Posttraumatic Stress Disorder Post Iraq and Afghanistan: Prevalence among Military Subgroups
Bibliographic record
Abstract
A large body of research has been produced in recent years investigating posttraumatic stress disorder (PTSD) among military personnel following deployment to Iraq and Afghanistan, resulting in apparent differences in PTSD prevalence. We compare prevalence estimates for current PTSD between military subgroups, providing insight into how groups may be differentially affected by deployment. Systematic literature searches using the terms PTSD, stress disorder, and acute stress, combined with terms relating to military personnel, identified 49 relevant papers. Studies with a sample size of less than 100 and studies based on data for treatment seeking or injured populations were excluded. Studies were categorized according to theatre of deployment (Iraq or Afghanistan), combat and noncombat deployed samples, sex, enlistment type (regular or reserve and [or] National Guard), and service branch (for example, army, navy, and air force). Meta-analysis was used to assess PTSD prevalence across subgroups. There was large variability in PTSD prevalence between studies, but, regardless of heterogeneity, prevalence rates of PTSD were higher among studies of Iraq-deployed personnel (12.9%; 95% CI 11.3% to 14.4%), compared with personnel deployed to Afghanistan (7.1%; 95% CI 4.6% to 9.6%), combat deployed personnel, and personnel serving in the Canadian, US, or UK army or the navy or marines (12.4%; 95% CI 10.9% to 13.4%), compared with the other services (4.9%; 95% CI 1.4% to 8.4%). Contrary to findings from within-study comparisons, we did not find a difference in PTSD prevalence for regular active-duty and reserve or National Guard personnel. Categorizing studies according to deployment location and branch of service identified differences among subgroups that provide further support for factors underlying the development of PTSD.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".