Exercise and PTSD Symptoms in Emergency Service and Frontline Medical Workers: A Systematic Review
Bibliographic record
Abstract
ABSTRACT Context: Emergency service and medical frontline workers are exposed to significant occupational stressors that may confer an increased risk of poor mental health, including posttraumatic stress disorder (PTSD). Emerging evidence suggests that physical activity and its structured subset, exercise, may be effective in improving symptoms of PTSD in veterans; however, the potential efficacy for other populations at high risk of occupational trauma exposure is currently unclear. Given the potential of physical activity interventions to improve both PTSD symptoms and physical comorbidities, there has been increasing interest in the potential role in the treatment of PTSD. Objective: The purpose of this review was to investigate the associations between physical activity levels and PTSD symptoms in emergency service and frontline medical workers. Design: A systematic review was conducted by searching major electronic databases for relevant studies published from database inception until February 2021. Eligibility Criteria: Studies among traditional emergency service occupations, e.g., police officers, firefighters, paramedics, and medical frontline workers, including doctors and nurses, were included. Study Selection: Experimental and observational studies with or without control groups were eligible for inclusion. Main Outcome Measure: The primary outcome measure was symptoms of PTSD. Results: The search identified eight eligible studies (four experimental and four observational). Three of the experimental studies showed that exercise significantly reduced symptoms of PTSD in emergency service personnel, including police and nurses. Based on the results of results of three studies, physical activity may be inversely associated with PTSD symptom severity among nurses and firefighters. Conclusions: Existing research suggests that physical activity may improve symptoms of PTSD in emergency service personnel and frontline workers. Considering physical activity promotion initiatives for occupations at high risk of trauma exposure may therefore be warranted to promote mental health. The existing research has several methodological limitations, and findings should therefore be interpreted with caution until further robust studies are available.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".