Caregiver‐directed home‐based intensive bimanual training in young children with unilateral spastic cerebral palsy: a randomized trial
Bibliographic record
Abstract
AIM: To examine the efficacy of caregiver-directed, home-based intensive bimanual training in children with unilateral spastic cerebral palsy (USCP) using a randomized control trial. METHOD: Twenty-four children (ages 2y 6mo-10y 1mo; 10 males, 14 females) performed home-based activities directed by a caregiver for 2 hours per day, 5 days per week, for 9 weeks (total=90h). Cohorts of children were age-matched into groups and randomized to receive home-based hand-arm bimanual intensive therapy (H-HABIT; n=12) or lower-limb functional intensive training (LIFT-control; n=12). Caregivers were trained before the intervention and supervised remotely via telerehabilitation. Dexterity and bimanual hand function were assessed using the Box and Blocks test (BBT) and the Assisting Hand Assessment (AHA) respectively. Caregiver perception of functional goals was measured using the Canadian Occupational Performance Measure (COPM). RESULTS: H-HABIT showed greater improvement on the BBT compared to LIFT-control and no improvement on the AHA. H-HABIT demonstrated significant improvement in COPM-Performance compared to LIFT-control and both groups showed equal improvement in COPM-Satisfaction. INTERPRETATION: H-HABIT improved dexterity and performance of functional goals, but not bimanual performance, in children with USCP compared to a control group receiving intervention of equal intensity/duration that also controlled for increased caregiver attention. Home-based models provide a valuable, family-centered approach to achieve increased treatment intensity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".