3 research outputs found
Exploring the Design of mHealth Systems for Health Behavior Change using Mobile Biosensors
A person’s health behavior plays a vital role in mitigating their risk of disease and promoting positive health outcomes. In recent years, mHealth systems have emerged to offer novel approaches for encouraging and supporting users in changing their health behavior. Mobile biosensors represent a promising technology in this regard; that is, sensors that collect physiological data (e.g., heart rate, respiration, skin conductance) that individuals wear, carry, or access during their normal daily activities. mHealth system designers have started to use the health information from physiological data to deliver behavior-change interventions. However, little research provides guidance about how one can design mHealth systems to use mobile biosensors for health behavior change. In order to address this research gap, we conducted an exploratory study. Following a hybrid approach that combines deductive and inductive reasoning, we integrated a body of fragmented literature and conducted 30 semi-structured interviews with mHealth stakeholders. From this study, we developed a theoretical framework and six general design guidelines that shed light on the theoretical pathways for how the mHealth interface can facilitate behavior change and provide practical design considerations
Co-design in mHealth Systems Development: Insights From a Systematic Literature Review
Mobile health (mHealth) systems hold great potential for supporting users in self-managing disease and engaging in a healthier life. However, given the mobile context and the multiple factors that affect a person’s health, designing mHealth systems involves much complexity and a range of pitfalls. To overcome these pitfalls, scholars have called on system designers to employ a co-design approach; that is, to involve stakeholders in all phases of the design process. However, the literature on how, when, and why designers use co-design in mHealth remains scant. To address this gap, we systematically reviewed 61 studies that co-designed mHealth systems. Our results show that co-designing mHealth systems constitutes a fragmented and rapidly evolving research field with only limited overlaps and a strong focus on the early design phases (i.e., pre-design, generative). Thereby, the co-designed artifacts cover various application contexts in disease management (e.g., heart disease, diabetes) and health promotion (e.g., physical activity, nutrition) and a diverse group of involved users, healthcare professionals, and system designers. Finally, guided by Sanders and Stappers’ (2014) co-design framework, we provide a concise overview of the most widely used methods in the different co-design phases
Using Co-design in Mobile Health System Development: A Qualitative Study With Experts in Co-design and Mobile Health System Development
BackgroundThe proliferation of mobile devices has enabled new ways of delivering health services through mobile health systems. Researchers and practitioners emphasize that the design of such systems is a complex endeavor with various pitfalls, including limited stakeholder involvement in design processes and the lack of integration into existing system landscapes. Co-design is an approach used to address these pitfalls. By recognizing users as experts of their own experience, co-design directly involves users in the design process and provides them an active role in knowledge development, idea generation, and concept development.
ObjectiveDespite the existence of a rich body of literature on co-design methodologies, limited research exists to guide the co-design of mobile health (mHealth) systems. This study aims to contextualize an existing co-design framework for mHealth applications and construct guidelines to address common challenges of co-designing mHealth systems.
MethodsTapping into the knowledge and experience of experts in co-design and mHealth systems development, we conducted an exploratory qualitative study consisting of 16 semistructured interviews. Thereby, a constructivist ontological position was adopted while acknowledging the socially constructed nature of reality in mHealth system development. Purposive sampling across web-based platforms (eg, Google Scholar and ResearchGate) and publications by authors with co-design experience in mHealth were used to recruit co-design method experts (n=8) and mHealth system developers (n=8). Data were analyzed using thematic analysis along with our objectives of contextualizing the co-design framework and constructing guidelines for applying co-design to mHealth systems development.
ResultsThe contextualized framework captures important considerations of the mHealth context, including dedicated prototyping and implementation phases, and an emphasis on immersion in real-world contexts. In addition, 7 guidelines were constructed that directly pertain to mHealth: understanding stakeholder vulnerabilities and diversity, health behavior change, co-design facilitators, immersion in the mHealth ecosystem, postdesign advocates, health-specific evaluation criteria, and usage data and contextual research to understand impact.
ConclusionsSystem designers encounter unique challenges when engaging in mHealth systems development. The contextualized co-design framework and constructed guidelines have the potential to serve as a shared frame of reference to guide the co-design of mHealth systems and facilitate interdisciplinary collaboration at the nexus of information technology and health research