Healthcare consumers' and professionals' perceived acceptability of evidence‐based interventions for rural transitional care
Bibliographic record
Abstract
BACKGROUND: There is a pressing need for high quality hospital-to-home transitional care in rural communities. Four evidence-based interventions (discharge planning, treatments, warning signs, and physical activity) have the potential to improve rural transitional care. However, there is limited understanding of how the perceptions of healthcare consumers and professionals compare on the acceptability of the interventions. Convergent views on intervention acceptability support implementation, whereas divergent views highlight areas requiring reconciliation prior to implementation. AIMS: This study compared the acceptability of four evidence-based interventions proposed for rural transitional care, as perceived by healthcare consumers and professionals. METHODS: A cross-sectional, comparative design was used. The convenience sample included 36 healthcare consumers (20 patients and 16 family caregivers) who had experienced a hospital-to-home transition in the past month and 30 healthcare professionals (29 registered nurses and one nurse practitioner) who provided transitional care in rural Ontario, Canada. Participants were presented with descriptions of the four interventions and completed an established intervention acceptability measure. Presentation of the four intervention descriptions and respective acceptability measures was randomized to control for possible order effects. The perceived overall acceptability of the interventions and their attributes (i.e., effectiveness, appropriateness, risk, and convenience) were compared using independent samples t-tests. RESULTS: Consumer ratings were consistently higher across all four interventions in terms of overall acceptability as well as effectiveness, appropriateness, and convenience (all p's < .01; effect sizes 0.70-1.13). No significant between-group differences in perceived risk were found. LINKING EVIDENCE TO ACTION: Contextual and methodological differences may account for variability in ratings, but further research is needed to explore these propositions. The results support future qualitative inquiry targeting professionals to better understand their perspectives on the effectiveness, appropriateness, and convenience of the four interventions.
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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 | 0.019 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".