Exploring the experience of residents during the first six months of family medicine residency training
Bibliographic record
Abstract
Background: The shift from undergraduate to postgraduate education signals a new phase in a doctor’s training. This study explored the resident’s perspective of how the transition from undergraduate to postgraduate (PGME) training is experienced in a Family Medicine program as they first meet the reality of feeling and having the responsibility as a doctor.Methods: Qualitative methods explored resident experiences using interpretative inquiry through monthly, individual in-depth interviews with five incoming residents during the first six months of training. Focus groups were also held with residents at various stages of training to gather their reflection about their experience of the first six months. Residents were asked to describe their initial concerns, changes that occurred and the influences they attributed to those changes.Results: Residents do not begin a Family Medicine PGME program knowing what it means to be a Family Physician, but learn what it means to fulfill this role. This process involves adjusting to significant shifts in responsibility in the areas of Knowledge, Practice Management, and Relationships as they become more responsible for care outcomes.Conclusion: This study illuminated the resident perspective of how the transition is experienced. This will assist medical educators to better understand the early training experiences of residents, how these experiences contribute to consolidating their new professional identity, and how to better align teaching strategies with resident learning needs.
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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 | 0.005 | 0.013 |
| 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 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".