Mental health in young adult emergency services personnel: A rapid review of the evidence
Bibliographic record
Abstract
This rapid review focussed on the mental health and wellbeing of young adult (16–25 years) emergency service volunteers and personnel. The study aimed to synthesise evidence on the experience of mental health conditions and wellbeing in this cohort. The review methods followed the Cochrane Rapid Review Guidelines and was registered with PROSPERO (CRD42020185937). Three databases were searched (PubMed, Embase, PsycINFO) with three concept terms; 1) emergency service personnel (paid/volunteer), 2) young adults, and 3) mental health and wellbeing. The search yielded 6521 studies, of which 15 met the inclusion criteria. Studies involved diverse samples and contexts, including a range of countries, and with varying service types (e.g., firefighters, medical technicians, aid workers, police). A narrative synthesis yielded two main themes from these studies: 1) rates of disorders including post-traumatic stress disorder (PTSD), depression, and anxiety, and 2) impact (including cumulative) of exposure. These themes are further discussed in the context of factors that may contribute to positive mental health and wellbeing, as identified in the included studies. Young emergency services personnel encounter uniquely challenging experiences in their work role that may contribute to adverse mental health. Understanding multiple factors at individual, social, and organisational levels may be useful in informing evidence-based training and support to minimise risk. This may enhance mental health and wellbeing in young adult personnel in emergency services. There is a scarcity of research focussed on this age group and on volunteer personnel, highlighting the need for future research focussed on these 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 | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".