Young Children Benefit from Intensive, Group-Based Pediatric Constraint-Induced Movement Therapy
Bibliographic record
Abstract
Background/Objectives: This quasi-experimental study examined the effectiveness of an intensive, group-based pediatric constraint-induced movement therapy (pCIMT) program for young children. Methods: Thirty-five children aged 21 months to 6 years, with unilateral hemiparesis (HP), or weakness on one side of the body from varying etiologies, participated in a 4-week intensive, interprofessional, theme- and group-based pCIMT clinic program in the Midwest, United States. The program ran for 4 weeks with 3 h of therapy per day, 5 days per week with 3 weeks of 24 h casting for the unaffected arm, followed by 1 week of bimanual focus. Outcome measures included the Quality Upper Extremity Skills Test (QUEST), Assisting Hand Assessment (AHA), Canadian Occupational Performance Measure (COPM), and Pediatric Evaluation of Disability Inventory (PEDI). Results: The participants statistically significantly improved the unilateral function of the HP arm in four of five QUEST variables (p < 0.009), bimanual coordination as measured by the AHA (p < 0.001), and some areas of occupational performance as measured by the COPM (p < 0.001) and PEDI (p < 0.05). Conclusions: This study revealed the intensive, group-based pCIMT clinic model was effective and feasible to implement with the support from various stakeholders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".