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Record W2927454481 · doi:10.1093/eurpub/ckz047

Social support and cognitive function in middle- and older-aged adults: descriptive analysis of CLSA tracking data

2019· article· en· W2927454481 on OpenAlexafffundabout
Mark Oremus, Candace Konnert, Jane Law, Colleen J. Maxwell, Megan E. O’Connell, Suzanne L. Tyas

Bibliographic record

VenueEuropean Journal of Public Health · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of SaskatchewanUniversity of CalgaryUniversity of Waterloo
FundersCanadian Institutes of Health ResearchCanada Foundation for InnovationGovernment of Canada
KeywordsVerbal fluency testCognitionPopulationGerontologyPsychological interventionPsychologyTest (biology)ResidenceCognitive testDescriptive statisticsDemographyMedicinePsychiatryEnvironmental healthNeuropsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive function is important for healthy aging. Social support availability (SSA) may modify cognitive function. We descriptively examined the association between SSA and cognitive function in a population-level sample of middle- and older-aged adults. METHODS: We analyzed the tracking dataset of the Canadian Longitudinal Study on Aging. Participants aged between 45 and 85 years answered questions about SSA and performed three cognitive tests (Rey Auditory Verbal Learning Test, Animal Fluency Test and Mental Alternation Test) via telephone. We divided global SSA and global cognitive function scores into tertiles and generated contingency tables for comparisons across strata defined by sex, age group, region of residence, urban vs. rural residence and education. RESULTS: The proportion of participants with low global cognitive function was often greater among persons who reported low global SSA. The proportion of persons with high cognitive function was greater in participants with high SSA. The findings were most pronounced for females, 45- to 54-year olds, all regions (especially Québec) except Atlantic Canada, urban dwellers and persons with less than high school education. CONCLUSIONS: Our results can help public health officials focus on providing social supports to subgroups of the population who would benefit the most from policy interventions.

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)0.010
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 score0.294
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.134
GPT teacher head0.362
Teacher spread0.228 · 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

Citations35
Published2019
Admission routes3
Has abstractyes

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