Factors associated with caregiver distress among home care clients in New Zealand: Evidence based on data from interRAI Home Care assessment
Bibliographic record
Abstract
OBJECTIVE: To identify factors associated with caregiver distress among home care clients in New Zealand. METHODS: The cohort consisted of 105,978 community-dwelling people aged 65 years or older requiring home care services in New Zealand who had at least one informal caregiver. Bivariate and multivariable logistic regression analyses were used to identify factors associated with caregiver distress. RESULTS: Variables associated with risk of caregiver distress included Depression Rating Scale score, aggressive behaviour symptoms, primary informal caregiver relationship to patient, Cognitive Performance Scale score, Changes in Health, End-stage disease, and Signs and Symptoms Scale score, informal care time, secondary informal caregiver relationship to care recipient, activities of daily living hierarchy scale score and any hospitalisation. CONCLUSIONS: The study has identified important characteristics that are associated with caregiver stress. These results suggest that caregiver distress can be relieved by promoting protective factors and aiming to reduce risk factors among home care clients in New Zealand.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".