ArticleJournal of medical Internet research2020
Identifying Mobile Health Engagement Stages: Interviews and Observations for Developing Brief Message Content.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 12 citations in OpenAlex.
- Advancing foundational models in digital health technology adoption: A systematic literature review of multidisciplinary factors.PLOS digital health · 2026Article
- Engagement in mHealth-Prompted Self-Measured Blood Pressure Monitoring Among Participants Recruited From a Safety-Net Emergency Department: Secondary Analysis of the Reach Out Trial.JMIR mHealth and uHealth · 2024Article
- Understanding Whether and How a Digital Health Intervention Improves Transition Care for Emerging Adults Living With Type 1 Diabetes: Protocol for a Mixed Methods Realist Evaluation.JMIR research protocols · 2023Article
- Mobile health for cardiovascular risk management after cardiac surgery: results of a sub-analysis of The Box 2.0 study.European heart journal. Digital health · 2023Article
- Development of clinical-guideline-based mobile application and its effect on head CT scan utilization in neurology and neurosurgery departments.BMC medical informatics and decision making · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInterest in mobile health (mHealth) has increased recently, and research suggests that mHealth devices can enhance end-user engagement, especially when used in conjunction with brief message content.
objectiveThis research aims to explore the stages of engagement framework for mHealth devices and develop a method to generate brief message content to promote sustained user engagement. This study uses the framework by O'Brien and Toms as a point of departure, where engagement is defined as the uptake or the use of an mHealth device. The framework is a linear repeatable process, including point of engagement, period of engagement, disengagement, and re-engagement. Each stage is characterized by attributes related to a person's technology experience. Although the literature has identified stages of engagement for health-related technology, few studies explore mHealth engagement. Furthermore, little research has determined a method for creating brief message content at each stage in this engagement journey.
methodsInterviews and observations from 19 participants who used mHealth technologies (apps, devices, or wellness websites) in a solo capacity were recruited for sample group 1. In sample group 2, interviews, and observations from 25 participants using mHealth technologies in a group capacity through the Global Corporate Challenge were used. These samples were investigated at 3 time points in both research contexts. The results underwent deductive-inductive thematic analysis for the engagement stages' framework and attributes.
resultsIn addition to the 4 stages identified by O'Brien and Toms, 2 additional stages, self-management and limited engagement, were identified. Self-management captures where users had disengaged from their technology but were still engaged with their health activity. Limited engagement captures where group mHealth users had minimal interaction with their mHealth technology but continued to engage in a group fitness activity. The results revealed that mHealth engagement stages were nonlinear and embedded in a wider engagement context and that each stage was characterized by a combination of 49 attributes that could be organized into 8 themes. Themes documented the total user experience and included technology usability, technology features, technology aesthetics, use motivations, health awareness, goal setting, social support, and interruptions. Different themes were found to have more relevance at different engagement stages. Knowing themes and attributes at all engagement stages allows technology developers and health care professionals to generate relevant brief message content informed by a person-centered approach.
conclusionsThis research extends an existing engagement stages framework and identifies attributes and themes relevant to mHealth technology users' total user experience and incorporates concepts derived from health, business studies, and information systems literature. In addition, we offer a practical 5-step process based on a person-centered approach to develop mHealth technology brief message content for sustained engagement.
Indexed as
Identifiers
What OpenQuestion holds
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.