and tables to present and illustrate your data.

• Tables and figures should be numbered according to the order in which they are mentioned in the main text of the paper.
• Information in figures should be relatively self-explanatory (with the aid of captions), and their design should include all definitions and other information necessary for readers to understand the findings without reading all of the text.
• Use tables and figures as a focal point to tell a clear and informative story about your research and avoid repeating information. But remember that while figures clarify and enhance the text, they cannot replace it.

Step 4 : Draft your Results section using the findings and figures you have organized.

• The goal is to communicate this complex information as clearly and precisely as possible; precise and compact phrases and sentences are most effective.
• In the opening paragraph of this section, restate your research questions or aims to focus the reader’s attention to what the results are trying to show. It is also a good idea to summarize key findings at the end of this section to create a logical transition to the interpretation and discussion that follows.
• Try to write in the past tense and the active voice to relay the findings since the research has already been done and the agent is usually clear. This will ensure that your explanations are also clear and logical.
• Make sure that any specialized terminology or abbreviation you have used here has been defined and clarified in the  Introduction section .

Step 5 : Review your draft; edit and revise until it reports results exactly as you would like to have them reported to your readers.

• Double-check the accuracy and consistency of all the data, as well as all of the visual elements included.
• Read your draft aloud to catch language errors (grammar, spelling, and mechanics), awkward phrases, and missing transitions.
• Ensure that your results are presented in the best order to focus on objectives and prepare readers for interpretations, valuations, and recommendations in the Discussion section . Look back over the paper’s Introduction and background while anticipating the Discussion and Conclusion sections to ensure that the presentation of your results is consistent and effective.
• Consider seeking additional guidance on your paper. Find additional readers to look over your Results section and see if it can be improved in any way. Peers, professors, or qualified experts can provide valuable insights.

One excellent option is to use a professional English proofreading and editing service  such as Wordvice, including our paper editing service . With hundreds of qualified editors from dozens of scientific fields, Wordvice has helped thousands of authors revise their manuscripts and get accepted into their target journals. Read more about the  proofreading and editing process  before proceeding with getting academic editing services and manuscript editing services for your manuscript.

As the representation of your study’s data output, the Results section presents the core information in your research paper. By writing with clarity and conciseness and by highlighting and explaining the crucial findings of their study, authors increase the impact and effectiveness of their research manuscripts.

For more articles and videos on writing your research manuscript, visit Wordvice’s Resources page.

Wordvice Resources

• How to Write a Research Paper Introduction 
• Which Verb Tenses to Use in a Research Paper
• How to Write an Abstract for a Research Paper
• How to Write a Research Paper Title
• Useful Phrases for Academic Writing
• Common Transition Terms in Academic Papers
• Active and Passive Voice in Research Papers
• 100+ Verbs That Will Make Your Research Writing Amazing
• Tips for Paraphrasing in Research Papers

Organizing Academic Research Papers: 7. The Results

• Purpose of Guide
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• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
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• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
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• Acknowledgements

The results section of the research paper is where you report the findings of your study based upon the information gathered as a result of the methodology [or methodologies] you applied. The results section should simply state the findings, without bias or interpretation, and arranged in a logical sequence. The results section should always be written in the past tense. A section describing results [a.k.a., "findings"] is particularly necessary if your paper includes data generated from your own research.

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 . Research results can only confirm or reject the research problem 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, using non-textual elements, such as figures and tables, if appropriate, to present results more effectively. In deciding what data to describe in your results section, you must clearly distinguish material that would normally be included in a research paper from any raw data or other material that could be included as an appendix. In general, raw data 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 rule 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].

Bates College; 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.

Structure and Writing Style

I. Structure and Approach

For most research paper formats, there are two ways of presenting and organizing the results .

• Present the results followed by a short explanation of the findings . For example, you may have noticed an unusual correlation between two variables during the analysis of your findings. It is correct to point this out 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 section and then discuss it, before presenting the next section then discussing it, and so on . This is more common in longer papers because it helps the reader to better understand each finding. In this model, it can be helpful to provide a brief conclusion in the results section that ties each of the findings together and links to the discussion.

NOTE: The discussion section should generally follow the same format chosen in presenting and organizing the results.

II.  Content

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

• An introductory context for understanding the results by restating the research problem that underpins the purpose of your study.
• A summary of your key findings arranged in a logical sequence that generally follows your methodology section.
• Inclusion of non-textual elements, such as, figures, charts, photos, maps, tables, etc. to further illustrate the findings, if appropriate.
• In the text, a systematic description of your results, highlighting for the reader observations that are most relevant to the topic under investigation [remember that not all results that emerge from the methodology that you used to gather the data may be relevant].
• Use of the past tense when refering to your results.
• The page length of your results section is guided by the amount and types of data to be reported. However, focus only on findings that are important and related to addressing the research problem.

Using Non-textual Elements

• Either place figures, tables, charts, etc. within the text of the result, or include them in the back of the report--do one or the other but never do both.
• In the text, refer to each non-textual element in numbered order [e.g.,  Table 1, Table 2; Chart 1, Chart 2; Map 1, Map 2].
• If you place non-textual elements at the end of the report, make sure they are clearly distinguished from any attached appendix materials, such as raw data.
• Regardless of placement, each non-textual element must be numbered consecutively and complete with caption [caption goes under the figure, table, chart, etc.]
• Each non-textual element must be titled, numbered consecutively, and complete with a heading [title with description goes above the figure, table, chart, etc.].
• In proofreading your results section, be sure that each non-textual element is sufficiently complete so that it could stand on its own, separate from the text.

III. Problems to Avoid

When writing the results section, avoid doing the following :

• Discussing or interpreting your results . Save all this for the next section of your paper, although where appropriate, you should compare or contrast specific results to those found in other studies [e.g., "Similar to 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 to provide additional background information or to explain the topic further, so don't think you did something wrong. Revise your introduction as needed.
• Ignoring negative results . If some of your results fail to support your hypothesis, do not ignore them. Document them, 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, often provides you with the opportunity to write a more engaging discussion section, therefore, don't be afraid 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 or lesser than..." or "demonstrates promising trends that...."
• Presenting the same data or repeating the same information more than once . If you feel the need to highlight something, you will have a chance to do that in the discussion section.
• Confusing figures with tables . Be sure to properly label any non-textual elements in your paper. If you are not sure, look up the term in a dictionary.

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); 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 social science journals where the author(s) have combined a description of the findings from the study with a discussion about their implications. You could do this. However, if you are inexperienced writing research papers, consider creating two sections for each element 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 your data and answer the "so what?" question. As you become more skilled writing research papers, you may want to meld the results of your study with a discussion of its implications.

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How to Write the Results Section of a Research Paper

Table of Contents

Laura Moro-Martin, freelance scientific writer on Kolabtree, provides expert tips on how to write the results section of a research paper . 

You have prepared a detailed −but concise− Methods section . Now it is time to write the Results of your research article. This part of the paper reports the findings of the experiments that you conducted to answer the research question(s). The Results can be considered the nucleus of a scientific article because they justify your claims, so you need to ensure that they are clear and understandable. You are telling a story −of course, a scientific story− and you want the readers to picture that same story in their minds. Let’s see how to avoid that your message ends up as in the ‘telephone game’.

The Results Section: Goals and Structure

Depending on the discipline, journal, and the nature of the study, the structure of the article can differ. We will focus on articles were the Results and Discussion appear in two separate sections, but it is possible in some cases to combine them.

In the Results section, you provide an overall description of the experiments and present the data that you obtained in a logical order, using tables and graphs as necessary. The Results section should simply state your findings without bias or interpretation. For example, in your analysis, you may have noticed a significant correlation between two variables never described before. It is correct to explain this in the Results section. However, speculation about the reasons for this correlation should go in the Discussion section of your paper.

In general, the Results section includes the following elements:

• A very short introductory context that repeats the research question and helps to understand your results.
• Report on data collection, recruitment, and/or participants. For example, in the case of clinical research, it is common to include a first table summarizing the demographic, clinical, and other relevant characteristics of the study participants.
• A systematic description of the main findings in a logical order (generally following the order of the Methods section), highlighting the most relevant results.
• Other important secondary findings, such as secondary outcomes or subgroup analyses (remember that you do not need to mention any single result).
• Visual elements, such as, figures, charts, maps, tables, etc. that summarize and illustrate the findings. These elements should be cited in the text and numbered in order. Figures and tables should be able to stand on its own without the text, which means that the legend should include enough information to understand the non-textual element.

