presentation of study results

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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.

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Home » Research Results Section – Writing Guide and Examples

Research Results Section – Writing Guide and Examples

Table of Contents

Research Results

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

Results Section in Research

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

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

Structure of Research Results Section

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

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

Outline of Research Results Section

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

I. Introduction

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

II. Descriptive statistics

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

III. Inferential statistics

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

IV. Effect sizes and confidence intervals

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

V. Subgroup analyses

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

VI. Limitations and assumptions

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

VII. Conclusions

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

Example of Research Results Section

An Example of a Research Results Section could be:

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

II. Participants

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

III. Results

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

IV. Discussion

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

V. Conclusion

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

Example of Research Results in Research Paper :

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

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

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

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

Example 3 :

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

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

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

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

Importance of Research Results

Research results are important for several reasons, including:

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

How to Write Results in A Research Paper

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

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

When to Write Research Results

Here are situations When to Write Research Results”

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

Purpose of Research Results

The purposes of Research Results are as follows:

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

Advantages of Research Results

Some Advantages of Research Results are as follows:

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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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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Research Guide

Chapter 7 presenting your findings.

Now that you have worked so hard in your project, how to ensure that you can communicate your findings in an effective and efficient way? In this section, I will introduce a few tips that could help you prepare your slides and preparing for your final presentation.

7.1 Sections of the Presentation

When preparing your slides, you need to ensure that you have a clear roadmap. You have a limited time to explain the context of your study, your results, and the main takeaways. Thus, you need to be organized and efficient when deciding what material will be included in the slides.

You need to ensure that your presentation contains the following sections:

• Motivation : Why did you choose your topic? What is the bigger question?
• Research question : Needs to be clear and concise. Include secondary questions, if available, but be clear about what is your research question.
• Literature Review : How does your paper fit in the overall literature? What are your contributions?
• Context : Give an overview of the issue and the population/countries that you analyzed
• Study Characteristics : This section is key, as it needs to include your model, identification strategy, and introduce your data (sources, summary statistics, etc.).
• Results : In this section, you need to answer your research question(s). Include tables that are readable.
• Additional analysis : Here, include any additional information that your public needs to know. For instance, did you try different specifications? did you find an obstacle (i.e. your data is very noisy, the sample is very small, something else) that may bias your results or create some issues in your analysis? Tell your audience! No research project is perfect, but you need to be clear about the imperfections of your project.
• Conclusion : Be repetitive! What was your research question? How did you answer it? What did you find? What is next in this topic?

7.2 How to prepare your slides

When preparing your slides, remember that humans have a limited capacity to pay attention. If you want to convey your convey your message in an effective way, you need to ensure that the message is simple and that you keep your audience attention. Here are some strategies that you may want to follow:

• Have a clear roadmap at the beginning of the presentation. Tell your audience what to expect.
• Number your slides. This will help you and your audience to know where you are in your analysis.
• Ensure that each slide has a purpose
• Ensure that each slide is connected to your key point.
• Make just one argument per slide
• State the objective of each slide in the headline
• Use bullet points. Do not include more than one sentence per bullet point.
• Choose a simple background.
• If you want to direct your audience attention to a specific point, make it more attractive (using a different font color)
• Each slide needs to have a similar structure (going from the general to the particular detauls).
• Use images/graphs when possible. Ensure that the axes for the graphs are clear.
• Use a large font for your tables. Keep them as simple as possible.
• If you can say it with an image, choose it over a table.
• Have an Appendix with slides that address potential questions.

7.3 How to prepare your presentation

One of the main constraints of having simple presentations is that you cannot rely on them and read them. Instead, you need to have extra notes and memorize them to explain things beyond what is on your slides. The following are some suggestions on how to ensure you communicate effectively during your presentation.

• Practice, practice, practice!
• Keep the right volume (practice will help you with that)
• Be journalistic about your presentation. Indicate what you want to say, then say it.
• Ensure that your audience knows where you are going
• Avoid passive voice.
• Be consistent with the terms you are using. You do not want to confuse your audience, even if using synonyms.
• Face your audience and keep an eye contact.
• Do not try reading your slides
• Ensure that your audience is focused on what you are presenting and there are no other distractions that you can control.
• Do not rush your presentation. Speak calmly and controlled.
• Be comprehensive when answering questions. Avoid yes/no answers. Instead, rephrase question (to ensure you are answering the right question), then give a short answer, then develop.
• If you lose track, do not panick. Go back a little bit or ask your audience for assistance.
• Again, practice is the secret.

You have worked so hard in your final project, and the presentation is your opportunity to share that work with the rest of the world. Use this opportunity to shine and enjoy it.

Since this is the first iteration of the Guide, I expect that there are going to be multiple typos and structure issues. Please feel free to let me know, and I will correct accordingly. ↩︎

Note that you would still need to refine some of the good questions even more. ↩︎

Princeton Correspondents on Undergraduate Research

How to Make a Successful Research Presentation

Turning a research paper into a visual presentation is difficult; there are pitfalls, and navigating the path to a brief, informative presentation takes time and practice. As a TA for  GEO/WRI 201: Methods in Data Analysis & Scientific Writing this past fall, I saw how this process works from an instructor’s standpoint. I’ve presented my own research before, but helping others present theirs taught me a bit more about the process. Here are some tips I learned that may help you with your next research presentation:

More is more

In general, your presentation will always benefit from more practice, more feedback, and more revision. By practicing in front of friends, you can get comfortable with presenting your work while receiving feedback. It is hard to know how to revise your presentation if you never practice. If you are presenting to a general audience, getting feedback from someone outside of your discipline is crucial. Terms and ideas that seem intuitive to you may be completely foreign to someone else, and your well-crafted presentation could fall flat.

Less is more

Limit the scope of your presentation, the number of slides, and the text on each slide. In my experience, text works well for organizing slides, orienting the audience to key terms, and annotating important figures–not for explaining complex ideas. Having fewer slides is usually better as well. In general, about one slide per minute of presentation is an appropriate budget. Too many slides is usually a sign that your topic is too broad.

Limit the scope of your presentation

Don’t present your paper. Presentations are usually around 10 min long. You will not have time to explain all of the research you did in a semester (or a year!) in such a short span of time. Instead, focus on the highlight(s). Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

You will not have time to explain all of the research you did. Instead, focus on the highlights. Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

Craft a compelling research narrative

After identifying the focused research question, walk your audience through your research as if it were a story. Presentations with strong narrative arcs are clear, captivating, and compelling.

• Introduction (exposition — rising action)

Orient the audience and draw them in by demonstrating the relevance and importance of your research story with strong global motive. Provide them with the necessary vocabulary and background knowledge to understand the plot of your story. Introduce the key studies (characters) relevant in your story and build tension and conflict with scholarly and data motive. By the end of your introduction, your audience should clearly understand your research question and be dying to know how you resolve the tension built through motive.

• Methods (rising action)

The methods section should transition smoothly and logically from the introduction. Beware of presenting your methods in a boring, arc-killing, ‘this is what I did.’ Focus on the details that set your story apart from the stories other people have already told. Keep the audience interested by clearly motivating your decisions based on your original research question or the tension built in your introduction.

• Results (climax)

Less is usually more here. Only present results which are clearly related to the focused research question you are presenting. Make sure you explain the results clearly so that your audience understands what your research found. This is the peak of tension in your narrative arc, so don’t undercut it by quickly clicking through to your discussion.

• Discussion (falling action)

By now your audience should be dying for a satisfying resolution. Here is where you contextualize your results and begin resolving the tension between past research. Be thorough. If you have too many conflicts left unresolved, or you don’t have enough time to present all of the resolutions, you probably need to further narrow the scope of your presentation.

• Conclusion (denouement)

Return back to your initial research question and motive, resolving any final conflicts and tying up loose ends. Leave the audience with a clear resolution of your focus research question, and use unresolved tension to set up potential sequels (i.e. further research).

Use your medium to enhance the narrative

Visual presentations should be dominated by clear, intentional graphics. Subtle animation in key moments (usually during the results or discussion) can add drama to the narrative arc and make conflict resolutions more satisfying. You are narrating a story written in images, videos, cartoons, and graphs. While your paper is mostly text, with graphics to highlight crucial points, your slides should be the opposite. Adapting to the new medium may require you to create or acquire far more graphics than you included in your paper, but it is necessary to create an engaging presentation.

The most important thing you can do for your presentation is to practice and revise. Bother your friends, your roommates, TAs–anybody who will sit down and listen to your work. Beyond that, think about presentations you have found compelling and try to incorporate some of those elements into your own. Remember you want your work to be comprehensible; you aren’t creating experts in 10 minutes. Above all, try to stay passionate about what you did and why. You put the time in, so show your audience that it’s worth it.

For more insight into research presentations, check out these past PCUR posts written by Emma and Ellie .

— Alec Getraer, Natural Sciences Correspondent

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Presentation of Quantitative Research Findings

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• Jan Koetsenruijter 3 &
• Michel Wensing 3  

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Valid and clear presentation of research findings is an important aspect of health services research. This chapter presents recommendations and examples for the presentation of quantitative findings, focusing on tables and graphs. The recommendations in this field are largely experience-based. Tables and graphs should be tailored to the needs of the target audience, which partly reflects conventional formats. In many cases, simple formats of tables and graphs with precise information are recommended. Misleading presentation formats must be avoided, and uncertainty of findings should be clearly conveyed in the presentation. Research showed that the latter does not reduce trust in the presented data.

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Koetsenruijter, J., Wensing, M. (2023). Presentation of Quantitative Research Findings. In: Wensing, M., Ullrich, C. (eds) Foundations of Health Services Research. Springer, Cham. https://doi.org/10.1007/978-3-031-29998-8_5

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Chapter 12: Descriptive Statistics

Expressing Your Results

Learning Objectives

• Write out simple descriptive statistics in American Psychological Association (APA) style.
• Interpret and create simple APA-style graphs—including bar graphs, line graphs, and scatterplots.
• Interpret and create simple APA-style tables—including tables of group or condition means and correlation matrixes.

Once you have conducted your descriptive statistical analyses, you will need to present them to others. In this section, we focus on presenting descriptive statistical results in writing, in graphs, and in tables—following American Psychological Association (APA) guidelines for written research reports. These principles can be adapted easily to other presentation formats such as posters and slide show presentations.

Presenting Descriptive Statistics in Writing

When you have a small number of results to report, it is often most efficient to write them out. There are a few important APA style guidelines here. First, statistical results are always presented in the form of numerals rather than words and are usually rounded to two decimal places (e.g., “2.00” rather than “two” or “2”). They can be presented either in the narrative description of the results or parenthetically—much like reference citations. Here are some examples:

The mean age of the participants was 22.43 years with a standard deviation of 2.34.

Among the low self-esteem participants, those in a negative mood expressed stronger intentions to have unprotected sex ( M  = 4.05,  SD  = 2.32) than those in a positive mood ( M  = 2.15,  SD  = 2.27).

The treatment group had a mean of 23.40 ( SD  = 9.33), while the control group had a mean of 20.87 ( SD  = 8.45).

The test-retest correlation was .96.

There was a moderate negative correlation between the alphabetical position of respondents’ last names and their response time ( r  = −.27).

Notice that when presented in the narrative, the terms  mean  and  standard deviation  are written out, but when presented parenthetically, the symbols  M and  SD  are used instead. Notice also that it is especially important to use parallel construction to express similar or comparable results in similar ways. The third example is  much  better than the following nonparallel alternative:

The treatment group had a mean of 23.40 ( SD  = 9.33), while 20.87 was the mean of the control group, which had a standard deviation of 8.45.

Presenting Descriptive Statistics in Graphs

When you have a large number of results to report, you can often do it more clearly and efficiently with a graph. When you prepare graphs for an APA-style research report, there are some general guidelines that you should keep in mind. First, the graph should always add important information rather than repeat information that already appears in the text or in a table. (If a graph presents information more clearly or efficiently, then you should keep the graph and eliminate the text or table.) Second, graphs should be as simple as possible. For example, the  Publication Manual  discourages the use of colour unless it is absolutely necessary (although colour can still be an effective element in posters, slide show presentations, or textbooks.) Third, graphs should be interpretable on their own. A reader should be able to understand the basic result based only on the graph and its caption and should not have to refer to the text for an explanation.

There are also several more technical guidelines for graphs that include the following:

• The graph should be slightly wider than it is tall.
• The independent variable should be plotted on the  x- axis and the dependent variable on the  y- axis.
• Values should increase from left to right on the  x- axis and from bottom to top on the  y- axis.
• Axis labels should be clear and concise and include the units of measurement if they do not appear in the caption.
• Axis labels should be parallel to the axis.
• Legends should appear within the boundaries of the graph.
• Text should be in the same simple font throughout and differ by no more than four points.
• Captions should briefly describe the figure, explain any abbreviations, and include the units of measurement if they do not appear in the axis labels.
• Captions in an APA manuscript should be typed on a separate page that appears at the end of the manuscript. See  Chapter 11 for more information.

