{"id":967,"date":"2026-06-22T08:43:20","date_gmt":"2026-06-22T08:43:20","guid":{"rendered":"https:\/\/www.editage.com\/blog\/?p=967"},"modified":"2026-06-22T08:43:22","modified_gmt":"2026-06-22T08:43:22","slug":"results-section-research-paper","status":"publish","type":"post","link":"https:\/\/www.editage.com\/blog\/results-section-research-paper\/","title":{"rendered":"How to Write the Results Section of a Research Paper: Tips, Examples, Guidelines"},"content":{"rendered":"\n<p>Contents<\/p>\n\n\n\n<ul><li><a href=\"#_Toc233029989\">Glossary of Key Terms<\/a><\/li><li><a href=\"#_Toc233029990\">Key Takeaways<\/a><\/li><li><a href=\"#_Toc233029991\">What Is the Results Section and What Belongs in It?<\/a><\/li><li><a href=\"#_Toc233029992\">How Do Quantitative Results Differ from Other Study Types?<\/a><\/li><li><a href=\"#_Toc233029993\">How Should Qualitative Results Be Presented?<\/a><\/li><li><a href=\"#_Toc233029994\">Mixed-Methods Results: How Are Both Strands Integrated?<\/a><\/li><li><a href=\"#_Toc233029995\">What Belongs in the Results Section of a Literature Review or Systematic Review?<\/a><\/li><li><a href=\"#_Toc233029996\">Figures and Tables: When to Use Each<\/a><\/li><li><a href=\"#_Toc233029997\">Reporting Checklists: Which Ones Apply to the Results Section?<\/a><\/li><li><a href=\"#_Toc233029998\">How to Write Your First Results Section<\/a><\/li><li><a href=\"#_Toc233029999\">Parallel Structure and Language Conventions<\/a><\/li><li><a href=\"#_Toc233030000\">Subgroup Analyses, Secondary Outcomes, and Exploratory Findings: How Should These Be Labeled?<\/a><\/li><li><a href=\"#_Toc233030001\">Participant Flow and Attrition: What Must Be Reported?<\/a><\/li><li><a href=\"#_Toc233030002\">Frequently Asked Questions<\/a><\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029989\">Glossary of Key Terms<\/a><\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Term<\/strong><\/td><td><strong>Definition<\/strong><\/td><\/tr><\/thead><tbody><tr><td><a href=\"https:\/\/www.editage.com\/blog\/what-is-confidence-intervals-and-why-is-it-important\/\">Confidence Interval<\/a> (CI)<\/td><td>A range of values, derived from sample data, that is likely to contain the true population parameter with a specified probability (e.g., 95% CI).<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/blog\/effect-size\/\">Effect Size<\/a><\/td><td>A quantitative measure of the magnitude of a result or relationship, independent of <a href=\"https:\/\/www.editage.com\/insights\/an-introduction-to-sample-size-effect-size-and-statistical-power-for-biomedical-researchers\">sample size<\/a> (e.g., Cohen&#8217;s d, odds ratio, eta-squared).<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/insights\/how-can-i-publish-negative-results\">Null Result<\/a><\/td><td>A finding in which no statistically significant difference or relationship was detected; equally valid and publishable as significant results.<\/td><\/tr><tr><td>Participant Flow<\/td><td>A description or diagram tracking how many participants entered, completed, and exited each stage of a study.<\/td><\/tr><tr><td><a href=\"https:\/\/researcher.life\/blog\/article\/what-is-p-value-calculation-statistical-significance\/\">p-value<\/a><\/td><td>The probability of observing data at least as extreme as the actual data, assuming the null hypothesis is true. Does not measure effect size or practical significance.<\/td><\/tr><tr><td>Primary Outcome<\/td><td>The main variable the study was designed to measure; determines sample size and is pre-specified before data collection.<\/td><\/tr><tr><td>Secondary Outcome<\/td><td>Additional variables measured alongside the primary outcome; reported after primary results.<\/td><\/tr><tr><td>Reporting Checklist<\/td><td>A structured list of items that authors must address when writing up a study; specific to study design (e.g., CONSORT for RCTs, PRISMA for systematic reviews).<\/td><\/tr><tr><td>Statistical Significance<\/td><td>A result unlikely to have occurred by chance, conventionally defined as p &lt; 0.05, though this threshold is increasingly questioned.<\/td><\/tr><tr><td>Subgroup Analysis<\/td><td>Analysis of results within a defined subset of participants; must be pre-specified or clearly labeled as exploratory.<\/td><\/tr><tr><td><a href=\"https:\/\/researcher.life\/blog\/article\/what-is-thematic-analysis-and-how-to-do-it-with-examples\/\">Thematic Analysis<\/a><\/td><td>A qualitative method for identifying, analyzing, and reporting patterns (themes) within data.<\/td><\/tr><tr><td>CONSORT<\/td><td>Consolidated Standards of Reporting Trials: a 25-item checklist for randomized controlled trials.<\/td><\/tr><tr><td>PRISMA<\/td><td>Preferred Reporting Items for Systematic reviews and Meta-Analyses: a 27-item checklist for systematic reviews.<\/td><\/tr><tr><td>STROBE<\/td><td>Strengthening the Reporting of Observational Studies in Epidemiology: a 22-item checklist for observational studies.<\/td><\/tr><tr><td>COREQ<\/td><td>Consolidated Criteria for Reporting Qualitative Research: a 32-item checklist for qualitative studies.<\/td><\/tr><tr><td>TRIPOD<\/td><td>Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis: for prediction model studies.<\/td><\/tr><tr><td>Forest Plot<\/td><td>A graphical display of results from multiple studies in a meta-analysis, showing individual and pooled effect sizes.<\/td><\/tr><tr><td>GRADE<\/td><td>Grading of Recommendations Assessment, Development and Evaluation: a framework for rating the certainty of evidence in systematic reviews.<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/blog\/mixed-methods-research\/\">Mixed Methods<\/a><\/td><td>Research that combines both quantitative and qualitative data collection and analysis within a single study.<\/td><\/tr><tr><td><a href=\"https:\/\/researcher.life\/blog\/article\/what-is-data-saturation-definition-types-examples-indicators\/\">Saturation<\/a><\/td><td>In <a href=\"https:\/\/researcher.life\/blog\/article\/what-is-quantitative-research-types-and-examples\/\">qualitative research<\/a>, the point at which no new themes or information emerge from additional data collection.