This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline.

Medicine is especially suitable for this exercise because it naturally combines symptoms, diagnoses, treatments, risk factors, biomarkers, patient-reported outcomes, clinical workflows, health-system performance, and ethical decision-making. It also supports quantitative, qualitative, and mixed methods designs, making it ideal for showing how the same medical issue can be studied through clinical trials, observational datasets, electronic health records, interviews, patient narratives, and integrated designs.

In medical research, common theoretical and conceptual foundations include the biomedical model, biopsychosocial model, clinical epidemiology, evidence-based medicine, health behavior theories, shared decision-making frameworks, patient-centered care models, implementation science frameworks, and models of health services quality and safety. These frameworks define constructs such as disease severity, treatment response, adherence, risk, trust, symptom burden, quality of life, acceptability, and care experience, which are then operationalized through laboratory values, diagnostic indicators, clinical scales, patient-reported outcome measures, utilization records, interviews, observations, or integrated clinical and experiential datasets.

Note: The entries in the Methodology are intentionally general and indicative. They are meant to illustrate plausible methodological directions, not to exhaust the full range of possible methods, model variants or analytic choices available to the researcher. Researchers are not expected to apply all of the methodological tools listed in column Methodology in a single study. The entries are intended to indicate suitable methodological options or families of approaches from which the researcher selects those that best fit the research question, hypothesis, data, and design.