As we have seen throughout this book,  bar graphs  are generally used to present and compare the mean scores for two or more groups or conditions. The bar graph in Figure 12.11 is an APA-style version of Figure 12.4. Notice that it conforms to all the guidelines listed. A new element in Figure 12.11 is the smaller vertical bars that extend both upward and downward from the top of each main bar. These are error bars , and they represent the variability in each group or condition. Although they sometimes extend one standard deviation in each direction, they are more likely to extend one standard error in each direction (as in Figure 12.11). The  standard error  is the standard deviation of the group divided by the square root of the sample size of the group. The standard error is used because, in general, a difference between group means that is greater than two standard errors is statistically significant. Thus one can “see” whether a difference is statistically significant based on a bar graph with error bars.

Line Graphs

Line graphs  are used to present correlations between quantitative variables when the independent variable has, or is organized into, a relatively small number of distinct levels. Each point in a line graph represents the mean score on the dependent variable for participants at one level of the independent variable. Figure 12.12 is an APA-style version of the results of Carlson and Conard. Notice that it includes error bars representing the standard error and conforms to all the stated guidelines.

In most cases, the information in a line graph could just as easily be presented in a bar graph. In Figure 12.12, for example, one could replace each point with a bar that reaches up to the same level and leave the error bars right where they are. This emphasizes the fundamental similarity of the two types of statistical relationship. Both are differences in the average score on one variable across levels of another. The convention followed by most researchers, however, is to use a bar graph when the variable plotted on the  x- axis is categorical and a line graph when it is quantitative.

Scatterplots

Scatterplots  are used to present relationships between quantitative variables when the variable on the  x- axis (typically the independent variable) has a large number of levels. Each point in a scatterplot represents an individual rather than the mean for a group of individuals, and there are no lines connecting the points. The graph in Figure 12.13 is an APA-style version of Figure 12.7, which illustrates a few additional points. First, when the variables on the x- axis and  y -axis are conceptually similar and measured on the same scale—as here, where they are measures of the same variable on two different occasions—this can be emphasized by making the axes the same length. Second, when two or more individuals fall at exactly the same point on the graph, one way this can be indicated is by offsetting the points slightly along the  x- axis. Other ways are by displaying the number of individuals in parentheses next to the point or by making the point larger or darker in proportion to the number of individuals. Finally, the straight line that best fits the points in the scatterplot, which is called the regression line, can also be included.

Expressing Descriptive Statistics in Tables

Like graphs, tables can be used to present large amounts of information clearly and efficiently. The same general principles apply to tables as apply to graphs. They should add important information to the presentation of your results, be as simple as possible, and be interpretable on their own. Again, we focus here on tables for an APA-style manuscript.

The most common use of tables is to present several means and standard deviations—usually for complex research designs with multiple independent and dependent variables. Figure 12.14, for example, shows the results of a hypothetical study similar to the one by MacDonald and Martineau (2002) [1] discussed in  Chapter 5 . (The means in Figure 12.14 are the means reported by MacDonald and Martineau, but the standard errors are not). Recall that these researchers categorized participants as having low or high self-esteem, put them into a negative or positive mood, and measured their intentions to have unprotected sex. Although not mentioned in  Chapter 5 , they also measured participants’ attitudes toward unprotected sex. Notice that the table includes horizontal lines spanning the entire table at the top and bottom, and just beneath the column headings. Furthermore, every column has a heading—including the leftmost column—and there are additional headings that span two or more columns that help to organize the information and present it more efficiently. Finally, notice that APA-style tables are numbered consecutively starting at 1 (Table 1, Table 2, and so on) and given a brief but clear and descriptive title.

Another common use of tables is to present correlations—usually measured by Pearson’s  r —among several variables. This kind of table is called a  correlation matrix . Figure 12.15 is a correlation matrix based on a study by David McCabe and colleagues (McCabe, Roediger, McDaniel, Balota, & Hambrick, 2010) [2] . They were interested in the relationships between working memory and several other variables. We can see from the table that the correlation between working memory and executive function, for example, was an extremely strong .96, that the correlation between working memory and vocabulary was a medium .27, and that all the measures except vocabulary tend to decline with age. Notice here that only half the table is filled in because the other half would have identical values. For example, the Pearson’s  r  value in the upper right corner (working memory and age) would be the same as the one in the lower left corner (age and working memory). The correlation of a variable with itself is always 1.00, so these values are replaced by dashes to make the table easier to read.

As with graphs, precise statistical results that appear in a table do not need to be repeated in the text. Instead, the writer can note major trends and alert the reader to details (e.g., specific correlations) that are of particular interest.

Key Takeaways

• In an APA-style article, simple results are most efficiently presented in the text, while more complex results are most efficiently presented in graphs or tables.
• APA style includes several rules for presenting numerical results in the text. These include using words only for numbers less than 10 that do not represent precise statistical results, and rounding results to two decimal places, using words (e.g., “mean”) in the text and symbols (e.g., “ M ”) in parentheses.
• APA style includes several rules for presenting results in graphs and tables. Graphs and tables should add information rather than repeating information, be as simple as possible, and be interpretable on their own with a descriptive caption (for graphs) or a descriptive title (for tables).

Long Descriptions

“Convincing” long description: A four-panel comic strip. In the first panel, a man says to a woman, “I think we should give it another shot.” The woman says, “We should break up, and I can prove it.”

In the second panel, there is a line graph with a downward trend titled “Our Relationship.”

In the third panel, the man, bent over and looking at the graph in the woman’s hands, says, “Huh.”

In the fourth panel, the man says, “Maybe you’re right.” The woman says, “I knew data would convince you.” The man replies, “No, I just think I can do better than someone who doesn’t label her axes.” [Return to “Convincing”]

Figure 12.11 long description: A sample APA-style bar graph, with a horizontal axis labelled “Condition” and a vertical axis labelled “Clinician Rating of Severity.” The caption of the graph says, “Figure X. Mean clinician’s rating of phobia severity for participants receiving the education treatment and the exposure treatment. Error bars represent standard errors.” At the top of each data bar is an error bar, which look likes a capital I: a vertical line with short horizontal lines attached to its top and bottom. The bottom half of each error bar hangs over the top of the data bar, while each top half sticks out the top of the data bar. [Return to Figure 12.11]

Figure 12.12 long description: A sample APA-style line graph with a horizontal axis labelled “Last Name Quartile” and a vertical axis labelled “Response Times (z Scores).” The caption of the graph says, “Figure X. Mean response time by the alphabetical position of respondents’ names in the alphabet. Response times are expressed as z scores. Error bars represent standard errors.” Each data point has an error bar sticking out of its top and bottom. [Return to Figure 12.12]

Figure 12.13 long description: Sample APA-style scatterplot with a horizontal axis labelled “Time 1” and a vertical axis labelled “Time 2.” Each axis has values from 10 to 30. The caption of the scatterplot says, “Figure X. Relationship between scores on the Rosenberg self-esteem scale taken by 25 research methods students on two occasions one week apart. Pearson’s r = .96.” Most of the data points are clustered around the dashed regression line that extends from approximately (12, 11) to (29, 22). [Return to Figure 12.13]

Figure 12.14 long description: Sample APA-style table presenting means and standard deviations. The table is titled “Table X” and is captioned, “Means and Standard Deviations of Intentions to Have Unprotected Sex and Attitudes Toward Unprotected Sex as a Function of Both Mood and Self-Esteem.” The data is organized into negative and positive mood and details intentions and attitudes toward unprotected sex.

Negative mood:

• High—Mean, 2.46
• High—Standard Deviation, 1.97
• Low—Mean, 4.05
• Low—Standard Deviation, 2.32
• High—Mean, 1.65
• High—Standard Deviation, 2.23
• Low—Mean, 1.95
• Low—Standard Deviation, 2.01

Positive mood:

• High—Mean, 2.45
• High—Standard Deviation, 2.00
• Low—Mean, 2.15
• Low—Standard Deviation, 2.27
• High—Mean, 1.82
• High—Standard Deviation, 2.32
• Low—Mean, 1.23
• Low—Standard Deviation, 1.75

[Return to Figure 12.14]

Figure 12.15 long description: Sample APA-style correlation matrix, titled “Table X: Correlations Between Five Cognitive Variables and Age.” The five cognitive variables are:

• Working memory
• Executive function
• Processing speed
• Episodic memory

The data is as such:

Media Attributions

• Convincing by XKCD  CC BY-NC (Attribution NonCommercial)
• MacDonald, T. K., & Martineau, A. M. (2002). Self-esteem, mood, and intentions to use condoms: When does low self-esteem lead to risky health behaviours? Journal of Experimental Social Psychology, 38 , 299–306. ↵
• McCabe, D. P., Roediger, H. L., McDaniel, M. A., Balota, D. A., & Hambrick, D. Z. (2010). The relationship between working memory capacity and executive functioning. Neuropsychology, 24 (2), 222–243. doi:10.1037/a0017619 ↵
• Buss, D. M., & Schmitt, D. P. (1993). Sexual strategies theory: A contextual evolutionary analysis of human mating. Psychological Review, 100 , 204–232. ↵

A figure in which the heights of the bars represent the group means.

Small bars at the top of each main bar in a bar graph that represent the variability in each group or condition.

The standard deviation of the group divided by the square root of the sample size of the group.

A graph used to present correlations between quantitative variables when the independent variable has, or is organized into, a relatively small number of distinct levels.

A graph which shows correlations between quantitative variables; each point represents one person’s score on both variables.

A table showing the correlation between every possible pair of variables in the study.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

By: Jenna Crossley (PhD). Expert Reviewed By: Dr. Eunice Rautenbach | August 2021

So, you’ve collected and analysed your qualitative data, and it’s time to write up your results chapter. But where do you start? In this post, we’ll guide you through the qualitative results chapter (also called the findings chapter), step by step. 

Overview: Qualitative Results Chapter

• What (exactly) the qualitative results chapter is
• What to include in your results chapter
• How to write up your results chapter
• A few tips and tricks to help you along the way
• Free results chapter template

What exactly is the results chapter?

The results chapter in a dissertation or thesis (or any formal academic research piece) is where you objectively and neutrally present the findings of your qualitative analysis (or analyses if you used multiple qualitative analysis methods ). This chapter can sometimes be combined with the discussion chapter (where you interpret the data and discuss its meaning), depending on your university’s preference.  We’ll treat the two chapters as separate, as that’s the most common approach.

In contrast to a quantitative results chapter that presents numbers and statistics, a qualitative results chapter presents data primarily in the form of words . But this doesn’t mean that a qualitative study can’t have quantitative elements – you could, for example, present the number of times a theme or topic pops up in your data, depending on the analysis method(s) you adopt.

Adding a quantitative element to your study can add some rigour, which strengthens your results by providing more evidence for your claims. This is particularly common when using qualitative content analysis. Keep in mind though that qualitative research aims to achieve depth, richness and identify nuances , so don’t get tunnel vision by focusing on the numbers. They’re just cream on top in a qualitative analysis.

So, to recap, the results chapter is where you objectively present the findings of your analysis, without interpreting them (you’ll save that for the discussion chapter). With that out the way, let’s take a look at what you should include in your results chapter.

What should you include in the results chapter?

As we’ve mentioned, your qualitative results chapter should purely present and describe your results , not interpret them in relation to the existing literature or your research questions . Any speculations or discussion about the implications of your findings should be reserved for your discussion chapter.

In your results chapter, you’ll want to talk about your analysis findings and whether or not they support your hypotheses (if you have any). Naturally, the exact contents of your results chapter will depend on which qualitative analysis method (or methods) you use. For example, if you were to use thematic analysis, you’d detail the themes identified in your analysis, using extracts from the transcripts or text to support your claims.

While you do need to present your analysis findings in some detail, you should avoid dumping large amounts of raw data in this chapter. Instead, focus on presenting the key findings and using a handful of select quotes or text extracts to support each finding . The reams of data and analysis can be relegated to your appendices.

While it’s tempting to include every last detail you found in your qualitative analysis, it is important to make sure that you report only that which is relevant to your research aims, objectives and research questions .  Always keep these three components, as well as your hypotheses (if you have any) front of mind when writing the chapter and use them as a filter to decide what’s relevant and what’s not.

Need a helping hand?

How do I write the results chapter?

Now that we’ve covered the basics, it’s time to look at how to structure your chapter. Broadly speaking, the results chapter needs to contain three core components – the introduction, the body and the concluding summary. Let’s take a look at each of these.

Section 1: Introduction

The first step is to craft a brief introduction to the chapter. This intro is vital as it provides some context for your findings. In your introduction, you should begin by reiterating your problem statement and research questions and highlight the purpose of your research . Make sure that you spell this out for the reader so that the rest of your chapter is well contextualised.

The next step is to briefly outline the structure of your results chapter. In other words, explain what’s included in the chapter and what the reader can expect. In the results chapter, you want to tell a story that is coherent, flows logically, and is easy to follow , so make sure that you plan your structure out well and convey that structure (at a high level), so that your reader is well oriented.

The introduction section shouldn’t be lengthy. Two or three short paragraphs should be more than adequate. It is merely an introduction and overview, not a summary of the chapter.

Pro Tip – To help you structure your chapter, it can be useful to set up an initial draft with (sub)section headings so that you’re able to easily (re)arrange parts of your chapter. This will also help your reader to follow your results and give your chapter some coherence.  Be sure to use level-based heading styles (e.g. Heading 1, 2, 3 styles) to help the reader differentiate between levels visually. You can find these options in Word (example below).

Section 2: Body

Before we get started on what to include in the body of your chapter, it’s vital to remember that a results section should be completely objective and descriptive, not interpretive . So, be careful not to use words such as, “suggests” or “implies”, as these usually accompany some form of interpretation – that’s reserved for your discussion chapter.

