Psychological impact of COVID-19 pandemic on health care workers of tertiary care hospitals
Bibliographic record
Abstract
Healthcare workers (HCWs) are at increased risk of mental health issues when faced with the challenges associated with pandemics. This study was conducted to assess the psychological impact of pandemic on HCWs working in tertiary care hospitals of Khyber-Pakhtunkhwa province of Pakistan. This cross-sectional study was conducted between April & June 2020. By convenience sampling an electronic form of Goldberg General Health Questionnaire was distributed among HCWs of the private sector and public tertiary care hospitals. Data were analyzed using SPSS version 22. Inferential analysis was done. The significant level was considered at p=<0.05. Total of 186 HCWs among which 105 (56.5%) males and 81 (43.5%) females participated in the survey, a mean age of 37.6±9.28 years. The highest prevalence was found for social dysfunction 184 (97.8%) followed by somatization, 169 (92.8%). Significance of difference was found between age group and anxiety (p=0.018), specialty of HCWs with somatization and social dysfunction (p=0.041 and 0.037 respectively). Pandemic poses a significant risk for the mental health of HCWs. During pandemics at its peak, proper mental health support program, personal and family protection assurance is highly recommended for provision of quality care by HCWs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".