From Early-Life to Late-Life: Patterns and Determinants of Mental Health in Older Chinese Adults
Bibliographic record
Abstract
Abstract Depressive symptoms are highly prevalent among Chinese older adults, with studies indicating that nearly a quarter experience such symptoms. By the 2010s, this figure had risen to nearly 40%, alongside a 13% prevalence of cognitive impairment. This symposium brings together five papers that explore the early- and late-life determinants of psychological and cognitive health in older Chinese adults. The research topics span childhood food insecurity, job loss, late-life living arrangements, social engagement, and end-of-life hospice care. Wuyi examines the long-term impact of childhood food insecurity on depression trajectories, considering the roles of hukou status and the timing of food insecurity. Dr. Song et al. analyze the effects of involuntary job loss on late-life depressive symptoms, focusing on the rural-urban hukou divide and work ownership differences. Dr. Zhang et al. assess how late-life living arrangement transitions impact depressive symptoms, particularly among rural and urban older adults. Zhang et al. explore the effects of reduced social engagement on cognitive function during the COVID-19 pandemic, emphasizing gender and urban-rural disparities. Lastly, Yi et al. investigate depression and anxiety symptom networks in Chinese hospice patients, comparing different symptom profiles. Together, these studies deepen our understanding of the social determinants of mental and cognitive health in older Chinese adults, offering insights for policy and intervention development. Chinese Gerontology Studies Interest Group Sponsored Symposium
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".