WHO CARES? PREFERENCES REGARDING FORMAL AND INFORMAL CARE AMONG OLDER ADULT SERVICE USERS
Bibliographic record
Abstract
Whereas personal care is provided to older adults either by formal or informal providers, less attention has been paid to older adults’ preferences regarding the type of service provision. This study examines the predictors of older adults’ preferences toward formal or informal care services in the context of Quebec, Canada. The data of 1,335 consists of both mail-in and online surveys distributed to a broad sample of older adults in Quebec through a monthly magazine. We computed a logistic regression analysis in predicting older adults’ preferences toward personal care services. Older adults’ age, gender, and income levels were controlled. Older adults receiving more public services were more likely to respond that they preferred to receive formal care services (OR = 1.41 95% CI [1.14, 1.75]). Feeling more comfortable receiving services from family members or friends was associated with lower preference of formal services (OR = 0.81 95% CI [0.68, 0.96]). Respondents’ younger age (OR = 0.77 95% CI [1.1, 1.8]) and higher income (OR = 1.54 95% CI [1.30, 1.84]) predicted greater preference for public services. The findings support expectations from the existing literature regarding the preference towards formal services among older adult service users. The Quebec context provides an interesting case because persistent austerity measures within the health and social services system have decreased the availability of formal care services under the justification that service users will gravitate towards informal provision wherever possible.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".