Stroke survivors’, caregivers’, and health care professionals’ perspectives on the weekend pass to facilitate transition home
Bibliographic record
Abstract
OBJECTIVE: To explore stroke survivors', caregivers', and health care professionals' perceptions of weekend passes offered during inpatient rehabilitation and its role in facilitating the transition home. DESIGN: Qualitative descriptive. SUBJECTS: Sixteen stroke survivors, 15 caregivers, and 20 health care professionals' from a rehabilitation hospital. METHODS: Participants discussed their perceptions of the purpose of the weekend pass, experiences with the weekend pass including supports needed, and weekend pass administration. Focus group and interview data were audio recorded, professionally transcribed, checked for accuracy, and analyzed using conventional content analysis. RESULTS: We identified 3 key themes: i) preparing for patients to be safe at home; ii) gaining insight through the weekend pass; and iii) the emotional context of the weekend pass. These themes varied by participant group. CONCLUSIONS: When offering weekend passes, stroke care systems should carefully consider patients' and caregivers' readiness, emotional state, and preparation for weekend passes. The weekend pass experience can inform in-patient therapy, provide patients and caregivers with insight into life after stroke, and help prepare patients and families for the ultimate transition home.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".