Type 2 & other diabetes

Psychosocial factors predict medication adherence in young adults with youth‐onset type 2 diabetes: Longitudinal results from the TODAY2 iCount study

Diabet MedPublished Longitudinal cohort 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 →

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