Ambulance personnel: Systematic review of mental health symptoms.
Bibliographic record
Abstract
Ambulance personnel, including paramedics, emergency medical technicians, and others, are exposed to potentially distressing situations frequently as a function of their duties. The present systematic review evaluated the prevalence of trauma-related mental disorders, including posttraumatic stress disorder (PTSD), depression, and anxiety in ambulance personnel with best-evidence narrative synthesis across an international dataset of 24 eligible studies to determine whether prevalence is elevated in this occupational group relative to the general population. In addition, we integrate and synthesize findings related to predictive factors for the prevalence of these disorders across the literature, broadly grouping predictive factors into three categories: individual-difference factors (e.g., sociodemographics), exposure-related factors (e.g., frequency), and organizational factors (e.g., support from supervisors). The relationship between exposure-related factors and depression/anxiety symptoms is of special interest because both disorders may occur outside the context of traumatic stress but are also highly comorbid with PTSD. We report strong evidence that prevalence rates of probable PTSD, depression, and anxiety disorder are elevated in ambulance personnel. The strongest predictive associations for PTSD symptoms concerned exposure-related and organizational factors, whereas individual-difference factors bore weak or inconsistent associations with symptoms. Importantly, there is a concerning lack of data regarding the impact of workplace traumatic exposure on depression and anxiety in ambulance personnel, and as such it is not possible at present to differentiate between manifestation of symptoms following exposure compared with ongoing symptoms unrelated to the workplace. Addressing this gap in the literature is of critical importance for guiding organizational response to these disorders in ambulance service. (PsycInfo Database Record (c) 2020 APA, all rights reserved)
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".