Psychosocial predictors of diabetes self-efficacy in young adults with youth-onset type 2 diabetes

Document Type

Journal Article

Publication Date

3-5-2025

Journal

Journal of behavioral medicine

DOI

10.1007/s10865-025-00554-1

Keywords

Depression; Self-efficacy; Social determinants of health; Social support; Type 2 diabetes mellitus

Abstract

The aim of this study was to identify psychosocial factors associated with, and predictive of, diabetes self-efficacy (DSE) in young adults with youth-onset type 2 diabetes (T2D), a vulnerable, understudied group. In this observational, longitudinal study (T1 = baseline, T2 = 1 year later), 348 participants in the TODAY2 multi-center study of youth-onset T2D, completed valid measures of: diabetes self-efficacy, beliefs about medicines, depression and anxiety symptoms, diabetes distress, attitudes, self-management support, and need insecurities. Multivariable logistic regression models evaluated independent associations of each psychosocial factor with the likelihood of being in the high/low DSE tertile groups. Multivariable linear regression models assessed associations with DSE as a continuous variable. Participants' mean age was 26 years, 67.9% were women, mean diabetes duration was 12.4 years, with mean of 2.5 diabetes-related complications. Greater self-care support increased the odds of high DSE at T2. Beliefs that medicines are overused, moderate-to-severe depressive or anxiety symptoms, and unmet material needs, decreased the odds of high DSE at T2. More support, fewer depressive and anxiety symptoms, and fewer unmet material needs at T1 predicted T2 DSE scores. Cognitions (beliefs that medicines are overused), emotions (depressive/anxiety symptoms), and social factors (self-management support, unmet material needs), were significant longitudinal predictors of DSE in young adults with youth-onset T2D. These potentially modifiable factors should be considered when screening for, and designing, interventions to enhance DSE, to improve health behaviors and forestall the development of complications in this at-risk group.

Department

Biostatistics and Bioinformatics

Link to Full Text

Share

COinS