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How to Write the Dissertation Findings or Results – Tips

Published by Grace Graffin at August 11th, 2021 , Revised On August 13, 2024

Each  part of the dissertation is unique, and some general and specific rules must be followed. The dissertation’s findings section presents the key results of your research without interpreting their meaning .

Theoretically, this is an exciting section of a dissertation because it involves writing what you have observed and found. However, it can be a little tricky if there is too much information to confuse the readers.

The goal is to include only the essential and relevant findings in this section. The results must be presented in an orderly sequence to provide clarity to the readers.

This section of the dissertation should be easy for the readers to follow, so you should avoid going into a lengthy debate over the interpretation of the results.

It is vitally important to focus only on clear and precise observations. The findings chapter of the  dissertation  is theoretically the easiest to write.

It includes  statistical analysis and a brief write-up about whether or not the results emerging from the analysis are significant. This segment should be written in the past sentence as you describe what you have done in the past.

This article will provide detailed information about  how to   write the findings of a dissertation .

When to Write Dissertation Findings Chapter

As soon as you have gathered and analysed your data, you can start to write up the findings chapter of your dissertation paper. Remember that it is your chance to report the most notable findings of your research work and relate them to the research hypothesis  or  research questions set out in  the introduction chapter of the dissertation .

You will be required to separately report your study’s findings before moving on to the discussion chapter  if your dissertation is based on the  collection of primary data  or experimental work.

However, you may not be required to have an independent findings chapter if your dissertation is purely descriptive and focuses on the analysis of case studies or interpretation of texts.

• Always report the findings of your research in the past tense.
• The dissertation findings chapter varies from one project to another, depending on the data collected and analyzed.
• Avoid reporting results that are not relevant to your research questions or research hypothesis.

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1. Reporting Quantitative Findings

The best way to present your quantitative findings is to structure them around the research  hypothesis or  questions you intend to address as part of your dissertation project.

Report the relevant findings for each research question or hypothesis, focusing on how you analyzed them.

Analysis of your findings will help you determine how they relate to the different research questions and whether they support the hypothesis you formulated.

While you must highlight meaningful relationships, variances, and tendencies, it is important not to guess their interpretations and implications because this is something to save for the discussion  and  conclusion  chapters.

Any findings not directly relevant to your research questions or explanations concerning the data collection process  should be added to the dissertation paper’s appendix section.

Use of Figures and Tables in Dissertation Findings

Suppose your dissertation is based on quantitative research. In that case, it is important to include charts, graphs, tables, and other visual elements to help your readers understand the emerging trends and relationships in your findings.

Repeating information will give the impression that you are short on ideas. Refer to all charts, illustrations, and tables in your writing but avoid recurrence.

The text should be used only to elaborate and summarize certain parts of your results. On the other hand, illustrations and tables are used to present multifaceted data.

It is recommended to give descriptive labels and captions to all illustrations used so the readers can figure out what each refers to.

How to Report Quantitative Findings

Here is an example of how to report quantitative results in your dissertation findings chapter;

Two hundred seventeen participants completed both the pretest and post-test and a Pairwise T-test was used for the analysis. The quantitative data analysis reveals a statistically significant difference between the mean scores of the pretest and posttest scales from the Teachers Discovering Computers course. The pretest mean was 29.00 with a standard deviation of 7.65, while the posttest mean was 26.50 with a standard deviation of 9.74 (Table 1). These results yield a significance level of .000, indicating a strong treatment effect (see Table 3). With the correlation between the scores being .448, the little relationship is seen between the pretest and posttest scores (Table 2). This leads the researcher to conclude that the impact of the course on the educators’ perception and integration of technology into the curriculum is dramatic.

Paired Samples

Paired Samples Correlation

Paired Samples Test

Also Read: How to Write the Abstract for the Dissertation.

2. Reporting Qualitative Findings

A notable issue with reporting qualitative findings is that not all results directly relate to your research questions or hypothesis.

The best way to present the results of qualitative research is to frame your findings around the most critical areas or themes you obtained after you examined the data.

In-depth data analysis will help you observe what the data shows for each theme. Any developments, relationships, patterns, and independent responses directly relevant to your research question or hypothesis should be mentioned to the readers.

Additional information not directly relevant to your research can be included in the appendix .

How to Report Qualitative Findings

Here is an example of how to report qualitative results in your dissertation findings chapter;

The last question of the interview focused on the need for improvement in Thai ready-to-eat products and the industry at large, emphasizing the need for enhancement in the current products being offered in the market. When asked if there was any particular need for Thai ready-to-eat meals to be improved and how to improve them in case of ‘yes,’ the males replied mainly by saying that the current products need improvement in terms of the use of healthier raw materials and preservatives or additives. There was an agreement amongst all males concerning the need to improve the industry for ready-to-eat meals and the use of more healthy items to prepare such meals. The females were also of the opinion that the fast-food items needed to be improved in the sense that more healthy raw materials such as vegetable oil and unsaturated fats, including whole-wheat products, to overcome risks associated with trans fat leading to obesity and hypertension should be used for the production of RTE products. The frozen RTE meals and packaged snacks included many preservatives and chemical-based flavouring enhancers that harmed human health and needed to be reduced. The industry is said to be aware of this fact and should try to produce RTE products that benefit the community in terms of healthy consumption.

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What to Avoid in Dissertation Findings Chapter

• Avoid using interpretive and subjective phrases and terms such as “confirms,” “reveals,” “suggests,” or “validates.” These terms are more suitable for the discussion chapter , where you will be expected to interpret the results in detail.
• Only briefly explain findings in relation to the key themes, hypothesis, and research questions. You don’t want to write a detailed subjective explanation for any research questions at this stage.

The Do’s of Writing the Findings or Results Section

• Ensure you are not presenting results from other research studies in your findings.
• Observe whether or not your hypothesis is tested or research questions answered.
• Illustrations and tables present data and are labelled to help your readers understand what they relate to.
• Use software such as Excel, STATA, and SPSS to analyse results and important trends.

Essential Guidelines on How to Write Dissertation Findings

The dissertation findings chapter should provide the context for understanding the results. The research problem should be repeated, and the research goals should be stated briefly.

This approach helps to gain the reader’s attention toward the research problem. The first step towards writing the findings is identifying which results will be presented in this section.

The results relevant to the questions must be presented, considering whether the results support the hypothesis. You do not need to include every result in the findings section. The next step is ensuring the data can be appropriately organized and accurate.

You will need to have a basic idea about writing the findings of a dissertation because this will provide you with the knowledge to arrange the data chronologically.

Start each paragraph by writing about the most important results and concluding the section with the most negligible actual results.

A short paragraph can conclude the findings section, summarising the findings so readers will remember as they transition to the next chapter. This is essential if findings are unexpected or unfamiliar or impact the study.

Our writers can help you with all parts of your dissertation, including statistical analysis of your results . To obtain free non-binding quotes, please complete our online quote form here .

Be Impartial in your Writing

When crafting your findings, knowing how you will organize the work is important. The findings are the story that needs to be told in response to the research questions that have been answered.

Therefore, the story needs to be organized to make sense to you and the reader. The findings must be compelling and responsive to be linked to the research questions being answered.

Always ensure that the size and direction of any changes, including percentage change, can be mentioned in the section. The details of p values or confidence intervals and limits should be included.

The findings sections only have the relevant parts of the primary evidence mentioned. Still, it is a good practice to include all the primary evidence in an appendix that can be referred to later.

The results should always be written neutrally without speculation or implication. The statement of the results mustn’t have any form of evaluation or interpretation.

Negative results should be added in the findings section because they validate the results and provide high neutrality levels.

The length of the dissertation findings chapter is an important question that must be addressed. It should be noted that the length of the section is directly related to the total word count of your dissertation paper.

The writer should use their discretion in deciding the length of the findings section or refer to the dissertation handbook or structure guidelines.

It should neither belong nor be short nor concise and comprehensive to highlight the reader’s main findings.

Ethically, you should be confident in the findings and provide counter-evidence. Anything that does not have sufficient evidence should be discarded. The findings should respond to the problem presented and provide a solution to those questions.

Structure of the Findings Chapter

The chapter should use appropriate words and phrases to present the results to the readers. Logical sentences should be used, while paragraphs should be linked to produce cohesive work.

You must ensure all the significant results have been added in the section. Recheck after completing the section to ensure no mistakes have been made.

The structure of the findings section is something you may have to be sure of primarily because it will provide the basis for your research work and ensure that the discussions section can be written clearly and proficiently.

One way to arrange the results is to provide a brief synopsis and then explain the essential findings. However, there should be no speculation or explanation of the results, as this will be done in the discussion section.

Another way to arrange the section is to present and explain a result. This can be done for all the results while the section is concluded with an overall synopsis.

This is the preferred method when you are writing more extended dissertations. It can be helpful when multiple results are equally significant. A brief conclusion should be written to link all the results and transition to the discussion section.

Numerous data analysis dissertation examples are available on the Internet, which will help you improve your understanding of writing the dissertation’s findings.

Problems to Avoid When Writing Dissertation Findings

One of the problems to avoid while writing the dissertation findings is reporting background information or explaining the findings. This should be done in the introduction section .

You can always revise the introduction chapter based on the data you have collected if that seems an appropriate thing to do.

Raw data or intermediate calculations should not be added in the findings section. Always ask your professor if raw data needs to be included.

If the data is to be included, then use an appendix or a set of appendices referred to in the text of the findings chapter.

Do not use vague or non-specific phrases in the findings section. It is important to be factual and concise for the reader’s benefit.

The findings section presents the crucial data collected during the research process. It should be presented concisely and clearly to the reader. There should be no interpretation, speculation, or analysis of the data.

The significant results should be categorized systematically with the text used with charts, figures, and tables. Furthermore, avoiding using vague and non-specific words in this section is essential.

It is essential to label the tables and visual material properly. You should also check and proofread the section to avoid mistakes.

The dissertation findings chapter is a critical part of your overall dissertation paper. If you struggle with presenting your results and statistical analysis, our expert dissertation writers can help you get things right. Whether you need help with the entire dissertation paper or individual chapters, our dissertation experts can provide customized dissertation support .

FAQs About Findings of a Dissertation

How do i report quantitative findings.

The best way to present your quantitative findings is to structure them around the research hypothesis or research questions you intended to address as part of your dissertation project. Report the relevant findings for each of the research questions or hypotheses, focusing on how you analyzed them.

How do I report qualitative findings?

The best way to present the qualitative research results is to frame your findings around the most important areas or themes that you obtained after examining the data.

An in-depth analysis of the data will help you observe what the data is showing for each theme. Any developments, relationships, patterns, and independent responses that are directly relevant to your research question or hypothesis should be clearly mentioned for the readers.

Can I use interpretive phrases like ‘it confirms’ in the finding chapter?

No, It is highly advisable to avoid using interpretive and subjective phrases in the finding chapter. These terms are more suitable for the discussion chapter , where you will be expected to provide your interpretation of the results in detail.

Can I report the results from other research papers in my findings chapter?

NO, you must not be presenting results from other research studies in your findings.

You May Also Like

Appendices or Appendixes are used to provide additional date related to your dissertation research project. Here we explain what is appendix in dissertation

A literature review is a survey of theses, articles, books and other academic sources. Here are guidelines on how to write dissertation literature review.

Table of contents is an essential part of dissertation paper. Here is all you need to know about how to create the best table of contents for dissertation.

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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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From Data to Discovery: The Findings Section of a Research Paper

Discover the role of the findings section of a research paper here. Explore strategies and techniques to maximize your understanding.

Are you curious about the Findings section of a research paper? Did you know that this is a part where all the juicy results and discoveries are laid out for the world to see? Undoubtedly, the findings section of a research paper plays a critical role in presenting and interpreting the collected data. It serves as a comprehensive account of the study’s results and their implications.

Well, look no further because we’ve got you covered! In this article, we’re diving into the ins and outs of presenting and interpreting data in the findings section. We’ll be sharing tips and tricks on how to effectively present your findings, whether it’s through tables, graphs, or good old descriptive statistics.

Overview of the Findings Section of a Research Paper

The findings section of a research paper presents the results and outcomes of the study or investigation. It is a crucial part of the research paper where researchers interpret and analyze the data collected and draw conclusions based on their findings. This section aims to answer the research questions or hypotheses formulated earlier in the paper and provide evidence to support or refute them.

In the findings section, researchers typically present the data clearly and organized. They may use tables, graphs, charts, or other visual aids to illustrate the patterns, trends, or relationships observed in the data. The findings should be presented objectively, without any bias or personal opinions, and should be accompanied by appropriate statistical analyses or methods to ensure the validity and reliability of the results.

Organizing the Findings Section

The findings section of the research paper organizes and presents the results obtained from the study in a clear and logical manner. Here is a suggested structure for organizing the Findings section:

Introduction to the Findings

Start the section by providing a brief overview of the research objectives and the methodology employed. Recapitulate the research questions or hypotheses addressed in the study.

To learn more about methodology, read this article .

Descriptive Statistics and Data Presentation

Present the collected data using appropriate descriptive statistics. This may involve using tables, graphs, charts, or other visual representations to convey the information effectively. Remember: we can easily help you with that.

Data Analysis and Interpretation

Perform a thorough analysis of the data collected and describe the key findings. Present the results of statistical analyses or any other relevant methods used to analyze the data. 

Discussion of Findings

Analyze and interpret the findings in the context of existing literature or theoretical frameworks . Discuss any patterns, trends, or relationships observed in the data. Compare and contrast the results with prior studies, highlighting similarities and differences. 

Limitations and Constraints

Acknowledge and discuss any limitations or constraints that may have influenced the findings. This could include issues such as sample size, data collection methods, or potential biases. 

Summarize the main findings of the study and emphasize their significance. Revisit the research questions or hypotheses and discuss whether they have been supported or refuted by the findings.

Presenting Data in the Findings Section

There are several ways to present data in the findings section of a research paper. Here are some common methods:

• Tables : Tables are commonly used to present organized and structured data. They are particularly useful when presenting numerical data with multiple variables or categories. Tables allow readers to easily compare and interpret the information presented. Learn how to cite tables in research papers here .
• Graphs and Charts: Graphs and charts are effective visual tools for presenting data, especially when illustrating trends, patterns, or relationships. Common types include bar graphs, line graphs, scatter plots, pie charts, and histograms. Graphs and charts provide a visual representation of the data, making it easier for readers to comprehend and interpret.
• Figures and Images: Figures and images can be used to present data that requires visual representation, such as maps, diagrams, or experimental setups. They can enhance the understanding of complex data or provide visual evidence to support the research findings.
• Descriptive Statistics: Descriptive statistics provide summary measures of central tendency (e.g., mean, median, mode) and dispersion (e.g., standard deviation, range) for numerical data. These statistics can be included in the text or presented in tables or graphs to provide a concise summary of the data distribution.

How to Effectively Interpret Results

Interpreting the results is a crucial aspect of the findings section in a research paper. It involves analyzing the data collected and drawing meaningful conclusions based on the findings. Following are the guidelines on how to effectively interpret the results.

Step 1 – Begin with a Recap

Start by restating the research questions or hypotheses to provide context for the interpretation. Remind readers of the specific objectives of the study to help them understand the relevance of the findings.

Step 2 – Relate Findings to Research Questions

Clearly articulate how the results address the research questions or hypotheses. Discuss each finding in relation to the original objectives and explain how it contributes to answering the research questions or supporting/refuting the hypotheses.

Step 3 – Compare with Existing Literature

Compare and contrast the findings with previous studies or existing literature. Highlight similarities, differences, or discrepancies between your results and those of other researchers. Discuss any consistencies or contradictions and provide possible explanations for the observed variations.

Step 4 – Consider Limitations and Alternative Explanations

Acknowledge the limitations of the study and discuss how they may have influenced the results. Explore alternative explanations or factors that could potentially account for the findings. Evaluate the robustness of the results in light of the limitations and alternative interpretations.

Step 5 – Discuss Implications and Significance

Highlight any potential applications or areas where further research is needed based on the outcomes of the study.

