Barriers and Facilitators of a Community-Based, Slow-Stream Rehabilitation, Hospital-to-Home Transition Program for Older Adults: Perspectives of a Multidisciplinary Care Team
Bibliographic record
Abstract
The purpose of this study was to examine the perspectives of support staff, health care professionals, and care coordinators working in or referring to a community-based, slow-stream rehabilitation, hospital-to-home transition program regarding gaps in services, and barriers and facilitators related to implementation and functioning of the program. This was a qualitative descriptive study. Recruitment was conducted through purposive sampling, and 23 individuals participated in a focus groups or individual semi-structured interview. Transcripts were analyzed by six researchers using inductive thematic analysis. Themes that emerged were organized based on a socio-ecological framework. Themes were categorized as: (1) macro level, meaning gaps while waiting for program, limited program capacity, and gaps in service post-program completion; (2) meso level, meaning lack of knowledge and awareness of the program, lack of specific referral process and procedures, lack of specific eligibility criteria, and need for enhanced communication among care settings; or (3) micro level, meaning services provided, program participant benefits, person-centred communication, program structure constraints, need for use of outcome measures, and follow-up or lack of follow-up. Implementation of seamless patient information sharing, documentation, use of specific referral criteria, and use of standardized outcome measures may reduce the number of unsuitable referrals and provide useful information for referral and program staff.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".