Examining the teaching roles and experiences of non-physician health care providers in family medicine education: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Primary Care reform in Canada and globally has encouraged the development of interprofessional primary care initiatives. This has led to significant involvement of non-physician Health Care Providers (NPHCPs) in the teaching of medical trainees. The objective of this study was to understand the experiences, supports and challenges facing non-physician health care providers in Family Medicine education. METHODS: Four focus groups were conducted using a semi-structured interview guide with twenty one NPHCPs involved in teaching at the University of Toronto, Department of Family & Community Medicine. The focus groups were transcribed and analyzed for recurrent themes. The multi-disciplinary research team held several meetings to discuss themes. RESULTS: NPHCPs were highly involved in Family Medicine education, formally and informally. NPHCPs felt valued as teachers, but this often did not occur until after learners understood their educator role through increased time and exposure. NPHCPs expressed a lack of advance information of learner knowledge level and expectations, and missed opportunities to give feedback or receive teaching evaluations. Adequate preparation time, teaching space and financial compensation were important to NPHCPs, yet were often lacking. There was low awareness but high interest in faculty status and professional development opportunities. CONCLUSIONS: Sharing learner goals and objectives and offering NPHCPs feedback and evaluation would help to formalize NPHCP roles and optimize their capacity for cross-professional teaching. Preparation time and dedicated space for teaching are also necessary. NPHCPs should be encouraged to pursue faculty appointments and to access ongoing Professional Development opportunities.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".