Distributed Medical Education (DME) in psychiatry: perspectives on facilitators, obstacles, and factors affecting psychiatrists' willingness to engage in teaching activities
Bibliographic record
Abstract
Abstract Background Distributed Medical Education (DME), a decentralized model focused on smaller cities and communities, has been implemented worldwide to bridge the gap in psychiatric education. Faculty engagement in teaching activities such as clinical teaching, supervision, and examinations is a crucial aspect of DME sites. Implementing or expanding DME sites requires careful consideration to identify enablers that contribute to success and barriers that need to be addressed. This study aims to examine enablers, barriers, and factors influencing psychiatrists' willingness to start or continue participating in teaching activities within Dalhousie University's Faculty of Medicine DME sites in two provinces in Atlantic Canada. Methodology This cross-sectional study was conducted as part of an environmental scan of Dalhousie Faculty of Medicine’s DME programs in Nova Scotia (NS) and New Brunswick (NB), Canada. In February 2023, psychiatrists from seven administrative health zones in these provinces anonymously participated in an online survey. The survey, created with OPINIO, collected data on sociodemographic factors, practice-related characteristics, medical education, and barriers to teaching activities. Five key outcomes were assessed, which included psychiatrists' willingness to engage in (i) clinical training and supervision, (ii) lectures or skills-based teaching, (iii) skills-based examinations, (iv) training and supervision of Canadian-trained psychiatrists, and (v) training and supervision of internationally trained psychiatrists. The study employed various statistical analyses, including descriptive analysis, chi-square tests, and logistic regression, to identify potential predictors associated with each outcome variable. Results The study involved 60 psychiatrists, primarily male (69%), practicing in NS (53.3%), with international medical education (69%), mainly working in outpatient services (41%). Notably, 60.3% lacked formal medical education training, yet they did not perceive the lack of training as a significant barrier, but lack of protected time as the main one. Despite this, there was a strong willingness to engage in teaching activities, with an average positive response rate of 81.98%. The lack of protected time for teaching/training was a major barrier reported by study participants. Availability to take the Royal College of Physicians and Surgeons of Canada Competency by Design training was the main factor associated with psychiatrists' willingness to participate in the five teaching activities investigated in this study: willingness to participate in clinical training and supervision of psychiatry residents (p = .01); provision of lectures or skills-based teaching for psychiatry residents (p < .01); skills-based examinations of psychiatry residents (p < .001); training/supervision of Canadian-trained psychiatrists (p < .01); and training and supervision of internationally trained psychiatrists (p < .01). Conclusion The study reveals a nuanced picture regarding psychiatrists' engagement in teaching activities at DME sites. Despite a significant association between interest in formal medical education training and willingness to participate in teaching activities, clinicians do not consider the lack of formal training as a barrier. Addressing this complexity requires thoughtful strategies, potentially involving resource allocation, policy modifications, and adjustments to incentive structures by relevant institutions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".