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Record W3109477992 · doi:10.1177/0091415020974616

Aging in Place With a Spouse in Need: Neighborhood Cohesion and Older Adult Spouses’ Physical and Mental Health

2020· article· en· W3109477992 on OpenAlexaff
Kyuho Lee, Patrik Marier

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsConcordia University
FundersDaegu University
KeywordsSpouseDepressive symptomsMental healthGerontologyActivities of daily livingHealth and Retirement StudyCognitionPsychologyPhysical healthWifeClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

This study examines the association of perceived neighborhood cohesion (NC) with older adults' health and the buffering effects of NC against the negative effects of spousal caregiving on health. Data of 3329 community-living older adults living with a spouse in need of care from the Health and Retirement Study were collected at two time-points. Multiple regression analyses were computed for each of the four health outcomes. For men, NC predicted fewer depressive symptoms and better cognition. NC buffered the negative effect of providing activities of daily living (ADL) help to the wife on cognition. For women, NC predicted fewer depressive symptoms and better cognition. NC buffered the negative effect of providing ADL help to the husband on ADL difficulties. The results accentuate the importance of residency location for older adults' physical and mental health. The health benefits of NC may have more implications for older adults providing spousal care.

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)0.000
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 score0.284
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.318
Teacher spread0.299 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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