Step 6 – Address Inconsistencies and Contradictions

If there are any inconsistencies or contradictions in the findings, address them directly. Discuss possible reasons for the discrepancies and consider their implications for the overall interpretation. Be transparent about any uncertainties or unresolved issues.

Step 7 – Be Objective and Data-Driven

Present the interpretation objectively, based on the evidence and data collected. Avoid personal biases or subjective opinions. Use logical reasoning and sound arguments to support your interpretations.

Reporting Statistical Significance

When reporting statistical significance in the findings section of a research paper, it is important to accurately convey the results of statistical analyses and their implications. Here are some guidelines on how to report statistical significance effectively:

• Clearly State the Statistical Test: Begin by clearly stating the specific statistical test or analysis used to determine statistical significance. For example, you might mention that a t-test, chi-square test, ANOVA, correlation analysis, or regression analysis was employed.
• Report the Test Statistic: Provide the value of the test statistic obtained from the analysis. This could be the t-value, F-value, chi-square value, correlation coefficient, or any other relevant statistic depending on the test used.
• State the Degrees of Freedom: Indicate the degrees of freedom associated with the statistical test. Degrees of freedom represent the number of independent pieces of information available for estimating a statistic. For example, in a t-test, degrees of freedom would be mentioned as (df = n1 + n2 – 2) for an independent samples test or (df = N – 2) for a paired samples test.
• Report the p-value: The p-value indicates the probability of obtaining results as extreme or more extreme than the observed results, assuming the null hypothesis is true. Report the p-value associated with the statistical test. For example, p < 0.05 denotes statistical significance at the conventional level of α = 0.05.
• Provide the Conclusion: Based on the p-value obtained, state whether the results are statistically significant or not. If the p-value is less than the predetermined threshold (e.g., p < 0.05), state that the results are statistically significant. If the p-value is greater than the threshold, state that the results are not statistically significant.
• Discuss the Interpretation: After reporting statistical significance, discuss the practical or theoretical implications of the finding. Explain what the significant result means in the context of your research questions or hypotheses. Address the effect size and practical significance of the findings, if applicable.
• Consider Effect Size Measures: Along with statistical significance, it is often important to report effect size measures. Effect size quantifies the magnitude of the relationship or difference observed in the data. Common effect size measures include Cohen’s d, eta-squared, or Pearson’s r. Reporting effect size provides additional meaningful information about the strength of the observed effects.
• Be Accurate and Transparent: Ensure that the reported statistical significance and associated values are accurate. Avoid misinterpreting or misrepresenting the results. Be transparent about the statistical tests conducted, any assumptions made, and potential limitations or caveats that may impact the interpretation of the significant results.

Conclusion of the Findings Section

The conclusion of the findings section in a research paper serves as a summary and synthesis of the key findings and their implications. It is an opportunity to tie together the results, discuss their significance, and address the research objectives. Here are some guidelines on how to write the conclusion of the Findings section:

Summarize the Key Findings

Begin by summarizing the main findings of the study. Provide a concise overview of the significant results, patterns, or relationships that emerged from the data analysis. Highlight the most important findings that directly address the research questions or hypotheses.

Revisit the Research Objectives

Remind the reader of the research objectives stated at the beginning of the paper. Discuss how the findings contribute to achieving those objectives and whether they support or challenge the initial research questions or hypotheses.

Suggest Future Directions

Identify areas for further research or future directions based on the findings. Discuss any unanswered questions, unresolved issues, or new avenues of inquiry that emerged during the study. Propose potential research opportunities that can build upon the current findings.

The Best Scientific Figures to Represent Your Findings 

Have you heard of any tool that helps you represent your findings through visuals like graphs, pie charts, and infographics? Well, if you haven’t, then here’s the tool you need to explore – Mind the Graph . It’s the tool that has the best scientific figures to represent your findings. Go, try it now, and make your research findings stand out!

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About Sowjanya Pedada

Sowjanya is a passionate writer and an avid reader. She holds MBA in Agribusiness Management and now is working as a content writer. She loves to play with words and hopes to make a difference in the world through her writings. Apart from writing, she is interested in reading fiction novels and doing craftwork. She also loves to travel and explore different cuisines and spend time with her family and friends.

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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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23 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?

For qualitative studies, can the findings be structured according to the Research questions? Thank you.

Do I need to include literature/references in my findings chapter?

This was very helpful

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The purpose of the discussion section is to interpret and describe the significance of your findings in relation to what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your research. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explains how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research.

Annesley, Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Peacock, Matthew. “Communicative Moves in the Discussion Section of Research Articles.” System 30 (December 2002): 479-497.

Importance of a Good Discussion

The discussion section is often considered the most important part of your research paper because it:

• Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;
• Presents the underlying meaning of your research, notes possible implications in other areas of study, and explores possible improvements that can be made in order to further develop the concerns of your research;
• Highlights the importance of your study and how it can contribute to understanding the research problem within the field of study;
• Presents how the findings from your study revealed and helped fill gaps in the literature that had not been previously exposed or adequately described; and,
• Engages the reader in thinking critically about issues based on an evidence-based interpretation of findings; it is not governed strictly by objective reporting of information.

Annesley Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Bitchener, John and Helen Basturkmen. “Perceptions of the Difficulties of Postgraduate L2 Thesis Students Writing the Discussion Section.” Journal of English for Academic Purposes 5 (January 2006): 4-18; Kretchmer, Paul. Fourteen Steps to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

• Do not be verbose or repetitive; be concise and make your points clearly
• Avoid the use of jargon or undefined technical language
• Follow a logical stream of thought; in general, interpret and discuss the significance of your findings in the same sequence you described them in your results section [a notable exception is to begin by highlighting an unexpected result or a finding that can grab the reader's attention]
• Use the present verb tense, especially for established facts; however, refer to specific works or prior studies in the past tense
• If needed, use subheadings to help organize your discussion or to categorize your interpretations into themes

II.  The Content

The content of the discussion section of your paper most often includes :

• Explanation of results : Comment on whether or not the results were expected for each set of findings; go into greater depth to explain findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning in relation to the research problem.
• References to previous research : Either compare your results with the findings from other studies or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results instead of being a part of the general literature review of prior research used to provide context and background information. Note that you can make this decision to highlight specific studies after you have begun writing the discussion section.
• Deduction : A claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or highlighting best practices.
• Hypothesis : A more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research]. This can be framed as new research questions that emerged as a consequence of your analysis.

III.  Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

• Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
• Use the same key terms, narrative style, and verb tense [present] that you used when describing the research problem in your introduction.
• Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
• Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequence of this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data [either within the text or as an appendix].
• Regardless of where it's mentioned, a good discussion section includes analysis of any unexpected findings. This part of the discussion should begin with a description of the unanticipated finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each of them in the order they appeared as you gathered or analyzed the data. As noted, the exception to discussing findings in the same order you described them in the results section would be to begin by highlighting the implications of a particularly unexpected or significant finding that emerged from the study, followed by a discussion of the remaining findings.
• Before concluding the discussion, identify potential limitations and weaknesses if you do not plan to do so in the conclusion of the paper. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of your findings. Avoid using an apologetic tone; however, be honest and self-critical [e.g., in retrospect, had you included a particular question in a survey instrument, additional data could have been revealed].
• The discussion section should end with a concise summary of the principal implications of the findings regardless of their significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This would demonstrate to the reader that you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results, usually in one paragraph.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the underlying meaning of your findings and state why you believe they are significant. After reading the discussion section, you want the reader to think critically about the results and why they are important. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. If applicable, begin this part of the section by repeating what you consider to be your most significant or unanticipated finding first, then systematically review each finding. Otherwise, follow the general order you reported the findings presented in the results section.

III.  Relate the Findings to Similar Studies

No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your results to those found in other studies, particularly if questions raised from prior studies served as the motivation for your research. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your study differs from other research about the topic. Note that any significant or unanticipated finding is often because there was no prior research to indicate the finding could occur. If there is prior research to indicate this, you need to explain why it was significant or unanticipated. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research in the social sciences is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your hypothesis or prior assumptions and biases. This is especially important when describing the discovery of significant or unanticipated findings.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Note any unanswered questions or issues your study could not address and describe the generalizability of your results to other situations. If a limitation is applicable to the method chosen to gather information, then describe in detail the problems you encountered and why. VI.  Make Suggestions for Further Research

You may choose to conclude the discussion section by making suggestions for further research [as opposed to offering suggestions in the conclusion of your paper]. Although your study can offer important insights about the research problem, this is where you can address other questions related to the problem that remain unanswered or highlight hidden issues that were revealed as a result of conducting your research. You should frame your suggestions by linking the need for further research to the limitations of your study [e.g., in future studies, the survey instrument should include more questions that ask..."] or linking to critical issues revealed from the data that were not considered initially in your research.

NOTE: Besides the literature review section, the preponderance of references to sources is usually found in the discussion section . A few historical references may be helpful for perspective, but most of the references should be relatively recent and included to aid in the interpretation of your results, to support the significance of a finding, and/or to place a finding within a particular context. If a study that you cited does not support your findings, don't ignore it--clearly explain why your research findings differ from theirs.

V.  Problems to Avoid

• Do not waste time restating your results . Should you need to remind the reader of a finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “In the case of determining available housing to single women with children in rural areas of Texas, the findings suggest that access to good schools is important...," then move on to further explaining this finding and its implications.
• As noted, recommendations for further research can be included in either the discussion or conclusion of your paper, but do not repeat your recommendations in the both sections. Think about the overall narrative flow of your paper to determine where best to locate this information. However, if your findings raise a lot of new questions or issues, consider including suggestions for further research in the discussion section.
• Do not introduce new results in the discussion section. Be wary of mistaking the reiteration of a specific finding for an interpretation because it may confuse the reader. The description of findings [results section] and the interpretation of their significance [discussion section] should be distinct parts of your paper. If you choose to combine the results section and the discussion section into a single narrative, you must be clear in how you report the information discovered and your own interpretation of each finding. This approach is not recommended if you lack experience writing college-level research papers.
• Use of the first person pronoun is generally acceptable. Using first person singular pronouns can help emphasize a point or illustrate a contrasting finding. However, keep in mind that too much use of the first person can actually distract the reader from the main points [i.e., I know you're telling me this--just tell me!].

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. "How to Write an Effective Discussion." Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008; The Lab Report. University College Writing Centre. University of Toronto; Sauaia, A. et al. "The Anatomy of an Article: The Discussion Section: "How Does the Article I Read Today Change What I Will Recommend to my Patients Tomorrow?” The Journal of Trauma and Acute Care Surgery 74 (June 2013): 1599-1602; Research Limitations & Future Research . Lund Research Ltd., 2012; Summary: Using it Wisely. The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion. Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide . Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Over-Interpret the Results!

Interpretation is a subjective exercise. As such, you should always approach the selection and interpretation of your findings introspectively and to think critically about the possibility of judgmental biases unintentionally entering into discussions about the significance of your work. With this in mind, be careful that you do not read more into the findings than can be supported by the evidence you have gathered. Remember that the data are the data: nothing more, nothing less.

MacCoun, Robert J. "Biases in the Interpretation and Use of Research Results." Annual Review of Psychology 49 (February 1998): 259-287; Ward, Paulet al, editors. The Oxford Handbook of Expertise . Oxford, UK: Oxford University Press, 2018.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretation of those results and their significance in relation to the research problem, not the data itself.

Azar, Beth. "Discussing Your Findings."  American Psychological Association gradPSYCH Magazine (January 2006).

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if the purpose of your research was to measure the impact of foreign aid on increasing access to education among disadvantaged children in Bangladesh, it would not be appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim or if analysis of other countries was not a part of your original research design. If you feel compelled to speculate, do so in the form of describing possible implications or explaining possible impacts. Be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand your discussion of the results in this way, while others don’t care what your opinion is beyond your effort to interpret the data in relation to the research problem.

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How To Write the Findings Section of a Research Paper

Posted by Rene Tetzner | Sep 2, 2021 | Paper Writing Advice | 0 |

How To Write the Findings Section of a Research Paper Each research project is unique, so it is natural for one researcher to make use of somewhat different strategies than another when it comes to designing and writing the section of a research paper dedicated to findings. The academic or scientific discipline of the research, the field of specialisation, the particular author or authors, the targeted journal or other publisher and the editor making the decisions about publication can all have a significant impact. The practical steps outlined below can be effectively applied to writing about the findings of most advanced research, however, and will prove especially helpful for early-career scholars who are preparing a research paper for a first publication.

Step 1 : Consult the guidelines or instructions that the targeted journal (or other publisher) provides for authors and read research papers it has already published, particularly ones similar in topic, methods or results to your own. The guidelines will generally outline specific requirements for the results or findings section, and the published articles will provide sound examples of successful approaches. Watch particularly for length limitations and restrictions on content. Interpretation, for instance, is usually reserved for a later discussion section, though not always – qualitative research papers often combine findings and interpretation. Background information and descriptions of methods, on the other hand, almost always appear in earlier sections of a research paper. In most cases it is appropriate in a findings section to offer basic comparisons between the results of your study and those of other studies, but knowing exactly what the journal wants in the report of research findings is essential. Learning as much as you can about the journal’s aims and scope as well as the interests of its readers is invaluable as well.

Step 2 : Reflect at some length on your research results in relation to the journal’s requirements while planning the findings section of your paper. Choose for particular focus experimental results and other research discoveries that are particularly relevant to your research questions and objectives, and include them even if they are unexpected or do not support your ideas and hypotheses. Streamline and clarify your report, especially if it is long and complex, by using subheadings that will help you avoid excessive and peripheral details as you write and also help your reader understand and remember your findings. Consider appendices for raw data that might interest specialists but prove too long or distracting for other readers. The opening paragraph of a findings section often restates research questions or aims to refocus the reader’s attention, and it is always wise to summarise key findings at the end of the section, providing a smooth intellectual transition to the interpretation and discussion that follows in most research papers. There are many effective ways in which to organise research findings. The structure of your findings section might be determined by your research questions and hypotheses or match the arrangement of your methods section. A chronological order or hierarchy of importance or meaningful grouping of main themes or categories might prove effective. It may be best to present all the relevant findings and then explain them and your analysis of them, or explaining the results of each trial or test immediately after reporting it may render the material clearer and more comprehensible for your readers. Keep your audience, your most important evidence and your research goals in mind.

Step 3 : Design effective visual presentations of your research results to enhance the textual report of your findings. Tables of various styles and figures of all kinds such as graphs, maps and photos are used in reporting research findings, but do check the journal guidelines for instructions on the number of visual aids allowed, any required design elements and the preferred formats for numbering, labelling and placement in the manuscript. As a general rule, tables and figures should be numbered according to first mention in the main text of the paper, and each one should be clearly introduced and explained at least briefly in that text so that readers know what is presented and what they are expected to see in a particular visual element. Tables and figures should also be self-explanatory, however, so their design should include all definitions and other information necessary for a reader to understand the findings you intend to show without returning to your text. If you construct your tables and figures before drafting your findings section, they can serve as focal points to help you tell a clear and informative story about your findings and avoid unnecessary repetition. Some authors will even work on tables and figures before organising the findings section (Step 2), which can be an extremely effective approach, but it is important to remember that the textual report of findings remains primary. Visual aids can clarify and enrich the text, but they cannot take its place.

Step 4 : Write your findings section in a factual and objective manner. The goal is to communicate information – in some cases a great deal of complex information – as clearly, accurately and precisely as possible, so well-constructed sentences that maintain a simple structure will be far more effective than convoluted phrasing and expressions. The active voice is often recommended by publishers and the authors of writing manuals, and the past tense is appropriate because the research has already been done. Make sure your grammar, spelling and punctuation are correct and effective so that you are conveying the meaning you intend. Statements that are vague, imprecise or ambiguous will often confuse and mislead readers, and a verbose style will add little more than padding while wasting valuable words that might be put to far better use in clear and logical explanations. Some specialised terminology may be required when reporting findings, but anything potentially unclear or confusing that has not already been defined earlier in the paper should be clarified for readers, and the same principle applies to unusual or nonstandard abbreviations. Your readers will want to understand what you are reporting about your results, not waste time looking up terms simply to understand what you are saying. A logical approach to organising your findings section (Step 2) will help you tell a logical story about your research results as you explain, highlight, offer analysis and summarise the information necessary for readers to understand the discussion section that follows.

