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Record W1973223490 · doi:10.3109/09638288.2014.947441

Disability correlates in Canadian Armed Forces Regular Force Veterans

2014· article· en· W1973223490 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDisability and Rehabilitation · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsCanadian Armed ForcesDalhousie UniversityVeterans Affairs CanadaQueen's University
FundersMinistère de la Défense NationaleCanadian Armed Forces
KeywordsOddsMental healthPopulationGerontologyMedicineLogistic regressionQuality of life (healthcare)Odds ratioEnvironmental healthDemographyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Purpose: This study was undertaken to inform disability mitigation for military veterans by identifying personal, environmental, and health factors associated with activity limitations. Method: A sample of 3154 Canadian Armed Forces Regular Force Veterans who were released during 1998–2007 participated in the 2010 Survey on Transition to Civilian Life. Associations between personal and environmental factors, health conditions and activity limitations were explored using ordinal logistic regression. Results: The prevalence of activity reduction in life domains was higher than the Canadian general population (49% versus 21%), as was needing assistance with at least one activity of daily living (17% versus 5%). Prior to adjusting for health conditions, disability odds were elevated for increased age, females, non-degree post-secondary graduation, low income, junior non-commissioned members, deployment, low social support, low mastery, high life stress, and weak sense of community belonging. Reduced odds were found for private/recruit ranks. Disability odds were highest for chronic pain (10.9), any mental health condition (2.7), and musculoskeletal conditions (2.6), and there was a synergistic additive effect of physical and mental health co-occurrence. Conclusions: Disability, measured as activity limitation, was associated with a range of personal and environmental factors and health conditions, indicating multifactorial and multidisciplinary approaches to disability mitigation.Implications for RehabilitationConsider activity limitations in all veterans with health problems, particularly women or veterans with current or lost marital relationship; post-secondary non-degree education; low income; junior non-commissioned member rank; high life stress; chronically painful conditions; musculoskeletal disorders; or mental health conditions.Comorbidity indicates the need for coordinated multidisciplinary care, especially between physical and mental health care services.Since disability is associated with psychosocial factors, service providers should be aware of the broad range of services and interventions available to mitigate disability in veterans.Do not be led astray by the absence of combat deployment history since disability occurs in former military personnel who have not deployed.

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.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.483
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.371
Teacher spread0.352 · 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