Real examples of abstract writing examples for quantitative research

Before we talk structure or theory, let’s look at real examples of abstract writing examples for quantitative research in different fields. Notice the consistent pattern: purpose, method, sample, key stats, and takeaway.

Example 1: Education – Online homework and algebra scores

Title: Impact of Adaptive Online Homework on Algebra I Achievement in U.S. High Schools

Abstract (example of a strong quantitative style):
This quasi-experimental study examined the effect of adaptive online homework on Algebra I achievement among 1,248 ninth-grade students from 14 public high schools in the Midwestern United States during the 2023–2024 school year. Students in the treatment group (n = 642) completed weekly adaptive online homework, while students in the comparison group (n = 606) received traditional paper-based assignments. End-of-course exam scores served as the primary outcome measure. After controlling for prior math achievement, gender, and socioeconomic status using multiple regression, students in the adaptive homework condition scored on average 6.3 points higher on the state Algebra I exam than students in the comparison group (β = 0.21, p < .001). Effects were larger for students scoring below the 40th percentile at baseline (β = 0.34, p < .001). Findings suggest that adaptive online homework can modestly improve algebra achievement, particularly for lower-performing students.

Why this works:

• States the design (quasi-experimental) and context.
• Gives sample size and groups.
• Names the analysis (multiple regression) and controls.
• Reports effect size and p-values.
• Ends with a clear, practical implication.

Example 2: Public health – Sleep and screen time in college students

Title: Associations Between Evening Screen Time and Sleep Duration Among U.S. College Students

Abstract:
This cross-sectional study investigated the relationship between evening screen time and sleep duration in a sample of 2,031 undergraduate students from a large public university in the United States in Spring 2024. Participants completed an online survey reporting average daily screen use after 8:00 p.m., self-reported sleep duration, and covariates including caffeine intake, physical activity, and depressive symptoms. Linear regression models indicated that each additional hour of evening screen time was associated with 21.4 fewer minutes of nightly sleep (β = −0.36, p < .001), after adjustment for covariates. Students reporting more than 4 hours of evening screen use were 2.3 times more likely to sleep fewer than 7 hours per night (95% CI: 1.8–2.9) compared with those reporting 0–1 hour. Results support current public health recommendations to limit evening screen exposure to promote adequate sleep among young adults.

If you’re looking for best examples of abstract writing examples for quantitative research in health sciences, this is a good model: it is concise but still reports the actual numbers and confidence intervals, which reviewers expect.

Example 3: Psychology – Mindfulness app and anxiety

Title: Effectiveness of a Smartphone-Based Mindfulness Intervention for Reducing Anxiety in Working Adults

Abstract:
This randomized controlled trial evaluated the effectiveness of a 6-week smartphone-based mindfulness intervention on anxiety symptoms among 312 full-time employees at a U.S. technology company in 2024. Participants were randomly assigned to a mindfulness app condition (n = 157) or a waitlist control group (n = 155). Anxiety was assessed at baseline and post-intervention using the Generalized Anxiety Disorder-7 (GAD-7) scale. Repeated-measures ANOVA revealed a significant time × group interaction (F(1, 310) = 18.92, p < .001). The intervention group showed a mean reduction of 3.8 points (SD = 4.1) on the GAD-7 compared with a 0.9-point reduction (SD = 3.7) in the control group, corresponding to a moderate effect size (Cohen’s d = 0.52). Findings indicate that a brief, app-based mindfulness program can meaningfully reduce anxiety symptoms in working adults.

This is one of those real examples of abstract writing examples for quantitative research that shows you can mention a specific instrument (GAD-7) and still keep the wording clean and readable.

