Digital Health Interventions to Improve Medication Adherence Among Older Adults: A Systematic Review.

Authors

Kaleab Taye Haile, Wejdan Shahin, Eyob Alemayehu Gebreyohannes, Abdella Birhan Yabeyu, Amina Hareem, Mulugeta Hayelom Kalayou, Xun Yi, Kate Wang

Published in

Australasian journal on ageing. Volume 45. Issue 3. Pages e70206.

Abstract

To review evidence on the type, characteristics and effect of digital health interventions (DHIs) on medication adherence among older people.
Articles were searched from inception to May 2025 in PubMed, Embase, CINAHL, Scopus and Web of Science. Randomised and non-randomised studies were included if they: involved older people aged 65 years or older; applied any DHI(s); compared the intervention with a comparator group or baseline; and reported medication adherence as an outcome. Risk of bias was assessed using the Cochrane risk of bias tools, and certainty of evidence using GRADE (Grading of Recommendations, Assessment, Development and Evaluation). A narrative synthesis was conducted.
A total of 35 articles were included, most of which were randomised controlled trials (n = 22). Risk of bias ranged from low to high, and certainty from very low to moderate. Nearly half of the studies (n = 17) reported DHIs improved medication adherence compared with control or baseline. Mobile apps (3/5), electronic reminders (3/3), social assistive robots (1/1), telenursing (1/1) and combined DHIs (2/2) showed the most promise. Interventions that used multiple functionalities or strategies to support behaviour change (reminders or prompts) were most likely to improve adherence. The other DHIs had mixed results or no significant effects.
While findings across DHIs varied, interventions incorporating tailored reminders, multicomponent features and interactivity may have the potential to be more effective in improving medication adherence among older adults. Further research is needed to identify usage patterns and investigate the factors underlying differences in effectiveness.

PMID:
42469587
Bibliographic data and abstract were imported from PubMed on 18 Jul 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.