The Ebb and Flow of Identity Formation and Competence Development in Sub-specialty Residents: Study of a Continuity Training Setting
Bibliographic record
Abstract
Abstract Background Professional identity and competence development are evolving processes, shaped by clinical experiences and socialization in the workplace. The purpose of this study was to investigate the simultaneous development of professional identify formation and competence in a sub-specialty training program. Methods The study was conducted in a General Internal Medicine sub-specialty (PGY-4 and PGY-5) continuity training setting, at an academic health sciences center, in Canada. Participants included: current residents, recent graduates, attending physicians and administrative assistants. Data was collected from 2017–2018. A constructivist grounded theory approach was used to analyze anonymized focus group and individual interviews. Results The study identified the following: 1) learning activities that support professional identity formation in advanced residents; 2) the relationship between professional identity formation and competencies; 3) the role of administrative assistants and continuity training supervisors in supporting professional identity formation; and 4) a set of invisible learning experiences that occurred as a result of assumptions made by residents about expectations of training and expectations of patient care. Although, there was limited data available on the latter, findings suggested that invisible learning experiences may adversely impact residents’ functioning as independent physicians. Conclusions Residents’ professional identities continue to evolve with increasing competency requirements during training. Training programs, for sub-specialty residents, must balance granting of independence with supporting ongoing professional identity formation. They must also be explicit about what constitutes healthy patient care expectations and how practicing physicians manage these expectations.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| 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".