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2><a id=\"_Toc233029990\">Key Takeaways<\/a><\/h2>\n\n\n\n<ul><li>The Results section of a <a href=\"https:\/\/www.editage.com\/blog\/how-to-write-a-good-research-paper\/\">research paper<\/a> reports findings only; interpretation and explanation belong in the Discussion section.<\/li><li>Every result presented must trace directly back to a research question or hypothesis stated in the Introduction.<\/li><li>Use figures and tables to present complex data; use prose to highlight the most important findings.<\/li><li>Report effect sizes and confidence intervals alongside p-values for all inferential statistics.<\/li><li>Null results must be reported with the same rigor and space as significant results.<\/li><li>Qualitative results require evidence, such as illustrative quotes, to support each identified theme.<\/li><li>Mixed-methods results should present quantitative and qualitative strands separately before integrating them.<\/li><li>Literature review and systematic review results center on the search process, study characteristics, and synthesis.<\/li><li>Reporting checklists are not optional: journals increasingly require completed checklists at submission.<\/li><li>Common omissions across all study designs include missing participant flow data, absent effect sizes, and <a href=\"https:\/\/researcher.life\/blog\/article\/what-is-attrition-bias-definition-causes-examples-mitigation-strategies\/\">unreported attrition<\/a>.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029991\">What Is the Results Section and What Belongs in It?<\/a><\/h2>\n\n\n\n<p>The Results section is where you present your findings objectively, without interpretation. Its sole purpose is to answer: what did the data show? Everything that does not directly present a finding belongs elsewhere: methods go in the <a href=\"https:\/\/www.editage.com\/blog\/methods-section-research-paper\/\">Methods section<\/a>, explanations go in the Discussion, and implications go in the Conclusion.<\/p>\n\n\n\n<h3>The Core Function of a Results Section<\/h3>\n\n\n\n<ul><li>Answers every research question and tests every hypothesis stated in <a href=\"https:\/\/www.editage.com\/blog\/introduction-research-paper\/\">the Introduction.<\/a><\/li><li>Presents data in the sequence that matches the research questions, not in the order data were collected.<\/li><li>Provides enough detail for a reader to independently evaluate the findings.<\/li><li>Refers to all tables and figures in the order they appear, without reproducing their content verbatim in prose.<\/li><\/ul>\n\n\n\n<h3>What Does Not Belong in the Results Section?<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Do NOT Include<\/strong><\/td><td><strong>Where It Belongs Instead<\/strong><\/td><\/tr><\/thead><tbody><tr><td>Why results came out the way they did<\/td><td>Discussion section<\/td><\/tr><tr><td>Comparison to prior literature<\/td><td>Discussion section<\/td><\/tr><tr><td>Limitations of the study<\/td><td>Discussion or Limitations section<\/td><\/tr><tr><td>Implications or recommendations<\/td><td>Conclusion section<\/td><\/tr><tr><td>Methodological detail about how data were collected<\/td><td>Methods section<\/td><\/tr><tr><td>Raw data files or full transcripts<\/td><td><a href=\"https:\/\/researcher.life\/blog\/article\/research-paper-appendix\/\">Supplementary appendices<\/a><\/td><\/tr><tr><td>Speculation about unexpected findings<\/td><td>Discussion section<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>How to Structure the Results Section<\/h3>\n\n\n\n<ul><li>Open with a brief statement reminding readers of the study aim (one to two sentences maximum).<\/li><li>If applicable, report participant characteristics and sample demographics first.<\/li><li>Report primary outcomes before secondary outcomes.<\/li><li>Use subheadings that mirror research questions when there are multiple distinct outcomes.<\/li><li>End each sub-result with a clear factual summary sentence before moving to the next.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029992\">How Do Quantitative Results Differ from Other Study Types?<\/a><\/h2>\n\n\n\n<p>Quantitative results differ from qualitative and mixed-methods results because they center on numerical data, statistical tests, and effect sizes. The key principle is: never report a statistical test result without also reporting the descriptive statistics that contextualize it.<\/p>\n\n\n\n<h3>Reporting <a href=\"https:\/\/www.editage.com\/blog\/what-are-descriptive-statistics-types-choosing-reporting\/\">Descriptive Statistics<\/a><\/h3>\n\n\n\n<ul><li>Report measures of central tendency (mean, median) and spread (standard deviation, interquartile range) for all key variables.<\/li><li>Use mean and SD for normally distributed data; use median and IQR for skewed data.<\/li><li>Report frequencies and percentages for categorical variables.<\/li><li>Always state the sample size (n) alongside any statistic.