Cited by 128Digital Mental Health InterventionsMobile Health and mHealth ApplicationsInnovative Human-Technology Interaction

Predicting user adherence to behavioral eHealth interventions in the real world: examining which aspects of intervention design matter most

Baumel, Amit, Yom-Tov, Elad·2018·Translational Behavioral Medicine

Abstract

Existing frameworks have identified a range of intervention design features that may facilitate adherence to eHealth interventions; however, empirical data are lacking on whether intervention design features can predict user adherence in the real world-where the public access available tools-and whether some design aspects of behavioral eHealth interventions are more important than others in predicting adherence. This study examined whether intervention design qualities predict user adherence to behavioral eHealth interventions in real-world use and which qualities matter the most. We correlated the online activities of users of 30 web-based behavioral interventions-collected from a proprietary data set of anonymized logs from consenting users of Microsoft Internet Explorer add-on-with interventions' quality ratings obtained by trained raters prior to empirical examination. The quality ratings included: Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness (i.e., persuasive design and incorporation of behavior change techniques), and Therapeutic Alliance. We found Therapeutic Persuasiveness (i.e., the incorporation of persuasive design/behavior change principles) to be the most robust predictor of adherence (i.e., duration of use, number of unique sessions; 40 ≤ rs ≤ .58, ps ≤ .005), explaining 42% of the variance in user adherence in our regression model. Results indicated up to six times difference in the percentage of users utilizing the interventions for more than a minimum amount of time and sessions based on Therapeutic Persuasiveness. Findings suggest the importance of persuasive design and behavior change techniques incorporation during the design and evaluation of digital behavioral interventions.

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Crossref · 10.1093/tbm/ibx037

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Authors
Baumel, A., & Yom-Tov, E.
Affiliations
  • Northwell Health (US)
  • Microsoft Research, Herzeliya, Israel
Corresponding author
Baumel, Amit
Venue
Translational Behavioral Medicine
Published
2018-02-17
Volume
8
Issue
5
Pages
793-798
ISSN
  • 1613-9860 (ISSN-L)
  • 1869-6716
OpenAlex
W2790152727
Cited by
128
References
32
Citations by year
2026: 6 · 2025: 8 · 2024: 14 · 2023: 8 · 2022: 6 · 2021: 14 · 2020: 59 · 2019: 10 · 2018: 3
FWCI
27.15
Type
journal article
Language
en
Open access
closed
Locations
  • Translational Behavioral Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
user adherence, intervention design, persuasive design, behaviour change techniques, therapeutic relationship, usability, user engagement, online intervention, real-world applications
MeSH terms
Therapeutic Alliance, Adult, Behavior Therapy, Mental Disorders, Humans, Outcome and Process Assessment, Health Care, Patient Compliance, Persuasive Communication, Telemedicine, Internet

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