Step 5 : Review the draft of your findings section and edit and revise until it reports your key findings exactly as you would have them presented to your readers. Check for accuracy and consistency in data across the section as a whole and all its visual elements. Read your prose aloud to catch language errors, awkward phrases and abrupt transitions. Ensure that the order in which you have presented results is the best order for focussing readers on your research objectives and preparing them for the interpretations, speculations, recommendations and other elements of the discussion that you are planning. This will involve looking back over the paper’s introductory and background material as well as anticipating the discussion and conclusion sections, and this is precisely the right point in the process for reviewing and reflecting. Your research results have taken considerable time to obtain and analyse, so a little more time to stand back and take in the wider view from the research door you have opened is a wise investment. The opinions of any additional readers you can recruit, whether they are professional mentors and colleagues or family and friends, will often prove invaluable as well.

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How To Write the Findings Section of a Research Paper These five steps will help you write a clear & interesting findings section for a research paper

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Home » Research Summary – Structure, Examples and Writing Guide

Research Summary – Structure, Examples and Writing Guide

Table of Contents

Research Summary

Definition:

A research summary is a brief and concise overview of a research project or study that highlights its key findings, main points, and conclusions. It typically includes a description of the research problem, the research methods used, the results obtained, and the implications or significance of the findings. It is often used as a tool to quickly communicate the main findings of a study to other researchers, stakeholders, or decision-makers.

Structure of Research Summary

The Structure of a Research Summary typically include:

• Introduction : This section provides a brief background of the research problem or question, explains the purpose of the study, and outlines the research objectives.
• Methodology : This section explains the research design, methods, and procedures used to conduct the study. It describes the sample size, data collection methods, and data analysis techniques.
• Results : This section presents the main findings of the study, including statistical analysis if applicable. It may include tables, charts, or graphs to visually represent the data.
• Discussion : This section interprets the results and explains their implications. It discusses the significance of the findings, compares them to previous research, and identifies any limitations or future directions for research.
• Conclusion : This section summarizes the main points of the research and provides a conclusion based on the findings. It may also suggest implications for future research or practical applications of the results.
• References : This section lists the sources cited in the research summary, following the appropriate citation style.

How to Write Research Summary

Here are the steps you can follow to write a research summary:

• Read the research article or study thoroughly: To write a summary, you must understand the research article or study you are summarizing. Therefore, read the article or study carefully to understand its purpose, research design, methodology, results, and conclusions.
• Identify the main points : Once you have read the research article or study, identify the main points, key findings, and research question. You can highlight or take notes of the essential points and findings to use as a reference when writing your summary.
• Write the introduction: Start your summary by introducing the research problem, research question, and purpose of the study. Briefly explain why the research is important and its significance.
• Summarize the methodology : In this section, summarize the research design, methods, and procedures used to conduct the study. Explain the sample size, data collection methods, and data analysis techniques.
• Present the results: Summarize the main findings of the study. Use tables, charts, or graphs to visually represent the data if necessary.
• Interpret the results: In this section, interpret the results and explain their implications. Discuss the significance of the findings, compare them to previous research, and identify any limitations or future directions for research.
• Conclude the summary : Summarize the main points of the research and provide a conclusion based on the findings. Suggest implications for future research or practical applications of the results.
• Revise and edit : Once you have written the summary, revise and edit it to ensure that it is clear, concise, and free of errors. Make sure that your summary accurately represents the research article or study.
• Add references: Include a list of references cited in the research summary, following the appropriate citation style.

Example of Research Summary

Here is an example of a research summary:

Title: The Effects of Yoga on Mental Health: A Meta-Analysis

Introduction: This meta-analysis examines the effects of yoga on mental health. The study aimed to investigate whether yoga practice can improve mental health outcomes such as anxiety, depression, stress, and quality of life.

Methodology : The study analyzed data from 14 randomized controlled trials that investigated the effects of yoga on mental health outcomes. The sample included a total of 862 participants. The yoga interventions varied in length and frequency, ranging from four to twelve weeks, with sessions lasting from 45 to 90 minutes.

Results : The meta-analysis found that yoga practice significantly improved mental health outcomes. Participants who practiced yoga showed a significant reduction in anxiety and depression symptoms, as well as stress levels. Quality of life also improved in those who practiced yoga.

Discussion : The findings of this study suggest that yoga can be an effective intervention for improving mental health outcomes. The study supports the growing body of evidence that suggests that yoga can have a positive impact on mental health. Limitations of the study include the variability of the yoga interventions, which may affect the generalizability of the findings.

Conclusion : Overall, the findings of this meta-analysis support the use of yoga as an effective intervention for improving mental health outcomes. Further research is needed to determine the optimal length and frequency of yoga interventions for different populations.

References :

• Cramer, H., Lauche, R., Langhorst, J., Dobos, G., & Berger, B. (2013). Yoga for depression: a systematic review and meta-analysis. Depression and anxiety, 30(11), 1068-1083.
• Khalsa, S. B. (2004). Yoga as a therapeutic intervention: a bibliometric analysis of published research studies. Indian journal of physiology and pharmacology, 48(3), 269-285.
• Ross, A., & Thomas, S. (2010). The health benefits of yoga and exercise: a review of comparison studies. The Journal of Alternative and Complementary Medicine, 16(1), 3-12.

Purpose of Research Summary

The purpose of a research summary is to provide a brief overview of a research project or study, including its main points, findings, and conclusions. The summary allows readers to quickly understand the essential aspects of the research without having to read the entire article or study.

Research summaries serve several purposes, including:

• Facilitating comprehension: A research summary allows readers to quickly understand the main points and findings of a research project or study without having to read the entire article or study. This makes it easier for readers to comprehend the research and its significance.
• Communicating research findings: Research summaries are often used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public. The summary presents the essential aspects of the research in a clear and concise manner, making it easier for non-experts to understand.
• Supporting decision-making: Research summaries can be used to support decision-making processes by providing a summary of the research evidence on a particular topic. This information can be used by policymakers or practitioners to make informed decisions about interventions, programs, or policies.
• Saving time: Research summaries save time for researchers, practitioners, policymakers, and other stakeholders who need to review multiple research studies. Rather than having to read the entire article or study, they can quickly review the summary to determine whether the research is relevant to their needs.

Characteristics of Research Summary

The following are some of the key characteristics of a research summary:

• Concise : A research summary should be brief and to the point, providing a clear and concise overview of the main points of the research.
• Objective : A research summary should be written in an objective tone, presenting the research findings without bias or personal opinion.
• Comprehensive : A research summary should cover all the essential aspects of the research, including the research question, methodology, results, and conclusions.
• Accurate : A research summary should accurately reflect the key findings and conclusions of the research.
• Clear and well-organized: A research summary should be easy to read and understand, with a clear structure and logical flow.
• Relevant : A research summary should focus on the most important and relevant aspects of the research, highlighting the key findings and their implications.
• Audience-specific: A research summary should be tailored to the intended audience, using language and terminology that is appropriate and accessible to the reader.
• Citations : A research summary should include citations to the original research articles or studies, allowing readers to access the full text of the research if desired.

When to write Research Summary

Here are some situations when it may be appropriate to write a research summary:

• Proposal stage: A research summary can be included in a research proposal to provide a brief overview of the research aims, objectives, methodology, and expected outcomes.
• Conference presentation: A research summary can be prepared for a conference presentation to summarize the main findings of a study or research project.
• Journal submission: Many academic journals require authors to submit a research summary along with their research article or study. The summary provides a brief overview of the study’s main points, findings, and conclusions and helps readers quickly understand the research.
• Funding application: A research summary can be included in a funding application to provide a brief summary of the research aims, objectives, and expected outcomes.
• Policy brief: A research summary can be prepared as a policy brief to communicate research findings to policymakers or stakeholders in a concise and accessible manner.

Advantages of Research Summary

Research summaries offer several advantages, including:

• Time-saving: A research summary saves time for readers who need to understand the key findings and conclusions of a research project quickly. Rather than reading the entire research article or study, readers can quickly review the summary to determine whether the research is relevant to their needs.
• Clarity and accessibility: A research summary provides a clear and accessible overview of the research project’s main points, making it easier for readers to understand the research without having to be experts in the field.
• Improved comprehension: A research summary helps readers comprehend the research by providing a brief and focused overview of the key findings and conclusions, making it easier to understand the research and its significance.
• Enhanced communication: Research summaries can be used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public, in a concise and accessible manner.
• Facilitated decision-making: Research summaries can support decision-making processes by providing a summary of the research evidence on a particular topic. Policymakers or practitioners can use this information to make informed decisions about interventions, programs, or policies.
• Increased dissemination: Research summaries can be easily shared and disseminated, allowing research findings to reach a wider audience.

Limitations of Research Summary

Limitations of the Research Summary are as follows:

• Limited scope: Research summaries provide a brief overview of the research project’s main points, findings, and conclusions, which can be limiting. They may not include all the details, nuances, and complexities of the research that readers may need to fully understand the study’s implications.
• Risk of oversimplification: Research summaries can be oversimplified, reducing the complexity of the research and potentially distorting the findings or conclusions.
• Lack of context: Research summaries may not provide sufficient context to fully understand the research findings, such as the research background, methodology, or limitations. This may lead to misunderstandings or misinterpretations of the research.
• Possible bias: Research summaries may be biased if they selectively emphasize certain findings or conclusions over others, potentially distorting the overall picture of the research.
• Format limitations: Research summaries may be constrained by the format or length requirements, making it challenging to fully convey the research’s main points, findings, and conclusions.
• Accessibility: Research summaries may not be accessible to all readers, particularly those with limited literacy skills, visual impairments, or language barriers.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Write an “Implications of Research” Section

4-minute read

• 24th October 2022

When writing research papers , theses, journal articles, or dissertations, one cannot ignore the importance of research. You’re not only the writer of your paper but also the researcher ! Moreover, it’s not just about researching your topic, filling your paper with abundant citations, and topping it off with a reference list. You need to dig deep into your research and provide related literature on your topic. You must also discuss the implications of your research.

Interested in learning more about implications of research? Read on! This post will define these implications, why they’re essential, and most importantly, how to write them. If you’re a visual learner, you might enjoy this video .

What Are Implications of Research?

Implications are potential questions from your research that justify further exploration. They state how your research findings could affect policies, theories, and/or practices.

Implications can either be practical or theoretical. The former is the direct impact of your findings on related practices, whereas the latter is the impact on the theories you have chosen in your study.

Example of a practical implication: If you’re researching a teaching method, the implication would be how teachers can use that method based on your findings.

Example of a theoretical implication: You added a new variable to Theory A so that it could cover a broader perspective.

Finally, implications aren’t the same as recommendations, and it’s important to know the difference between them .

Questions you should consider when developing the implications section:

●  What is the significance of your findings?

●  How do the findings of your study fit with or contradict existing research on this topic?

●  Do your results support or challenge existing theories? If they support them, what new information do they contribute? If they challenge them, why do you think that is?

Why Are Implications Important?

You need implications for the following reasons:

● To reflect on what you set out to accomplish in the first place

● To see if there’s a change to the initial perspective, now that you’ve collected the data

● To inform your audience, who might be curious about the impact of your research

How to Write an Implications Section

Usually, you write your research implications in the discussion section of your paper. This is the section before the conclusion when you discuss all the hard work you did. Additionally, you’ll write the implications section before making recommendations for future research.

Implications should begin with what you discovered in your study, which differs from what previous studies found, and then you can discuss the implications of your findings.

Your implications need to be specific, meaning you should show the exact contributions of your research and why they’re essential. They should also begin with a specific sentence structure.

Examples of starting implication sentences:

●  These results build on existing evidence of…

●  These findings suggest that…

●  These results should be considered when…

●  While previous research has focused on x , these results show that y …

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You should write your implications after you’ve stated the results of your research. In other words, summarize your findings and put them into context.

The result : One study found that young learners enjoy short activities when learning a foreign language.

The implications : This result suggests that foreign language teachers use short activities when teaching young learners, as they positively affect learning.

 Example 2

The result : One study found that people who listen to calming music just before going to bed sleep better than those who watch TV.

The implications : These findings suggest that listening to calming music aids sleep quality, whereas watching TV does not.

To summarize, remember these key pointers:

●  Implications are the impact of your findings on the field of study.

●  They serve as a reflection of the research you’ve conducted.              

●  They show the specific contributions of your findings and why the audience should care.

●  They can be practical or theoretical.

●  They aren’t the same as recommendations.

●  You write them in the discussion section of the paper.

●  State the results first, and then state their implications.

Are you currently working on a thesis or dissertation? Once you’ve finished your paper (implications included), our proofreading team can help ensure that your spelling, punctuation, and grammar are perfect. Consider submitting a 500-word document for free.

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Science, health, and public trust.

September 8, 2021

Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

• Discoveries in Basic Science: A Perfectly Imperfect Process
• When Clinical Research Is in the News
• What is Basic Science and Why is it Important?
• ​ What is a Research Organism?
• What Are Clinical Trials and Studies?
• Basic Research – Digital Media Kit
• Decoding Science: How Does Science Know What It Knows? (NAS)
• Can Science Help People Make Decisions ? (NAS)

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When bats were wiped out, more human babies died, a study found. Here's why

Researchers find infant deaths increased after farmers used more pesticides to compensate for rise of pests.

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A deadly pandemic has decimated bats in North America — and that has ultimately had harmful effects on humans, including higher rates of infant mortality, according to a new study.

The research is part of growing evidence that humans rely on the animal and plant species around them, and are harmed when those species decline or go extinct.

White-nose syndrome is a deadly fungal disease that kills an average of 70 per cent of bats it infects, and has been spreading to new areas since it was first reported on the continent in 2006.

The disease wakes bats during their hibernation, often causing them to freeze and starve to death.

What happens when bats aren't there for farmers?

Ecologists know that bats play a crucial role in eating up and controlling insect pests.

Because of that, Eyal Frank, an environmental economist at the University of Chicago, decided to look at what happened when white-nose syndrome spread into new counties in the eastern U.S., decimating bat populations.

He found that farmers responded to the resulting insect outbreaks by increasing their pesticide use 31 per cent. Pesticides are toxic, and often associated with human health impacts such as increases in infant deaths.

Frank found that infant mortality went up eight per cent after the arrival of white-nose syndrome in a county, according to his study published today in the journal Science .

"At first I was surprised," Frank said, noting those increases are "big effects."

But he noted that in regions affected by white-nose syndrome, bat populations don't just decline, but plummet, and are often wiped out altogether.

"This is really turning off the switch on biological pest control in some of these counties," he said.

That forces farmers to compensate with "a lot more insecticides," which he notes are toxic by design.

• World's globetrotting animals at risk due to habitat loss, climate change

Frank also found evidence that not only were the pesticides expensive, but they weren't as good as the bats at controlling insects — farmers' revenue from crop sales fell 29 per cent in areas hit by the bat pandemic.

He estimates that in total, farmers in communities with bat die-offs lost $26.9 billion between 2006 and 2017. Putting a number to damages from infant mortality resulted in a societal cost of $39.6 billion from the loss of bats.

B.C. researchers trying to stave off deadly bat disease

The importance of biodiversity.

The study shows how interactions between species such as bats and insects stabilize the ecosystems that other species rely on, including humans, who can be harmed when those species disappear, Frank said.

"These ecosystems are very complex systems with many interactions between species, and we do not fully understand what to expect or what will happen when we allow one species to fall below some viable population level or to go extinct," said Frank, who had previously linked the deaths of half a million people in India to the collapse of local vulture populations due to accidental poisoning.

• When India's vulture population collapsed, half a million human deaths followed: study

He added that preserving more species and more biodiversity can provide redundancies so that if one species declines, another may be able to fill its role.