How to Write the Results Section of a Research Paper: Tips

The first tip −applicable to other sections of the paper too− is to check and apply the requirements of the journal to which you are submitting your work.

In the Results section, you need to write concisely and objectively, leaving interpretation for the Discussion section. As always, ‘learning from others’ can help you. Select a few papers from your field, including some published in your target journal, which you consider ‘good quality’ and well written. Read them carefully and observe how the Results section is structured, the type and amount of information provided, and how the findings are exposed in a logical order. Keep an eye on visual elements, such as figures, tables, and supplementary materials. Understand what works well in those papers to effectively convey their findings, and apply it to your writing.

Your Results section needs to describe the sequence of what you did and found, the frequency of occurrence of a particular event or result, the quantities of your observations, and the causality (i.e. the relationships or connections) between the events that you observed.

To organize the results, you can try to provide them alongside the research questions. In practice, this means that you will organize this section based on the sequence of tables and figures summarizing the results of your statistical analysis. In this way, it will be easier for readers to look at and understand your findings. You need to report your statistical findings, without describing every step of your statistical analysis. Tables and figures generally report summary-level data (for example, means and standard deviations), rather than all the raw data.

Following, you can prepare the summary text to support those visual elements. You need not only to present but also to explain your findings, showing how they help to address the research question(s) and how they align with the objectives that you presented in the Introduction . Keep in mind that results do not speak for themselves, so if you do not describe them in words, the reader may perceive the findings differently from you. Build coherence along this section using goal statements and explicit reasoning (guide the reader through your reasoning, including sentences of this type: ‘In order to…, we performed….’; ‘In view of this result, we ….’, etc.).

In summary, the general steps for writing the Results section of a research article are:

• Check the guidelines of your target journal and read articles that it has published in similar topics to your study.
• Catalogue your findings in relation to the journal requirements, and design figures and tables to organize your data.
• Write the Results section following the order of figures and tables.
• Edit and revise your draft and seek additional input from colleagues or experts.

The Style of the Results Section

‘If you are out to describe the truth, leave elegance to the tailor’, Austrian physicist Ludwig Boltzmann said. Although the scope of the Results section −and of scientific papers in general− is eminently functional, this does not mean that you cannot write well. Try to improve the rhythm to move the reader along, use transitions and connectors between different sections and paragraphs, and dedicate time to revise your writing.

The Results section should be written in the past tense. Although writing in the passive voice may be tempting, the use of the active voice makes the action much more visualizable. The passive voice weakens the power of language and increases the number of words needed to say the same thing, so we recommend using the active voice as much as possible. Another tip to make your language visualizable and reduce sentence length is the use of verbal phrases instead of long nouns. For example, instead of writing ‘As shown in Table 1, there was a significant increase in gene expression’, you can say ‘As shown in Table 1, gene expression increased significantly’.

Get a Second (And Even Third) Opinion

Writing a scientific article is not an individual work. Take advantage of your co-authors by making them check the Results section and adding their comments and suggestions. Not only that, but an external opinion will help you to identify misinterpretations or errors. Ask a colleague that is not directly involved in the work to review your Results and then try to evaluate what your colleague did or did not understand. If needed, seek additional help from a qualified expert.

Common Errors to Avoid While Writing the Results Section

Several mistakes frequently occur when you write the Results section of a research paper. Here we have collected a few examples:

• Including raw results and/or endlessly repetitive data. You do not need to present every single number and calculation, but a summary of the results. If relevant, raw data can be included in supplementary materials.
• Including redundant information. If data are contained in the tables or figures, you do not need to repeat all of them in the Results section. You will have the opportunity to highlight the most relevant results in the Discussion .
• Repeating background information or methods , or introducing several sentences of introductory information (if you feel that more background information is necessary to present a result, consider inserting that information in the Introduction ).
• Results and Methods do not match . You need to explain the methodology used to obtain all the experimental observations.
• Ignoring negative results or results that do not support the conclusions. In addition to posing potential ethical concerns on your work, reviewers will not like it. You need to mention all relevant findings, even if they failed to support your predictions or hypotheses. Negative results are useful and will guide future studies on the topic. Provide your interpretation for negative results in the Discussion .
• Discussing or interpreting the results . Leave that for the Discussion , unless your target journal allows preparing one section combining Results and Discussion .
• Errors in figures/tables are varied and common . Examples of errors include using an excessive number of figures/tables (it is a good idea to select the most relevant ones and move the rest to supplementary materials), very complex figures/tables (hard-to-read figures with many subfigures or enormous tables may confuse your readers; think how these elements will be visualized in the final format of the article), difficult to interpret figures/tables (cryptic abbreviations; inadequate use of colors, axis, scales, symbols, etc.), and figures/tables that are not self-standing (figures/tables require a caption, all abbreviations used need to be explained in the legend or a footnote, and statistical tests applied are frequently reported). Do not include tables and figures that are not mentioned in the body text of your Results .

In summary, the Results section is the nucleus of your paper that justifies your claims. Take time to adequately organize it and prepare understandable figures and tables to convey your message to the reader. Good writing!

• The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. https://abacus.bates.edu/~ganderso/biology/resources/writing/HTWsections.html – methods (accessed on 30th September 2020)
• Organizing Academic Research Papers: 7. The Results. https://library.sacredheart.edu/c.php?g=29803&p=185931 (accessed on 30th September 2020)
• Kendra Cherry. How to Write an APA Results Section. https://www.verywellmind.com/how-to-write-a-results-section-2795727 (accessed on 30th September 2020)
• Chapin Rodríguez. Empowering your scientific language by making it “visualizable”. http://creaducate.eu/wp-content/uploads/2019/11/tipsheet36_visualizable-lang-tip-sheet.pdf (accessed on 1st October 2020)
• IMRaD Results Discussion. https://writingcenter.gmu.edu/guides/imrad-results-discussion (accessed on 1st October 2020)
• Writing the Results Section for a Research Paper. https://wordvice.com/writing-the-results-section-for-a-research-paper/ (accessed on 1st October 2020)
• Scott L. Montgomery. The Chicago Guide to Communicating Science , Chapter 9. Second edition, The University of Chicago Press, 2017.
• Hilary Glasman-Deal . Science Research Writing for Non-Native Speakers of English, Unit 2 . Imperial College Press, 2010.

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Ramya Sriram manages digital content and communications at Kolabtree (kolabtree.com), the world's largest freelancing platform for scientists. She has over a decade of experience in publishing, advertising and digital content creation.

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How To Write The Results/Findings Chapter

For quantitative studies (dissertations & theses).

By: Derek Jansen (MBA). Expert Reviewed By: Kerryn Warren (PhD) | July 2021

So, you’ve completed your quantitative data analysis and it’s time to report on your findings. But where do you start? In this post, we’ll walk you through the results chapter (also called the findings or analysis chapter), step by step, so that you can craft this section of your dissertation or thesis with confidence. If you’re looking for information regarding the results chapter for qualitative studies, you can find that here .

Overview: Quantitative Results Chapter

• What exactly the results/findings/analysis chapter is
• What you need to include in your results chapter
• How to structure your results chapter
• A few tips and tricks for writing top-notch chapter

What exactly is the results chapter?

The results chapter (also referred to as the findings or analysis chapter) is one of the most important chapters of your dissertation or thesis because it shows the reader what you’ve found in terms of the quantitative data you’ve collected. It presents the data using a clear text narrative, supported by tables, graphs and charts. In doing so, it also highlights any potential issues (such as outliers or unusual findings) you’ve come across.

But how’s that different from the discussion chapter?

Well, in the results chapter, you only present your statistical findings. Only the numbers, so to speak – no more, no less. Contrasted to this, in the discussion chapter , you interpret your findings and link them to prior research (i.e. your literature review), as well as your research objectives and research questions . In other words, the results chapter presents and describes the data, while the discussion chapter interprets the data.

Let’s look at an example.

In your results chapter, you may have a plot that shows how respondents to a survey  responded: the numbers of respondents per category, for instance. You may also state whether this supports a hypothesis by using a p-value from a statistical test. But it is only in the discussion chapter where you will say why this is relevant or how it compares with the literature or the broader picture. So, in your results chapter, make sure that you don’t present anything other than the hard facts – this is not the place for subjectivity.

