Systematic review of the impact of the COVID-19 pandemic on suicidal behaviour amongst health and social care workers across the world
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has had an impact on the mental health of healthcare and social care workers, and its potential effect on suicidal thoughts and behaviour is of particular concern. METHODS: This systematic review identified and appraised the published literature that has reported on the impact of COVID-19 on suicidal thoughts and behaviour and self-harm amongst healthcare and social care workers worldwide up to May 31, 2021. RESULTS: Out of 37 potentially relevant papers identified, ten met our eligibility criteria. Our review has highlighted that the impact of COVID-19 has varied as a function of setting, working relationships, occupational roles, and psychiatric comorbidities. LIMITATIONS: There have been no completed cohort studies comparing pre- and post-pandemic suicidal thoughts and behaviours. It is possible some papers may have been missed in the search. CONCLUSIONS: The current quality of evidence pertaining to suicidal behaviour in healthcare workers is poor, and evidence is entirely absent for those working in social care. The clinical relevance of this work is to bring attention to what evidence exists, and to encourage, in practice, proactive approaches to interventions for improving healthcare and social care worker mental health.
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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 | 0.011 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".