A Matched-Pair Analysis of Gross Motor Skills of 3- to 5-Year-Old Children With and Without a Chronic Physical Illness
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare the gross motor skills of children with a chronic physical illness with those of their healthy peers. METHODS: Data for children with a chronic physical illness come from the Multimorbidity in Children and Youth Across the Life Course study, and data from children without a physical illness come from the Health Outcomes and Physical Activity in Preschoolers study. Multimorbidity in Children and Youth Across the Life Course and Health Outcomes and Physical Activity in Preschoolers included children ages 3-5 years and administered the Peabody Development Motor Scales-second edition. Participants were sex and age matched (20 male and 15 female pairs; Mage = 54.03 [9.5] mo). RESULTS: Gross motor skills scores were "below average" for 47% of children with a physical illness compared with 9% of children without a physical illness (P = .003). Matched-paired t tests detected significant differences in total gross motor scores (dz = -0.35), locomotor (dz = -0.31), and object control (dz = -0.39) scores, with healthy children exhibiting better motor skills, and no significant difference in stationary scores (dz = -0.19). CONCLUSIONS: This skill gap may increase burden on children with physical illness and future research should assess gross motor skills longitudinally to establish whether the gap widens with age.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".