Effect of Neurodevelopmental treatment on function and participation of children with Spastic Diplegic Cerebral Palsy
Bibliographic record
Abstract
This study focused on analyzing the effect of NDT on the function and participation of a child with spastic Diplegic Cerebral Palsy. NDT can be used as an active approach and with proper facilitation, carry-over at home, parent involvement, and looking at function from a participatory perspective. Changes can be expected in all domains of ICF thereby enhancing the quality of life of an individual with Cerebral Palsy and also their families. 25 children with Spastic diplegic cerebral palsy with GMFCS level I-III, CFCS level I-III, EDACS level I-III, and VFCS level I-III were enrolled at Latika Roy Memorial Foundation, Dehradun, Uttarakhand, India. A baseline assessment was done using the Gross motor function measure (GMFM) 66, the Functional independence measure (WeeFim), the Goal attainment scale (GAS), and the pediatric balance scale. Outcome measures used to analyze participation were the Canadian Occupational Performance Measure (COPM) and Child Engagement in daily life measures. The group underwent a 10-week intervention program based on NDT. Pre and post-intervention data was analyzed. The results post-intervention showed positive outcomes indicating that NDT can be useful for improving the function and participation of children with cerebral palsy. The performance and satisfaction levels of participants improved as per COPM. There was an improvement in the participation of the children as per Child engagement in daily life measure. The Weefim scores, GMFM 66 total increased. GAS scores and balance scores of PBS were achieved and showed positive improvement.
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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 | 0.001 |
| 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".