Anxiety and Coping Strategies among Italian-Speaking Physicians: A Comparative Analysis of the Contractually Obligated and Voluntary Care of COVID-19 Patients
Bibliographic record
Abstract
This study aims to explore the differences in the psychological impact of COVID-19 on physicians, specifically those who volunteered or were contractually obligated to provide care for COVID-19 patients. While previous research has predominantly focused on the physical health consequences and risk of exposure for healthcare workers, limited attention has been given to their work conditions. This sample comprised 300 physicians, with 68.0% of them men (mean age = 54.67 years; SD = 12.44; range: 23–73). Participants completed measurements including the State-Trait Anxiety Inventory (STAI), Coping Inventory in Stressful Situations (CISS), and Coronavirus Anxiety Scale (C.A.S.). Pearson’s correlations were conducted to examine the relationships between the variables of interest. This study employed multivariate models to test the differences between work conditions: (a) involvement in COVID-19 patient care, (b) volunteering for COVID-19 patient management, (c) contractual obligation to care for COVID-19 patients, and (d) COVID-19 contraction in the workplace. The results of the multivariate analysis revealed that direct exposure to COVID-19 patients and contractual obligation to care for them significantly predicted state anxiety and dysfunctional coping strategies [Wilks’ Lambda = 0.917 F = 3.254 p < 0.001]. In contrast, volunteering or being affected by COVID-19 did not emerge as significant predictors for anxiety or dysfunctional coping strategies. The findings emphasize the importance of addressing the psychological well-being of physicians involved in COVID-19 care and highlight the need for targeted interventions to support their mental and occupational health.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".