Profiling the littlest movers: Quantity and predictors of toddlers' physical activity levels measured using a novel machine learning model

2026-02-01 pediatrics Title + abstract only

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ObjectiveThe objectives of this study were to: (1) quantify toddlers total physical activity (TPA) and guideline adherence using a machine learning method; and (2) explore socio-ecological predictors (e.g., sex, childcare) of TPA. MethodsToddlers (n=103, 21.4 {+/-} 6.9 months, 52% female) from the Hamilton, Canada region completed a gross motor assessment (Peabody Developmental Motor Scales 2nd ed; PDMS-2) and wore an ActiGraph wGT3X-BT accelerometer on the right hip for 4-8 days. Parents compl...

Profiling the littlest movers: Quantity and predictors of toddlers' physical activity levels measured using a novel machine learning model

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