Delays in treatment initiation for posttraumatic stress disorder in the Canadian Armed Forces: A scoping review
Bibliographic record
Abstract
Introduction: Previous research suggests delays in treatment initiation for combat-related posttraumatic stress disorder (PTSD) are problematic for the military population. The purpose of this scoping review was to summarize what is known about the potential factors contributing to delayed treatment initiation for combat-related PTSD for service members and Veterans of the Canadian Armed Forces. Methods: This scoping review was conducted using the five-stage methodological framework developed by Arksey and O'Malley. Reporting was guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. A systematic and comprehensive search of several online databases, including Omni, PsycInfo, PTSDpubs, PubMed, and Web of Science, was conducted for studies published between March 2002 and December 2020. Results: The review included a total of 12 publications. Three thematic groupings were identified among the included articles: 1) stigmatization and attitudinal barriers, 2) deployment characteristics, and 3) role of military service component. Discussion: This analysis illustrates three key factors that can delay treatment initiation in this population. The most influential factor affecting timing of treatment initiation was the effect of stigmatization and the attitudinal barriers of military personnel. Further research is required to learn how to mitigate these factors and decrease the time between returning from combat and initiating treatment for a combat-related mental health condition, including 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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".