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Record W4406137922 · doi:10.1177/07334648241311661

Psychosocial Function in Mild Cognitive Impairment: Social Participation is Associated With Cognitive Performance in Multiple Domains

2025· article· en· W4406137922 on OpenAlexafffund
Sana Rehan, Natalie A. Phillips

Bibliographic record

VenueJournal of Applied Gerontology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsJewish General HospitalConcordia UniversityCentre for Research on Brain Language and Music
FundersCanadian Institutes of Health ResearchAlzheimer Society Research ProgramAlzheimer SocietyConsortium canadien en neurodégénérescence associée au vieillissement
KeywordsPsychosocialPsychologyCognitionVerbal fluency testClinical psychologyEffects of sleep deprivation on cognitive performanceSocial engagementSocial supportDevelopmental psychologyPsychiatryNeuropsychologySocial psychology

Abstract

fetched live from OpenAlex

Psychosocial function is associated with cognitive performance cross-sectionally and cognitive decline over time. Using data from the COMPASS-ND study, we examined associations between psychosocial and cognitive function in 126 individuals with mild cognitive impairment, an at-risk group for Alzheimer's disease (AD). Psychosocial function was measured using questionnaires about mental health, social support, and social engagement. Composite scores for five cognitive domains were derived using principal component analysis. Multiple linear regression models were used to test the effects of various psychosocial factors on cognitive performance, controlling for age, sex, education, MoCA scores, and living circumstances. We found that low current participation in one's social networks, over other psychosocial factors, was associated with worse verbal fluency and processing speed scores than those endorsing normal or high social participation. Our findings provide groundwork for further psychosocial-cognitive analyses in individuals at-risk for AD to better understand the role of poor social engagement in cognitive decline.

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)0.001
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 score0.057
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.355
Teacher spread0.315 · 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

Citations7
Published2025
Admission routes2
Has abstractyes

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