Nurse‐led health promotion interventions improve quality of life in frail older home care clients: lessons learned from three randomized trials in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: This paper explores the lessons learned from a series of three randomized controlled trials that included 498 community-living frail older adults (≥65 years) using home care services in Southern Ontario, Canada. Each study was designed to evaluate the effectiveness of different multi-component nurse-led health promotion and disease prevention (HPDP) interventions. METHODS: The nurse-led HPDP interventions were 6- or 12-month multi-component and evidence-based strategies targeting known risk factors for functional decline and frailty. Across the three studies, a common approach was used to measure the change in health-related quality of life (HRQOL) (SF-36) and the costs of use of health services (Health and Social Services Utilization Inventory) from baseline to the end of the intervention. RESULTS: The main lesson learned from the three studies is that nurse-led HPDP interventions for frail older home care clients provide greater improvements in HRQOL compared with usual home care. Such approaches are highly acceptable to this population and can be implemented using existing home care resources. Nurse-led HPDP interventions should include multiple home visits, multidimensional screening and assessment, multi-component evidence-based HPDP strategies, intensive case management, inter-professional collaboration, providers with geriatric training and experience, referral to and coordination of community services, and theory use. CONCLUSION: The results of the three trials underscore the need to reinvest in nurse-led HPDP interventions in home care to optimize HRQOL and promote ageing in place in the target population of frail older adults. More studies are needed to evaluate the effectiveness of additional nurse-led HPDP interventions in other contexts and settings.
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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 | 0.023 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".