%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 26
%N 
%P e50508
%T User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review
%A Eaton,Cyd
%A Vallejo,Natalie
%A McDonald,Xiomara
%A Wu,Jasmine
%A Rodríguez,Rosa
%A Muthusamy,Nishanth
%A Mathioudakis,Nestoras
%A Riekert,Kristin A
%+ Johns Hopkins School of Medicine, 5200 Eastern Avenue, Baltimore, MD, 21224, United States, 1 6673066201, ceaton4@jhmi.edu
%K mobile health
%K mHealth
%K digital health
%K treatment adherence
%K self-management
%K user engagement
%K chronic health conditions
%K mobile phone
%D 2024
%7 24.9.2024
%9 Review
%J J Med Internet Res
%G English
%X Background: There are numerous mobile health (mHealth) interventions for treatment adherence and self-management; yet, little is known about user engagement or interaction with these technologies. Objective: This systematic review aimed to answer the following questions: (1) How is user engagement defined and measured in studies of mHealth interventions to promote adherence to prescribed medical or health regimens or self-management among people living with a health condition? (2) To what degree are patients engaging with these mHealth interventions? (3) What is the association between user engagement with mHealth interventions and adherence or self-management outcomes? (4) How often is user engagement a research end point? Methods: Scientific database (Ovid MEDLINE, Embase, Web of Science, PsycINFO, and CINAHL) search results (2016-2021) were screened for inclusion and exclusion criteria. Data were extracted in a standardized electronic form. No risk-of-bias assessment was conducted because this review aimed to characterize user engagement measurement rather than certainty in primary study results. The results were synthesized descriptively and thematically. Results: A total of 292 studies were included for data extraction. The median number of participants per study was 77 (IQR 34-164). Most of the mHealth interventions were evaluated in nonrandomized studies (157/292, 53.8%), involved people with diabetes (51/292, 17.5%), targeted medication adherence (98/292, 33.6%), and comprised apps (220/292, 75.3%). The principal findings were as follows: (1) >60 unique terms were used to define user engagement; “use” (102/292, 34.9%) and “engagement” (94/292, 32.2%) were the most common; (2) a total of 11 distinct user engagement measurement approaches were identified; the use of objective user log-in data from an app or web portal (160/292, 54.8%) was the most common; (3) although engagement was inconsistently evaluated, most of the studies (99/195, 50.8%) reported >1 level of engagement due to the use of multiple measurement methods or analyses, decreased engagement across time (76/99, 77%), and results and conclusions suggesting that higher engagement was associated with positive adherence or self-management (60/103, 58.3%); and (4) user engagement was a research end point in only 19.2% (56/292) of the studies. Conclusions: The results revealed major limitations in the literature reviewed, including significant variability in how user engagement is defined, a tendency to rely on user log-in data over other measurements, and critical gaps in how user engagement is evaluated (infrequently evaluated over time or in relation to adherence or self-management outcomes and rarely considered a research end point). Recommendations are outlined in response to our findings with the goal of improving research rigor in this area. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022289693; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022289693 
%M 39316431
%R 10.2196/50508
%U https://www.jmir.org/2024/1/e50508
%U https://doi.org/10.2196/50508
%U http://www.ncbi.nlm.nih.gov/pubmed/39316431