Effectiveness of Modified Constraint-Induced Movement Therapy in Children With Unilateral Spastic Cerebral Palsy: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: In children with unilateral spastic cerebral palsy (CP), there is only limited evidence for the effectiveness of modified constraint-induced movement therapy (mCIMT). OBJECTIVE: To investigate whether 6 weeks of mCIMT followed by 2 weeks of bimanual task-specific training (mCIMT-BiT) in children with unilateral spastic CP improves the spontaneous use of the affected limb in both qualitative and quantitative terms more than usual care (UC) of the same duration. METHODS: Children with unilateral spastic CP with Manual Ability Classification System (MACS) scores I, II, or III and aged 2.5 to 8 years were recruited and randomly allocated to either the mCIMT-BiT group (three 3-hour sessions per week: 6 weeks of mCIMT, followed by 2 weeks of task-specific training in goal-directed bimanual play and self-care activities) or to 1.5 hours of more general physical or occupational weekly plus encouragement to use the affected hand for the UC group. Primary outcome measures were the Assisting Hand Assessment and the ABILHAND-Kids. Secondary outcomes were the Melbourne Assessment of Unilateral Upper Limb Function, the Canadian Occupational Performance Measure, and the Goal Attainment Scale. RESULTS: Twenty-eight children were allocated to mCIMT-BiT and 24 to UC. Except for the Melbourne, all primary and secondary outcome measures demonstrated significant improvements in the mCIMT-BiT group. CONCLUSION: mCIMT followed by task-specific training of goal-directed bimanual play and self-care activities is an effective intervention to improve the spontaneous use of the more affected upper limb in children with relatively good baseline upper extremity function.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".