The Effects of Living Arrangements on Depression and Life Satisfaction in Rural Chinese Older Adults: A 20-Year Study
Bibliographic record
Abstract
Abstract Objectives China has experienced rapid socio-economic transformations over the past two decades. Based on individualization and intergenerational solidarity theories, this study explores changes in the associations between the living arrangement on psychological well-being over time and across different chronic conditions. Methods Eight waves of longitudinal data (2001–2021) collected in Anhui, China were employed, including. 9,765 (person-year) observations. Mixed linear models containing interaction terms for time and chronic conditions were used to examine the effects of living arrangements on life satisfaction and depression. Results Compared to living with children, the negative correlation with life satisfaction and the positive correlation with depression for those living alone or with spouse only decreased over time, while the negative correlation between living in skipped-generation household and life satisfaction also diminished. As the number of chronic conditions increases, life satisfaction declines further for older adults living alone, with a spouse only, or in a skipped-generation household. Living alone leads to a higher increase in depression, but living with others reduces it. Discussion This study is the first to identify the changes in dynamic relationships between living arrangements on psychological well-being of older adults across time and chronic health conditions, reflecting shifts in filial piety and family culture. While older adults increasingly accept independent living, coresiding with children remains beneficial during multimorbidity. These findings contribute to the understanding of ageing in the context of economic and cultural transitions in developing regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".