<\/li><\/ul>\n\n\n\n<h3>Reporting <a href=\"https:\/\/www.editage.com\/blog\/guide-to-types-of-inferential-statistics-for-biomedical-researchers\/\">Inferential Statistics<\/a><\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Statistic Type<\/strong><\/td><td><strong>Required Elements<\/strong><\/td><td><strong>Example in Text<\/strong><\/td><\/tr><\/thead><tbody><tr><td>t-test<\/td><td>t, df, p, Cohen&#8217;s d<\/td><td>t(48) = 3.21, p = .002, d = 0.91<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/blog\/anova-types-uses-assumptions-a-quick-guide-for-biomedical-researchers\/\">ANOVA<\/a><\/td><td>F, df (between, within), p, eta-squared or partial eta-squared<\/td><td>F(2, 147) = 8.44, p &lt; .001, \u03b7\u00b2p = .10<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/blog\/chi-square-test-types-explained-for-biomedical-researchers\/\">Chi-square<\/a><\/td><td>\u03c7\u00b2, df, p, Cramer&#8217;s V or phi<\/td><td>\u03c7\u00b2(1, N = 200) = 12.3, p &lt; .001, \u03c6 = .25<\/td><\/tr><tr><td>Pearson correlation<\/td><td>r, df or n, p, 95% CI<\/td><td>r(98) = .42, p &lt; .001, 95% CI [.24, .57]<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/blog\/what-is-regression-and-types-of-regression-for-biomedical-researchers\/\">Regression<\/a> (coefficient)<\/td><td>b or \u03b2, SE, t, p, 95% CI<\/td><td>\u03b2 = .31, SE = .07, t(99) = 4.43, p &lt; .001<\/td><\/tr><tr><td><a href=\"https:\/\/www.editage.com\/blog\/what-is-regression-and-types-of-regression-for-biomedical-researchers\/\">Regression (model)<\/a><\/td><td>R\u00b2, F, df, p<\/td><td>R\u00b2 = .22, F(3, 96) = 9.07, p &lt; .001<\/td><\/tr><tr><td>Mann-Whitney U<\/td><td>U, z, p, r (effect size)<\/td><td>U = 1204, z = -2.87, p = .004, r = .29<\/td><\/tr><tr><td>Logistic regression<\/td><td>OR, 95% CI, p, Nagelkerke R\u00b2<\/td><td>OR = 2.14, 95% CI [1.32, 3.47], p = .002<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>Common Mistakes in Quantitative Results<\/h3>\n\n\n\n<ul><li>Reporting only p-values without effect sizes or confidence intervals.<\/li><li>Using p = .000 instead of p &lt; .001.<\/li><li>Failing to report the test statistic (t, F, U, etc.) alongside the p-value.<\/li><li>Reporting means without standard deviations.<\/li><li>Not clarifying whether standard deviation or standard error is reported.<\/li><li>Presenting only significant results and omitting non-significant ones.<\/li><li>Repeating in prose every number already in a table, instead of highlighting key values.<\/li><\/ul>\n\n\n\n<h3>Figures and Tables for Quantitative Results<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Visual Type<\/strong><\/td><td><strong>Best Used For<\/strong><\/td><td><strong>Notes<\/strong><\/td><\/tr><\/thead><tbody><tr><td>Bar chart<\/td><td>Comparing means across groups<\/td><td>Include error bars showing 95% CI or SD; label the error bar type<\/td><\/tr><tr><td>Box plot<\/td><td>Showing distribution, median, and outliers<\/td><td>Preferred over bar charts for skewed data<\/td><\/tr><tr><td>Scatter plot<\/td><td>Showing relationships between two continuous variables<\/td><td>Add a regression line with equation and R\u00b2 when relevant<\/td><\/tr><tr><td>Line graph<\/td><td>Showing change over time or dose-response relationships<\/td><td>Use for repeated measures or time-series data<\/td><\/tr><tr><td>Histogram<\/td><td>Showing data distribution<\/td><td>Use to illustrate normality or skewness<\/td><\/tr><tr><td>Heat map<\/td><td>Showing correlation matrices or multi-variable patterns<\/td><td>Label all cells; include a color-scale legend<\/td><\/tr><tr><td>Table: descriptive stats<\/td><td>Reporting means, SDs, frequencies per group<\/td><td>One row per variable; columns per group<\/td><\/tr><tr><td>Table: regression results<\/td><td>Multiple predictors and their coefficients<\/td><td>Include B, SE, \u03b2, t, p, and 95% CI columns<\/td><\/tr><tr><td>Table: correlation matrix<\/td><td>Showing all pairwise correlations<\/td><td>Use asterisks for significance; include a footnote key<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2><a id=\"_Toc233029993\">How Should Qualitative Results Be Presented?<\/a><\/h2>\n\n\n\n<p>Qualitative results should be presented thematically, not chronologically. Each theme is a finding in itself and must be supported by evidence from the data, typically direct participant quotes, field notes, or document excerpts.<\/p>\n\n\n\n<h3>The Core Structure of Qualitative Results<\/h3>\n\n\n\n<ul><li>Begin with a brief overview of the number of themes (or categories, codes) identified and how they relate to the research question.<\/li><li>Dedicate a subsection to each theme, with a descriptive subheading.<\/li><li>Define each theme clearly in one to two sentences at the start of its subsection.<\/li><li>Provide two to four illustrative quotes per theme; more if the findings are complex.<\/li><li>Attribute quotes by participant identifier only, not by name (e.g., Participant 3, P7, or a pseudonym).<\/li><li>Explain how each quote illustrates the theme rather than letting quotes stand alone.<\/li><li>End each theme subsection with a synthesizing sentence connecting back to the research question.<\/li><\/ul>\n\n\n\n<h3>Formatting Quotes in Qualitative Results<\/h3>\n\n\n\n<ul><li>Short quotes (fewer than 40 words): integrate into the paragraph with quotation marks.<\/li><li>Long quotes (40 words or more): set as a block quotation, indented, without quotation marks.<\/li><li>Use ellipses (&#8230;) to indicate omitted text; use square brackets [&#8230;] to add clarifying words.<\/li><li>Never alter a quote&#8217;s meaning, even when cleaning up grammar.<\/li><\/ul>\n\n\n\n<h3>Figures and Tables for Qualitative Results<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Visual Type<\/strong><\/td><td><strong>Best Used For<\/strong><\/td><td><strong>Notes<\/strong><\/td><\/tr><\/thead><tbody><tr><td>Thematic map \/ concept map<\/td><td>Showing relationships among themes and subthemes<\/td><td>Useful in grounded theory and thematic analysis<\/td><\/tr><tr><td>Table: theme summary<\/td><td>Listing themes, definitions, and participant attribution counts<\/td><td>Include a column showing how many participants mentioned each theme<\/td><\/tr><tr><td>Coding tree<\/td><td>Showing the hierarchy from codes to categories to themes<\/td><td>Common in framework analysis and content analysis<\/td><\/tr><tr><td>Matrix table<\/td><td>Cross-tabulating themes against participant characteristics<\/td><td>Useful when exploring variation by group<\/td><\/tr><tr><td>Quote table<\/td><td>Presenting multiple exemplary quotes side by side<\/td><td>Keep to two to three columns; label by participant<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>What Researchers Frequently Get Wrong in Qualitative Results<\/h3>\n\n\n\n<ul><li>Using too many quotes without interpretation, creating a collection rather than a findings section.