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Record W4402253349 · doi:10.1177/07334648241274532

Influence of Reading or Writing Activities Shared with Others on Older Adults: Results From a Scoping Study

2024· review· en· W4402253349 on OpenAlexafffund
Mélanie Levasseur, Olivier Dezutter, T. H. Trang Nguyen, Julie Babin, Nathalie Bier, Marie Lee Biron

Bibliographic record

VenueJournal of Applied Gerontology · 2024
Typereview
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversité LavalHealth and Social Services Centre University Institute of Geriatrics of SherbrookeUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de Sherbrooke
FundersFonds de Recherche du Québec - Santé
KeywordsReading (process)RecreationPsychologyInterpersonal communicationInterpersonal relationshipActivities of daily livingAffect (linguistics)Developmental psychologyGerontologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

This study aimed to provide integrated knowledge on the influence of shared reading or writing activities, that is, recreational occupations involving dynamic relationships based on personal development, on adults aged 55 and older. Using a scoping study framework, six databases were searched with 25 relevant keywords for papers, theses, and scientific reports published in 2001-2023. Based on the Human Development Model-Disability Creation Process, the content analysis of 20 documents showed that shared reading or writing activities mostly benefited aging adults' behavioral capabilities like positive affect, their intellectual capacities, such as developing new perspectives on life, their interpersonal relationships, and social support. Negative instances, such as frustration, were often mentioned at the beginning of the activities but decreased over time. These results suggest the importance of shared reading or writing activities for healthy aging and the necessity to better support these activities for more inclusive and caring aging societies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.109
GPT teacher head0.436
Teacher spread0.327 · 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 designOther design
Domainnot available
GenreReview

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

Citations4
Published2024
Admission routes2
Has abstractyes

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