Sample size determination across study designs in health professions education research: a methodology guide.

Background: Sample size determination is one of the least reported elements in the methods sections of health professions education (HPE) research. Underpowered studies miss real effects, whereas overpowered studies waste participants and resources. Guidance remains fragmented across statistical textbooks and discipline-specific papers, with no unified reference for HPE researchers. Methods: We developed this guide as a structured narrative synthesis. Sources were identified through targeted database searching, citation chaining, and standard statistical texts, and selected against pre-specified criteria; where recommendations conflicted, precedence was given to the primary methodological source and to empirical evidence generated within HPE. Rather than proposing a universal formula, which does not exist, we organised sample-size logic by study design. We set out a stepwise workflow and emphasise that the expected difference should be anchored to previous evidence and to educational importance, with pilot work used to estimate variability, recruitment and attrition rather than the effect size itself. For each design we give the statistical rationale, the applicable formula or rule, a worked example with fully stated assumptions, and reporting expectations. Results: The designs covered include two-group comparisons of means and proportions, pre-post and repeated-measures designs, cluster-randomized educational trials, survey and questionnaire studies, Delphi and consensus studies, pilot and feasibility studies, qualitative enquiry, simulation-based education, and instrument validation. The guide concludes with a reporting checklist for the methods section, serving investigators, peer reviewers, and journal editors. Precision-based planning, software implementation, and designs beyond closed-form calculation are addressed separately. Conclusions: Sample size in HPE research is a design-specific judgment, not a formula-specific calculation. The numerical benchmarks reproduced here are illustrative anchors rather than methodological minima. This guide consolidates that judgment into a practical reference reflecting the methodological diversity of the field.