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Record W3168131161 · doi:10.1080/21635781.2021.1927917

A Retrospective Cohort Study Comparing the Use of Provincially Funded Mental Health Services between Female Military Spouses Living in Ontario and the General Population

2021· article· en· W3168131161 on OpenAlexaffabout
Alyson Mahar, Heidi Cramm, Alice Aiken, Lixia Zhang, Simon Chen, Ben Ouellette, Lynda Manser, Paul Kurdyak

Bibliographic record

VenueMilitary Behavioral Health · 2021
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsCanadian Armed ForcesUniversity of TorontoDalhousie UniversityQueen's UniversityUniversity of ManitobaInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsMental healthMedicineResidencePopulationPsychiatryFamily medicineCohortRetrospective cohort studyPublic healthNursingDemographyEnvironmental health

Abstract

fetched live from OpenAlex

The spouses of military members experience frequent geographic mobility, absences, risk, and other lifestyle dimensions that may cause a greater need for mental health services and barriers to their use, relative to civilians. This was a retrospective, matched cohort study of female spouses of Canadian Armed Forces (CAF) members posted between 04/01/2008 and 03/31/2013 with follow-up to 03/31/2017. 3,358 military-connected spouses were identified and 13,342 civilians matched 4:1 on age, sex, and region of residence. Psychiatric hospitalizations and emergency department (ED) visits, psychiatrist visits, and mental health-related primary care visits were studied. Almost one third of spouses of CAF members visited a family physician for mental health reasons, while a minority visited an ED, a psychiatrist or were hospitalized. Spouses of CAF members were as likely to see a primary care physician, less likely to visit a psychiatrist, visited all measured outpatient sources of mental health services less frequently than the general population and had a longer interval to their first psychiatrist visit than the general population. Information on how mental health services are accessed in the public health system are critical to understanding pathways of care, and the planning and delivery of mental health services to military-connected families.

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 score0.116
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.079
GPT teacher head0.366
Teacher spread0.287 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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