A Pilot Study of a Screening Process for Evaluating the Physical, Mental and Cognitive Health of Senior Physicians
Bibliographic record
Abstract
Physicians are not immune to changes that accompany aging, including decreases in physical and cognitive health and abilities. Many are calling for, or turning to, screening senior physicians for decrements in their ability to provide safe care. Our purpose was to determine the acceptability and feasibility of a pilot screening process, which evaluates the physical, mental and cognitive health of senior physicians. The screening process was developed by the University of California, San Diego, Physician Assessment and Clinical Education Program. The screen included: mental health screening (PHQ-9, GAD-7, and substance abuse screen), cognitive health screening (MicroCog™ and Montreal Cognitive Assessment [MoCA©]) and physical health screening (medical history review and physical examination). Qualitative semi-structured interviews were conducted post-screening. Thirty senior physicians participated in the pilot process, including post-screening interviews. Eight (27%) participants were judged to “require”/“may require” further evaluation after cognitive assessment. No physicians were found to have physical or mental health issues that would prevent them from practicing competently. Interviews revealed that participants felt the screening process was a positive experience that was effective, acceptable, efficient and relevant to their practice. The results of this pilot study indicate that screening physical, mental and cognitive health is considered both feasible and acceptable to senior physicians. This is important as screening the health and cognition of senior physicians is integral to the national discussion related to regulation and patient safety.
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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 | 0.041 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".