Cross-Sectional Study of the Psychological Well-Being of Healthcare Workers in a Large European University Hospital after the COVID-19 Initial Wave
Bibliographic record
Abstract
BACKGROUND: The SARS-CoV-2 pandemic greatly impacted healthcare workers (HCWs) dedicated to caring for COVID-19 patients. The study was conducted in a large European hospital to study the psychological distress of HCWs engaged in COVID-19 wards in the early phase of the pandemic. METHODS: A questionnaire was sent to 1229 HCWs aimed at collecting the following information: 1) sociodemographic data; 2) depression, anxiety, and stress scales (DASS-21); 3) event impact scale (IES-R); 4) perceived stress scale (PSS); and 5) work interface analysis. The responses were collected through Google® forms and then statistically analyzed. Regardless of the outcome of the questionnaire, all subjects were offered psychological support voluntarily. RESULTS: Approximately two-thirds of the workers reported no symptoms according to the DASS-21 scales, while the IES-R and PSS scales showed 36% and 43%, respectively. There were no statistically significant differences in the levels of depression investigated through the different scales in the various occupational categories. Symptoms of anxiety, stress, and depression were more pronounced in women, while the highest stress levels were observed in the younger age groups. The highest scores were observed on the DAS-21 scales of anxiety and IES-R but not on the others. Only 51 workers, most of them with previous SARS-CoV-2 infection, sought clinical psychological counseling, and more than half received subsequent psychological support. CONCLUSIONS: Our results agree with most of the literature data that anxiety, depression, and stress are associated with gender (female), age (18-44 vs. over 55), and having cared for patients with COVID-19.
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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 | 0.002 | 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 | 0.001 |
| 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".