what is the analysis section of a research paper

How to Write the Analysis Section of My Research Paper

How to Write a Technical Essay

Data collection is only the beginning of the research paper writing process. Writing up the analysis is the bulk of the project. As Purdue University’s Online Writing Lab notes, analysis is a useful tool for investigating content you find in various print and other sources, like journals and video media.

Locate and collect documents. Make multiple photocopies of all relevant print materials. Label and store these in a way that provides easy access. Conduct your analysis.

Create a heading for the analysis section of your paper. Specify the criteria you looked for in the data. For instance, a research paper analyzing the possibility of life on other planets may look for the weight of evidence supporting a particular theory, or the scientific validity of particular publications.

Write about the patterns you found, and note the number of instances a particular idea emerged during analysis. For example, an analysis of Native American cultures may look for similarities between spiritual beliefs, gender roles or agricultural techniques. Researchers frequently repeat the process to find patterns that were missed during the first analysis. You can also write about your comparative analysis, if you did one. It is common to ask a colleague to perform the process and compare their findings with yours.

Summarize your analysis in a paragraph or two. Write the transition for the conclusions section of your paper.

• Use compare and contrast language. Indicate where there are similarities and differences in the data through the use of phrases like ''in contrast'' and ''similarly.''

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• Purdue University Online Writing Lab - Analysis

Adam Simpson is an author and blogger who started writing professionally in 2006 and has written for OneStopEnglish and other Web sites. He has chapters in the volumes "Teaching and learning vocabulary in another language" and "Educational technology in the Arabian gulf," among others. Simpson attended the University of Central Lancashire where he earned a B.A. in international management.

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Academic Paper: Discussion and Analysis

5 min read • march 10, 2023

Dylan Black

Introduction

After presenting your data and results to readers, you have one final step before you can finally wrap up your paper and write a conclusion: analyzing your data! This is the big part of your paper that finally takes all the stuff you've been talking about - your method, the data you collected, the information presented in your literature review - and uses it to make a point!

The major question to be answered in your analysis section is simply "we have all this data, but what does it mean?" What questions does this data answer? How does it relate to your research question ? Can this data be explained by, and is it consistent with, other papers? If not, why? These are the types of questions you'll be discussing in this section.

Source: GIPHY

Writing a Discussion and Analysis

Explain what your data means.

The primary point of a discussion section is to explain to your readers, through both statistical means and thorough explanation, what your results mean for your project. In doing so, you want to be succinct, clear, and specific about how your data backs up the claims you are making. These claims should be directly tied back to the overall focus of your paper.

What is this overall focus, you may ask? Your research question ! This discussion along with your conclusion forms the final analysis of your research - what answers did we find? Was our research successful? How do the results we found tie into and relate to the current consensus by the research community? Were our results expected or unexpected? Why or why not? These are all questions you may consider in writing your discussion section.

You showing off all of the cool findings of your research! Source: GIPHY

Why Did Your Results Happen?

After presenting your results in your results section, you may also want to explain why your results actually occurred. This is integral to gaining a full understanding of your results and the conclusions you can draw from them. For example, if data you found contradicts certain data points found in other studies, one of the most important aspects of your discussion of said data is going to be theorizing as to why this disparity took place.

Note that making broad, sweeping claims based on your data is not enough! Everything, and I mean just about everything you say in your discussions section must be backed up either by your own findings that you showed in your results section or past research that has been performed in your field.

For many situations, finding these answers is not easy, and a lot of thinking must be done as to why your results actually occurred the way they did. For some fields, specifically STEM-related fields, a discussion might dive into the theoretical foundations of your research, explaining interactions between parts of your study that led to your results. For others, like social sciences and humanities, results may be open to more interpretation.

However, "open to more interpretation" does not mean you can make claims willy nilly and claim "author's interpretation". In fact, such interpretation may be harder than STEM explanations! You will have to synthesize existing analysis on your topic and incorporate that in your analysis.

Liam Neeson explains the major question of your analysis. Source: GIPHY

Discussion vs. Summary & Repetition

Quite possibly the biggest mistake made within a discussion section is simply restating your data in a different format. The role of the discussion section is to explain your data and what it means for your project. Many students, thinking they're making discussion and analysis, simply regurgitate their numbers back in full sentences with a surface-level explanation.

Phrases like "this shows" and others similar, while good building blocks and great planning tools, often lead to a relatively weak discussion that isn't very nuanced and doesn't lead to much new understanding.

Instead, your goal will be to, through this section and your conclusion, establish a new understanding and in the end, close your gap! To do this effectively, you not only will have to present the numbers and results of your study, but you'll also have to describe how such data forms a new idea that has not been found in prior research.

This, in essence, is the heart of research - finding something new that hasn't been studied before! I don't know if it's just us, but that's pretty darn cool and something that you as the researcher should be incredibly proud of yourself for accomplishing.

Rubric Points

Before we close out this guide, let's take a quick peek at our best friend: the AP Research Rubric for the Discussion and Conclusion sections.

Source: CollegeBoard

Scores of One and Two: Nothing New, Your Standard Essay

Responses that earn a score of one or two on this section of the AP Research Academic Paper typically don't find much new and by this point may not have a fully developed method nor well-thought-out results. For the most part, these are more similar to essays you may have written in a prior English class or AP Seminar than a true Research paper. Instead of finding new ideas, they summarize already existing information about a topic.

Score of Three: New Understanding, Not Enough Support

A score of three is the first row that establishes a new understanding! This is a great step forward from a one or a two. However, what differentiates a three from a four or a five is the explanation and support of such a new understanding. A paper that earns a three lacks in building a line of reasoning and does not present enough evidence, both from their results section and from already published research.

Scores of Four and Five: New Understanding With A Line of Reasoning

We've made it to the best of the best! With scores of four and five, successful papers describe a new understanding with an effective line of reasoning, sufficient evidence, and an all-around great presentation of how their results signify filling a gap and answering a research question .

As far as the discussions section goes, the difference between a four and a five is more on the side of complexity and nuance. Where a four hits all the marks and does it well, a five exceeds this and writes a truly exceptional analysis. Another area where these two sections differ is in the limitations described, which we discuss in the Conclusion section guide.

You did it!!!! You have, for the most part, finished the brunt of your research paper and are over the hump! All that's left to do is tackle the conclusion, which tends to be for most the easiest section to write because all you do is summarize how your research question was answered and make some final points about how your research impacts your field. Finally, as always...

Key Terms to Review ( 1 )

Research Question

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Research Paper Writing: 6. Results / Analysis

• 1. Getting Started
• 2. Abstract
• 3. Introduction
• 4. Literature Review
• 5. Methods / Materials
• 6. Results / Analysis
• 7. Discussion
• 8. Conclusion
• 9. Reference

Writing about the information

There are two sections of a research paper depending on what style is being written. The sections are usually straightforward commentary of exactly what the writer observed and found during the actual research. It is important to include only the important findings, and avoid too much information that can bury the exact meaning of the context.

The results section should aim to narrate the findings without trying to interpret or evaluate, and also provide a direction to the discussion section of the research paper. The results are reported and reveals the analysis. The analysis section is where the writer describes what was done with the data found.  In order to write the analysis section it is important to know what the analysis consisted of, but does not mean data is needed. The analysis should already be performed to write the results section.

Written explanations

How should the analysis section be written?

• Should be a paragraph within the research paper
• Consider all the requirements (spacing, margins, and font)
• Should be the writer’s own explanation of the chosen problem
• Thorough evaluation of work
• Description of the weak and strong points
• Discussion of the effect and impact
• Includes criticism

How should the results section be written?

• Show the most relevant information in graphs, figures, and tables
• Include data that may be in the form of pictures, artifacts, notes, and interviews
• Clarify unclear points
• Present results with a short discussion explaining them at the end
• Include the negative results
• Provide stability, accuracy, and value

How the style is presented

Analysis section

• Includes a justification of the methods used
• Technical explanation

Results section

• Purely descriptive
• Easily explained for the targeted audience
• Data driven

Example of a Results Section

Publication Manual of the American Psychological Association Sixth Ed. 2010

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Analysis is a type of primary research that involves finding and interpreting patterns in data, classifying those patterns, and generalizing the results. It is useful when looking at actions, events, or occurrences in different texts, media, or publications. Analysis can usually be done without considering most of the ethical issues discussed in the overview, as you are not working with people but rather publicly accessible documents. Analysis can be done on new documents or performed on raw data that you yourself have collected.

Here are several examples of analysis:

• Recording commercials on three major television networks and analyzing race and gender within the commercials to discover some conclusion.
• Analyzing the historical trends in public laws by looking at the records at a local courthouse.
• Analyzing topics of discussion in chat rooms for patterns based on gender and age.

Analysis research involves several steps:

• Finding and collecting documents.
• Specifying criteria or patterns that you are looking for.
• Analyzing documents for patterns, noting number of occurrences or other factors.

How to Write the Discussion Section of a Research Paper

The discussion section of a research paper analyzes and interprets the findings, provides context, compares them with previous studies, identifies limitations, and suggests future research directions.

Updated on September 15, 2023

Structure your discussion section right, and you’ll be cited more often while doing a greater service to the scientific community. So, what actually goes into the discussion section? And how do you write it?

The discussion section of your research paper is where you let the reader know how your study is positioned in the literature, what to take away from your paper, and how your work helps them. It can also include your conclusions and suggestions for future studies.

First, we’ll define all the parts of your discussion paper, and then look into how to write a strong, effective discussion section for your paper or manuscript.

Discussion section: what is it, what it does

The discussion section comes later in your paper, following the introduction, methods, and results. The discussion sets up your study’s conclusions. Its main goals are to present, interpret, and provide a context for your results.

What is it?

The discussion section provides an analysis and interpretation of the findings, compares them with previous studies, identifies limitations, and suggests future directions for research.

This section combines information from the preceding parts of your paper into a coherent story. By this point, the reader already knows why you did your study (introduction), how you did it (methods), and what happened (results). In the discussion, you’ll help the reader connect the ideas from these sections.

Why is it necessary?

The discussion provides context and interpretations for the results. It also answers the questions posed in the introduction. While the results section describes your findings, the discussion explains what they say. This is also where you can describe the impact or implications of your research.

Adds context for your results

Most research studies aim to answer a question, replicate a finding, or address limitations in the literature. These goals are first described in the introduction. However, in the discussion section, the author can refer back to them to explain how the study's objective was achieved. 

Shows what your results actually mean and real-world implications

The discussion can also describe the effect of your findings on research or practice. How are your results significant for readers, other researchers, or policymakers?

What to include in your discussion (in the correct order)

A complete and effective discussion section should at least touch on the points described below.

Summary of key findings

The discussion should begin with a brief factual summary of the results. Concisely overview the main results you obtained.

Begin with key findings with supporting evidence

Your results section described a list of findings, but what message do they send when you look at them all together?

Your findings were detailed in the results section, so there’s no need to repeat them here, but do provide at least a few highlights. This will help refresh the reader’s memory and help them focus on the big picture.

Read the first paragraph of the discussion section in this article (PDF) for an example of how to start this part of your paper. Notice how the authors break down their results and follow each description sentence with an explanation of why each finding is relevant. 

State clearly and concisely

Following a clear and direct writing style is especially important in the discussion section. After all, this is where you will make some of the most impactful points in your paper. While the results section often contains technical vocabulary, such as statistical terms, the discussion section lets you describe your findings more clearly. 

Interpretation of results

Once you’ve given your reader an overview of your results, you need to interpret those results. In other words, what do your results mean? Discuss the findings’ implications and significance in relation to your research question or hypothesis.

Analyze and interpret your findings

Look into your findings and explore what’s behind them or what may have caused them. If your introduction cited theories or studies that could explain your findings, use these sources as a basis to discuss your results.

For example, look at the second paragraph in the discussion section of this article on waggling honey bees. Here, the authors explore their results based on information from the literature.

Unexpected or contradictory results

Sometimes, your findings are not what you expect. Here’s where you describe this and try to find a reason for it. Could it be because of the method you used? Does it have something to do with the variables analyzed? Comparing your methods with those of other similar studies can help with this task.

Context and comparison with previous work

Refer to related studies to place your research in a larger context and the literature. Compare and contrast your findings with existing literature, highlighting similarities, differences, and/or contradictions.

How your work compares or contrasts with previous work

Studies with similar findings to yours can be cited to show the strength of your findings. Information from these studies can also be used to help explain your results. Differences between your findings and others in the literature can also be discussed here. 

How to divide this section into subsections

If you have more than one objective in your study or many key findings, you can dedicate a separate section to each of these. Here’s an example of this approach. You can see that the discussion section is divided into topics and even has a separate heading for each of them. 

Limitations

Many journals require you to include the limitations of your study in the discussion. Even if they don’t, there are good reasons to mention these in your paper.

Why limitations don’t have a negative connotation

A study’s limitations are points to be improved upon in future research. While some of these may be flaws in your method, many may be due to factors you couldn’t predict.

Examples include time constraints or small sample sizes. Pointing this out will help future researchers avoid or address these issues. This part of the discussion can also include any attempts you have made to reduce the impact of these limitations, as in this study .

How limitations add to a researcher's credibility

Pointing out the limitations of your study demonstrates transparency. It also shows that you know your methods well and can conduct a critical assessment of them.  

Implications and significance

The final paragraph of the discussion section should contain the take-home messages for your study. It can also cite the “strong points” of your study, to contrast with the limitations section.

Restate your hypothesis

Remind the reader what your hypothesis was before you conducted the study. 

How was it proven or disproven?

Identify your main findings and describe how they relate to your hypothesis.

How your results contribute to the literature

Were you able to answer your research question? Or address a gap in the literature?

Future implications of your research

Describe the impact that your results may have on the topic of study. Your results may show, for instance, that there are still limitations in the literature for future studies to address. There may be a need for studies that extend your findings in a specific way. You also may need additional research to corroborate your findings. 

Sample discussion section

This fictitious example covers all the aspects discussed above. Your actual discussion section will probably be much longer, but you can read this to get an idea of everything your discussion should cover.

Our results showed that the presence of cats in a household is associated with higher levels of perceived happiness by its human occupants. These findings support our hypothesis and demonstrate the association between pet ownership and well-being. 

The present findings align with those of Bao and Schreer (2016) and Hardie et al. (2023), who observed greater life satisfaction in pet owners relative to non-owners. Although the present study did not directly evaluate life satisfaction, this factor may explain the association between happiness and cat ownership observed in our sample.

Our findings must be interpreted in light of some limitations, such as the focus on cat ownership only rather than pets as a whole. This may limit the generalizability of our results.

Nevertheless, this study had several strengths. These include its strict exclusion criteria and use of a standardized assessment instrument to investigate the relationships between pets and owners. These attributes bolster the accuracy of our results and reduce the influence of confounding factors, increasing the strength of our conclusions. Future studies may examine the factors that mediate the association between pet ownership and happiness to better comprehend this phenomenon.

This brief discussion begins with a quick summary of the results and hypothesis. The next paragraph cites previous research and compares its findings to those of this study. Information from previous studies is also used to help interpret the findings. After discussing the results of the study, some limitations are pointed out. The paper also explains why these limitations may influence the interpretation of results. Then, final conclusions are drawn based on the study, and directions for future research are suggested.

How to make your discussion flow naturally

If you find writing in scientific English challenging, the discussion and conclusions are often the hardest parts of the paper to write. That’s because you’re not just listing up studies, methods, and outcomes. You’re actually expressing your thoughts and interpretations in words.

• How formal should it be?
• What words should you use, or not use?
• How do you meet strict word limits, or make it longer and more informative?

Always give it your best, but sometimes a helping hand can, well, help. Getting a professional edit can help clarify your work’s importance while improving the English used to explain it. When readers know the value of your work, they’ll cite it. We’ll assign your study to an expert editor knowledgeable in your area of research. Their work will clarify your discussion, helping it to tell your story. Find out more about AJE Editing.

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• Research guides

Writing an Educational Research Paper

Research paper sections, customary parts of an education research paper.

There is no one right style or manner for writing an education paper. Content aside, the writing style and presentation of papers in different educational fields vary greatly. Nevertheless, certain parts are common to most papers, for example:

Title/Cover Page

Contains the paper's title, the author's name, address, phone number, e-mail, and the day's date.

Not every education paper requires an abstract. However, for longer, more complex papers abstracts are particularly useful. Often only 100 to 300 words, the abstract generally provides a broad overview and is never more than a page. It describes the essence, the main theme of the paper. It includes the research question posed, its significance, the methodology, and the main results or findings. Footnotes or cited works are never listed in an abstract. Remember to take great care in composing the abstract. It's the first part of the paper the instructor reads. It must impress with a strong content, good style, and general aesthetic appeal. Never write it hastily or carelessly.

Introduction and Statement of the Problem

A good introduction states the main research problem and thesis argument. What precisely are you studying and why is it important? How original is it? Will it fill a gap in other studies? Never provide a lengthy justification for your topic before it has been explicitly stated.

Limitations of Study

Indicate as soon as possible what you intend to do, and what you are not going to attempt. You may limit the scope of your paper by any number of factors, for example, time, personnel, gender, age, geographic location, nationality, and so on.

Methodology

Discuss your research methodology. Did you employ qualitative or quantitative research methods? Did you administer a questionnaire or interview people? Any field research conducted? How did you collect data? Did you utilize other libraries or archives? And so on.

Literature Review

The research process uncovers what other writers have written about your topic. Your education paper should include a discussion or review of what is known about the subject and how that knowledge was acquired. Once you provide the general and specific context of the existing knowledge, then you yourself can build on others' research. The guide Writing a Literature Review will be helpful here.

Main Body of Paper/Argument

This is generally the longest part of the paper. It's where the author supports the thesis and builds the argument. It contains most of the citations and analysis. This section should focus on a rational development of the thesis with clear reasoning and solid argumentation at all points. A clear focus, avoiding meaningless digressions, provides the essential unity that characterizes a strong education paper.

After spending a great deal of time and energy introducing and arguing the points in the main body of the paper, the conclusion brings everything together and underscores what it all means. A stimulating and informative conclusion leaves the reader informed and well-satisfied. A conclusion that makes sense, when read independently from the rest of the paper, will win praise.

Works Cited/Bibliography

See the Citation guide .

Education research papers often contain one or more appendices. An appendix contains material that is appropriate for enlarging the reader's understanding, but that does not fit very well into the main body of the paper. Such material might include tables, charts, summaries, questionnaires, interview questions, lengthy statistics, maps, pictures, photographs, lists of terms, glossaries, survey instruments, letters, copies of historical documents, and many other types of supplementary material. A paper may have several appendices. They are usually placed after the main body of the paper but before the bibliography or works cited section. They are usually designated by such headings as Appendix A, Appendix B, and so on.