Jianping Xu, a McMaster University professor who studies white-nose syndrome in North American bats, said the new study shows that bats are important "not only for ecosystem, but also for agriculture and for human health."

Xu, who did not participate in the research, said the "data looks pretty solid." While the study focused on the eastern U.S., Xu said white-nose syndrome is in all 10 Canadian provinces, and bats here are even more affected, as it's colder and they have a longer hibernation.

He'd like to see similar Canadian data on the link between bat declines,  pesticides and infant mortality.

"I wouldn't be surprised if Canadian data show a similar pattern," he said.

Xu added that increased use of pesticides is also linked to bat declines, creating a "vicious cycle." He believes pesticide applications should be limited to areas without bats.

• Can urban parks protect biodiversity as they welcome more visitors?
• Independent scientist resigns from pesticide regulator over transparency concerns

Bruce Lanphear, a health sciences professor and expert in pesticides at Simon Fraser University, said the study "elegantly" uses the pandemic among bats as a natural experiment to show the impact of pesticides on human health. But he noted the research has limitations in determining which pesticides were implicated in these health impacts.

Lanphear, who has been critical of the federal government's transparency when it comes to pesticides, said the findings should also lead us to "ask questions like, 'Why aren't our governments finding ways to reduce pesticide use?'"

ABOUT THE AUTHOR

Science, Climate, Environment Reporter

Emily Chung covers science, the environment and climate for CBC News. She has previously worked as a digital journalist for CBC Ottawa and as an occasional producer at CBC's Quirks & Quarks. She has a PhD in chemistry from the University of British Columbia. In 2019, she was part of the team that won a Digital Publishing Award for best newsletter for "What on Earth." You can email story ideas to [email protected].

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Presenting and Evaluating Qualitative Research

The purpose of this paper is to help authors to think about ways to present qualitative research papers in the American Journal of Pharmaceutical Education . It also discusses methods for reviewers to assess the rigour, quality, and usefulness of qualitative research. Examples of different ways to present data from interviews, observations, and focus groups are included. The paper concludes with guidance for publishing qualitative research and a checklist for authors and reviewers.

INTRODUCTION

Policy and practice decisions, including those in education, increasingly are informed by findings from qualitative as well as quantitative research. Qualitative research is useful to policymakers because it often describes the settings in which policies will be implemented. Qualitative research is also useful to both pharmacy practitioners and pharmacy academics who are involved in researching educational issues in both universities and practice and in developing teaching and learning.

Qualitative research involves the collection, analysis, and interpretation of data that are not easily reduced to numbers. These data relate to the social world and the concepts and behaviors of people within it. Qualitative research can be found in all social sciences and in the applied fields that derive from them, for example, research in health services, nursing, and pharmacy. 1 It looks at X in terms of how X varies in different circumstances rather than how big is X or how many Xs are there? 2 Textbooks often subdivide research into qualitative and quantitative approaches, furthering the common assumption that there are fundamental differences between the 2 approaches. With pharmacy educators who have been trained in the natural and clinical sciences, there is often a tendency to embrace quantitative research, perhaps due to familiarity. A growing consensus is emerging that sees both qualitative and quantitative approaches as useful to answering research questions and understanding the world. Increasingly mixed methods research is being carried out where the researcher explicitly combines the quantitative and qualitative aspects of the study. 3 , 4

Like healthcare, education involves complex human interactions that can rarely be studied or explained in simple terms. Complex educational situations demand complex understanding; thus, the scope of educational research can be extended by the use of qualitative methods. Qualitative research can sometimes provide a better understanding of the nature of educational problems and thus add to insights into teaching and learning in a number of contexts. For example, at the University of Nottingham, we conducted in-depth interviews with pharmacists to determine their perceptions of continuing professional development and who had influenced their learning. We also have used a case study approach using observation of practice and in-depth interviews to explore physiotherapists' views of influences on their leaning in practice. We have conducted in-depth interviews with a variety of stakeholders in Malawi, Africa, to explore the issues surrounding pharmacy academic capacity building. A colleague has interviewed and conducted focus groups with students to explore cultural issues as part of a joint Nottingham-Malaysia pharmacy degree program. Another colleague has interviewed pharmacists and patients regarding their expectations before and after clinic appointments and then observed pharmacist-patient communication in clinics and assessed it using the Calgary Cambridge model in order to develop recommendations for communication skills training. 5 We have also performed documentary analysis on curriculum data to compare pharmacist and nurse supplementary prescribing courses in the United Kingdom.

It is important to choose the most appropriate methods for what is being investigated. Qualitative research is not appropriate to answer every research question and researchers need to think carefully about their objectives. Do they wish to study a particular phenomenon in depth (eg, students' perceptions of studying in a different culture)? Or are they more interested in making standardized comparisons and accounting for variance (eg, examining differences in examination grades after changing the way the content of a module is taught). Clearly a quantitative approach would be more appropriate in the last example. As with any research project, a clear research objective has to be identified to know which methods should be applied.

Types of qualitative data include:

• Audio recordings and transcripts from in-depth or semi-structured interviews
• Structured interview questionnaires containing substantial open comments including a substantial number of responses to open comment items.
• Audio recordings and transcripts from focus group sessions.
• Field notes (notes taken by the researcher while in the field [setting] being studied)
• Video recordings (eg, lecture delivery, class assignments, laboratory performance)
• Case study notes
• Documents (reports, meeting minutes, e-mails)
• Diaries, video diaries
• Observation notes
• Press clippings
• Photographs

RIGOUR IN QUALITATIVE RESEARCH

Qualitative research is often criticized as biased, small scale, anecdotal, and/or lacking rigor; however, when it is carried out properly it is unbiased, in depth, valid, reliable, credible and rigorous. In qualitative research, there needs to be a way of assessing the “extent to which claims are supported by convincing evidence.” 1 Although the terms reliability and validity traditionally have been associated with quantitative research, increasingly they are being seen as important concepts in qualitative research as well. Examining the data for reliability and validity assesses both the objectivity and credibility of the research. Validity relates to the honesty and genuineness of the research data, while reliability relates to the reproducibility and stability of the data.

The validity of research findings refers to the extent to which the findings are an accurate representation of the phenomena they are intended to represent. The reliability of a study refers to the reproducibility of the findings. Validity can be substantiated by a number of techniques including triangulation use of contradictory evidence, respondent validation, and constant comparison. Triangulation is using 2 or more methods to study the same phenomenon. Contradictory evidence, often known as deviant cases, must be sought out, examined, and accounted for in the analysis to ensure that researcher bias does not interfere with or alter their perception of the data and any insights offered. Respondent validation, which is allowing participants to read through the data and analyses and provide feedback on the researchers' interpretations of their responses, provides researchers with a method of checking for inconsistencies, challenges the researchers' assumptions, and provides them with an opportunity to re-analyze their data. The use of constant comparison means that one piece of data (for example, an interview) is compared with previous data and not considered on its own, enabling researchers to treat the data as a whole rather than fragmenting it. Constant comparison also enables the researcher to identify emerging/unanticipated themes within the research project.

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

Qualitative researchers have been criticized for overusing interviews and focus groups at the expense of other methods such as ethnography, observation, documentary analysis, case studies, and conversational analysis. Qualitative research has numerous strengths when properly conducted.

Strengths of Qualitative Research

• Issues can be examined in detail and in depth.
• Interviews are not restricted to specific questions and can be guided/redirected by the researcher in real time.
• The research framework and direction can be quickly revised as new information emerges.
• The data based on human experience that is obtained is powerful and sometimes more compelling than quantitative data.
• Subtleties and complexities about the research subjects and/or topic are discovered that are often missed by more positivistic enquiries.
• Data usually are collected from a few cases or individuals so findings cannot be generalized to a larger population. Findings can however be transferable to another setting.

Limitations of Qualitative Research

• Research quality is heavily dependent on the individual skills of the researcher and more easily influenced by the researcher's personal biases and idiosyncrasies.
• Rigor is more difficult to maintain, assess, and demonstrate.
• The volume of data makes analysis and interpretation time consuming.
• It is sometimes not as well understood and accepted as quantitative research within the scientific community
• The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.
• Issues of anonymity and confidentiality can present problems when presenting findings
• Findings can be more difficult and time consuming to characterize in a visual way.

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

The following extracts are examples of how qualitative data might be presented:

Data From an Interview.

The following is an example of how to present and discuss a quote from an interview.

The researcher should select quotes that are poignant and/or most representative of the research findings. Including large portions of an interview in a research paper is not necessary and often tedious for the reader. The setting and speakers should be established in the text at the end of the quote.

The student describes how he had used deep learning in a dispensing module. He was able to draw on learning from a previous module, “I found that while using the e learning programme I was able to apply the knowledge and skills that I had gained in last year's diseases and goals of treatment module.” (interviewee 22, male)

This is an excerpt from an article on curriculum reform that used interviews 5 :

The first question was, “Without the accreditation mandate, how much of this curriculum reform would have been attempted?” According to respondents, accreditation played a significant role in prompting the broad-based curricular change, and their comments revealed a nuanced view. Most indicated that the change would likely have occurred even without the mandate from the accreditation process: “It reflects where the profession wants to be … training a professional who wants to take on more responsibility.” However, they also commented that “if it were not mandated, it could have been a very difficult road.” Or it “would have happened, but much later.” The change would more likely have been incremental, “evolutionary,” or far more limited in its scope. “Accreditation tipped the balance” was the way one person phrased it. “Nobody got serious until the accrediting body said it would no longer accredit programs that did not change.”

Data From Observations

The following example is some data taken from observation of pharmacist patient consultations using the Calgary Cambridge guide. 6 , 7 The data are first presented and a discussion follows:

Pharmacist: We will soon be starting a stop smoking clinic. Patient: Is the interview over now? Pharmacist: No this is part of it. (Laughs) You can't tell me to bog off (sic) yet. (pause) We will be starting a stop smoking service here, Patient: Yes. Pharmacist: with one-to-one and we will be able to help you or try to help you. If you want it. In this example, the pharmacist has picked up from the patient's reaction to the stop smoking clinic that she is not receptive to advice about giving up smoking at this time; in fact she would rather end the consultation. The pharmacist draws on his prior relationship with the patient and makes use of a joke to lighten the tone. He feels his message is important enough to persevere but he presents the information in a succinct and non-pressurised way. His final comment of “If you want it” is important as this makes it clear that he is not putting any pressure on the patient to take up this offer. This extract shows that some patient cues were picked up, and appropriately dealt with, but this was not the case in all examples.

Data From Focus Groups

This excerpt from a study involving 11 focus groups illustrates how findings are presented using representative quotes from focus group participants. 8

Those pharmacists who were initially familiar with CPD endorsed the model for their peers, and suggested it had made a meaningful difference in the way they viewed their own practice. In virtually all focus groups sessions, pharmacists familiar with and supportive of the CPD paradigm had worked in collaborative practice environments such as hospital pharmacy practice. For these pharmacists, the major advantage of CPD was the linking of workplace learning with continuous education. One pharmacist stated, “It's amazing how much I have to learn every day, when I work as a pharmacist. With [the learning portfolio] it helps to show how much learning we all do, every day. It's kind of satisfying to look it over and see how much you accomplish.” Within many of the learning portfolio-sharing sessions, debates emerged regarding the true value of traditional continuing education and its outcome in changing an individual's practice. While participants appreciated the opportunity for social and professional networking inherent in some forms of traditional CE, most eventually conceded that the academic value of most CE programming was limited by the lack of a systematic process for following-up and implementing new learning in the workplace. “Well it's nice to go to these [continuing education] events, but really, I don't know how useful they are. You go, you sit, you listen, but then, well I at least forget.”

The following is an extract from a focus group (conducted by the author) with first-year pharmacy students about community placements. It illustrates how focus groups provide a chance for participants to discuss issues on which they might disagree.

Interviewer: So you are saying that you would prefer health related placements? Student 1: Not exactly so long as I could be developing my communication skill. Student 2: Yes but I still think the more health related the placement is the more I'll gain from it. Student 3: I disagree because other people related skills are useful and you may learn those from taking part in a community project like building a garden. Interviewer: So would you prefer a mixture of health and non health related community placements?

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Qualitative research is becoming increasingly accepted and published in pharmacy and medical journals. Some journals and publishers have guidelines for presenting qualitative research, for example, the British Medical Journal 9 and Biomedcentral . 10 Medical Education published a useful series of articles on qualitative research. 11 Some of the important issues that should be considered by authors, reviewers and editors when publishing qualitative research are discussed below.

Introduction.

A good introduction provides a brief overview of the manuscript, including the research question and a statement justifying the research question and the reasons for using qualitative research methods. This section also should provide background information, including relevant literature from pharmacy, medicine, and other health professions, as well as literature from the field of education that addresses similar issues. Any specific educational or research terminology used in the manuscript should be defined in the introduction.

The methods section should clearly state and justify why the particular method, for example, face to face semistructured interviews, was chosen. The method should be outlined and illustrated with examples such as the interview questions, focusing exercises, observation criteria, etc. The criteria for selecting the study participants should then be explained and justified. The way in which the participants were recruited and by whom also must be stated. A brief explanation/description should be included of those who were invited to participate but chose not to. It is important to consider “fair dealing,” ie, whether the research design explicitly incorporates a wide range of different perspectives so that the viewpoint of 1 group is never presented as if it represents the sole truth about any situation. The process by which ethical and or research/institutional governance approval was obtained should be described and cited.

The study sample and the research setting should be described. Sampling differs between qualitative and quantitative studies. In quantitative survey studies, it is important to select probability samples so that statistics can be used to provide generalizations to the population from which the sample was drawn. Qualitative research necessitates having a small sample because of the detailed and intensive work required for the study. So sample sizes are not calculated using mathematical rules and probability statistics are not applied. Instead qualitative researchers should describe their sample in terms of characteristics and relevance to the wider population. Purposive sampling is common in qualitative research. Particular individuals are chosen with characteristics relevant to the study who are thought will be most informative. Purposive sampling also may be used to produce maximum variation within a sample. Participants being chosen based for example, on year of study, gender, place of work, etc. Representative samples also may be used, for example, 20 students from each of 6 schools of pharmacy. Convenience samples involve the researcher choosing those who are either most accessible or most willing to take part. This may be fine for exploratory studies; however, this form of sampling may be biased and unrepresentative of the population in question. Theoretical sampling uses insights gained from previous research to inform sample selection for a new study. The method for gaining informed consent from the participants should be described, as well as how anonymity and confidentiality of subjects were guaranteed. The method of recording, eg, audio or video recording, should be noted, along with procedures used for transcribing the data.

Data Analysis.

A description of how the data were analyzed also should be included. Was computer-aided qualitative data analysis software such as NVivo (QSR International, Cambridge, MA) used? Arrival at “data saturation” or the end of data collection should then be described and justified. A good rule when considering how much information to include is that readers should have been given enough information to be able to carry out similar research themselves.

One of the strengths of qualitative research is the recognition that data must always be understood in relation to the context of their production. 1 The analytical approach taken should be described in detail and theoretically justified in light of the research question. If the analysis was repeated by more than 1 researcher to ensure reliability or trustworthiness, this should be stated and methods of resolving any disagreements clearly described. Some researchers ask participants to check the data. If this was done, it should be fully discussed in the paper.

An adequate account of how the findings were produced should be included A description of how the themes and concepts were derived from the data also should be included. Was an inductive or deductive process used? The analysis should not be limited to just those issues that the researcher thinks are important, anticipated themes, but also consider issues that participants raised, ie, emergent themes. Qualitative researchers must be open regarding the data analysis and provide evidence of their thinking, for example, were alternative explanations for the data considered and dismissed, and if so, why were they dismissed? It also is important to present outlying or negative/deviant cases that did not fit with the central interpretation.