The structure of your body section is very important , so make sure that you plan it out well. When planning out your qualitative results chapter, create sections and subsections so that you can maintain the flow of the story you’re trying to tell. Be sure to systematically and consistently describe each portion of results. Try to adopt a standardised structure for each portion so that you achieve a high level of consistency throughout the chapter.

For qualitative studies, results chapters tend to be structured according to themes , which makes it easier for readers to follow. However, keep in mind that not all results chapters have to be structured in this manner. For example, if you’re conducting a longitudinal study, you may want to structure your chapter chronologically. Similarly, you might structure this chapter based on your theoretical framework . The exact structure of your chapter will depend on the nature of your study , especially your research questions.

As you work through the body of your chapter, make sure that you use quotes to substantiate every one of your claims . You can present these quotes in italics to differentiate them from your own words. A general rule of thumb is to use at least two pieces of evidence per claim, and these should be linked directly to your data. Also, remember that you need to include all relevant results , not just the ones that support your assumptions or initial leanings.

In addition to including quotes, you can also link your claims to the data by using appendices , which you should reference throughout your text. When you reference, make sure that you include both the name/number of the appendix , as well as the line(s) from which you drew your data.

As referencing styles can vary greatly, be sure to look up the appendix referencing conventions of your university’s prescribed style (e.g. APA , Harvard, etc) and keep this consistent throughout your chapter.

Section 3: Concluding summary

The concluding summary is very important because it summarises your key findings and lays the foundation for the discussion chapter . Keep in mind that some readers may skip directly to this section (from the introduction section), so make sure that it can be read and understood well in isolation.

In this section, you need to remind the reader of the key findings. That is, the results that directly relate to your research questions and that you will build upon in your discussion chapter. Remember, your reader has digested a lot of information in this chapter, so you need to use this section to remind them of the most important takeaways.

Importantly, the concluding summary should not present any new information and should only describe what you’ve already presented in your chapter. Keep it concise – you’re not summarising the whole chapter, just the essentials.

Tips for writing an A-grade results chapter

Now that you’ve got a clear picture of what the qualitative results chapter is all about, here are some quick tips and reminders to help you craft a high-quality chapter:

• Your results chapter should be written in the past tense . You’ve done the work already, so you want to tell the reader what you found , not what you are currently finding .
• Make sure that you review your work multiple times and check that every claim is adequately backed up by evidence . Aim for at least two examples per claim, and make use of an appendix to reference these.
• When writing up your results, make sure that you stick to only what is relevant . Don’t waste time on data that are not relevant to your research objectives and research questions.
• Use headings and subheadings to create an intuitive, easy to follow piece of writing. Make use of Microsoft Word’s “heading styles” and be sure to use them consistently.
• When referring to numerical data, tables and figures can provide a useful visual aid. When using these, make sure that they can be read and understood independent of your body text (i.e. that they can stand-alone). To this end, use clear, concise labels for each of your tables or figures and make use of colours to code indicate differences or hierarchy.
• Similarly, when you’re writing up your chapter, it can be useful to highlight topics and themes in different colours . This can help you to differentiate between your data if you get a bit overwhelmed and will also help you to ensure that your results flow logically and coherently.

If you have any questions, leave a comment below and we’ll do our best to help. If you’d like 1-on-1 help with your results chapter (or any chapter of your dissertation or thesis), check out our private dissertation coaching service here or book a free initial consultation to discuss how we can help you.

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20 Comments

This was extremely helpful. Thanks a lot guys

Hi, thanks for the great research support platform created by the gradcoach team!

I wanted to ask- While “suggests” or “implies” are interpretive terms, what terms could we use for the results chapter? Could you share some examples of descriptive terms?

I think that instead of saying, ‘The data suggested, or The data implied,’ you can say, ‘The Data showed or revealed, or illustrated or outlined’…If interview data, you may say Jane Doe illuminated or elaborated, or Jane Doe described… or Jane Doe expressed or stated.

I found this article very useful. Thank you very much for the outstanding work you are doing.

What if i have 3 different interviewees answering the same interview questions? Should i then present the results in form of the table with the division on the 3 perspectives or rather give a results in form of the text and highlight who said what?

I think this tabular representation of results is a great idea. I am doing it too along with the text. Thanks

That was helpful was struggling to separate the discussion from the findings

this was very useful, Thank you.

Very helpful, I am confident to write my results chapter now.

It is so helpful! It is a good job. Thank you very much!

Very useful, well explained. Many thanks.

Hello, I appreciate the way you provided a supportive comments about qualitative results presenting tips

I loved this! It explains everything needed, and it has helped me better organize my thoughts. What words should I not use while writing my results section, other than subjective ones.

Thanks a lot, it is really helpful

Thank you so much dear, i really appropriate your nice explanations about this.

Thank you so much for this! I was wondering if anyone could help with how to prproperly integrate quotations (Excerpts) from interviews in the finding chapter in a qualitative research. Please GradCoach, address this issue and provide examples.

what if I’m not doing any interviews myself and all the information is coming from case studies that have already done the research.

Very helpful thank you.

This was very helpful as I was wondering how to structure this part of my dissertation, to include the quotes… Thanks for this explanation

This is very helpful, thanks! I am required to write up my results chapters with the discussion in each of them – any tips and tricks for this strategy?

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Qualitative Data Analysis

23 Presenting the Results of Qualitative Analysis

Mikaila Mariel Lemonik Arthur

Qualitative research is not finished just because you have determined the main findings or conclusions of your study. Indeed, disseminating the results is an essential part of the research process. By sharing your results with others, whether in written form as scholarly paper or an applied report or in some alternative format like an oral presentation, an infographic, or a video, you ensure that your findings become part of the ongoing conversation of scholarship in your field, forming part of the foundation for future researchers. This chapter provides an introduction to writing about qualitative research findings. It will outline how writing continues to contribute to the analysis process, what concerns researchers should keep in mind as they draft their presentations of findings, and how best to organize qualitative research writing

As you move through the research process, it is essential to keep yourself organized. Organizing your data, memos, and notes aids both the analytical and the writing processes. Whether you use electronic or physical, real-world filing and organizational systems, these systems help make sense of the mountains of data you have and assure you focus your attention on the themes and ideas you have determined are important (Warren and Karner 2015). Be sure that you have kept detailed notes on all of the decisions you have made and procedures you have followed in carrying out research design, data collection, and analysis, as these will guide your ultimate write-up.

First and foremost, researchers should keep in mind that writing is in fact a form of thinking. Writing is an excellent way to discover ideas and arguments and to further develop an analysis. As you write, more ideas will occur to you, things that were previously confusing will start to make sense, and arguments will take a clear shape rather than being amorphous and poorly-organized. However, writing-as-thinking cannot be the final version that you share with others. Good-quality writing does not display the workings of your thought process. It is reorganized and revised (more on that later) to present the data and arguments important in a particular piece. And revision is totally normal! No one expects the first draft of a piece of writing to be ready for prime time. So write rough drafts and memos and notes to yourself and use them to think, and then revise them until the piece is the way you want it to be for sharing.

Bergin (2018) lays out a set of key concerns for appropriate writing about research. First, present your results accurately, without exaggerating or misrepresenting. It is very easy to overstate your findings by accident if you are enthusiastic about what you have found, so it is important to take care and use appropriate cautions about the limitations of the research. You also need to work to ensure that you communicate your findings in a way people can understand, using clear and appropriate language that is adjusted to the level of those you are communicating with. And you must be clear and transparent about the methodological strategies employed in the research. Remember, the goal is, as much as possible, to describe your research in a way that would permit others to replicate the study. There are a variety of other concerns and decision points that qualitative researchers must keep in mind, including the extent to which to include quantification in their presentation of results, ethics, considerations of audience and voice, and how to bring the richness of qualitative data to life.

Quantification, as you have learned, refers to the process of turning data into numbers. It can indeed be very useful to count and tabulate quantitative data drawn from qualitative research. For instance, if you were doing a study of dual-earner households and wanted to know how many had an equal division of household labor and how many did not, you might want to count those numbers up and include them as part of the final write-up. However, researchers need to take care when they are writing about quantified qualitative data. Qualitative data is not as generalizable as quantitative data, so quantification can be very misleading. Thus, qualitative researchers should strive to use raw numbers instead of the percentages that are more appropriate for quantitative research. Writing, for instance, “15 of the 20 people I interviewed prefer pancakes to waffles” is a simple description of the data; writing “75% of people prefer pancakes” suggests a generalizable claim that is not likely supported by the data. Note that mixing numbers with qualitative data is really a type of mixed-methods approach. Mixed-methods approaches are good, but sometimes they seduce researchers into focusing on the persuasive power of numbers and tables rather than capitalizing on the inherent richness of their qualitative data.

A variety of issues of scholarly ethics and research integrity are raised by the writing process. Some of these are unique to qualitative research, while others are more universal concerns for all academic and professional writing. For example, it is essential to avoid plagiarism and misuse of sources. All quotations that appear in a text must be properly cited, whether with in-text and bibliographic citations to the source or with an attribution to the research participant (or the participant’s pseudonym or description in order to protect confidentiality) who said those words. Where writers will paraphrase a text or a participant’s words, they need to make sure that the paraphrase they develop accurately reflects the meaning of the original words. Thus, some scholars suggest that participants should have the opportunity to read (or to have read to them, if they cannot read the text themselves) all sections of the text in which they, their words, or their ideas are presented to ensure accuracy and enable participants to maintain control over their lives.

Audience and Voice

When writing, researchers must consider their audience(s) and the effects they want their writing to have on these audiences. The designated audience will dictate the voice used in the writing, or the individual style and personality of a piece of text. Keep in mind that the potential audience for qualitative research is often much more diverse than that for quantitative research because of the accessibility of the data and the extent to which the writing can be accessible and interesting. Yet individual pieces of writing are typically pitched to a more specific subset of the audience.

Let us consider one potential research study, an ethnography involving participant-observation of the same children both when they are at daycare facility and when they are at home with their families to try to understand how daycare might impact behavior and social development. The findings of this study might be of interest to a wide variety of potential audiences: academic peers, whether at your own academic institution, in your broader discipline, or multidisciplinary; people responsible for creating laws and policies; practitioners who run or teach at day care centers; and the general public, including both people who are interested in child development more generally and those who are themselves parents making decisions about child care for their own children. And the way you write for each of these audiences will be somewhat different. Take a moment and think through what some of these differences might look like.

If you are writing to academic audiences, using specialized academic language and working within the typical constraints of scholarly genres, as will be discussed below, can be an important part of convincing others that your work is legitimate and should be taken seriously. Your writing will be formal. Even if you are writing for students and faculty you already know—your classmates, for instance—you are often asked to imitate the style of academic writing that is used in publications, as this is part of learning to become part of the scholarly conversation. When speaking to academic audiences outside your discipline, you may need to be more careful about jargon and specialized language, as disciplines do not always share the same key terms. For instance, in sociology, scholars use the term diffusion to refer to the way new ideas or practices spread from organization to organization. In the field of international relations, scholars often used the term cascade to refer to the way ideas or practices spread from nation to nation. These terms are describing what is fundamentally the same concept, but they are different terms—and a scholar from one field might have no idea what a scholar from a different field is talking about! Therefore, while the formality and academic structure of the text would stay the same, a writer with a multidisciplinary audience might need to pay more attention to defining their terms in the body of the text.

It is not only other academic scholars who expect to see formal writing. Policymakers tend to expect formality when ideas are presented to them, as well. However, the content and style of the writing will be different. Much less academic jargon should be used, and the most important findings and policy implications should be emphasized right from the start rather than initially focusing on prior literature and theoretical models as you might for an academic audience. Long discussions of research methods should also be minimized. Similarly, when you write for practitioners, the findings and implications for practice should be highlighted. The reading level of the text will vary depending on the typical background of the practitioners to whom you are writing—you can make very different assumptions about the general knowledge and reading abilities of a group of hospital medical directors with MDs than you can about a group of case workers who have a post-high-school certificate. Consider the primary language of your audience as well. The fact that someone can get by in spoken English does not mean they have the vocabulary or English reading skills to digest a complex report. But the fact that someone’s vocabulary is limited says little about their intellectual abilities, so try your best to convey the important complexity of the ideas and findings from your research without dumbing them down—even if you must limit your vocabulary usage.

When writing for the general public, you will want to move even further towards emphasizing key findings and policy implications, but you also want to draw on the most interesting aspects of your data. General readers will read sociological texts that are rich with ethnographic or other kinds of detail—it is almost like reality television on a page! And this is a contrast to busy policymakers and practitioners, who probably want to learn the main findings as quickly as possible so they can go about their busy lives. But also keep in mind that there is a wide variation in reading levels. Journalists at publications pegged to the general public are often advised to write at about a tenth-grade reading level, which would leave most of the specialized terminology we develop in our research fields out of reach. If you want to be accessible to even more people, your vocabulary must be even more limited. The excellent exercise of trying to write using the 1,000 most common English words, available at the Up-Goer Five website ( https://www.splasho.com/upgoer5/ ) does a good job of illustrating this challenge (Sanderson n.d.).

