Transcranial direct current stimulation for improving gross motor function in children with cerebral palsy: A systematic review
Bibliographic record
Abstract
Introduction The functional abilities of children with cerebral palsy are often compromised because of limited motor function. Transcranial direct current stimulation is a neuromodulation tool used as an adjunct to other therapeutic modalities to improve gross motor function. This review aimed to examine the quality of evidence and the effectiveness of transcranial direct current stimulation for improving gross motor function in children with cerebral palsy. Method A systematic review was conducted, and eligible studies were critically appraised for methodological quality. Randomised controlled trials were selected to undergo meta-analysis for assessing the effectiveness of transcranial direct current stimulation on clinical outcomes. Results Eight studies, including seven randomised controlled trials, fitted the inclusion criteria. All the randomised controlled trials were rated ‘moderate’ quality based on the grading of recommendations assessment, development and evaluation (GRADE) system. Using meta-analysis, only cadence, an outcome measure of gait variables, demonstrated efficacy of intervention, mean difference 16.57 (10.88, 22.25); I 2 = 0%, P = 0.83. Other gross motor and functional outcomes had either inconsistent mean difference or high heterogeneity. Conclusion Overall, the effectiveness of transcranial direct current stimulation as a treatment in children with cerebral palsy remains unclear, and the findings should be interpreted with caution. The quality of evidence was mostly moderate, and more vigorous research incorporating functional outcomes should be conducted to guide clinical practice.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".