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Record W7120462361

Perfil de participação na comunidade e ambiente de crianças pequenas brasileiras com Paralisia Cerebral : Recorte do estudo multicêntrico PartiCipa Brasil

2025· dissertation· pt· W7120462361 on OpenAlexaboutno aff
Viviann Alves de Pontes

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2025
Typedissertation
Languagept
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
FundersUniversidade Federal da Paraíba
KeywordsCerebral palsyIntervention (counseling)General partnershipScale (ratio)Community participationGross motor skillRehabilitation
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Participation is an important indicator of early childhood health in children with Cerebral Palsy (CP) and should be prioritized in rehabilitation programs. However, young children with CP tend to face restrictions in participating in community activities, which reinforces the need to investigate this outcome in low- and middle-income countries such as Brazil. Objective: To describe community participation and the environmental profile of young Brazilian children with CP, to analyze the correlation between participation domains, environmental factors and the child's GMFCS level, and to suggest an intervention strategy to improve participation. Methods: This study, part of the “PartiCipa Brasil” multicenter project, involved Brazilian children with CP, aged between 2 and 5 years and 11 months. A questionnaire of contextual factors, the Gross Motor Function Classification System (GMFCS) - Family Report was used to classify gross motor function, and the Young Children's Participation and Environment Measure (YC-PEM) was used to assess participation (Frequency, Involvement and Desire for change) and the environment (Supports, Barriers, Aids, Resources and General Environmental Support). The analyses were carried out using Jamovi software (version 2.3.28) with descriptive statistics and Spearman's correlation, adopting p<0.05. In addition, as a second product, a book chapter was written with a clinical case of a 7-year-old child with CP, with an intervention based on the Pathways and Resources for Engagement and Participation (PREP) approach. The Canadian Occupational Therapy Measure (COPM), Participation and Environment Measure for Children and Youth (PEM-CY) and the Therapeutic Goals Scale agreed in partnership with the family (GAS) were used. Results: Of the 541 children with CP followed up by PartiCipa Brasil, 109 answered the YC-PEM and were included in this study, with a mean age of 44.8 months (SD=12.0). There was a predominance of males, spastic CP and GMFCS level V, with children from low-income families. On average, the children participated in the community “once in the last month” and were involved at the “more or less” level, with an emphasis on activities related to “commitments”. A higher level of support was observed compared to the barriers faced, and 49.8% of caregivers expressed a desire for change in participation. Frequency of Participation correlated significantly with the child's GMFCS (r²=-0.240, p=0.011); Involvement with Supports (r²=0.230, p=0.016), Environmental Helpfulness (r²=0.210, p=0.028) and Overall Environmental Support (r²=0.238, p=0.012); and Desire to Change with Supports (r²=-0.274, p=0.003), Barriers (r²=0.340, p=0.001), Environmental Helpfulness (r²=-0.359, p=0.001) and Overall Environmental Support (r²=-0.344, p=0.001). For the book chapter, clinically significant changes were seen in the COPM and GAS with scores above 2 points and 50 points, respectively, and improvement in the Participation and Environment scores on the PEM-CY. Conclusion: This is the first study using PartiCipa Brasil data to describe how young children with CP from different regions of Brazil participate in the community. Understanding participation and environmental factors can support interventions, such as the PREP approach, to improve opportunities for this audience to participate in society.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.293
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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