May I long experience the joy of healing: professional and personal wellbeing among physicians from a Canadian province
Bibliographic record
Abstract
BACKGROUND: The development of best practices to promote physician wellbeing at the individual and organisational levels is receiving increased attention. Few studies have documented how physicians perceive their wellbeing in these contexts. The purpose of this qualitative study is to identify and discuss the reported factors that hinder wellbeing, as well as the reported factors that would promote wellbeing among physicians. METHODS: There were 165 physicians from a province of Canada who wrote their open-ended responses to two questions, as part of a larger self-report questionnaire. The questions asked what causes them stress, and what interventions should be implemented at organisational/institutional levels. The largest specialty was family medicine, followed by internal medicine, and surgical disciplines, with 58% of participants male. A general inductive approach was used to analyze the data and themes and sub-themes were discovered using the socio-ecological model as the framework. RESULTS: Reponses were both personal and professional which resulted in the emergence of four major themes to reflect this diversity. These themes were external constraints on the practice of medicine, issues at the professional/institutional levels, issues at the individual practice level, and work/life balance. The work/life balance theme received the highest number of responses followed by external constraints on the practice of medicine. In the major theme of work-life balance, work-life conflict received the most responses, and in the major theme of external constraints on practice of medicine, lack of resources (human and material) and restrictions to autonomy received the most responses. Ideas for interventions in the work/life balance theme were health promotion, and healthy workplace initiatives. In the second largest theme, suggested ideas for interventions were collegiality/professionalism and policy formulation at the health care system. CONCLUSION: Our findings have implications for governance and health policy, health human resources and education. In particular, the socio-ecological framework was a useful framework to analyse physician wellbeing due to its applicability for issues at the structural, organisational, and individual levels. Future research should target interventions at the organisational and institutional levels to address work-life conflict and job dissatisfaction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".