Physical therapy in children with cerebral palsy in Brazil: a scoping review
Bibliographic record
Abstract
AIM: To identify and assess published studies concerning physical therapy in Brazilian children and adolescents with cerebral palsy (CP) using the International Classification of Functioning, Disability and Health (ICF) framework. METHOD: Articles in English and Portuguese published until October 2020, with no date restrictions, were searched in several different databases. Study characteristics, journal metrics, sample characteristics, and ICF domains explored intervention components and outcomes were extracted. Studies were classified according to the Oxford Centre for Evidence-Based Medicine hierarchy levels to characterize the evidence. RESULTS: Ninety-four studies were included. Spastic CP with fewer limitations in gross motor abilities was the most reported; 67% of the studies had low levels of evidence and were published in journals without an impact factor. The three most frequent interventions were neurodevelopmental treatment, suit therapy, and transcranial direct current stimulation. Intervention components explored body functions and structures (73.4%), activity (59.6%), environment (2.1%). They did not explore participation (0%). The outcomes investigated addressed activity (79.8%), body functions and structures (67.0%), and participation (1.1%), but not environment (0%). INTERPRETATION: Studies of physical therapy for Brazilian children and adolescents with CP focused on reducing impairments and activity limitations. Studies with higher levels of evidence and an expanded focus on participation and environmental factors are necessary.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".