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Record W2121299385 · doi:10.1186/s12939-015-0136-4

Socio-economic factors related with the subjective well-being of the rural elderly people living independently in China

2015· article· en· W2121299385 on OpenAlexaboutno aff
Yicheng Zhou, Linyi Zhou, Changluan Fu, You Wang, Hongtao Wu, Rongjun Zhang, Linfeng Zheng

Bibliographic record

VenueInternational Journal for Equity in Health · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsGovernment of Jiangsu ProvinceNational Social Science Fund of ChinaNational Natural Science Foundation of China
KeywordsSpouseHappinessSubjective well-beingAffect (linguistics)Life satisfactionChinaGerontologyPsychologyRural areaActivities of daily livingSocial supportDemographyMedicineSocial psychologyGeographyPsychiatrySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Many Chinese elderly increasingly face the serious problem of the "empty nest" phenomenon. The elderly living independently, also called empty-nest elderly, refers to elderly people living alone whose children left home. However few studies concerned about the subjective well-being (SWB) of the elderly living independently. METHODS: This study employs The Memorial University of Newfoundland Scale of Happiness (MUNSH) to explore the SWB of the elderly living independently in rural areas of Wenzhou, a relatively developed region in China. 536 sampled are randomly selected. RESULTS: The results indicate that participants obtained low scores in positive affect, positive experience, and the total SWB score, but high scores in negative affect and negative experience. Age, low education, poor health condition and little income were found to be negatively correlated with SWB. The SWB score of the elderly living with a spouse is higher than those who divorced or lost their spouse and the score of women is lower than that of men. In addition, the survey revealed that children's support has a positive influence on the SWB of the rural elderly living independently. CONCLUSIONS: The elderly living independently in rural Wenzhou, China have unfavorable SWB. Poor socio-economic statuses are negative impact factors. But the children's support can help to improve. Special attention is needed to those with lower socio-economic status and less children's support.

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)0.002
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 score0.030
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.040
GPT teacher head0.399
Teacher spread0.358 · 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

Citations92
Published2015
Admission routes1
Has abstractyes

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