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Record W4409168952 · doi:10.1186/s12889-025-22036-4

Social capital, health status, and sociodemographic factors associated with subjective well-being among older adults: a comparative study of community dwellings and nursing homes

2025· article· en· W4409168952 on OpenAlexaboutno aff
Yan Chen, Dahui Wang, Wenhao Chen, Wanjing Li, Shanshan Zhu, Xianlan Wu

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersDepartment of Education of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsBiostatisticsMedicinePublic healthGerontologyEnvironmental healthSocial capitalEpidemiologyNursing homesSocial statusNursing

Abstract

fetched live from OpenAlex

BACKGROUND: This study aimed to examine the differences in relationships among social capital components, health status, sociodemographic characteristics, and subjective well-being (SWB) among older adults in institutionalized versus non-institutionalized care environments. METHODS: A cross-sectional survey was conducted involving 1,037 older adults aged 65-95 years from nine communities and nine nursing homes across three regions of Zhejiang Province, China. Social capital and SWB were assessed using the Social Capital Scale and the Memorial University of Newfoundland Scale of Happiness (MUNSH), respectively. Propensity score matching (PSM, 1:1, caliper width 0.02) was applied to balance key sociodemographic characteristics and health status between community-dwelling and nursing home residents. Multivariable linear regression was utilized to analyze the relationships among social capital components, health status, sociodemographic factors, and SWB in both groups. RESULTS: PSM identified 290 older adults in community dwellings and a comparable group (n = 290) in nursing homes. Comparative analysis showed that nursing home residents demonstrated lower SWB. Multivariable linear regression revealed that social connection, trust, and cohesion were positively associated with SWB in both groups. However, social participation was only significantly linked with community dwellings residents. Both groups showed a positive relationship between SWB and self-rated health, but the number of chronic conditions did not show a significant link with SWB. Additionally, higher income (≥ 3000 RMB) and a middle school education linked to higher SWB among community-dwelling older adults, whereas family structure, specifically being not in union and having three or more children, was associated with lower SWB in the nursing home group. CONCLUSION: Social capital and health status showed a strong and consistent association with SWB in both groups. Strengthening social connections, trust, and cohesion, along with maintaining positive health perceptions, is expected to enhance the well-being of older adults, particularly for those in institutional settings. Notably, differences in how sociodemographic factors influence SWB across settings. These findings indicate the necessity for tailored interventions that address the unique needs of each care environment to promote healthier aging experiences.

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)0.001
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.053
GPT teacher head0.373
Teacher spread0.319 · 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

Citations12
Published2025
Admission routes1
Has abstractyes

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