It’s worth mentioning that some universities prefer you to combine the results and discussion chapters. Even so, it is good practice to separate the results and discussion elements within the chapter, as this ensures your findings are fully described. Typically, though, the results and discussion chapters are split up in quantitative studies. If you’re unsure, chat with your research supervisor or chair to find out what their preference is.

What should you include in the results chapter?

Following your analysis, it’s likely you’ll have far more data than are necessary to include in your chapter. In all likelihood, you’ll have a mountain of SPSS or R output data, and it’s your job to decide what’s most relevant. You’ll need to cut through the noise and focus on the data that matters.

This doesn’t mean that those analyses were a waste of time – on the contrary, those analyses ensure that you have a good understanding of your dataset and how to interpret it. However, that doesn’t mean your reader or examiner needs to see the 165 histograms you created! Relevance is key.

How do I decide what’s relevant?

At this point, it can be difficult to strike a balance between what is and isn’t important. But the most important thing is to ensure your results reflect and align with the purpose of your study .  So, you need to revisit your research aims, objectives and research questions and use these as a litmus test for relevance. Make sure that you refer back to these constantly when writing up your chapter so that you stay on track.

As a general guide, your results chapter will typically include the following:

• Some demographic data about your sample
• Reliability tests (if you used measurement scales)
• Descriptive statistics
• Inferential statistics (if your research objectives and questions require these)
• Hypothesis tests (again, if your research objectives and questions require these)

We’ll discuss each of these points in more detail in the next section.

Importantly, your results chapter needs to lay the foundation for your discussion chapter . This means that, in your results chapter, you need to include all the data that you will use as the basis for your interpretation in the discussion chapter.

For example, if you plan to highlight the strong relationship between Variable X and Variable Y in your discussion chapter, you need to present the respective analysis in your results chapter – perhaps a correlation or regression analysis.

Need a helping hand?

How do I write the results chapter?

There are multiple steps involved in writing up the results chapter for your quantitative research. The exact number of steps applicable to you will vary from study to study and will depend on the nature of the research aims, objectives and research questions . However, we’ll outline the generic steps below.

Step 1 – Revisit your research questions

The first step in writing your results chapter is to revisit your research objectives and research questions . These will be (or at least, should be!) the driving force behind your results and discussion chapters, so you need to review them and then ask yourself which statistical analyses and tests (from your mountain of data) would specifically help you address these . For each research objective and research question, list the specific piece (or pieces) of analysis that address it.

At this stage, it’s also useful to think about the key points that you want to raise in your discussion chapter and note these down so that you have a clear reminder of which data points and analyses you want to highlight in the results chapter. Again, list your points and then list the specific piece of analysis that addresses each point. 

Next, you should draw up a rough outline of how you plan to structure your chapter . Which analyses and statistical tests will you present and in what order? We’ll discuss the “standard structure” in more detail later, but it’s worth mentioning now that it’s always useful to draw up a rough outline before you start writing (this advice applies to any chapter).

Step 2 – Craft an overview introduction

As with all chapters in your dissertation or thesis, you should start your quantitative results chapter by providing a brief overview of what you’ll do in the chapter and why . For example, you’d explain that you will start by presenting demographic data to understand the representativeness of the sample, before moving onto X, Y and Z.

This section shouldn’t be lengthy – a paragraph or two maximum. Also, it’s a good idea to weave the research questions into this section so that there’s a golden thread that runs through the document.

Step 3 – Present the sample demographic data

The first set of data that you’ll present is an overview of the sample demographics – in other words, the demographics of your respondents.

For example:

• What age range are they?
• How is gender distributed?
• How is ethnicity distributed?
• What areas do the participants live in?

The purpose of this is to assess how representative the sample is of the broader population. This is important for the sake of the generalisability of the results. If your sample is not representative of the population, you will not be able to generalise your findings. This is not necessarily the end of the world, but it is a limitation you’ll need to acknowledge.

Of course, to make this representativeness assessment, you’ll need to have a clear view of the demographics of the population. So, make sure that you design your survey to capture the correct demographic information that you will compare your sample to.

But what if I’m not interested in generalisability?

Well, even if your purpose is not necessarily to extrapolate your findings to the broader population, understanding your sample will allow you to interpret your findings appropriately, considering who responded. In other words, it will help you contextualise your findings . For example, if 80% of your sample was aged over 65, this may be a significant contextual factor to consider when interpreting the data. Therefore, it’s important to understand and present the demographic data.

 Step 4 – Review composite measures and the data “shape”.

Before you undertake any statistical analysis, you’ll need to do some checks to ensure that your data are suitable for the analysis methods and techniques you plan to use. If you try to analyse data that doesn’t meet the assumptions of a specific statistical technique, your results will be largely meaningless. Therefore, you may need to show that the methods and techniques you’ll use are “allowed”.

Most commonly, there are two areas you need to pay attention to:

#1: Composite measures

The first is when you have multiple scale-based measures that combine to capture one construct – this is called a composite measure .  For example, you may have four Likert scale-based measures that (should) all measure the same thing, but in different ways. In other words, in a survey, these four scales should all receive similar ratings. This is called “ internal consistency ”.

Internal consistency is not guaranteed though (especially if you developed the measures yourself), so you need to assess the reliability of each composite measure using a test. Typically, Cronbach’s Alpha is a common test used to assess internal consistency – i.e., to show that the items you’re combining are more or less saying the same thing. A high alpha score means that your measure is internally consistent. A low alpha score means you may need to consider scrapping one or more of the measures.

#2: Data shape

The second matter that you should address early on in your results chapter is data shape. In other words, you need to assess whether the data in your set are symmetrical (i.e. normally distributed) or not, as this will directly impact what type of analyses you can use. For many common inferential tests such as T-tests or ANOVAs (we’ll discuss these a bit later), your data needs to be normally distributed. If it’s not, you’ll need to adjust your strategy and use alternative tests.

To assess the shape of the data, you’ll usually assess a variety of descriptive statistics (such as the mean, median and skewness), which is what we’ll look at next.

Step 5 – Present the descriptive statistics

Now that you’ve laid the foundation by discussing the representativeness of your sample, as well as the reliability of your measures and the shape of your data, you can get started with the actual statistical analysis. The first step is to present the descriptive statistics for your variables.

For scaled data, this usually includes statistics such as:

• The mean – this is simply the mathematical average of a range of numbers.
• The median – this is the midpoint in a range of numbers when the numbers are arranged in order.
• The mode – this is the most commonly repeated number in the data set.
• Standard deviation – this metric indicates how dispersed a range of numbers is. In other words, how close all the numbers are to the mean (the average).
• Skewness – this indicates how symmetrical a range of numbers is. In other words, do they tend to cluster into a smooth bell curve shape in the middle of the graph (this is called a normal or parametric distribution), or do they lean to the left or right (this is called a non-normal or non-parametric distribution).
• Kurtosis – this metric indicates whether the data are heavily or lightly-tailed, relative to the normal distribution. In other words, how peaked or flat the distribution is.

A large table that indicates all the above for multiple variables can be a very effective way to present your data economically. You can also use colour coding to help make the data more easily digestible.

For categorical data, where you show the percentage of people who chose or fit into a category, for instance, you can either just plain describe the percentages or numbers of people who responded to something or use graphs and charts (such as bar graphs and pie charts) to present your data in this section of the chapter.

When using figures, make sure that you label them simply and clearly , so that your reader can easily understand them. There’s nothing more frustrating than a graph that’s missing axis labels! Keep in mind that although you’ll be presenting charts and graphs, your text content needs to present a clear narrative that can stand on its own. In other words, don’t rely purely on your figures and tables to convey your key points: highlight the crucial trends and values in the text. Figures and tables should complement the writing, not carry it .

Depending on your research aims, objectives and research questions, you may stop your analysis at this point (i.e. descriptive statistics). However, if your study requires inferential statistics, then it’s time to deep dive into those .

Step 6 – Present the inferential statistics

Inferential statistics are used to make generalisations about a population , whereas descriptive statistics focus purely on the sample . Inferential statistical techniques, broadly speaking, can be broken down into two groups .

First, there are those that compare measurements between groups , such as t-tests (which measure differences between two groups) and ANOVAs (which measure differences between multiple groups). Second, there are techniques that assess the relationships between variables , such as correlation analysis and regression analysis. Within each of these, some tests can be used for normally distributed (parametric) data and some tests are designed specifically for use on non-parametric data.