<\/li><li>Using too few quotes and making claims without evidence.<\/li><li>Quoting only participants who agree, ignoring contradictory voices (this is selective reporting).<\/li><li>Failing to report negative cases or deviant cases that challenge the main themes.<\/li><li>Reporting the number of times a code appeared as if frequency equals importance (a quantitative thinking error applied to qualitative work).<\/li><li>Not distinguishing between themes from the data and themes imposed from a theoretical framework.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029994\">Mixed-Methods Results: How Are Both Strands Integrated?<\/a><\/h2>\n\n\n\n<p>Mixed-methods results are integrated only after each strand has been reported separately. The integration point clarifies whether the quantitative and qualitative findings converge, diverge, or complement each other in answering the research question.<\/p>\n\n\n\n<h3>Three Common Integration Approaches<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Integration Approach<\/strong><\/td><td><strong>When to Use It<\/strong><\/td><td><strong>How to Present in Results<\/strong><\/td><\/tr><\/thead><tbody><tr><td>Convergent (triangulation)<\/td><td>When both strands were collected simultaneously to cross-validate<\/td><td>Report each strand separately, then present a joint display or table comparing findings<\/td><\/tr><tr><td>Explanatory sequential<\/td><td>When quantitative results are collected first, then qualitative data explain them<\/td><td>Report quantitative strand fully; present qualitative strand as an explanation in a subsequent subsection<\/td><\/tr><tr><td>Exploratory sequential<\/td><td>When qualitative findings inform the development of a quantitative instrument or framework<\/td><td>Report qualitative strand first; show how it shaped the quantitative phase; report quantitative results last<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>The Joint Display<\/h3>\n\n\n\n<p>A joint display is a table or figure that places quantitative and qualitative results side by side to show convergence or divergence. It is the most common and recommended integration tool in mixed-methods results sections.<\/p>\n\n\n\n<ul><li>Column 1: quantitative finding (e.g., a statistically significant group difference).<\/li><li>Column 2: qualitative finding (e.g., the theme that explains or contradicts the quantitative pattern).<\/li><li>Column 3: integration inference (what the combined findings mean for the research question).<\/li><\/ul>\n\n\n\n<h3>Common Mistakes in Mixed-Methods Results<\/h3>\n\n\n\n<ul><li>Reporting both strands and then failing to integrate them at all, leaving the reader to draw their own conclusions.<\/li><li>Letting one strand dominate and treating the other as supplementary rather than equal.<\/li><li>Using qualitative quotes merely to illustrate quantitative findings rather than to add new meaning.<\/li><li>Not explaining what it means when quantitative and qualitative findings diverge.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029995\">What Belongs in the Results Section of a Literature Review or Systematic Review?<\/a><\/h2>\n\n\n\n<p>In a systematic review or meta-analysis, the Results section covers the search process, study selection, study characteristics, quality assessment, and synthesized findings. In a narrative literature review, results center on the body of literature identified and its key patterns.<\/p>\n\n\n\n<h3>Systematic Review Results: Required Components<\/h3>\n\n\n\n<ul><li>Search results: total records identified, duplicates removed, records screened, full texts assessed, and studies included (typically presented as a PRISMA flow diagram).<\/li><li>Study characteristics: a table summarizing the included studies (author, year, design, population, intervention or exposure, outcomes, key findings).<\/li><li>Risk of bias or quality assessment: a summary table showing each study&#8217;s scores on the chosen appraisal tool.<\/li><li>Synthesis: the pooled effect estimate for each outcome, with heterogeneity statistics (I-squared, Q statistic) when a meta-analysis is performed.<\/li><\/ul>\n\n\n\n<h3>Figures and Tables for Literature and Systematic Reviews<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Visual Type<\/strong><\/td><td><strong>Best Used For<\/strong><\/td><td><strong>Notes<\/strong><\/td><\/tr><\/thead><tbody><tr><td>PRISMA flow diagram<\/td><td>Tracking records through search, screening, and inclusion<\/td><td>Mandatory for systematic reviews; include at each stage the reason for exclusion at full-text screening<\/td><\/tr><tr><td>Study characteristics table<\/td><td>Summarizing included studies<\/td><td>Keep to four columns maximum; use supplementary material for additional columns<\/td><\/tr><tr><td>Risk of bias table or heat map<\/td><td>Showing quality appraisal results across studies<\/td><td>Use the tool&#8217;s own rating categories (low, unclear, high risk)<\/td><\/tr><tr><td>Forest plot<\/td><td>Showing individual and pooled effect sizes in meta-analysis<\/td><td>Include the heterogeneity statistic; label each study row<\/td><\/tr><tr><td>Funnel plot<\/td><td>Assessing publication bias in meta-analysis<\/td><td>Include only when at least ten studies are included<\/td><\/tr><tr><td>Summary of findings (SoF) table<\/td><td>Presenting GRADE-rated evidence per outcome<\/td><td>Standard in Cochrane systematic reviews; shows certainty of evidence<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>Narrative Literature Review Results<\/h3>\n\n\n\n<ul><li>Identify and describe the body of literature: years covered, databases searched, number of relevant studies found.<\/li><li>Organize findings by theme, chronology, or conceptual category rather than study by study.<\/li><li>Use a summary table listing key studies, designs, populations, and findings.