Peer‑led bioethics education in clinical rotations: Three generalisable lessons from a CFIR‑informed implementation case study.

BACKGROUND

Integrating bioethics into clinical training is challenging, particularly in resource-constrained settings. Scalable and low‑cost models are needed but are under‑evaluated. This implementation case study assessed the feasibility and perceived impact of a peer-led, case-based bioethics discussion model.

METHODOLOGY/PRINCIPAL FINDINGS: We conducted a single embedded case study at the College of Medicine in the Kurdistan Region of Iraq. Forty-four final-year medical students participated in structured peer‑led discussions of authentic clinical ethics cases using a four‑step analytical framework. Quantitative data (post-intervention Likert questionnaire) were analyzed descriptively. Qualitative data (open‑ended responses, case summaries) underwent deductive thematic analysis guided by the Consolidated Framework for Implementation Research (CFIR) to identify barriers and facilitators across five domains. Students strongly endorsed the intervention: 59.1% strongly agreed that ethics education is important (mean 4.51/5.0). Enjoyment was high (75% agreed/strongly agreed). Self-efficacy was variable (54.5% confident, 29.5% uncertain). CFIR analysis revealed key implementation determinants: low cost and high perceived relevance (facilitators), supportive peer culture (facilitator), limited time (barrier), and need for faculty orientation (barrier). From these findings, we derived three generalizable propositions for implementing low‑cost ethics curricula.

CONCLUSIONS/SIGNIFICANCE: A peer-led, case-based bioethics model is feasible and well received. Three generalizable lessons are offered: (1) peer‑led models require protected time and leveraged peer cultures; (2) single sessions raise awareness, but longitudinal reinforcement is essential for self‑efficacy; and (3) CFIR reporting enables analytical generalizability for single‑case studies. These propositions provide a blueprint for replication and further testing in low‑resource settings.