GAIT- AND BALANCE-RELATED FACTORS AFFECTING PARTICIPATION IN SCHOOL-AGED CHILDREN WITH UNILATERAL CEREBRAL PALSY
Bibliographic record
Abstract
Although gait and balance impairments are prevalent in children with unilateral cerebral palsy (UCP), their effects on participation are not completely elucidated. This study aims to explore factors affecting participation in children with UCP, particularly those related to gait and balance. This descriptive relation-seeker study was completed with 40 children with UCP at Gross Motor Function Classification System (GMFCS) levels I and II (50% female; median age = 11 (7-12)years). "The Gross Motor Function Measure (GMFM-66)", "The Pediatric Balance Scale (PBS)", "The Timed Up and Go test (TUG) and The Functional Mobility Scale (FMS)", and "The BTS G-Walk Spatiotemporal Gait Analysis System" were used to evaluate the gross motor function, balance, functional mobility, and quantitative gait parameters, respectively. "The Canadian Occupational Performance Measure (COPM)" was employed to evaluate participation. Variables affecting the COPM scores were analyzed by multivariate regression analysis.The factors affecting the COPM-performance score were cadence (B = 79.859, p = 0.001) and FMS (B = 0.352, p<0.001). These variables explained about 45% of thevariation in the COPM-performance score (R2adj = 0.445). The factors affecting the COPM-satisfaction score were cadence (B = 0.188, p=0.044) and stride length of the more affected side (B = 0.137, p=0.008), which explained 26% of thevariation in the COPM-satisfaction score (R2adj =0 .260).The factors affecting participation in children with UCP were cadence, stride length of the more affected side, and functional mobility. We recommend that rehabilitation specialists consider these factors, as they may be beneficial in designing rehabilitation interventions that effectively promote participation in 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".