The Effect of a Long-Term Care Insurance Program on Subjective Well-Being of Older Adults with a Disability: Quasi-Experimental Evidence from China
Bibliographic record
Abstract
China launched its long-term care insurance (LTCI) program for older adults in 2016. Although the scheme has shown some promising outcomes, little is known about whether it improves subjective well-being. This study explored this topic among older persons with a disability and identified the underlying mechanisms associated with the channel of this effect using data from a national survey. The LTCI program was shown to improve the subjective well-being among older persons with a disability and this effect increased over time. The LTCI program has great positive effect among women and those who lived alone compared to their counterparts. Mechanism analysis revealed that the main channel by which the LTCI program has positive effect occurred through the satisfaction of long-term care needs and improved self-reported health. This study suggests promising benefits of the LTCI program for older Chinese adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".