Family caregivers’ perspectives on the acceptability of four interventions proposed for rural transitional care: A multi-method study
Bibliographic record
Abstract
BACKGROUND: There is a critical need for hospital-to-home transitional care interventions to prepare family caregivers for patients' post-discharge care in rural communities. Four evidence-based interventions (named discharge planning, treatments, warning signs, and physical activity) have the potential to meet this need but family caregivers' perspectives on the acceptability of the interventions have not been examined. This gap is significant because unacceptable interventions are unlikely to be used or used as designed, thereby undermining outcome achievement. Accordingly, this study examined the perceived acceptability of the four interventions to rural family caregivers. MATERIALS AND METHODS: A multi-method descriptive design was used. The quantitative method entailed the administration of an established scale to assess the interventions' perceived acceptability to family caregivers. The qualitative method involved semi-structured interviews to explore family caregivers' perceived acceptability of the interventions in greater depth, including acceptable and unacceptable aspects, in the context of their own transitional care experience. Participants were the family caregivers of a relative who had been discharged home in a rural community from an acute care hospital in Ontario, Canada. RESULTS: The purposive sample included 16 participants who were mostly middle-aged women (n = 14; 87.5%) caring for a parent (n = 9; 56.3%) at high risk for hospital readmission. The mean scores on the acceptability measure were 3 or higher for all interventions, indicating that, on average, the four interventions were perceived as acceptable. In terms of acceptable aspects, four themes were identified: the interventions: 1) involve family caregivers and proactively prepare them for discharge, 2) provide clear, written, and detailed guidance, 3) place the onus on healthcare providers to initiate communication, and 4) ensure post-discharge follow-up. In terms of unacceptable aspects, one theme was identified: the physical activity intervention would be challenging to implement. DISCUSSION: The findings support implementing the four interventions in practice throughout the hospital-to-home transition. Healthcare providers should assess family caregivers' comfort in participating in the physical activity intervention and tailor their role accordingly.
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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 | 0.034 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".