Advancing physician wellness, engagement and excellence in a mental health setting: a Canadian perspective
Bibliographic record
Abstract
This article describes the development and implementation of wellness initiatives within a large Canadian academic mental health hospital, based on the Mental Health Commission of Canada's workplace standards for mental health. To support the implementation of an organizational framework for physician wellness, a needs assessment of Centre for Addiction and Mental Health physicians (N = 181) was conducted between 21 November and 5 December 2017, including measuring physician burnout rates using two items on the Maslach Burnout Inventory tool. Based on findings, and the organizational wellness framework, a multi-pronged wellness approach was developed, improving physician supports at the individual, team and organizational levels. Eighty-four survey responses (46% response rate) were gathered across eight clinical divisions, with 59% of respondents stating that they were negatively impacted by emotionally stressful events at work within the past year. Themes emerging from open-ended questions included the importance of a culture of safety and wellbeing, leadership accountability and availability of formal supports and processes. In response to survey findings, and our organizational framework, the following six initiatives were implemented: (i) a peer support program, (ii) an office of professionalism, (iii) individual and group mentorship opportunities, (iv) communities of practice, (v) enhanced training and leadership development opportunities, and (vi) efforts to optimize use of electronic health records to enhance efficiency of practice. It is possible to implement a multifaceted organizational approach to physician wellness, engaging physicians and continuously adapting in response to physician input. Future robust evaluation of these strategies can inform organizational roadmaps to improve physician wellness.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.027 | 0.011 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".