There are a seemingly endless number of tests that you can use to crunch your data, so it’s easy to run down a rabbit hole and end up with piles of test data. Ultimately, the most important thing is to make sure that you adopt the tests and techniques that allow you to achieve your research objectives and answer your research questions .

In this section of the results chapter, you should try to make use of figures and visual components as effectively as possible. For example, if you present a correlation table, use colour coding to highlight the significance of the correlation values, or scatterplots to visually demonstrate what the trend is. The easier you make it for your reader to digest your findings, the more effectively you’ll be able to make your arguments in the next chapter.

Step 7 – Test your hypotheses

If your study requires it, the next stage is hypothesis testing. A hypothesis is a statement , often indicating a difference between groups or relationship between variables, that can be supported or rejected by a statistical test. However, not all studies will involve hypotheses (again, it depends on the research objectives), so don’t feel like you “must” present and test hypotheses just because you’re undertaking quantitative research.

The basic process for hypothesis testing is as follows:

• Specify your null hypothesis (for example, “The chemical psilocybin has no effect on time perception).
• Specify your alternative hypothesis (e.g., “The chemical psilocybin has an effect on time perception)
• Set your significance level (this is usually 0.05)
• Calculate your statistics and find your p-value (e.g., p=0.01)
• Draw your conclusions (e.g., “The chemical psilocybin does have an effect on time perception”)

Finally, if the aim of your study is to develop and test a conceptual framework , this is the time to present it, following the testing of your hypotheses. While you don’t need to develop or discuss these findings further in the results chapter, indicating whether the tests (and their p-values) support or reject the hypotheses is crucial.

Step 8 – Provide a chapter summary

To wrap up your results chapter and transition to the discussion chapter, you should provide a brief summary of the key findings . “Brief” is the keyword here – much like the chapter introduction, this shouldn’t be lengthy – a paragraph or two maximum. Highlight the findings most relevant to your research objectives and research questions, and wrap it up.

Some final thoughts, tips and tricks

Now that you’ve got the essentials down, here are a few tips and tricks to make your quantitative results chapter shine:

• When writing your results chapter, report your findings in the past tense . You’re talking about what you’ve found in your data, not what you are currently looking for or trying to find.
• Structure your results chapter systematically and sequentially . If you had two experiments where findings from the one generated inputs into the other, report on them in order.
• Make your own tables and graphs rather than copying and pasting them from statistical analysis programmes like SPSS. Check out the DataIsBeautiful reddit for some inspiration.
• Once you’re done writing, review your work to make sure that you have provided enough information to answer your research questions , but also that you didn’t include superfluous information.

If you’ve got any questions about writing up the quantitative results chapter, please leave a comment below. If you’d like 1-on-1 assistance with your quantitative analysis and discussion, check out our hands-on coaching service , or book a free consultation with a friendly coach.

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Thank you. I will try my best to write my results.

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this was great explaination

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• Indian J Anaesth
• v.60(9); 2016 Sep

Interpretation and display of research results

Dilip kumar kulkarni.

Department of Anaesthesiology and Intensive Care, Nizam's Institute of Medical Sciences, Hyderabad, Telangana, India

It important to properly collect, code, clean and edit the data before interpreting and displaying the research results. Computers play a major role in different phases of research starting from conceptual, design and planning, data collection, data analysis and research publication phases. The main objective of data display is to summarize the characteristics of a data and to make the data more comprehensible and meaningful. Usually data is presented depending upon the type of data in different tables and graphs. This will enable not only to understand the data behaviour, but also useful in choosing the different statistical tests to be applied.

INTRODUCTION

Collection of data and display of results is very important in any study. The data of an experimental study, observational study or a survey are required to be collected in properly designed format for documentation, taking into consideration the design of study and different end points of the study. Usually data are collected in the proforma of the study. The data recorded and documented should be stored carefully in documents and in electronic form for example, excel sheets or data bases.

The data are usually classified into qualitative and quantitative [ Table 1 ]. Qualitative data is further divided into two categories, unordered qualitative data, such as blood groups (A, B, O, AB); and ordered qualitative data, such as severity of pain (mild, moderate, severe). Quantitative data are numerical and fall into two categories: discrete quantitative data, such as the internal diameter of endotracheal tube; and continuous quantitative data, such as blood pressure.[ 1 ]

Examples of types of data and display of data

Data Coding is needed to allow the data recorded in categories to be used easily in statistical analysis with a computer. Coding assigns a unique number to each possible response. A few statistical packages analyse categorical data directly. If a number is assigned to categorical data, it becomes easier to analyse. This means that when the data are analysed and reported, the appropriate label needs to be assigned back to the numerical value to make it meaningful. The codes such as 1/0 for yes/no has the added advantage that the variable's 1/0 values can be easily analysed. The record of the codes modified is to be stored for later reference. Such coding can also be done for categorical ordinal data to convert in to numerical ordinal data, for example the severity of pain mild, moderate and severe into 1, 2 and 3 respectively.

PROCESS OF DATA CHECKING, CLEANING AND EDITING

In clinical research, errors occur despite designing the study properly, entering data carefully and preventing errors. Data cleaning and editing are carried out to identify and correct these errors, so that the study results will be accurate.[ 2 ]

Data entry errors in case of sex, dates, double entries and unexpected results are to be corrected unquestionably. Data editing can be done in three phases namely screening, diagnosing and editing [ Figure 1 ].

Process of data checking, cleaning and editing in three phases

Screening phase

During screening of data, it is possible to distinguish the odd data, excess of data, double entries, outliers, and unexpected results. Screening methods are checking of questionnaires, data validation, browsing the excel sheets, data tables and graphical methods to observe data distribution.

Diagnostic phase

The nature of the data can be assessed in this phase. The data entries can be true normal, true errors, outliers, unexpected results.

Treatment phase

Once the data nature is identified the editing can be done by correcting, deleting or leaving the data sets unchanged.

The abnormal data points usually have to be corrected or to be deleted.[ 2 ] However some authors advocate these data points to be included in analysis.[ 3 ] If these extreme data points are deleted, they should be reported as “excluded from analysis”.[ 4 ]

ROLE OF COMPUTERS IN RESEARCH

The role of computers in scientific research is very high; the computers have the ability to perform the analytic tasks with high speed, accuracy and consistency. The Computers role in research process can be explained in different phases.[ 5 ]

Role of computer in conceptual phase

The conceptual phase consists of formulation of research problem, literature survey, theoretical frame work and developing the hypothesis. Computers are useful in searching the literatures. The references can be stored in the electronic database.

Role of computers in design and planning phase

This phase consists of research design preparation and determining sample design, population size, research variables, sampling plan, reviewing research plan and pilot study. The role of computers in these process is almost indispensable.

Role of computers in data collection phase

The data obtained from the subjects stored in computers are word files or excel spread sheets or statistical software data files or from data centers of hospital information management systems (data warehouse). If the data are stored in electronic format checking the data becomes easier. Thus, computers help in data entry, data editing, and data management including follow up actions. Examples of editors are Word Pad, SPSS data editor, word processors.

Role of computers in data analysis

This phase mainly consist of statistical analysis of the data and interpretation of results. Software like Minitab (Minitab Inc. USA.), SPSS (IBM Crop. New York), NCSS (LLC. Kaysville, Utah, USA) and spreadsheets are widely used.

Role of computer in research publication

Research article, research paper, research thesis or research dissertation is typed in word processing software in computers and stored. Which can be easily published in different electronic formats.[ 5 ]

DATA DISPLAY AND DESCRIPTION OF RESEARCH DATA

Data display and description is an important part of any research project which helps in knowing the distribution of data, detecting errors, missing values and outliers. Ultimately the data should be more comprehensible and meaningful.

Tables are commonly used for describing both qualitative and quantitative data. The graphs are useful for visualising the data and understanding the variations and trends of the data. Qualitative data are usually described by using bar or pie charts. Histograms, polygons or box plots are used to represent quantitative data.[ 1 ]

Qualitative data

Tabulation of qualitative data.

