Understanding the barriers and enablers for postgraduate medical trainees becoming simulation educators: a qualitative study
Bibliographic record
Abstract
INTRODUCTION : There is increasing evidence that Simulation-based learning (SBL) is an effective teaching method for healthcare professionals. However, SBL requires a large number of faculty to facilitate small group sessions. Like many other African contexts, Mbarara University of Science and Technology (MUST) in Uganda has large numbers of medical students, but limited resources, including limited simulation trained teaching faculty. Postgraduate medical trainees (PGs) are often involved in clinical teaching of undergraduates. To establish sustainable SBL in undergraduate medical education (UME), the support of PGs is crucial, making it critical to understand the enablers and barriers of PGs to become simulation educators. METHODS: We used purposive sampling and conducted in-depth interviews (IDIs) with the PGs, key informant interviews (KIIs) with university staff, and focus group discussions (FGDs) with the PGs in groups of 5-10 participants. Data collection tools were developed using the Consolidated framework for implementation research (CFIR) tool. Data were analyzed using the rigorous and accelerated data reduction (RADaR) technique. RESULTS: We conducted seven IDIs, seven KIIs and four focus group discussions. The barriers identified included: competing time demands, negative attitude towards transferability of simulation learning, inadequacy of medical simulation equipment, and that medical simulation facilitation is not integrated in the PGs curriculum. The enablers included: perceived benefits of medical simulation to medical students plus PGs and in-practice health personnel, favorable departmental attitude, enthusiasm of PGs to be simulation educators, and improved awareness of the duties of a simulation educator. Participants recommended sensitization of key stakeholders to simulation, training and motivation of PG educators, and evaluation of the impact of a medical simulation program that involves PGs as educators. CONCLUSION: In the context of a low resource setting with large undergraduate classes and limited faculty members, SBL can assist in clinical skill acquisition. Training of PGs as simulation educators should address perceived barriers and integration of SBL into UME. Involvement of departmental leadership and obtaining their approval is critical in the involvement of PGs as simulation educators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".