Psychological distress of mental health workers during the COVID‐19 pandemic: A comparison with the general population in high‐ and low‐incidence regions
Bibliographic record
Abstract
OBJECTIVE: Despite their essential role during this health crisis, little is known about the psychological distress of mental health workers (MHW). METHOD: A total of 616 MHW and 658 workers from the general population (GP) completed an online survey including depressive, anxiety, irritability, loneliness, and resilience measures. RESULTS: Overall, MHW had fewer cases with above cut-off clinically significant depression (19% MHW vs. 27%) or anxiety (16% MHW vs. 29%) than the GP. MHW in high-incidence regions of COVID-19 cases displayed the same levels of depressive and anxiety symptoms than the GP and higher levels compared to MHW from low-incidence regions. MHW in high-incidence regions presented higher levels of irritability and lower levels of resilience than the MHW in low-incidence regions. Moreover, MHW in high-incidence regions reported more feelings of loneliness than all other groups. CONCLUSION: Implications for social and organizational preventive strategies to minimize the distress of MHW in times of crisis are discussed.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".