H-GRASP: the feasibility of an upper limb home exercise program monitored by phone for individuals post stroke
Bibliographic record
Abstract
PURPOSE: To investigate the feasibility of a phone-monitored home exercise program for the upper limb following stroke. METHODS: A pre-post double baseline repeated measures design was used. Participants completed an 8-week home exercise program that included behavioural strategies to promote greater use of the affected upper limb. Participants were monitored weekly by therapists over the phone. The following feasibility outcomes were collected: Process (e.g. recruitment rate); Resources (e.g. exercise adherence rate); Management (e.g. therapist monitoring) and Scientific (e.g. safety, effect sizes). Clinical outcomes included: The Chedoke Arm and Hand Inventory, Motor Activity Log, grip strength and the Canadian Occupational Performance Measure. RESULTS: Eight individuals with stroke were recruited and six participants completed the exercise program. All but one of the six participants met the exercise target of 60 minutes/day, 6 days/week. Participants were stable across the baseline period. The following post-treatment effect sizes were observed: CAHAI (0.944, p = 0.046); MALQ (0.789, p = 0.03) grip strength (0.947, p = 0.046); COPM (0.789, p = 0.03). Improvements were maintained at three and six month follow ups. CONCLUSIONS: Community dwelling individuals with stroke may benefit from a phone-monitored upper limb home exercise program that includes behavioural strategies that promote transfer of exercise gains into daily upper limb use. Implications for Rehabilitation A repetitive, task-oriented home exercise program that utilizes telephone supervision may be an effective method for the treatment of the upper limb following stroke This program is best suited for individuals with mild to moderate level impairment and experience a sufficient level of challenge from the exercises An exercise program that includes behavioural strategies may promote transfer of exercise gains into greater use of the affected upper limb during daily activities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".