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Influência do ambiente domiciliar no desenvolvimento motor de lactentes com síndrome de Down

2018· article· pt· W2894831648 on OpenAlexaboutno aff
Natália Alves Goulart Knychala, Edna Alves de Oliveira, Lúcio Borges de Araújo, Vívian Mara Gonçalves de Oliveira Azevedo

Bibliographic record

VenueFisioterapia e Pesquisa · 2018
Typearticle
Languagept
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
FundersUniversidade Federal de Uberlândia
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

RESUMO Crianças com síndrome de Down apresentam atrasos no desenvolvimento neuropsicomotor relacionados a tônus muscular, controle postural e equilíbrio. O desenvolvimento motor sofre interferência multifatorial, que envolve características biológicas, psicológicas, sociais e ambientais. Assim, o ambiente em que o lactente está incluído pode atuar como facilitador do desenvolvimento neuropsicomotor. O objetivo deste estudo foi avaliar a influência do ambiente domiciliar no desenvolvimento motor de lactentes com síndrome de Down. Participaram do estudo 16 lactentes com a síndrome, divididos em grupo I (3 a 11 meses) e grupo II (12 a 18 meses), avaliados pela Alberta Infant Motor Scale (AIMS) e pelo questionário Affordances in the Home Environment for Motor Development - Infant Scale (AHEMD-IS). A análise de dados foi feita por meio do teste de Kruskal-Wallis, coeficiente de correlação de Spearman e teste de razão de verossimilhança. Os resultados evidenciaram uma correlação positiva significativa entre o escore bruto da AIMS e a variedade de estímulos (p=0,01, r=0,78) e com o escore total do questionário AHEMD-IS (p=0,02, r=0,74) no grupo II. Verificou-se, ainda, correlação entre a renda familiar e as oportunidades com brinquedos de função motora grossa (p=0,05, r=0,49), porém com correlação fraca. Conclui-se que o ambiente domiciliar tem importante papel no desenvolvimento motor de crianças com síndrome de Down entre 12 e 18 meses, por proporcionar oportunidades de vivências e experimentações. Assim, pode-se afirmar que ambientes mais adequados proporcionam melhor desempenho motor.

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 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)0.000
metaresearch head score (Gemma)0.003
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.264
Teacher spread0.253 · 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".

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Citations6
Published2018
Admission routes1
Has abstractyes

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