Another element of voice is whether to write in the first person. While many students are instructed to avoid the use of the first person in academic writing, this advice needs to be taken with a grain of salt. There are indeed many contexts in which the first person is best avoided, at least as long as writers can find ways to build strong, comprehensible sentences without its use, including most quantitative research writing. However, if the alternative to using the first person is crafting a sentence like “it is proposed that the researcher will conduct interviews,” it is preferable to write “I propose to conduct interviews.” In qualitative research, in fact, the use of the first person is far more common. This is because the researcher is central to the research project. Qualitative researchers can themselves be understood as research instruments, and thus eliminating the use of the first person in writing is in a sense eliminating information about the conduct of the researchers themselves.

But the question really extends beyond the issue of first-person or third-person. Qualitative researchers have choices about how and whether to foreground themselves in their writing, not just in terms of using the first person, but also in terms of whether to emphasize their own subjectivity and reflexivity, their impressions and ideas, and their role in the setting. In contrast, conventional quantitative research in the positivist tradition really tries to eliminate the author from the study—which indeed is exactly why typical quantitative research avoids the use of the first person. Keep in mind that emphasizing researchers’ roles and reflexivity and using the first person does not mean crafting articles that provide overwhelming detail about the author’s thoughts and practices. Readers do not need to hear, and should not be told, which database you used to search for journal articles, how many hours you spent transcribing, or whether the research process was stressful—save these things for the memos you write to yourself. Rather, readers need to hear how you interacted with research participants, how your standpoint may have shaped the findings, and what analytical procedures you carried out.

Making Data Come Alive

One of the most important parts of writing about qualitative research is presenting the data in a way that makes its richness and value accessible to readers. As the discussion of analysis in the prior chapter suggests, there are a variety of ways to do this. Researchers may select key quotes or images to illustrate points, write up specific case studies that exemplify their argument, or develop vignettes (little stories) that illustrate ideas and themes, all drawing directly on the research data. Researchers can also write more lengthy summaries, narratives, and thick descriptions.

Nearly all qualitative work includes quotes from research participants or documents to some extent, though ethnographic work may focus more on thick description than on relaying participants’ own words. When quotes are presented, they must be explained and interpreted—they cannot stand on their own. This is one of the ways in which qualitative research can be distinguished from journalism. Journalism presents what happened, but social science needs to present the “why,” and the why is best explained by the researcher.

So how do authors go about integrating quotes into their written work? Julie Posselt (2017), a sociologist who studies graduate education, provides a set of instructions. First of all, authors need to remain focused on the core questions of their research, and avoid getting distracted by quotes that are interesting or attention-grabbing but not so relevant to the research question. Selecting the right quotes, those that illustrate the ideas and arguments of the paper, is an important part of the writing process. Second, not all quotes should be the same length (just like not all sentences or paragraphs in a paper should be the same length). Include some quotes that are just phrases, others that are a sentence or so, and others that are longer. We call longer quotes, generally those more than about three lines long, block quotes , and they are typically indented on both sides to set them off from the surrounding text. For all quotes, be sure to summarize what the quote should be telling or showing the reader, connect this quote to other quotes that are similar or different, and provide transitions in the discussion to move from quote to quote and from topic to topic. Especially for longer quotes, it is helpful to do some of this writing before the quote to preview what is coming and other writing after the quote to make clear what readers should have come to understand. Remember, it is always the author’s job to interpret the data. Presenting excerpts of the data, like quotes, in a form the reader can access does not minimize the importance of this job. Be sure that you are explaining the meaning of the data you present.

A few more notes about writing with quotes: avoid patchwriting, whether in your literature review or the section of your paper in which quotes from respondents are presented. Patchwriting is a writing practice wherein the author lightly paraphrases original texts but stays so close to those texts that there is little the author has added. Sometimes, this even takes the form of presenting a series of quotes, properly documented, with nothing much in the way of text generated by the author. A patchwriting approach does not build the scholarly conversation forward, as it does not represent any kind of new contribution on the part of the author. It is of course fine to paraphrase quotes, as long as the meaning is not changed. But if you use direct quotes, do not edit the text of the quotes unless how you edit them does not change the meaning and you have made clear through the use of ellipses (…) and brackets ([])what kinds of edits have been made. For example, consider this exchange from Matthew Desmond’s (2012:1317) research on evictions:

The thing was, I wasn’t never gonna let Crystal come and stay with me from the get go. I just told her that to throw her off. And she wasn’t fittin’ to come stay with me with no money…No. Nope. You might as well stay in that shelter.

A paraphrase of this exchange might read “She said that she was going to let Crystal stay with her if Crystal did not have any money.” Paraphrases like that are fine. What is not fine is rewording the statement but treating it like a quote, for instance writing:

The thing was, I was not going to let Crystal come and stay with me from beginning. I just told her that to throw her off. And it was not proper for her to come stay with me without any money…No. Nope. You might as well stay in that shelter.

But as you can see, the change in language and style removes some of the distinct meaning of the original quote. Instead, writers should leave as much of the original language as possible. If some text in the middle of the quote needs to be removed, as in this example, ellipses are used to show that this has occurred. And if a word needs to be added to clarify, it is placed in square brackets to show that it was not part of the original quote.

Data can also be presented through the use of data displays like tables, charts, graphs, diagrams, and infographics created for publication or presentation, as well as through the use of visual material collected during the research process. Note that if visuals are used, the author must have the legal right to use them. Photographs or diagrams created by the author themselves—or by research participants who have signed consent forms for their work to be used, are fine. But photographs, and sometimes even excerpts from archival documents, may be owned by others from whom researchers must get permission in order to use them.

A large percentage of qualitative research does not include any data displays or visualizations. Therefore, researchers should carefully consider whether the use of data displays will help the reader understand the data. One of the most common types of data displays used by qualitative researchers are simple tables. These might include tables summarizing key data about cases included in the study; tables laying out the characteristics of different taxonomic elements or types developed as part of the analysis; tables counting the incidence of various elements; and 2×2 tables (two columns and two rows) illuminating a theory. Basic network or process diagrams are also commonly included. If data displays are used, it is essential that researchers include context and analysis alongside data displays rather than letting them stand by themselves, and it is preferable to continue to present excerpts and examples from the data rather than just relying on summaries in the tables.

If you will be using graphs, infographics, or other data visualizations, it is important that you attend to making them useful and accurate (Bergin 2018). Think about the viewer or user as your audience and ensure the data visualizations will be comprehensible. You may need to include more detail or labels than you might think. Ensure that data visualizations are laid out and labeled clearly and that you make visual choices that enhance viewers’ ability to understand the points you intend to communicate using the visual in question. Finally, given the ease with which it is possible to design visuals that are deceptive or misleading, it is essential to make ethical and responsible choices in the construction of visualization so that viewers will interpret them in accurate ways.

The Genre of Research Writing

As discussed above, the style and format in which results are presented depends on the audience they are intended for. These differences in styles and format are part of the genre of writing. Genre is a term referring to the rules of a specific form of creative or productive work. Thus, the academic journal article—and student papers based on this form—is one genre. A report or policy paper is another. The discussion below will focus on the academic journal article, but note that reports and policy papers follow somewhat different formats. They might begin with an executive summary of one or a few pages, include minimal background, focus on key findings, and conclude with policy implications, shifting methods and details about the data to an appendix. But both academic journal articles and policy papers share some things in common, for instance the necessity for clear writing, a well-organized structure, and the use of headings.

So what factors make up the genre of the academic journal article in sociology? While there is some flexibility, particularly for ethnographic work, academic journal articles tend to follow a fairly standard format. They begin with a “title page” that includes the article title (often witty and involving scholarly inside jokes, but more importantly clearly describing the content of the article); the authors’ names and institutional affiliations, an abstract , and sometimes keywords designed to help others find the article in databases. An abstract is a short summary of the article that appears both at the very beginning of the article and in search databases. Abstracts are designed to aid readers by giving them the opportunity to learn enough about an article that they can determine whether it is worth their time to read the complete text. They are written about the article, and thus not in the first person, and clearly summarize the research question, methodological approach, main findings, and often the implications of the research.

After the abstract comes an “introduction” of a page or two that details the research question, why it matters, and what approach the paper will take. This is followed by a literature review of about a quarter to a third the length of the entire paper. The literature review is often divided, with headings, into topical subsections, and is designed to provide a clear, thorough overview of the prior research literature on which a paper has built—including prior literature the new paper contradicts. At the end of the literature review it should be made clear what researchers know about the research topic and question, what they do not know, and what this new paper aims to do to address what is not known.

The next major section of the paper is the section that describes research design, data collection, and data analysis, often referred to as “research methods” or “methodology.” This section is an essential part of any written or oral presentation of your research. Here, you tell your readers or listeners “how you collected and interpreted your data” (Taylor, Bogdan, and DeVault 2016:215). Taylor, Bogdan, and DeVault suggest that the discussion of your research methods include the following:

• The particular approach to data collection used in the study;
• Any theoretical perspective(s) that shaped your data collection and analytical approach;
• When the study occurred, over how long, and where (concealing identifiable details as needed);
• A description of the setting and participants, including sampling and selection criteria (if an interview-based study, the number of participants should be clearly stated);
• The researcher’s perspective in carrying out the study, including relevant elements of their identity and standpoint, as well as their role (if any) in research settings; and
• The approach to analyzing the data.

After the methods section comes a section, variously titled but often called “data,” that takes readers through the analysis. This section is where the thick description narrative; the quotes, broken up by theme or topic, with their interpretation; the discussions of case studies; most data displays (other than perhaps those outlining a theoretical model or summarizing descriptive data about cases); and other similar material appears. The idea of the data section is to give readers the ability to see the data for themselves and to understand how this data supports the ultimate conclusions. Note that all tables and figures included in formal publications should be titled and numbered.

At the end of the paper come one or two summary sections, often called “discussion” and/or “conclusion.” If there is a separate discussion section, it will focus on exploring the overall themes and findings of the paper. The conclusion clearly and succinctly summarizes the findings and conclusions of the paper, the limitations of the research and analysis, any suggestions for future research building on the paper or addressing these limitations, and implications, be they for scholarship and theory or policy and practice.

After the end of the textual material in the paper comes the bibliography, typically called “works cited” or “references.” The references should appear in a consistent citation style—in sociology, we often use the American Sociological Association format (American Sociological Association 2019), but other formats may be used depending on where the piece will eventually be published. Care should be taken to ensure that in-text citations also reflect the chosen citation style. In some papers, there may be an appendix containing supplemental information such as a list of interview questions or an additional data visualization.

Note that when researchers give presentations to scholarly audiences, the presentations typically follow a format similar to that of scholarly papers, though given time limitations they are compressed. Abstracts and works cited are often not part of the presentation, though in-text citations are still used. The literature review presented will be shortened to only focus on the most important aspects of the prior literature, and only key examples from the discussion of data will be included. For long or complex papers, sometimes only one of several findings is the focus of the presentation. Of course, presentations for other audiences may be constructed differently, with greater attention to interesting elements of the data and findings as well as implications and less to the literature review and methods.

Concluding Your Work

After you have written a complete draft of the paper, be sure you take the time to revise and edit your work. There are several important strategies for revision. First, put your work away for a little while. Even waiting a day to revise is better than nothing, but it is best, if possible, to take much more time away from the text. This helps you forget what your writing looks like and makes it easier to find errors, mistakes, and omissions. Second, show your work to others. Ask them to read your work and critique it, pointing out places where the argument is weak, where you may have overlooked alternative explanations, where the writing could be improved, and what else you need to work on. Finally, read your work out loud to yourself (or, if you really need an audience, try reading to some stuffed animals). Reading out loud helps you catch wrong words, tricky sentences, and many other issues. But as important as revision is, try to avoid perfectionism in writing (Warren and Karner 2015). Writing can always be improved, no matter how much time you spend on it. Those improvements, however, have diminishing returns, and at some point the writing process needs to conclude so the writing can be shared with the world.

Of course, the main goal of writing up the results of a research project is to share with others. Thus, researchers should be considering how they intend to disseminate their results. What conferences might be appropriate? Where can the paper be submitted? Note that if you are an undergraduate student, there are a wide variety of journals that accept and publish research conducted by undergraduates. Some publish across disciplines, while others are specific to disciplines. Other work, such as reports, may be best disseminated by publication online on relevant organizational websites.

After a project is completed, be sure to take some time to organize your research materials and archive them for longer-term storage. Some Institutional Review Board (IRB) protocols require that original data, such as interview recordings, transcripts, and field notes, be preserved for a specific number of years in a protected (locked for paper or password-protected for digital) form and then destroyed, so be sure that your plans adhere to the IRB requirements. Be sure you keep any materials that might be relevant for future related research or for answering questions people may ask later about your project.

And then what? Well, then it is time to move on to your next research project. Research is a long-term endeavor, not a one-time-only activity. We build our skills and our expertise as we continue to pursue research. So keep at it.

• Find a short article that uses qualitative methods. The sociological magazine Contexts is a good place to find such pieces. Write an abstract of the article.
• Choose a sociological journal article on a topic you are interested in that uses some form of qualitative methods and is at least 20 pages long. Rewrite the article as a five-page research summary accessible to non-scholarly audiences.
• Choose a concept or idea you have learned in this course and write an explanation of it using the Up-Goer Five Text Editor ( https://www.splasho.com/upgoer5/ ), a website that restricts your writing to the 1,000 most common English words. What was this experience like? What did it teach you about communicating with people who have a more limited English-language vocabulary—and what did it teach you about the utility of having access to complex academic language?
• Select five or more sociological journal articles that all use the same basic type of qualitative methods (interviewing, ethnography, documents, or visual sociology). Using what you have learned about coding, code the methods sections of each article, and use your coding to figure out what is common in how such articles discuss their research design, data collection, and analysis methods.
• Return to an exercise you completed earlier in this course and revise your work. What did you change? How did revising impact the final product?
• Find a quote from the transcript of an interview, a social media post, or elsewhere that has not yet been interpreted or explained. Write a paragraph that includes the quote along with an explanation of its sociological meaning or significance.

