Progressive Independence in Clinical Training: A Tradition Worth Defending?
Bibliographic record
Abstract
BACKGROUND: Progressive independence is a traditional premise of clinical training. Recently, issues such as managed care, work hours limitation, and patient safety have begun to impact the degree of autonomy afforded to clinical trainees. This article reviews empirical evidence and theory pertaining to the role of progressive autonomy in clinical learning. METHOD: A computerized literature search was performed using Medline, PsycINFO, Social Sciences Citation Index, and Educational Resources Information Center. This article presents a synthetic review of relevant empirical and theoretical concepts from the domains of medicine, psychology, education, kinesiology, and sociology. RESULTS: The clinical psychology and medical education literatures provide evidence that clinical trainees act more independently as their training progresses, but have not yet evaluated the educational efficacy of providing progressive independence, or the consequences of failing to do so. The expertise and motor learning literatures provide some theoretical evidence (as yet untested in complex clinical environments) that the provision of too much guidance or feedback to trainees could be educationally detrimental in the long term. The sociology literature provides insight into the cultural values underlying the behavior of clinical teachers and trainees relating to issues of supervision and independence. CONCLUSIONS: There is limited empirical support for the current model of progressive independence in clinical learning; however, diverse theoretical perspectives raise concern about the potential educational consequences of eroding progressive independence. These perspectives could inform future research programs that would create a creative and effective response to the social and economic forces impacting clinical education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".