The Evidence Base for Interventions Targeting Individuals With Work-Related PTSD: A Systematic Review and Recommendations
Bibliographic record
Abstract
The purpose of this study was to summarize the evidence base for interventions targeting individuals with work-related posttraumatic stress disorder (PTSD), to make recommendations for clinicians and administrative decision makers involved in their rehabilitation, and to guide future research in this area. Particular attention was given to studies that were conducted in naturalistic clinical settings or in a workers' compensation claim context. Electronic searches of Cochrane Central Register of Controlled Trials, MEDLINE, PubMed, PsycINFO, CINAHL, PILOTS, and EMBASE identified 11 articles. Study populations included railroad personnel, police officers, disaster workers, and individuals with industrial injuries. Interventions included trauma-focused cognitive-behavioral therapy and eye movement desensitization and reprocessing. Several studies specifically targeted workers who had failed to return to work (RTW) after standard PTSD treatment. The results suggest that psychotherapy interventions are beneficial for helping clients recover from PTSD symptoms and RTW. In studies that reported on work status, RTW rates increased over time and generally lay between 58% and 80% across follow-up time points. Narrative impressions were supplemented by calculation of Risk Differences for individuals working at pretreatment versus posttreatment. Clinical consideration, methodological issues limiting the current body of work, and recommendations for future research are discussed.
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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 | 0.020 | 0.079 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.020 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".