Does Gender or Religion Contribute to the Risk of COVID-19 in Hospital Doctors in the UK?
Bibliographic record
Abstract
Abstract The novel coronavirus pandemic is posing significant challenges to healthcare workers (HCWs) in adjusting to redeployed clinical settings and enhanced risk to their own health. Studies suggest a variable impact of COVID-19 based on factors such as age, gender, comorbidities and ethnicity. Workplace measures such as personal protective equipment (PPE), social distancing (SD) and avoidance of exposure for the vulnerable, mitigate this risk. This online questionnaire-based study explored the impact of gender and religion in addition to workplace measures associated with risk of COVID-19 in hospital doctors in acute and mental health institutions in the UK. The survey had 1206 responses, majority (94%) from BAME backgrounds. A quarter of the respondents had either confirmed or suspected COVID-19, a similar proportion reported inadequate PPE and 2/3 could not comply with SD. One third reported being reprimanded in relation to PPE or avoidance of risk. In univariate analysis, age over 50 years, being female, Muslim and inability to avoid exposure in the workplace was associated with risk of COVID-19. On multivariate analysis, inadequate PPE remained an independent predictor with a twofold (OR 2.29, (CI - 1.22-4.33), p=0.01) risk of COVID-19. This study demonstrates that PPE, SD and workplace measures to mitigate risk remain important for reducing risk of COVID-19 in hospital doctors. Gender and religion did not appear to be independent determinants. It is imperative that employers consolidate risk reduction measures and foster a culture of safety to encourage employees to voice any safety concerns. (240 words)
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".