Research Methodology
This domain tests whether you can read and critique dental research.
Core rules
- Study designs include case report, cross-sectional, case-control, cohort, randomized controlled trial and systematic review. RCTs best support causation; cohorts estimate incidence; case-control studies suit rare outcomes.
- Bias includes selection, measurement, recall, publication and confounding. Randomization and blinding reduce bias.
- Diagnostic statistics include sensitivity, specificity, positive predictive value and negative predictive value. Positive predictive value depends on prevalence.
- A p value is the probability of the data given the null hypothesis, not the probability that the null is true. Confidence intervals show precision. Intention-to-treat preserves randomization.
- Sample size depends on effect size, power, alpha and variance.
Worked example
A trial reports p = 0.04 and a mean pain difference of 0.3 on a 10-point scale. The result is statistically significant but may not be clinically important. Interpret the confidence interval and the smallest worthwhile effect, not the p value alone.
Traps
Equating statistical with clinical significance; ignoring confounding; quoting positive predictive value without prevalence; overtrusting post hoc subgroup analyses.