The qualitative observations are categorised in to different categories. The category frequency is nothing but the number of observations with in that category. The category relative frequency can be calculated by dividing the number of observations in the category by total number of observations. The Percentage for a category is more commonly used to describe qualitative data. It can be computed by multiplying relative frequency with hundred.[ 6 , 7 ]

The classification of 30 Patients of a group by severity of postoperative pain presented in Table 2 . The frequency table for this data computed by using the software NCSS[ 8 ] is shown in Table 3 .

The classification of post-operative pain in patients

The frequency table for the variable pain

Graphical display of qualitative data

The qualitative data are commonly displayed by bar graphs and pie charts.[ 9 ]

Bar graphs displays information of the frequency, relative frequency or percentage of each category on vertical axis or horizontal axis of the graph. [ Figure 2 ] Pie charts depicts the same information in divided slices in a complete circle. The area for the circle is equal to the frequency, relative frequency or percentage of that category [ Figure 3 ].

The bar graph generated by computer using NCSS software for the variable pain

The Pie graph generated by computer using NCSS software for the variable pain

Quantitative data

Tabulation of quantitative data.

The quantitative data are usually presented as frequency distribution or relative frequency rather than percentage. The data are divided into different classes. The upper and lower limits or the width of classes will depend up on the size of the data and can easily be adjusted.

The frequency distribution and relative frequency distribution table can be constructed in the following manner:

• The quantitative data are divided into number of classes. The lower limit and upper limit of the classes have to be defined.
• The range or width of the class intervals can be calculated by dividing the difference in the upper limit and lower limit by total number of classes.
• The class frequency is the number of observations that fall in that class.
• The relative class frequency can be calculated by dividing class frequency by total number of observations.

Example of frequency table for the data of Systolic blood pressure of 60 patients undergoing craniotomy is shown in Table 4 . The number of classes were 20, the lower limit and the upper limit were 86 mm of Hg and 186 mm of Hg respectively.

Frequency tabulation of systolic blood pressure in sixty patients (unit is mm Hg)

Graphical description of quantitative data

The frequency distribution is usually depicted in histograms. The count or frequency is plotted along the vertical axis and the horizontal axis represents data values. The normality of distribution can be assessed visually by histograms. A frequency histogram is constructed for the dataset of systolic blood pressure, from the frequency Table 4 [ Figure 4 ].

The frequency histogram for the data set of systolic blood pressure (BP), for which the frequency table is constructed in Table 4

Box plot gives the information of spread of observations in a single group around a centre value. The distribution pattern and extreme values can be easily viewed by box plot. A boxplot is constructed for the dataset of systolic blood pressure, from the frequency Table 4 [ Figure 5 ].

Box plot is constructed from data of Table 4

Polygon construction is similar to histogram. However it is a line graph connecting the data points at mid points of class intervals. The polygon is simpler and outline the data pattern clearly[ 8 ] [ Figure 6 ].

A frequency polygon constructed from data of Table 4 in NCSS software

It is often necessary to further summarise quantitative data, for example, for hypothesis testing. The most important elements of a data are its location, which is measured by mean, median and mode. The other parameters are variability (range, interquartile range, standard deviation and variance) and shape of the distribution (normal, skewness, and kurtosis). The details of which will be discussed in the next chapter.

The proper designing of research methodology is an important step from the conceptual phase to the conclusion phase and the computers play an invaluable role from the beginning to the end of a study. The data collection, data storage and data management are vital for any study. The data display and interpretation will help in understating the behaviour of the data and also to know the assumptions for statistical analysis.

Do research responsibly and ethically on marginalized communities such as LGBTQ+ people

Working together while recognizing each other’s strengths is how we create equitable and impactful community change..

Finn Shelp-Peck is the transgender and gender expansive justice specialist at inclusion tennessee who moved from North Carolina to Nashville in 2022 for graduate school at Vanderbilt University.

As activism and community-centered research evolves, we have a chance to turn a new page in ethical commitments to data collection, distribution, and implementation.

In the last six years I have conducted over 3,000 hours of research in multiple different fields ranging from reproductive and cellular biology to social science and community health.

I have attended and spoken at conferences, written and edited publications, and analyzed and disseminated data. Thankfully, I have been lucky to have incredible mentors who have taught me and guided me through these endeavors.

Through this time I have noticed an opportunity for research to take a more community-centric approach.

Data has been collected on marginalized communities with little regard for their well-being

I love the ways that activism informs research projects and strategies, just as research is informed, inspired, and shaped by social movements and community needs. In Nashville, 48% of LGBT people don’t feel a sense of belonging, showcasing the disconnect between place, community, and purpose.

All of the researchers I know are passionate about what they are doing and the communities they work with. Similarly, all of the activists, advocates, and organizers I know love the communities they serve with every cell of themselves. These fields seem different and separate, but really are deeply dependent on one another.

Historically , marginalized communities have had information and data collected from them without a regard for the physical, emotional, and mental lasting impact of such actions. Those in positions of power and privilege have taken this information for their benefit and often do not implement change using the extracted data but rather leave that to professionals and organizers in different fields.

Data is not subjective, but rather infused with bias shaped by the creator – no matter how hard they try to neutralize it. Big Data and machine learning is not without bias, but inevitably reinforces existing stereotypes and biases because it is created to generalize populations.

In chapter one of her book, "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy," Cathy O’Neil talks about mathematical models as being mere simplifications which “reflect the judgments and priorities of its creators” (page 21). She goes on to discuss the impact of bias on predictive models for events as benign as the outcome of a baseball game to viciously harmful engrained systems like racism.

More: Tennessee lawmakers prefer to target transgender citizens than solve real-world problems

These four important steps will produce ethical and community-oriented results

Given the history and pattern of Big Data, apprehension about participating in data collection is understandable and expected. This is where I think there is a poignant opportunity for those collecting data to more ethically partner with communities, activists, and organizers to create equitable and impactful programming and resources.

• This starts by including community members, advocates, activists, and organizers in the process of creating surveys and collecting data. Better collaboration will lead to more empathetic and trustworthy surveys.
• Next, there needs to be an intentional and active effort to appropriately compensate participants and organizers for their time and contributions. Taking a survey that asks you to disclose personal and delicate information about yourself is taxing in many ways, asking someone to spend valuable time and remain uncompensated is unethical.
• The third step is making sure that people who participate in the research projects are the first to receive results and are not left guessing about what will come of their time and information. This is an important step in conducting community-centric research.
• Finally, there need to be collaborative efforts in using gathered data to implement impactful programming. While research is important, if the information taken from a community is not given back then it can be harmful and perpetuate an existing power imbalance. This collaboration can look like mutual aid, information sharing, or program development to name a few.

Ultimately, activism and research support one another and are inextricably linked. An effort needs to be made to actively collaborate and support more sustainable and ethical practices. Working together while recognizing each other’s strengths is how we create equitable and impactful community change.

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Striking findings from 2023

Pew Research Center has gathered data around some of this year’s defining news stories, from the rise of artificial intelligence to the debate over affirmative action in college admissions . Here’s a look back at 2023 through some of our most striking research findings.

These findings only scratch the surface of the Center’s research from this past year .

A record-high share of 40-year-olds in the U.S. have never been married, according to a Center analysis of the most recent U.S. Census Bureau data . As of 2021, a quarter of 40-year-olds had never been married – up from 6% in 1980.

In 2021, the demographic groups most likely not to have ever been married by age 40 include men, Black Americans and those without a four-year college degree.

A Center survey conducted in April found that relatively few Americans see marriage as essential for people to live a fulfilling life compared with factors like job satisfaction and friendship. While majorities say that having a job or career they enjoy (71%) and having close friends (61%) are extremely or very important for living a fulfilling life, far fewer say this about having children (26%) or being married (23%). Larger shares, in fact, say having children (42%) or being married (44%) are not too or not at all important.

About half of Americans say the increased use of artificial intelligence in daily life makes them feel more concerned than excited – up 14 percentage points from last year, according to an August survey . Overall, 52% of Americans say they feel this way, an increase from 38% in December 2022.

Just 10% of adults say they are more excited than concerned about the increased use of AI, while 36% say they feel an equal mix of these emotions.

The rise in concern about AI has taken place alongside growing public awareness of the technology. Nine-in-ten adults say they have heard either a lot (33%) or a little (56%) about artificial intelligence. The share of those who have heard  a lot  is up 7 points since December 2022.

For the first time in over 30 years of public opinion polling, Americans’ views of the U.S. Supreme Court are more negative than positive, a July survey found . A narrow majority (54%) have an unfavorable view of the high court, while fewer than half (44%) express a favorable one.