Example 4: Business/marketing – Social media ads and click-through rates

Title: A/B Testing Social Media Ad Formats: Effects on Click-Through and Conversion Rates

Abstract:
This field experiment analyzed the impact of three social media advertising formats on click-through rate (CTR) and conversion rate in a U.S.-based direct-to-consumer apparel brand’s 2024 campaign. Over a 6-week period, 1.2 million impressions were randomly assigned to static image ads, short-form video ads, or carousel ads. Logistic regression models controlling for time of day and device type showed that short-form video ads produced a 27% higher CTR (OR = 1.27, 95% CI: 1.22–1.32) and a 19% higher conversion rate (OR = 1.19, 95% CI: 1.11–1.28) compared with static image ads. Carousel ads yielded intermediate results. Results suggest that short-form video ads outperform static images in driving both engagement and conversions in paid social campaigns.

For business students searching for examples of abstract writing examples for quantitative research, this is a strong pattern for experiments with large digital datasets.

Example 5: STEM education – Hybrid labs vs. traditional labs

Title: Learning Outcomes in Hybrid Versus Traditional Introductory Biology Labs

Abstract:
This comparative study evaluated learning outcomes in hybrid versus traditional laboratory formats in an introductory biology course at a large U.S. community college during the 2023–2024 academic year. A total of 486 students self-enrolled in either hybrid labs (n = 241), meeting in person once per week with online simulations, or traditional labs (n = 245), meeting in person twice per week. Outcomes included final lab exam scores and concept inventory scores administered pre- and post-course. ANCOVA controlling for prior GPA and math placement scores indicated no significant difference in final lab exam scores between formats (F(1, 481) = 1.84, p = .18). However, students in the hybrid format demonstrated larger gains on the biology concept inventory (mean gain = 18.2%, SD = 9.5) than students in the traditional format (mean gain = 14.7%, SD = 8.9; F(1, 481) = 7.13, p = .008). Findings suggest that hybrid lab formats can support conceptual understanding at least as effectively as traditional labs.

Example 6: Data science – Predicting hospital readmission

Title: Machine Learning Prediction of 30-Day Hospital Readmission Among Patients With Heart Failure

Abstract:
Using electronic health record data from 18,407 adult patients hospitalized with heart failure at a large U.S. health system between 2020 and 2023, this retrospective cohort study developed and validated machine learning models to predict 30-day hospital readmission. Patients were randomly split into training (70%) and test (30%) sets. Gradient boosting, random forest, and logistic regression models were compared using area under the receiver operating characteristic curve (AUC). The gradient boosting model achieved the highest performance (AUC = 0.81, 95% CI: 0.80–0.83), outperforming logistic regression (AUC = 0.74, 95% CI: 0.72–0.76). Key predictors included prior-year admissions, number of comorbidities, and discharge disposition. Calibration plots showed good agreement between predicted and observed risk. These results demonstrate that machine learning models can meaningfully improve prediction of 30-day readmission for patients with heart failure and may support targeted post-discharge interventions.

If you’re writing in health or data science, compare your draft against best examples of abstract writing examples for quantitative research like this: note the clear statement of data source, time frame, model types, and performance metrics.

Key patterns in strong abstract writing for quantitative research

When you read through these examples of abstract writing examples for quantitative research, a few patterns show up again and again.

They always answer five questions clearly:

• What problem or question did you study?
• Who or what did you study (sample, data source, time frame)?
• What design and methods did you use?
• What did you find (with actual numbers)?
• Why does it matter for practice, policy, or future research?

Strong abstracts for quantitative work also:

• Use past tense to describe what you did and found.
• Name the design: randomized trial, cross-sectional survey, cohort study, A/B test, etc.
• Report sample size and basic group information.
• Include at least one concrete statistical result (effect size, odds ratio, AUC, F-statistic, etc.).
• Avoid long literature reviews or theoretical digressions.

If your abstract doesn’t do all of that, compare it sentence by sentence with the real examples of abstract writing examples for quantitative research above and adjust.

Updated 2024–2025 expectations for quantitative abstracts

Editors and reviewers are quietly raising the bar. If you want your work to look current, these trends matter:

1. Transparency and open science language
Many journals now expect a nod to transparency. You might briefly mention:

• That the study was preregistered (e.g., on OSF or ClinicalTrials.gov).
• That data or code will be made available (if allowed by your institution and IRB).