The style or personality of a piece of writing, including such elements as tone, word choice, syntax, and rhythm.

A quotation, usually one of some length, which is set off from the main text by being indented on both sides rather than being placed in quotation marks.

A classification of written or artistic work based on form, content, and style.

A short summary of a text written from the perspective of a reader rather than from the perspective of an author.

Social Data Analysis Copyright © 2021 by Mikaila Mariel Lemonik Arthur is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Blog Business How to Present a Case Study like a Pro (With Examples)

How to Present a Case Study like a Pro (With Examples)

Written by: Danesh Ramuthi Sep 07, 2023

Okay, let’s get real: case studies can be kinda snooze-worthy. But guess what? They don’t have to be!

In this article, I will cover every element that transforms a mere report into a compelling case study, from selecting the right metrics to using persuasive narrative techniques.

And if you’re feeling a little lost, don’t worry! There are cool tools like Venngage’s Case Study Creator to help you whip up something awesome, even if you’re short on time. Plus, the pre-designed case study templates are like instant polish because let’s be honest, everyone loves a shortcut.

Click to jump ahead: 

What is a case study presentation?

What is the purpose of presenting a case study, how to structure a case study presentation, how long should a case study presentation be, 5 case study presentation examples with templates, 6 tips for delivering an effective case study presentation, 5 common mistakes to avoid in a case study presentation, how to present a case study faqs.

A case study presentation involves a comprehensive examination of a specific subject, which could range from an individual, group, location, event, organization or phenomenon.

They’re like puzzles you get to solve with the audience, all while making you think outside the box.

Unlike a basic report or whitepaper, the purpose of a case study presentation is to stimulate critical thinking among the viewers. 

The primary objective of a case study is to provide an extensive and profound comprehension of the chosen topic. You don’t just throw numbers at your audience. You use examples and real-life cases to make you think and see things from different angles.

The primary purpose of presenting a case study is to offer a comprehensive, evidence-based argument that informs, persuades and engages your audience.

Here’s the juicy part: presenting that case study can be your secret weapon. Whether you’re pitching a groundbreaking idea to a room full of suits or trying to impress your professor with your A-game, a well-crafted case study can be the magic dust that sprinkles brilliance over your words.

Think of it like digging into a puzzle you can’t quite crack . A case study lets you explore every piece, turn it over and see how it fits together. This close-up look helps you understand the whole picture, not just a blurry snapshot.

It’s also your chance to showcase how you analyze things, step by step, until you reach a conclusion. It’s all about being open and honest about how you got there.

Besides, presenting a case study gives you an opportunity to connect data and real-world scenarios in a compelling narrative. It helps to make your argument more relatable and accessible, increasing its impact on your audience.

One of the contexts where case studies can be very helpful is during the job interview. In some job interviews, you as candidates may be asked to present a case study as part of the selection process.

Having a case study presentation prepared allows the candidate to demonstrate their ability to understand complex issues, formulate strategies and communicate their ideas effectively.

The way you present a case study can make all the difference in how it’s received. A well-structured presentation not only holds the attention of your audience but also ensures that your key points are communicated clearly and effectively.

In this section, let’s go through the key steps that’ll help you structure your case study presentation for maximum impact.

Let’s get into it. 

Open with an introductory overview 

Start by introducing the subject of your case study and its relevance. Explain why this case study is important and who would benefit from the insights gained. This is your opportunity to grab your audience’s attention.

Explain the problem in question

Dive into the problem or challenge that the case study focuses on. Provide enough background information for the audience to understand the issue. If possible, quantify the problem using data or metrics to show the magnitude or severity.

Detail the solutions to solve the problem

After outlining the problem, describe the steps taken to find a solution. This could include the methodology, any experiments or tests performed and the options that were considered. Make sure to elaborate on why the final solution was chosen over the others.

Key stakeholders Involved

Talk about the individuals, groups or organizations that were directly impacted by or involved in the problem and its solution. 

Stakeholders may experience a range of outcomes—some may benefit, while others could face setbacks.

For example, in a business transformation case study, employees could face job relocations or changes in work culture, while shareholders might be looking at potential gains or losses.

Discuss the key results & outcomes

Discuss the results of implementing the solution. Use data and metrics to back up your statements. Did the solution meet its objectives? What impact did it have on the stakeholders? Be honest about any setbacks or areas for improvement as well.

Include visuals to support your analysis

Visual aids can be incredibly effective in helping your audience grasp complex issues. Utilize charts, graphs, images or video clips to supplement your points. Make sure to explain each visual and how it contributes to your overall argument.

Pie charts illustrate the proportion of different components within a whole, useful for visualizing market share, budget allocation or user demographics.

This is particularly useful especially if you’re displaying survey results in your case study presentation.

Stacked charts on the other hand are perfect for visualizing composition and trends. This is great for analyzing things like customer demographics, product breakdowns or budget allocation in your case study.

Consider this example of a stacked bar chart template. It provides a straightforward summary of the top-selling cake flavors across various locations, offering a quick and comprehensive view of the data.

Not the chart you’re looking for? Browse Venngage’s gallery of chart templates to find the perfect one that’ll captivate your audience and level up your data storytelling.

Recommendations and next steps

Wrap up by providing recommendations based on the case study findings. Outline the next steps that stakeholders should take to either expand on the success of the project or address any remaining challenges.

Acknowledgments and references

Thank the people who contributed to the case study and helped in the problem-solving process. Cite any external resources, reports or data sets that contributed to your analysis.

Feedback & Q&A session

Open the floor for questions and feedback from your audience. This allows for further discussion and can provide additional insights that may not have been considered previously.

Closing remarks

Conclude the presentation by summarizing the key points and emphasizing the takeaways. Thank your audience for their time and participation and express your willingness to engage in further discussions or collaborations on the subject.

Well, the length of a case study presentation can vary depending on the complexity of the topic and the needs of your audience. However, a typical business or academic presentation often lasts between 15 to 30 minutes. 

This time frame usually allows for a thorough explanation of the case while maintaining audience engagement. However, always consider leaving a few minutes at the end for a Q&A session to address any questions or clarify points made during the presentation.

When it comes to presenting a compelling case study, having a well-structured template can be a game-changer. 

It helps you organize your thoughts, data and findings in a coherent and visually pleasing manner. 

Not all case studies are created equal and different scenarios require distinct approaches for maximum impact. 

To save you time and effort, I have curated a list of 5 versatile case study presentation templates, each designed for specific needs and audiences. 

Here are some best case study presentation examples that showcase effective strategies for engaging your audience and conveying complex information clearly.

1 . Lab report case study template

Ever feel like your research gets lost in a world of endless numbers and jargon? Lab case studies are your way out!

Think of it as building a bridge between your cool experiment and everyone else. It’s more than just reporting results – it’s explaining the “why” and “how” in a way that grabs attention and makes sense.

This lap report template acts as a blueprint for your report, guiding you through each essential section (introduction, methods, results, etc.) in a logical order.

Want to present your research like a pro? Browse our research presentation template gallery for creative inspiration!

2. Product case study template

It’s time you ditch those boring slideshows and bullet points because I’ve got a better way to win over clients: product case study templates.

Instead of just listing features and benefits, you get to create a clear and concise story that shows potential clients exactly what your product can do for them. It’s like painting a picture they can easily visualize, helping them understand the value your product brings to the table.

Grab the template below, fill in the details, and watch as your product’s impact comes to life!

3. Content marketing case study template

In digital marketing, showcasing your accomplishments is as vital as achieving them. 

A well-crafted case study not only acts as a testament to your successes but can also serve as an instructional tool for others. 

With this coral content marketing case study template—a perfect blend of vibrant design and structured documentation, you can narrate your marketing triumphs effectively.

4. Case study psychology template

Understanding how people tick is one of psychology’s biggest quests and case studies are like magnifying glasses for the mind. They offer in-depth looks at real-life behaviors, emotions and thought processes, revealing fascinating insights into what makes us human.

Writing a top-notch case study, though, can be a challenge. It requires careful organization, clear presentation and meticulous attention to detail. That’s where a good case study psychology template comes in handy.

Think of it as a helpful guide, taking care of formatting and structure while you focus on the juicy content. No more wrestling with layouts or margins – just pour your research magic into crafting a compelling narrative.

5. Lead generation case study template

Lead generation can be a real head-scratcher. But here’s a little help: a lead generation case study.

Think of it like a friendly handshake and a confident resume all rolled into one. It’s your chance to showcase your expertise, share real-world successes and offer valuable insights. Potential clients get to see your track record, understand your approach and decide if you’re the right fit.

No need to start from scratch, though. This lead generation case study template guides you step-by-step through crafting a clear, compelling narrative that highlights your wins and offers actionable tips for others. Fill in the gaps with your specific data and strategies, and voilà! You’ve got a powerful tool to attract new customers.

Related: 15+ Professional Case Study Examples [Design Tips + Templates]

So, you’ve spent hours crafting the perfect case study and are now tasked with presenting it. Crafting the case study is only half the battle; delivering it effectively is equally important. 

Whether you’re facing a room of executives, academics or potential clients, how you present your findings can make a significant difference in how your work is received. 

Forget boring reports and snooze-inducing presentations! Let’s make your case study sing. Here are some key pointers to turn information into an engaging and persuasive performance:

• Know your audience : Tailor your presentation to the knowledge level and interests of your audience. Remember to use language and examples that resonate with them.
• Rehearse : Rehearsing your case study presentation is the key to a smooth delivery and for ensuring that you stay within the allotted time. Practice helps you fine-tune your pacing, hone your speaking skills with good word pronunciations and become comfortable with the material, leading to a more confident, conversational and effective presentation.
• Start strong : Open with a compelling introduction that grabs your audience’s attention. You might want to use an interesting statistic, a provocative question or a brief story that sets the stage for your case study.
• Be clear and concise : Avoid jargon and overly complex sentences. Get to the point quickly and stay focused on your objectives.
• Use visual aids : Incorporate slides with graphics, charts or videos to supplement your verbal presentation. Make sure they are easy to read and understand.
• Tell a story : Use storytelling techniques to make the case study more engaging. A well-told narrative can help you make complex data more relatable and easier to digest.

Ditching the dry reports and slide decks? Venngage’s case study templates let you wow customers with your solutions and gain insights to improve your business plan. Pre-built templates, visual magic and customer captivation – all just a click away. Go tell your story and watch them say “wow!”

Nailed your case study, but want to make your presentation even stronger? Avoid these common mistakes to ensure your audience gets the most out of it:

Overloading with information

A case study is not an encyclopedia. Overloading your presentation with excessive data, text or jargon can make it cumbersome and difficult for the audience to digest the key points. Stick to what’s essential and impactful. Need help making your data clear and impactful? Our data presentation templates can help! Find clear and engaging visuals to showcase your findings.

Lack of structure

Jumping haphazardly between points or topics can confuse your audience. A well-structured presentation, with a logical flow from introduction to conclusion, is crucial for effective communication.

Ignoring the audience

Different audiences have different needs and levels of understanding. Failing to adapt your presentation to your audience can result in a disconnect and a less impactful presentation.

Poor visual elements

While content is king, poor design or lack of visual elements can make your case study dull or hard to follow. Make sure you use high-quality images, graphs and other visual aids to support your narrative.

Not focusing on results

A case study aims to showcase a problem and its solution, but what most people care about are the results. Failing to highlight or adequately explain the outcomes can make your presentation fall flat.

How to start a case study presentation?

Starting a case study presentation effectively involves a few key steps:

• Grab attention : Open with a hook—an intriguing statistic, a provocative question or a compelling visual—to engage your audience from the get-go.
• Set the stage : Briefly introduce the subject, context and relevance of the case study to give your audience an idea of what to expect.
• Outline objectives : Clearly state what the case study aims to achieve. Are you solving a problem, proving a point or showcasing a success?
• Agenda : Give a quick outline of the key sections or topics you’ll cover to help the audience follow along.
• Set expectations : Let your audience know what you want them to take away from the presentation, whether it’s knowledge, inspiration or a call to action.

How to present a case study on PowerPoint and on Google Slides?

Presenting a case study on PowerPoint and Google Slides involves a structured approach for clarity and impact using presentation slides :

• Title slide : Start with a title slide that includes the name of the case study, your name and any relevant institutional affiliations.
• Introduction : Follow with a slide that outlines the problem or situation your case study addresses. Include a hook to engage the audience.
• Objectives : Clearly state the goals of the case study in a dedicated slide.
• Findings : Use charts, graphs and bullet points to present your findings succinctly.
• Analysis : Discuss what the findings mean, drawing on supporting data or secondary research as necessary.
• Conclusion : Summarize key takeaways and results.
• Q&A : End with a slide inviting questions from the audience.

What’s the role of analysis in a case study presentation?

