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Record W4318165561 · doi:10.1177/23337214221150061

How an Intergenerational Book Club Can Prevent Cognitive Decline in Older Adults: A Pilot Study

2023· article· en· W4318165561 on OpenAlexaboutno aff
Jamie Plummer, Katlyn Nguyen, Janet Everly, Abby Kiesow, Katherine H. Leith

Bibliographic record

VenueGerontology and Geriatric Medicine · 2023
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
Fundersnot available
KeywordsClubSocial isolationGerontologyRelocationCognitionPsychological interventionPsychologyIntervention (counseling)Isolation (microbiology)Quality of life (healthcare)Affect (linguistics)Cognitive declineMedicinePsychiatry

Abstract

fetched live from OpenAlex

Older adults are at higher risk for social isolation because of widowhood, loss of friends, retirement, physical limitations, geographic relocation, and caregiving demands. Behavioral interventions aimed at increasing social contact may help to maintain cognition and prevent cognitive decline. The purpose of this pilot study was to examine a novel intervention for social isolation with an intergenerational book club that had weekly in-person and virtual meetings of college students and older adults. We wanted to know whether the study was feasible and if our methods would be likely to generate meaningful results should it be expanded to a larger number of participants. We predicted that wellbeing and cognition would improve following participation in the book club. Results found that while measures of quality of life and affect were not statistically different before and after participation in a book club, scores on a measure of cognition (the Montreal Cognitive Assessment) were statistically significant between groups (intervention and control) showing greater improvement among book club participants.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.390
Teacher spread0.326 · 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.

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

Citations11
Published2023
Admission routes1
Has abstractyes

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