Variation in the health outcomes associated with frailty among home care clients: relevance of caregiver distress and client sex
Bibliographic record
Abstract
BACKGROUND: The identification of contextual factors that modify associations between client frailty and their health and service use outcomes is essential for informed home health care and policy planning. Our objective was to examine variation in the associations between frailty and select 1-year health outcomes by caregiver distress and client sex among community-residing older care recipients. METHODS: We conducted a retrospective cohort study using linked population-based clinical and health administrative databases for all long-stay home care clients (n = 234,552) aged 66+ years assessed during April 2010-2013 in Ontario, Canada. Frailty was assessed using a previously validated 72-item frailty index (FI). Presence of caregiver distress was derived from clinical assessment items administered by trained home care assessors. Multivariable log-binomial regression models were used to examine variations in the associations between frailty and outcomes of interest (mortality, nursing home [NH] placement, all-cause and prolonged hospitalization) by caregiver distress, with further model stratification by client sex. RESULTS: Frailty prevalence varied little by sex (19.3% women, 19.9% men) despite significant sex-differences in clients' sociodemographic and health characteristics. In both sexes, frailty was significantly associated with all outcomes, particularly NH placement (RR = 3.84, 95%CI 3.75-3.93) and death (RR = 2.32, 95%CI 2.27-2.37), though risk ratios were greater for women. Caregiver distress was more common with increasing frailty and for male clients, and a significant independent predictor of NH placement and prolonged hospitalization in both sexes. The association between frailty and NH placement (but not other outcomes) varied by caregiver distress for both men and women (p < 0.001 interaction terms), showing a greater magnitude of association among clients without (vs. with) a distressed caregiver. CONCLUSIONS: As caregiver distress varies by client sex, represents a key driver of NH placement (even among relatively robust clients), and modifies the impact of other risk factors such as frailty, it should be routinely assessed. Further, sex-differences should be considered when developing and evaluating community-based services for older adults and their caregivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".