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Record W4392459230 · doi:10.1177/21568693241232410

Cumulative Exposure to Social Isolation and Longitudinal Changes in Life Satisfaction among Older Adults

2024· article· en· W4392459230 on OpenAlexaff
Jinho Kim, Gum‐Ryeong Park

Bibliographic record

VenueSociety and Mental Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Toronto
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaNational Research Foundation
KeywordsPsychologySocial isolationLife satisfactionGerontologyLongitudinal studyLongitudinal dataDevelopmental psychologyDemographySocial psychologySociologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

This study examines the longitudinal association between cumulative exposure to social isolation and life satisfaction and whether this association differs by gender. Using seven waves of the Korean Longitudinal Study of Aging from 2006 to 2018 (3,543 adults aged 65 or older), fixed effects models were estimated. Cumulative social isolation was longitudinally associated with a decline in life satisfaction in older adults. Gender-specific analyses revealed that older women exposed to cumulative social isolation continued to experience a decline in life satisfaction up to the fourth and subsequent waves of exposure (relative to the initial wave in which there was no social isolation; b = −13.038, p < .001). In contrast, a decline in life satisfaction associated with cumulative social isolation was less pronounced among older men ( b = −6.200 for the fourth and subsequent waves of exposure, p < .05). Cumulative social isolation can be a persistent risk factor for life satisfaction in older adults, particularly older women. The study’s findings hold important implications for programs aimed at reducing social isolation and improving psychological well-being among older adults.

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 score0.276
Threshold uncertainty score0.974

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 studies0.0010.000
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 head0.027
GPT teacher head0.360
Teacher spread0.332 · 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

Citations22
Published2024
Admission routes1
Has abstractyes

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