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• Last Updated: Dec 5, 2023 2:26 PM
• Subjects: Education
• Tags: education , education_paper , education_research_paper

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• Online Guide to Writing

Structuring the Research Paper

Formal research structure.

These are the primary purposes for formal research:

enter the discourse, or conversation, of other writers and scholars in your field

learn how others in your field use primary and secondary resources

find and understand raw data and information

For the formal academic research assignment, consider an organizational pattern typically used for primary academic research.  The pattern includes the following: introduction, methods, results, discussion, and conclusions/recommendations.

Usually, research papers flow from the general to the specific and back to the general in their organization. The introduction uses a general-to-specific movement in its organization, establishing the thesis and setting the context for the conversation. The methods and results sections are more detailed and specific, providing support for the generalizations made in the introduction. The discussion section moves toward an increasingly more general discussion of the subject, leading to the conclusions and recommendations, which then generalize the conversation again.

Sections of a Formal Structure

The introduction section.

Many students will find that writing a structured  introduction  gets them started and gives them the focus needed to significantly improve their entire paper. 

Introductions usually have three parts:

presentation of the problem statement, the topic, or the research inquiry

purpose and focus of your paper

summary or overview of the writer’s position or arguments

In the first part of the introduction—the presentation of the problem or the research inquiry—state the problem or express it so that the question is implied. Then, sketch the background on the problem and review the literature on it to give your readers a context that shows them how your research inquiry fits into the conversation currently ongoing in your subject area. 

In the second part of the introduction, state your purpose and focus. Here, you may even present your actual thesis. Sometimes your purpose statement can take the place of the thesis by letting your reader know your intentions. 

The third part of the introduction, the summary or overview of the paper, briefly leads readers through the discussion, forecasting the main ideas and giving readers a blueprint for the paper. 

The following example provides a blueprint for a well-organized introduction.

Example of an Introduction

Entrepreneurial Marketing: The Critical Difference

In an article in the Harvard Business Review, John A. Welsh and Jerry F. White remind us that “a small business is not a little big business.” An entrepreneur is not a multinational conglomerate but a profit-seeking individual. To survive, he must have a different outlook and must apply different principles to his endeavors than does the president of a large or even medium-sized corporation. Not only does the scale of small and big businesses differ, but small businesses also suffer from what the Harvard Business Review article calls “resource poverty.” This is a problem and opportunity that requires an entirely different approach to marketing. Where large ad budgets are not necessary or feasible, where expensive ad production squanders limited capital, where every marketing dollar must do the work of two dollars, if not five dollars or even ten, where a person’s company, capital, and material well-being are all on the line—that is, where guerrilla marketing can save the day and secure the bottom line (Levinson, 1984, p. 9).

By reviewing the introductions to research articles in the discipline in which you are writing your research paper, you can get an idea of what is considered the norm for that discipline. Study several of these before you begin your paper so that you know what may be expected. If you are unsure of the kind of introduction your paper needs, ask your professor for more information.  The introduction is normally written in present tense.

THE METHODS SECTION

The methods section of your research paper should describe in detail what methodology and special materials if any, you used to think through or perform your research. You should include any materials you used or designed for yourself, such as questionnaires or interview questions, to generate data or information for your research paper. You want to include any methodologies that are specific to your particular field of study, such as lab procedures for a lab experiment or data-gathering instruments for field research. The methods section is usually written in the past tense.

THE RESULTS SECTION

How you present the results of your research depends on what kind of research you did, your subject matter, and your readers’ expectations. 

Quantitative information —data that can be measured—can be presented systematically and economically in tables, charts, and graphs. Quantitative information includes quantities and comparisons of sets of data. 

Qualitative information , which includes brief descriptions, explanations, or instructions, can also be presented in prose tables. This kind of descriptive or explanatory information, however, is often presented in essay-like prose or even lists.

There are specific conventions for creating tables, charts, and graphs and organizing the information they contain. In general, you should use them only when you are sure they will enlighten your readers rather than confuse them. In the accompanying explanation and discussion, always refer to the graphic by number and explain specifically what you are referring to; you can also provide a caption for the graphic. The rule of thumb for presenting a graphic is first to introduce it by name, show it, and then interpret it. The results section is usually written in the past tense.

THE DISCUSSION SECTION

Your discussion section should generalize what you have learned from your research. One way to generalize is to explain the consequences or meaning of your results and then make your points that support and refer back to the statements you made in your introduction. Your discussion should be organized so that it relates directly to your thesis. You want to avoid introducing new ideas here or discussing tangential issues not directly related to the exploration and discovery of your thesis. The discussion section, along with the introduction, is usually written in the present tense.

THE CONCLUSIONS AND RECOMMENDATIONS SECTION

Your conclusion ties your research to your thesis, binding together all the main ideas in your thinking and writing. By presenting the logical outcome of your research and thinking, your conclusion answers your research inquiry for your reader. Your conclusions should relate directly to the ideas presented in your introduction section and should not present any new ideas.

You may be asked to present your recommendations separately in your research assignment. If so, you will want to add some elements to your conclusion section. For example, you may be asked to recommend a course of action, make a prediction, propose a solution to a problem, offer a judgment, or speculate on the implications and consequences of your ideas. The conclusions and recommendations section is usually written in the present tense.

Key Takeaways

• For the formal academic research assignment, consider an organizational pattern typically used for primary academic research. 
•  The pattern includes the following: introduction, methods, results, discussion, and conclusions/recommendations.

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Table of Contents: Online Guide to Writing

Chapter 1: College Writing

How Does College Writing Differ from Workplace Writing?

What Is College Writing?

Why So Much Emphasis on Writing?

Chapter 2: The Writing Process

Doing Exploratory Research

Getting from Notes to Your Draft

Introduction

Prewriting - Techniques to Get Started - Mining Your Intuition

Prewriting: Targeting Your Audience

Prewriting: Techniques to Get Started

Prewriting: Understanding Your Assignment

Rewriting: Being Your Own Critic

Rewriting: Creating a Revision Strategy

Rewriting: Getting Feedback

Rewriting: The Final Draft

Techniques to Get Started - Outlining

Techniques to Get Started - Using Systematic Techniques

Thesis Statement and Controlling Idea

Writing: Getting from Notes to Your Draft - Freewriting

Writing: Getting from Notes to Your Draft - Summarizing Your Ideas

Writing: Outlining What You Will Write

Chapter 3: Thinking Strategies

A Word About Style, Voice, and Tone

A Word About Style, Voice, and Tone: Style Through Vocabulary and Diction

Critical Strategies and Writing

Critical Strategies and Writing: Analysis

Critical Strategies and Writing: Evaluation

Critical Strategies and Writing: Persuasion

Critical Strategies and Writing: Synthesis

Developing a Paper Using Strategies

Kinds of Assignments You Will Write

Patterns for Presenting Information

Patterns for Presenting Information: Critiques

Patterns for Presenting Information: Discussing Raw Data

Patterns for Presenting Information: General-to-Specific Pattern

Patterns for Presenting Information: Problem-Cause-Solution Pattern

Patterns for Presenting Information: Specific-to-General Pattern

Patterns for Presenting Information: Summaries and Abstracts

Supporting with Research and Examples

Writing Essay Examinations

Writing Essay Examinations: Make Your Answer Relevant and Complete

Writing Essay Examinations: Organize Thinking Before Writing

Writing Essay Examinations: Read and Understand the Question

Chapter 4: The Research Process

Planning and Writing a Research Paper

Planning and Writing a Research Paper: Ask a Research Question

Planning and Writing a Research Paper: Cite Sources

Planning and Writing a Research Paper: Collect Evidence

Planning and Writing a Research Paper: Decide Your Point of View, or Role, for Your Research

Planning and Writing a Research Paper: Draw Conclusions

Planning and Writing a Research Paper: Find a Topic and Get an Overview

Planning and Writing a Research Paper: Manage Your Resources

Planning and Writing a Research Paper: Outline

Planning and Writing a Research Paper: Survey the Literature

Planning and Writing a Research Paper: Work Your Sources into Your Research Writing

Research Resources: Where Are Research Resources Found? - Human Resources

Research Resources: What Are Research Resources?

Research Resources: Where Are Research Resources Found?

Research Resources: Where Are Research Resources Found? - Electronic Resources

Research Resources: Where Are Research Resources Found? - Print Resources

Structuring the Research Paper: Formal Research Structure

Structuring the Research Paper: Informal Research Structure

The Nature of Research

The Research Assignment: How Should Research Sources Be Evaluated?

The Research Assignment: When Is Research Needed?

The Research Assignment: Why Perform Research?

Chapter 5: Academic Integrity

Academic Integrity

Giving Credit to Sources

Giving Credit to Sources: Copyright Laws

Giving Credit to Sources: Documentation

Giving Credit to Sources: Style Guides

Integrating Sources

Practicing Academic Integrity

Practicing Academic Integrity: Keeping Accurate Records

Practicing Academic Integrity: Managing Source Material

Practicing Academic Integrity: Managing Source Material - Paraphrasing Your Source

Practicing Academic Integrity: Managing Source Material - Quoting Your Source

Practicing Academic Integrity: Managing Source Material - Summarizing Your Sources

Types of Documentation

Types of Documentation: Bibliographies and Source Lists

Types of Documentation: Citing World Wide Web Sources

Types of Documentation: In-Text or Parenthetical Citations

Types of Documentation: In-Text or Parenthetical Citations - APA Style

Types of Documentation: In-Text or Parenthetical Citations - CSE/CBE Style

Types of Documentation: In-Text or Parenthetical Citations - Chicago Style

Types of Documentation: In-Text or Parenthetical Citations - MLA Style

Types of Documentation: Note Citations

Chapter 6: Using Library Resources

Finding Library Resources

Chapter 7: Assessing Your Writing

How Is Writing Graded?

How Is Writing Graded?: A General Assessment Tool

The Draft Stage

The Draft Stage: The First Draft

The Draft Stage: The Revision Process and the Final Draft

The Draft Stage: Using Feedback

The Research Stage

Using Assessment to Improve Your Writing

Chapter 8: Other Frequently Assigned Papers

Reviews and Reaction Papers: Article and Book Reviews

Reviews and Reaction Papers: Reaction Papers

Writing Arguments

Writing Arguments: Adapting the Argument Structure

Writing Arguments: Purposes of Argument

Writing Arguments: References to Consult for Writing Arguments

Writing Arguments: Steps to Writing an Argument - Anticipate Active Opposition

Writing Arguments: Steps to Writing an Argument - Determine Your Organization

Writing Arguments: Steps to Writing an Argument - Develop Your Argument

Writing Arguments: Steps to Writing an Argument - Introduce Your Argument

Writing Arguments: Steps to Writing an Argument - State Your Thesis or Proposition

Writing Arguments: Steps to Writing an Argument - Write Your Conclusion

Writing Arguments: Types of Argument

Appendix A: Books to Help Improve Your Writing

Dictionaries

General Style Manuals

Researching on the Internet

Special Style Manuals

Writing Handbooks

Appendix B: Collaborative Writing and Peer Reviewing

Collaborative Writing: Assignments to Accompany the Group Project

Collaborative Writing: Informal Progress Report

Collaborative Writing: Issues to Resolve

Collaborative Writing: Methodology

Collaborative Writing: Peer Evaluation

Collaborative Writing: Tasks of Collaborative Writing Group Members

Collaborative Writing: Writing Plan

General Introduction

Peer Reviewing

Appendix C: Developing an Improvement Plan

Working with Your Instructor’s Comments and Grades

Appendix D: Writing Plan and Project Schedule

Devising a Writing Project Plan and Schedule

Reviewing Your Plan with Others

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Research Tips and Infromation

07 Easy Steps for Writing Discussion Section of a Research Paper

In my role as a journal reviewer, I’ve had the privilege (and sometimes the frustration) of reviewing numerous research papers.

I’ve encountered papers where authors neglect to discuss how their results benefit the problem at hand, the domain they are working in, and society at large. This oversight often fails to make a lasting impression on reviewers

One recurring issue that I’ve noticed, time and again, is the challenge of properly delineating the boundaries of the discussion section in research papers. It’s not uncommon to come across papers where authors blur the lines between various crucial sections in a research paper.

Some authors mistakenly present their results within the discussion section, failing to provide a clear delineation between the findings of their study and their interpretation. Even if the journal allows to combine the results and discussion section, adopting a structured approach, such as dedicating a paragraph for results and a paragraph for discussing the results, can enhance the flow and readability of the paper, ensuring that readers can easily follow the progression of the study and its implications.

I vividly recall one instance where an author proceeded to rehash the entire methodology, complete with block diagrams, within the discussion section—without ever drawing any substantive conclusions. It felt like wading through familiar territory, only to find myself back at square one.

And then there are those authors who seem more interested in speculating about future directions than analyzing the outcomes of their current work in the discussion section. While it’s important to consider the implications of one’s research, it shouldn’t overshadow the critical analysis of the results at hand.

In another instance, a researcher concealed all failures or limitations in their work, presenting only the best-case scenarios, which created doubts about the validity of their findings. As a reviewer, I promptly sent it back for a relook and suggested adding various scenarios to reflect the true behaviour of the experiment.

In this post, I’ll delve into practical strategies for crafting the discussion section of a research paper. Drawing from my experiences as a reviewer and researcher, I’ll explore the nuances of the discussion section and provide insights into how to engage in critical discussion.

Introduction

I. focus on the relevance.

• II. Highlight  the Limitations 
• III. Introduce  New Discoveries

IV. Highlight the Observations

V. compare and relate with other research works.

• VI. Provide  Alternate View Points

A. Future Directions

B. conclusion, how to validate the claims i made in the discussion section of my research paper, phrases that can be used in the discussion section of a research paper, phrases that can be used in the analysis part of the discussion section of a research paper.

• Your Next Move...

Whether charts and graphs are allowed in discussion section of my Research Paper?

Can i add citations in discussion section of my research paper, can i combine results and discussion section in my research paper, what is the weightage of discussion section in a research paper in terms of selection to a journal, whether literature survey paper has a discussion section.

The Discussion section of a research paper is where authors interpret their findings, contextualize their research, and propose future directions. It is a crucial section that provides the reader with insights into the significance and implications of the study.

Writing an effective discussion section is a crucial aspect of any research paper, as it allows researchers to delve into the significance of their findings and explore their implications. A well-crafted discussion section not only summarizes the key observations and limitations of the study but also establishes connections with existing research and opens avenues for future exploration. In this article, we will present a comprehensive guide to help you structure your discussion section in seven simple steps.

By following these steps, you’ll be able to write a compelling Discussion section that enhances the reader’s understanding of your research and contributes to the broader scientific community.

Please note, the discussion section usually follows after the Results Section. I have written a comprehensive article on ” How to Write Results Section of your Research Paper “. Please visit the article to enhance your write-up on the results section.

Which are these 07 steps for writing an Effective Discussion Section of a Research Paper?

Step 1: Focus on the Relevance : In the first step, we will discuss the importance of emphasizing the relevance of your research findings to the broader scientific context. By clearly articulating the significance of your study, you can help readers understand how your work contributes to the existing body of knowledge and why it matters.

Step 2: Highlight the Limitations : Every research study has its limitations, and it is essential to address them honestly and transparently. We will explore how to identify and describe the limitations of your study, demonstrating a thorough understanding of potential weaknesses and areas for improvement.

Step 3: Highlight the Observations : In this step, we will delve into the core findings of your study. We will discuss the key observations and results, focusing on their relevance to your research objectives. By providing a concise summary of your findings, you can guide readers through the main outcomes of your study.

Step 4: Compare and Relate with Other Research Works : Research is a collaborative and cumulative process, and it is vital to establish connections between your study and previous research. We will explore strategies to compare and relate your findings to existing literature, highlighting similarities, differences, and gaps in knowledge.

Step 5: Provide Alternate Viewpoints: Science thrives on the diversity of perspectives. Acknowledging different viewpoints and interpretations of your results fosters a more comprehensive understanding of the research topic. We will discuss how to incorporate alternative viewpoints into your discussion, encouraging a balanced and nuanced analysis.

Step 6: Show Future Directions : A well-crafted discussion section not only summarizes the present but also points towards the future. We will explore techniques to suggest future research directions based on the implications of your study, providing a roadmap for further investigations in the field.

Step 7: Concluding Thoughts : In the final step, we will wrap up the discussion section by summarizing the key points and emphasizing the overall implications of your research. We will discuss the significance of your study’s contributions and offer some closing thoughts to leave a lasting impression on your readers.

By following these seven steps, you can craft a comprehensive and insightful discussion section that not only synthesizes your findings but also engages readers in a thought-provoking dialogue about the broader implications and future directions of your research. Let’s delve into each step in detail to enhance the quality and impact of your discussion section.

The purpose of every research is to implement the results for the positive development of the relevant subject. In research, it is crucial to emphasize the relevance of your study to the field and its potential impact. Before delving into the details of how the research was conceived and the sequence of developments that took place, consider highlighting the following factors to establish the relevance of your work:

• Identifying a pressing problem or research gap: Example: “This research addresses the critical problem of network security in wireless communication systems. With the widespread adoption of wireless networks, the vulnerability to security threats has increased significantly. Existing security mechanisms have limitations in effectively mitigating these threats. Therefore, there is a pressing need to develop novel approaches that enhance the security of wireless communication systems.”
• Explaining the significance and potential impact of the research: Example: “By developing an intelligent intrusion detection system using machine learning algorithms, this research aims to significantly enhance the security of wireless networks. The successful implementation of such a system would not only protect sensitive data and communication but also ensure the reliability and integrity of wireless networks in various applications, including Internet of Things (IoT), smart cities, and critical infrastructure.”
• Establishing connections with previous research and advancements in the field: Example: “This study builds upon previous research on intrusion detection systems and machine learning techniques. By leveraging recent advancements in deep learning algorithms and anomaly detection methods, we aim to overcome the limitations of traditional rule-based intrusion detection systems and achieve higher detection accuracy and efficiency.”

By emphasizing the relevance of your research and articulating its potential impact, you set the stage for readers to understand the significance of your work in the broader context. This approach ensures that readers grasp the motivations behind your research and the need for further exploration in the field.

