Personalized goal setting and predictors of functional gains following constraint-induced movement therapy in preschool-aged children with unilateral cerebral palsy
Bibliographic record
Abstract
OBJECTIVE: This study aimed to identify caregiver-selected goal characteristics that predict functional improvements following constraint-induced movement therapy (CIMT), offering novel insights into personalized rehabilitation for younger children with unilateral cerebral palsy (UCP). METHODS: This study included 19 children with UCP aged 4-6 years who participated in a three-week CIMT program comprising 15 sessions (30 hours total), during which the unaffected hand was constrained to encourage intensive use of the affected limb. Caregivers identified five meaningful rehabilitation goals per child using the Canadian Occupational Performance Measure, categorizing them into self-care, productivity, or leisure domains and ranking them by importance. Upper-limb function was objectively evaluated using the Assisting Hand Assessment before and immediately after CIMT. Linear regression analyses identified the factors influencing goal selection, and least absolute shrinkage and selection operator regression determined whether prioritized goal types predicted improvements in upper limb function. RESULTS: Self-care goals were most frequently selected (72.6%), followed by leisure (26.3%) and rarely productivity (1.1%). Leisure goal selection was significantly associated with greater baseline upper limb range of motion and lower baseline occupational performance scores. The higher prioritization of goals involving quiet leisure activities (e.g., arts, crafts, computer play) and dressing tasks (e.g., buttoning, zipping) significantly predicted greater functional improvements post-intervention. CONCLUSION: This study provides important new evidence indicating that caregiver-selected rehabilitation goals that are closely aligned with a child's latent motor capacities positively affect functional outcomes. These findings underscore the clinical importance of individualized, family-driven goal setting for optimizing therapeutic effectiveness in preschool-aged children with UCP.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".