Influence of the home environment on the motor development of infants with Down syndrome
Bibliographic record
Abstract
ABSTRACT Children with Down syndrome present impairments in neuro-psychomotor development, which are related to muscle tone, postural control and balance. Motor development is influenced by biological, psychological, social and environmental factors. Thus, the environment in which the infant is in can facilitate the neuro-psychomotor development. The objective of this study was to evaluate the influence of the home environment on the motor development of infants with Down syndrome. Sixteen infants with Down syndrome were divided into Group I (3 to 11 months of age) and Group II (12 to 18 months of age), evaluated by the Alberta Infant Motor Scale (AIMS) and the Affordances in the Home Environment for Motor Development Infant-Scale (AHEMD-IS) questionnaire. Data analysis was performed using the Kruskall-Wallis test, Spearman’s correlation coefficient and the likelihood ratio test. The results showed a significant positive relationship between the gross AIMS score and the variety of stimuli (p=0.01, r=0.78) and with the AHEMD-IS questionnaire score (p=0.02, r=0.74) in Group 2. Family income and affordances with motor function toys (p=0.05, r=0.49) were also correlated, but the correlation was weak. The home environment plays an important role in the motor development of children with Down syndrome aged between 12 and 18 months, as it provides opportunities for experiencing and experimenting. Better suited environments provide better motor performance.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".