ArticleProceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies2018
Is More Always Better?: Discovering Incentivized mHealth Intervention Engagement Related to Health Behavior Trends.
Article in Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Impact of Push Notifications on Physical Activity and Sodium Intake Among Patients with Hypertension: Microrandomized Trial of a Just-in-Time Adaptive Intervention.Journal of medical Internet research · 2026Trial
- Moving the dial on prenatal stress mechanisms of neurodevelopmental vulnerability to mental health problems: A personalized prevention proof of concept.Developmental psychobiology · 2021Trial
- A Social Media Intervention to Increase Caregiver Knowledge of Early Infant Communication: Multiple Methods Intervention Development and Pilot Study.JMIR pediatrics and parenting · 2026Article
- Engagement With a Relaxation-Based Mobile Health Intervention for Perioperative Anxiety: Prospective Longitudinal Cohort Mixed Methods Study.JMIR mHealth and uHealth · 2026Article
- Engagement of Users in Digital Health Applications: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Nonrandomized Open Trial of a Mindfulness- and Compassion-Based Selective Preventive Mobile Health Intervention for Forcibly Displaced People.Mindfulness · 2025Article
- Designing a Visual Analytics Tool to Support Data Analysis Tasks of Digital Mental Health Interventions: Case Study.JMIR human factors · 2025Article
- Artificial Intelligence-Based Mobile Phone Apps for Child Mental Health: Comprehensive Review and Content Analysis.JMIR mHealth and uHealth · 2025Review
- Exploring Generation Z and Young Millennials' Perspectives of a Spiritual Self-Care App and Their Spiritual Identity (Skylight): Qualitative Semistructured Interview Study.JMIR formative research · 2023Article
- Identifying Design Opportunities for Adaptive mHealth Interventions That Target General Well-Being: Interview Study With Informal Care Partners.JMIR formative research · 2023Article
- An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study.Journal of medical Internet research · 2023Article
- A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training.Information processing & management · 2022Article
- Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series.JMIR mental health · 2022Article
- Review, Assess, Classify, and Evaluate (RACE): a framework for studying m-health apps and its application for opioid apps.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Active Use and Engagement in an mHealth Initiative Among Young Men With Obesity: Mixed Methods Study.JMIR formative research · 2022Article
- Estimating the impact of engagement with digital health interventions on patient outcomes in randomized trials.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study.JMIR mHealth and uHealth · 2021Observational
- An Iterative and Collaborative End-to-End Methodology Applied to Digital Mental Health.Frontiers in psychiatry · 2021Article
- SMART: Study protocol for a sequential multiple assignment randomized controlled trial to optimize weight loss management.Contemporary clinical trials · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Behavioral medicine is devoting increasing attention to the topic of participant engagement and its role in effective mobile health (mHealth) behavioral interventions. Several definitions of the term "engagement" have been proposed and discussed, especially in the context of digital health behavioral interventions. We consider that engagement refers to specific interaction and use patterns with the mHealth tools such as smartphone applications for intervention, whereas adherence refers to compliance with the directives of the health intervention, independent of the mHealth tools. Through our analysis of participant interaction and self-reported behavioral data in a college student health study with incentives, we demonstrate an example of measuring "effective engagement" as engagement behaviors that can be linked to the goals of the desired intervention. We demonstrate how clustering of one year of weekly health behavior self-reports generate four interpretable clusters related to participants' adherence to the desired health behaviors: healthy and steady, unhealthy and steady, decliners, and improvers. Based on the intervention goals of this study (health promotion and behavioral change), we show that not all app usage metrics are indicative of the desired outcomes that create effective engagement. As such, mHealth intervention design might consider eliciting not just more engagement or use overall, but rather, effective engagement defined by use patterns related to the desired behavioral outcome.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.