Pattern of Visual-Motor Integration, Visual Perception, and Fine Motor Coordination Abilities in Children Being Assessed for Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
OBJECTIVE: Motor skill assessment is part of the fetal alcohol spectrum disorder (FASD) multidisciplinary assessment. Some clinicians opt to exclude assessment of the subcomponents of visual-motor integration (visual perception and motor coordination), on the assumption that challenges will be revealed based on the assessment of visual-motor integration. The objective is to describe the visual-motor integration, visual perception, and fine motor coordination pattern of abilities in children with confirmed prenatal alcohol exposure being assessed for fetal alcohol spectrum disorder. METHODS: This cross-sectional study included 91 children (65 males; mean age: 10 years, 6 months SD = 2 years, 10 months) undergoing assessment for FASD. Friedman and Wilcoxon statistics were used to compare mean visual-motor integration, visual perception, and fine motor coordination percentiles from the Beery-Buktenica Developmental Test of Visual-Motor Integration, Sixth Edition (Beery-6). RESULTS: Children being assessed for FASD (n = 91) had the highest normative scores in visual perception, followed by visual-motor integration and fine motor coordination (mean percentiles (SD): 35.9 (24.9), 20.6 (18.3), and 13.8 (15.5), respectively) (χ 2 distribution = 46.909, p ≤ 0.001). CONCLUSION: Children being assessed for FASD experience more challenges with fine motor coordination compared with visual-motor integration and visual perception tasks. This pattern differs from the pattern established for the general population in which tasks that require visual-motor integration are more challenging than tasks that isolate visual perception and fine motor coordination. These results suggest that fine motor coordination should be included in FASD diagnostic assessments and considered as an area for intervention.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".