The interpretation should usually be grounded in interviewees or respondents' contributions and may be semi-quantified, if this is possible or appropriate, for example, “Half of the respondents said …” “The majority said …” “Three said…” Readers should be presented with data that enable them to “see what the researcher is talking about.” 1 Sufficient data should be presented to allow the reader to clearly see the relationship between the data and the interpretation of the data. Qualitative data conventionally are presented by using illustrative quotes. Quotes are “raw data” and should be compiled and analyzed, not just listed. There should be an explanation of how the quotes were chosen and how they are labeled. For example, have pseudonyms been given to each respondent or are the respondents identified using codes, and if so, how? It is important for the reader to be able to see that a range of participants have contributed to the data and that not all the quotes are drawn from 1 or 2 individuals. There is a tendency for authors to overuse quotes and for papers to be dominated by a series of long quotes with little analysis or discussion. This should be avoided.

Participants do not always state the truth and may say what they think the interviewer wishes to hear. A good qualitative researcher should not only examine what people say but also consider how they structured their responses and how they talked about the subject being discussed, for example, the person's emotions, tone, nonverbal communication, etc. If the research was triangulated with other qualitative or quantitative data, this should be discussed.

Discussion.

The findings should be presented in the context of any similar previous research and or theories. A discussion of the existing literature and how this present research contributes to the area should be included. A consideration must also be made about how transferrable the research would be to other settings. Any particular strengths and limitations of the research also should be discussed. It is common practice to include some discussion within the results section of qualitative research and follow with a concluding discussion.

The author also should reflect on their own influence on the data, including a consideration of how the researcher(s) may have introduced bias to the results. The researcher should critically examine their own influence on the design and development of the research, as well as on data collection and interpretation of the data, eg, were they an experienced teacher who researched teaching methods? If so, they should discuss how this might have influenced their interpretation of the results.

Conclusion.

The conclusion should summarize the main findings from the study and emphasize what the study adds to knowledge in the area being studied. Mays and Pope suggest the researcher ask the following 3 questions to determine whether the conclusions of a qualitative study are valid 12 : How well does this analysis explain why people behave in the way they do? How comprehensible would this explanation be to a thoughtful participant in the setting? How well does the explanation cohere with what we already know?

CHECKLIST FOR QUALITATIVE PAPERS

This paper establishes criteria for judging the quality of qualitative research. It provides guidance for authors and reviewers to prepare and review qualitative research papers for the American Journal of Pharmaceutical Education . A checklist is provided in Appendix 1 to assist both authors and reviewers of qualitative data.

ACKNOWLEDGEMENTS

Thank you to the 3 reviewers whose ideas helped me to shape this paper.

Appendix 1. Checklist for authors and reviewers of qualitative research.

Introduction

• □ Research question is clearly stated.
• □ Research question is justified and related to the existing knowledge base (empirical research, theory, policy).
• □ Any specific research or educational terminology used later in manuscript is defined.
• □ The process by which ethical and or research/institutional governance approval was obtained is described and cited.
• □ Reason for choosing particular research method is stated.
• □ Criteria for selecting study participants are explained and justified.
• □ Recruitment methods are explicitly stated.
• □ Details of who chose not to participate and why are given.
• □ Study sample and research setting used are described.
• □ Method for gaining informed consent from the participants is described.
• □ Maintenance/Preservation of subject anonymity and confidentiality is described.
• □ Method of recording data (eg, audio or video recording) and procedures for transcribing data are described.
• □ Methods are outlined and examples given (eg, interview guide).
• □ Decision to stop data collection is described and justified.
• □ Data analysis and verification are described, including by whom they were performed.
• □ Methods for identifying/extrapolating themes and concepts from the data are discussed.
• □ Sufficient data are presented to allow a reader to assess whether or not the interpretation is supported by the data.
• □ Outlying or negative/deviant cases that do not fit with the central interpretation are presented.
• □ Transferability of research findings to other settings is discussed.
• □ Findings are presented in the context of any similar previous research and social theories.
• □ Discussion often is incorporated into the results in qualitative papers.
• □ A discussion of the existing literature and how this present research contributes to the area is included.
• □ Any particular strengths and limitations of the research are discussed.
• □ Reflection of the influence of the researcher(s) on the data, including a consideration of how the researcher(s) may have introduced bias to the results is included.

Conclusions

• □ The conclusion states the main finings of the study and emphasizes what the study adds to knowledge in the subject area.

• Open access
• Published: 05 September 2024

Exploring transitions in care among patients with head and neck CANCER: a multimethod study

• Jaling Kersen 1 ,
• Pamela Roach 1 , 4 , 5 ,
• Shamir Chandarana 2 , 3 ,
• Paul Ronksley 1 , 4 &
• Khara Sauro 1 , 2 , 3 , 4  

BMC Cancer volume  24 , Article number:  1108 ( 2024 ) Cite this article

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Patients with head and neck cancers (HNC) experience many transitions in care (TiC), occurring when patients are transferred between healthcare providers and/or settings. TiC can compromise patient safety, decrease patient satisfaction, and increase healthcare costs. The evidence around TiC among patients with HNC is sparse. The objective of this study was to improve our understanding of TiC among patients with HNC to identify ways to improve care.

This multimethod study consisted of two phases: Phase I (retrospective population-based cohort study) characterized the number and type of TiC that patients with HNC experienced using deterministically linked, population-based administrative health data in Alberta, Canada (January 1, 2012, to September 1, 2020), and Phase II (qualitative descriptive study) used semi-structured interviews to explore the lived experiences of patients with HNC and their healthcare providers during TiC.

There were 3,752 patients with HNC; most were male (70.8%) with a mean age at diagnosis of 63.3 years (SD 13.1). Patients underwent an average of 1.6 (SD 0.7) treatments, commonly transitioning from surgery to radiotherapy (21.2%). Many patients with HNC were admitted to the hospital during the study period, averaging 3.3 (SD 3.0) hospital admissions and 7.8 (SD 12.6) emergency department visits per patient over the study period. Visits to healthcare providers were also frequent, with the highest number of physician visits being to general practitioners (average = 70.51 per patient). Analysis of sixteen semi-structured interviews (ten patients with HNC and six healthcare providers) revealed three themes: (1) Navigating the healthcare system including challenges with the complexity of HNC care amongst healthcare system pressures, (2) Relational head and neck cancer care which encompasses patient expectations and relationships, and (3) System and individual impact of transitions in care.

Conclusions

This study identified challenges faced by both patients with HNC and their healthcare providers amidst the frequent TiC within cancer care, which was perceived to have an impact on quality of care. These findings provide crucial insights that can inform and guide future research or the development of health interventions aiming to improve the quality of TiC within this patient population.

Peer Review reports

Head and Neck Cancers (HNC) are a group of cancers that affect diverse anatomical structures including the pharynx, larynx, naso-, oro-, hypopharynx, nasal cavity, oral cavity, middle ear, and salivary glands [ 1 ]. HNC are the sixth most common cancer in the world [ 2 ] accounting for approximately 931,931 new diagnoses worldwide each year, with a projected 30% annual increase by the year 2030 [ 1 , 3 ]. There are several risk factors for HNC which include alcohol and tobacco use, malnutrition, lower socioeconomic status, age, sex, exposure to carcinogens and contracting the Human Papilloma Virus (HPV) [ 4 , 5 ]. The presence of these risk factors results in differences in disease presentation, progression, and patient outcomes [ 6 , 7 ]. Although the 5-year age-standardized survival rates for HNC vary between countries and the site of the HNC, they remain relatively low, with age standardized estimates ranging from 2.5 to 8.3 per 100,000 [ 8 , 9 , 10 , 11 ].

Patients with HNC are cared for by multidisciplinary healthcare teams which collaboratively develop treatment plans, manage treatment sequelae, and provide comprehensive supportive care and rehabilitation [ 12 , 13 ]. These treatment plans often include a combination of surgery, radiation, chemotherapy, and immunotherapy [ 12 , 14 ]. As a result of their complex treatment plans, and vulnerability to physical and psychological effects from HNC and its associated treatments, patients with HNC are some of the highest users of healthcare resources [ 15 , 16 , 17 ]. As this patient population requires care from many healthcare providers across different healthcare settings, they consequently experience many transitions in care (TiC) [ 12 , 18 , 19 ]. TiC occur when the responsibility for a patient’s care is transferred between healthcare providers, institutions, or settings [ 20 ]. TiC can also occur when patients move from one level of care to another (e.g., from the intensive care unit to the hospital ward) [ 20 ]. TiC represent a challenging period in the delivery of care as they interrupt continuity of care, opening opportunities for inadequate transfer of information and potential breakdown in communication [ 21 ]. In other patient populations, poorly executed TiC have been associated with compromised patient safety, increased medical errors, high distress levels in patients and their families, excessive healthcare cost and resource use [ 22 , 23 , 24 , 25 , 26 , 27 ]. As such, organizations such as the Joint Commission and the National Academy of Medicine have identified a critical need to effectively bridge the TiC that patients experience to help mitigate adverse effects on patient health outcomes [ 28 , 29 ]. Despite the complex multidisciplinary care of patients with HNC and the established risks of poor care during TiC, there is a gap in our understanding of TiC for patients with HNC.

The objectives of this study are to (1) estimate the number and type of TiC patients with HNC experience, (2) understand TiC from the perspective of patients with HNC and healthcare providers, (3) explore the quality of care during TiC, from the perspective of patients with HNC and healthcare providers.

This multimethod study was approved by the University of Calgary Health Research Ethics Board of Alberta (HREABA.CC-20-0474) and consisted of two distinct phases: a retrospective population-based cohort study and a qualitative descriptive study.

Phase 1: retrospective cohort study

This study was conducted in Alberta, Canada where healthcare services are provided by a provincially integrated single-payer healthcare system (Alberta Health Services (AHS)) [ 30 , 31 ]. AHS is the largest integrated provincial healthcare system in Canada [ 31 ] composed of 106 acute care hospitals, five psychiatric facilities, and partners with 40 primary care networks [ 30 ]. Cancer care for patients with HNC is delivered by AHS in two main cancer care centres in Alberta: Tom Baker Cancer Centre in Calgary and the Holy Cross Cancer Centre in Edmonton [ 30 , 31 ] .

Population and data sources

This retrospective population-based cohort study quantitatively characterized the number and type of TiC that patients with HNC experience throughout their cancer journey, using routinely collected, population-based administrative health data. The cohort included adult patients ( \(\:\ge\:\:\) 18 years old) diagnosed with HNC in Alberta between January 1, 2012, to September 1, 2020, as indicated by a record in the population-based Alberta Cancer Registry (ACR).

Data from four administrative health data sources were deterministically linked using a unique personal healthcare number that is assigned to each person in the province at birth or immigration to the province and follows them throughout their life. The ACR, a population-based registry, records patient demographic information (name, date of birth, sex, postal code) and cancer-specific variables (diagnosis with dates, pathology, treatments with dates, and staging) [ 32 ]. The Discharge Abstract Database (DAD) includes information on acute care hospital admissions including demographics, diagnoses (using the International Classification of Disease version 10 (ICD-10) codes), procedures, and admission and discharge information [ 33 ]. Physician billing claims include diagnostic codes (ICD-9) assigned by physicians used to bill the Government of Alberta for services provided to patients. The National Ambulatory Care Reporting System (NACRS) collects demographic, administrative, clinical, and service-specific data from both hospital-based and community-based ambulatory care visits [ 34 , 35 ].

Patient demographic variables (age, sex, and socioeconomic status), cancer-related variables (site, stage, and presence of multiple tumours) and treatment-related variables (treatment modalities) were extracted from ACR. The Charlson Comorbidity Index (categorized as 0,1,2+) was calculated using established coding algorithms [ 36 ].

The primary outcome variables were the number and type of TiC. The TiC examined included the transitions between treatments, healthcare institutions (hospital visits and associated discharges, emergency department visits), and different healthcare providers. The type of TiC variables were dichotomously coded, with a 0 indicating that a patient did not experience a TiC and a 1 that a patient experienced a TiC (Supplementary Table 1 ). TiC rates were computed individually for each patient across four distinct periods: six months before diagnosis, from diagnosis to initial treatment, one-year post-first treatment, and three years post-first treatment.

The cohort characteristics were described using descriptive statistics; means with standard deviations (SD) or medians and interquartile ranges (IQR) where appropriate, and frequencies (proportions). The TiC rates were calculated as number per month across the 4 periods described above. All analyses were conducted using STATA 16 SE [ 37 ]. This phase is reported according to the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) and the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) (Appendix 1 ) [ 38 , 39 ].

Phase 2: qualitative description

The qualitative descriptive study followed the general tenets of naturalistic inquiry to provide a richer understanding of TiC and care delivery among patients with HNC and their healthcare providers [ 40 , 41 ]. In-depth, semi-structured interviews were conducted with two participant groups: (1) adult patients with HNC, who received care in Alberta, at any stage of their cancer journey and (2) multi-professional healthcare providers who care for patients with HNC in Alberta. This phase was reported in line with the Consolidated Criteria for Reporting Qualitative Research (COREQ) (Appendix 2 ) [ 42 ].

Participants and recruitment

Recruitment occurred between September 1, 2022, to July 15th, 2023. Different sampling strategies were employed for the two participant groups. Patients with HNC were recruited through purposive sampling and employed media-based approaches to ensure maximum variation in patient characteristics [ 43 ]. Healthcare providers were also recruited through purposive sampling, using the researchers’ professional networks. All potential participants were provided with the contact information for the principal investigator.

Data collection

Interviews were completed using semi-structured interview guides uniquely developed for each participant group, informed by our methodological framework. These guides included open-ended questions relevant to the objectives of the study and probing questions to elicit data [ 44 ]. The interview guides were pilot-tested within the research team and iteratively refined by the authors (J.K and K.M.S).

Semi-structured interviews were conducted via telephone ( n  = 2) or secure video conferencing platform (Zoom) ( n  = 14) [ 45 ] with no other participants present. The interviews were conducted by the first author (J.K) who has formal graduate training and practical experience in qualitative methods and interview facilitation. The interviewer did not have any previous relationships with patients with HNC, however, due to the sampling method for healthcare professionals, the interviewer had a professional relationship with one of the included healthcare providers. The interviews were audio recorded and transcribed verbatim using transcription services (rev.com), with a unique study identifier replacing the participant’s name. Participants were recruited and data was collected until saturation was reached. Saturation was achieved when no novel themes were generated from the data [ 46 ].

Written, informed consent was obtained from all participants before participating in the semi-structured interviews. Additional consent was received from all participants to audio record the interviews and to use anonymized quotations in research publications and dissemination.

Data analysis

The data from the semi-structured interviews was analyzed using an inductive approach, whereby two independent reviewers (J.K and K.M.S) followed Braun and Clarke’s approach to thematic analysis [ 46 ]. Thematic analysis was facilitated by the qualitative software Nvivo [ 47 ]. The themes from the patients with HNC and the healthcare providers were also compared and contrasted to ensure alignment to an overarching central concept [ 48 ]. Qualitative analysis and generated themes were discussed with the study team to facilitate peer debriefing [ 41 ] .

Reflexivity

The interview facilitator and first analyst (J.K) was a graduate student (MSc), familiar with evidence suggesting that TiC are vulnerable periods for patients. The second analyst (K.M.S) was an Assistant Professor whose broad research area encompassed TiC among patients with HNC. Due to their previous experiences and knowledge, both researchers acknowledged that their perception of TiC may be inherently negative and this was frequently debriefed with the team in order to consciously reduce any impact on their findings. Throughout the research process, the reviewers also critically examined their assumptions and challenged them to mitigate any potential bias.

Retrospective cohort study

The cohort included 3,752 patients with HNC. Demographic characteristics of the cohort are presented in Table  1 . Briefly, most patients were male (70.8%) and had a mean age at diagnosis of 63.3 years (SD = 13.1).

The overall, all-cause mortality of patients was 44.86% ( n  = 1,683) within the study period. The mean number of TiC per patient was 210.3 (SD = 164.6). The mean TiC rate per patient was 7.7 (SD = 10.2) during the six months preceding diagnosis. Following diagnosis and before the first treatment, the mean TiC rate per patient increased to 23.1 (SD = 34.9) per patient. Subsequently, the mean TiC rate per patient declined to 4.2 (SD = 5.3) one year post-first treatment with a further decrease to 2.0 (SD = 2.2) per patient three years post-first treatment. Patients with HNC had frequent transitions between different treatments. A total of 47.9% of patients underwent two or more treatments during the study period, with an average of 1.6 (SD = 0.7) treatments per patient. The most common treatment was radiotherapy, followed closely by surgery; the most common treatment transition was the transition from surgery to radiotherapy (21.2%) (Table  2 ).