<\/li><li>Note gaps, contradictions, and methodological variation across the literature.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029996\">Figures and Tables: When to Use Each<\/a><\/h2>\n\n\n\n<p>Use a figure when a visual pattern conveys more information than prose; use a table when exact numbers matter. Never duplicate information: if something is in a table or figure, summarize it in text but do not reproduce every number.<\/p>\n\n\n\n<h3>General Rules for Figures<\/h3>\n\n\n\n<ul><li>Every figure must have a concise, self-explanatory caption placed below it.<\/li><li>Captions must describe what is shown, the data source, the sample size, and any abbreviations.<\/li><li>Axes must be labeled with units in parentheses (e.g., Age (years)).<\/li><li>Error bars must be defined in the caption (SD, SEM, or 95% CI).<\/li><li>Avoid three-dimensional effects, excessive gridlines, and decorative elements that obscure data.<\/li><li>Use grayscale or colorblind-safe color palettes when possible.<\/li><\/ul>\n\n\n\n<h3>General Rules for Tables<\/h3>\n\n\n\n<ul><li>Every table must have a concise, self-explanatory title placed above it.<\/li><li>Use a maximum of four columns to keep tables readable on a standard page.<\/li><li>Align numbers to the decimal point within each column.<\/li><li>Use footnotes (a, b, c or *, **, ***) to define abbreviations and significance levels.<\/li><li>Avoid vertical lines; use horizontal lines only to separate the header from the body and the body from the footer.<\/li><li>Do not repeat in prose every value already in the table; instead, direct the reader to the table and highlight one or two key findings.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029997\">Reporting Checklists: Which Ones Apply to the Results Section?<\/a><\/h2>\n\n\n\n<p>Reporting checklists specify what must be present in your Results section based on study design. Below is a guide to the most widely used checklists and the Results-specific items researchers most commonly miss or misreport.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Checklist<\/strong><\/td><td><strong>Study Design<\/strong><\/td><td><strong>Key Results Items Required<\/strong><\/td><td><strong>Most Frequently Missed in Results<\/strong><\/td><\/tr><\/thead><tbody><tr><td>CONSORT 2010<\/td><td>Randomized controlled trials (RCTs)<\/td><td>Participant flow diagram; recruitment dates; baseline characteristics table; numbers analyzed per group; primary and secondary outcomes with effect sizes and CIs; ancillary and exploratory analyses labeled as such; harms and adverse events<\/td><td>Harms and adverse events; confidence intervals alongside p-values; distinction between pre-specified and exploratory analyses; attrition reasons by group<\/td><\/tr><tr><td>PRISMA 2020<\/td><td>Systematic reviews and meta-analyses<\/td><td>PRISMA flow diagram with exclusion reasons; study characteristics table; risk of bias summary; results of individual studies; results of syntheses (pooled estimates, I-squared, prediction intervals); publication bias assessment; certainty of evidence (GRADE)<\/td><td>Heterogeneity statistics (I-squared); prediction intervals alongside pooled estimates; GRADE certainty ratings; reporting why studies were excluded at full-text stage<\/td><\/tr><tr><td>STROBE<\/td><td>Observational studies (cohort, case-control, cross-sectional)<\/td><td>Participants in each stage of the study; non-participation reasons; participant characteristics; outcome data; unadjusted and adjusted estimates with CIs; subgroup analyses<\/td><td>Reporting both unadjusted and adjusted effect estimates; confidence intervals; clear labeling of what variables confounders were adjusted for<\/td><\/tr><tr><td>COREQ<\/td><td>Qualitative research (interviews, focus groups)<\/td><td>Participant characteristics; data saturation statement; coding tree or thematic map; participant quotes for each theme; negative case analysis<\/td><td>Negative case analysis; data saturation description; attribution of quotes to participant identifiers; reflexivity statement from the researcher<\/td><\/tr><tr><td>TRIPOD+AI<\/td><td>Prediction model studies<\/td><td>Flow of participants; predictors used; performance metrics (discrimination: C-statistic or AUC; calibration: Hosmer-Lemeshow or calibration plot); missing data handling results<\/td><td>Calibration statistics alongside discrimination; reporting performance in validation cohort separately from development cohort; missing data approach<\/td><\/tr><tr><td>STARD<\/td><td>Diagnostic accuracy studies<\/td><td>Flow diagram of participant recruitment; cross-tabulation of results (2&#215;2 table); sensitivity, specificity, predictive values, likelihood ratios; estimates by subgroup if pre-specified<\/td><td>2&#215;2 table or equivalent; confidence intervals around sensitivity and specificity; indeterminate or uninterpretable test results<\/td><\/tr><tr><td>ARRIVE 2.0<\/td><td>Animal research<\/td><td>Number of animals per group; excluded animals with reasons; primary and secondary outcomes with effect sizes and CIs; sex and\/or species subgroup results if applicable<\/td><td>Excluded animals and reasons; effect sizes; sex-disaggregated data where applicable<\/td><\/tr><tr><td>SQUIRE 2.0<\/td><td>Quality improvement studies<\/td><td>Initial and subsequent steps of the intervention as it evolved; data from outcome measures over time; unintended consequences; association of changes in context with changes in outcomes<\/td><td>Time-series or run chart data; unintended consequences; context changes that affected results<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>How to Use a Reporting Checklist Correctly<\/h3>\n\n\n\n<ul><li>Download the checklist before you write, not after, so you know what the Results section must include.<\/li><li>For each checklist item, record the page number in your manuscript where it is addressed.