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Record W2040977128 · doi:10.1017/s1041610213000902

Life satisfaction and frailty in community-based older adults: cross-sectional and prospective analyses

2013· article· en· W2040977128 on OpenAlexafffund
Philip D. St. John, Suzanne L. Tyas, Patrick R. Montgomery

Bibliographic record

VenueInternational Psychogeriatrics · 2013
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsIsland HealthUniversity of WaterlooUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsGerontologyConfoundingMarital statusMedicineCross-sectional studyDemographyCohortLife satisfactionPopulationPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Frailty may be associated with reduced life satisfaction (LS). The objectives of this paper are to determine if (1) frailty is associated with LS in community-dwelling older adults in cross-sectional analyses; (2) frailty predicts LS five years later; and (3) specific domains of LS are preferentially associated with frailty. METHODS: This paper presents analysis of an existing population-based cohort study of 1,751 persons aged 65+ who were assessed in 1991, with follow-up five years later. LS was measured using the terrible-delightful scale, which measures overall LS and LS in specific domains. Frailty was measured using the Brief Frailty Instrument. Analyses were adjusted for age, gender, education, and marital status. RESULTS: Frailty was associated with overall LS at time 1 and predicted overall LS at time 2. This was seen in unadjusted analyses and after adjusting for confounding factors. Frailty was associated with all domains of LS at time 1, and predicted LS at time 2 in all domains except housing and self-esteem. However, the effect was stronger for LS with health than with other domains for both times 1 and 2. CONCLUSIONS: Frailty is associated with LS, and the effect is strongest for LS with health.

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)0.001
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 score0.005
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.036
GPT teacher head0.372
Teacher spread0.335 · 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

Citations37
Published2013
Admission routes2
Has abstractyes

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