Leveraging an intensive time series of young children's movement to capture impulsive and inattentive behaviors in a preschool setting
Andrew E. Koepp,
Elizabeth T. Gershoff
Abstract:Studying within‐person variability in children's behavior is frequently hindered by challenges collecting repeated observations. This study used wearable accelerometers to collect an intensive time series (2.7 million observations) of young children's movement at school (N = 62, Mage = 4.5 years, 54% male, 74% Non‐Hispanic White) in 2021. Machine learning analyses indicated that children's typical forward acceleration was strongly correlated with lower teacher‐reported inhibitory control and attention (r = −.6… Show more
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