II. Highlight  the Limitations 

Many times the research is on a subject that might have legal limitations or restrictions. This limitation might have caused certain imperfections in carrying out research or in results. This issue should be acknowledged by the researcher before the work is criticized by others later in his/her discussion section.

In computer science research, it is important to identify and openly acknowledge the limitations of your study. By doing so, you demonstrate transparency and a thorough understanding of potential weaknesses, allowing readers to interpret the findings in a more informed manner. Here’s an example:

Example: “It is crucial to acknowledge certain limitations and constraints that have affected the outcomes of this research. In the context of privacy-sensitive applications such as facial recognition systems, there are legal limitations and ethical concerns that can impact the accuracy and performance of the developed algorithm. These limitations stem from regulations and policies that impose restrictions on data collection, access, and usage to protect individuals’ privacy rights. As a result, the algorithm developed in this study operates under these legal constraints, which may have introduced certain imperfections.”

In this example, the researcher is working on a facial recognition system and acknowledges the legal limitations and ethical concerns associated with privacy-sensitive applications. By openly addressing these limitations, the researcher demonstrates an understanding of the challenges imposed by regulations and policies. This acknowledgement sets the stage for a more nuanced discussion and prevents others from solely criticizing the work based on these limitations without considering the broader legal context.

By highlighting the limitations, researchers can also offer potential solutions or future directions to mitigate the impact of these constraints. For instance, the researcher may suggest exploring advanced privacy-preserving techniques or collaborating with legal experts to find a balance between privacy protection and system performance.

By acknowledging and addressing the limitations, researchers demonstrate their awareness of potential weaknesses in their study, maintaining credibility, and fostering a more constructive discussion of their findings within the context of legal and ethical considerations.

III. Introduce  New Discoveries

Begin the discussion section by stating all the major findings in the course of the research. The first paragraph should have the findings mentioned, which is expected to be synoptic, naming and briefly describing the analysis of results.

Example: “In this study, several significant discoveries emerged from the analysis of the collected data. The findings revealed compelling insights into the performance of parallel computing architectures for large-scale data processing. Through comprehensive experimentation and analysis, the following key discoveries were made:

• Discovery 1: The proposed parallel computing architecture demonstrated a 30% improvement in processing speed compared to traditional sequential computing methods. This finding highlights the potential of parallel computing for accelerating data-intensive tasks.
• Discovery 2: A direct relationship between the number of processing cores and the overall system throughput was observed. As the number of cores increased, the system exhibited a near-linear scalability, enabling efficient utilization of available computational resources.
• Discovery 3: The analysis revealed a trade-off between processing speed and energy consumption. While parallel computing achieved faster processing times, it also resulted in higher energy consumption. This finding emphasizes the importance of optimizing energy efficiency in parallel computing systems.

These discoveries shed light on the performance characteristics and trade-offs associated with parallel computing architectures for large-scale data processing tasks. The following sections will delve into the implications of these findings, discussing their significance, limitations, and potential applications.”

In this example, the researcher presents a concise overview of the major discoveries made during the research. Each discovery is briefly described, highlighting the key insights obtained from the analysis. By summarizing the findings in a synoptic manner, the reader gains an immediate understanding of the notable contributions and can anticipate the subsequent detailed discussion.

This approach allows the discussion section to begin with a clear and impactful introduction of the major discoveries, capturing the reader’s interest and setting the stage for a comprehensive exploration of each finding in subsequent paragraphs.

Coming to the major part of the findings, the discussion section should interpret the key observations, the analysis of charts, and the analysis of tables. In the field of computer science, presenting and explaining the results in a clear and accessible manner is essential for readers to grasp the significance of the findings. Here are some examples of how to effectively highlight observations in computer science research:

Begin with explaining the objective of the research, followed by what inspired you as a researcher to study the subject:

In a study on machine learning algorithms for sentiment analysis, start by stating the goal of developing an accurate and efficient sentiment analysis model. Share your motivation for choosing this research topic, such as the increasing importance of sentiment analysis in various domains like social media, customer feedback analysis, and market research.

Example: The objective of this research was to develop a sentiment analysis model using machine learning algorithms. As sentiment analysis plays a vital role in understanding public opinion and customer feedback, we were motivated by the need for an accurate and efficient model that could be applied in various domains such as social media analysis, customer reviews, and market research.

Explain the meaning of the findings, as every reader might not understand the analysis of graphs and charts as easily as people who are in the same field as you:

If your research involves analyzing performance metrics of different algorithms, consider presenting the results in a visually intuitive manner, such as line graphs or bar charts. In the discussion section, explain the significance of the trends observed in the graphs. For instance, if a particular algorithm consistently outperforms others in terms of accuracy, explain why this finding is noteworthy and how it aligns with existing knowledge in the field.

Example: To present the performance evaluation of the algorithms, we analyzed multiple metrics, including precision, recall, and F1 score. The line graph in Figure 1 demonstrates the trends observed. It is noteworthy that Algorithm A consistently outperformed the other algorithms across all metrics. This finding indicates that Algorithm A has a higher ability to accurately classify sentiment in comparison to its counterparts. This aligns with previous studies that have also highlighted the robustness of Algorithm A in sentiment analysis tasks.

Ensure the reader can understand the key observations without being forced to go through the whole paper:

In computer science research, it is crucial to present concise summaries of your key observations to facilitate understanding for readers who may not have the time or expertise to go through the entire paper. For example, if your study compares the runtime performance of two programming languages for a specific task, clearly state the observed differences and their implications. Highlight any unexpected or notable findings that may challenge conventional wisdom or open up new avenues for future exploration.

Example: In this study comparing the runtime performance of Python and Java for a specific computational task, we observed notable differences. Python consistently showed faster execution times, averaging 20% less time than Java across varying input sizes. These results challenge the common perception that Java is the superior choice for computationally intensive tasks. The observed performance advantage of Python in this context suggests the need for further investigation into the underlying factors contributing to this discrepancy, such as differences in language design and optimization strategies.

By employing these strategies, researchers can effectively highlight their observations in the discussion section. This enables readers to gain a clear understanding of the significance of the findings and their implications without having to delve into complex technical details.

No one is ever the only person researching a particular subject. A researcher always has companions and competitors. The discussion section should have a detailed comparison of the research. It should present the facts that relate the research to studies done on the same subject.

Example: The table below compares some of the well-known prediction techniques with our fuzzy predictor with MOM defuzzification for response time, relative error and Environmental constraints. Based on the results obtained it can be concluded that the Fuzzy predictor with MOM defuzzification has a less relative error and quick response time as compared to other prediction techniques.  The proposed predictor is more flexible, simple to implement and deals with noisy and uncertain data from real-life situations. The relative error of 5-10% is acceptable for our system as the predicted fuzzy region and the fuzzy region of the actual position remains the same.

Table 1 : Comparison of well-known Robot Motion prediction Techniques

VI. Provide  Alternate View Points

Almost every time, it has been noticed that analysis of charts and graphs shows results that tend to have more than one explanation. The researcher must consider every possible explanation and potential enhancement of the study from alternative viewpoints. It is critically important that this is clearly put out to the readers in the discussion section.

In the discussion section of a research paper, it is important to acknowledge that data analysis often yields results that can be interpreted in multiple ways. By considering different viewpoints and potential enhancements, researchers can provide a more comprehensive and nuanced analysis of their findings. Here are some examples:

Example 1: “The analysis of our experimental data showed a decrease in system performance following the implementation of the proposed optimization technique. While our initial interpretation suggested that the optimization failed to achieve the desired outcome, an alternate viewpoint could be that the decrease in performance was influenced by an external factor, such as the configuration of the hardware setup. Further investigation into the hardware settings and benchmarking protocols is necessary to fully understand the observed results and identify potential enhancements.”

Example 2: “The analysis of user feedback revealed a mixed response to the redesigned user interface. While some participants reported improved usability and satisfaction, others expressed confusion and dissatisfaction. An alternate viewpoint could be that the diverse range of user backgrounds and preferences might have influenced these varied responses. Further research should focus on conducting user studies with a larger and more diverse sample to gain a deeper understanding of the underlying factors contributing to the contrasting user experiences.”

Example 3: “Our study found a positive correlation between the implementation of agile methodologies and project success rates. However, an alternate viewpoint suggests that other factors, such as team dynamics and project complexity, could have influenced the observed correlation. Future research should explore the interactions between agile methodologies and these potential confounding factors to gain a more comprehensive understanding of their impact on project success.”

In these examples, researchers present alternative viewpoints that offer different interpretations or explanations for the observed results. By acknowledging these alternate viewpoints, researchers demonstrate a balanced and comprehensive analysis of their findings. It is crucial to clearly communicate these alternative perspectives to readers in the discussion section, as it encourages critical thinking and highlights the complexity and potential limitations of the research.

By presenting alternate viewpoints, researchers invite further exploration and discussion, fostering a more comprehensive understanding of the research topic. This approach enriches the scientific discourse and promotes a deeper analysis of the findings, contributing to the overall advancement of knowledge in the field.

VII. Future Directions and Conclusion

The section must have suggestions for research that should be done to unanswered questions. These should be suggested at the beginning of the discussion section to avoid questions being asked by critics. Emphasizing the importance of following future directions can lead to new research as well.

Example: ” While this study provides valuable insights into the performance of the proposed algorithm, there are several unanswered questions and avenues for future research that merit attention. By identifying these areas, we aim to stimulate further exploration and contribute to the continuous advancement of the field. The following future directions are suggested:

• Future Direction 1: Investigating the algorithm’s performance under different dataset characteristics and distributions. The current study focused on a specific dataset, but it would be valuable to evaluate the algorithm’s robustness and generalizability across a broader range of datasets, including real-world scenarios and diverse data sources.
• Future Direction 2: Exploring the potential integration of additional machine learning techniques or ensemble methods to further enhance the algorithm’s accuracy and reliability. By combining the strengths of multiple models, it is possible to achieve better performance and handle complex patterns and outliers more effectively.
• Future Direction 3: Extending the evaluation to consider the algorithm’s scalability in large-scale deployment scenarios. As the volume of data continues to grow exponentially, it is crucial to assess the algorithm’s efficiency and scalability in handling big data processing requirements.

By suggesting these future directions, we hope to inspire researchers to explore new avenues and build upon the foundation laid by this study. Addressing these unanswered questions will contribute to a more comprehensive understanding of the algorithm’s capabilities and limitations, paving the way for further advancements in the field.”

In this example, the researcher presents specific future directions that can guide further research. Each future direction is described concisely, highlighting the specific area of investigation and the potential benefits of pursuing those directions. By suggesting these future directions early in the discussion section, the researcher proactively addresses potential questions or criticisms and demonstrates a proactive approach to knowledge expansion.

By emphasizing the importance of following future directions, researchers not only inspire others to continue the research trajectory but also contribute to the collective growth of the field. This approach encourages ongoing exploration, innovation, and collaboration, ensuring the continuous development and improvement of computer science research.

In the final step, wrap up the discussion section by summarizing the key points and emphasizing the overall implications of your research. We will discuss the significance of your study’s contributions and offer some closing thoughts to leave a lasting impression on your readers. This section serves as a crucial opportunity to reinforce the main findings and highlight the broader impact of your work. Here are some examples:

Example 1: “In conclusion, this research has made significant contributions to the field of natural language processing. By proposing a novel neural network architecture for language generation, we have demonstrated the effectiveness and versatility of the model in generating coherent and contextually relevant sentences. The experimental results indicate a significant improvement in language generation quality compared to existing approaches. The implications of this research extend beyond traditional applications, opening up new possibilities for automated content creation, chatbot systems, and dialogue generation in artificial intelligence.”

Example 2: “In summary, this study has provided valuable insights into the optimization of network routing protocols for wireless sensor networks. By proposing a novel hybrid routing algorithm that combines the advantages of both reactive and proactive protocols, we have demonstrated enhanced network performance in terms of latency, energy efficiency, and scalability. The experimental results validate the effectiveness of the proposed algorithm in dynamic and resource-constrained environments. These findings have implications for various applications, including environmental monitoring, industrial automation, and smart city infrastructure.”

Example 3: “In closing, this research sheds light on the security vulnerabilities of blockchain-based smart contracts. By conducting an extensive analysis of existing smart contract platforms and identifying potential attack vectors, we have highlighted the need for robust security measures to mitigate risks and protect user assets. The insights gained from this study can guide the development of more secure and reliable smart contract frameworks, ensuring the integrity and trustworthiness of blockchain-based applications across industries such as finance, supply chain, and decentralized applications.”

In these examples, the concluding thoughts summarize the main contributions and findings of the research. They emphasize the significance of the study’s implications and highlight the potential impact on various domains within computer science. By providing a succinct and impactful summary, the researcher leaves a lasting impression on readers, reinforcing the value and relevance of the research in the field.

Validating claims in the discussion section of a research paper is essential to ensure the credibility and reliability of your findings. Here are some strategies to validate the claims made in the discussion section:

• Referencing supporting evidence: Cite relevant sources from the existing literature that provide evidence or support for your claims. These sources can include peer-reviewed studies, research articles, and authoritative sources in your field. By referencing credible and reputable sources, you establish the validity of your claims and demonstrate that your interpretations are grounded in existing knowledge.
• Relating to the results: Connect your claims to the results presented in the earlier sections of your research paper. Clearly demonstrate how the findings support your claims and provide evidence for your interpretations. Refer to specific data, measurements, statistical analyses, or other evidence from your results section to substantiate your claims.
• Comparing with previous research: Discuss how your findings align with or diverge from previous research in the field. Reference relevant studies and explain how your results compare to or build upon existing knowledge. By contextualizing your claims within the broader research landscape, you provide further validation for your interpretations.
• Addressing limitations and alternative explanations: Acknowledge the limitations of your study and consider alternative explanations for your findings. By addressing potential counterarguments and alternative viewpoints, you demonstrate a thorough evaluation of your claims and increase the robustness of your conclusions.
• Seeking peer feedback: Prior to submitting your research paper, consider seeking feedback from colleagues or experts in your field. They can provide valuable insights and suggestions for further validating your claims or improving the clarity of your arguments.
• Inviting replication and further research: Encourage other researchers to replicate your study or conduct further investigations. By promoting replication and future research, you contribute to the ongoing validation and refinement of your claims.

Remember, the validation of claims in the discussion section is a critical aspect of scientific research. By employing rigorous methods and logical reasoning, you can strengthen the credibility and impact of your findings and contribute to the advancement of knowledge in your field.

Here are some common phrases that can be used in the discussion section of a paper or research article. I’ve included a table with examples to illustrate how these phrases might be used:

Here are some common academic phrases that can be used in the analysis section of a paper or research article. I have included a table with examples to illustrate how these phrases might be used:

Your Next Move…

I believe you will proceed to write conclusion section of your research paper. Conclusion section is the most neglected part of the research paper as many authors feel it is unnecessary but write in a hurry to submit the article to some reputed journal.

Please note, once your paper gets published , the readers decide to read your full paper based only on abstract and conclusion. They decide the relevance of the paper based on only these two sections. If they don’t read then they don’t cite and this in turn affects your citation score. So my sincere advice to you is not to neglect this section.

Visit my article on “How to Write Conclusion Section of Research Paper” for further details.

Please visit my article on “ Importance and Improving of Citation Score for Your Research Paper ” for increasing your visibility in research community and on Google Scholar Citation Score.

The Discussion section of a research paper is an essential part of any study, as it allows the author to interpret their results and contextualize their findings. To write an effective Discussion section, authors should focus on the relevance of their research, highlight the limitations, introduce new discoveries, highlight their observations, compare and relate their findings to other research works, provide alternate viewpoints, and show future directions.

By following these 7 steps, authors can ensure that their Discussion section is comprehensive, informative, and thought-provoking. A well-written Discussion section not only helps the author interpret their results but also provides insights into the implications and applications of their research.

In conclusion, the Discussion section is an integral part of any research paper, and by following these 7 steps, authors can write a compelling and informative discussion section that contributes to the broader scientific community.

Frequently Asked Questions

Yes, charts and graphs are generally allowed in the discussion section of a research paper. While the discussion section is primarily focused on interpreting and discussing the findings, incorporating visual aids such as charts and graphs can be helpful in presenting and supporting the analysis.

Yes, you can add citations in the discussion section of your research paper. In fact, it is highly recommended to support your statements, interpretations, and claims with relevant and credible sources. Citations in the discussion section help to strengthen the validity and reliability of your arguments and demonstrate that your findings are grounded in existing literature.

Combining the results and discussion sections in a research paper is a common practice in certain disciplines, particularly in shorter research papers or those with specific formatting requirements. This approach can help streamline the presentation of your findings and provide a more cohesive narrative. However, it is important to note that the decision to combine these sections should be based on the guidelines of the target journal or publication and the specific requirements of your field.

The weightage of the discussion section in terms of the selection of a research paper for publication in a journal can vary depending on the specific requirements and criteria of the journal. However, it is important to note that the discussion section is a critical component of a research paper as it allows researchers to interpret their findings, contextualize them within the existing literature, and discuss their implications.

In general, literature survey papers typically do not have a separate section explicitly labeled as “Discussion.” However, the content of a literature survey paper often incorporates elements of discussion throughout the paper. The focus of a literature survey paper is to review and summarize existing literature on a specific topic or research question, rather than presenting original research findings.

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How To Write An Analysis Section Of An Academic Paper

The analysis section of an academic essay is extremely important. In this section, you main thoughts and ideas will come out in regards to the research that you have conducted for your work. In this article, we will discuss how to properly write an analysis section that ensures that your work receives much praise amongst your fellow academics.

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Academic Essays

Before we get onto the analysis section, we must take a quick look at academic papers. Academic papers are unlike any other types of essays you may have come across during college. For science students, they come across as a particular shock since they do not have much essay writing experience during college. Nevertheless, it is not impossible to become acquainted with the structure of an academic essay, and to write one to a high standard even if you have little essay writing experience.

To truly understand the analysis section of an academic paper, we must see the role it plays in your writing. As you probably already know, the structure of an academic piece of writing is as follows:

• Introduction: the introduction of your paper should tell the reader what they will be reading about during the course of your writing. You will also make your thesis statement in the introduction.
• Literature Review: In the literature review, you go through the previous research that has been conducted on the topic you are writing about.
• Methodology: The methodology discusses and analyzes the methods you will undertake for your paper.
• Results: The results section tells the reader the results of your research.
• Analysis: This is the section that we are concerned with. Here, you will analyze the results of the previous part of your paper.
• Conclusion: The conclusion should provide the reader with a summary of your results and analysis, telling the reader the overall result as well as whether or not your thesis statement has been met as a result of your research.