<\/li><li>If an item is not applicable, write N\/A and briefly explain why in the submission cover letter.<\/li><li>Use the EQUATOR Network website to identify the correct checklist for your study design.<\/li><li>Some journals require the completed checklist as a supplementary submission file; check author guidelines before submission.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029998\">How to Write Your First Results Section<\/a><\/h2>\n\n\n\n<p>Writing your first Results section is one of the most common points of confusion in academic training. The guidance below addresses the specific challenges that first-time authors face, from understanding what counts as a result to navigating statistical software output.<\/p>\n\n\n\n<h3>Before You Write: The Pre-Writing Checklist<\/h3>\n\n\n\n<ul><li>Go back to your Introduction and list every research question and hypothesis.<\/li><li>For each research question, identify the specific data or analysis that answers it.<\/li><li>Decide the order in which results will be presented (match the order of your research questions).<\/li><li>Produce all tables and figures before you write any prose: the prose describes what the visuals show.<\/li><li>Print or open your statistical output or coded qualitative data alongside your draft.<\/li><\/ul>\n\n\n\n<h3>The Most Common First-Timer Mistakes and How to Avoid Them<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><td><strong>Mistake<\/strong><\/td><td><strong>Why It Happens<\/strong><\/td><td><strong>How to Fix It<\/strong><\/td><\/tr><\/thead><tbody><tr><td>Mixing results and interpretation<\/td><td>Students feel the urge to explain their findings immediately<\/td><td>After each result, ask: &#8216;Am I explaining why this happened?&#8217; If yes, move that sentence to the Discussion.<\/td><\/tr><tr><td>Reporting only significant results<\/td><td>Fear that non-significant results look like failure<\/td><td>Non-significant results are findings; report them with the same statistics and the same amount of space.<\/td><\/tr><tr><td>Copying statistical output tables directly from SPSS or R<\/td><td>Convenience and time pressure<\/td><td>Reproduce statistics in APA or journal-specific format; never paste raw software output.<\/td><\/tr><tr><td>Not referring to tables and figures in the text<\/td><td>Assuming the reader will look at tables automatically<\/td><td>Every table and figure must be explicitly cited in the prose: &#8216;As shown in Table 1&#8230;&#8217; or &#8216;(see Figure 2)&#8217;.<\/td><\/tr><tr><td>Using imprecise language (&#8216;significant trend&#8217;, &#8216;almost significant&#8217;)<\/td><td>Wanting to make borderline results sound positive<\/td><td>A result is either statistically significant at your stated threshold, or it is not; use &#8216;did not reach significance&#8217; or &#8216;approached significance (p = .07)&#8217; carefully and sparingly.<\/td><\/tr><tr><td>Writing the Results and Discussion as one combined section when the journal separates them<\/td><td>Conflating two functions<\/td><td>Check the target journal&#8217;s structure before you write; most empirical journals require separate sections.<\/td><\/tr><tr><td>Forgetting to report demographic or sample characteristics<\/td><td>Focusing entirely on outcomes<\/td><td>Always include a participant characteristics table (or equivalent sample description) before outcome results.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3>Step-by-Step Framework for First-Time Writers<\/h3>\n\n\n\n<ol type=\"1\"><li>State the purpose: Write one sentence restating the study aim to orient the reader.<\/li><li>Report the sample: Present participant flow and demographics (Table 1 is usually this table).<\/li><li>Address research question 1: Provide descriptive statistics, then the inferential test, then the effect size.<\/li><li>Address research question 2 and beyond: Repeat step 3 for each remaining question.<\/li><li>Report secondary and exploratory analyses: Clearly label these as secondary or exploratory.<\/li><li>Review against the checklist: Go item by item through the relevant reporting checklist before submitting a draft to your supervisor.<\/li><\/ol>\n\n\n\n<h3>Qualitative-Specific Guidance for First-Time Writers<\/h3>\n\n\n\n<ul><li>Do not list every code; report only the themes that emerged from groups of codes.<\/li><li>A theme is not a topic: a theme is an interpretive claim about the data (e.g., not &#8216;stress&#8217; but &#8216;participants described stress as a barrier to help-seeking&#8217;).<\/li><li>The names you give to themes matter: they should convey meaning, not just label content.<\/li><li>Aim for two to four themes in a standard journal article; more than six usually indicates under-developed analysis.<\/li><li>Quotes are evidence, not results: the result is the theme; the quote is the proof.<\/li><\/ul>\n\n\n\n<h3>How to Handle Unexpected or Contradictory Results<\/h3>\n\n\n\n<ul><li>Report them fully without downplaying; unexpected results are often the most interesting part of a study.<\/li><li>Do not attempt to explain them in the Results section; save the explanation for the Discussion.<\/li><li>Label them clearly as unexpected or unplanned if they emerged post-hoc.<\/li><li>If a result contradicts a hypothesis, state this plainly: &#8216;Contrary to Hypothesis 2, no significant difference was found&#8230;&#8217;<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233029999\">Parallel Structure and Language Conventions<\/a><\/h2>\n\n\n\n<p>The language of a Results section is precise, objective, and past tense. Consistent grammatical structure helps readers follow complex information without added cognitive load.<\/p>\n\n\n\n<h3>Tense and Voice<\/h3>\n\n\n\n<ul><li>Use past tense throughout: &#8216;scores were higher&#8217;, not &#8216;scores are higher&#8217;.<\/li><li>Use <a href=\"https:\/\/www.editage.com\/insights\/how-to-effectively-use-active-and-passive-voice-in-research-writing\">active or passive voice<\/a> as your target journal requires; check author guidelines.