Future practice of comprehensive care: Practice intentions of exiting family medicine residents in Canada.
Bibliographic record
Abstract
OBJECTIVE: To describe exiting family medicine (FM) residents' reported practice intentions after completing a Triple C Competency-based Curriculum. DESIGN: The surveys were intended to capture residents' perceptions of FM, their perceptions of their competency-based training, and their intentions to practise FM. Entry (T1) and exit (T2) self-reported survey results were compared considering the influence of the curriculum change. Unmatched aggregate-level data were reviewed. The T1 survey was administered in the summer of 2012 and the T2 survey was administered in the spring of 2014. SETTING: Six Canadian FM residency programs across 4 provinces in Canada (Alberta, Saskatchewan, Ontario, and Quebec). PARTICIPANTS: Overall, 341 entering FM residents in 2012 responded to the T1 survey and 325 exiting FM residents completing their residency programs in spring 2014 responded to the T2 survey. MAIN OUTCOME MEASURES: Self-reported data on FM residents' future practice intentions related to comprehensive care, providing care across clinical domains and settings, and providing comprehensive care individually or in teams. RESULTS: A total of 341 (71.3%) residents responded to the T1 survey and a total of 325 (71.4%) residents responded to the T2 survey. Of these, 78.7% responded that they intended to provide comprehensive FM in multiple clinical settings in their future practices, with 70.8% indicating a comprehensive care practice with a special interest and 36.6% intending to provide care in a focused practice. Overall, 92.9% reported that they intended to work in group practice environments. Ninety percent reported they intended to work in interprofessional team practices. CONCLUSION: While an upward trend toward the practice of comprehensive care was demonstrated, findings also showed an increased trend toward providing care in focused practices. Further research is needed to better determine how FM residents understand the definition of comprehensive FM and its practice models. The survey provides an opportunity to explore questions related to practice intentions that could be helpful in work force planning. As the first study to compare entry and exit data from learners who have been exposed to a Triple C competency-based approach, this survey provides important baseline data for use by many.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".