SPORTS STARS: a practitioner-led, peer-group sports intervention for ambulant children with cerebral palsy. Activity and participation outcomes of a randomised controlled trial.
Bibliographic record
Abstract
PURPOSE: To investigate the effectiveness of a practitioner-led, peer-group sports intervention for children with CP at GMFCS Level I-II. METHOD: included eight-weeks (eight hours) of physiotherapist-led, sports-specific gross motor activity training, sports education, teamwork development and confidence building. Sports participation was measured using self-identified participation goals (modified Canadian Occupational Performance Measure (mCOPM)). Physical competence was measured with mCOPM activity goals and high-level gross motor batteries (Test of Gross Motor Development (TGMD-2); GMFM-Challenge) and walking (Timed-Up-and-Go), running (Muscle Power Sprint Test; 10x5m Sprint Test), jumping (Standing Broad Jump; Vertical Jump) and throwing (Seated Throw) items. General participation and quality of life were also measured. Outcomes were measured pre, post and 12-weeks post-intervention. Data were analysed using linear mixed models. RESULTS: = 0.001-0.009) compared to the waitlist-control. CONCLUSION: improves sports-specific physical activity competence in locomotor and object control skills.Sport-specific interventions should incorporate sport-specific gross motor activity training as well as sports education, confidence building and teamwork.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".