MétaCan
Menu
Back to cohort
Record W4390082440 · doi:10.1016/j.actpsy.2023.104117

Sexual orientation and cognition in aging populations: Results from the Canadian Longitudinal Study on Aging

2023· article· en· W4390082440 on OpenAlexaffabout
Wook Yang, Shelley L. Craig, John A. E. Anderson, Lori E. Ross, Carles Muntaner

Bibliographic record

VenueActa Psychologica · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsPublic Health OntarioCarleton UniversityUniversity of Toronto
Fundersnot available
KeywordsSexual orientationPsychologyCognitionFlexibility (engineering)MediationLongitudinal studyDevelopmental psychologyPopulationCognitive agingCognitive flexibilityVerbal fluency testSuccessful agingLesbianPopulation ageingSocial cognitive theoryClinical psychologyGerontologySocial psychologyMedicineNeuropsychologyPsychiatry

Abstract

fetched live from OpenAlex

The current study utilized the Canadian Longitudinal Study on Aging (CLSA) data to investigate the relationship between sexual orientation and cognitive health of the aging population. Cognitive flexibility and verbal fluency were examined as outcome variables in the study. A total of 45,993 respondents were included in the analyses. Each model had social support or social participation as a mediator. A series of mediation analysis, stratified by gender, revealed that aging gay men performed better in cognitive tasks related to cognitive flexibility when compared to their heterosexual counterparts. The results also indicated that social support is a protective factor for cognitive health in aging lesbian women. This study provides an opportunity to consider how clinical and social services can strategize to build inclusive environments for the aging sexual minority population.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.021
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
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 head0.275
GPT teacher head0.474
Teacher spread0.198 · 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

Citations7
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueActa PsychologicaSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207