Physician, heal thyself: Survey of users of the Quebec Physicians Health Program.
Bibliographic record
Abstract
OBJECTIVE: To document the opinions of the users of the Quebec Physicians Health Program (QPHP) about the services they received. DESIGN: Mailed questionnaire. SETTING: Quebec. PARTICIPANTS: A total of 126 physicians who used QPHP services between 1999 and 2004. MAIN OUTCOME MEASURES: Users' overall rating of the QPHP services, their opinions about the program, and whether their situations improved as a result of accessing QPHP services. RESULTS: Ninety-two of the 126 physicians surveyed returned their completed questionnaires, providing a response rate of 73%. Most respondents thought that the QPHP services were good or excellent (90%), most would use the program again (86%) or recommend it (96%), and most thought the Quebec physician associations and the Collège des médecins du Québec should continue funding the QPHP (97%). Most respondents thought the service confidentiality was excellent (84%), as was staff professionalism (82%), and 62% thought the quality of the services they were referred to was excellent. However, only 57% believed their situations had improved with the help of the QPHP. CONCLUSION: The QPHP received good marks from its users. Given the effects of physician burnout on patients and on the health care system, it is not only a personal problem, but also a collective problem. Thus, actions are needed not only to set up programs like the QPHP for those suffering from burnout, but also to prevent these types of problems. Because family physicians are likely to be the first ones consulted by their physician patients in distress, they play a key role in acknowledging these problems and referring those colleagues to the appropriate help programs when needed.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".