Psychosocial factors predict medication adherence in young adults with youth‐onset type 2 diabetes: Longitudinal results from the TODAY2 iCount study
Authors' conclusion
Suboptimal medication adherence, common in young adults with youth-onset type 2 diabetes, is predicted by interfering beliefs about medicines and social factors. We must address these beliefs and unmet needs to develop tailored interventions for this vulnerable group.
Study context
- Population
- Young adults (mean age 26 years) with youth-onset T2D in the TODAY2 cohort171 OHA
- Outcome
- Psychosocial predictors of low adherence (<80% of pills/insulin) and per cent adherence to OHAs and insulin
- Follow-up
- T2 ( , ≈1 year later)
Methodological detailssecondary analysis of TODAY2 cohort (iCount study), unannounced telephone pill counts
- Secondary analysis of TODAY2 cohort (iCount study)
- Unannounced telephone pill counts
Main finding
As reported in the abstract
OHA adherence · T2
- Low adherent to oral hypoglycaemia agents (OHAs)
- 65.4%
- Concerns about diabetes medicines (adverse effects, dependence) at T1 predicted higher odds of OHA low adherence at T2
- p = 0.019
- Housing insecurity at T1 predicted lower per cent OHA adherence at T2
- p = 0.045
- Reporting ≥2 need insecurities at T1 predicted lower per cent OHA adherence at T2
- p = 0.027
Observational data: associations, not effects.
Further findings
Insulin adherence · T2
- Low adherent to insulin
- 36.3%
- Beliefs that medicines are overused predicted higher odds of insulin low adherence
- P = 0.013
- Beliefs that medicines are harmful predicted lower per cent insulin adherence
- P = 0.004
- Beliefs that medicines are overused predicted lower per cent insulin adherence
- P = 0.010
- Adjusted, including T1 adherence
- Self-reported insulin adherence
Original publication
Psychosocial factors predict medication adherence in young adults with youth‐onset type 2 diabetes: Longitudinal results from the TODAY2 iCount study. Diabet Med. Published 17 February 2023. doi:10. 1111/ dme. 15062
Composed by AI from the published abstract and checked against it. How Briefs are made →