The Needs of Older Adults With Disabilities With Regard to Adaptation to Aging and Home Care: Questionnaire Study
Bibliographic record
Abstract
BACKGROUND: The home environment is an important means of support in home-based care services for older people. A home environment that facilitates healthy aging can help older adults maximize their self-care abilities and integrate and utilize care resources. However, some home environments fail to meet the needs of older adults with disabilities. OBJECTIVE: This paper aimed to study the needs of older adults with disabilities with respect to adaptation to aging, and to analyze the associations of individual factors and dysfunction with those needs. METHODS: A questionnaire survey was administered to 400 older adults with disabilities from 10 communities in Ningbo City, Zhejiang Province, China. The survey was conducted from August 2018 to February 2019. RESULTS: A total of 370 participants completed the survey. The proportion of participants with mild dysfunction was the highest (128/370, 34.59%), followed by those with extremely mild (107/370, 28.92%), moderate (72/370, 19.46%), and severe (63/370, 17.03%) dysfunction. The care needs of older adults with extremely mild and mild dysfunction pertained primarily to resting, a supportive environment, and transformation of indoor activity spaces. The care needs of older adults with moderate dysfunction pertained mainly to resting and renovation of bathing and toilet spaces. Factors influencing the needs of older adults with disabilities were dysfunction (P=.007), age (P=.006), monthly income (P=.005), and living conditions (P=.04). CONCLUSIONS: The needs of older adults with disabilities varied by the degree of dysfunction, and many factors influenced these needs in the community. These findings may provide a scientific basis for developing community-specific aging-related adaptation services for older adults with disabilities in the future.
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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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".