Evaluating Scientific Evidence Flashcards

A researcher claims that a new drug reduces blood pressure based solely on a study of 12 patients over two weeks. Which limitation most significantly weakens this evidence?

Answer: The sample size is too small to generalize findings

A sample of 12 patients is far too small to draw reliable generalizations, making the findings ungeneralizable to broader populations.

Which study design provides the strongest evidence for establishing a causal relationship between an intervention and a health outcome?

Answer: Randomized controlled trial

Randomized controlled trials minimize confounding through random assignment, making them the gold standard for establishing causality.

A meta-analysis of 20 studies concludes that vitamin D supplementation reduces fracture risk. One study in the analysis had 10,000 participants while the others averaged 200. What is the most appropriate concern?

Answer: The large study may disproportionately influence the pooled result

In meta-analyses, a single large study can dominate the pooled estimate, potentially skewing results if that study has unique methodological features.

A study reports a statistically significant result with p = 0.04. What does this indicate?

Answer: The result has a 4% chance of occurring if the null hypothesis is true

A p-value of 0.04 means there is a 4% probability of observing a result this extreme or more extreme assuming the null hypothesis is true.

Researchers find a strong positive correlation (r = 0.85) between ice cream sales and drowning rates. The most accurate interpretation is:

Answer: A third variable (hot weather) likely explains both

Correlation does not imply causation; a confounding variable like hot weather explains both increased ice cream sales and increased swimming activity.

Which of the following best describes 'publication bias' in the context of medical research?

Answer: Journals preferentially publish studies with positive or significant results

Publication bias occurs when journals disproportionately publish studies showing positive or statistically significant results, skewing the literature.

An observational study concludes that coffee drinkers have lower rates of type 2 diabetes. A reviewer notes that coffee drinkers in the study also exercised more. This is an example of:

Answer: Confounding

Confounding occurs when a third variable (exercise) is associated with both the exposure (coffee) and the outcome (diabetes), distorting the apparent relationship.