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Record W2133536851 · doi:10.1093/geronb/62.6.p331

It's Never Too Late to Engage in Lifestyle Activities: Significant Concurrent but not Change Relationships Between Lifestyle Activities and Cognitive Speed

2007· article· en· W2133536851 on OpenAlexaff
Allison A. M. Bielak, Tiffany F. Hughes, Brent J. Small, Roger A. Dixon

Bibliographic record

VenueThe Journals of Gerontology Series B · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Victoria
FundersNational Institute on Aging
KeywordsLongitudinal studyCognitionPsychologyPhysical activityDevelopmental psychologyLongitudinal dataDemographyMedicineStatisticsPhysical medicine and rehabilitationMathematicsSociology

Abstract

fetched live from OpenAlex

Little is known about potential longitudinal relationships between participation in social, physical, and intellectual activities and later cognitive performance. Data from the Victoria Longitudinal Study (n = 530) were used to test whether baseline and change in lifestyle engagement were related to corresponding indicators of cognitive speed (measured by mean-level and intraindividual variability). Regressions based on random effects model estimates showed that cross-sectional activity participation predicted corresponding values of both mean-level and intraindividual variability, but few longitudinal relationships were significant. Overall, a higher frequency of participation in cognitively complex activities was related to faster response times and lower intraindividual variability. Findings suggest that activity level at one point in time may be a more important predictor of cognition than an individual's changes in activity level.

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)0.006
metaresearch head score (Gemma)0.002
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 score0.157
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.177
GPT teacher head0.403
Teacher spread0.226 · 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

Citations81
Published2007
Admission routes1
Has abstractyes

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