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Record W3048000795 · doi:10.1177/0164027520923111

Differential Effects of Social Support by Sexual Orientation: A Study of Depression Symptoms Among Older Canadians in the CLSA

2020· article· en· W3048000795 on OpenAlexafffundabout
Arne Stinchcombe, Nicole G. Hammond, Kimberley Wilson

Bibliographic record

VenueResearch on Aging · 2020
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of OttawaUniversity of GuelphBrock University
FundersCanadian Institutes of Health Research
KeywordsSexual orientationDepression (economics)PsychologySocial supportDevelopmental psychologyOrientation (vector space)Differential effectsClinical psychologyGerontologyDemographyMedicineSocial psychologySociologyInternal medicine

Abstract

fetched live from OpenAlex

This study examined differences in symptoms of mental illness, specifically depression, by sexual orientation and examined the protective role of social support among lesbian, gay, and bisexual (LGB) older Canadians. Data were drawn from the Canadian Longitudinal Study on Aging, a national study of adults aged 45–85 years at baseline ( n = 46,157). We examined whether the effect of sexual orientation on depression symptoms was moderated by four types of social support: emotional/informational support, affectionate support, tangible support, and positive social interaction. LGB identification was associated with increased depression symptoms relative to heterosexual participants. After adjustment for covariates, bisexual identity remained a significant predictor of depression symptoms. Low emotional/informational social support was associated with increased depression symptoms, an effect that was most pronounced for lesbian and gay participants. The findings contribute to the growing body of research on the mental health of older LGB people.

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)0.002
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 score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.464
Teacher spread0.399 · 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

Citations17
Published2020
Admission routes3
Has abstractyes

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