The impact of the COVID-19 pandemic on health service utilisation following self-harm: a systematic review
Bibliographic record
Abstract
Abstract Background Evidence on the impacts of the pandemic on healthcare presentations for self-harm has accumulated rapidly. However, existing reviews do not include studies published beyond 2020. Aims To systematically review evidence on health services utilisation for self-harm during the COVID-19 pandemic. Methods A comprehensive search of multiple databases (WHO COVID-19 database; Medline; medRxiv; Scopus; PsyRxiv; SocArXiv; bioRxiv; COVID-19 Open Research Dataset, PubMed) was conducted. Studies reporting presentation frequencies for self-harm published from 1 st Jan. 2020 to 7 th Sept. 2021 were included. Study quality was assessed using a critical appraisal tool. Results Fifty-one studies were included. 59% (30/51) were rated as ‘low’ quality, 29% (15/51) as ‘moderate’ and 12% (6/51) as ‘high-moderate’. Most evidence (84%, 43/51 studies) was from high-income countries. 47% (24/51) of studies reported reductions in presentation frequency, including all 6 rated as high-moderate quality, which reported reductions of 17- 56%. Settings treating higher lethality self-harm were overrepresented among studies reporting increased demand. Two of the 3 higher quality studies including study observation months from 2021 reported reductions in service utilisation. Evidence from 2021 suggested increased use of health services following self-harm among adolescents, particularly girls. Conclusions Sustained reductions in service utilisation were seen into the first half of 2021. However, evidence from low- and middle-income countries is lacking. The increased use of health services among adolescents, particularly girls, into 2021 is of concern. Our findings may reflect changes in thresholds for help seeking, use of alternative sources of support and variable effects of the pandemic across different groups.
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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 | 0.015 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".