<\/li><li>You can use the first person as long as your journal\/institution permit it.<\/li><\/ul>\n\n\n\n<h3>Numerical Reporting Conventions<\/h3>\n\n\n\n<ul><li>Use numerals for all statistics: p = .032, n = 47, M = 3.2.<\/li><li>Report p-values to two or three decimal places; use p &lt; .001 for very small p-values, never p = .000.<\/li><li>Round means and SDs to two decimal places unless precision is scientifically necessary.<\/li><li>Use consistent decimal places within a table column.<\/li><\/ul>\n\n\n\n<h3>Phrases That Signal the Results Section<\/h3>\n\n\n\n<ul><li>Describing a finding: &#8216;The analysis revealed&#8230;&#8217;, &#8216;Results indicated&#8230;&#8217;, &#8216;A significant difference was found&#8230;&#8217;<\/li><li>Referring to a visual: &#8216;As shown in Table 2&#8230;&#8217;, &#8216;Figure 3 illustrates&#8230;&#8217;, &#8216;(see Figure 1)&#8217;<\/li><li>Reporting non-significance: &#8216;No significant difference was found&#8230;&#8217;, &#8216;The groups did not differ significantly&#8230;&#8217;<\/li><li>Reporting unexpected findings: &#8216;Contrary to Hypothesis 1&#8230;&#8217;, &#8216;Unexpectedly&#8230;&#8217;<\/li><li>Transitioning between research questions: &#8216;Turning to the second research question&#8230;&#8217;, &#8216;With respect to&#8230;&#8217;<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233030000\">Subgroup Analyses, Secondary Outcomes, and Exploratory Findings: How Should These Be Labeled?<\/a><\/h2>\n\n\n\n<p>Subgroup and secondary analyses must be labeled explicitly as pre-specified or exploratory. Readers and reviewers use these labels to calibrate how much confidence to place in the results; mislabeling undermines the integrity of the report.<\/p>\n\n\n\n<ul><li>Pre-specified secondary outcome: planned before data collection; reported after primary outcomes with the same statistical rigor.<\/li><li>Pre-specified subgroup analysis: planned before data collection; report the interaction test, not just the subgroup results.<\/li><li>Post-hoc or exploratory analysis: conducted after seeing the data; must be clearly labeled as exploratory and interpreted cautiously.<\/li><li>Do not adjust the primary analysis p-value threshold based on subgroup findings.<\/li><li>If more than five subgroup analyses are conducted, consider reporting them in a supplementary table with a note in the main text.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233030001\">Participant Flow and Attrition: What Must Be Reported?<\/a><\/h2>\n\n\n\n<p>Participant flow must be reported in any study involving human participants. Missing attrition data is one of the most frequent compliance failures on reporting checklists across all study designs.<\/p>\n\n\n\n<ul><li>Report the number of participants assessed for eligibility, consented, enrolled, randomized (if applicable), and analyzed.<\/li><li>Report the number who withdrew, were lost to follow-up, or were excluded at each stage, with the reason for each exclusion.<\/li><li>Report whether the analysis was intention-to-treat (ITT), per-protocol (PP), or another approach, and how missing data were handled.<\/li><li>A participant flow diagram (CONSORT-style) is mandatory for RCTs and strongly recommended for any longitudinal quantitative study.<\/li><li>For qualitative studies, report how many participants were approached, agreed to participate, and ultimately contributed data.<\/li><\/ul>\n\n\n\n<h2><a id=\"_Toc233030002\">Frequently Asked Questions<\/a><\/h2>\n\n\n\n<h3>Can I write the Results and Discussion sections together if my findings are complex?<\/h3>\n\n\n\n<p>Some journals allow a combined Results and Discussion section, often labeled &#8216;Results and Discussion&#8217; or &#8216;Findings and Interpretation.&#8217; Check the target journal&#8217;s author guidelines first. If the journal requires separate sections, keep them separate even if your findings seem to demand immediate explanation. When combined sections are permitted, they typically work best for qualitative studies or case study research; they are less common in quantitative or clinical research where separating reporting from interpretation is a transparency requirement.<\/p>\n\n\n\n<h3>Do I need to report results that were not significant? My advisor says to leave them out.<\/h3>\n\n\n\n<p>Yes: non-significant results must be reported in full. Selective reporting of significant results is a recognized form of reporting bias that distorts the published literature and can harm readers who rely on the research for clinical, policy, or practical decisions. A result of p = .72 is a finding: it tells the reader that the intervention had no statistically significant effect under the conditions studied. If you pre-registered your study, you are additionally required to report all pre-specified outcomes regardless of significance. Speak with your advisor about this principle; they may be confusing &#8216;leave out exploratory post-hoc analyses&#8217; with &#8216;leave out non-significant primary outcomes,&#8217; which are very different situations.<\/p>\n\n\n\n<h3>How long should the Results section be relative to the rest of the paper?<\/h3>\n\n\n\n<p>There is no universal rule, but common patterns in empirical journals suggest the following rough proportions: Introduction (10-15%), Methods (25-30%), Results (20-30%), Discussion (25-30%), and Conclusion (5-10%). For qualitative studies, Results (or Findings) sections tend to be longer, sometimes 35 to 45% of the paper, because they must present and interpret themes with illustrative quotes. For brief reports, technical notes, or short communications, the Results section may be compressed to two to four paragraphs with one or two tables. The guiding principle is completeness, not length: the section should be as long as needed to report all pre-specified outcomes clearly.