ICF-based functioning profiles in children and adolescents with cerebral palsy: Evidence from a population-based study in Argentina
Bibliographic record
Abstract
PURPOSE: In Argentina, there is no consensus on the functional assessment of children with cerebral palsy (CP). The International Classification of Functioning, Disability and Health (ICF) Core Sets for children with CP are tools that standardize clinical functional assessments. The aim was to build functioning profiles of children with CP aged 2 to 18 years in eight Argentine cities, to identify their functional needs and contribute to improving assessment processes. METHODS: Cross-sectional study, developed in stages. This article describes the last stage, the creation of the functional profile of a sample surveyed in eight cities. Twenty-five categories established in the common abbreviated core set of CP were evaluated through the application of a protocol called PC-CIFuncional (previously created). This protocol consists of scales or culturally sensitive instruments, assessed through clinical evaluations and questionnaires for children and families. RESULTS: One hundred thirty-three functioning profiles were built using the previously developed PC-CIFuncional protocol. Of the participants, 52.7% had severe motor compromise with Gross Motor Function Classification System (GMFCS) levels IV and V. In children at GMFCS level IV-V, most categories in activities and participation-including recreation, communication and physical activity-showed severe limitations and restrictions, compared with their peers. The use of technology for daily living and mobility in children with less motor compromise (GMFCS level I-III) was neither a facilitator nor a barrier, but in children with greater compromise it was a complete facilitator. CONCLUSIONS: Differences in functional needs were identified in children with CP according to motor involvement. This project standardizes the identification of functional needs and therapeutic goals based on ICF language, creating novel functioning profiles in Argentina.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".