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Implementation of structured feedback in a psychiatry residency program in Canada: a qualitative analysis study
Anupam Thakur1,2, Shaheen Darani1,2, Csilla Kalocsai2,3
1Centre for Addiction and Mental Health, Toronto, ON, Canada.
The R2C2 feedback model aids competency-based medical education (CBME) progression. Key facilitators for its implementation include structured training, self-efficacy, and organizational readiness, crucial for effective feedback delivery.
Area of Science:
- Medical Education
- Psychiatry Residency Training
- Implementation Science
Background:
- Structured feedback is vital for learner progression in competency-based medical education (CBME).
- The R2C2 feedback model is evidence-based but factors influencing its implementation require further study.
- This pilot study examines R2C2 implementation in a psychiatry CBME program.
Purpose of the Study:
- To describe the implementation of the R2C2 feedback model in a psychiatry residency program.
- To identify factors influencing the implementation of the R2C2 model using the Consolidated Framework for Implementation Research (CFIR).
Main Methods:
- A pilot study involving three phases: planning, implementation, and evaluation.
- Fifteen supervisors received training and utilized the R2C2 model with residents.
- Semi-structured interviews with 10 supervisors explored their experiences, analyzed using CFIR domains.
Main Results:
- Qualitative analysis identified four key themes: perceptions of R2C2, implementation facilitators/barriers, fidelity, and intersectionality.
- The CFIR framework structured the analysis of implementation factors.
- Key facilitators included the model's structure, supervisor self-efficacy, educational expertise, learning culture, organizational readiness, and training support.
Conclusions:
- The R2C2 model is a valuable tool for structured feedback in CBME.
- Successful implementation hinges on factors like model structure, self-efficacy, institutional support, and training.
- Further research should investigate learner perspectives and model fidelity.
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