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Record W4410947558 · doi:10.3138/jmvfh-2024-0066

Beyond first-line approaches: A scoping review of emerging operational stress interventions for military and public safety personnel

2025· review· en· W4410947558 on OpenAlexaffvenueabout
Ashleigh Forsyth, Anees Bahji, Jeremy G. Stewart, Matthew J. Simpson, Dianne Groll

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2025
Typereview
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsUniversity of CalgaryQueen's University
Fundersnot available
KeywordsPsychological interventionSafety cultureBusinessPolitical sciencePublic relationsEngineeringMedicineManagementNursingEconomics

Abstract

fetched live from OpenAlex

LAY SUMMARY Mental health issues such as posttraumatic stress disorder (PTSD) are increasingly common among military Veterans and public safety personnel. Typical or traditional treatments such as therapy and medication work for only about 50%−60% of individuals, showing a clear need for more options. A search of PTSD treatment programs in Canada between 2011 and 2022 to identify available programs was conducted. The authors screened hundreds of records and found 13 studies, plus an additional seven programs through a search of a public database. These programs use many methods, some of which include complementary and alternative medicine, such as yoga and mindfulness. This review found that Canada has many novel mental health programs; however, very few of these programs have been evaluated for their effectiveness, which may lead some health care providers to be resistant to recommending them. The authors suggest that much more research needs to be conducted to better understand and improve programs that are effective for military and public safety personnel.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.266
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.282
GPT teacher head0.499
Teacher spread0.217 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes3
Has abstractyes

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