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Record W2606907827 · doi:10.1186/s12877-017-0485-5

Trajectories of Life Satisfaction and their Predictors among Korean Older Adults

2017· article· en· W2606907827 on OpenAlexaff
Hyun J. Lim, Dae Kee Min, Lilian Thorpe, Chel Hee Lee

Bibliographic record

VenueBMC Geriatrics · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLife satisfactionMedicineMental healthGerontologyDemographyRehabilitationLogistic regressionScale (ratio)Longitudinal studyPsychologyPsychiatryPhysical therapySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Among older adults, life satisfaction (LS) correlates with health, mortality, and successful ageing. As various potential threats to LS tend to increase with advancing years, patterns of age-related changes in LS among older adults remain inconsistent. This study aimed to identify LS trajectories in older adults and the characteristics of individuals who experience them. METHODS: Large-scale, nationally representative, longitudinal data collected from 2005 to 2013 were analyzed for this study. The outcome measure was a summary of multidimensional domains influencing LS: health, finance, housing, neighbor relationships, and family relationships. Latent class growth models and logistic regression models were used to identify trajectory groups and their predictors, respectively. RESULTS: Within 3517 individuals aged 65 or older, five trajectories were identified across eight follow-up years: "low-stable" (TG1; n = 282; 8%), "middle-stable" (TG2; n = 1146; 32.6%), "improving" (TG3; n = 75; 2.1%), "upper middle-stable" (TG4; n = 1653; 47%), and "high" (TG5; n = 361; 10.3%). High trajectory individuals more frequently had higher education, financial security, good physical health, and good mental health than those in the stable, but less satisfied, groups. Similarly, compared to the largest group (upper middle-stable trajectory), individuals in the low-stable or middle-stable trajectory group not only had poorer physical and mental health but were more likely to be living alone, financially stressed, and residing in urban locations. Individuals with improving trajectory were younger and in poorer mental health at baseline compared to the upper middle-stable trajectory group. CONCLUSION: Life satisfaction in the older follows distinct trajectories. For older adults, trajectories are stable over time and predictable, in part, from individual characteristics. Knowledge of these patterns is important for effective policy and program development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations57
Published2017
Admission routes1
Has abstractyes

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