What is the threshold dose of upper limb training for children with cerebral palsy to improve function? A systematic review
Bibliographic record
Abstract
INTRODUCTION: Neuroplasticity is harnessed through high-intensity or high-dose training. Given the costs and time burden for families of children with cerebral palsy (CP), it is important to quantify which rehabilitation training approaches and doses confer the largest clinical gain. The main objective of this systematic review was to determine any threshold dose of upper limb training needed for children with CP to achieve clinically significant functional improvements. METHODS: This systematic review included studies if they were as follows: randomised controlled trials; participants had a diagnosis of CP or brain injury; mean age of participants was 0-18 years; and intervention was an active upper limb training intervention. Two raters independently extracted data. Data were pooled and analysed using a receiver operator characteristic (ROC) curve and odds ratios to investigate the dose of practice that led to clinically significant gains. RESULTS: A total of 74 trials were included in this review. Quantitative analyses included 25 studies (707 participants; age range 18 months to 21 years) for motor function (Assisting Hand Assessment) and 20 studies (491 participants; age range 3 months to 17 years) for individual goal achievement (Canadian Occupational Performance Measure). ROC curve analyses found that approximately 40 hr of practice is needed to improve upper limb motor ability in the unilateral population. For all typographies of CP, individual goals were achieved at a lower dose (14-25 hr) of practice when goal-directed interventions were provided. CONCLUSION: To improve individual goals, children need to practice goals for more than 14-25 hr, combining face-to-face therapy with home practice. To improve general upper limb function (based on evidence in the unilateral population), children need to practice for more than 30-40 hr. Interventions that set functional goals and involve actual practice of those goals lead to goal achievement at a lower dose than general upper limb motor training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".