Implementation of the Community Assets Supporting Transitions (CAST) transitional care intervention for older adults with multimorbidity and depressive symptoms: A qualitative descriptive study
Bibliographic record
Abstract
BACKGROUND: Older adults with multimorbidity experience frequent care transitions, particularly from hospital to home, which are often poorly coordinated and fragmented. We conducted a pragmatic randomized controlled trial to test the implementation and effectiveness of Community Assets Supporting Transitions (CAST), an evidence-informed nurse-led intervention to support older adults with multimorbidity and depressive symptoms with the aim of improving health outcomes and enhancing transitions from hospital to home. This trial was conducted in three sites, representing suburban/rural and urban communities, within two health regions in Ontario, Canada. PURPOSE: This paper reports on facilitators and barriers to implementing CAST. METHODS: Data collection and analysis were guided by the Consolidated Framework for Implementation Research framework. Data were collected through study documents and individual and group interviews conducted with Care Transition Coordinators and members from local Community Advisory Boards. Study documents included minutes of meetings with research team members, study partners, Community Advisory Boards, and Care Transition Coordinators. Data were analyzed using content analysis. FINDINGS: Intervention implementation was facilitated by: (a) engaging the community to gain buy-in and adapt CAST to the local community contest; (b) planning, training, and research meetings; (c) facilitating engagement, building relationships, and collaborating with local partners; (d) ensuring availability of support and resources for Care Transition Coordinators; and (e) tailoring of the intervention to individual client (i.e., older adult) needs and preferences. Implementation barriers included: (a) difficulties recruiting and retaining intervention staff; (b) difficulties engaging older adults in the intervention; (c) balancing tailoring the intervention with delivering the core intervention components; and (c) Care Transition Coordinators' challenges in engaging providers within clients' circles of care. CONCLUSION: This research enhances our understanding of the importance of considering intervention characteristics, the context within which the intervention is being implemented, and the processes required for implementing transitional care intervention for complex older adults.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".