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Record W2118266182 · doi:10.1080/00048670902721061

Post-Traumatic Stress Disorder and Health Problems Among Medically Ill Canadian Peacekeeping Veterans

2009· article· en· W2118266182 on OpenAlexaffabout
Julie Richardson, Jordan Pekevski, Jon D. Elhai

Bibliographic record

VenueAustralian & New Zealand Journal of Psychiatry · 2009
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsSt Joseph's Health CareParkwood InstituteWestern University
FundersU.S. Department of Veterans Affairs
KeywordsHeadachesAffect (linguistics)MedicinePsychiatryPeacekeepingPosttraumatic stressTraumatic stressClinical psychologyOccupational safety and healthPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the present study was to examine the relationship between post-traumatic stress disorder (PTSD) symptom severity and four significant health conditions (gastrointestinal disorders, musculoskeletal problems, headaches, and cardiovascular problems). METHOD: Participants included 707 Canadian peacekeeping veterans with service-related disabilities, from a random, national Canadian survey, who had been deployed overseas. RESULTS: PTSD severity was significantly related to gastrointestinal disorders, musculoskeletal problems, and headaches, but not to cardiovascular problems. Controlling for demographic factors did not affect PTSD's relationships with the three significant health conditions. CONCLUSIONS: The present study supports previous work in finding consistent relations between PTSD severity and specific types of medical problems.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.074
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.353
Teacher spread0.311 · 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 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

Citations21
Published2009
Admission routes2
Has abstractyes

Explore more

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