Anatomy of a Research Paper
Scientific papers follow a standard structure. Understanding each section helps you extract meaningful information and evaluate the research quality.
The Abstract
The abstract summarizes the entire study in a paragraph. While useful for quick assessment, it has limitations:
- May emphasize positive findings
- Omits methodology details
- Cannot capture nuance or limitations
Tip: Use the abstract to decide if the full paper is worth reading, but never rely on it alone for conclusions.
Introduction
The introduction provides background and states the research question. Look for:
- What gap in knowledge does this address?
- What prior research informs this study?
- What is the specific hypothesis or objective?
Methods
The methods section is crucial for evaluating quality. Key questions:
Study Design
- Was this in vitro, animal, or human research?
- Was there a control group?
- Were subjects randomized? Blinded?
Subjects/Samples
- How many subjects were included?
- What were the inclusion/exclusion criteria?
- How representative are they of broader populations?
Procedures
- What exactly was done to subjects?
- What doses, durations, and administration routes were used?
- What outcomes were measured and how?
Analysis
- What statistical methods were used?
- Were they appropriate for the data type?
- Was the study powered to detect meaningful differences?
Results
The results present data without interpretation. Look for:
- Effect sizes — How large were the differences?
- Statistical significance — P-values indicate probability results are due to chance
- Confidence intervals — Show the range of plausible effect sizes
- All outcomes — Were all measured outcomes reported, or just selected ones?
Tip: Statistical significance doesn't equal practical significance. A tiny effect can be statistically significant with large sample sizes.
Discussion
The discussion interprets results and acknowledges limitations. Look for:
- How do findings compare to prior research?
- What limitations do the authors acknowledge?
- What alternative explanations exist for the findings?
- What future research is needed?
Tip: Authors may spin findings positively. Consider whether their interpretation is supported by the actual data.
Evaluating Quality
After reading, assess overall quality:
- Sample size — Larger is generally better for detecting real effects
- Controls — Proper control groups isolate the variable being studied
- Blinding — Reduces bias in assessment of outcomes
- Replication — Has this been repeated by independent researchers?
- Conflicts of interest — Who funded the study? Do authors have commercial ties?
- Journal quality — Reputable journals have rigorous peer review
Common Pitfalls
- Treating preliminary findings as conclusive
- Generalizing from specific populations or conditions
- Ignoring limitations and alternative explanations
- Confusing correlation with causation
- Cherry-picking studies that support desired conclusions