Many patients with HNC were admitted to the hospital during the study period (Table  3 ), with an average of 3.3 (SD = 3.0) hospital admissions per patient. When patients were admitted to hospital, frequently they were admitted from home (82.6%) and discharged to home with no support (as indicated in their discharge report; 82.8%) (Table  3 ). Visits to an emergency department were common ( n  = 3,475 patients) with an average of 7.8 (SD = 12.6) visits per patient during the study period. The number of emergency department visits increased after diagnosis and again after the first treatment (Table  4 ). The highest number of physician visits were to general practitioners (family medicine) (average = 70.6 per patient) followed by other specialists (average = 65.2 per patient; Table  5 ). The number of visits to most healthcare providers increased after diagnosis (Table  5 ).

Qualitative description

Sixteen interviews (ten patients and six healthcare providers) were conducted between July 17 th, 2022, to June 7 th, 2023. The interviews ranged between 30 and 90 min (median = 46 min). The mean age of patients with HNC at the time of the interview was 66 years old (range = 47–77 years), most were female ( n  = 7, 70%) and experienced many TiC. Healthcare providers included surgeons ( n  = 3), a medical oncologist ( n  = 1), a radiation oncologist ( n  = 1), and a licensed practical nurse ( n  = 1). The healthcare providers were mostly male ( n  = 4), with the average years of practice being 21 years (range = 7.5–31 years).

The qualitative analysis generated three interconnected themes: (1) Navigating the Healthcare System (subthemes: head and neck cancer care complexities, disrupted continuity of head and neck cancer care, and healthcare system pressures), (2) Relational Head and Neck Cancer Care (subthemes: patient expectations during Transitions in Care, feeling valued as a Head and Neck Cancer patient and healthcare provider roles and responsibilities) and (3) System and Individual Impact of Transitions in Care (subthemes: impact of resource-intensive nature of TiC and the Impact of Transitions in Care on Quality of Care). Additional exemplar quotations for each theme are presented in Table  6 .

Navigating the healthcare system

Despite the healthcare system’s overarching goal of providing high-quality care, participants expressed struggles with navigating complex healthcare systems, leading to poor quality of care.

Head and neck cancer care complexities

While both patients with HNC and healthcare providers reported that navigating the complexities of HNC care is challenging, healthcare providers noted the necessity for multidisciplinary care, while patients described confusion by the care pathways used during their treatment. Patients perceived their care to be overly complex, involving many healthcare disciplines and many of the processes were unfamiliar to them. Although healthcare providers recognized the need for care pathways, guidelines, and protocols to ensure standardized care, they also recognized that patients did not intuitively know how to navigate these complex pathways and the health system.

Disrupted continuity of head and neck cancer care

Patients and healthcare providers described a siloed healthcare system which affected all aspects of patient care, hindering communication, resulting in prolonged waits, and disrupting the continuity of care. There were many instances where healthcare silos were identified as the cause of communication breakdowns among patients with HNC and their healthcare providers, with patients struggling to contact the appropriate healthcare providers and the communication between the multidisciplinary healthcare teams becoming strained. However, only patients with HNC associated the siloed healthcare system structure with prolonged waits and fragmented care, reporting wait times of five to six weeks between different healthcare departments (surgery, dermatology, and psychiatry) and lapses in continuous care. Healthcare silos were physical and geographical, requiring patients to travel to different healthcare institutions for their care.

Patients with HNC and healthcare providers proposed potential solutions which they felt could address these issues, including consolidating healthcare teams and departments into a centralized facility and the direct communication via telephone between patients, oncologists, and other healthcare providers.

Healthcare system pressures

Patients with HNC and healthcare providers recognized that a prominent constraint facing the healthcare system is the shortage of trained healthcare professionals. Patients with HNC described inadequate access to healthcare providers, specifically primary care providers and psychologists who they felt were critical to their care. Healthcare providers commonly noted that constrained human resources necessitated taking on additional responsibilities beyond their designated roles, often without appropriate support or adjustment to their workload. Healthcare providers, most notably specialists, were sometimes placed into uncomfortable situations where patients expected them to manage their daily care which is beyond their scope of practice.

Relational head and neck cancer care

Patients with HNC and healthcare providers identified interconnected factors including patients’ expectations of their care, their perception of being valued within the healthcare system and their understanding of healthcare provider roles and responsibilities that influenced how patients experienced their healthcare journey and TiC.

Patient expectations during transitions in care

Patient expectations of the healthcare system and their care were pivotal in shaping their experiences with cancer care. Some patients faced difficulties aligning what they anticipated their care to look like with the actual care they received. Patients struggled to establish expectations for their TiC that were aligned with their actual care due to their unfamiliarity with the complex healthcare system and the complexity of HNC care. These divergent expectations were especially evident during the transition from active treatment to survivorship when a patient’s interactions with the healthcare team dramatically decreased. Expectations of care not being met also led to heightened frustration and stress among patients with HNC. However, patients hesitated to voice these feelings with their healthcare providers for fear of being labelled as “high maintenance” when advocating for their needs.

Feeling valued as a head and neck cancer patient

Emotional support during the cancer continuum was perceived to be crucial by patients with HNC and healthcare providers. The healthcare providers noted that professional psychological care, although in short supply, is a key source of support. However, patients perceived the existing patient-provider relationship as an equally crucial source of support. Strong patient-provider relationships were rooted in mutual knowledge, respect, and trust and thrived when healthcare providers exhibited compassion and empathy. Patients valued long-lasting patient-provider relationships, which extended beyond a specific episode of care, creating an enduring continuum of support. While an abundance of patients experienced strong patient-provider relationships, some patients had weak patient-provider relationships, where the relationship lacked trust, communication and collaboration leaving patients feeling unsupported and abandoned. These weak patient-provider relationships triggered patients to transition to other healthcare providers more frequently. Patients with HNC proposed that further involvement in the decision-making process would help make them feel valued. They expressed a desire to have their opinions heard, particularly when it came to decisions that governed their care during TiC.

Healthcare provider roles and responsibilities

Patients with HNC and healthcare providers acknowledged that there is a lack of clarity about the specific roles and responsibilities of each healthcare provider caring for patients with HNC. This lack of clarity was especially endorsed by patients. Patients found understanding who was responsible for specific aspects of their cancer care (usually by oncologists) and non-cancer related care (usually by general practitioners) confusing which led to challenges in deciding who to consult about their concerns, with the general practitioners and oncologists often redirecting the patient to each other. To add to this confusion, the addition of medical residents and fellows to the patients with HNC’s care team was described as confusing and disruptive.

System and individual impact of transitions in care

Patients and providers experienced TiC differently during the cancer continuum. Healthcare providers perceived TiC as contributing to increased workloads and emotional distress, while patients with HNC associated TiC with decreased quality of care due to ineffective care and lack of patient-centeredness.

Impact of resource-intensive nature of transitions in care

Healthcare providers perceived the volume of tasks associated with TiC contributed to the burden on healthcare providers and patients with HNC. Many healthcare providers noted that high-quality TiC demanded significant time and effort to do well (transfer information between providers). Additional challenges related to ensuring a high-quality TiC included, adapting to evolving electronic health record systems and collaborating with patients and colleagues. The extensive documentation required during TiC also created time constraints for healthcare providers, preventing them from spending adequate time with each patient. The introduction of a new electronic medical records system in Alberta further compounded this issue, with surgeons and oncologists describing difficulties in understanding and utilizing the system when transferring a patient’s care, potentially resulting in insufficient information for the healthcare provider the patient is transitioning to. Additionally, healthcare providers noted that the additional responsibilities associated with TiC led to heightened stress levels and emotional repercussions due to witnessing their patients deteriorate after experiencing poor TiC. Although the resource-intensive nature of TiC was commonly discussed by healthcare providers, patients with HNC also described instances where they had to dedicate significant time and effort to organize their care, facilitate communication between healthcare providers and access information during TiC. A widely endorsed solution by both patients with HNC and their healthcare providers to improve TiC was the introduction of a care coordinator or patient navigator envisioning it as a strategy to improve TiC.

Impact of transitions in care on quality of care

The opinions of patients with HNC and their healthcare providers diverged when discussing the factors that influenced the quality of care throughout the cancer continuum. Patients highlighted areas that needed improvement such as effectiveness and patient-centeredness. Ineffective care occurred when healthcare providers (especially primary care providers and dentists) failed to provide the appropriate care or identify symptoms as potential cancer resulting in prolonged diagnosis. A lack of patient-centeredness was noted by patients when healthcare providers did not take the time to understand them holistically, resulting in healthcare that was not customized around a patient’s needs, characteristics and preferences. In contrast, healthcare providers focussed on the broader healthcare system barriers including budgetary constraints and a lack of awareness about TiC. Healthcare providers believed that the allocated operating budgets were constrained, which prevented the optimization of HNC care within the healthcare system. Additionally, healthcare providers emphasized the lack of awareness about TiC and their consequences for patient outcomes and healthcare expenditure.

This multimethod study quantified the large number and variety of types of TiC patients with HNC encounter during their care; patients with HNC had an especially high number of emergency department visits, hospital admissions and visits to general practitioners. The high number of TiC was described as a source of distress by patients and providers.

The findings of this study are consistent with evidence showing that patients with cancer use a high amount of healthcare resources. Studies have found that patients with cancer account for 10.5% of hospital admissions and patients with lung and colorectal cancer have, on average, 3.3 hospital admissions (Sauro K: Transitions in care among patients with lung, bladder, colorectal and head and neck cancer: A retrospective cohort study, In preparation). Similarly, in the present study patients had, on average, 7.8 emergency department visits during the study period, which may be higher compared to other oncological patient populations with a median number of emergency department visits of 2.0 over 4 years [ 49 ]. The differences in estimates between the present study and previous work may be partly explained by differences in patient populations and the objectives of each study. Similarly, consistent with our findings that patients with HNC consult many physicians, previous work found that patients with cancer see a median of 32 different physicians during their cancer journey [ 50 ]. Unfortunately, each TiC represents an opportunity for the occurrence of medical errors, adverse events, increased mortality risk, low patient satisfaction, elevated emergency department visits and poor quality of care [ 51 , 52 , 53 , 54 , 55 , 56 ]. Poor quality of care can stem from challenges reported in this study such as fragmented care, resource limitations and communication breakdowns between patients and healthcare providers. Patients with HNC in this study also emphasized the importance of patient-centeredness which are pillars of quality of care, and mirror findings in other oncology patient populations [ 57 , 58 , 59 , 60 ], where it has been reported that preferences, values, and needs are not adequately considered in their care [ 57 , 58 , 61 ].

As healthcare providers play a pivotal role in delivering care, factors such as physician wellness and burnout have been associated with poor quality of care [ 62 , 63 ]. Oncology ranks as a highly stressful specialty compared to other healthcare specialties (internal medicine, neurology, and cardiology), leading to higher healthcare provider burnout rates [ 64 , 65 ]. This elevated burnout can also be attributed to electronic health records usage, high workloads, and emotional distress resulting from long hours, high work intensity, time constraints and under-resourced work environments [ 63 , 66 , 67 , 68 , 69 ]. Our findings illustrate a need to develop and implement tailored interventions prioritizing quality of care and alleviating healthcare provider burnout. Addressing the challenges identified by patients with HNC and their healthcare providers can help bridge the quality-of-care gaps within HNC care.

While the present study found a high number of TiC among patients with HNC, some of these transitions are appropriate and necessary to provide high-quality, evidence-based care. While minimizing the TiC can decrease the risk associated with these vulnerable points in cancer care, another approach, which acknowledges the importance and necessity of TiC is to develop interventions to improve TiC. While some of the patient suggested strategies are innovative and understudied (consolidating HNC care), others have been shown to be effective at improving the quality of care during TiC [ 70 , 71 ]. Shared decision-making (patients and their healthcare providers jointly making informed treatment decisions) [ 72 ], reduces decision conflict, sets accurate expectations, and aligns with patient values [ 73 , 74 ]. Telehealth (the process of facilitating or delivering health services through any form of digital or telecommunication) [ 75 ], can improve TiC (reduce preventable hospital admissions) by fostering better multidisciplinary communication, strengthening the patient-provider relationship, and mitigating the impact of healthcare-provider shortages [ 76 , 77 , 78 , 79 ]. However, telehealth may not be feasible among a patient population whose ability to hear and speak can be significantly compromised. The implementation of patient navigators within HNC care was the most widely endorsed strategy. Patient navigators are dedicated members of the multidisciplinary team who are liaisons and advocates internally and externally within the healthcare system [ 80 ]. This strategy can alleviate some of the concerns expressed by patients with HNC in our study: enhancing continuity of care, providing more information, connecting patients with the most appropriate healthcare provider, and ultimately mitigating the difficulties they face when navigating the healthcare system [ 81 , 82 ]. Additionally, this resource can ease the strain on healthcare providers by providing patients additional support, therefore, reducing burnout rates, minimizing the occurrence of medical errors and preventing turnover among healthcare providers [ 83 ]. In oncology, patient navigators have decreased hospital admissions, optimized resource consumption, increased quality of life and improved patient outcomes, among other benefits [ 84 , 85 ]. Implementing a feasible and effective intervention such as patient navigators within HNC care can address challenges faced by patients and their healthcare providers during TiC. Future research should investigate the effectiveness of these strategies within HNC care, especially impacts on patient outcomes, provider well-being and the overall healthcare system.

Limitations

This multimethod study integrated both quantitative and qualitative methodology, which generated a rich understanding of TiC among patients with HNC, enhancing the strengths of each method and mitigating their respective weaknesses. In the retrospective cohort study, we were limited to the recorded information and existing variables in the databases used in this study, thus limiting the TiC we could explore. There were also limitations to the qualitative component of this work. Our included patient population is mostly female which does not reflect the general demographic of patients with HNC who is mostly male. This may be attributed to women being more inclined to seek medical attention, visit healthcare facilities and participate in research. Therefore, the perspectives of patients with HNC in our study may be less transferable to other populations of patients with HNC. Potential mitigation strategies for recruitment difficulties could be to partner with additional patient advocacy groups and offer tailored participation incentives for patients.

In conclusion, this study identified a myriad of challenges faced by both patients with HNC and healthcare providers amidst frequent TiC. Our findings suggest that TiC can impact the quality of care and provide crucial insights that can inform and guide future research or the development of health interventions aiming to improve TiC within this patient population. These findings also identified potentially feasible interventions for further exploration, such as shared decision-making, telehealth, or a patient navigator within HNC care.

Availability of data and materials

Data will be made available upon reasonable request to the corresponding author.

Abbreviations

Head and Neck Cancers

Transitions in Care

Health Research Ethics Board of Alberta

Alberta Health Services

STrengthening the Reporting of Observational Studies in Epidemiology

REporting of studies Conducted using Observational Routinely-collected Data

Alberta Cancer Registry

Discharge Abstract Database

National Ambulatory Care Reporting System

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This study was supported by an Alberta Graduate Excellence Scholarship and the Cumming School of Medicine Graduate Program Scholarship awarded to Jaling Kersen, and a Canadian Cancer Society Challenge Grant awarded to Khara Sauro. The funders of the study had no role in study design, data collection, data analysis, data interpretation or writing of the manuscript.

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Pamela Roach, Paul Ronksley & Khara Sauro

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J.K made substantial contributions to the conceptualization of the study, data collection, interpretation of the data, writing the original draft, and reviewing and editing the original draft. K.M.S made substantial contributions to funding acquisition, conceptualization of the study, data collection, interpretation of the data, drafting, revising the original draft, and reviewing and editing the original draft. S.C, P.R, P.R and J.D made substantial contributions to reviewing and editing the original draft. All authors reviewed and critically revised the article and approved the version to be published and agree to be accountable for all aspects of the work.

