Diabetes support from romantic partners during early emerging adulthood.

We examined support for type 1 diabetes in casual versus committed romantic relationships and links to blood glucose, self-care, and affect in 101 young adults (Mage 18.8). Individuals provided survey and daily measures of support and blood glucose and affect during a 14-day diary period. Survey data indicated individuals viewed partners as helpful, with partners in committed relationships rated more helpful than those in casual relationships. Daily assessments indicated partners were seen as only moderately helpful. Individuals in committed relationships discussed diabetes with partners on more diary days than those in casual relationships. When individuals in any relationship type experienced more helpful partner support than their average, they reported higher positive and lower negative affect. However, those in casual relationships also experienced more negative affect and higher mean blood glucose the next day. Results suggest tradeoffs between immediate benefits and subsequent costs of partner support to adults in casual relationships.

The separation in coordination between social- and self-regulation for emerging adults with type 1 diabetes.

To examine how self-regulation and social-regulation surrounding type 1 diabetes (T1D) management are coordinated during early emerging adulthood and whether classes of coordination relate to HbA1c and executive functioning (EF). Emerging adult participants (N = 212) with T1D (M age = 18.8 years, SD = .40) completed a 14-day diary to capture components of self-regulation and social-regulation. A mixture multi-level latent coordination model first determined the separate but coordinated factor structure of self- and social-regulation, then determined the number of distinct classes of coordination and how those classes linked to HbA1c and EF. The best-fitting model included three coordinative factors (self, mother, and father) of regulation and two distinct classes. The class with lower HbA1c and higher EF had more stable self- and social-regulation, more connections between self- and social-regulation and reflected more adaptive patterns, consistent with medical management goals. Social connection with parents may aid in regulation during this at-risk transitional time of emerging adulthood.

Coordination of Self- and Parental-Regulation Surrounding Type I Diabetes Management in Late Adolescence.

Background: Type 1 diabetes management involves self- and social-regulation, with past research examining components through individual differences unable to capture daily processes. Purpose: Dynamical systems modeling was used to examine the coordinative structure of self- and social-regulation (operationalized as parental-regulation) related to daily diabetes management during late adolescence. Methods: Two hundred and thirty-six late adolescents with type 1 diabetes (M age = 17.77 years, SD = .39) completed a 14-day diary reporting aspects of self- (e.g., adherence behaviors, cognitive self-regulation failures, and positive and negative affect) and parental-regulation (disclosure to parents, knowledge parents have, and help parents provide). Results: Self-regulation functioned as one coordinative structure that was separate from parental-regulation, where mothers and fathers were coordinated separately from each other. Mothers' perceived helpfulness served as a driver of returning adolescents back to homeostasis. Conclusions: The results illustrate a dynamic process whereby numerous facets of self- and social-regulation are coordinated in order to return diabetes management to a stable state.

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.