<\/p>\n\n\n\n<h3>Is it okay to include a figure in the Results section that I generated using AI tools?<\/h3>\n\n\n\n<p>AI-generated figures (created by tools such as ChatGPT image generation, Midjourney, or similar) are generally not appropriate for the Results section of an empirical paper, because the Results section should present data, not AI-generated illustrations. If you used an AI-assisted tool to visualize data (for example, a Python-based tool with an AI-assisted plotting feature), you may use the output as long as the underlying data are genuine and the figure accurately represents them. Disclose the tool used in the Methods section. Several journals now require explicit disclosure of any AI tool used in figure preparation. Do not use AI to generate figures that represent data you do not have.<\/p>\n\n\n\n<h3>My qualitative study has too many quotes. How do I decide which ones to keep?<\/h3>\n\n\n\n<p>Select quotes based on three criteria.<\/p>\n\n\n\n<ul><li>First, typicality: the quote should represent what most participants said about a theme, not an outlier.<\/li><li>Second, vividness: when two quotes are equally representative, choose the one that communicates the idea most clearly and concisely.<\/li><li>Third, diversity: across all your quotes for a theme, aim to include voices from different participant subgroups (e.g., different genders, ages, or professional roles) where possible.<\/li><\/ul>\n\n\n\n<p>As a general target, two to four quotes per theme is standard for a journal article. For a dissertation chapter, four to six may be appropriate. Remove any quote that you cannot explain or connect to the theme in at least one sentence of your own analysis.<\/p>\n\n\n\n<h3>My supervisor wants me to report the results in a different order than my research questions. Which takes priority?<\/h3>\n\n\n\n<p>As a general principle, the order of results should follow the order in which research questions or hypotheses were stated in the Introduction. This creates a coherent through-line for the reader. However, there are legitimate reasons to deviate: your supervisor may want primary outcomes before secondary outcomes regardless of question order, or they may want demographic and sample-descriptive results first. Discuss the logic with your supervisor and then apply the agreed order consistently. Whatever order you choose, use subheadings that make the structure immediately clear to the reader.<\/p>\n\n\n\n<h3>What is the difference between reporting in APA format versus a specific journal&#8217;s house style, and which should I use?<\/h3>\n\n\n\n<p>APA format (currently 7th edition) provides default standards for reporting statistics, tables, figures, and references that are used by many psychology, education, and social science journals. However, individual journals may deviate from APA in specific ways: they may require different decimal places, different table layouts, or different abbreviations. Always use the specific journal&#8217;s author guidelines as the final authority. If your target journal does not specify a style, APA 7th edition is a safe default for social sciences; Vancouver style is common in biomedical journals. For a thesis or dissertation, use the style specified by your institution.<\/p>\n\n\n\n<h3>I found an error in my Results section after submitting to a journal. What should I do?<\/h3>\n\n\n\n<p>Contact the journal editor as soon as possible, before peer review is completed if you can. Most journals have a procedure for authors to withdraw a submitted manuscript, correct it, and resubmit. If the paper has already been accepted or published, the journal will issue a correction notice (also called an erratum). Errors discovered after publication must always be formally corrected through the journal; do not simply upload a corrected version to a preprint server without also notifying the journal. Transparency about errors, reported promptly, is far less damaging to your reputation than errors discovered by reviewers or readers after publication.<\/p>\n","protected":false},"excerpt":{"rendered":"Contents Glossary of Key Terms Key Takeaways What Is the Results Section and What Belongs in It? How Do Quantitative Results Differ from Other Study Types? How Should Qualitative Results Be Presented? Mixed-Methods Results: How Are Both Strands Integrated? What Belongs in the Results Section of a Literature Review or Systematic Review? Figures and Tables: [&hellip;]","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_ayudawp_aiss_exclude":false,"_ayudawp_aiss_summary":"Quantitative results differ from qualitative and mixed-methods results because they center on numerical data, statistical tests, and effect sizes. Some journals allow a combined Results and Discussion section, often labeled 'Results and Discussion' or 'Findings and Interpretation.' Check the target journal's author guidelines first. AI-generated figures (created by tools such as ChatGPT image generation, Midjourney, or similar) are generally not appropriate for the Results section of an empirical paper, because the Results section should present data, not AI-generated illustrations.","_ayudawp_aiss_summary_provider":"extractive","_ayudawp_aiss_summary_hash":"6979ecadc6e321ce7b9e04f2f789642c05f7fb57"},"categories":[14],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How to Write the Results Section of a Research Paper: Tips, Examples, Guidelines - Educational Articles For Researchers, Students And Authors - Editage Blog<\/title>\n<meta name=\"description\" content=\"Learn how to structure and report the results section of a qualitative\/quantitative\/mixed-methods study or a literature review, with detailed tips for figures and tables.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.editage.com\/blog\/results-section-research-paper\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to Write the Results Section of a Research Paper: Tips, Examples, Guidelines - 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