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Kersen, J., Roach, P., Chandarana, S. et al. Exploring transitions in care among patients with head and neck CANCER: a multimethod study. BMC Cancer 24 , 1108 (2024). https://doi.org/10.1186/s12885-024-12862-x

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A, Homicide rates were calculated using counts of homicide victims from Chicago Police Department records and interpolated population counts for the City of Chicago from the US Census Bureau decennial census and American Community Survey. B, Boxes highlight when members of each age cohort were aged 13 through 19 years, considered high-risk ages for participation in and exposure to gun violence. Dotted blue lines indicate midpoints of rolling survey data collection for each wave.

Survival curves were estimated using the Turnbull nonparametric maximum likelihood estimator for interval-censored events. Interval censoring results in plateaus in curves between survey waves 3 and 5 and regions where curves are not uniquely identified, indicated by diagonal lines. The observed data are consistent with any increasing line connecting the ends of the diagonal segments. At-risk respondent counts are model estimates as the exact number of respondents at-risk at any time is unknown due to interval censoring. Initial at-risk respondents are different between seen shot (2417 respondents) and been shot (2135 respondents) outcomes because been shot questions were not asked in the first survey wave. Triangles at base of panels E and F indicate the approximate age of each cohort at the time of the 1994 violence peak in Chicago (see Figure 1 ).

Hazard ratios (HR) and incidence rate ratios (IRR) greater than 1 indicate higher estimated exposure to gun violence. HRs were estimated with multivariable semiparametric Turnbull proportional hazards models. IRRs were estimated with a multivariable negative binomial regression. Reference categories are White for race, female for sex, and 1981 for cohort. Models were weighted to permit generalizing estimates of exposure to the population of children growing up in Chicago in the 1990s. The case weights applied during estimation are the product of the survey design weights and attrition weights at each wave, constructed using estimated probabilities from binary logistic regression models. 15 Observations received the combined weight at their final follow-up period (eg, an individual observed through wave 3 would receive a weight equal to the product of the survey design weight, their wave 2 attrition weight, and their wave 3 attrition weight). Results are insensitive to trimming weights to the center 90% of the distribution. Results are also similar with alternative specifications of survival models (eFigure 2 in Supplement 1 ) and without weights (eFigure 3 in Supplement 1 ). Sample sizes are 2417 respondents for seen shot, 2135 respondents for been shot, and 649 respondents for nearby shootings.

A, C, and E depict race-specific quintiles of frequencies of shootings within 250 m of respondents' residence in the past year. B, D, and F depict representative locations with counts of nearby shootings approximately equal to the mean of each group's fifth quintile (7 shootings for Black respondents, 2 shootings for Hispanic respondents, and 1 shooting for White respondents). Red dots are shootings. Circles are 250-m radii around respondent places of residence but are shifted to protect anonymity. Only race differences are shown because nearby shooting frequencies did not notably differ by sex or age cohort. Analysis was restricted to Black, Hispanic, and White respondents of wave 5 (649 respondents). Map tiles by Stamen Design; map data by OpenStreetMap (OpenStreetMap Foundation).

eAppendix 1. Survey Measures

eFigure 1. Cox Proportional Hazard Model Estimates

eAppendix 2. Accelerated Failure Time Models

eFigure 2. Interval Censored Accelerated Failure Time Models

eFigure 3. Unweighted Model Estimates

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• Youth Parental Death Due to Drug Poisoning and Firearm Violence in the US JAMA Original Investigation May 28, 2024 This cross-sectional study uses a demographic projection model and publicly available vital statistics data to estimate the national incidence of parental death due to drugs and firearms overall and by race and ethnicity. Benjamin-Samuel Schlüter, PhD; Diego Alburez-Gutierrez, PhD; Kirsten Bibbins-Domingo, PhD, MD, MAS; Monica J. Alexander, PhD; Mathew V. Kiang, ScD
• Structural Racism and Long-term Disparities in Youth Exposure to Firearm Violence JAMA Network Open Invited Commentary May 9, 2023 Jonathan Jay, DrPH, JD

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Lanfear CC , Bucci R , Kirk DS , Sampson RJ. Inequalities in Exposure to Firearm Violence by Race, Sex, and Birth Cohort From Childhood to Age 40 Years, 1995-2021. JAMA Netw Open. 2023;6(5):e2312465. doi:10.1001/jamanetworkopen.2023.12465

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Inequalities in Exposure to Firearm Violence by Race, Sex, and Birth Cohort From Childhood to Age 40 Years, 1995-2021

• 1 Institute of Criminology, University of Cambridge, Cambridge, United Kingdom
• 2 Department of Sociology, Harvard University, Cambridge, Massachusetts
• 3 Department of Sociology and Nuffield College, University of Oxford, Oxford, United Kingdom
• Invited Commentary Structural Racism and Long-term Disparities in Youth Exposure to Firearm Violence Jonathan Jay, DrPH, JD JAMA Network Open
• Original Investigation Youth Parental Death Due to Drug Poisoning and Firearm Violence in the US Benjamin-Samuel Schlüter, PhD; Diego Alburez-Gutierrez, PhD; Kirsten Bibbins-Domingo, PhD, MD, MAS; Monica J. Alexander, PhD; Mathew V. Kiang, ScD JAMA

Question   Did the likelihood of being shot, seeing someone shot, or living near firearm violence vary by race, sex, and birth cohort over the life course during the past 3 decades?

Findings   This cohort study found that the likelihood of exposure to all forms of firearm violence varied significantly and persistently over the life course by race. Sex differences were greatest for being shot compared to witnessing or proximity to firearm violence, and cohort differences were most pronounced for witnessing violence.

Meaning   These finding suggest that understanding who gets exposed to firearm violence and when requires simultaneous attention to inequality by race, sex, and cohort.

Importance   The past quarter-century has seen both sharp declines and increases in firearm violence in the United States. Yet, little is known about the age of first exposure to firearm violence and how it may differ by race, sex, and cohort.

Objective   To examine race, sex, and cohort differences in exposure to firearm violence in a representative longitudinal study of children who grew up in periods with varying rates of firearm violence in the United States and to examine spatial proximity to firearm violence in adulthood.

Design, Setting, and Participants   This population-based representative cohort study included multiple cohorts of children followed-up from 1995 through 2021 in the Project on Human Development in Chicago Neighborhoods (PHDCN). Participants included Black, Hispanic, and White respondents from 4 age cohorts of Chicago, Illinois, residents, with modal birth years of 1981, 1984, 1987, and 1996. Data analyses were conducted from May 2022 to March 2023.

Main Outcomes and Measures   Firearm violence exposure, including age when first shot, age when first saw someone shot, and past-year frequency of fatal and nonfatal shootings within 250 m of residence.

Results   There were 2418 participants in wave 1 (in the mid-1990s), and they were evenly split by sex, with 1209 males (50.00%) and 1209 females (50.00%). There were 890 Black respondents, 1146 Hispanic respondents, and 382 White respondents. Male respondents were much more likely than female respondents to have been shot (adjusted hazard ratio [aHR], 4.23; 95% CI, 2.28-7.84), but only moderately more likely to have seen someone shot (aHR, 1.48; 95% CI, 1.27-1.72). Compared with White individuals, Black individuals experienced higher rates of all 3 forms of exposure (been shot: aHR, 3.05; 95% CI, 1.22-7.60; seen someone shot: aHR, 4.69; 95% CI, 3.41-6.46; nearby shootings: adjusted incidence rate ratio [aIRR], 12.40; 95% CI, 6.88-22.35), and Hispanic respondents experienced higher rates of 2 forms of violence exposure (seen someone shot: aHR, 2.59; 95% CI, 1.85-3.62; nearby shootings: aIRR, 3.77; 95% CI, 2.08-6.84). Respondents born in the mid-1990s who grew up amidst large declines in homicide but reached adulthood during city and national spikes in firearm violence in 2016 were less likely to have seen someone shot than those born in the early 1980s who grew up during the peak of homicide in the early 1990s (aHR, 0.49; 95% CI, 0.35-0.69). However, the likelihood of having been shot did not significantly differ between these cohorts (aHR, 0.81; 95% CI, 0.40-1.63).

Conclusions and Relevance   In this longitudinal multicohort study of exposure to firearm violence, there were stark differences by race and sex, yet the extent of exposure to violence was not simply the product of these characteristics. These findings on cohort differences suggest changing societal conditions were key factors associated with whether and at what life stage individuals from all race and sex groups were exposed to firearm violence.

Nearly 21 000 individuals in the US were killed by gun violence in 2021, a rate of 6.3 deaths per 100 000 population. 1 A rate of this magnitude has not been seen since 1994, near the late–20th-century peak in firearm violence. 2 After that, an unexpectedly steady and sizable multidecade decline in violence took place, with the national gun homicide rate decreasing to 3.5 deaths per 100 000 population by 2014. Taking experts by surprise, homicides then began increasing before spiking in 2016 and again in 2020. 3 Firearm deaths have now surpassed motor vehicle crashes as the leading cause of death for US children, with Black children, boys, and children from disadvantaged neighborhoods in cities like Chicago, Illinois, disproportionately impacted. 4 - 7

The extreme fluctuation in lethal violence in the US over the past 3 decades means that successive cohorts of children growing up and reaching adulthood in these times experienced much different social worlds, what has been called the “birth lottery of history.” 8 Even if they are from the same socioeconomic status, some adults today were raised during an era of relative calm, whereas others, sometimes just a handful of years older or younger, reached their formative years of adolescence and early adulthood during epidemic levels of firearm violence.

Despite increasing attention to the burden of firearms on health and mortality, exposure to firearm violence over the life course is not well understood, particularly exposure to nonfatal firearm violence. 9 Much of the focus has been on national estimates of homicides and suicides. Other studies have sought to examine the causes of aggregate changes in violence over recent decades. 10 , 11 While important, such studies do not reveal when in the life course exposure occurs and whether dynamic patterns differ by race, sex, and birth cohort. Long-term longitudinal studies of exposure to firearm violence are relatively rare, especially those that document how both witnessing violence and personally experiencing violence unfold over the life course and differ by race and sex. 12 , 13

Rarer still are studies that examine different cohorts who reached late adolescence and transitioned to adulthood during times of historic highs and lows in violence over the last quarter-century. Without studies of multiple cohorts, it is challenging to pinpoint whether and how broad societal changes, such as the 1990s and 2000s crime decline, the steady weakening of gun laws, or the COVID-19 pandemic, might have influenced exposure to firearm violence by age.

In this study, we leverage a unique longitudinal design to examine exposure to firearm violence from childhood through midadulthood by comparing the likelihood of being shot as well as seeing someone shot for multiple cohorts of children from Chicago, separated in age by approximately 15 years. Although followed over the same period, 1995 to 2021, the children from these cohorts reached key developmental periods in the life course during much different societal contexts. We highlight cohort inequalities in exposure to firearm violence, as well as disparities by race and sex. Finally, we examine race, sex, and birth cohort differences in spatial proximity to firearm violence in the present decade.

This cohort study was approved by the Harvard University institutional review board. Adult respondents provided written or verbal informed consent to participate in the study, and parents consented for child respondents. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline for cohort studies.

The Project in Human Development in Chicago Neighborhoods (PHDCN) began in the mid-1990s as a representative sample of 6207 age-eligible children drawn from a screening of more than 35 000 households in a stratified representative sample of 80 of Chicago’s 343 neighborhoods. Children falling within 7 age cohorts, including infancy (mean age, 6 months) and ages 3, 6, 9, 12, 15, and 18 years, were sampled from randomly selected households and studied over 3 waves of data collection, to the early 2000s. 14 Modal birth years of the original age cohorts were 1978, 1981, 1984, 1987, 1990, 1993, and 1996.

In 2011 to 2012, the PHDCN was extended through a random sample of wave 3 participants. Resource constraints prohibited following-up with the entire sample. Therefore, a 60% random sample of 4 of the original 7 PHDCN cohorts (infancy and age cohorts of 9, 12, and 15 years) with high retention rates at wave 3 (78.6%) and a wide age range was selected, yielding 1057 participants at wave 4 (63% response rate). 15

In 2021, wave 4 respondents were followed-up for a fifth survey wave no matter where they lived in the US, yielding a sample of 682 respondents (66% response rate). We examine 2418 Black, Hispanic, and White respondents from the 4 sampled cohorts, including 1770 original members who were not part of the subsample drawn at wave 4. The difference between the original sample and the analytic sample size reflects subsampling at wave 4 and attrition, which we address through weights, and the fact that our youngest cohort was not asked questions about exposure to firearm violence until they were adults in wave 5. Additional information on the study design has been previously published. 15

The current analysis also draws on data from the Gun Violence Archive (GVA), a not-for-profit corporation that aggregates data on incidents of gun violence from more than 7500 sources, including police departments, media, and government. We obtained all incidents throughout the US that occurred within 250 m of the respondents’ addresses in the year prior to respondents’ wave 5 interview dates in 2021.

To illustrate the historical context of the data collection, we plot the ages of respondents and homicide rates in Chicago in Figure 1 . The wave 1 survey in the mid-1990s coincided with the beginning of a long decline in lethal violence in Chicago, as in the rest of the country. 6 , 10 Our oldest age cohort of respondents, born in 1981, reached their teenage years (ie, age 13-19 years) in the early 1990s when lethal firearm violence was at its peak. In contrast, the 1987 cohort, born only 6 years later, reached the formative years of adolescence in a much safer context. The 1984 cohort came of age between these periods, when crime was still high but declining. The youngest cohort, born in 1996, reached their teenage years at the lowest levels of lethal violence in both the US and Chicago in more than 40 years. However, by the time the 1996 cohort reached late adolescence and early adulthood, beginning in 2015 to 2016, Chicago was experiencing a surge in violence. By their 20th birthdays, these individuals were confronted by a dramatically more violent context than members of the other cohorts at age 20 years, despite being born into a period of rapidly declining violence. These patterns motivate our substantive focus on estimating cohort differences, in addition to race and sex inequalities, in exposure to firearm violence over the life course during these changing times.

Age when first saw someone shot (ie, seen shot) was calculated from questions in waves 1, 2, 3, and 5. Respondents were asked if they had ever seen or been present when someone was shot, when this last occurred, if they had seen someone shot in the past year, and at what age they had first seen this. Respondents were not asked about the age of exposure in wave 5. The combination of these responses results in either a year of age or interval of ages in which first exposure occurred (eAppendix 1 in Supplement 1 ). Age when first shot (ie, been shot) was calculated from questions in waves 2, 3, and 5 asking respondents if they had ever been shot, the age this first occurred, and if they had been shot in the past year. Nearby shootings is the count of shootings resulting in a death or injury recorded by GVA that occurred in the past year within 250 m of a respondent’s residential location as reported at wave 5. This radius was chosen to capture events happening within the approximate distance of a standard Chicago city block (results are similar using distances of 100, 500, or 1000 m).

Race of respondents was reported by their primary caregiver, which was categorized first by ethnicity (Hispanic or non-Hispanic) and then by racial group (Black or White) for those who were non-Hispanic. We excluded 102 individuals (4.0%) of other races (eg, American Indian, Asian, or Pacific Islander) because the sample was too small to conduct longitudinal analyses. Sex was recorded by interviewers. Cohort was defined by age at enrollment in the study. Respondents were sampled by eligible ages (ie, infancy and ages 9, 12, and 15 years at wave 1) during the first wave of data collection, which occurred over approximately 3 years. Because of this design, there is variation in birth year within age cohorts. To ease interpretation of results, we refer to cohorts by their modal birth year (ie, 1981, 1984, 1987, and 1996).

We estimated survival curves of the cumulative percentage of respondents exposed to firearm violence by race, sex, and cohort by a given age using the nonparametric Turnbull maximum-likelihood estimator (NPMLE), a generalization of the Kaplan-Meier estimator applicable to interval-censored data. 16 , 17 Accounting for interval censoring is necessary for the seen shot outcome because age at time of exposure is uncertain for respondents exposed in the years between wave 3 and 1 year prior to wave 5. This is less consequential for the been shot outcome, since wave 5 respondents were asked for the age when first shot, resulting in smaller censoring intervals.

