COVID-19 pandemic-related anxiety, distress and burnout: prevalence and associated factors in healthcare workers of North-West Italy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic caused drastic changes in healthcare and severe social restrictions. Healthcare workers (HCWs) are on the front line against the virus and have been highly exposed to pandemic-related stressors, but there are limited data on their psychological involvement for a large sample in Italy. AIMS: To investigate the prevalence of anxiety, distress and burnout in HCWs of North-West Italy during the COVID-19 pandemic, and to detect potential psychosocial factors associated with their emotional response. METHOD: This cross-sectional, survey-based study enrolled 797 HCWs. Participants completed the Impact of Event Scale - Revised, the State-Trait Anxiety Inventory - Form Y and the Maslach Burnout Inventory; demographic, family and work characteristics were also collected. Global psychological outcome, differences among professions and independent factors associated with worst psychological outcome were assessed. RESULTS: Almost a third of the sample had severe state anxiety and distress, high emotional exhaustion and depersonalisation, and low personal accomplishment. Distress was higher in women and nurses, whereas depersonalisation was higher in men. Family division, increased workload, job changes and frequent contact with COVID-19 were associated with worst psychological outcome. Trait anxiety was associated with significantly higher risk for developing state anxiety, distress and burnout. CONCLUSIONS: An elevated psychological burden related to the COVID-19 pandemic was observed in HCWs of North-West Italy. The identification of family and work characteristics and a psychological pre-existing condition as factors associated with worst psychological outcome may help provide a tailored, preventive, organisational and psychological approach in counteracting the psychological effects of future pandemics.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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 it