Mental health, job satisfaction, and intention to relocate. Opinions of physicians in rural British Columbia.
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of depression and burnout among family physicians working in British Columbia's Northern and Isolation Allowance communities. Current level of satisfaction with work and intention to move were also investigated. DESIGN: Cross-sectional, mailed survey. SETTING: Family practices in rural communities eligible for British Columbia's Northern and Isolation Allowance. PARTICIPANTS: A random sample of family physicians practising in rural BC communities. Initial response rate was 66% (131/198 surveys returned); excluding physicians on leave and in temporary situations and those who received duplicate mailings gave a corrected response rate of 92% (131/142 surveys returned). MAIN OUTCOME MEASURES: Demographics; self-reported depression and burnout; Beck Depression Inventory and Maslach Burnout Inventory scores; job satisfaction; and intention to leave. RESULTS: Self-reported depression rate was 29%; the Beck Depression Inventory indicated 31% of physicians suffered from mild to severe depression. About 13% of physicians reported taking antidepressants in the past 5 years. Self-reported burnout rate was 55%; the Maslach Burnout Inventory showed that 80% of physicians suffered from moderate-to-severe emotional exhaustion, 61% suffered from moderate-to-severe depersonalization, and 44% had moderate-to-low feelings of personal accomplishment. Depression scores correlated with emotional exhaustion scores. More than half the respondents were considering relocation. CONCLUSION: Physicians working in these communities suffer from high levels of depression and very high levels of burnout and are dissatisfied with their current jobs. More than half are considering relocating. Intention to move is strongly associated with poor mental health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".