ArticleJournal of biomedical informatics2019
A multi-faceted approach to characterizing user behavior and experience in a digital mental health intervention.
Article in Journal of biomedical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- User Experiences of and Preferences for Self-Guided Digital Interventions for the Treatment of Mild to Moderate Eating Disorders: Systematic Review and Metasynthesis.JMIR mental health · 2025Pooled it
- Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Patient experiences with technology enabled care across healthcare settings- a systematic review.BMC health services research · 2020Pooled it
- Identifying Content-Based Engagement Patterns in a Smoking Cessation Website and Associations With User Characteristics and Cessation Outcomes: A Sequence and Cluster Analysis.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2021Trial
- Artificial Intelligence Discontinuation Effects (AI-DICE): An Emerging Phenomenon in Mental Health Applications.JMIR AI · 2026Article
- Exploring digital health user engagement: General app usage patterns from a clinical trial with the mLab App.PLOS digital health · 2026Article
- Effectiveness of a guided mobile app intervention for depression and anxiety in university students (PROMES-U study): protocol of a multicenter randomized controlled trial.BMC public health · 2025Article
- Designing a Visual Analytics Tool to Support Data Analysis Tasks of Digital Mental Health Interventions: Case Study.JMIR human factors · 2025Article
- Behavioral engagement patterns and psychosocial outcomes in web-based interpretation bias training for anxiety.PLOS digital health · 2025Article
- Digital Mental Health Interventions for Adolescents and Young People: Evaluating Efficacy and Accessibility.Cureus · 2025Review
- Engagement With an Internet-Administered, Guided, Low-Intensity Cognitive Behavioral Therapy Intervention for Parents of Children Treated for Cancer: Analysis of Log-Data From the ENGAGE Feasibility Trial.JMIR formative research · 2025Article
- Development of a supportive mHealth device for persons with schizophrenia spectrum disorders (KisoLightFrontiers in psychology · 2025Article
- User Engagement in an Online Digital Health Intervention to Promote Problem Solving.Interacting with computers · 2024Article
- The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder.Internet interventions · 2024Article
- User-Centered Development of a Mobile App to Assess the Quality of Life of Patients With Cancer: Iterative Investigation and Usability Testing.JMIR cancer · 2023Article
- Human Support in App-Based Cognitive Behavioral Therapies for Emotional Disorders: Scoping Review.Journal of medical Internet research · 2022Article
- Identifying App-Based Meditation Habits and the Associated Mental Health Benefits: Longitudinal Observational Study.Journal of medical Internet research · 2021Observational
- Mental Health and the Perceived Usability of Digital Mental Health Tools Among Essential Workers and People Unemployed Due to COVID-19: Cross-sectional Survey Study.JMIR mental health · 2021Article
- Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement.NPJ digital medicine · 2021Review
- Engagement With a Behavior Change App for Alcohol Reduction: Data Visualization for Longitudinal Observational Study.Journal of medical Internet research · 2020Observational
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Digital interventions offer great promise for supporting health-related behavior change. However, there is much that we have yet to learn about how people respond to them. In this study, we present a novel mixed-methods approach to analysis of the complex and rich data that digital interventions collect. We perform secondary analysis of IntelliCare, an intervention in which participants are able to try 14 different mental health apps over the course of eight weeks. The goal of our analysis is to characterize users' app use behavior and experiences, and is rooted in theoretical conceptualizations of engagement as both usage and user experience. In the first aim, we employ cluster analysis to identify subgroups of participants that share similarities in terms of the frequency of their usage of particular apps, and then employ other engagement measures to compare the clusters. We identified four clusters with different app usage patterns: Low Usage, High Usage, Daily Feats Users, and Day to Day users. Each cluster was distinguished by its overall frequency of app use, or the main app that participants used. In the second aim, we developed a computer-assisted text analysis and visualization method - message highlighting - to facilitate comparison of the clusters. Last, we performed a qualitative analysis using participant messages to better understand the mechanisms of change and usability of salient apps from the cluster analysis. Our novel approach, integrating text and visual analytics with more traditional qualitative analysis techniques, can be used to generate insights concerning the behavior and experience of users in digital health contexts, for subsequent personalization and to identify areas for improvement of intervention technologies.
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Registered trials
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