Preferences of Integrated Care and the Influencing Factors Among Chinese Community-Dwelling Older Adults
Bibliographic record
Abstract
Objective: Population aging and epidemiological transition have prompted requests for integrating health and social care. The goal of meeting complex care needs necessitates the understanding of preferred patterns among older adults. The study aimed to elicit the preferred care patterns and the influencing factors of integrated health and social care among community-dwelling older adults in multiple regions of China. Methods: From a national survey, 1184 community-dwelling older adults in three cities across China were included in the study. Individual characteristics and preferred care patterns were measured. Five preferred care patterns were classified, including Home-based health and social care, Community-based health and social care, Home-based health care but community-based social care, Community-based health care but home-based social care, and Institution-based health and social care. Multivariate logistic regression and random forest model were applied to obtain reliable results. Results: Overall, approximately half of the participants (47.7%) in the survey preferred Home-based health and social care and more than a quarter of participants (25.6%) preferred Community-based health and social care, followed by Institution-based health and social care (14.4%). A relatively small fraction of participants reported preferences for Home-based health care but community-based social care (8.0%) and Community-based health care but home-based social care (4.2%). Gender, age, education, living arrangement, resident city, income per month, access to medication, and self-care capability were significantly associated with older adults' preferences (p<0.05 each). Education, living arrangement, age, resident city, and income per month were the most relevant predictors, followed by gender, number of chronic diseases, self-care capability, and access to medication. Conclusion: To effectively meet care needs, efforts should focus on home- and community-based care. Since the preferred care patterns were characterized by obvious variability, policymakers and service providers should carefully consider the differences in making tailored strategies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".