A qualitative study of home care client and caregiver experiences with a complex cardio-respiratory management model
Bibliographic record
Abstract
BACKGROUND: Home care clients are typically older and have some degree of medical, physical, cognitive or social conditions that require formal or informal support to promote healthy aging in the community. Home care clients contribute a significant proportion of health service use, including emergency department visits. The DIVERT-CARE trial introduced a cardio-respiratory management model to improve client motivation, symptoms and rates of unwarranted health service use. Our objective was to explore the perceptions and experiences of individuals who participated in the DIVERT-CARE self-management support and education intervention. METHODS: A qualitative study was nested within a pragmatic randomized control trial and conducted following a 15-week multi-component cardio-respiratory intervention. A phenomenological descriptive design was employed using thematic analysis. Post-intervention, clients and their caregivers were invited to participate in a semi-structured telephone interview. Interview questions were designed to elicit the experience with the intervention components. RESULTS: A total of 29 interviews were completed from June 2018 to March 2020 from participants in Ontario, Newfoundland, and British Columbia. Three themes were identified; self-care trajectory and burden of responsibility, learning and behaviour change, and feeling connected pre-emptively to care providers, the information and medical advice, and connection through the therapeutic relationship. CONCLUSIONS: Home care clients experience unique challenges in managing cardio-respiratory related chronic disease. Home-based interventions fostered a therapeutic relationship of connectedness while equipping clients with necessary knowledge and skills. These results inform recommendations for community nursing, and home-based self-management supports for older community-residing individuals.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".