Once you know the structure of an academic essay, we can move on to discussing the analysis part of the paper.

As can be seen above, the analysis section of an academic essay is concerned with analyzing the results you have achieved through your research. The analysis should aim to answer questions such as:

• What do these results show?
• What are the possible consequences of these results?
• Has my thesis statement been satisfied by my research? If not, why not?
• How could these results be different if the methodology was adjusted?

The main purpose of the analysis is to see whether or not the thesis statement you made in your introduction has been satisfied. The pivotal part of your essay is the thesis statement, and so it is worth analyzing this in depth to ensure a high mark for your work.

As you can see, many students have a lot of misconceptions about the analysis part of an academic paper. However, by utilizing our guide, you can compose a high quality analysis section that will bring you a lot of success.

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• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

Definition and Introduction

Journal article analysis assignments require you to summarize and critically assess the quality of an empirical research study published in a scholarly [a.k.a., academic, peer-reviewed] journal. The article may be assigned by the professor, chosen from course readings listed in the syllabus, or you must locate an article on your own, usually with the requirement that you search using a reputable library database, such as, JSTOR or ProQuest . The article chosen is expected to relate to the overall discipline of the course, specific course content, or key concepts discussed in class. In some cases, the purpose of the assignment is to analyze an article that is part of the literature review for a future research project.

Analysis of an article can be assigned to students individually or as part of a small group project. The final product is usually in the form of a short paper [typically 1- 6 double-spaced pages] that addresses key questions the professor uses to guide your analysis or that assesses specific parts of a scholarly research study [e.g., the research problem, methodology, discussion, conclusions or findings]. The analysis paper may be shared on a digital course management platform and/or presented to the class for the purpose of promoting a wider discussion about the topic of the study. Although assigned in any level of undergraduate and graduate coursework in the social and behavioral sciences, professors frequently include this assignment in upper division courses to help students learn how to effectively identify, read, and analyze empirical research within their major.

Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students make the most of Scholarly Articles." Library Management 33 (2012): 525-535.

Benefits of Journal Article Analysis Assignments

Analyzing and synthesizing a scholarly journal article is intended to help students obtain the reading and critical thinking skills needed to develop and write their own research papers. This assignment also supports workplace skills where you could be asked to summarize a report or other type of document and report it, for example, during a staff meeting or for a presentation.

There are two broadly defined ways that analyzing a scholarly journal article supports student learning:

Improve Reading Skills

Conducting research requires an ability to review, evaluate, and synthesize prior research studies. Reading prior research requires an understanding of the academic writing style , the type of epistemological beliefs or practices underpinning the research design, and the specific vocabulary and technical terminology [i.e., jargon] used within a discipline. Reading scholarly articles is important because academic writing is unfamiliar to most students; they have had limited exposure to using peer-reviewed journal articles prior to entering college or students have yet to gain exposure to the specific academic writing style of their disciplinary major. Learning how to read scholarly articles also requires careful and deliberate concentration on how authors use specific language and phrasing to convey their research, the problem it addresses, its relationship to prior research, its significance, its limitations, and how authors connect methods of data gathering to the results so as to develop recommended solutions derived from the overall research process.

Improve Comprehension Skills

In addition to knowing how to read scholarly journals articles, students must learn how to effectively interpret what the scholar(s) are trying to convey. Academic writing can be dense, multi-layered, and non-linear in how information is presented. In addition, scholarly articles contain footnotes or endnotes, references to sources, multiple appendices, and, in some cases, non-textual elements [e.g., graphs, charts] that can break-up the reader’s experience with the narrative flow of the study. Analyzing articles helps students practice comprehending these elements of writing, critiquing the arguments being made, reflecting upon the significance of the research, and how it relates to building new knowledge and understanding or applying new approaches to practice. Comprehending scholarly writing also involves thinking critically about where you fit within the overall dialogue among scholars concerning the research problem, finding possible gaps in the research that require further analysis, or identifying where the author(s) has failed to examine fully any specific elements of the study.

In addition, journal article analysis assignments are used by professors to strengthen discipline-specific information literacy skills, either alone or in relation to other tasks, such as, giving a class presentation or participating in a group project. These benefits can include the ability to:

• Effectively paraphrase text, which leads to a more thorough understanding of the overall study;
• Identify and describe strengths and weaknesses of the study and their implications;
• Relate the article to other course readings and in relation to particular research concepts or ideas discussed during class;
• Think critically about the research and summarize complex ideas contained within;
• Plan, organize, and write an effective inquiry-based paper that investigates a research study, evaluates evidence, expounds on the author’s main ideas, and presents an argument concerning the significance and impact of the research in a clear and concise manner;
• Model the type of source summary and critique you should do for any college-level research paper; and,
• Increase interest and engagement with the research problem of the study as well as with the discipline.

Kershaw, Trina C., Jennifer Fugate, and Aminda J. O'Hare. "Teaching Undergraduates to Understand Published Research through Structured Practice in Identifying Key Research Concepts." Scholarship of Teaching and Learning in Psychology . Advance online publication, 2020; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students make the most of Scholarly Articles." Library Management 33 (2012): 525-535; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946.

Structure and Organization

A journal article analysis paper should be written in paragraph format and include an instruction to the study, your analysis of the research, and a conclusion that provides an overall assessment of the author's work, along with an explanation of what you believe is the study's overall impact and significance. Unless the purpose of the assignment is to examine foundational studies published many years ago, you should select articles that have been published relatively recently [e.g., within the past few years].

Since the research has been completed, reference to the study in your paper should be written in the past tense, with your analysis stated in the present tense [e.g., “The author portrayed access to health care services in rural areas as primarily a problem of having reliable transportation. However, I believe the author is overgeneralizing this issue because...”].

Introduction Section

The first section of a journal analysis paper should describe the topic of the article and highlight the author’s main points. This includes describing the research problem and theoretical framework, the rationale for the research, the methods of data gathering and analysis, the key findings, and the author’s final conclusions and recommendations. The narrative should focus on the act of describing rather than analyzing. Think of the introduction as a more comprehensive and detailed descriptive abstract of the study.

Possible questions to help guide your writing of the introduction section may include:

• Who are the authors and what credentials do they hold that contributes to the validity of the study?
• What was the research problem being investigated?
• What type of research design was used to investigate the research problem?
• What theoretical idea(s) and/or research questions were used to address the problem?
• What was the source of the data or information used as evidence for analysis?
• What methods were applied to investigate this evidence?
• What were the author's overall conclusions and key findings?

Critical Analysis Section

The second section of a journal analysis paper should describe the strengths and weaknesses of the study and analyze its significance and impact. This section is where you shift the narrative from describing to analyzing. Think critically about the research in relation to other course readings, what has been discussed in class, or based on your own life experiences. If you are struggling to identify any weaknesses, explain why you believe this to be true. However, no study is perfect, regardless of how laudable its design may be. Given this, think about the repercussions of the choices made by the author(s) and how you might have conducted the study differently. Examples can include contemplating the choice of what sources were included or excluded in support of examining the research problem, the choice of the method used to analyze the data, or the choice to highlight specific recommended courses of action and/or implications for practice over others. Another strategy is to place yourself within the research study itself by thinking reflectively about what may be missing if you had been a participant in the study or if the recommended courses of action specifically targeted you or your community.

Possible questions to help guide your writing of the analysis section may include:

Introduction

• Did the author clearly state the problem being investigated?
• What was your reaction to and perspective on the research problem?
• Was the study’s objective clearly stated? Did the author clearly explain why the study was necessary?
• How well did the introduction frame the scope of the study?
• Did the introduction conclude with a clear purpose statement?

Literature Review

• Did the literature review lay a foundation for understanding the significance of the research problem?
• Did the literature review provide enough background information to understand the problem in relation to relevant contexts [e.g., historical, economic, social, cultural, etc.].
• Did literature review effectively place the study within the domain of prior research? Is anything missing?
• Was the literature review organized by conceptual categories or did the author simply list and describe sources?
• Did the author accurately explain how the data or information were collected?
• Was the data used sufficient in supporting the study of the research problem?
• Was there another methodological approach that could have been more illuminating?
• Give your overall evaluation of the methods used in this article. How much trust would you put in generating relevant findings?

Results and Discussion

• Were the results clearly presented?
• Did you feel that the results support the theoretical and interpretive claims of the author? Why?
• What did the author(s) do especially well in describing or analyzing their results?
• Was the author's evaluation of the findings clearly stated?
• How well did the discussion of the results relate to what is already known about the research problem?
• Was the discussion of the results free of repetition and redundancies?
• What interpretations did the authors make that you think are in incomplete, unwarranted, or overstated?
• Did the conclusion effectively capture the main points of study?
• Did the conclusion address the research questions posed? Do they seem reasonable?
• Were the author’s conclusions consistent with the evidence and arguments presented?
• Has the author explained how the research added new knowledge or understanding?

Overall Writing Style

• If the article included tables, figures, or other non-textual elements, did they contribute to understanding the study?
• Were ideas developed and related in a logical sequence?
• Were transitions between sections of the article smooth and easy to follow?

Overall Evaluation Section

The final section of a journal analysis paper should bring your thoughts together into a coherent assessment of the value of the research study . This section is where the narrative flow transitions from analyzing specific elements of the article to critically evaluating the overall study. Explain what you view as the significance of the research in relation to the overall course content and any relevant discussions that occurred during class. Think about how the article contributes to understanding the overall research problem, how it fits within existing literature on the topic, how it relates to the course, and what it means to you as a student researcher. In some cases, your professor will also ask you to describe your experiences writing the journal article analysis paper as part of a reflective learning exercise.

Possible questions to help guide your writing of the conclusion and evaluation section may include:

• Was the structure of the article clear and well organized?
• Was the topic of current or enduring interest to you?
• What were the main weaknesses of the article? [this does not refer to limitations stated by the author, but what you believe are potential flaws]
• Was any of the information in the article unclear or ambiguous?
• What did you learn from the research? If nothing stood out to you, explain why.
• Assess the originality of the research. Did you believe it contributed new understanding of the research problem?
• Were you persuaded by the author’s arguments?
• If the author made any final recommendations, will they be impactful if applied to practice?
• In what ways could future research build off of this study?
• What implications does the study have for daily life?
• Was the use of non-textual elements, footnotes or endnotes, and/or appendices helpful in understanding the research?
• What lingering questions do you have after analyzing the article?

NOTE: Avoid using quotes. One of the main purposes of writing an article analysis paper is to learn how to effectively paraphrase and use your own words to summarize a scholarly research study and to explain what the research means to you. Using and citing a direct quote from the article should only be done to help emphasize a key point or to underscore an important concept or idea.

Business: The Article Analysis . Fred Meijer Center for Writing, Grand Valley State University; Bachiochi, Peter et al. "Using Empirical Article Analysis to Assess Research Methods Courses." Teaching of Psychology 38 (2011): 5-9; Brosowsky, Nicholaus P. et al. “Teaching Undergraduate Students to Read Empirical Articles: An Evaluation and Revision of the QALMRI Method.” PsyArXi Preprints , 2020; Holster, Kristin. “Article Evaluation Assignment”. TRAILS: Teaching Resources and Innovations Library for Sociology . Washington DC: American Sociological Association, 2016; Kershaw, Trina C., Jennifer Fugate, and Aminda J. O'Hare. "Teaching Undergraduates to Understand Published Research through Structured Practice in Identifying Key Research Concepts." Scholarship of Teaching and Learning in Psychology . Advance online publication, 2020; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Reviewer's Guide . SAGE Reviewer Gateway, SAGE Journals; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946; Gyuris, Emma, and Laura Castell. "To Tell Them or Show Them? How to Improve Science Students’ Skills of Critical Reading." International Journal of Innovation in Science and Mathematics Education 21 (2013): 70-80; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students Make the Most of Scholarly Articles." Library Management 33 (2012): 525-535.

Writing Tip

Not All Scholarly Journal Articles Can Be Critically Analyzed

There are a variety of articles published in scholarly journals that do not fit within the guidelines of an article analysis assignment. This is because the work cannot be empirically examined or it does not generate new knowledge in a way which can be critically analyzed.

If you are required to locate a research study on your own, avoid selecting these types of journal articles:

• Theoretical essays which discuss concepts, assumptions, and propositions, but report no empirical research;
• Statistical or methodological papers that may analyze data, but the bulk of the work is devoted to refining a new measurement, statistical technique, or modeling procedure;
• Articles that review, analyze, critique, and synthesize prior research, but do not report any original research;
• Brief essays devoted to research methods and findings;
• Articles written by scholars in popular magazines or industry trade journals;
• Pre-print articles that have been posted online, but may undergo further editing and revision by the journal's editorial staff before final publication; and
• Academic commentary that discusses research trends or emerging concepts and ideas, but does not contain citations to sources.

Journal Analysis Assignment - Myers . Writing@CSU, Colorado State University; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36.

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How to write statistical analysis section in medical research

Alok kumar dwivedi.

Department of Molecular and Translational Medicine, Division of Biostatistics and Epidemiology, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA

Associated Data

jim-2022-002479supp001.pdf

Data sharing not applicable as no datasets generated and/or analyzed for this study.

Reporting of statistical analysis is essential in any clinical and translational research study. However, medical research studies sometimes report statistical analysis that is either inappropriate or insufficient to attest to the accuracy and validity of findings and conclusions. Published works involving inaccurate statistical analyses and insufficient reporting influence the conduct of future scientific studies, including meta-analyses and medical decisions. Although the biostatistical practice has been improved over the years due to the involvement of statistical reviewers and collaborators in research studies, there remain areas of improvement for transparent reporting of the statistical analysis section in a study. Evidence-based biostatistics practice throughout the research is useful for generating reliable data and translating meaningful data to meaningful interpretation and decisions in medical research. Most existing research reporting guidelines do not provide guidance for reporting methods in the statistical analysis section that helps in evaluating the quality of findings and data interpretation. In this report, we highlight the global and critical steps to be reported in the statistical analysis of grants and research articles. We provide clarity and the importance of understanding study objective types, data generation process, effect size use, evidence-based biostatistical methods use, and development of statistical models through several thematic frameworks. We also provide published examples of adherence or non-adherence to methodological standards related to each step in the statistical analysis and their implications. We believe the suggestions provided in this report can have far-reaching implications for education and strengthening the quality of statistical reporting and biostatistical practice in medical research.

Introduction

Biostatistics is the overall approach to how we realistically and feasibly execute a research idea to produce meaningful data and translate data to meaningful interpretation and decisions. In this era of evidence-based medicine and practice, basic biostatistical knowledge becomes essential for critically appraising research articles and implementing findings for better patient management, improving healthcare, and research planning. 1 However, it may not be sufficient for the proper execution and reporting of statistical analyses in studies. 2 3 Three things are required for statistical analyses, namely knowledge of the conceptual framework of variables, research design, and evidence-based applications of statistical analysis with statistical software. 4 5 The conceptual framework provides possible biological and clinical pathways between independent variables and outcomes with role specification of variables. The research design provides a protocol of study design and data generation process (DGP), whereas the evidence-based statistical analysis approach provides guidance for selecting and implementing approaches after evaluating data with the research design. 2 5 Ocaña-Riola 6 reported a substantial percentage of articles from high-impact medical journals contained errors in statistical analysis or data interpretation. These errors in statistical analyses and interpretation of results do not only impact the reliability of research findings but also influence the medical decision-making and planning and execution of other related studies. A survey of consulting biostatisticians in the USA reported that researchers frequently request biostatisticians for performing inappropriate statistical analyses and inappropriate reporting of data. 7 This implies that there is a need to enforce standardized reporting of the statistical analysis section in medical research which can also help rreviewers and investigators to improve the methodological standards of the study.

Biostatistical practice in medicine has been improving over the years due to continuous efforts in promoting awareness and involving expert services on biostatistics, epidemiology, and research design in clinical and translational research. 8–11 Despite these efforts, the quality of reporting of statistical analysis in research studies has often been suboptimal. 12 13 We noticed that none of the methods reporting documents were developed using evidence-based biostatistics (EBB) theory and practice. The EBB practice implies that the selection of statistical analysis methods for statistical analyses and the steps of results reporting and interpretation should be grounded based on the evidence generated in the scientific literature and according to the study objective type and design. 5 Previous works have not properly elucidated the importance of understanding EBB concepts and related reporting in the write-up of statistical analyses. As a result, reviewers sometimes ask to present data or execute analyses that do not match the study objective type. 14 We summarize the statistical analysis steps to be reported in the statistical analysis section based on review and thematic frameworks.

We identified articles describing statistical reporting problems in medicine using different search terms ( online supplemental table 1 ). Based on these studies, we prioritized commonly reported statistical errors in analytical strategies and developed essential components to be reported in the statistical analysis section of research grants and studies. We also clarified the purpose and the overall implication of reporting each step in statistical analyses through various examples.

Supplementary data

Although biostatistical inputs are critical for the entire research study ( online supplemental table 2 ), biostatistical consultations were mostly used for statistical analyses only 15 . Even though the conduct of statistical analysis mismatched with the study objective and DGP was identified as the major problem in articles submitted to high-impact medical journals. 16 In addition, multivariable analyses were often inappropriately conducted and reported in published studies. 17 18 In light of these statistical errors, we describe the reporting of the following components in the statistical analysis section of the study.

Step 1: specify study objective type and outcomes (overall approach)

The study objective type provides the role of important variables for a specified outcome in statistical analyses and the overall approach of the model building and model reporting steps in a study. In the statistical framework, the problems are classified into descriptive and inferential/analytical/confirmatory objectives. In the epidemiological framework, the analytical and prognostic problems are broadly classified into association, explanatory, and predictive objectives. 19 These study objectives ( figure 1 ) may be classified into six categories: (1) exploratory, (2) association, (3) causal, (4) intervention, (5) prediction and (6) clinical decision models in medical research. 20

Comparative assessments of developing and reporting of study objective types and models. Association measures include odds ratio, risk ratio, or hazard ratio. AUC, area under the curve; C, confounder; CI, confidence interval; E, exposure; HbA1C: hemoglobin A1c; M, mediator; MFT, model fit test; MST, model specification test; PI, predictive interval; R 2 , coefficient of determinant; X, independent variable; Y, outcome.

