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Record W294729479 · doi:10.1177/070674370705200809

Posttraumatic Stress Disorder and Associated Risk Factors in Canadian Peacekeeping Veterans with Health-Related Disabilities

2007· article· en· W294729479 on OpenAlexaffvenueabout
J. Don Richardson, James A. Naifeh, Jon D. Elhai

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2007
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsVeterans Affairs CanadaSt Joseph's Health Care
FundersU.S. Department of Veterans Affairs
KeywordsPosttraumatic stressPsychiatryPeacekeepingPsychologyRisk factorMental healthOccupational safety and healthClinical psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: This study investigates posttraumatic stress disorder (PTSD) and its associated risk factors in a random, national, Canadian sample of United Nations peacekeeping veterans with service-related disabilities. METHODS: Participants included 1016 male veterans (age < 65 years) who served in the Canadian Forces from 1990 to 1999 and were selected from a larger random sample of 1968 veterans who voluntarily and anonymously completed a general health survey conducted by Veterans Affairs Canada in 1999. Survey instruments included the PTSD Checklist-Military Version (PCL-M), Center for Epidemiological Studies-Depression Scale (CES-D), and questionnaires regarding life events during the past year, current stressors, sociodemographic characteristics, and military history. RESULTS: We found that rates of probable PTSD (PCL-M score > 50) among veterans were 10.92% for veterans deployed once and 14.84% for those deployed more than once. The rates of probable clinical depression (CES-D score > 16) were 30.35% for veterans deployed once and 32.62% for those deployed more than once. We found that, in multivariate analyses, probable PTSD rates and PTSD severity were associated with younger age, single marital status, and deployment frequency. CONCLUSIONS: PTSD is an important health concern in the veteran population. Understanding such risk factors as younger age and unmarried status can help predict morbidity among trauma-exposed veterans.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.032
GPT teacher head0.321
Teacher spread0.288 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations46
Published2007
Admission routes3
Has abstractyes

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