Doctors' attitudes to maintenance of professional competence: A scoping review
Bibliographic record
Abstract
CONTEXT: Recent decades have seen the international implementation of programmes aimed at assuring the continuing competence of doctors. Maintenance of Professional Competence (MPC) programmes aim to encourage doctors' lifelong learning and ensure high-quality, safe patient care; however, programme requirements can be perceived as bureaucratic and irrelevant to practice, leading to disengagement. Doctors' attitudes and beliefs about MPC are critical to translating regulatory requirements into committed and effective lifelong learning. We aimed to summarise knowledge about doctors' attitudes to MPC to inform the development of MPC programmes and identify under-researched areas. METHODS: We undertook a scoping review following Arksey and O'Malley, including sources of evidence about doctors' attitudes to MPC in the United States, the United Kingdom, Canada, Australia, New Zealand and Ireland, and using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) as a guide. RESULTS: One hundred and twenty-five sources of evidence were included in the review. One hundred and two were peer-reviewed publications, and 23 were reports. Most were from the United Kingdom or the United States and used quantitative or mixed methods. There was agreement across jurisdictions that MPC is a good idea in theory but doubt that it achieves its objectives in practice. Attitudes to the processes of MPC, and their impact on learning and practice were mixed. The lack of connection between MPC and practice was a recurrent theme. Barriers to participation were lack of time and resources, complexity of the requirements and a lack of flexibility in addressing doctors' personal and professional circumstances. CONCLUSIONS: Overall, the picture that emerged is that doctors are supportive of the concept of MPC but have mixed views on its processes. We highlight implications for research and practice arising from these findings.
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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 | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".