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Record W3200850276 · doi:10.2196/33151

Four Decades of Military Posttraumatic Stress: Protocol for a Meta-analysis and Systematic Review of Treatment Approaches and Efficacy

2021· article· en· W3200850276 on OpenAlexaffvenueabout
Jenny J. W. Liu, Anthony Nazarov, Bethany Easterbrook, Rachel A. Plouffe, Tri Le, Callista Forchuk, Alec Brandwood, Kate St. Cyr, Édouard Auger, Ken Balderson, Mathieu Bilodeau, Amer M. Burhan, Murray W. Enns, Patrick Smith, Fardous Hosseiny, Gabrielle Dupuis, Maya Roth, Natalie Mota, Vicky Lavoie, J. Don Richardson

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsToronto Metropolitan UniversityUniversité LavalOntario Centre of Excellence for Child and Youth Mental HealthUniversity of ManitobaCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleRunning Injury ClinicOntario Shores Centre for Mental Health SciencesPublic Health OntarioWestern UniversityUniversity of TorontoMcMaster UniversityLawson Health Research Institute
Fundersnot available
KeywordsProtocol (science)Posttraumatic stressMeta-analysisPsychologySystematic reviewMedicineMilitary personnelClinical psychologyMEDLINEAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

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. TRIAL REGISTRATION: PROSPERO CRD42021245754; https://tinyurl.com/y9u57c59. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33151.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.079
metaresearch head score (Gemma)0.105
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.079
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.105
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0220.035
Bibliometrics0.0100.011
Science and technology studies0.0040.004
Scholarly communication0.0080.007
Open science0.0060.005
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0560.006

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.

Opus teacher head0.704
GPT teacher head0.611
Teacher spread0.094 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations7
Published2021
Admission routes3
Has abstractyes

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