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Record W4200308903 · doi:10.3138/jmvfh-2021-0030

Correlates of posttraumatic stress disorder among Veterans in the Canadian Longitudinal Study on Aging

2021· article· en· W4200308903 on OpenAlexaffvenueabout
Danielle E. Gauvin, Christina Wolfson, Alice Aiken, Anthony Feinstein, Parminder Raina, Linda VanTil

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsVeterans Affairs CanadaMcMaster UniversityUniversity of TorontoDalhousie UniversityImpactMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMental healthLongitudinal studyMilitary servicePosttraumatic stressGerontologyPsychologyService memberHealthy agingBaseline (sea)MedicinePopulationPsychiatryClinical psychologyMilitary personnelEnvironmental health

Abstract

fetched live from OpenAlex

LAY SUMMARY Little is known about the mental health of Veterans as they get older. How does the mental health and aging process of Veterans compare to people who have not served in the military? The Canadian Longitudinal Study on Aging (CLSA) is a long-term national study of the aging adult population in Canada. A total of 51,338 participants across Canada aged 45 to 85 years were recruited at the study baseline between 2011 and 2015. Of the CLSA participants, about 4,500 self-identified as Veterans, with military service dating back as early as 1941. The goal of this study was to describe the mental health, in particular posttraumatic stress disorder, of Veterans in the CLSA at the study baseline and examine differences across Veteran sub-groups and compared to non-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 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)0.001
metaresearch head score (Gemma)0.003
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 score0.022
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.133
GPT teacher head0.412
Teacher spread0.279 · 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

Citations9
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Military Veteran and Family HealthSame topicPosttraumatic Stress Disorder ResearchFrench-language works237,207