Associations between psychosocial stressors at work and moral injury in frontline healthcare workers and leaders facing the COVID-19 pandemic in Quebec, Canada: A cross-sectional study
Bibliographic record
Abstract
Healthcare workers (HCWs) on the frontline of the COVID-19 pandemic exhibit a high prevalence of depression and psychological distress. Moral injury (MI) can lead to such mental health problems. MI occurs when perpetrating, failing to prevent, or bearing witness to acts that transgress deeply held moral beliefs and expectations. Since the start of the pandemic, psychosocial stressors at work (PSWs) might have been exacerbated, which might in turn have led to an increased risk of MI in HCWs. However, research into the associations between PSWs and MI is lacking. Considering these stressors are frequent and most of them are modifiable occupational risk factors, they may constitute promising prevention targets. This study aims to evaluate the associations between a set of PSWs and MI in HCWs during the third wave of the COVID-19 pandemic in Quebec, Canada. Furthermore, our study aims to explore potential differences between urban and non-urban regions. The sample of this study consisted of 572 HCWs and leaders from the Quebec province. Prevalence ratios (PR) of MI and their 95% confidence intervals (CI) were modelled using robust Poisson regressions. Several covariates were considered, including age, sex, gender, socio-economic indicators, and lifestyle factors. Results indicated HCWs exposed to PSWs were 2.22-5.58 times more likely to experience MI. Low ethical culture had the strongest association (PR: 5.58, 95% CI: 1.34-23.27), followed by low reward (PR: 4.43, 95% CI: 2.14-9.16) and high emotional demands (PR: 4.32, 95% CI: 1.89-9.88). Identifying predictors of MI could contribute to the reduction of mental health problems and the implementation of targeted interventions in urban and non-urban areas.
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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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| 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".