The role of analysis in a case study presentation is to interpret the data and findings, providing context and meaning to them. 

It helps your audience understand the implications of the case study, connects the dots between the problem and the solution and may offer recommendations for future action.

Is it important to include real data and results in the presentation?

Yes, including real data and results in a case study presentation is crucial to show experience,  credibility and impact. Authentic data lends weight to your findings and conclusions, enabling the audience to trust your analysis and take your recommendations more seriously

How do I conclude a case study presentation effectively?

To conclude a case study presentation effectively, summarize the key findings, insights and recommendations in a clear and concise manner. 

End with a strong call-to-action or a thought-provoking question to leave a lasting impression on your audience.

What’s the best way to showcase data in a case study presentation ?

The best way to showcase data in a case study presentation is through visual aids like charts, graphs and infographics which make complex information easily digestible, engaging and creative. 

Don’t just report results, visualize them! This template for example lets you transform your social media case study into a captivating infographic that sparks conversation.

Choose the type of visual that best represents the data you’re showing; for example, use bar charts for comparisons or pie charts for parts of a whole. 

Ensure that the visuals are high-quality and clearly labeled, so the audience can quickly grasp the key points. 

Keep the design consistent and simple, avoiding clutter or overly complex visuals that could distract from the message.

Choose a template that perfectly suits your case study where you can utilize different visual aids for maximum impact. 

Need more inspiration on how to turn numbers into impact with the help of infographics? Our ready-to-use infographic templates take the guesswork out of creating visual impact for your case studies with just a few clicks.

Related: 10+ Case Study Infographic Templates That Convert

Congrats on mastering the art of compelling case study presentations! This guide has equipped you with all the essentials, from structure and nuances to avoiding common pitfalls. You’re ready to impress any audience, whether in the boardroom, the classroom or beyond.

And remember, you’re not alone in this journey. Venngage’s Case Study Creator is your trusty companion, ready to elevate your presentations from ordinary to extraordinary. So, let your confidence shine, leverage your newly acquired skills and prepare to deliver presentations that truly resonate.

Go forth and make a lasting impact!

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How to Create a Survey

How to turn survey results into a great presentation

Turning survey results into presentation, choose the best data to share, tell a story, adhere to common design rules, create an additional report.

You’ve launched your survey . The results are in. Now it’s time to make sense of them.

Creating a survey results presentation is one of the best ways to analyze your results and present them to stakeholders in a format that makes them clear and understandable.

It’s not as simple as copying and pasting everything into a PowerPoint presentation, though. Here’s how you can create an awesome survey results presentation.

Why you should turn survey results into a presentation

Not everyone is going to be willing to sift through all your survey responses and tease out the relevant findings. That’s why you need to succinctly summarize those findings and make them digestible for everyone. A survey results presentation is the perfect tool.

How to create a survey results presentation: Best practices

Before you rush to turn your responses into a presentation, take the time to acquaint yourself with the following best practices.

Not every insight you collect from your survey is going to be relevant to your target audience. So start by narrowing down your dataset to include only information that’s useful. Think about what you want your audience to take away from your presentation, and then choose your data accordingly.

If you really want to capture your audience’s attention, tell a story with your presentation. Rather than just show them the raw data, explain what the findings mean and why your audience should care.

Using subjective feedback from surveys can work well. While it’s helpful to show data that proves your point, using specific examples can make your presentations much more powerful, writes corporate trainer Dana Brownlee .

There are several design best practices you should follow, writes Shonna Waters, Ph.D. , vice president of strategic alliances and partnerships at professional coaching platform BetterUp. That includes using a minimalistic background, placing only your major points on each slide, and avoiding blocks of copy. “Keep the presentation stimulating and appealing without overwhelming your audience with bright colors or too much font,” Waters advises.

Not all of your survey findings will be suitable to include in your presentation, but they may still be essential for stakeholders. “If you’re presenting data to senior executives or business clients, you might want to prepare a full report on your findings,” writes Swetha Amaresan , senior marketing coordinator at Nickelodeon International. “You wouldn’t refer to this document during a presentation, but you might hand this to your audience to read through on their own time.”

Turn survey results into a presentation with Jotform Report Builder

If you’re worried about keeping track of all the best practices above, let Jotform’s Report Builder do the hard work for you. Jotform Report Builder automatically turns your Jotform survey responses into beautiful, professional reports.

Create the perfect report with a range of charts and tables. You can drag and drop design elements to suit your tastes. Don’t worry about having to update your presentation once it’s designed — presentations are updated automatically with each new form submission.

Just so you know

Automatically turn your survey responses into professional presentations with Jotform Report Builder .

How Jotform can make surveys easy

Whether you want to create a survey or turn your existing survey into a report, Jotform is the ideal tool. With over 800 free survey templates , it’s easy to get started.

You can tailor the survey to your needs, choosing the format that works best for you. That could be a classic survey where all questions are listed on a single page, or you may opt for Jotform Cards, where you ask one question per page.

If you want to dig deeper, you can use conditional logic to create an interactive survey that changes depending on each user’s response. Conditional logic improves the quality of answers from respondents while also improving the completion rate.

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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.

• Open access
• Published: 14 May 2024

Objective response after immune checkpoint inhibitors in a chemotherapy-refractory pMMR/MSS metastatic rectal cancer patient primed with experimental AlloStim® immunotherapy

• Ariel Hirschfeld 1 ,
• Daniel Gurell 2 &
• Michael Har-Noy   ORCID: orcid.org/0000-0002-9342-9337 3  

Translational Medicine Communications volume  9 , Article number:  15 ( 2024 ) Cite this article

153 Accesses

Metrics details

Immune Checkpoint Inhibitor (ICI) immunotherapy is most effective in immune effector cell infiltrated ‘hot’ tumor lesions, such as occurs in deficient mismatch repair, microsatellite instability high (dMMR/MSI-H) colorectal cancer (CRC). However, most all metastatic CRC tumors are mismatch repair proficient/microsatellite stable (pMMR/MSS) ‘cold’ lesions, without significant immune cell infiltration, and are unresponsive to ICI. AlloStim®, is an experimental, allogeneic immunomodulatory cell therapy designed to convert ‘cold’ metastatic tumor lesions to ‘hot’ inflamed lesions. After AlloStim® immunotherapy, this cold to hot inflammatory mechanism can make it difficult to distinguish between pseudoprogression and actual progression on restaging CT scans, as inflamed metastatic lesions can appear larger and occult disease can appear as new small lesions.

To explore whether radiological progression after AlloStim® immunotherapy is due to immune-flare or disease progression, we administered a short course of a combination ICI therapy to a pMMR/MSS chemotherapy-refractory metastatic colorectal cancer patient enrolled in the StimVax Phase IIb clinical study that presented with radiological progression after AlloStim® immunotherapy. Our rationale was that an accelerated response to ICI should occur if the lesions were inflamed, while if the enlarged lesions were due to disease progression there would not be a response.

Here we report a rapid, significant reduction in tumor burden in response to ICI administration in an AlloStim® primed pMMR/MSS mCRC patient with retroperitoneal and lung metastases.

This rare objective response to ICIs in a pMMR/MSS mCRC patient supports further evaluation of the combination of AlloStim® with ICI immunotherapy in MSS mCRC and other cold or ICI refractory tumors.

Trial registration

National Library of Medicine (NLM) at the National Institutes of Health (NIH). Registered 22 June 2020, https://clinicaltrials.gov/study/NCT04444622 .

Immune checkpoint inhibitor (ICI)-based regimens have not yet shown meaningful positive outcomes in proficient DNA mismatch repair/microsatellite stable (pMMR/MSS) metastatic colorectal cancers (mCRC). Here we report a rare objective response in a pMMR/MSS heavily pre-treated metastatic colorectal cancer (mCRC) patient subsequent to a short course of an immune checkpoint inhibitor (ICI) combination after first being primed with an experimental immunomodulatory cell therapy drug, AlloStim®, designed to convert immunologically ‘cold’ tumors to ‘hot’ tumors, and a short, low dose course of regorafenib.

The FDA has approved ICI drugs targeting CTLA-4, PD-1, PD-L1 and LAG-3 checkpoint molecules for a variety of solid tumor indications, including melanoma, renal, bladder, lung, gastric, gastroesophageal junction, hepatocellular carcinoma and head and neck cancers. However, ICIs have demonstrated only limited efficacy in mCRC.

An anti-CTLA4 ICI, pembrolizumab, was approved in first line mCRC [ 1 ] and also approved in combination with the anti-PD-1 ICI, nivolumab, for a subset of mCRC patients that have deficient DNA mismatch repair/microsatellite instability-high (dMMR/MSI-H) status [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. However, this dMMR/MSI-H subset constitutes only ~ 5% of mCRC patients [ 9 ], while the remaining ~ 95% that present with pMMR/MSS status do not respond to ICI [ 6 , 8 , 10 , 11 , 12 , 13 ].

Most dMMR/MSI-H status tumors are considered immunologically ‘hot’ tumors, while pMMR/MSS status tumors are considered to be ‘cold’ [ 14 ]. ICI have demonstrated greater efficacy in hot tumors, characterized by an inflamed phenotype, including a high level of infiltrating T-cells and NK cells, an interferon-γ (IFN-γ) signature and upregulated PD-L1 expression, while cold tumors have an absence of tumor-infiltrating lymphocytes [ 15 ].

While dMMR/MSI-H mCRC patients are more responsive to ICI therapy, approximately 50% are refractory [ 16 , 17 , 18 ]. Resistance to ICI responsiveness, regardless of MMR/MSI status, is correlated with tumor mutational burden (TMB) [ 19 ]. Since somatic mutations can encode immunogenic neoantigens, high TMB is believed to be more likely to prime for infiltrating tumor-specific effector immune cells. Consistent with this, the dMMR/MSI-H patients that present with lower TMB values have been shown to be the non-responders, whereas patients with the highest TMB values tend to obtain benefit from ICI [ 16 ], particularly with anti-CTLA-4/PD-1 combination ICI immunotherapy [ 20 ].

Present strategies for increasing the effectiveness of ICI immunotherapy in pMMR/MSS mCRC cold tumors include evaluating combinations with other therapeutic methods, such as chemotherapy, targeted therapy, and radiotherapy [ 21 ]. In addition, strategies to convert immunologically cold tumors to hot tumors are thought to be a fruitful line of investigation for increasing ICI efficacy in ICI refractory tumors [ 22 , 23 ].

AlloStim® is an experimental cellular immunotherapy drug designed to convert immunologically cold tumors to hot tumors by mirroring the graft vs. tumor (GVT) mechanism of allogeneic stem cell transplant procedures to create a host vs tumor (HVT) effect without graft vs. host disease (GVHD) toxicity [ 24 ]. AlloStim® is currently being evaluated as a monotherapy in the STIMVAX Phase IIB open label clinical trial in third-line chemotherapy-refractory pMMR/MSS mCRC (NCT04444622). The primary end-point in this study is overall survival (OS) and an exploratory end-point is objective tumor response by RECIST 1.1.

AlloStim® is a living, allogeneic (“off-the-shelf”), non-genetically manipulated, activated Th1-like immune cell therapy derived from CD4 + T-cell precursors isolated from the blood of healthy donors. The STIMVAX protocol provides for three monthly cycles of weekly AlloStim® administration (intradermal and intravenous) designed to increase circulating memory Th1/Th2 ratio [ 25 ], activate circulating memory T cells and NK cells, which in turn causes their extravasation to tumor sites [ 24 ]. The anti-tumor effects are correlated with the establishment of an IFN-γ dominated microenvironment [ 26 ]. The systemic tumor infiltration mechanism serves to convert immunologically cold tumors to hot tumors. The modulation of the tumor microenvironment (TME) can also counter-regulate tumor-mediated immune suppression [ 27 ].

AlloStim®-mediated intratumoral type I cytokine production by infiltrating activated T-cells and NK cells, including IL-12 and IFN-γ, is believed to: upregulate MHC-I on tumor cells making them susceptible to CD8 + T-cell recognition; cause maturation of dendritic cells to DC1 (IL-12 + CD80/86 positive, MHC I and MHC II positive); convert M2 macrophages to M1 [ 28 ]; and, release neoantigens into the TME [ 29 , 30 ]. The release of neoantigens into an inflammatory TME creates the conditions for in-situ vaccination [ 31 ] where immature dendritic cells mature to type I dendritic cells (DC1), process the released chaperoned neoantigens, migrate to the draining lymph nodes, resulting in a patient-specific anti-tumor adaptive immune response [ 32 ].

In previous clinical studies, the inflammatory mechanism of AlloStim® almost always caused post-treatment CT scan images to be read as progressive disease (PD), with systemic increases in size of existing tumor lesions and often the appearance of new small lesions (especially in lungs). However, this PD determination did not always correlate with the clinical status of the patient or with overall survival (OS). As the systemic increase in target lesion size could be due to peritumoral inflammation that occurs when tumor lesions convert from cold to hot and new small lesions could be the result of inflammation of occult disease, it is difficult to distinguish tumor progression from pseudoprogression using CT scan imaging after experimental AlloStim® experimental treatment.

Pseudoprogression after immunotherapy has been observed in patients with various tumor types and is thought to be due to transient immune cell infiltration into the tumor [ 33 ]. The phenomenon of pseudoprogression has led to modification of the RECIST 1.1 evaluation criteria [ 34 ]. The understanding that tumor growth by RECIST does not necessarily translate to disease progression in patients treated with immunotherapy has also led to the development of immune-related response criteria (irRC) to better surveil these patients [ 35 , 36 ].