The exploratory objective type is a specific type of determinant study and is commonly known as risk factors or correlates study in medical research. In an exploratory study, all covariates are considered equally important for the outcome of interest in the study. The goal of the exploratory study is to present the results of a model which gives higher accuracy after satisfying all model-related assumptions. In the association study, the investigator identifies predefined exposures of interest for the outcome, and variables other than exposures are also important for the interpretation and considered as covariates. The goal of an association study is to present the adjusted association of exposure with outcome. 20 In the causal objective study, the investigator is interested in determining the impact of exposure(s) on outcome using the conceptual framework. In this study objective, all variables should have a predefined role (exposures, confounders, mediators, covariates, and predictors) in a conceptual framework. A study with a causal objective is known as an explanatory or a confirmatory study in medical research. The goal is to present the direct or indirect effects of exposure(s) on an outcome after assessing the model’s fitness in the conceptual framework. 19 21 The objective of an interventional study is to determine the effect of an intervention on outcomes and is often known as randomized or non-randomized clinical trials in medical research. In the intervention objective model, all variables other than the intervention are treated as nuisance variables for primary analyses. The goal is to present the direct effect of the intervention on the outcomes by eliminating biases. 22–24 In the predictive study, the goal is to determine an optimum set of variables that can predict the outcome, particularly in external settings. The clinical decision models are a special case of prognostic models in which high dimensional data at various levels are used for risk stratification, classification, and prediction. In this model, all variables are considered input features. The goal is to present a decision tool that has high accuracy in training, testing, and validation data sets. 20 25 Biostatisticians or applied researchers should properly discuss the intention of the study objective type before proceeding with statistical analyses. In addition, it would be a good idea to prepare a conceptual model framework regardless of study objective type to understand study concepts.

A study 26 showed a favorable effect of the beta-blocker intervention on survival outcome in patients with advanced human epidermal growth factor receptor (HER2)-negative breast cancer without adjusting for all the potential confounding effects (age or menopausal status and Eastern Cooperative Oncology Performance Status) in primary analyses or validation analyses or using a propensity score-adjusted analysis, which is an EBB preferred method for analyzing non-randomized studies. 27 Similarly, another study had the goal of developing a predictive model for prediction of Alzheimer’s disease progression. 28 However, this study did not internally or externally validate the performance of the model as per the requirement of a predictive objective study. In another study, 29 investigators were interested in determining an association between metabolic syndrome and hepatitis C virus. However, the authors did not clearly specify the outcome in the analysis and produced conflicting associations with different analyses. 30 Thus, the outcome should be clearly specified as per the study objective type.

Step 2: specify effect size measure according to study design (interpretation and practical value)

The study design provides information on the selection of study participants and the process of data collection conditioned on either exposure or outcome ( figure 2 ). The appropriate use of effect size measure, tabular presentation of results, and the level of evidence are mostly determined by the study design. 31 32 In cohort or clinical trial study designs, the participants are selected based on exposure status and are followed up for the development of the outcome. These study designs can provide multiple outcomes, produce incidence or incidence density, and are preferred to be analyzed with risk ratio (RR) or hazards models. In a case–control study, the selection of participants is conditioned on outcome status. This type of study can have only one outcome and is preferred to be analyzed with an odds ratio (OR) model. In a cross-sectional study design, there is no selection restriction on outcomes or exposures. All data are collected simultaneously and can be analyzed with a prevalence ratio model, which is mathematically equivalent to the RR model. 33 The reporting of effect size measure also depends on the study objective type. For example, predictive models typically require reporting of regression coefficients or weight of variables in the model instead of association measures, which are required in other objective types. There are agreements and disagreements between OR and RR measures. Due to the constancy and symmetricity properties of OR, some researchers prefer to use OR in studies with common events. Similarly, the collapsibility and interpretability properties of RR make it more appealing to use in studies with common events. 34 To avoid variable practice and interpretation issues with OR, it is recommended to use RR models in all studies except for case–control and nested case–control studies, where OR approximates RR and thus OR models should be used. Otherwise, investigators may report sufficient data to compute any ratio measure. Biostatisticians should educate investigators on the proper interpretation of ratio measures in the light of study design and their reporting. 34 35

Effect size according to study design.

Investigators sometimes either inappropriately label their study design 36 37 or report effect size measures not aligned with the study design, 38 39 leading to difficulty in results interpretation and evaluation of the level of evidence. The proper labeling of study design and the appropriate use of effect size measure have substantial implications for results interpretation, including the conduct of systematic review and meta-analysis. 40 A study 31 reviewed the frequency of reporting OR instead of RR in cohort studies and randomized clinical trials (RCTs) and found that one-third of the cohort studies used an OR model, whereas 5% of RCTs used an OR model. The majority of estimated ORs from these studies had a 20% or higher deviation from the corresponding RR.

Step 3: specify study hypothesis, reporting of p values, and interval estimates (interpretation and decision)

The clinical hypothesis provides information for evaluating formal claims specified in the study objectives, while the statistical hypothesis provides information about the population parameters/statistics being used to test the formal claims. The inference about the study hypothesis is typically measured by p value and confidence interval (CI). A smaller p value indicates that the data support against the null hypothesis. Since the p value is a conditional probability, it can never tell about the acceptance or rejection of the null hypothesis. Therefore, multiple alternative strategies of p values have been proposed to strengthen the credibility of conclusions. 41 42 Adaption of these alternative strategies is only needed in the explanatory objective studies. Although exact p values are recommended to be reported in research studies, p values do not provide any information about the effect size. Compared with p values, the CI provides a confidence range of the effect size that contains the true effect size if the study were repeated and can be used to determine whether the results are statistically significant or not. 43 Both p value and 95% CI provide complementary information and thus need to be specified in the statistical analysis section. 24 44

Researchers often test one or more comparisons or hypotheses. Accordingly, the side and the level of significance for considering results to be statistically significant may change. Furthermore, studies may include more than one primary outcome that requires an adjustment in the level of significance for multiplicity. All studies should provide the interval estimate of the effect size/regression coefficient in the primary analyses. Since the interpretation of data analysis depends on the study hypothesis, researchers are required to specify the level of significance along with the side (one-sided or two-sided) of the p value in the test for considering statistically significant results, adjustment of the level of significance due to multiple comparisons or multiplicity, and reporting of interval estimates of the effect size in the statistical analysis section. 45

A study 46 showed a significant effect of fluoxetine on relapse rates in obsessive-compulsive disorder based on a one-sided p value of 0.04. Clearly, there was no reason for using a one-sided p value as opposed to a two-sided p value. A review of the appropriate use of multiple test correction methods in multiarm clinical trials published in major medical journals in 2012 identified over 50% of the articles did not perform multiple-testing correction. 47 Similar to controlling a familywise error rate due to multiple comparisons, adjustment of the false discovery rate is also critical in studies involving multiple related outcomes. A review of RCTs for depression between 2007 and 2008 from six journals reported that only limited studies (5.8%) accounted for multiplicity in the analyses due to multiple outcomes. 48

Step 4: account for DGP in the statistical analysis (accuracy)

The study design also requires the specification of the selection of participants and outcome measurement processes in different design settings. We referred to this specific design feature as DGP. Understanding DGP helps in determining appropriate modeling of outcome distribution in statistical analyses and setting up model premises and units of analysis. 4 DGP ( figure 3 ) involves information on data generation and data measures, including the number of measurements after random selection, complex selection, consecutive selection, pragmatic selection, or systematic selection. Specifically, DGP depends on a sampling setting (participants are selected using survey sampling methods and one subject may represent multiple participants in the population), clustered setting (participants are clustered through a recruitment setting or hierarchical setting or multiple hospitals), pragmatic setting (participants are selected through mixed approaches), or systematic review setting (participants are selected from published studies). DGP also depends on the measurements of outcomes in an unpaired setting (measured on one occasion only in independent groups), paired setting (measured on more than one occasion or participants are matched on certain subject characteristics), or mixed setting (measured on more than one occasion but interested in comparing independent groups). It also involves information regarding outcomes or exposure generation processes using quantitative or categorical variables, quantitative values using labs or validated instruments, and self-reported or administered tests yielding a variety of data distributions, including individual distribution, mixed-type distribution, mixed distributions, and latent distributions. Due to different DGPs, study data may include messy or missing data, incomplete/partial measurements, time-varying measurements, surrogate measures, latent measures, imbalances, unknown confounders, instrument variables, correlated responses, various levels of clustering, qualitative data, or mixed data outcomes, competing events, individual and higher-level variables, etc. The performance of statistical analysis, appropriate estimation of standard errors of estimates and subsequently computation of p values, the generalizability of findings, and the graphical display of data rely on DGP. Accounting for DGP in the analyses requires proper communication between investigators and biostatisticians about each aspect of participant selection and data collection, including measurements, occasions of measurements, and instruments used in the research study.

Common features of the data generation process.

A study 49 compared the intake of fresh fruit and komatsuna juice with the intake of commercial vegetable juice on metabolic parameters in middle-aged men using an RCT. The study was criticized for many reasons, but primarily for incorrect statistical methods not aligned with the study DGP. 50 Similarly, another study 51 highlighted that 80% of published studies using the Korean National Health and Nutrition Examination Survey did not incorporate survey sampling structure in statistical analyses, producing biased estimates and inappropriate findings. Likewise, another study 52 highlighted the need for maintaining methodological standards while analyzing data from the National Inpatient Sample. A systematic review 53 identified that over 50% of studies did not specify whether a paired t-test or an unpaired t-test was performed in statistical analysis in the top 25% of physiology journals, indicating poor transparency in reporting of statistical analysis as per the data type. Another study 54 also highlighted the data displaying errors not aligned with DGP. As per DGP, delay in treatment initiation of patients with cancer defined from the onset of symptom to treatment initiation should be analyzed into three components: patient/primary delay, secondary delay, and tertiary delay. 55 Similarly, the number of cancerous nodes should be analyzed with count data models. 56 However, several studies did not analyze such data according to DGP. 57 58

Step 5: apply EBB methods specific to study design features and DGP (efficiency and robustness)

The continuous growth in the development of robust statistical methods for dealing with a specific problem produced various methods to analyze specific data types. Since multiple methods are available for handling a specific problem yet with varying performances, heterogeneous practices among applied researchers have been noticed. Variable practices could also be due to a lack of consensus on statistical methods in literature, unawareness, and the unavailability of standardized statistical guidelines. 2 5 59 However, it becomes sometimes difficult to differentiate whether a specific method was used due to its robustness, lack of awareness, lack of accessibility of statistical software to apply an alternative appropriate method, intention to produce expected results, or ignorance of model diagnostics. To avoid heterogeneous practices, the selection of statistical methodology and their reporting at each stage of data analysis should be conducted using methods according to EBB practice. 5 Since it is hard for applied researchers to optimally select statistical methodology at each step, we encourage investigators to involve biostatisticians at the very early stage in basic, clinical, population, translational, and database research. We also appeal to biostatisticians to develop guidelines, checklists, and educational tools to promote the concept of EBB. As an effort, we developed the statistical analysis and methods in biomedical research (SAMBR) guidelines for applied researchers to use EBB methods for data analysis. 5 The EBB practice is essential for applying recent cutting-edge robust methodologies to yield accurate and unbiased results. The efficiency of statistical methodologies depends on the assumptions and DGP. Therefore, investigators may attempt to specify the choice of specific models in the primary analysis as per the EBB.

Although details of evidence-based preferred methods are provided in the SAMBR checklists for each study design/objective, 5 we have presented a simplified version of evidence-based preferred methods for common statistical analysis ( online supplemental table 3 ). Several examples are available in the literature where inefficient methods not according to EBB practice have been used. 31 57 60

Step 6: report variable selection method in the multivariable analysis according to study objective type (unbiased)

Multivariable analysis can be used for association, prediction or classification or risk stratification, adjustment, propensity score development, and effect size estimation. 61 Some biological, clinical, behavioral, and environmental factors may directly associate or influence the relationship between exposure and outcome. Therefore, almost all health studies require multivariable analyses for accurate and unbiased interpretations of findings ( figure 1 ). Analysts should develop an adjusted model if the sample size permits. It is a misconception that the analysis of RCT does not require adjusted analysis. Analysis of RCT may require adjustment for prognostic variables. 23 The foremost step in model building is the entry of variables after finalizing the appropriate parametric or non-parametric regression model. In the exploratory model building process due to no preference of exposures, a backward automated approach after including any variables that are significant at 25% in the unadjusted analysis can be used for variable selection. 62 63 In the association model, a manual selection of covariates based on the relevance of the variables should be included in a fully adjusted model. 63 In a causal model, clinically guided methods should be used for variable selection and their adjustments. 20 In a non-randomized interventional model, efforts should be made to eliminate confounding effects through propensity score methods and the final propensity score-adjusted multivariable model may adjust any prognostic variables, while a randomized study simply should adjust any prognostic variables. 27 Maintaining the event per variable (EVR) is important to avoid overfitting in any type of modeling; therefore, screening of variables may be required in some association and explanatory studies, which may be accomplished using a backward stepwise method that needs to be clarified in the statistical analyses. 10 In a predictive study, a model with an optimum set of variables producing the highest accuracy should be used. The optimum set of variables may be screened with the random forest method or bootstrap or machine learning methods. 64 65 Different methods of variable selection and adjustments may lead to different results. The screening process of variables and their adjustments in the final multivariable model should be clearly mentioned in the statistical analysis section.

A study 66 evaluating the effect of hydroxychloroquine (HDQ) showed unfavorable events (intubation or death) in patients who received HDQ compared with those who did not (hazard ratio (HR): 2.37, 95% CI 1.84 to 3.02) in an unadjusted analysis. However, the propensity score-adjusted analyses as appropriate with the interventional objective model showed no significant association between HDQ use and unfavorable events (HR: 1.04, 95% CI 0.82 to 1.32), which was also confirmed in multivariable and other propensity score-adjusted analyses. This study clearly suggests that results interpretation should be based on a multivariable analysis only in observational studies if feasible. A recent study 10 noted that approximately 6% of multivariable analyses based on either logistic or Cox regression used an inappropriate selection method of variables in medical research. This practice was more commonly noted in studies that did not involve an expert biostatistician. Another review 61 of 316 articles from high-impact Chinese medical journals revealed that 30.7% of articles did not report the selection of variables in multivariable models. Indeed, this inappropriate practice could have been identified more commonly if classified according to the study objective type. 18 In RCTs, it is uncommon to report an adjusted analysis based on prognostic variables, even though an adjusted analysis may produce an efficient estimate compared with an unadjusted analysis. A study assessing the effect of preemptive intervention on development outcomes showed a significant effect of an intervention on reducing autism spectrum disorder symptoms. 67 However, this study was criticized by Ware 68 for not reporting non-significant results in unadjusted analyses. If possible, unadjusted estimates should also be reported in any study, particularly in RCTs. 23 68

Step 7: provide evidence for exploring effect modifiers (applicability)

Any variable that modifies the effect of exposure on the outcome is called an effect modifier or modifier or an interacting variable. Exploring the effect modifiers in multivariable analyses helps in (1) determining the applicability/generalizability of findings in the overall or specific subpopulation, (2) generating ideas for new hypotheses, (3) explaining uninterpretable findings between unadjusted and adjusted analyses, (4) guiding to present combined or separate models for each specific subpopulation, and (5) explaining heterogeneity in treatment effect. Often, investigators present adjusted stratified results according to the presence or absence of an effect modifier. If the exposure interacts with multiple variables statistically or conceptually in the model, then the stratified findings (subgroup) according to each effect modifier may be presented. Otherwise, stratified analysis substantially reduces the power of the study due to the lower sample size in each stratum and may produce significant results by inflating type I error. 69 Therefore, a multivariable analysis involving an interaction term as opposed to a stratified analysis may be presented in the presence of an effect modifier. 70 Sometimes, a quantitative variable may emerge as a potential effect modifier for exposure and an outcome relationship. In such a situation, the quantitative variable should not be categorized unless a clinically meaningful threshold is not available in the study. In fact, the practice of categorizing quantitative variables should be avoided in the analysis unless a clinically meaningful cut-off is available or a hypothesis requires for it. 71 In an exploratory objective type, any possible interaction may be obtained in a study; however, the interpretation should be guided based on clinical implications. Similarly, some objective models may have more than one exposure or intervention and the association of each exposure according to the level of other exposure should be presented through adjusted analyses as suggested in the presence of interaction effects. 70

A review of 428 articles from MEDLINE on the quality of reporting from statistical analyses of three (linear, logistic, and Cox) commonly used regression models reported that only 18.5% of the published articles provided interaction analyses, 17 even though interaction analyses can provide a lot of useful information.

Step 8: assessment of assumptions, specifically the distribution of outcome, linearity, multicollinearity, sparsity, and overfitting (reliability)

The assessment and reporting of model diagnostics are important in assessing the efficiency, validity, and usefulness of the model. Model diagnostics include satisfying model-specific assumptions and the assessment of sparsity, linearity, distribution of outcome, multicollinearity, and overfitting. 61 72 Model-specific assumptions such as normal residuals, heteroscedasticity and independence of errors in linear regression, proportionality in Cox regression, proportionality odds assumption in ordinal logistic regression, and distribution fit in other types of continuous and count models are required. In addition, sparsity should also be examined prior to selecting an appropriate model. Sparsity indicates many zero observations in the data set. 73 In the presence of sparsity, the effect size is difficult to interpret. Except for machine learning models, most of the parametric and semiparametric models require a linear relationship between independent variables and a functional form of an outcome. Linearity should be assessed using a multivariable polynomial in all model objectives. 62 Similarly, the appropriate choice of the distribution of outcome is required for model building in all study objective models. Multicollinearity assessment is also useful in all objective models. Assessment of EVR in multivariable analysis can be used to avoid the overfitting issue of a multivariable model. 18

Some review studies highlighted that 73.8%–92% of the articles published in MEDLINE had not assessed the model diagnostics of the multivariable regression models. 17 61 72 Contrary to the monotonically, linearly increasing relationship between systolic blood pressure (SBP) and mortality established using the Framingham’s study, 74 Port et al 75 reported a non-linear relationship between SBP and all-cause mortality or cardiovascular deaths by reanalysis of the Framingham’s study data set. This study identified a different threshold for treating hypertension, indicating the role of linearity assessment in multivariable models. Although a non-Gaussian distribution model may be required for modeling patient delay outcome data in cancer, 55 a study analyzed patient delay data using an ordinary linear regression model. 57 An investigation of the development of predictive models and their reporting in medical journals identified that 53% of the articles had fewer EVR than the recommended EVR, indicating over half of the published articles may have an overfitting model. 18 Another study 76 attempted to identify the anthropometric variables associated with non-insulin-dependent diabetes and found that none of the anthropometric variables were significant after adjusting for waist circumference, age, and sex, indicating the presence of collinearity. A study reported detailed sparse data problems in published studies and potential solutions. 73

Step 9: report type of primary and sensitivity analyses (consistency)

Numerous considerations and assumptions are made throughout the research processes that require assessment, evaluation, and validation. Some assumptions, executions, and errors made at the beginning of the study data collection may not be fixable 13 ; however, additional information collected during the study and data processing, including data distribution obtained at the end of the study, may facilitate additional considerations that need to be verified in the statistical analyses. Consistencies in the research findings via modifications in the outcome or exposure definition, study population, accounting for missing data, model-related assumptions, variables and their forms, and accounting for adherence to protocol in the models can be evaluated and reported in research studies using sensitivity analyses. 77 The purpose and type of supporting analyses need to be specified clearly in the statistical analyses to differentiate the main findings from the supporting findings. Sensitivity analyses are different from secondary or interim or subgroup analyses. 78 Data analyses for secondary outcomes are often referred to as secondary analyses, while data analyses of an ongoing study are called interim analyses and data analyses according to groups based on patient characteristics are known as subgroup analyses.

