Supervised near-peer clinical teaching in the ambulatory clinic: an exploratory study of family medicine residents’ perspectives
Bibliographic record
Abstract
Near-peer teaching is used extensively in hospital-based rotations but its use in ambulatory care is less well studied. The objective of this study was to verify the benefits of near-peer teaching found in other contexts and to explore the benefits and challenges of near-peer clinical supervision unique to primary care. A qualitative descriptive design using semi-structured interviews was chosen to accomplish this. A faculty preceptor supervised senior family medicine residents as they supervised a junior resident. We then elicited residents' perceptions of the experience. The study took place at a family medicine teaching unit in Canada. Six first-year and three second-year family medicine residents participated. Both junior and senior residents agreed that near-peer clinical supervision should be an option during family medicine residency training. The senior resident was perceived to benefit the most. Near-peer teaching was found to promote self-reflection and confidence in the supervising resident. Residents felt that observation by a faculty preceptor was required. In conclusion, the benefits of near-peer teaching previously described in hospital settings can be extended to ambulatory care training programmes. However, the perceived need for direct observation in a primary care context may make it more challenging to implement.
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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 | 0.016 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".