However, it is still considered challenging to distinguish radiological progression from pseudoprogression and, consequently, to define the best management for these patients. In additional, a new category of “hyper-progression” and dissociated atypical responses have also been described after immunotherapy [ 37 ]. These issues have resulted in some subjects being prematurely removed from immunotherapy clinical trials [ 38 ].

In the CheckMate 142 clinical trial, nivolumab (3 mg/kg) plus low-dose ipilimumab (1 mg/kg) provided durable clinical benefit, and a manageable safety profile in patients with previously treated dMMR/MSI-H metastatic CRC [ 39 ]. Due to the improved safety profile of the lower dose ipilimumab in this combination, we decided to test this regimen in a chemotherapy-refractory mCRC pMMR/MSS patient presenting with radiological progression after 3 cycles of AlloStim® experimental immunotherapy.

We hypothesized that if the radiological progression was due to inflammation within the tumor lesions (hot tumors), a short course of ICI immunotherapy should result in a rapid reduction in tumor burden, due to release of suppression of resident infiltrating effector immune cells. On the other hand, if the enlarged and increased number of lesions were due to true progression and no infiltrating effector immune cells were present, either no response or further progression would be expected to be observed.

Case presentation

A 69 yo Caucasian male presented in March 2011 with blood in the stool. The patient’s medical and social history was significant for type 2 diabetes, hypertension, hypercholesterolemia, atrial fibrillation (s/p ablation) and was a former 2 pack/day smoker. Upon workup, was found to have a rectal mass and subsequently underwent low anterior resection (LAR). 2 of 24 nodes were found to be positive for adenocarcinoma disease with initial staging of pT2N1b. The patient was treated with adjuvant FOLFOX and achieved a complete response (CR). In August 2014, disease recurred and he underwent transanal resection plus radiation therapy (XRT). In April 2016, a right inguinal node was identified as metastatic adenocarcinoma and he received additional XRT. In January 2022, he presented with enlarged retroperitoneal nodes and was treated with 22 cycles of FOLFIRI plus Avastin from January 2022 to November 2022. In January 2023, was treated again with FOLFOX, but developed a reaction to oxaliplatin.

CT scan on April 26, 2023 showed appearance of innumerable bilateral pleural parenchymal lung nodules significantly increased in size and number from prior examination on March 8, 2023 and significant worsening of mediastinal and hilar lymphadenopathy consistent with progressive metastatic disease. No suspicious liver lesions were found and stable non-specific retroperitoneal adenopathy was also noted. Target lesions were identified in the lungs. The retroperitoneal disease was too small (< 15 mm) to be included in the RECIST 1.1 evaluation.

Patient consented on April 21, 2023 to received AlloStim® experimental immunotherapy as part of the STIMVAX Phase IIB clinical trial (NCT04444622). Eligible patients had histologically confirmed pMMR/MSS adenocarcinoma of the colon or rectum; received all available standard systemic therapies (fluoropyrimidines, oxaliplatin, irinotecan, and bevacizumab; cetuximab or panitumumab if RAS wild-type tumors); were aged 18 years or older; had adequate organ function; Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1, and measurable disease. The study was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice Guidelines after approval by a central institutional review board (IRB) and the ethics board at each institution where applicable.

The dosing and procedure schedule is shown in Table  1 and longitudinal changes in lung target lesions from CT scans are shown in Fig.  1 . Three 28-day cycles of weekly AlloStim® immunotherapy were administered per protocol from May 9, 2023 to September 26, 2023. The CT scan comparison from baseline (April 26, 2023) to completion of the AlloStim® three cycles (October 10, 2023) demonstrated progressive disease (PD) by RECIST 1.1 evaluating target lesions in the lungs and retroperitoneum (sum of diameters of target lesions =  + 73%) with increased non-target retroperitoneal adenopathy and innumerable enlarging and new thoracic nodules.

Matched CT scans and biopsies of liver target lesions in two MSS mCRC subjects at baseline and at day 84 after 3 AlloStim® cycles. Subject #1 shows extensive tumor (red circle) on the periphery of areas of fibrosis without immune cell infiltration at baseline. The corresponding CT scan shows the biopsied target tumor in liver After 3 cycles of AlloStim®, the re-staging CT scan on day 84 shows progressive disease. However, the corresponding biopsies show areas of coagulative necrosis and immune cell infiltration. Subject #2 has almost completely solid tumor at baseline. The re-staging CT scan indicates progressive disease, however note the extensive peri-tumoral inflammation. The corresponding biopsy indicates large area of tumor necrosis and tumor admixed with immune cells

From October 11, 2023 to October 23, 2023, a short, reduced dose of regorafenib was administered followed by a short course of nivolumab (240 mg) and low dose ipilimumab (1 mg/kg) administered between October 23, 2023 and December 4, 2023. No treatment was administered from December 12, 2023 and February 8, 2024 during which time a tapering dose of oral prednisone beginning at 60 mg/day was administered for treatment of colitis (adverse effect from the combination ICI immunotherapy), a restaging CT scan was then obtained on February 8, 2024.

The February 8, 2024 scan demonstrated a partial response (PR) by RECIST 1.1 criteria in comparison to the post-AlloStim® scan on October 10, 2023 (change in sum of diameters of target lesions = -48%) with the previously observed innumerable non-target thoracic lesions and retroperitoneal adenopathy uniformly decreased in size and number. Comparison to the April 26, 2023 baseline scan was read as stable disease (SD) with a 10% decrease in sum of diameters of target lesions (see Fig. 2 ).

Longitudinal changes in two lung target lesions (orange arrows). The slices are adjusted to show the view with the measurement in the longest tumor diameter. Red circles indicate presence or absence of non-target lesions in the selected slices. An increase in size of non-target existing lesions and appearance of new non-target lesions seen on post-AlloStim October 10, 2023 compared to April 26, 2023 baseline. Elimination or reduction in size of the non-target lesions seen in the post-ICI February 8, 2024 scan. According to RECIST 1.1, the October 10, 2023 scan compared to April 26, 2023 is scored as PD. The February 8, 2024 scan compared to October 10, 2023 is scored as PR. The February 8, 2024 compared to April 26, 2023 is scored as SD.

Serum levels of IL-12 levels were negligible prior to AlloStim® administration. After AlloStim® dosing, IL-12 became detectable after the first cycle and remained detectible over the 3 cycles of AlloStim® administration. Soluble heat shock protein (HSP)-70 was also negligible at baseline but was elevated throughout the experimental immunotherapy dosing (see Fig.  3 ).

IL-12 and HSP70 serum levels during allostim administration. Whole blood samples were collected longitudinally from subjects in SST Tiger Top tubes. The tubes were spun at 3000 rpm and shipped overnight at 2-80C to the central lab facility where the serum was aseptically transferred to cryotubes and stored at -800C until analysis. For analysis, samples were diluted 1:2 and plated in triplicate on ELISA plates (R&D Systems) and incubated for 2-3h at RT. The plates were read on a Cytation 7 plate reader (Agilent BioTek) at 650nm absorbance. A standard curve was generated using known samples. Quantitative levels were determined by comparing absorbance values to the standard curve. The bar graph shows the mean +/- SE at each sample timepoint

Here we present a rare case of rapid tumor debulking response subsequent to a short course of combination ICI immunotherapy in a heavily pre-treated pMMR/MSS mCRC patient presenting with radiological progression after third-line experimental AlloStim® immunotherapy and a short course of low dose regorafenib. Here we consider the question whether the ICI immunotherapy alone or in combination with previous AlloStim®, or in combination with previous regorafenib alone, or with prior AlloStim® and regorafenib together was most likely responsible for eliciting this rare objective response in a cold tumor indication.

It seems unlikely that the combination ICI immunotherapy could be solely responsible for the observed response. ICI-based regimens both as monotherapy [ 40 , 41 ] or as combination therapies [ 42 ] have not previously shown any meaningful positive outcomes in pMMR/MSS colorectal cancers.

For example, an initial phase II study assessed the efficacy of tremelimumab, a monoclonal antibody against CTLA4, in patients with treatment-refractory mCRC, which resulted in no improvement post-treatment [ 43 ]. Furthermore, two phase I studies of anti-PD-1 [ 44 ] and anti-PD-L1 [ 45 ] in previously-treated mCRC patients produced no responses. ICI regimens also failed as maintenance therapy after first line therapy in the MODUL study [ 46 ].

In general, ICI immunotherapy combining CTLA-4 and PD-L1 inhibitors have also shown very limited clinical benefit in patients with non-selected mCRC. A rare partial response (PR) (1/119) was reported in a randomized phase 2 clinical trial which evaluated the efficacy of combination durvalumab (anti-PD-L1) and tremelimumab (anti-CTLA-4) in patients with advanced refractory mCRC. In this study, 119 patients were assigned to the treatment group and 61 patients were assigned to best supportive care (BSC) alone. Patients in the treatment group received a median of 12 weeks of durvalumab and 12 weeks of tremelimumab [ 47 ], while in the present case only 5 weeks of ICI combination therapy was administered.

The phase II KEYNOTE-016 trial was performed to evaluate the clinical efficacy of single agent pembrolizumab in patients with pMMR/MSS mCRC, dMMR/MSI-H mCRC and or dMMR/MSI-H non-CRC. No responses were noted in 18 patients in the pMMR/MSS mCRC group [ 48 ]. In a clinical study which included 59 pMMR/MSS mCRC patients treated with ICI beyond radiological progression by RECIST 1.1, no patient demonstrated subsequent radiographical tumor shrinkage at a median of 42 days [ 49 ].

It has been reported that a small subset (~ 2%) of patients with pMMR/MSS colorectal cancer with a mutation in POLE and POLD1 enzymes and those without liver metastases have a higher chance of a response to ICI immunotherapy [ 50 ]. While the patient in the present case did not have POLE or POLD1 mutations, no liver metastases were present. Therefore, it is possible this patient was more susceptible to ICI immunotherapy, but seems unlikely that the short course of combination ICI alone was solely responsible for the extensive tumor debulking observed.

ICI strategies in combination with other drugs or procedures are under investigation, including evaluations of ICI in combinations with chemotherapy, radiotherapy, vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) inhibitors, mitogen-activated protein kinase (MEK) inhibitors, and signal transducer and activation of transcription 3 (STAT3) inhibitors [ 51 ]. However, these combination approaches have yet to demonstrate any significant anti-tumor activity in the clinical setting [ 12 , 52 , 53 ].

Could the short course of regorafenib alone or in combination with ICI immunotherapy be responsible for the objective tumor response observed in this case?

Regorafenib is approved for third-line mCRC based on the results of the CORRECT trial which demonstrated only a 1.4 month increase in the median survival compared to a placebo control (6.4 months vs. 5.0 months) [ 54 ]. In the Phase II TEXCAN trial, no objective responses were reported in 35 mCRC patients after 2 months of treatment with regorafenib according to RECIST 1.1, Choi, and modified Choi [ 55 ]. Therefore, it seems unlikely that the prior short course of low dose regorafenib alone could be responsible for the rare objective response reported here.

Regorafenib is a multi-kinase inhibitor that targets several receptor tyrosine kinases involved in angiogenesis and metastases (VEGFR1, VEGFR2, VEGFR3, FGFR1, FGFR2, TIE2, PDGFRs), oncogenesis (KIT, RET, RAF1), and tumor immunity (CSF1R). While regorafenib does not directly convert cold tumors to hot tumors, regorafenib is believed to possibly contribute to shifting the tumor microenvironment toward a more immune-responsive state. This constellation of mechanisms suggests that regorafenib could potentially be a combination partner for ICIs [ 56 ].

There are mixed results on the combination of regorafenib with ICI in clinical trials. Regorafenib in combination with PD‐1 antibody as a third‐line mCRC therapy has been evaluated in several studies. For example, 24 patients with MSS mCRC were included in the REGONIVO study. In this study, regorafenib was administered at 80–160 mg once daily for 21 days on and 7 days off together with nivolumab at 3 mg/kg every 2 weeks. A 33.3% objective response rate was reported with this regimen [ 57 ]. However, this promising activity has not been observed in other studies.

In a single site study, 18 mCRC patients treated with a combination of regorafenib and nivolumab, no objective responses were observed. In this study, 13 patients (69%) had progressive disease, and the median progression-free survival (PFS) was only 2 months. Four out of five patients in this study evaluated with stable disease (SD) occurred in patients without liver metastases, whereas a short disease stabilization was seen in 1 of 14 patients with history of liver metastases [ 58 ].

In another study in MSS mCRC patients, a combination of regorafenib and toripalimab, an anti-PD-1 ICI yielded an objective response rate of 15.2% (5 of 33 patients) with all (3 of 3) with lung-only metastasis responding [ 59 ]. In a retrospective study that involved 14 Chinese medical centers, a partial response rate of 5% (4 of 84 patients) was reported in MSS mCRC patients administered regorafenib combined with ICIs [ 60 ].

In a phase 2 study in patients from the USA with pMMR/MSS mCRC, regorafenib plus nivolumab yielded an objective response rate of 7%, with all responses observed in patients without liver metastases [ 61 ]. In this study, regorafenib was administered at 80 mg/day on a 3 weeks on/1 week off schedule and was increased to 120 mg/day if the 80 mg/day was well tolerated. Nivolumab was administered at 480 mg every 4 weeks.