Almost all studies require some form of sensitivity analysis to validate the findings under different conditions. However, it is often underutilized in medical journals. Only 18%–20.3% of studies reported some forms of sensitivity analyses. 77 78 A review of nutritional trials from high-quality journals reflected that 17% of the conclusions were reported inappropriately using findings from sensitivity analyses not based on the primary/main analyses. 77

Step 10: provide methods for summarizing, displaying, and interpreting data (transparency and usability)

Data presentation includes data summary, data display, and data from statistical model analyses. The primary purpose of the data summary is to understand the distribution of outcome status and other characteristics in the total sample and by primary exposure status or outcome status. Column-wise data presentation should be preferred according to exposure status in all study designs, while row-wise data presentation for the outcome should be preferred in all study designs except for a case–control study. 24 32 Summary statistics should be used to provide maximum information on data distribution aligned with DGP and variable type. The purpose of results presentation primarily from regression analyses or statistical models is to convey results interpretation and implications of findings. The results should be presented according to the study objective type. Accordingly, the reporting of unadjusted and adjusted associations of each factor with the outcome may be preferred in the determinant objective model, while unadjusted and adjusted effects of primary exposure on the outcome may be preferred in the explanatory objective model. In prognostic models, the final predictive models may be presented in such a way that users can use models to predict an outcome. In the exploratory objective model, a final multivariable model should be reported with R 2 or area under the curve (AUC). In the association and interventional models, the assessment of internal validation is critically important through various sensitivity and validation analyses. A model with better fit indices (in terms of R 2 or AUC, Akaike information criterion, Bayesian information criterion, fit index, root mean square error) should be finalized and reported in the causal model objective study. In the predictive objective type, the model performance in terms of R 2 or AUC in training and validation data sets needs to be reported ( figure 1 ). 20 21 There are multiple purposes of data display, including data distribution using bar diagram or histogram or frequency polygons or box plots, comparisons using cluster bar diagram or scatter dot plot or stacked bar diagram or Kaplan-Meier plot, correlation or model assessment using scatter plot or scatter matrix, clustering or pattern using heatmap or line plots, the effect of predictors with fitted models using marginsplot, and comparative evaluation of effect sizes from regression models using forest plot. Although the key purpose of data display is to highlight critical issues or findings in the study, data display should essentially follow DGP and variable types and should be user-friendly. 54 79 Data interpretation heavily relies on the effect size measure along with study design and specified hypotheses. Sometimes, variables require standardization for descriptive comparison of effect sizes among exposures or interpreting small effect size, or centralization for interpreting intercept or avoiding collinearity due to interaction terms, or transformation for achieving model-related assumptions. 80 Appropriate methods of data reporting and interpretation aligned with study design, study hypothesis, and effect size measure should be specified in the statistical analysis section of research studies.

Published articles from reputed journals inappropriately summarized a categorized variable with mean and range, 81 summarized a highly skewed variable with mean and standard deviation, 57 and treated a categorized variable as a continuous variable in regression analyses. 82 Similarly, numerous examples from published studies reporting inappropriate graphical display or inappropriate interpretation of data not aligned with DGP or variable types are illustrated in a book published by Bland and Peacock. 83 84 A study used qualitative data on MRI but inappropriately presented with a Box-Whisker plot. 81 Another study reported unusually high OR for an association between high breast parenchymal enhancement and breast cancer in both premenopausal and postmenopausal women. 85 This reporting makes suspicious findings and may include sparse data bias. 86 A poor tabular presentation without proper scaling or standardization of a variable, missing CI for some variables, missing unit and sample size, and inconsistent reporting of decimal places could be easily noticed in table 4 of a published study. 29 Some published predictive models 87 do not report intercept or baseline survival estimates to use their predictive models in clinical use. Although a direct comparison of effect sizes obtained from the same model may be avoided if the units are different among variables, 35 a study had an objective to compare effect sizes across variables but the authors performed comparisons without standardization of variables or using statistical tests. 88

A sample for writing statistical analysis section in medical journals/research studies

Our primary study objective type was to develop a (select from figure 1 ) model to assess the relationship of risk factors (list critical variables or exposures) with outcomes (specify type from continuous/discrete/count/binary/polytomous/time-to-event). To address this objective, we conducted a (select from figure 2 or any other) study design to test the hypotheses of (equality or superiority or non-inferiority or equivalence or futility) or develop prediction. Accordingly, the other variables were adjusted or considered as (specify role of variables from confounders, covariates, or predictors or independent variables) as reflected in the conceptual framework. In the unadjusted or preliminary analyses as per the (select from figure 3 or any other design features) DGP, (specify EBB preferred tests from online supplemental table 3 or any other appropriate tests) were used for (specify variables and types) in unadjusted analyses. According to the EBB practice for the outcome (specify type) and DGP of (select from figure 3 or any other), we used (select from online supplemental table 1 or specify a multivariable approach) as the primary model in the multivariable analysis. We used (select from figure 1 ) variable selection method in the multivariable analysis and explored the interaction effects between (specify variables). The model diagnostics including (list all applicable, including model-related assumptions, linearity, or multicollinearity or overfitting or distribution of outcome or sparsity) were also assessed using (specify appropriate methods) respectively. In such exploration, we identified (specify diagnostic issues if any) and therefore the multivariable models were developed using (specify potential methods used to handle diagnostic issues). The other outcomes were analyzed with (list names of multivariable approaches with respective outcomes). All the models used the same procedure (or specify from figure 1 ) for variable selection, exploration of interaction effects, and model diagnostics using (specify statistical approaches) depending on the statistical models. As per the study design, hypothesis, and multivariable analysis, the results were summarized with effect size (select as appropriate or from figure 2 ) along with (specify 95% CI or other interval estimates) and considered statistically significant using (specify the side of p value or alternatives) at (specify the level of significance) due to (provide reasons for choosing a significance level). We presented unadjusted and/or adjusted estimates of primary outcome according to (list primary exposures or variables). Additional analyses were conducted for (specific reasons from step 9) using (specify methods) to validate findings obtained in the primary analyses. The data were summarized with (list summary measures and appropriate graphs from step 10), whereas the final multivariable model performance was summarized with (fit indices if applicable from step 10). We also used (list graphs) as appropriate with DGP (specify from figure 3 ) to present the critical findings or highlight (specify data issues) using (list graphs/methods) in the study. The exposures or variables were used in (specify the form of the variables) and therefore the effect or association of (list exposures or variables) on outcome should be interpreted in terms of changes in (specify interpretation unit) exposures/variables. List all other additional analyses if performed (with full details of all models in a supplementary file along with statistical codes if possible).

Concluding remarks

We highlighted 10 essential steps to be reported in the statistical analysis section of any analytical study ( figure 4 ). Adherence to minimum reporting of the steps specified in this report may enforce investigators to understand concepts and approach biostatisticians timely to apply these concepts in their study to improve the overall quality of methodological standards in grant proposals and research studies. The order of reporting information in statistical analyses specified in this report is not mandatory; however, clear reporting of analytical steps applicable to the specific study type should be mentioned somewhere in the manuscript. Since the entire approach of statistical analyses is dependent on the study objective type and EBB practice, proper execution and reporting of statistical models can be taught to the next generation of statisticians by the study objective type in statistical education courses. In fact, some disciplines ( figure 5 ) are strictly aligned with specific study objective types. Bioinformaticians are oriented in studying determinant and prognostic models toward precision medicine, while epidemiologists are oriented in studying association and causal models, particularly in population-based observational and pragmatic settings. Data scientists are heavily involved in prediction and classification models in personalized medicine. A common thing across disciplines is using biostatistical principles and computation tools to address any research question. Sometimes, one discipline expert does the part of others. 89 We strongly recommend using a team science approach that includes an epidemiologist, biostatistician, data scientist, and bioinformatician depending on the study objectives and needs. Clear reporting of data analyses as per the study objective type should be encouraged among all researchers to minimize heterogeneous practices and improve scientific quality and outcomes. In addition, we also encourage investigators to strictly follow transparent reporting and quality assessment guidelines according to the study design ( https://www.equator-network.org/ ) to improve the overall quality of the study, accordingly STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) for observational studies, CONSORT (Consolidated Standards of Reporting Trials) for clinical trials, STARD (Standards for Reporting Diagnostic Accuracy Studies) for diagnostic studies, TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis OR Diagnosis) for prediction modeling, and ARRIVE (Animal Research: Reporting of In Vivo Experiments) for preclinical studies. The steps provided in this document for writing the statistical analysis section is essentially different from other guidance documents, including SAMBR. 5 SAMBR provides a guidance document for selecting evidence-based preferred methods of statistical analysis according to different study designs, while this report suggests the global reporting of essential information in the statistical analysis section according to study objective type. In this guidance report, our suggestion strictly pertains to the reporting of methods in the statistical analysis section and their implications on the interpretation of results. Our document does not provide guidance on the reporting of sample size or results or statistical analysis section for meta-analysis. The examples and reviews reported in this study may be used to emphasize the concepts and related implications in medical research.

Summary of reporting steps, purpose, and evaluation measures in the statistical analysis section.

Role of interrelated disciplines according to study objective type.

Acknowledgments

The author would like to thank the reviewers for their careful review and insightful suggestions.

Contributors: AKD developed the concept and design and wrote the manuscript.

Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests: AKD is a Journal of Investigative Medicine Editorial Board member. No other competing interests declared.

Provenance and peer review: Commissioned; externally peer reviewed.

Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Data availability statement

Ethics statements, patient consent for publication.

Not required.

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How to write the results section of a research paper

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Table of Contents

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

Difference between results and discussion

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

Structure of the results section

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

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

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

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

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

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

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

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

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Home » Research Results Section – Writing Guide and Examples

Research Results Section – Writing Guide and Examples

Table of Contents

Research Results

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

Results Section in Research

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

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

Structure of Research Results Section

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

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

Outline of Research Results Section

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

I. Introduction

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

II. Descriptive statistics

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

III. Inferential statistics

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

IV. Effect sizes and confidence intervals

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

V. Subgroup analyses

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

VI. Limitations and assumptions

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

VII. Conclusions

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

Example of Research Results Section

An Example of a Research Results Section could be:

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

II. Participants

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

III. Results

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

IV. Discussion

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

V. Conclusion

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

Example of Research Results in Research Paper :

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

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

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

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

Example 3 :

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

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

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

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

Importance of Research Results

Research results are important for several reasons, including:

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

How to Write Results in A Research Paper

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

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

When to Write Research Results

Here are situations When to Write Research Results”

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

Purpose of Research Results

The purposes of Research Results are as follows:

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

Advantages of Research Results

Some Advantages of Research Results are as follows:

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• New insights into medical image analysis with ChatGPT

April 29, 2024

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• Paper spotlight .

Large Language model provides contradictory answers

Researchers from Charité – Universitätsmedizin Berlin have new findings on the analysis of nuclear medicine images using ChatGPT to report. In this section, they answer questions about their research results.

What was the research question or scientific inquiry behind your study?

Large language models such as ChatGPT, powered by artificial intelligence, can handle and even create complex and long texts. These tools are now capable of analyzing images as well. With people all over the world using these technologies, including patients who consult ChatGPT about diagnostic images, it is important to know how well these models can analyse and process images, especially in the medical field.

How did you approach the topic?

We showed ChatGPT, in its "GPT-4V(ision)" version, fifteen representative nuclear medicine images. The task was for ChatGPT to identify the type of examination and to interpret the findings in the images. To check whether the results could be reliably repeated, we ran three rounds of tests. We then evaluated the quality of the responses. Due to unresolved privacy concerns related to GPT, we only used images from published studies and did not include any internal patient data.

What did you discover?

ChatGPT accurately identified the type of medical test being performed in up to 60 percent of instances. It was able to identify the radioactive substance used in about half of these images. However, ChatGPT was rarely able to mark findings within the images correctly. This suggests that the artificial intelligence may not fully understand the content of the images, even though it can identify the type of test. Importantly, ChatGPT advised consulting a specialist in all cases.

Was there anything that surprised you?

It was surprising to find a lot of inconsistency in ChatGPT's responses when the same questions were asked more than once. There were significant differences in the answers in over 75 percent of these queries, showing that ChatGPT's ability to interpret nuclear medicine images is currently neither reliably predictable nor dependable.

What’s your takeaway?

ChatGPT currently has clear limitations in analyzing nuclear medicine images and isn't suitable for clinical use. A major problem is the lack of transparency about what data was used to train the artificial intelligence. There are also unresolved privacy concerns and often inconsistent responses. Language models should be trained transparently with valid data. If they are to be used in medicine, it must be ensured that the models are appropriate and deliver reliable results.

Rogasch JMM et al. Keeping up with ChatGPT: Evaluating its Recognition and Interpretation of Nuclear Medicine Images. Clin Nucl Med 2024 April 1, doi: 10.1097/RLU.0000000000005207

PD Dr. Imke Schatka PD Dr. Julian Rogasch Department of Nuclear Medicine Charité – Universitätsmedizin Berlin

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What It Means To Be Asian in America

The lived experiences and perspectives of asian americans in their own words.

Asians are the fastest growing racial and ethnic group in the United States. More than 24 million Americans in the U.S. trace their roots to more than 20 countries in East and Southeast Asia and the Indian subcontinent.

The majority of Asian Americans are immigrants, coming to understand what they left behind and building their lives in the United States. At the same time, there is a fast growing, U.S.-born generation of Asian Americans who are navigating their own connections to familial heritage and their own experiences growing up in the U.S.

In a new Pew Research Center analysis based on dozens of focus groups, Asian American participants described the challenges of navigating their own identity in a nation where the label “Asian” brings expectations about their origins, behavior and physical self. Read on to see, in their own words, what it means to be Asian in America.

• Introduction

Table of Contents

This is how i view my identity, this is how others see and treat me, this is what it means to be home in america, about this project, methodological note, acknowledgments.

No single experience defines what it means to be Asian in the United States today. Instead, Asian Americans’ lived experiences are in part shaped by where they were born, how connected they are to their family’s ethnic origins, and how others – both Asians and non-Asians – see and engage with them in their daily lives. Yet despite diverse experiences, backgrounds and origins, shared experiences and common themes emerged when we asked: “What does it mean to be Asian in America?”

In the fall of 2021, Pew Research Center undertook the largest focus group study it had ever conducted – 66 focus groups with 264 total participants – to hear Asian Americans talk about their lived experiences in America. The focus groups were organized into 18 distinct Asian ethnic origin groups, fielded in 18 languages and moderated by members of their own ethnic groups. Because of the pandemic, the focus groups were conducted virtually, allowing us to recruit participants from all parts of the United States. This approach allowed us to hear a diverse set of voices – especially from less populous Asian ethnic groups whose views, attitudes and opinions are seldom presented in traditional polling. The approach also allowed us to explore the reasons behind people’s opinions and choices about what it means to belong in America, beyond the preset response options of a traditional survey.

The terms “Asian,” “Asians living in the United States” and “Asian American” are used interchangeably throughout this essay to refer to U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic identity.

“The United States” and “the U.S.” are used interchangeably with “America” for variations in the writing.

Multiracial participants are those who indicate they are of two or more racial backgrounds (one of which is Asian). Multiethnic participants are those who indicate they are of two or more ethnicities, including those identified as Asian with Hispanic background.

U.S. born refers to people born in the 50 U.S. states or the District of Columbia, Puerto Rico, or other U.S. territories.

Immigrant refers to people who were not U.S. citizens at birth – in other words, those born outside the U.S., Puerto Rico or other U.S. territories to parents who were not U.S. citizens. The terms “immigrant,” “first generation” and “foreign born” are used interchangeably in this report.  

Second generation refers to people born in the 50 states or the District of Columbia with at least one first-generation, or immigrant, parent.

The pan-ethnic term “Asian American” describes the population of about 22 million people living in the United States who trace their roots to more than 20 countries in East and Southeast Asia and the Indian subcontinent. The term was popularized by U.S. student activists in the 1960s and was eventually adopted by the U.S. Census Bureau. However, the “Asian” label masks the diverse demographics and wide economic disparities across the largest national origin groups (such as Chinese, Indian, Filipino) and the less populous ones (such as Bhutanese, Hmong and Nepalese) living in America. It also hides the varied circumstances of groups immigrated to the U.S. and how they started their lives there. The population’s diversity often presents challenges . Conventional survey methods typically reflect the voices of larger groups without fully capturing the broad range of views, attitudes, life starting points and perspectives experienced by Asian Americans. They can also limit understanding of the shared experiences across this diverse population.

Across all focus groups, some common findings emerged. Participants highlighted how the pan-ethnic “Asian” label used in the U.S. represented only one part of how they think of themselves. For example, recently arrived Asian immigrant participants told us they are drawn more to their ethnic identity than to the more general, U.S.-created pan-ethnic Asian American identity. Meanwhile, U.S.-born Asian participants shared how they identified, at times, as Asian but also, at other times, by their ethnic origin and as Americans.

Another common finding among focus group participants is the disconnect they noted between how they see themselves and how others view them. Sometimes this led to maltreatment of them or their families, especially at heightened moments in American history such as during Japanese incarceration during World War II, the aftermath of 9/11 and, more recently, the COVID-19 pandemic. Beyond these specific moments, many in the focus groups offered their own experiences that had revealed other people’s assumptions or misconceptions about their identity.

Another shared finding is the multiple ways in which participants take and express pride in their cultural and ethnic backgrounds while also feeling at home in America, celebrating and blending their unique cultural traditions and practices with those of other Americans.

