Longitudinal Associations Between Movement Behaviours and Development Among Infants Using Compositional Data Analysis
Bibliographic record
Abstract
BACKGROUND: The study examined the longitudinal associations of sleep time, restrained time, back time and tummy time with development in a sample of infants using compositional data analysis. METHODS: Participants were a subsample of 93 parent-infant dyads from the Early Movers project in Edmonton, Canada. Parents completed a 3-day time-use diary at 2, 4 and 6 months of age. Time spent in four mutually exclusive movement behaviours were calculated representing sleep (i.e., sleep time), sedentary behaviour (i.e., restrained time and back time) and physical activity (i.e., tummy time). Communication, fine motor, gross motor, personal-social, problem solving and total development were measured at 2, 4 and 6 months of age with the Ages and Stages Questionnaire (ASQ-3). Gross motor development was also measured by a physiotherapist using the Alberta Infant Motor Scale (AIMS) at 6 months. The age six major gross motor milestones (i.e., independent sitting, crawling, assisted standing, assisted walking, independent standing, independent walking) were achieved according to World Health Organization criteria, in the first 18 months of life, were calculated. RESULTS: : 0.02-0.15). More sleep time or tummy time relative to other movement behaviours was associated with more advanced development and earlier achievement of some milestones. The opposite was observed for back time. Associations with restrained time were mixed. The optimal movement behaviour durations (minutes/day) for AIMS and WHO milestone outcomes, were 38-43 of tummy time, 51-54 of back time, 43-96 of restrained time and 845-900 of sleep time. CONCLUSIONS: Targeting healthy movement behaviour patterns in infants may be a promising health promotion strategy.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".