Designing Disease-Specific mHealth Apps for Clinical Value
Open accessAbstract
mHealth apps for patient use are promising but continue to face a plateau in usage. Current apps work for a limited segment of the patient population, i.e., those who enjoy tracking for intrinsic rewards. There are many opportunities to support patient care in between health care provider visits that are not currently being met for many diseases and patient types (personas). This is an area of great potential growth for mHealth apps and could contribute greatly to patient health and wellness. In this chapter, we propose a framework for how to think about the between-visit needs of patients that would motivate continued use of mhealth apps. We view the app design process from the following perspectives: 1) disease-specific needs, 2) non-disease specific needs, 3) behavioral theoretical aspects of app usage and 4) app-intrinsic usage motivators. Myasthenia gravis serves as the use case for illustrating these perspectives and how to use them in designing a disease-specific mHealth app.
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The system uses context-triggered alerts only when risk thresholds are crossed, minimizing unnecessary interruptions to prevent notification fatigue.
“To prevent notification fatigue a known barrier to long-term engagement in mHealth programs the system uses contexttriggered alerts only when risk thresholds are crossed, minimizing unnecessary interruptions (Keshavjee et al., 2022; Park et al., 2023).”
From SiKurang: Development and Field Evaluation of an Offline-First mHealth System for Community-Based Stunting Risk Detection and Counselling in Low-Connectivity Primary Care Settings (2026) · cites this paper as Keshavjee et al., 2022
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- Authors
- Keshavjee, K., Johnston-Jewell, D., Lee, B., & Kyba, R.
- Corresponding author
- Keshavjee, Karim
- ORCID
- Keshavjee, Karim
- Venue
- Smart and Pervasive Healthcare
- Publisher
- IntechOpen
- Published
- 2022-01-12
- OpenAlex
- W4229019078
- Cited by
- 6
- References
- 63
- Citations by year
- 2025: 2 · 2023: 4
- FWCI
- 10.57
- Type
- book chapter
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- IntechOpen eBooks (publishedVersion, cc-by)
- Contact-less Assessment of In-vivo Body Signals Using Microwave Doppler Radar (InTech) (submittedVersion, cc-by)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- mobile health apps, patient motivation, myasthenia gravis, behavioral theory, intrinsic motivation
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