This focus group project is part of a broader research agenda about Asians living in the United States. The findings presented here offer a small glimpse of what participants told us, in their own words, about how they identify themselves, how others see and treat them, and more generally, what it means to be Asian in America.

Illustrations by Jing Li

Publications from the Being Asian in America project

• Read the data essay: What It Means to Be Asian in America
• Watch the documentary: Being Asian in America
• Explore the interactive: In Their Own Words: The Diverse Perspectives of Being Asian in America
• View expanded interviews: Extended Interviews: Being Asian in America
• About this research project: More on the Being Asian in America project
• Q&A: Why and how Pew Research Center conducted 66 focus groups with Asian Americans

One of the topics covered in each focus group was how participants viewed their own racial or ethnic identity. Moderators asked them how they viewed themselves, and what experiences informed their views about their identity. These discussions not only highlighted differences in how participants thought about their own racial or ethnic background, but they also revealed how different settings can influence how they would choose to identify themselves. Across all focus groups, the general theme emerged that being Asian was only one part of how participants viewed themselves.

The pan-ethnic label ‘Asian’ is often used more in formal settings

“I think when I think of the Asian Americans, I think that we’re all unique and different. We come from different cultures and backgrounds. We come from unique stories, not just as a group, but just as individual humans.” Mali , documentary participant

Many participants described a complicated relationship with the pan-ethnic labels “Asian” or “Asian American.” For some, using the term was less of an active choice and more of an imposed one, with participants discussing the disconnect between how they would like to identify themselves and the available choices often found in formal settings. For example, an immigrant Pakistani woman remarked how she typically sees “Asian American” on forms, but not more specific options. Similarly, an immigrant Burmese woman described her experience of applying for jobs and having to identify as “Asian,” as opposed to identifying by her ethnic background, because no other options were available. These experiences highlight the challenges organizations like government agencies and employers have in developing surveys or forms that ask respondents about their identity. A common sentiment is one like this:

“I guess … I feel like I just kind of check off ‘Asian’ [for] an application or the test forms. That’s the only time I would identify as Asian. But Asian is too broad. Asia is a big continent. Yeah, I feel like it’s just too broad. To specify things, you’re Taiwanese American, that’s exactly where you came from.”

–U.S.-born woman of Taiwanese origin in early 20s

Smaller ethnic groups default to ‘Asian’ since their groups are less recognizable

Other participants shared how their experiences in explaining the geographic location and culture of their origin country led them to prefer “Asian” when talking about themselves with others. This theme was especially prominent among those belonging to smaller origin groups such as Bangladeshis and Bhutanese. A Lao participant remarked she would initially say “Asian American” because people might not be familiar with “Lao.”

“​​[When I fill out] forms, I select ‘Asian American,’ and that’s why I consider myself as an Asian American. [It is difficult to identify as] Nepali American [since] there are no such options in forms. That’s why, Asian American is fine to me.”

–Immigrant woman of Nepalese origin in late 20s

“Coming to a big country like [the United States], when people ask where we are from … there are some people who have no idea about Bhutan, so we end up introducing ourselves as being Asian.”

–Immigrant woman of Bhutanese origin in late 40s

But for many, ‘Asian’ as a label or identity just doesn’t fit

Many participants felt that neither “Asian” nor “Asian American” truly captures how they view themselves and their identity. They argue that these labels are too broad or too ambiguous, as there are so many different groups included within these labels. For example, a U.S.-born Pakistani man remarked on how “Asian” lumps many groups together – that the term is not limited to South Asian groups such as Indian and Pakistani, but also includes East Asian groups. Similarly, an immigrant Nepalese man described how “Asian” often means Chinese for many Americans. A Filipino woman summed it up this way:

“Now I consider myself to be both Filipino and Asian American, but growing up in [Southern California] … I didn’t start to identify as Asian American until college because in [the Los Angeles suburb where I lived], it’s a big mix of everything – Black, Latino, Pacific Islander and Asian … when I would go into spaces where there were a lot of other Asians, especially East Asians, I didn’t feel like I belonged. … In media, right, like people still associate Asian with being East Asian.”

–U.S.-born woman of Filipino origin in mid-20s

Participants also noted they have encountered confusion or the tendency for others to view Asian Americans as people from mostly East Asian countries, such as China, Japan and Korea. For some, this confusion even extends to interactions with other Asian American groups. A Pakistani man remarked on how he rarely finds Pakistani or Indian brands when he visits Asian stores. Instead, he recalled mostly finding Vietnamese, Korean and Chinese items.

Among participants of South Asian descent, some identified with the label “South Asian” more than just “Asian.” There were other nuances, too, when it comes to the labels people choose. Some Indian participants, for example, said people sometimes group them with Native Americans who are also referred to as Indians in the United States. This Indian woman shared her experience at school:

“I love South Asian or ‘Desi’ only because up until recently … it’s fairly new to say South Asian. I’ve always said ‘Desi’ because growing up … I’ve had to say I’m the red dot Indian, not the feather Indian. So annoying, you know? … Always a distinction that I’ve had to make.”

–U.S.-born woman of Indian origin in late 20s

Participants with multiethnic or multiracial backgrounds described their own unique experiences with their identity. Rather than choosing one racial or ethnic group over the other, some participants described identifying with both groups, since this more accurately describes how they see themselves. In some cases, this choice reflected the history of the Asian diaspora. For example, an immigrant Cambodian man described being both Khmer/Cambodian and Chinese, since his grandparents came from China. Some other participants recalled going through an “identity crisis” as they navigated between multiple identities. As one woman explained:

“I would say I went through an identity crisis. … It’s because of being multicultural. … There’s also French in the mix within my family, too. Because I don’t identify, speak or understand the language, I really can’t connect to the French roots … I’m in between like Cambodian and Thai, and then Chinese and then French … I finally lumped it up. I’m just an Asian American and proud of all my roots.”

–U.S.-born woman of Cambodian origin in mid-30s

In other cases, the choice reflected U.S. patterns of intermarriage. Asian newlyweds have the highest intermarriage rate of any racial or ethnic group in the country. One Japanese-origin man with Hispanic roots noted:

“So I would like to see myself as a Hispanic Asian American. I want to say Hispanic first because I have more of my mom’s culture in me than my dad’s culture. In fact, I actually have more American culture than my dad’s culture for what I do normally. So I guess, Hispanic American Asian.”

–U.S.-born man of Hispanic and Japanese origin in early 40s

Other identities beyond race or ethnicity are also important

Focus group participants also talked about their identity beyond the racial or ethnic dimension. For example, one Chinese woman noted that the best term to describe her would be “immigrant.” Faith and religious ties were also important to some. One immigrant participant talked about his love of Pakistani values and how religion is intermingled into Pakistani culture. Another woman explained:

“[Japanese language and culture] are very important to me and ingrained in me because they were always part of my life, and I felt them when I was growing up. Even the word itadakimasu reflects Japanese culture or the tradition. Shinto religion is a part of the culture. They are part of my identity, and they are very important to me.”

–Immigrant woman of Japanese origin in mid-30s

For some, gender is another important aspect of identity. One Korean participant emphasized that being a woman is an important part of her identity. For others, sexual orientation is an essential part of their overall identity. One U.S.-born Filipino participant described herself as “queer Asian American.” Another participant put it this way:

“I belong to the [LGBTQ] community … before, what we only know is gay and lesbian. We don’t know about being queer, nonbinary. [Here], my horizon of knowing what genders and gender roles is also expanded … in the Philippines, if you’ll be with same sex, you’re considered gay or lesbian. But here … what’s happening is so broad, on how you identify yourself.”

–Immigrant woman of Filipino origin in early 20s

Immigrant identity is tied to their ethnic heritage

Participants born outside the United States tended to link their identity with their ethnic heritage. Some felt strongly connected with their ethnic ties due to their citizenship status. For others, the lack of permanent residency or citizenship meant they have stronger ties to their ethnicity and birthplace. And in some cases, participants said they held on to their ethnic identity even after they became U.S. citizens. One woman emphasized that she will always be Taiwanese because she was born there, despite now living in the U.S.

For other participants, family origin played a central role in their identity, regardless of their status in the U.S. According to some of them, this attitude was heavily influenced by their memories and experiences in early childhood when they were still living in their countries of origin. These influences are so profound that even after decades of living in the U.S., some still feel the strong connection to their ethnic roots. And those with U.S.-born children talked about sending their kids to special educational programs in the U.S. to learn about their ethnic heritage.

“Yes, as for me, I hold that I am Khmer because our nationality cannot be deleted, our identity is Khmer as I hold that I am Khmer … so I try, even [with] my children today, I try to learn Khmer through Zoom through the so-called Khmer Parent Association.”

–Immigrant man of Cambodian origin in late 50s

Navigating life in America is an adjustment

Many participants pointed to cultural differences they have noticed between their ethnic culture and U.S. culture. One of the most distinct differences is in food. For some participants, their strong attachment to the unique dishes of their families and their countries of origin helps them maintain strong ties to their ethnic identity. One Sri Lankan participant shared that her roots are still in Sri Lanka, since she still follows Sri Lankan traditions in the U.S. such as preparing kiribath (rice with coconut milk) and celebrating Ramadan.

For other participants, interactions in social settings with those outside their own ethnic group circles highlighted cultural differences. One Bangladeshi woman talked about how Bengalis share personal stories and challenges with each other, while others in the U.S. like to have “small talk” about TV series or clothes.

Many immigrants in the focus groups have found it is easier to socialize when they are around others belonging to their ethnicity. When interacting with others who don’t share the same ethnicity, participants noted they must be more self-aware about cultural differences to avoid making mistakes in social interactions. Here, participants described the importance of learning to “fit in,” to avoid feeling left out or excluded. One Korean woman said:

“Every time I go to a party, I feel unwelcome. … In Korea, when I invite guests to my house and one person sits without talking, I come over and talk and treat them as a host. But in the United States, I have to go and mingle. I hate mingling so much. I have to talk and keep going through unimportant stories. In Korea, I am assigned to a dinner or gathering. I have a party with a sense of security. In America, I have nowhere to sit, and I don’t know where to go and who to talk to.”

–Immigrant woman of Korean origin in mid-40s

And a Bhutanese immigrant explained:

“In my case, I am not an American. I consider myself a Bhutanese. … I am a Bhutanese because I do not know American culture to consider myself as an American. It is very difficult to understand the sense of humor in America. So, we are pure Bhutanese in America.”

–Immigrant man of Bhutanese origin in early 40s

Language was also a key aspect of identity for the participants. Many immigrants in the focus groups said they speak a language other than English at home and in their daily lives. One Vietnamese man considered himself Vietnamese since his Vietnamese is better than his English. Others emphasized their English skills. A Bangladeshi participant felt that she was more accepted in the workplace when she does more “American” things and speaks fluent English, rather than sharing things from Bangladeshi culture. She felt that others in her workplace correlate her English fluency with her ability to do her job. For others born in the U.S., the language they speak at home influences their connection to their ethnic roots.

“Now if I go to my work and do show my Bengali culture and Asian culture, they are not going to take anything out of it. So, basically, I have to show something that they are interested in. I have to show that I am American, [that] I can speak English fluently. I can do whatever you give me as a responsibility. So, in those cases I can’t show anything about my culture.”

–Immigrant woman of Bangladeshi origin in late 20s

“Being bi-ethnic and tri-cultural creates so many unique dynamics, and … one of the dynamics has to do with … what it is to be Americanized. … One of the things that played a role into how I associate the identity is language. Now, my father never spoke Spanish to me … because he wanted me to develop a fluency in English, because for him, he struggled with English. What happened was three out of the four people that raised me were Khmer … they spoke to me in Khmer. We’d eat breakfast, lunch and dinner speaking Khmer. We’d go to the temple in Khmer with the language and we’d also watch videos and movies in Khmer. … Looking into why I strongly identify with the heritage, one of the reasons is [that] speaking that language connects to the home I used to have [as my families have passed away].”

–U.S.-born man of Cambodian origin in early 30s

Balancing between individualistic and collective thinking

For some immigrant participants, the main differences between themselves and others who are seen as “truly American” were less about cultural differences, or how people behave, and more about differences in “mindset,” or how people think . Those who identified strongly with their ethnicity discussed how their way of thinking is different from a “typical American.” To some, the “American mentality” is more individualistic, with less judgment on what one should do or how they should act . One immigrant Japanese man, for example, talked about how other Japanese-origin co-workers in the U.S. would work without taking breaks because it’s culturally inconsiderate to take a break while others continued working. However, he would speak up for himself and other workers when they are not taking any work breaks. He attributed this to his “American” way of thinking, which encourages people to stand up for themselves.

Some U.S.-born participants who grew up in an immigrant family described the cultural clashes that happened between themselves and their immigrant parents. Participants talked about how the second generation (children of immigrant parents) struggles to pursue their own dreams while still living up to the traditional expectations of their immigrant parents.

“I feel like one of the biggest things I’ve seen, just like [my] Asian American friends overall, is the kind of family-individualistic clash … like wanting to do your own thing is like, is kind of instilled in you as an American, like go and … follow your dream. But then you just grow up with such a sense of like also wanting to be there for your family and to live up to those expectations, and I feel like that’s something that’s very pronounced in Asian cultures.”

–U.S.-born man of Indian origin in mid-20s

Discussions also highlighted differences about gender roles between growing up in America compared with elsewhere.

“As a woman or being a girl, because of your gender, you have to keep your mouth shut [and] wait so that they call on you for you to speak up. … I do respect our elders and I do respect hearing their guidance but I also want them to learn to hear from the younger person … because we have things to share that they might not know and that [are] important … so I like to challenge gender roles or traditional roles because it is something that [because] I was born and raised here [in America], I learn that we all have the equal rights to be able to speak and share our thoughts and ideas.”

U.S. born have mixed ties to their family’s heritage

“I think being Hmong is somewhat of being free, but being free of others’ perceptions of you or of others’ attempts to assimilate you or attempts to put pressure on you. I feel like being Hmong is to resist, really.” Pa Houa , documentary participant

How U.S.-born participants identify themselves depends on their familiarity with their own heritage, whom they are talking with, where they are when asked about their identity and what the answer is used for. Some mentioned that they have stronger ethnic ties because they are very familiar with their family’s ethnic heritage. Others talked about how their eating habits and preferred dishes made them feel closer to their ethnic identity. For example, one Korean participant shared his journey of getting closer to his Korean heritage because of Korean food and customs. When some participants shared their reasons for feeling closer to their ethnic identity, they also expressed a strong sense of pride with their unique cultural and ethnic heritage.

“I definitely consider myself Japanese American. I mean I’m Japanese and American. Really, ever since I’ve grown up, I’ve really admired Japanese culture. I grew up watching a lot of anime and Japanese black and white films. Just learning about [it], I would hear about Japanese stuff from my grandparents … myself, and my family having blended Japanese culture and American culture together.”

–U.S.-born man of Japanese origin in late 20s

Meanwhile, participants who were not familiar with their family’s heritage showed less connection with their ethnic ties. One U.S.-born woman said she has a hard time calling herself Cambodian, as she is “not close to the Cambodian community.” Participants with stronger ethnic ties talked about relating to their specific ethnic group more than the broader Asian group. Another woman noted that being Vietnamese is “more specific and unique than just being Asian” and said that she didn’t feel she belonged with other Asians. Some participants also disliked being seen as or called “Asian,” in part because they want to distinguish themselves from other Asian groups. For example, one Taiwanese woman introduces herself as Taiwanese when she can, because she had frequently been seen as Chinese.

Some in the focus groups described how their views of their own identities shifted as they grew older. For example, some U.S.-born and immigrant participants who came to the U.S. at younger ages described how their experiences in high school and the need to “fit in” were important in shaping their own identities. A Chinese woman put it this way:

“So basically, all I know is that I was born in the United States. Again, when I came back, I didn’t feel any barrier with my other friends who are White or Black. … Then I got a little confused in high school when I had trouble self-identifying if I am Asian, Chinese American, like who am I. … Should I completely immerse myself in the American culture? Should I also keep my Chinese identity and stuff like that? So yeah, that was like the middle of that mist. Now, I’m pretty clear about myself. I think I am Chinese American, Asian American, whatever people want.”

–U.S.-born woman of Chinese origin in early 20s

Identity is influenced by birthplace

“I identified myself first and foremost as American. Even on the forms that you fill out that says, you know, ‘Asian’ or ‘Chinese’ or ‘other,’ I would check the ‘other’ box, and I would put ‘American Chinese’ instead of ‘Chinese American.’” Brent , documentary participant

When talking about what it means to be “American,” participants offered their own definitions. For some, “American” is associated with acquiring a distinct identity alongside their ethnic or racial backgrounds, rather than replacing them. One Indian participant put it this way:

“I would also say [that I am] Indian American just because I find myself always bouncing between the two … it’s not even like dual identity, it just is one whole identity for me, like there’s not this separation. … I’m doing [both] Indian things [and] American things. … They use that term like ABCD … ‘American Born Confused Desi’ … I don’t feel that way anymore, although there are those moments … but I would say [that I am] Indian American for sure.”

–U.S.-born woman of Indian origin in early 30s

Meanwhile, some U.S.-born participants view being American as central to their identity while also valuing the culture of their family’s heritage.

Many immigrant participants associated the term “American” with immigration status or citizenship. One Taiwanese woman said she can’t call herself American since she doesn’t have a U.S. passport. Notably, U.S. citizenship is an important milestone for many immigrant participants, giving them a stronger sense of belonging and ultimately calling themselves American. A Bangladeshi participant shared that she hasn’t received U.S. citizenship yet, and she would call herself American after she receives her U.S. passport.

Other participants gave an even narrower definition, saying only those born and raised in the United States are truly American. One Taiwanese woman mentioned that her son would be American since he was born, raised and educated in the U.S. She added that while she has U.S. citizenship, she didn’t consider herself American since she didn’t grow up in the U.S. This narrower definition has implications for belonging. Some immigrants in the groups said they could never become truly American since the way they express themselves is so different from those who were born and raised in the U.S. A Japanese woman pointed out that Japanese people “are still very intimidated by authorities,” while those born and raised in America give their opinions without hesitation.

“As soon as I arrived, I called myself a Burmese immigrant. I had a green card, but I still wasn’t an American citizen. … Now I have become a U.S. citizen, so now I am a Burmese American.”

–Immigrant man of Burmese origin in mid-30s

“Since I was born … and raised here, I kind of always view myself as American first who just happened to be Asian or Chinese. So I actually don’t like the term Chinese American or Asian American. I’m American Asian or American Chinese. I view myself as American first.”