The court’s favorable rating has declined 26 percentage points since 2020, following a series of high-profile rulings on issues including affirmative action in college admissions, LGBTQ+ rights and student loans. The drop in favorability is primarily due to a decline among Democrats and Democratic-leaning independents, just 24% of whom express a favorable opinion of the court.

A growing share of U.S. adults say the federal government should take steps to restrict false information online, even if it limits freedom of information, a June survey found . The share of U.S. adults with this view has risen from 39% in 2018 to 55% in 2023.

In the most recent survey, 42% of adults took the opposite view, saying the government should protect freedom of information, even if it means false information can be published.

Still, Americans remain more likely to say that tech companies – rather than the U.S. government – should be responsible for restricting false information online. About two-thirds (65%) said this in June.

The number of U.S. children and teens killed by gunfire rose 50% in just two years, according to a 2023 analysis of data from the Centers for Disease Control and Prevention (CDC). In 2019, there were 1,732 gun deaths among U.S. children and teens under 18. By 2021, that figure had increased to 2,590.

The gun death  rate  among children and teens – a measure that adjusts for changes in the nation’s population – rose 46% during that span.

Both the number and rate of children and teens killed by gunfire in 2021 were the highest since at least 1999, the earliest year for which this information is available in the CDC’s mortality database.

Most Asian Americans view their ancestral homelands favorably – but not Chinese Americans, according to a multilingual, nationally representative survey of Asian American adults .

Only about four-in-ten Chinese Americans (41%) have a favorable opinion of China, while 35% have an unfavorable one. Another 22% say they have a neither favorable nor unfavorable view. This stands in contrast to how other Asian Americans view their ancestral homelands. For instance, about nine-in-ten Taiwanese and Japanese Americans have a very or somewhat favorable opinion of their place of origin, as do large majorities of Korean, Indian and Filipino Americans.

While Chinese Americans’ views of China are more mixed, they still have a more favorable opinion of the country than other Asian adults do. Just 14% of other Asian Americans view China favorably.

Even before the Israel-Hamas war, Israelis had grown more skeptical of a two-state solution. In a survey conducted in March and April , prior to the war, just 35% of Israelis thought “a way can be found for Israel and an independent Palestinian state to coexist peacefully.” This share had declined by 9 percentage points since 2017 and 15 points since 2013.

Among both Arabs and Jews living in Israel, there have been declines over the past decade in the share of people who believe that a peaceful coexistence between Israel and an independent Palestinian state is possible.

A majority of Americans say they would tip 15% or less for an average restaurant dining experience, including 2% who wouldn’t leave a tip at all, an August survey shows . The survey presented respondents with a hypothetical scenario in which they went to a sit-down restaurant and had average – but not exceptional – food and service. About six-in-ten (57%) say they would leave a tip of 15% or less in this situation. Another 12% say they would leave a tip of 18%, and a quarter of people say they’d tip 20% or more.

Adults in lower-income households and those ages 65 and older are more likely than their counterparts to say they would tip 15% or less in a situation like this.

Partisan views of Twitter – the social media platform now called X – have shifted over the last two years, with Republican users’ views of the site growing more positive and those of Democratic users becoming more negative, according to a March survey . The share of Republican and GOP-leaning users who said the site is mostly bad for American democracy fell from 60% in 2021 to 21% earlier this year. At the same time, the share of Republican users who said the site is mostly good for democracy rose from 17% to 43% during the same span.

Democrats’ views moved in the opposite direction during that time frame. The percentage of Democratic and Democratic-leaning Twitter users who said the platform is good for American democracy decreased from 47% to 24%, while the share who said it is bad for democracy increased – though more modestly – from 28% to 35%.

These changes in views follow Elon Musk’s takeover of the platform in fall 2022.

Nearly half of U.S. workers who get paid time off don’t take all the time off their employer offers, according to a February survey of employed Americans . Among those who say their employer offers paid time off for vacation, doctors’ appointments or to deal with minor illnesses, 46% say they take less time off than they are allowed. A similar share (48%) say they typically take all the time off they are offered.

Among those who don’t take all their paid time off, the most common reasons cited are not feeling the need to take more time off (52% say this), worrying they might fall behind at work (49%), and feeling badly about their co-workers taking on additional work (43%).

Smaller shares cite other concerns, including the feeling that taking more time off might hurt their chances for job advancement (19%) or that they might risk losing their job (16%). Some 12% say their manager or supervisor discourages them from taking time off.

An overwhelming majority of Americans (79%) express a negative sentiment when asked to describe politics in the United States these days, a July survey found . Just 2% offer a positive word or phrase, while 10% say something neutral.

Among those who volunteered an answer, 8% use the word “ divisive” or variations of it, while 2% cite the related term “polarized.” “Corrupt” is the second-most frequent answer, given by 6% of respondents.

The top 15 most cited words also include “messy,” “chaos,” “broken” and “dysfunctional.” Many respondents are even more negative in their views: “terrible,” “disgusting,” “disgrace” and the phrase “dumpster fire” are each offered by at least 1% of respondents.

Around half of Americans (53%) say they have ever been visited by a dead family member in a dream or in another form, according to a spring survey . Overall, 46% of Americans report that they’ve been visited by a dead family member in a dream, while 31% report having been visited by dead relatives in some other form.

Women are more likely than men to report these experiences.

While the survey asked whether people have had interactions with dead relatives, it did not ask for explanations. So, we don’t know whether people view these experiences as mysterious or supernatural, whether they see them as having natural or scientific causes, or some of both.

For example, the survey did not ask what respondents meant when they said they had been visited in a dream by a dead relative. Some might have meant that relatives were trying to send them messages or information from beyond the grave. Others might have had something more commonplace in mind, such as dreaming about a favorite memory of a family member.

More Americans disapprove than approve of selective colleges and universities taking race and ethnicity into account when making admissions decisions, according to another spring survey , fielded before the Supreme Court ruled on the practice in June. Half of U.S. adults disapprove of colleges considering race and ethnicity to increase diversity at the schools, while a third approve and 16% are not sure.

Views differ widely by party, as well as by race and ethnicity. Around three-quarters of Republicans and Republican leaners (74%) disapprove of the practice, while 54% of Democrats and Democratic leaners approve of it.

Nearly half of Black Americans (47%) say they approve of colleges and universities considering race and ethnicity in admissions, while smaller shares of Hispanic (39%), Asian (37%) and White (29%) Americans say the same.

The share of Americans who say science has had a mostly positive effect on society has declined since 2019, before the coronavirus outbreak, a fall survey shows : 57% say science has had a mostly positive effect on society, down from 73% in 2019.

About a third of adults (34%) now say the impact of science on society has been equally positive and negative. And 8% say science has had a mostly negative impact on society.

Democrats have become much more likely than Republicans to say science has had a mostly positive impact on society (69% vs. 47%). This gap is the result of steeper declines in positive ratings among Republicans than among Democrats since 2019 (down 23 points and 8 points, respectively).

Nearly three-in-ten Americans express an unfavorable opinion of both major political parties – the highest share in at least three decades, according to a July survey . Overall, 28% of Americans have an unfavorable opinion of both the Republican and Democratic parties. This is more than quadruple the share in 1994, when just 6% of Americans viewed both parties negatively.

A majority of Americans say TikTok is a threat to national security, according to a survey conducted in May . About six-in-ten adults (59%) see the social media platform as a major or minor threat to national security in the United States. Just 17% say it is  not  a threat to national security and another 23% aren’t sure.

Views vary by partisanship and age. Seven-in-ten Republicans and GOP leaners say TikTok is at least a minor threat to national security, compared with 53% of Democrats and Democratic leaners. Conservative Republicans are more likely than moderate or liberal Republicans – or Democrats of any ideology – to say the view the app as a major threat.

Nearly half of those ages 65 and older (46%) see TikTok as a major threat to national security, compared with a much smaller share (13%) of adults ages 18 to 29.

