Predictors of Long-Term Care Facility Residents’ Self-Reported Quality of Life With Individual and Facility Characteristics in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Identify predictors of long-term care (LTC) facility residents' self-reported quality of life (QoL). METHOD: QoL of a convenience sample of 928 residents from 48 volunteer LTC facilities across six Canadian provinces was assessed using the inter-Resident Assessment Instrument (interRAI) Self-Report Nursing Home Quality of Life Survey. Multivariate regression models were used to identify predictors. RESULTS: In logistic regression modeling, residents who were religious and socially engaged, had a positive global disposition, or resided in rural, private, or municipal facilities were less likely to report low QoL. Those with post-secondary education and who were dependent on activities of daily living were more likely to report low QoL. These factors, except for religiosity and residence in municipal facilities, were significant in generalized estimating equation (GEE) modeling. DISCUSSION: QoL is significantly associated with select resident and LTC facility characteristics with implications for improving residents' QoL and LTC facility programming, and guiding future research and social policy development.
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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 | 0.003 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it