Associations Between Burnout and Mental Disorder Symptoms Among Nurses in Canada
Bibliographic record
Abstract
BACKGROUND: Nurses appear to be at a greater risk of burnout compared to other medical professionals. Higher levels of burnout are significantly associated with higher levels of anxiety, stress, and depression symptoms. PURPOSE: The current study was designed to estimate levels of burnout among Canadian nurses, examine the association between burnout and mental disorder symptoms, and identify characteristics that may increase the risk for reporting symptoms of burnout. METHOD: = 3257; 94.3% women) were surveyed online in both English and French. The survey assessed current symptoms of burnout and mental disorders (i.e., Posttraumatic Stress Disorder, Major Depressive Disorder, Generalized Anxiety Disorder, Panic Disorder). RESULTS: Most nurses (63.2%) reported at least some symptoms of burnout and many (29.3%) reported clinically significant levels of burnout. Age and years of service were the only demographic variables that explained burnout rates. Participants reporting clinically significant levels of burnout were significantly more likely than participants with no burnout to screen positive for all mental disorders, but particularly for Major Depressive Disorder. CONCLUSIONS: Monitoring burnout may be an effective way to identify nurses at risk of developing symptoms of mental disorders. Younger and early-career nurses are an important group to target for prevention programs.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".