The virtual family conference in stroke rehabilitation: Education, preparation, and transition planning
Bibliographic record
Abstract
OBJECTIVE: To examine the virtual family conference as an educational, preparatory, and transition planning intervention in stroke rehabilitation. DESIGN: Observational-cross-sectional study. SETTING: Inpatient stroke rehabilitation. SUBJECTS: Eighty-seven carers, participating in 48 conferences, were evaluated. INTERVENTIONS: The virtual family conference, involving the patient, carer(s), and interdisciplinary rehabilitation team, completed prior to community transition. The conference protocol and framework, consisting of nine primary themes and additional sub-themes, are outlined. Teleconferencing was the utilized virtual modality. MAIN MEASURES: . Information Satisfaction Questionnaire, and Kingston Caregiver Stress Scale. RESULTS: Significant improvement in post-conference carer-rating was noted for knowledge, pertaining to stroke nature/impairments, stroke management/prevention, functional status, and community services. Significant gains were demonstrated in post-conference satisfaction with information provided regarding stroke and discharge planning, across all assessed topics. There was also a significant increase in carer-reported confidence and preparedness for the community transition as well as a significant reduction in self-perceived stress for elements of the caregiving role. Organization of community follow-up care was consistently enabled within the proposed framework. CONCLUSIONS: The virtual family conference intervention demonstrated efficacy in facilitating carer education and preparation, along with discharge planning prior to community transition from stroke rehabilitation. Thus, illustrating potential benefits of family conferences and feasibility of their virtual application in stroke rehabilitative care.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".