Four Decades of Military Posttraumatic Stress: Protocol for a Meta-analysis and Systematic Review of Treatment Approaches and Efficacy (Preprint)
Bibliographic record
Abstract
BACKGROUND Over 85% of active members of the Canadian Armed Forces have been exposed to potentially traumatic events linked to the development of posttraumatic stress disorder (PTSD). At the time of transition to civilian life, as high as 1 in 8 veterans may be diagnosed with PTSD. Given the high prevalence of PTSD in military and veteran populations, the provision of effective treatment considering their unique challenges and experiences is critical for mental health support and the well-being of these populations. OBJECTIVE This paper presents the protocol for a meta-analysis and systematic review that will examine the effectiveness of treatment approaches for military-related PTSD. METHODS This PROSPERO-preregistered meta-analysis is being conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and Cochrane guidelines. A comprehensive search of the literature was conducted using the databases PsycInfo, Medline, Embase, CINAHL, and ProQuest Dissertation & Theses. Effect sizes will be computed based on changes in PTSD symptom scores over time across studies using validated PTSD scales. A multilevel meta-analysis will examine the overall effects, between-study effects, and within-study effects of available evidence for PTSD treatments in military populations. Effect sizes will be compared between pharmacotherapeutic, psychotherapeutic, and alternative/emerging treatment interventions. Finally, meta-regression and subgroup analyses will explore the moderating roles of clinical characteristics (eg, PTSD symptom clusters), treatment approaches (eg, therapeutic orientations in psychotherapy and alternative therapies and classifications of drugs in pharmacotherapy), as well as treatment characteristics (eg, length of intervention) on treatment outcomes. RESULTS The literature search was completed on April 14, 2021. After the removal of duplicates, a total of 12,002 studies were screened for inclusion. As of July 2021, title and abstract screening has been completed, with 1469 out of 12,002 (12.23%) studies included for full-text review. Full review is expected to be completed in the summer of 2021, with initial results expected for publication by early winter of 2021. CONCLUSIONS This meta-analysis will provide information on the current state of evidence on the efficacy and effectiveness of various treatment approaches for military-related PTSD and identify factors that may influence treatment outcomes. The results will inform clinical decision-making for service providers and service users. Finally, the findings will provide insights into future treatment development and practice recommendations to better support the well-being of military and veteran populations. CLINICALTRIAL PROSPERO CRD42021245754; https://tinyurl.com/y9u57c59 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/33151
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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 | 0.069 | 0.100 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.081 | 0.008 |
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".