When I see a headline about a new scientific study, my first reflex isn't excitement — it's curiosity. As a reader and editor, I've learned that the real story is often in the details journalists don't always have room to print. Over the years I’ve developed a set of practical questions I ask myself to decide whether a study deserves attention, caution, or outright skepticism. Here’s the checklist I use and explain to readers so you can read reported science with more confidence and fewer surprises.
Who funded the research and who is reporting it?
Start with incentives. Funding sources and institutional ties matter because they can shape research priorities and, in some cases, interpretation. A pharmaceutical company funding a drug trial isn't a deal-breaker — industry funds many rigorously conducted studies — but it does mean I want to see transparency about conflicts of interest and independent replication.
- Check whether the article or press release names the funder and the authors’ affiliations.
- Look for statements about conflicts of interest in the original paper (often in the acknowledgements or at the end).
- Be wary if a media report relies solely on a press release from a single company or university without independent expert comment.
What kind of study is it?
All studies are not created equal. The headline “study shows” can mean wildly different things depending on design.
- Randomized controlled trials (RCTs) are the strongest design for testing cause-and-effect for interventions (like drugs or behavioral programs).
- Observational studies can detect associations but cannot prove causation; they’re vulnerable to confounding variables.
- Meta-analyses and systematic reviews can be powerful if they aggregate high-quality studies, but their value depends on the quality and consistency of included research.
- Animal or cellular studies are valuable for mechanisms but often don’t translate directly to humans.
I always look for the study type early in the paper or press materials; if the reporting never states it, that’s a red flag.
How large and representative was the sample?
Sample size and selection determine how much we can generalize results.
- Small sample sizes (tens rather than hundreds or thousands) often produce noisy results and exaggerated effects.
- Non-representative samples — for instance, convenience samples like volunteers on social media or students in a psychology lab — limit generalizability.
- For clinical research, check whether the sample reflects the population likely to use the intervention (age, sex, comorbidities, ethnicity).
When reading a press report that claims “this works for everyone,” I ask whether the study actually tested a diverse group or just a narrow slice of people.
What were the outcomes and how were they measured?
Outcomes matter as much as the headline. Researchers can measure everything from hard endpoints (death, hospitalization) to softer or surrogate markers (biomarkers, self-reported symptoms).
- Objective, clinically meaningful outcomes are more convincing than self-reported surveys or surrogate markers.
- Look for clear definitions: what does “improved” mean? By how much? Over what time period?
- Be skeptical of studies that report multiple outcomes without clear primary endpoints — this can be a sign of “p-hacking” or data mining for significant results.
Are the results statistically and practically significant?
Statistical significance (a p-value under 0.05) doesn't automatically mean the effect is important in the real world.
- Ask for effect sizes and confidence intervals — they tell you how big and certain the effect is, not just whether it exists statistically.
- A tiny relative improvement (e.g., 5% relative reduction) may sound impressive in a news headline but translate into negligible absolute benefit.
- Large studies can find statistically significant but trivial differences; small studies can miss meaningful effects.
How was the analysis done — and was it pre-registered?
Science has moved toward greater transparency. Pre-registration (declaring the study plan and primary outcomes in advance) helps prevent selective reporting.
- Check whether the study was pre-registered on a public registry (ClinicalTrials.gov for clinical trials, Open Science Framework for other studies).
- Beware of post-hoc analyses presented as if they were planned; those are exploratory and require independent confirmation.
- Ask whether the researchers adjusted for key confounders and used appropriate statistical controls.
Were there control groups and blinding?
Controls and blinding reduce bias.
- In trials, a placebo or active comparator helps reveal whether an effect is real or due to expectation.
- Blinding (participants and researchers unaware of group assignments) prevents conscious or unconscious influence on outcomes.
- Unblinded studies can still be informative, but their limitations must be clearly acknowledged.
Do independent experts agree or raise concerns?
When a study is covered in the media, look for quotes from independent scientists who don’t have a stake in the research. Their perspective helps contextualize the findings.
- Good reporting includes diverse expert voices — critique and praise alike.
- If coverage lacks independent comment and relies only on the study authors, treat interpretations with caution.
Is the study being over-simplified or sensationalized?
Headlines are designed to attract clicks. As someone who edits daily, I watch for common distortions:
- Claiming causation from correlation (“X causes Y” when the study only finds an association).
- Extrapolating from animal labs to human behavior without caveats.
- Cherry-picking single studies to contradict broad, well-established evidence.
If a report promises a dramatic single-sentence takeaway, I dig into the original paper before sharing or believing it.
Has this been replicated or contradicted by prior research?
One study rarely settles a question. Science advances through replication and synthesis.
- Search for systematic reviews, meta-analyses, or other recent studies on the topic.
- If findings are novel and surprising, they deserve extra scrutiny and independent replication before being accepted as fact.
Where can I find the original paper and data?
I always try to read the original study, or at least the abstract. Open access journals, preprint servers (like bioRxiv, medRxiv), and institutional repositories make that easier. When available, raw data and code are gold — they let independent analysts verify results.
- If the article links to a paywalled paper, look for a preprint or contact the authors; many will share a copy.
- Transparency improves trust: studies that share data and methods are easier to evaluate and replicate.
Reading science reported in the media is an active process — not a passive one. By asking these questions I’ve avoided false alarms, recognized real advances, and helped readers understand the nuance behind the headlines. You don’t need to be a scientist to apply them; you only need curiosity and a little skepticism. If you want, I can walk through a recent high-profile study and apply this checklist step by step so you can see how it works in practice.
