Psychological interventions for post-traumatic stress injuries among public safety personnel: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Public safety personnel (PSP) are exposed to potentially psychologically traumatic events (PPTE) far more often than the general public, which increases the risk for various post-traumatic stress injuries (PTSIs). While there are many evidence-based psychological interventions for PTSI, the effectiveness of each intervention for PSP remains unclear. Objectives The current study assessed the effectiveness and acceptability of psychological interventions for PTSI among PSPs. Methods A systematic review and random-effects meta-analysis were performed on the effectiveness and acceptability of psychotherapies for PTSIs (i.e., symptoms of depression, anxiety, post-traumatic stress disorder) among PSP. The review adhered to the PRISMA reporting guidelines and used standardized mean differences (Cohen’s d ), rate ratios (RR), and their 95% confidence intervals (95% CI) to measure pooled effect sizes across studies; negative d values and RR values less than one indicated a reduction in symptoms compared to baseline or control groups. In addition, heterogeneity was quantified using I 2 , and publication bias was evaluated using Egger’s test. Results The analyses included data from eight randomized controlled trials representing 402 PSP (79.4% male, 35.3 years). Psychological interventions included narrative exposure therapy ( n = 1), cognitive behavioral therapy ( n = 2), eclectic psychotherapy ( n = 2), eye-movement desensitization and reprocessing ( n = 1), supportive counseling ( n = 2), and group critical incident stress debriefing ( n = 1). The interventions were associated with statistically significant reductions in symptoms associated with PTSD ( d = − 1.23; 95% CI − 1.81, − 0.65; 7 studies; I 2 = 81%), anxiety (− 0.76; 95% CI − 1.28, − 0.24; 3 studies; I 2 = 47%), and depression ( d = − 1.10; 95% CI − 1.62, − 0.58; 5 studies; I 2 = 64%). There were smaller but statistically significant improvements at follow-up for symptoms of PTSD ( d = − 1.29 [− 2.31, − 0.27]), anxiety ( d = − 0.82 [− 1.20, − 0.44]), and depression ( d = − 0.46 [− 0.77, − 0.14]). There were no statistically significant differences in dropout rates (RR = 1.00 [0.96, 1.05]), suggesting high acceptability across interventions. Conclusions There is preliminary evidence that psychotherapies help treat PTSIs in PSP; however, the shortage of high-quality studies on PSP indicates a need for additional research into treating PTSI among PSP. Systematic review registration PROSPERO: CRD42019133534.
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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 | 0.022 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.051 | 0.026 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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; both teacher heads agree on what is shown here.
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".