For instance, a line like: “The analysis plan was preregistered on ClinicalTrials.gov (NCT01234567)” is increasingly common in medical and psychological research. You can see how major agencies talk about transparency by browsing the National Institutes of Health policies on data sharing.

2. Clearer reporting of effect sizes, not just p-values
Abstracts that only say “significant” without numbers feel dated. Look again at the examples of abstract writing examples for quantitative research above: they report effect sizes (β, Cohen’s d, odds ratios, AUC) and confidence intervals.

3. Plain-language implications
Editors want readers outside your subfield to understand why your results matter. That’s why most of the best examples end with a sentence like “Findings suggest that…” or “Results support…” followed by a real-world takeaway.

You can see this style in many current articles indexed by PubMed and described on CDC and Mayo Clinic pages that summarize quantitative studies in accessible language.

How to build your own abstract using these examples

Use the examples of abstract writing examples for quantitative research as templates, not scripts. A practical way to draft your own:

Start with your results, not your introduction.
Write down, in plain language:

• What you measured.
• What changed or differed between groups.
• The one or two numbers that best capture your main finding.

Then wrap the rest of the abstract around those results.

A reliable structure you see in almost every example of abstract writing examples for quantitative research above looks like this (phrased as moves, not a rigid formula):

• Opening move – Purpose and context
  One or two sentences: the problem, population, and aim. Avoid long background.

• Method move – Design, sample, measures, analysis
  Two to four sentences: design, sample size, location/time, key variables, and main analysis method.

• Results move – Numbers that matter
  Two to three sentences: main effect(s) with statistics, direction of relationships, and any important subgroup findings.

• Conclusion move – So what?
  One or two sentences: what your results imply for practice, policy, or future research.

If you’re stuck, grab one of the best examples above in your field and literally substitute your own:

• Population
• Sample size
• Design
• Measures
• Statistical tests
• Key numeric results

You’ll quickly see where your own abstract is vague or missing details.

FAQ: Common questions about examples of abstract writing for quantitative research

How long should a quantitative research abstract be?
Most journals ask for 150–250 words, but conference abstracts might be shorter (100–150 words) or longer (up to 300). Always check the specific instructions for authors. Many of the real examples of abstract writing examples for quantitative research above sit comfortably around 200–230 words, which is a safe target for most academic venues.

Do I have to include statistics in the abstract?
If you are doing quantitative research, yes. At least one example of a key result with a number should appear: an effect size, odds ratio, regression coefficient, or test statistic. Saying “there was a significant effect” without numbers is considered weak reporting in 2024.

Can I mention limitations in the abstract?
Often you can, especially in health and social sciences. If space is tight, a short clause can work: “Findings, based on self-reported data from a single institution, should be interpreted with caution.” Look at recent articles in journals indexed by NIH or Harvard libraries to see how they phrase limitations in abstracts.

Where can I find more real examples of abstract writing examples for quantitative research?
You can browse:

• Open-access articles through PubMed Central for health and biomedical studies.
• Education research through the What Works Clearinghouse (U.S. Department of Education) for program evaluations and intervention studies.
• University repositories (for example, searching “quantitative thesis abstract site:.edu” in Google) for student theses with full abstracts.

Should I write the abstract before or after the paper?
Most experienced researchers draft it last. You can sketch a placeholder early, but your final abstract should be written after your analyses are complete so that it accurately reflects your methods and findings. Use the examples of abstract writing examples for quantitative research in this guide as a final checklist before you submit.

Final check before you submit

Once your abstract is drafted, compare it against the patterns in the best examples of abstract writing examples for quantitative research above and ask:

• Does it state the design, sample, and setting?
• Does it clearly describe the main variables and measures?
• Does it report at least one or two specific statistics, not just “significant”?
• Does it end with a meaningful implication, not just “more research is needed”?

If you can answer yes to those questions, you’re much closer to the level of the real, publishable examples you’ve just seen—and your abstract is far more likely to get your quantitative study the attention it deserves.