We estimated associations between sociodemographic characteristics and exposure to firearm violence using multivariable semiparametric Turnbull (SPT) proportional hazards models. 18 , 19 The SPT model is analogous to the Cox proportional hazards model but estimates the baseline hazard using the NPMLE to account for interval censoring. A Cox model with interval midpoints as exposure times yields similar estimates (eFigure 1 in Supplement 1 ). No formal test of the proportional hazards’ assumption exists for SPT models, but accelerated failure time models that relax the proportional odds assumption produce substantively equivalent estimates (eFigure 2 and eAppendix 2 in Supplement 1 ).

We used a negative binomial regression model to estimate the association between our covariates and counts of past-year shootings occurring within 250 m of a respondent’s residence. These models include combined survey design and attrition weights to permit inferences to the population of Chicago children. We performed statistical analyses in R software version 4.2.2 using the interval, icenReg, and MASS packages (R Project for Statistical Computing), with a 2-tailed significance level of P  < .05. 17 , 19 , 20 Because our analyses are descriptive and not directed at formal hypothesis testing, the purpose of calculating CIs is to draw inferences from our sample to the population. Data analyses were conducted from May 2022 to March 2023.

The overall sample size was 2418 respondents, with 1209 males (50.00%) and 1209 females (50.00%) and 890 Black respondents, 1146 Hispanic respondents, and 382 White respondents. By age 40 years, 6.46% of respondents had been shot and 50.00% of respondents had seen someone shot. Seeing others shot tended to occur earlier in life (mean [SD] age of exposure, 14.26 [5.83] years) than being shot (mean [SD] age of exposure, 17.11 [6.97] years). Counts of recent shootings within 250 m of a respondent’s residence were concentrated among a small number of sample members (mean [SD], 0.45 [2.04] shootings; maximum, 15 shootings).

Figure 2 presents cumulative exposure curves by race, sex, and cohort. Racial differences in exposure to firearm violence were pronounced, with both forms of exposure lowest for White respondents ( Figure 2 A). By age 40, 7.47% of Black respondents and 7.05% of Hispanic respondents had been shot, with 1 Black respondent and 1 Hispanic respondent having been fatally shot. In contrast, 3.13% of White respondents had been shot by age 40 years. Racial and ethnic differences were also strongly age-patterned: no White respondents but 7 Black respondents and 5 Hispanic respondents were shot after age 21 years. Similarly, 56.34% of Black respondents and 55.75% of Hispanic respondents saw someone shot by age 40 years, compared with 25.53% of White respondents ( Figure 2 B).

Sex differences in being shot were also significant, with the cumulative exposure of male respondents (11.40%) 5 times higher than that of female respondents (2.28%) by age 40 years ( Figure 2 C). Differences again were age-patterned. Most reports of being shot for female respondents occurred during their midteenaged years, whereas males reported being shot throughout their teenaged years and their 20s and 30s. Sex differences in seeing others shot by age 40 years were more modest: 42.81% of female respondents and 57.64% of male respondents had seen someone shot ( Figure 2 D).

Direct experience of being shot was typically highest at all ages for the 1981 cohort, whose adolescence coincided with the 1990s peak in violence ( Figure 2 E). All cohorts displayed rapid increases in incidence of experiencing gun violence in late adolescence, except for the 1996 cohort, whose increase began earlier and was more gradual. The cumulative incidence of experiencing gun violence by the end of follow-up for the 1996 cohort (ie, in their mid-20s) fell between the high-exposure cohorts (1981 and 1984) and low-exposure cohort (1987).

Similar to direct experience of being shot, the cumulative risk of having seen someone shot was higher for the 1981 and 1984 cohorts ( Figure 2 F). The 1987 cohort reached mid-to-late adolescence during the low-violence period of the early 2000s, whereas the 2 older cohorts reached the same developmental stage in a more violent era in the 1990s, with greater exposure among the latter 2 cohorts, despite the 1987 cohort initially having had more exposure in early childhood. The 1996 cohort experienced lower exposure than the other cohorts. At the end of the observation period, at approximately ages 26 to 27 years, the cumulative risk of having seen someone shot for the 1996 cohort was approximately the same as when the older cohorts were just age 15 years.

Figure 3 presents adjusted hazard ratios (aHRs) and adjusted incidence rate ratios (aIRRs) with 95% CIs from multivariate SPT models of been shot and seen shot, as well as the negative binomial model of nearby shootings. Independent measures of nearby shootings provide a complement to self-reported indicators of being shot and seeing someone shot. We assess proximity to shootings by race, sex, and cohort during a period of elevated violence in 2020 to 2021.

Statistical power is low for estimates of been shot due to the rarity of the event ( Figure 3 A). Hence, 95% CIs are wide. The hazard of being shot was more than 3 times as high for Black individuals (aHR, 3.05; 95% CI, 1.22-7.60) compared with White individuals. The difference between Hispanic and White individuals was not significant (aHR, 1.85; 95% CI, 0.68-5.09). Compared with female respondents, hazards of being shot were more than 4 times higher for male respondents (aHR, 4.23; 95% CI, 2.28-7.84). Although the 1987 cohort exhibited the lowest hazard of being shot (aHR, 0.37; 95% CI, 0.12-1.15) compared with the 1981 cohort, which exhibited the highest estimated exposure, the difference between the cohorts was not statistically significant ( Figure 2 E). The 1996 and 1984 cohorts exhibited hazards similar to the 1981 cohort but these differences were also not significant (1996: aHR, 0.81; 95% CI, 0.40-1.63; 1984: aHR, 0.84; 95% CI, 0.47-1.51).

Analyses of the hazard of witnessing violence found that, compared with White individuals, the hazard of seeing someone shot was more than 4.5 times as high for Black individuals (aHR, 4.69; 95% CI, 3.41-6.46) and more than 2.5 times as high for Hispanic individuals (aHR, 2.59; 95% CI, 1.85-3.62) ( Figure 3 B). Compared with female respondents, male respondents were significantly more likely to have seen someone shot (aHR, 1.48; 95% CI, 1.27-1.72). Finally, consistent with results presented in Figure 2 F, SPT results indicate that the 3 older cohorts had approximately similar hazards of seeing someone shot, but the 1996 cohort exhibited a hazard approximately half that of the 1981 cohort (aHR, 0.49; 95% CI, 0.35-0.69).

Figure 3 C presents estimates of the correlates of the count of shootings within 250 m of a respondent’s residence during the 12 months preceding their wave 5 interview. While there were no significant differences by sex or cohort in proximity to nearby shootings, we observed significant racial disparities. Black individuals (aIRR, 12.40; 95% CI, 6.88-22.35) and Hispanic individuals (aIRR, 3.77; 95% CI, 2.08-6.84) experienced higher rates of shootings in close proximity to their residences than White individuals. Notably, we detected no race or sex by cohort interactions for this measure or for having been shot or having seen someone shot.

Figure 4 depicts the magnitude of these race differences in terms of raw counts. In the most violent neighborhoods (ie, the fifth quintile, denoting the top 20% of residential locations by the frequency of shootings), a mean of 7 shootings occurred in the preceding year within 250 m of the residences of Black respondents, compared with more than 2 for Hispanic respondents and less than 1 for White respondents.

In this cohort study, the accelerated longitudinal design of the extended PHDCN allowed us to examine multiple forms of firearm violence exposure from childhood through midadulthood in a population sample. We found significant differences in exposure to firearm violence by race and sex, and our findings on cohort differences point to changing societal conditions as key factors associated with whether and at what life-stage individuals were exposed to firearm violence. For instance, participants from the 1987 cohort had the lowest incidence of having been shot, which could have been because they reached the formative years of late adolescence when firearm violence was at its lowest point in the past 3 decades. Examples of other changing conditions that merit future research include the surge in firearm purchasing in the wake of the COVID-19 pandemic, the loosening of gun regulations in the US, and widespread unrest over excessive police use of force in Black communities.

Recent surges in lethal firearm violence have captivated public and media attention, but the reach of firearm violence is broader than immediate fatalities. Particularly for Black and Hispanic males growing up in urban neighborhoods, seeing someone shot or being shot before even reaching age 20 years is pervasive. And for Black and Hispanic individuals who reached adulthood without being exposed to firearm violence, there was still a considerable likelihood that they would be exposed by age 40 years. In addition, at the time of our most recent survey in 2021, Black and Hispanic respondents were residing in communities with firearm violence that far exceeded the rates in the communities of White respondents.

A broader focus beyond fatalities to include nonfatal gunshot injuries and witnessing of incidents is critical for understanding the full health outcomes associated with firearm violence. In addition, the sustained stress resulting from routine exposure to firearm violence can take a cumulative physiological toll on the body, and is associated with damage to the body’s regulatory system and the acceleration of aging and susceptibility to disease. 21 - 23 To the extent that major and potentially chronic stressors are disproportionately endured by some sociodemographic groups, as we have shown here, variation in these stressors may contribute to dramatic sociodemographic differences in health. 24 The stress from chronic exposure to firearm violence may also contribute to subsequent violence, through its impact on aggression, or even through the normalization of violence. 25 , 26

Consistent with the life-course framework of the current study, future work should focus not simply on the consequences associated with having ever seen someone shot or having been shot themselves, but also the timing of the exposure and accumulation of exposures. Furthermore, a focus on the consequences of exposure to firearm violence should examine both near-term and long-term outcomes. Additionally, further research is necessary to explain the variations in firearm exposure by race, sex, and cohort that were identified in this study, including studies that examine the role of residential segregation, as well as residential mobility.

This study has some limitations. Although this long-term study uses a representative sample of children who reached the formative years of adolescence at differing times over the last quarter-century, it is based on children originally from Chicago. This raises generalizability questions, but violence rates and trends in Chicago parallel those in other major cities in the US, such as Philadelphia, Pennsylvania. Furthermore, the extended PHDCN data collection followed-up with respondents wherever they moved. Although retention rates compare well with contemporary urban samples and the analyses were weighted to reflect the sampling design and attrition, selection out of the sample on unobserved covariates may bias the results. Another potential limitation, common to self-report surveys, is recall error, such as difficulty in recalling the precise timing of events.

A 2020 study 27 using GVA data found undercounting of nonfatal shootings due to selective reporting of firearm violence by the media. However, race or ethnicity of individuals who were shot was not associated with the likelihood of reporting, suggesting the racial and ethnic differences in nearby shootings reported in this study are unlikely to be biased by selective reporting. Moreover, we found similar racial and ethnic differences when restricting our analyses to fatal shootings.

This cohort study reports on previously undocumented inequalities in exposure to firearm violence over the life course by race, sex, and cohort. Life-course exposure to firearm violence was significantly and persistently higher for Black and Hispanic individuals. Sex disparities in witnessing and proximity to firearm violence were small, but men were at significantly higher risk of being shot than women. Cohort differences were most pronounced for having seen someone shot; in particular, the youngest cohort in our study had a lower likelihood of having seen someone shot than counterparts born in earlier decades. The perspective we have taken reorients the study of exposure to firearm violence toward a focus on sex and racial inequalities over the life course in the context of ongoing social changes that differentiate the life experience of successive birth cohorts.

Accepted for Publication: March 24, 2023.

Published: May 9, 2023. doi:10.1001/jamanetworkopen.2023.12465

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Lanfear CC et al. JAMA Network Open .

Corresponding Author: Robert J. Sampson, PhD, Department of Sociology, Harvard University, William James Hall, 33 Kirkland St, Cambridge, MA 02138 ( [email protected] ).

Author Contributions: Drs Lanfear and Sampson had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Lanfear, Bucci, Sampson.

Obtained funding: Kirk, Sampson.

Administrative, technical, or material support: Lanfear, Bucci, Kirk.

Supervision: Lanfear, Kirk, Sampson.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by funding from the National Collaborative on Gun Violence Research, the National Institute of Justice (grant No. 2020-JX-FX-0002), and the Leverhulme Trust through the Leverhulme Centre for Demographic Science.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

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• Knowledge Base

Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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• | August 21, 2024

Alkami Market Study Reveals Differences in AI Outlook between Financial Institutions and Consumers

96% of financial institutions foresee AI playing a critical role in the next five years 

August 21, 2024 (Plano, Texas) – Alkami Technology, Inc. (Nasdaq: ALKT) (“Alkami”), a leading cloud-based digital banking solutions provider for financial institutions in the U.S., today released commissioned research findings regarding the distinct perspectives on artificial intelligence (AI) held by regional and community financial institutions (RCFIs) compared to consumers, particularly in terms of its potential, use cases and adoption. The research revealed a disparity between these two groups, highlighting the dual task that financial institutions encounter when adopting AI: leveraging AI to enhance operational efficiencies and account holder satisfaction while navigating the complexities of data security, privacy concerns and ethical considerations.

Alkami’s primary research surveyed RCFIs and how they are currently using or planning to use AI across various digital banking use cases, their attitudes towards the opportunities and challenges AI presents, and their outlook on its potential future impact to their business. Over the same time period, a commissioned research study in partnership with The Center for Generational Kinetics was conducted where digital banking consumers were asked to compare and contrast their attitudes, perceptions and beliefs to the RCFIs that serve them.

Key findings include:

• While 96% of financial institutions foresee AI playing a critical role in the next five years, only 61% of consumers expect AI to significantly influence their banking interactions.
• A considerable majority of these institutions—78%—see AI as a catalyst for uncovering new business opportunities, while additional benefits are expected in areas such as time savings for employees (77%), reducing operational costs (59%), and revenue growth (56%).
• The progress of leveraging AI in an RCFI is not correlated with size. Just 21% of RCFIs with more than $5 billion in assets are successfully leveraging AI in at least a few key areas today compared with 19% of those institutions with less than $1 billion in assets.
• Millennials are the most comfortable with their data being used by AI to deliver a better digital banking experience, with 51% agreeing to the same, statistically higher than all other generations – Generation Z (Gen Z), Generation X (Gen X), and baby boomers .
• Younger generations (Millennials and Gen Z) cite financial wellness as one of the areas where they would be most comfortable with AI, however it is among the least popular for RCFIs in terms of AI application or planned experimentation.

“Many financial institutions are beginning to understand the potential for AI across the range of their operations, and as they navigate an internal strategy for implementation and use cases, we want to provide the broader industry with benchmarks directly from market research in various areas of AI,” said Allison Cerra, chief marketing officer at Alkami. “The study reveals the more common applications for AI today and where RCFIs believe AI will have the biggest impact in banking, both of which can prove useful to RCFIs benchmarking their own AI progress.”

The study also found that a significant majority of financial institutions remain in the foundational stages of understanding and implementing AI. For those that have experimented with AI, their success rates are impressive, with at least 88% of RCFIs saying their AI initiatives in customer service, data insights, marketing, and/or security and fraud protection have been mostly or very successful.

“We are proud to continue our work with Alkami to prepare their customers with resources that enable them to navigate the latest innovations and technology,” said Jason Dorsey, president of The Center for Generational Kinetics . “As the study outlines, a key part of the path forward for RCFIs is education, and we hope this study encourages banks and credit unions to delve deeper into AI literacy and adopt a structured and strategic framework to maximize potential and navigate the inherent complexities.”

This announcement follows the news that Alkami was recently certified by J.D. Power for “An Outstanding Mobile Banking Platform Experience1” as a part of its commitment to help financial institutions usher in the latest technology and services.

To download the complete AI market study, “The Application and Consumer Perception of Artificial Intelligence in Banking,” please click here .

1J.D. Power 2024 Mobile App Platform Certification ProgramSM recognition is based on successful completion of an audit and exceeding a customer experience benchmark through a survey of recent servicing interactions. For more information, visit jdpower.com/awards.

About The Center for Generational Kinetics

The Center for Generational Kinetics is a global research firm focused on delivering custom research that uncovers emerging trends, hidden behavioral drivers, and actionable insights for leaders. The firm has led more than 120 custom research studies around the world for global brands and industry pioneers. To learn more, visit GenHQ.com .

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