Read the other posts in our striking findings series:

• Striking findings from 2022
• Striking findings from 2021
• 20 striking findings from 2020
• 19 striking findings from 2019
• 18 striking findings from 2018
• 17 striking findings from 2017
• 16 striking findings from 2016
• 15 striking findings from 2015
• 14 striking findings from 2014
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• Supreme Court
• Trust in Science
• Twitter (X)
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Katherine Schaeffer is a research analyst at Pew Research Center

Private, selective colleges are most likely to use race, ethnicity as a factor in admissions decisions

Americans and affirmative action: how the public sees the consideration of race in college admissions, hiring, asian americans hold mixed views around affirmative action, more americans disapprove than approve of colleges considering race, ethnicity in admissions decisions, hispanic enrollment reaches new high at four-year colleges in the u.s., but affordability remains an obstacle, most popular.

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It's not just you: Reddit is taking over Google

• Google's AI search engine and the rise of forum posts like Reddit and Quora are upheaving SEO.
• Google's shift to promoting more human, helpful sites has led to a surge in traffic to Reddit.
• This rise in Reddit's visibility is being exploited by spammers, raising concerns.

If you think you've been seeing an awful lot more Reddit results lately when you search on Google, you're not imagining things.

The internet is in upheaval, and for website owners the rules of "winning" Google Search have never been murkier.

Google's generative AI search engine is coming from one direction. It's creeping closer to mainstream deployment and bringing an existential crisis for SEOs and website makers everywhere.

Coming from the other direction is an influx of posts from Reddit, Quora, and other internet forums that have climbed up through the traditional set of Google links.

Data analysis from Semrush, which predicts traffic based on search ranking, shows that traffic to Reddit has climbed at an impressive clip since August. Semrush estimated that Reddit had over 132 million visitors in August 2023. At the time of publishing, it was projected to have over 346 million visitors in April 2024.

None of this is accidental. For years, Google has been watching users tack on "Reddit" to the end of search queries and finally decided to do something about it.

Google started dropping hints in 2022 when it promised to do a better job of promoting sites that weren't just chasing the top of search but were more helpful and human.

Last August, Google rolled out a big update to Search that seemed to kick this into action. Reddit, Quora, and other forum sites started getting more visibility in Google, both within the traditional links and within a new "discussions and forums" section, which you may have spotted if you're US-based.

The timing of this Reddit bump has led to some conspiracy theories. In February, Google and Reddit announced a blockbuster deal that would let Google train its AI models on Reddit content. Google said the deal, reportedly worth $60 million , would "facilitate more content-forward displays of Reddit information," leading to some speculation that Google promised Reddit better visibility in exchange for the valuable training data. A few weeks later, Reddit also went public .

A Google spokesperson told BI: "Our agreement with Reddit absolutely did not include ranking its content higher on Search."

Indeed, SEO experts have watched this Reddit bump since August when Google rolled out a crucial search update six months before the deal was announced.

It's not just Reddit. Q&A forum Quora is getting a huge visibility bump in Google search results, per Semrush and Sistrix data. Google says "hundreds" of other forums and communities across the web are also getting the bump.

Still, given Reddit's size, its rise is the most noticeable. Per Sistrix data, Reddit is now as visible in top Google Search results as Instagram.

Steve Paine, marketing manager at Sistrix, called the rise of Reddit "unprecedented."

"There hasn't been a website that's grown so much search visibility so quickly in the US in at least the last five years," he told Business Insider.

Right now, Reddit ranks high for product searches. Reddit's main competitors are Wikipedia, YouTube, and Fandom, Paine said, and it also competes in "high-value commercial searches," putting it up against Amazon. The "real competitors," he said, are the subreddits that compete with brands on the web.

Giving the people what they want

Why is Google doing this, and why now ?

The company's stance here is simple: it's giving users what they want.

"Our research has shown that people often want to learn from others' experiences with a topic, so we've continued to make it easier to find helpful perspectives on Search when it's relevant to a query," a Google spokesperson told BI. "Our systems surface content from hundreds of forums and other communities across the web, and we conduct rigorous testing to ensure results are helpful and high quality."

Responding to a post on X , Google search liaison Danny Sullivan said users not only like seeing "forum content" but that they "proactively seek it out."

This shift in search behavior has already been happening for several years. In July 2022, Google's search head Prabhakar Raghavan said younger users were turning to alternative sources such as TikTok and Instagram for information and recommendations. Last year, during the Reddit blackout in June, Google Search got considerably worse .

Google's Reddit deal and its endorsement of Reddit content in Search show how much it sees Reddit as a crucial part of the future of search.

Related stories

"It's obvious that Google has this vision that they need more user-generated content," said Aleyda Solis, an SEO consultant for Orainti, who added that this is one way Google can respond to the rise in TikTok, Instagram, and other social spaces.

While Google might not be pumping Reddit results in exchange for training data, Google's AI systems would benefit from the more up-to-date information Reddit can give, especially when SGE rolls out in full .

Furthermore, a paper written by several Google employees , published in late 2023, claims that pulling information from an internet search can better improve the accuracy of chatbots.

Named FreshPrompt, the method would incorporate "relevant and up-to-date information retrieved from a search engine" to improve a chatbot such as Google's Gemini or OpenAI's ChatGPT .

Grifters can hijack search

The question is whether this Reddit bump will continue or Google will nerf it. There are risks associated with Reddit, which relies on unpaid moderators to police unsavory content and spam.

Google told BI its systems work on all websites, including Quora and Reddit. Still, there's evidence that people are already abusing the rise of these sites in Google rankings. In a February study , SEO blogger Glen Allsopp found that 51% of Reddit's top-ranking threads in Google Search's forums sections contained spam as a top comment.

YouTube already has heaps of videos offering advice on hijacking Reddit to rise to the top of Google Search. One of the most popular videos right now teaches viewers to purchase abandoned Reddit accounts, seek out popular Reddit posts to post comments filled with affiliate links, and then artificially inflate their popularity using "upvotes" purchased from third-party websites. This way, they can feasibly rocket to the top of Google.

It might not be that difficult. Search Engine Journal reported this week that one Reddit user climbed to top-ranking Google Search results in minutes (BI could confirm the post ranked in the top 10, but couldn't independently verify the time it took to get there).

A Google spokesperson said the company's anti-spam policies apply to all content and that it takes particular attention to searches for sensitive topics such as health or finance.

Still, it's unclear how much Google's spam-attacking systems, which just got a boost , work right now. Reddit is "heavily manipulated at the end of the day," and people can easily take advantage of it by posting content there, Solis said.

Lily Ray, vice president of SEO strategy and research for marketing agency Amsive, told BI she is concerned that Google is "shifting the burden" of monitoring abuse onto Reddit moderators. Neglected subreddits risk getting spammed with unhelpful or even false content.

Ray wrote on LinkedIn last week that she found an example of Reddit ranking prominently at the top of Google when she searched "How to lose 10 pounds in a week".

"A redditor suggested 'cutting your arm off,'" she wrote.

This raises questions about whether Google can keep bad content from being eaten by its AI-generated search engine, which often sources its responses from the top search results. Already, Google is fighting an influx of AI-generated content flooding the web. At the same time, rivals such as OpenAI and Perplexity try to steal Google's lunch with AI chatbots that work like search engineers.

A Google spokesperson told BI that the company's analysis did not find that more harmful content on Search comes from forums.

There's room to grow - and that's good news for Reddit investors

The assessment in the SEO community right now is that Google has leaned too hard into community discussion, and it may need to recalibrate once users start complaining that, actually, too much Reddit in Google results can be a bad thing.

Sistrix's Paine said 48.9% of the reddit.com ranking content appears in the top 10 Google Search results, yet only 8% show in the top 3, according to a study from his firm — giving plenty of room for Reddit only to grow, which is something Reddit investors will be pleased to know.

Google may also decide to course-correct.

"Personally, I would expect this current dominance by Reddit to calm down once Google notes that the search experience has not been improved by the increased inclusion of Reddit," SEO consultant Natalie Slater told BI.

"One of the questions is, will it retain this visibility?" Paine said of Reddit. "On one hand, this is unprecedented growth, and there's a feeling that it must end soon."

On the other, he added, there's plenty of space for Reddit's presence in Google Search to grow even bigger.

For now, Reddit and Google need each other, and it may be in neither of their interests to stop a good thing.

On February 28, Axel Springer, Business Insider's parent company, joined 31 other media groups and filed a $2.3 billion suit against Google in Dutch court, alleging losses suffered due to the company's advertising practices.

Watch: What is ChatGPT, and should we be afraid of AI chatbots?