–U.S.-born man of Chinese origin in early 60s

“[I used to think of myself as] Filipino, but recently I started saying ‘Filipino American’ because I got [U.S.] citizenship. And it just sounds weird to say Filipino American, but I’m trying to … I want to accept it. I feel like it’s now marry-able to my identity.”

–Immigrant woman of Filipino origin in early 30s

For others, American identity is about the process of ‘becoming’ culturally American

Immigrant participants also emphasized how their experiences and time living in America inform their views of being an “American.” As a result, some started to see themselves as Americans after spending more than a decade in the U.S. One Taiwanese man considered himself an American since he knows more about the U.S. than Taiwan after living in the U.S. for over 52 years.

But for other immigrant participants, the process of “becoming” American is not about how long they have lived in the U.S., but rather how familiar they are with American culture and their ability to speak English with little to no accent. This is especially true for those whose first language is not English, as learning and speaking it without an accent can be a big challenge for some. One Bangladeshi participant shared that his pronunciation of “hot water” was very different from American English, resulting in confusions in communication. By contrast, those who were more confident in their English skills felt they can better understand American culture and values as a result, leading them to a stronger connection with an American identity.

“[My friends and family tease me for being Americanized when I go back to Japan.] I think I seem a little different to people who live in Japan. I don’t think they mean anything bad, and they [were] just joking, because I already know that I seem a little different to people who live in Japan.”

–Immigrant man of Japanese origin in mid-40s

“I value my Hmong culture, and language, and ethnicity, but I also do acknowledge, again, that I was born here in America and I’m grateful that I was born here, and I was given opportunities that my parents weren’t given opportunities for.”

–U.S.-born woman of Hmong origin in early 30s

During the focus group discussions about identity, a recurring theme emerged about the difference between how participants saw themselves and how others see them. When asked to elaborate on their experiences and their points of view, some participants shared experiences they had with people misidentifying their race or ethnicity. Others talked about their frustration with being labeled the “model minority.” In all these discussions, participants shed light on the negative impacts that mistaken assumptions and labels had on their lives.

All people see is ‘Asian’

For many, interactions with others (non-Asians and Asians alike) often required explaining their backgrounds, reacting to stereotypes, and for those from smaller origin groups in particular, correcting the misconception that being “Asian” means you come from one of the larger Asian ethnic groups. Several participants remarked that in their own experiences, when others think about Asians, they tend to think of someone who is Chinese. As one immigrant Filipino woman put it, “Interacting with [non-Asians in the U.S.], it’s hard. … Well, first, I look Spanish. I mean, I don’t look Asian, so would you guess – it’s like they have a vision of what an Asian [should] look like.” Similarly, an immigrant Indonesian man remarked how Americans tended to see Asians primarily through their physical features, which not all Asian groups share.

Several participants also described how the tendency to view Asians as a monolithic group can be even more common in the wake of the COVID-19 pandemic.

“The first [thing people think of me as] is just Chinese. ‘You guys are just Chinese.’ I’m not the only one who felt [this] after the COVID-19 outbreak. ‘Whether you’re Japanese, Korean, or Southeast Asian, you’re just Chinese [to Americans]. I should avoid you.’ I’ve felt this way before, but I think I’ve felt it a bit more after the COVID-19 outbreak.”

–Immigrant woman of Korean origin in early 30s

At the same time, other participants described their own experiences trying to convince others that they are Asian or Asian American. This was a common experience among Southeast Asian participants.

“I have to convince people I’m Asian, not Middle Eastern. … If you type in Asian or you say Asian, most people associate it with Chinese food, Japanese food, karate, and like all these things but then they don’t associate it with you.”

–U.S.-born man of Pakistani origin in early 30s

The model minority myth and its impact

“I’ve never really done the best academically, compared to all my other Asian peers too. I never really excelled. I wasn’t in honors. … Those stereotypes, I think really [have] taken a toll on my self-esteem.” Diane , documentary participant

Across focus groups, immigrant and U.S.-born participants described the challenges of the seemingly positive stereotypes of Asians as intelligent, gifted in technical roles and hardworking. Participants often referred to this as the “model minority myth.”

The label “model minority” was coined in the 1960s and has been used to characterize Asian Americans as financially and educationally successful and hardworking when compared with other groups. However, for many Asians living in the United States, these characterizations do not align with their lived experiences or reflect their socioeconomic backgrounds. Indeed, among Asian origin groups in the U.S., there are wide differences in economic and social experiences. 

Academic research on the model minority myth has pointed to its impact beyond Asian Americans and towards other racial and ethnic groups, especially Black Americans, in the U.S. Some argue that the model minority myth has been used to justify policies that overlook the historical circumstances and impacts of colonialism, slavery, discrimination and segregation on other non-White racial and ethnic groups.

Many participants noted ways in which the model minority myth has been harmful. For some, expectations based on the myth didn’t match their own experiences of coming from impoverished communities. Some also recalled experiences at school when they struggled to meet their teachers’ expectations in math and science.

“As an Asian person, I feel like there’s that stereotype that Asian students are high achievers academically. They’re good at math and science. … I was a pretty mediocre student, and math and science were actually my weakest subjects, so I feel like it’s either way you lose. Teachers expect you to fit a certain stereotype and if you’re not, then you’re a disappointment, but at the same time, even if you are good at math and science, that just means that you’re fitting a stereotype. It’s [actually] your own achievement, but your teachers might think, ‘Oh, it’s because they’re Asian,’ and that diminishes your achievement.”

–U.S.-born woman of Korean origin in late 20s

Some participants felt that even when being Asian worked in their favor in the job market, they encountered stereotypes that “Asians can do quality work with less compensation” or that “Asians would not complain about anything at work.”

“There is a joke from foreigners and even Asian Americans that says, ‘No matter what you do, Asians always do the best.’ You need to get A, not just B-plus. Otherwise, you’ll be a disgrace to the family. … Even Silicon Valley hires Asian because [an] Asian’s wage is cheaper but [they] can work better. When [work] visa overflow happens, they hire Asians like Chinese and Indian to work in IT fields because we are good at this and do not complain about anything.”

–Immigrant man of Thai origin in early 40s

Others expressed frustration that people were placing them in the model minority box. One Indian woman put it this way:

“Indian people and Asian people, like … our parents or grandparents are the ones who immigrated here … against all odds. … A lot of Indian and Asian people have succeeded and have done really well for themselves because they’ve worked themselves to the bone. So now the expectations [of] the newer generations who were born here are incredibly unrealistic and high. And you get that not only from your family and the Indian community, but you’re also getting it from all of the American people around you, expecting you to be … insanely good at math, play an instrument, you know how to do this, you know how to do that, but it’s not true. And it’s just living with those expectations, it’s difficult.”

–U.S.-born woman of Indian origin in early 20s

Whether U.S. born or immigrants, Asians are often seen by others as foreigners

“Being only not quite 10 years old, it was kind of exciting to ride on a bus to go someplace. But when we went to Pomona, the assembly center, we were stuck in one of the stalls they used for the animals.” Tokiko , documentary participant

Across all focus groups, participants highlighted a common question they are asked in America when meeting people for the first time: “Where are you really from?” For participants, this question implied that people think they are “foreigners,” even though they may be longtime residents or citizens of the United States or were born in the country. One man of Vietnamese origin shared his experience with strangers who assumed that he and his friends are North Korean. Perhaps even more hurtful, participants mentioned that this meant people had a preconceived notion of what an “American” is supposed to look like, sound like or act like. One Chinese woman said that White Americans treated people like herself as outsiders based on her skin color and appearance, even though she was raised in the U.S.

Many focus group participants also acknowledged the common stereotype of treating Asians as “forever foreigners.” Some immigrant participants said they felt exhausted from constantly being asked this question by people even when they speak perfect English with no accent. During the discussion, a Korean immigrant man recalled that someone had said to him, “You speak English well, but where are you from?” One Filipino participant shared her experience during the first six months in the U.S.:

“You know, I spoke English fine. But there were certain things that, you know, people constantly questioning you like, oh, where are you from? When did you come here? You know, just asking about your experience to the point where … you become fed up with it after a while.”

–Immigrant woman of Filipino origin in mid-30s

U.S.-born participants also talked about experiences when others asked where they are from. Many shared that they would not talk about their ethnic origin right away when answering such a question because it often led to misunderstandings and assumptions that they are immigrants.

“I always get that question of, you know, ‘Where are you from?’ and I’m like, ‘I’m from America.’ And then they’re like, ‘No. Where are you from-from ?’ and I’m like, ‘Yeah, my family is from Pakistan,’ so it’s like I always had like that dual identity even though it’s never attached to me because I am like, of Pakistani descent.”

–U.S.-born man of Pakistani origin in early 20s

One Korean woman born in the U.S. said that once people know she is Korean, they ask even more offensive questions such as “Are you from North or South Korea?” or “Do you still eat dogs?”

In a similar situation, this U.S.-born Indian woman shared her responses:

“I find that there’s a, ‘So but where are you from?’ Like even in professional settings when they feel comfortable enough to ask you. ‘So – so where are you from?’ ‘Oh, I was born in [names city], Colorado. Like at [the hospital], down the street.’ ‘No, but like where are you from?’ ‘My mother’s womb?’”

–U.S.-born woman of Indian origin in early 40s

Ignorance and misinformation about Asian identity can lead to contentious encounters

“I have dealt with kids who just gave up on their Sikh identity, cut their hair and groomed their beard and everything. They just wanted to fit in and not have to deal with it, especially [those] who are victim or bullied in any incident.” Surinder , documentary participant

In some cases, ignorance and misinformation about Asians in the U.S. lead to inappropriate comments or questions and uncomfortable or dangerous situations. Participants shared their frustration when others asked about their country of origin, and they then had to explain their identity or correct misunderstandings or stereotypes about their background. At other times, some participants faced ignorant comments about their ethnicity, which sometimes led to more contentious encounters. For example, some Indian or Pakistani participants talked about the attacks or verbal abuse they experienced from others blaming them for the 9/11 terrorist attacks. Others discussed the racial slurs directed toward them since the COVID-19 pandemic in 2020. Some Japanese participants recalled their families losing everything and being incarcerated during World War II and the long-term effect it had on their lives.

“I think like right now with the coronavirus, I think we’re just Chinese, Chinese American, well, just Asian American or Asians in general, you’re just going through the same struggles right now. Like everyone is just blaming whoever looks Asian about the virus. You don’t feel safe.”

–U.S.-born man of Chinese origin in early 30s

“At the beginning of the pandemic, a friend and I went to celebrate her birthday at a club and like these guys just kept calling us COVID.”

–U.S.-born woman of Korean origin in early 20s

“There [were] a lot of instances after 9/11. One day, somebody put a poster about 9/11 [in front of] my business. He was wearing a gun. … On the poster, it was written ‘you Arabs, go back to your country.’ And then someone came inside. He pointed his gun at me and said ‘Go back to your country.’”

–Immigrant man of Pakistani origin in mid-60s

“[My parents went through the] internment camps during World War II. And my dad, he was in high school, so he was – they were building the camps and then he was put into the Santa Anita horse track place, the stables there. And then they were sent – all the Japanese Americans were sent to different camps, right, during World War II and – in California. Yeah, and they lost everything, yeah.”

–U.S.-born woman of Japanese origin in mid-60s

As focus group participants contemplated their identity during the discussions, many talked about their sense of belonging in America. Although some felt frustrated with people misunderstanding their ethnic heritage, they didn’t take a negative view of life in America. Instead, many participants – both immigrant and U.S. born – took pride in their unique cultural and ethnic backgrounds. In these discussions, people gave their own definitions of America as a place with a diverse set of cultures, with their ethnic heritage being a part of it.

Taking pride in their unique cultures

“Being a Pakistani American, I’m proud. … Because I work hard, and I make true my dreams from here.” Shahid , documentary participant

Despite the challenges of adapting to life in America for immigrant participants or of navigating their dual cultural identity for U.S.-born ones, focus group participants called America their home. And while participants talked about their identities in different ways – ethnic identity, racial (Asian) identity, and being American – they take pride in their unique cultures. Many also expressed a strong sense of responsibility to give back or support their community, sharing their cultural heritage with others on their own terms.

“Right now it has been a little difficult. I think it has been for all Asians because of the COVID issue … but I’m glad that we’re all here [in America]. I think we should be proud to be here. I’m glad that our families have traveled here, and we can help make life better for communities, our families and ourselves. I think that’s really a wonderful thing. We can be those role models for a lot of the future, the younger folks. I hope that something I did in the last years will have impacted either my family, friends or students that I taught in other community things that I’ve done. So you hope that it helps someplace along the line.”

“I am very proud of my culture. … There is not a single Bengali at my workplace, but people know the name of my country. Maybe many years [later] – educated people know all about the country. So, I don’t have to explain that there is a small country next to India and Nepal. It’s beyond saying. People after all know Bangladesh. And there are so many Bengali present here as well. So, I am very proud to be a Bangladeshi.”

Where home is

When asked about the definition of home, some immigrant participants said home is where their families are located. Immigrants in the focus groups came to the United States by various paths, whether through work opportunities, reuniting with family or seeking a safe haven as refugees. Along their journey, some received support from family members, their local community or other individuals, while others overcame challenges by themselves. Either way, they take pride in establishing their home in America and can feel hurt when someone tells them to “go back to your country.” In response, one Laotian woman in her mid-40s said, “This is my home. My country. Go away.”

“If you ask me personally, I view my home as my house … then I would say my house is with my family because wherever I go, I cannot marry if I do not have my family so that is how I would answer.”

–Immigrant man of Hmong origin in late 30s

“[If somebody yelled at me ‘go back to your country’] I’d feel angry because this is my country! I live here. America is my country. I grew up here and worked here … I’d say, ‘This is my country! You go back to your country! … I will not go anywhere. This is my home. I will live here.’ That’s what I’d say.”

–Immigrant woman of Laotian origin in early 50s

‘American’ means to blend their unique cultural and ethnic heritage with that in the U.S.

“I want to teach my children two traditions – one American and one Vietnamese – so they can compare and choose for themselves the best route in life.” Helen , documentary participant (translated from Vietnamese)

Both U.S.-born and immigrant participants in the focus groups shared their experiences of navigating a dual cultural environment between their ethnic heritage and American culture. A common thread that emerged was that being Asian in America is a process of blending two or more identities as one.

“Yeah, I want to say that’s how I feel – because like thinking about it, I would call my dad Lao but I would call myself Laotian American because I think I’m a little more integrated in the American society and I’ve also been a little more Americanized, compared to my dad. So that’s how I would see it.”

–U.S.-born man of Laotian origin in late 20s

“I mean, Bangladeshi Americans who are here, we are carrying Bangladeshi culture, religion, food. I am also trying to be Americanized like the Americans. Regarding language, eating habits.”

–Immigrant man of Bangladeshi origin in mid-50s

“Just like there is Chinese American, Mexican American, Japanese American, Italian American, so there is Indian American. I don’t want to give up Indianness. I am American by nationality, but I am Indian by birth. So whenever I talk, I try to show both the flags as well, both Indian and American flags. Just because you make new relatives but don’t forget the old relatives.”

–Immigrant man of Indian origin in late 40s

Pew Research Center designed these focus groups to better understand how members of an ethnically diverse Asian population think about their place in America and life here. By including participants of different languages, immigration or refugee experiences, educational backgrounds, and income levels, this focus group study aimed to capture in people’s own words what it means to be Asian in America. The discussions in these groups may or may not resonate with all Asians living in the United States. Browse excerpts from our focus groups with the interactive quote sorter below, view a video documentary focused on the topics discussed in the focus groups, or tell us your story of belonging in America via social media. The focus group project is part of a broader research project studying the diverse experiences of Asians living in the U.S.

Read sortable quotes from our focus groups

Browse excerpts in the interactive quote sorter from focus group participants in response to the question “What does it mean to be [Vietnamese, Thai, Sri Lankan, Hmong, etc.] like yourself in America?” This interactive allows you to sort quotes from focus group participants by ethnic origin, nativity (U.S. born or born in another country), gender and age.

Video documentary

Videos throughout the data essay illustrate what focus group participants discussed. Those recorded in these videos did not participate in the focus groups but were sampled to have similar demographic characteristics and thematically relevant stories.

Watch the full video documentary and watch additional shorter video clips related to the themes of this data essay.

Share the story of your family and your identity

Did the voices in this data essay resonate? Share your story of what it means to be Asian in America with @pewresearch. Tell us your story by using the hashtag #BeingAsianInAmerica and @pewidentity on Twitter, as well as #BeingAsianInAmerica and @pewresearch on Instagram.

This cross-ethnic, comparative qualitative research project explores the identity, economic mobility, representation, and experiences of immigration and discrimination among the Asian population in the United States. The analysis is based on 66 focus groups we conducted virtually in the fall of 2021 and included 264 participants from across the U.S. More information about the groups and analysis can be found in this appendix .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. This data essay was funded by The Pew Charitable Trusts, with generous support from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation; the Robert Wood Johnson Foundation; the Henry Luce Foundation; The Wallace H. Coulter Foundation; The Dirk and Charlene Kabcenell Foundation; The Long Family Foundation; Lu-Hebert Fund; Gee Family Foundation; Joseph Cotchett; the Julian Abdey and Sabrina Moyle Charitable Fund; and Nanci Nishimura.

The accompanying video clips and video documentary were made possible by The Pew Charitable Trusts, with generous support from The Sobrato Family Foundation and The Long Family Foundation.

We would also like to thank the Leaders Forum for its thought leadership and valuable assistance in helping make this study possible. This is a collaborative effort based on the input and analysis of a number of individuals and experts at Pew Research Center and outside experts.

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Title: enhancing legal compliance and regulation analysis with large language models.

Abstract: This research explores the application of Large Language Models (LLMs) for automating the extraction of requirement-related legal content in the food safety domain and checking legal compliance of regulatory artifacts. With Industry 4.0 revolutionizing the food industry and with the General Data Protection Regulation (GDPR) reshaping privacy policies and data processing agreements, there is a growing gap between regulatory analysis and recent technological advancements. This study aims to bridge this gap by leveraging LLMs, namely BERT and GPT models, to accurately classify legal provisions and automate compliance checks. Our findings demonstrate promising results, indicating LLMs' significant potential to enhance legal compliance and regulatory analysis efficiency, notably by reducing manual workload and improving accuracy within reasonable time and financial constraints.

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