Examination of physical activity development in early childhood: protocol for a longitudinal cohort study of mother-toddler dyads.

BACKGROUND: Physical activity (PA) development in toddlers (age 1 and 2 years) is not well understood, partly because of a lack of analytic tools for accelerometer-based data processing that can accurately evaluate PA among toddlers. This has led to a knowledge gap regarding how parenting practices around PA, mothers' PA level, mothers' parenting stress, and child developmental and behavioral problems influence PA development in early childhood. METHODS: The Child and Mother Physical Activity Study is a longitudinal study to observe PA development in toddlerhood and examine the influence of personal and parental characteristics on PA development. The study is designed to refine and validate an accelerometer-based machine learning algorithm for toddler activity recognition (Aim 1), apply the algorithm to compare the trajectories of toddler PA levels in males and females age 1-3 years (Aim 2), and explore the association between gross motor development and PA development in toddlerhood, as well as how parenting practices around PA, mothers' PA, mothers' parenting stress, and child developmental and behavioral problems are associated with toddlerhood PA development (Exploratory Aims 3a-c). DISCUSSION: This study will be one of the first to use longitudinal data to validate a machine learning activity recognition algorithm and apply the algorithm to quantify free-living ambulatory movement in toddlers. The study findings will help fill a significant methodological gap in toddler PA measurement and expand the body of knowledge on the factors influencing early childhood PA development.

Screen Time, Sociodemographic Factors, and Psychological Well-Being Among Young Children.

Importance: Young children's screen time increased during the COVID-19 lockdown in 2020, but it is unknown whether their screen time returned to prepandemic levels in 2021. Knowledge of the relationship between screen time and child development and health will inform prevention and intervention targets and strategies. Objective: To evaluate screen time by family income and race and ethnicity in the prepandemic (ie, 2018, 2019) and pandemic (ie, 2020, 2021) periods and to examine the relationship between screen time and psychological well-being among young children in the US. Design, Setting, and Participants: Cross-sectional population-based web or mail survey study of 2018-2021 National Survey of Children's Health participants aged 6 months to 5 years. Exposure: Daily screen time (<1, 1, 2, 3, or ≥4 h/d) reported by participants' primary caregivers. Main outcomes and Measures: Flourishing and externalizing behaviors, as indicators of psychological well-being. All analyses were weighted, accounting for the complex survey sample design. Results: Of the 48 775 participants (50.7% female), the proportion of those with high screen time (defined as ≥1 h/d for children aged 6 months-1 year and ≥2 h/d for children aged 2-5 years) was 48.5% (95% CI, 46.3%-50.7%) in 2018, 49.2% (95% CI, 47.0%-51.5%) in 2019, 55.3% (95% CI, 53.4%-57.2%) in 2020, and 50.0% (95% CI, 48.3%-51.6%) in 2021. Among children living in poverty (federal poverty level <100%), the proportion of those with high screen time was 48.7% (95% CI, 42.8%-54.6%) in 2018, 52.0% (95% CI, 45.4%-58.6%) in 2019, 60.9% (95% CI, 55.4%-66.4%) in 2020, and 58.9% (53.7%-64.1%) in 2021. Adjusted odds ratio of flourishing was 0.66 (95% CI, 0.51-0.85), 0.81 (95% CI, 0.66-0.99), 0.68 (95% CI, 0.52-0.88), and 0.53 (95% CI, 0.42-0.69) for less than 1, 2, 3, and 4 or more hours per day vs 1 hour per day of screen time, respectively, among children aged 3 to 5 years. No association between screen time and flourishing was found among children aged 6 months to 2 years. An adjusted externalizing behavior score was higher by 0.2 points (95% CI, -0.1 to 0.5), 0.5 points (95% CI, 0.3 to 0.8), 1.3 points (95% CI, 1.0 to 1.6), and 2.1 points (95% CI, 1.7 to 2.5) for less than 1, 2, 3, and 4 or more hours per day vs 1 hour per day of screen time, respectively, among children aged 3 to 5 years. Conclusions and Relevance: In this multiyear cross-sectional study of a representative sample of young children in the US, the increased prevalence of high screen time in 2020 returned to prepandemic levels in 2021; however, it remained elevated in children living in poverty. Two hours or more of daily screen time was associated with lower psychological well-being among preschool-aged children.

Reward value and internal state differentially drive impulsivity and motivation.

Goal-directed behavior is influenced by both reward value as well as internal state. A large body of research has focused on how reward value and internal drives such as hunger influence motivation in rodent models, however less work has focused on how these factors may differentially affect impulsivity. In these studies, we tested the effect of internal drive versus reward value on different facets of reward-related behavior including impulsive action, impulsive choice and, motivation. We varied reward value by changing the concentration of sucrose in the reward outcome, and varied internal drive by manipulating thirst through water restriction. Consistent with the literature we found that both internal state and reward value influenced motivation. However, we found that in high effort paradigms, only internal state influenced motivation with minimal effects of reward value. Interestingly, we found that internal state and reward value differentially influence different subtypes of impulsivity. Internal state, and to a lesser extent, reward value, influenced impulsive action as measured by premature responding. On the other hand, there were minimal effects of either reward value or homeostatic state on impulsive choice as measured by delay discounting. Overall, these studies begin to address how internal state and reward value differentially drive impulsive behavior. Understanding how these factors influence impulsivity is important for developing behavioral interventions and treatment targets for patients with dysregulated motivated or impulsive behavior.

DIY-NAMIC Behavior: A High-Throughput Method to Measure Complex Phenotypes in the Homecage.

Complex behavioral assessment is necessary to comprehensively assess in vivo manipulations in rodent models for neuropsychiatric disorders. Operant behavioral paradigms provide rich datasets and allow for the careful analysis of behavioral phenotypes. However, one major limitation in these studies is the expense and work-load that are required using traditional methods. The equipment for commercial operant boxes can be prohibitively expensive, and the daily experimenter effort and mouse costs required for these studies is extensive. Rodents are generally trained on task-specific paradigms for months, tested every day for 5-7 d/week. Additionally, appetitive paradigms usually require food restriction and are also commonly run in the non-active light phase of the rodent circadian rhythm. These limitations make operant behavioral testing especially difficult during adolescence, a time period of interest with regards to the development of adult-like phenotypes and a high-risk period for the development of neuropsychiatric disorders, including those which involve impulsive behavior. In order to address these issues, we developed an automated, inexpensive, open-source method which allows the implementation of most standard operant paradigms in the homecage of rodents in shorter time frames without food restriction, and with much less experimenter effort. All construction and code for the do-it-yourself Nautiyal Automated Modular Instrumental Conditioning (DIY-NAMIC) system are open source. We demonstrate their utility here by measuring impulsive behavior in a pharmacology experiment, as well as in adolescent mice.