Excessive screen time for children ages 3-5 years is linked with poor sleep, inactivity, and behavior problems.
The WHO recommends children under 5 get <1 hour of screen time per day, but few children meet this guideline.
This is partly attributable to the rapid growth of digital media technology (i.e., smartphones, tablets), which make
screen time more available across multiple contexts. Unfortunately, our understanding of the unique ways
children and families use digital media lags behind the rapid adoption of this technology. Therefore, we need
updated paradigms to understand how the content, timing, and context of digital media use impacts health.
There are three key limitations of existing digital media use research (1) an exclusive focus on use duration (2)
reliance on subjective measures and (3) a failure to account for the fact that digital media use effects people
differently depending on context (i.e., heterogeneity). The proposed project will overcome these limitations by
using passive mobile sensing to objectively measure digital media timing, content and duration. We will use
ecological momentary assessment (EMA) and accelerometry to measure screen time context. This data will be
used to understand the unique ways screen habits unfold and ultimately influence children’s sleep, activity, and
social/emotional functioning.
The proposed study is a multiyear observational cohort of preschoolers (age 3-5) designed to uncover the
mechanisms underlying children’s digital media use. We will use passive mobile sensing, accelerometry and
ecological momentary assessment (EMA) to collect intensive longitudinal data on children’s digital media use,
sleep, physical activity, sedentary behavior, and behavior problems. By collecting this intensive longitudinal data,
we can uncover micro-temporal dynamics - defined as: bi-directional effects that unfold over a short amount of
time (i.e., minutes, hours). Within these micro-temporal dynamics, we aim to identify systems of ‘Granger
causality’: systems where one behavior (i.e., digital media use) predicts future behavior (i.e., sleep). We expect
the Granger causal links between behaviors to vary in direction and magnitude between different children. We
will quantify this heterogeneity by identifying ‘digital phenotypes’: a child-specific web of links between multiple
health behaviors. Lastly, we aim to evaluate the longitudinal association between digital phenotypes and
cardiovascular health risk (obesity) and mental health risk (internalizing/externalizing disorder symptoms). The
utility of digital phenotypes lies in their ability to identify salient intervention targets for tailored just-in-time
interventions for multiple health behaviors. The first step in harnessing these linkages is to identify digital
phenotypes and examine their association with health outcomes over time. This project is innovative in the
simultaneous objective measurement of children’s digital media use, sleep, and activity. This work is significant
because findings will contribute to evidence upon which digital media guidelines are based and inform
personalized intervention strategies.
