Exploring Parent-Child Dyadic Networks to Design a Smartphone-based Mindfulness Intervention for Underserved Families

Abstract

Parents from socioeconomically disadvantaged and minoritized backgrounds disproportionately experience higher rates of daily negative mood and lower levels of physical activity, negatively impacting health outcomes across the lifespan. Scalable, evidence-based interventions to promote family wellbeing and that fit into the busy lives of parents juggling many responsibilities remain beyond reach, especially for families from minoritized groups experiencing the greatest barriers to health. Mindfulness holds promise for addressing these disparities in access to evidence-based behavioral health interventions because it can be engaged upon at any given moment, can be delivered using smartphones, has higher rates of program completion relative to other evidence-based treatments, and has high rates of being integrated into daily life following study completion. In this study, we used smartphone experience-sampling and accelerometry to respectively measure mood and physical activity in 31 parent-child dyads. Parents reported negative mood and stress 10 times per day across 14 days for themselves and their child (3-8 years old). We used Group Iterative Multiple Model Estimation to construct networks describing associations among negative mood, stress, and physical activity for each parent and child dyad. Our findings suggest that we can use a complex systems approach to model the associations among mood, stress, and physical activity in parents and children in daily life. We discuss opportunities for using these parent-child dyad networks to inform the design of parent focused smartphone-based mindfulness interventions to support healthy parent-child interactions and reduce health disparities.