Development and Evaluation of Self-Management and Task-Oriented Approach to Rehabilitation Training (START) in the Home: Case Report
Bibliographic record
Abstract
BACKGROUND: The incidence of stroke and subsequent level of disability will increase, as age is the greatest risk factor for stroke and the world's population is aging. Hospital admissions are too brief for patients to regain necessary function. Research to examine therapy delivered within the home environment has the potential to expedite relearning of function and reduce health care expenditures. PURPOSE: This case report describes the use of the knowledge-to-action cycle (KTA) to develop and evaluate an evidence-based approach for rehabilitation in the home that incorporates self-management and task-oriented functional training (TOFT) for people with stroke. CASE DESCRIPTION: The KTA cycle was used to guide adaptation of evidence from self-management and TOFT into an approach titled START (Self-Management and Task-Oriented Approach to Rehabilitation Training). Three stakeholder symposiums identified barriers and supports to implementation. Clinical practice leaders were engaged as partners in the development of the intervention. An online learning management system housed the resources to support therapist training. Therapist focus groups were conducted and stroke outcomes were used to assess patient response. OUTCOMES: Eight therapists completed 4 workshops and applied the home intervention in 12 people with stroke. A mentoring process for therapists included feedback from peers and experts after viewing treatment videos. Therapist response was determined from the focus groups; patient response was measured by standardized assessments. The therapists noted that the intervention was easier to implement with patients who were motivated and had minimal cognitive impairment. DISCUSSION: The KTA cycle provided a structure for the development of this evidence-based rehabilitation intervention, which was feasible to implement in the home. Further evaluation needs to be undertaken to assess the effectiveness of START.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 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".