Thesis Defense Announcement
College of Arts and Sciences announces the Final Thesis Defense of
for the Degree of Master of Science
April 18, 2019 at 3:00 PM in Johnson Hall, Room 222
Advisor: Kristoffer Berlin
Social Information- Processing Variables Predict Hemoglobin A1c Trajectories in Youth with Type 1 Diabetes
ABSTRACT: Glycemic control, measured as hemoglobin A1c (HbA1c), is a robust predictor of long-term negative health complications in individuals with type 1 diabetes (T1D). Predicting long-term trajectories in HbA1c can inform interventions to improve health outcomes in this population throughout the lifespan. Previous research has shown that higher negative attributions of friends' reactions to doing adherence behaviors in front of them is related to higher anticipated adherence difficulties in those situations, higher diabetes-related stress, and higher HbA1c, cross-sectionally. However, it is not known if these social-information processing variables predict longitudinal trajectory of HbA1c. The purpose of the present study is to determine if social information- processing variables can predict membership into empirically derived subgroups of longitudinal HbA1c trajectories in youth with T1D. 195 adolescents with T1D were recruited from an outpatient endocrinology clinic. Youth completed the Diabetes Stress Questionnaire, a measure of diabetes-related stress, and the Attributions of Peer Reactions scale (APR), which includes two subscales: Negative Attributions of Friend Reactions (NAFR) and Anticipated Adherence Difficulties (AAD). Youth read 3 vignettes in which individuals with T1D need to practice diabetes self-care while with friends and rated their agreement with statements about how their friends would perceive them doing diabetes care in this situation (NAFR) and their anticipated adherence difficulties in this situation (AAD). HbA1c values were extracted from youths' medical record at 3 timepoints, approximately six months apart. Growth mixture modeling will be used to derive patterns of HbA1c trajectories, controlling for illness duration.