Based on these data, we cannot rule out the possibility that the regorafenib pre-treatment may have primed for responsiveness to the ICI immunotherapy in this pMMR/MSS mCRC patient that presented without liver metastases.

However, in this case, the doses and frequencies of both regorafenib and of the combination ICI immunotherapy that were actually administered were significantly less that the doses administered in clinical trials where objective responses were observed.

In addition, in the present case, corticosteroids (CS) were administered 6 weeks after start of ICI administration. In a retrospective single institution study, patients were evaluated in two cohorts based on timing of initiation of CS after initiation of ICI immunotherapy (≥ 2 months vs < 2 months). The administration of CS < 2 months after initiation of ICI immunotherapy was found to significantly hinder ICI efficacy [ 62 ].

Since regorafenib does not directly convert cold tumors to hot tumors, which is necessary for priming ICI responsiveness, and the doses and frequencies of both regorafenib and the ICI immunotherapy used in the present case were at sub-optimal therapeutic levels, combined with the early use of CS, we believe, while possible, it is unlikely that the regorafenib priming was responsible for the rare objective tumor response observed here and it is more likely that a combination that converted the cold tumors to hot was responsible.

Therefore, we finally consider whether the experimental AlloStim® priming alone or in combination with regorafenib contributed to the ICI objective response.

We hypothesized that if the restaging CT scan after AlloStim® immunotherapy reported as progressive disease (PD) by RECIST 1.1, was actually pseudoprogression due to ‘hot’ inflammation of the tumor lesions which would make them appear to be larger than the actual tumor burden, that ICI immunotherapy would elicit a rapid tumor debulking response due to resident infiltrating effector immune cell release from suppression.

The present subject was negative for serum IL-12 at baseline. After three cycles of experimental AlloStim® immunotherapy the subject seroconverted to IL-12 positivity, supporting that the host immune system was modulated. We previously reported that IL-12 positivity correlated with long-term survival after AlloStim® immunotherapy [ 63 ].

IL-12 is an effector cytokine that promotes anti-tumor immunity by activating an effector Th1 response, which is required for the activation of cytotoxic T and NK cells [ 64 ]. IL-12 promotes production of IFN-γ which acts to upregulate PD-L1 in the tumor microenvironment (TME), which may make these tumors more susceptible to anti-PD-L1 ICI immunotherapy [ 65 , 66 , 67 ].

The presence of IL-12 can have many beneficial anti-tumor effects, including: increasing production of IFN-γ from NK and T cells [ 68 ]; stimulation of growth and cytotoxicity of activated NK cells and CD8 +  and CD4 +  T cells [ 69 ], shifting the Th1/Th2 balance in favor of the Th1 phenotype [ 70 ]; induction of antiangiogenic cytokine and chemokine production [ 71 ]; remodeling of the peritumoral extracellular matrix and tumor stroma [ 72 ], reprogramming of myeloid-derived suppressor cells [ 73 ], and increasing expression of MHC class I molecules necessary of cytolytic T-lymphocyte (CTL) recognition of tumor cells [ 74 ].

Soluble heat shock protein (HSP)-70 was also detected in the serum after AlloStim® administration. HSP-70 is a stress-inducible chaperone that is overexpressed within tumor cells, including CRC [ 75 ]. The finding of HSP-70 in serum suggests that tumor cells have been killed in a manner where the cell membrane is disrupted (immunological cell death), releasing the HSP along with danger signals into the tumor microenvironment. Hsp70 extracellular function is believed to be immunogenic and extracellular Hsp70 can serve as an adjuvant to activate the innate immune system [ 76 ] and can eventually lead to tumor-specific adaptive immunity [ 77 ]. Endogenous HSP chaperone all tumor cell antigens, including self- and neo-antigens. Tumors accumulate mutations that can cause tumor-specific neo-antigen expression. Since these neo-antigens are intracellular, they may not have been previously exposed to the immune system, as the tumors sequester these neoantigens. Thus the presence of soluble HSP-70 supports that AlloStim® modified the TME in a manner that caused tumor lysis and release of chaperoned neoantigens. Exposure of tumor neoantigens to the immune system increases responsiveness to ICI [ 78 ].

The mechanism of action of AlloStim® is also consistent with the conclusion that an inflammatory cold to hot conversion occurred which caused the dramatic 73% increase in target lesion size by RECIST 1.1. The immune systems of patients with metastatic cancers are dysregulated resulting in a shift toward Th2 dominance [ 79 , 80 , 81 ]. AlloStim® experimental immunotherapy modulates the dysregulated immune systems of these patients to a Th1 dominance using a strategy of allo-priming [ 82 ]. The STIMVAX protocol incorporated a first series of intradermal injections of AlloStim®. The host rejection of the intentionally mis-matched AlloStim® cells shortly after administration results in increased titers of allo-specific Th1 and CTL cells, modulating the resident Th1/Th2 balance.

These allo-specific cells elicited after intradermal injections are non-specifically activated by cytokine release after intravenous infusion of AlloStim® through a bystander activation mechanism [ 83 ]. Activated T-cells can extravasate and local inflammation attracts these cells into tissues and sites of inflammation, including tumors [ 84 ]. Thus, the intravenous infusion of AlloStim® after allo-priming can convert “cold” tumors into “hot” tumors with extensive infiltration of Th1/CTL memory cells, which could possibly account for the 73% increase in target lesion size.

Inflamed tumor lesions can enlarge and appear as PD by RECIST 1.1. However, the putative anti-tumor mechanism leading to tumor debulking immunity may take several additional months before a radiological response can be detected and patients are often removed from the treatment protocols before a later assessment can be conducted.

We hypothesized that based on the mechanism of action of AlloStim® that radiological progression after 3 cycles likely represents a beneficial immune response that has primed the tumor lesions for an eventual debulking anti-tumor response. In order to support this hypothesis, we administered a short course of combination ICI immunotherapy. Since pMMR/MSS mCRC is known not to be responsive to ICI immunotherapy, we predicted that if a rapid tumor debulking response were observed, this would provide evidence supporting that the tumor lesions had been previously primed with infiltrating effector immune cells.

The available evidence makes it appear likely that AlloStim® played a role in eliciting the objective response observed after regorafenib and combination ICI immunotherapy.

The rare objective response in this case provides support for further investigation of the combination of AlloStim® combined with ICI immunotherapy with/or without regorafenib in ICI resistant patients.

Availability of data and materials

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

Abbreviations

Twice a day

Basic supportive care

Colorectal cancer

Corticosteroid

Colony stimulating factor receptor-1

Computed tomography

Cytolytic T-lymphocyte

Cytotoxic T-lymphocyte associated protein 4

C-X-C motif chemokine receptor-3

Dendritic cell type 1

Deficient DNA mismatch repair

Deoxyribonucleic acid

Eastern Cooperative Oncology Group

Food and drug administration

Epidermal growth factor receptor-1

Epidermal growth factor receptor-2

Folinic acid, fluorouracil and irinotecan

Folinic acid, fluorouracil and oxaliplatin

Graft vs. host disease

Graft vs. tumor

Immune checkpoint inhibitor

Intradermal

Interleukin

Immune related response criteria

Intravenous

Lymphocyte activation gene

Low anterior resection

• Metastatic colorectal cancer

Microsatellite instability high

• Microsatellite stable

Natural killer cell

Overall survival

Peripheral blood mononuclear cell

Progressive disease

Programmed death receptor-1

Platelet derived growth factor receptor

Programmed death receptor-ligand 1

Progression free survival

Proficient DNA mismatch repair

Polymerase delta-1

Polymerase epsilon

Partial response

Raf-1 proto-oncogene, serine/threonine kinase

Rat sarcoma gene

Response evaluation in solid tumors

Status post

Stable Disease

Signal transducer and activator of transcription 3

T-helper type 1

T-helper type 2

Three times a day

TEK tyrosine kinase, endothelial

Tumor infiltrating lymphocytes

Tumor mutational burden

Tumor microenvironment

United States of America

Vascular endothelial growth factor

Vascular endothelial growth factor receptor

Radiation therapy

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Acknowledgements

The authors wish to thank Axella Clinical Research (CRO) for assistance in coordinating data collection and research blood samples, Dr. Xiaochuan Yang and Eirini Topouzi for analyzing blood samples and assisting with preparation of figures. Dr. Elena Fingerut for managing the manufacturing of the study drug in accordance with good manufacturing practices and Thu Bui for managing blood donor collection pursuant to 21 CFR 1271 and the distribution of the frozen investigational product to the clinical site.

Mirror Biologics, Inc. is the sponsor of ITL-032-MCRC3-STIMVAX Phase IIB clinical trial and has funded the research.

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MHN wrote the manuscript with input and review from other authors. AH conceived the design of the study and was responsible for implementing the protocol and for patient care. DW reviewed the longitudinal CT scans and determined the RECIST 1.1 conclusions and selected the CT scan images.

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Correspondence to Michael Har-Noy .

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Salus IRB, 2111 W. Braker Lane, Ste 100, Austin, TX 78758, serves as the central ethics committee for this study (ITL-032-MCRC3-STIMVAX). Informed consent was obtained from all individual participants included in the study.

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The patient informed consent form provided consent to publish non-identifiable results.

Competing interests

MHN is the inventor of the investigational AlloStim® product and is the founder of Mirror Biologics, Inc. which sponsored the clinical study. AH and DG declare that they have no competing interests.

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Hirschfeld, A., Gurell, D. & Har-Noy, M. Objective response after immune checkpoint inhibitors in a chemotherapy-refractory pMMR/MSS metastatic rectal cancer patient primed with experimental AlloStim® immunotherapy. transl med commun 9 , 15 (2024). https://doi.org/10.1186/s41231-024-00174-y

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Published : 14 May 2024

DOI : https://doi.org/10.1186/s41231-024-00174-y

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Minghui Pharmaceutical to Present the Phase I/II Study of MHB088C (B7-H3 ADC) for the Treatment of Patients with Recurrent or Metastatic Solid Tumors in Late-breaking Oral Presentation at the 2024 ASCO Annual Meeting

S HANGHAI, May 8, 2024 PRNewswire -- Minghui Pharmaceutical, Inc., a late-stage clinical biopharmaceutical company focused on autoimmune diseases and oncology, will feature Dr. Lin Shen from Beijing Cancer Hospital at the upcoming ASCO Annual Meeting in Chicago. Dr. Shen will present the results from the Phase III clinical study of MHB088C, a well-differentiated B7-H3-targeting antibody-drug conjugate (ADC) for recurrent or metastatic solid tumors, in an oral presentation.

Oral PresentationAbstract Title: Results of a Phase 12 Study of MHB088C: a Novel B7-H3 Antibody-Drug Conjugate (ADC) Incorporating a Potent DNA Topoisomerase I Inhibitor in Recurrent or Metastatic Solid TumorsSession Title: Developmental Therapeutics - Molecularly Targeted Agents and Tumor BiologySession Date and Time: 632024; 8:00 AM-9:30 AM CDTPresentation TimeDuration: 8:00 AM - 8:06 AM CDTPresenter: Dr. Lin ShenAbstract ID: 3012

About MHB088C

MHB088C is a novel B7-H3 ADC generated through Minghui's SuperTopoiTM ADC platform. Minghui's proprietary payload is 5 to 10 times more potent than Dxd, retaining key advantages such as bystander effect while eliminating the risk of interstitial lung disease. Conjugated with Minghui's proprietary B7-H3 antibody, which has superior binding and internalization compared to the competitor's antibodies, MHB088C has demonstrated remarkable anti-tumor efficacy across various cancer types. It was 3 to 10 times more potent in killing tumor cells than the competitor's compound in xenograft models.

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About Minghui Pharmaceutical

Minghui Pharmaceutical, Inc. is a late-stage clinical biopharmaceutical company dedicated to developing innovative medicines for unmet medical needs in oncology and autoimmune diseases. Leveraging the expertise in medical science and the proprietary technology platforms, the company is developing a rich clinical-stage pipeline including a variety of first-in-class or best-in-class product candidates. For more information, please visit www.minghuipharma.com .

Forward-Looking Statements

This press release provided by Minghui Pharmaceutical Inc. (the "Company") contains forward-looking statements within the meaning of the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995, which may be accompanied by such words as "aim," "anticipate," "believe," "could," "estimate," "expect," "forecast," "intend," "may," "plan," "potential," "possible," "predict," "should," "will," "would" or words of similar meaning. These statements are based on the Company's current beliefs and expectations and subject to risks and uncertainties that may cause actual results to differ materially from those set forth in the statements herein. Risks and uncertainties include but not limited to: general industry conditions and competition; changes in economic and financial conditions of the Company's and the collaborators' businesses; the risk that clinical trials are discontinued or delayed for any reasons, including for efficacy, safety, enrollment, or manufacturing; the risk that success in early stage clinical trials may not be predictive of results in later stage trials or trials of other potential indications; the risk that positive results in a clinical trial may not be replicated in subsequent or confirmatory trials; expectations for regulatory approvals; challenges to obtain, maintain and enforce patents and other intellectual property protection for the Company's product(s) and product candidate(s). These forward-looking statements speak only as of the date they are posted to this website, and the Company undertakes no obligation to update any forward-looking statements contained herein.

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