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Researchers detect a new molecule in space

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New research from the group of MIT Professor Brett McGuire has revealed the presence of a previously unknown molecule in space. The team's open-access paper, “ Rotational Spectrum and First Interstellar Detection of 2-Methoxyethanol Using ALMA Observations of NGC 6334I ,” appears in April 12 issue of The Astrophysical Journal Letters .

Zachary T.P. Fried , a graduate student in the McGuire group and the lead author of the publication, worked to assemble a puzzle comprised of pieces collected from across the globe, extending beyond MIT to France, Florida, Virginia, and Copenhagen, to achieve this exciting discovery. 

“Our group tries to understand what molecules are present in regions of space where stars and solar systems will eventually take shape,” explains Fried. “This allows us to piece together how chemistry evolves alongside the process of star and planet formation. We do this by looking at the rotational spectra of molecules, the unique patterns of light they give off as they tumble end-over-end in space. These patterns are fingerprints (barcodes) for molecules. To detect new molecules in space, we first must have an idea of what molecule we want to look for, then we can record its spectrum in the lab here on Earth, and then finally we look for that spectrum in space using telescopes.”

Searching for molecules in space

The McGuire Group has recently begun to utilize machine learning to suggest good target molecules to search for. In 2023, one of these machine learning models suggested the researchers target a molecule known as 2-methoxyethanol. 

“There are a number of 'methoxy' molecules in space, like dimethyl ether, methoxymethanol, ethyl methyl ether, and methyl formate, but 2-methoxyethanol would be the largest and most complex ever seen,” says Fried. To detect this molecule using radiotelescope observations, the group first needed to measure and analyze its rotational spectrum on Earth. The researchers combined experiments from the University of Lille (Lille, France), the New College of Florida (Sarasota, Florida), and the McGuire lab at MIT to measure this spectrum over a broadband region of frequencies ranging from the microwave to sub-millimeter wave regimes (approximately 8 to 500 gigahertz). 

The data gleaned from these measurements permitted a search for the molecule using Atacama Large Millimeter/submillimeter Array (ALMA) observations toward two separate star-forming regions: NGC 6334I and IRAS 16293-2422B. Members of the McGuire group analyzed these telescope observations alongside researchers at the National Radio Astronomy Observatory (Charlottesville, Virginia) and the University of Copenhagen, Denmark. 

“Ultimately, we observed 25 rotational lines of 2-methoxyethanol that lined up with the molecular signal observed toward NGC 6334I (the barcode matched!), thus resulting in a secure detection of 2-methoxyethanol in this source,” says Fried. “This allowed us to then derive physical parameters of the molecule toward NGC 6334I, such as its abundance and excitation temperature. It also enabled an investigation of the possible chemical formation pathways from known interstellar precursors.”

Looking forward

Molecular discoveries like this one help the researchers to better understand the development of molecular complexity in space during the star formation process. 2-methoxyethanol, which contains 13 atoms, is quite large for interstellar standards — as of 2021, only six species larger than 13 atoms were detected outside the solar system , many by McGuire’s group, and all of them existing as ringed structures.  

“Continued observations of large molecules and subsequent derivations of their abundances allows us to advance our knowledge of how efficiently large molecules can form and by which specific reactions they may be produced,” says Fried. “Additionally, since we detected this molecule in NGC 6334I but not in IRAS 16293-2422B, we were presented with a unique opportunity to look into how the differing physical conditions of these two sources may be affecting the chemistry that can occur.”

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Superradiant atoms could push the boundaries of how precisely time can be measured

Superradiant atoms can help us measure time more precisely than ever. In a new study, researchers from the University of Copenhagen present a new method for measuring the time interval, the second, mitigating some of the limitations that today's most advanced atomic clocks encounter. The result could have broad implications in areas such as space travel, volcanic eruptions and GPS systems.

The second is the most precisely-defined unit of measurement, compared to other base units such as the kilogram, meter, and degree Kelvin. Time is currently measured by atomic clocks in different places around the world, which together, tell us what time it is. Using radio waves, atomic clocks continuously send signals that synchronize our computers, phones and wristwatches.

Oscillations are the key to keeping time. In a grandfather clock, these oscillations are from a pendulum's swinging from side to side every second, while in an atomic clock, it is a laser beam which corresponds to an energy transition in strontium and oscillates about a million billion times per second.

But according to PhD fellow Eliot Bohr from the Niels Bohr Institute -- great-grandson of Niels Bohr -- even atomic clocks could become more precise. This is because the detection laser, used by most modern atomic clocks to read the oscillation of atoms, heats up the atoms so much that they escape -- which degrades precision.

"Because the atoms constantly need to be replaced with fresh new atoms, while new atoms are being prepared, the clock loses time ever so slightly.Therefore, we are attempting to overcome some of the current challenges and limitations of the world's best atomic clocks by, among other things, reusing the atoms so that they don't need to be replaced as often," explains Eliot Bohr who was employed at the Niels Bohr Institute when he did the research, but who is now PhD fellow at the University of Colorado.

He is the lead author of a new study published in the scientific journal Nature Communications , which uses an innovative and perhaps more efficient way of measuring time.

Superradiance and cooling to absolute zero

The current methodology consists of a hot oven that spits roughly 300 million strontium atoms into an extraordinarily chilly ball of cold atoms known as a magneto-optical trap, or MOT. The temperature of these atoms is approximately -273 °C -- very near absolute zero -- and there are two mirrors with a light field in between them to enhance the atomic interactions. Together with his research colleagues, Bohr has developed a new method to read out the atoms.

"When the atoms land in the vacuum chamber, they lie completely still because it is so cold, which makes it possible to register their oscillations with the two mirrors at opposing ends of the chamber," explains Eliot Bohr.

The reason why the researchers don't need to heat the atoms with a laser and destroy them is thanks to a quantum physical phenomenon known as 'superradiance'. The phenomenon occurs when the group of strontium atoms is entangled and at the same time emits light in the field between the two mirrors.

"Themirrors cause the atoms to behave as a single unit. Collectively, they emit a powerful light signal that we can use to read out the atomic state, a crucial step for measuring time. This method heats up the atoms minimally, so It all happens without replacing the atoms, and this has the potential to make it a more precise measurement method," explains Bohr.

GPS, space missions and volcanic eruptions

According to Eliot Bohr, the new research result may be beneficial for developing a more accurate GPS system. Indeed, the roughly 30 satellites that constantly circle Earth and tell us where we are need atomic clocks to measure time.

"Whenever satellites determine the position of your phone or GPS, you are using an atomic clock in a satellite. The precision of the atomic clocks is so important that If that atomic clock is off by a microsecond, it means an inaccuracy of about 100 meters on the Earth's surface," explains Eliot Bohr.

Future space missions are another area where the researcher foresees more precise atomic clocks making a significant impact.

"When people and crafts are sent out into space, they venture even further away from our satellites. Consequently, the requirements for precise time measurements to navigate in space are much greater," he says.

The result could also be helpful in the development of a new generation of smaller, portable atomic clocks that could be used for more than "just" measuring time.

"Atomic clocks are sensitive to gravitational changes and can therefore be used to detect changes in Earth's mass and gravity, and this could help us predict when volcanic eruptions and earthquakes will occur," says Bohr.

Bohr emphasizes that while the new method using superradiant atoms is very promising, it is still a "proof of concept" which needs further refinement. .

The research was conducted by the team of Jörg Helge Müller and Jan Thomsen at the Niels Bohr Institute, in collaboration with PhD students Sofus Laguna Kristensen and Julian Robinson-Tait, and postdoc Stefan Alaric Schäffer. The project also included contributions from theorists Helmut Ritsch and Christoph Hotter from the University of Innsbruck, as well as Tanya Zelevinsky from Columbia University.

• Engineering
• Weapons Technology
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• Quantum Physics
• Global Positioning System
• Electron configuration
• Time in physics
• Oscillation
• Special relativity
• Constructal theory

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Materials provided by University of Copenhagen - Faculty of Science . Note: Content may be edited for style and length.

Journal Reference :

• Eliot A. Bohr, Sofus L. Kristensen, Christoph Hotter, Stefan A. Schäffer, Julian Robinson-Tait, Jan W. Thomsen, Tanya Zelevinsky, Helmut Ritsch, Jörg H. Müller. Collectively enhanced Ramsey readout by cavity sub- to superradiant transition . Nature Communications , 2024; 15 (1) DOI: 10.1038/s41467-024-45420-x

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