UC Berkeley

Background: Digital health is a broad, multidisciplinary field that uses technology to deliver and enhance health care. Within the digital health landscape, mobile health (mHealth) has become one of the largest sectors of digital health, with mHealth interventions accounting for a majority of digital health interventions. This dissertation focuses on mHealth interventions designed to provide clinical support for health behavior change to patients. Despite there being countless mHealth interventions targeting a wide variety of health behaviors and concerns, insufficient user engagement and low acceptance of mHealth continue to hinder the field’s growth. As such, a greater emphasis on understanding predictors of user engagement and individual acceptance of technology is necessary. Many of these predictors are influenced by socio-demographic factors, access to technology, digital literacy, health literacy, human resources, and environmental factors. Although one of the goals of mHealth has always been to expand access to care and reduce health disparities, at present, mHealth is often implemented inequitably and without sufficient consideration of their intended users’ circumstances. Thus, further research gathering the perspectives of low-income individuals, racial and ethnic minority populations, immigrant populations, those in low-resource service settings, and other underserved populations is necessary so mHealth interventions can be tailored to their needs and preferences.Methods: This dissertation contributes to equitable digital health design and implementation by exploring the needs and preferences of diverse individuals intended to benefit from mHealth interventions. Additionally, it provides key insights into creating engaging, helpful, and culturally responsive health behavior change content and designing accessible, inclusive, and user-friendly mobile platforms for individuals with varying technology familiarity and digital literacy. The first paper of this dissertation describes use of an implementation strategy designed to improve low-income ethnic minority patients’ engagement with and adherence to treatment within a public healthcare system. The implementation strategy consisted of a text messaging adjunct that sent patients mood rating messages, therapeutic content messages, and treatment and medication reminders to improve patient attendance at group therapy for depression. Descriptive statistics, inferential statistical tests, content analysis, and thematic analysis of qualitative feedback were conducted to explain the mechanisms of change behind this text messaging adjunct and determine what types of text messages were most effective at eliciting patient engagement. The second and third papers of this dissertation employ qualitative thematic analysis of interview data collected from key digital health stakeholder groups, with a focus on immigrant populations and racial and ethnic minority groups, to explore the utility, value, and appropriateness of mHealth interventions designed to provide clinical support for health behavior change. The second paper utilizes interview responses from intended users of mHealth to provide recommendations for designing and improving mHealth interventions that encourage healthy lifestyle behaviors and decrease the risk of chronic disease, while the third paper explores medical providers’ views of mHealth applications as they relate to patient health behavior change and provider workflow and responsibilities.Results: Across the three papers, individuals generally held positive views of mHealth programs designed to support health behavior change. mHealth interventions that delivered encouraging content and messages that uplifted mood, increased motivation, related to individuals’ health goals, provided directive content, offered suggestions and feedback, and connected individuals to support from providers or community were received most positively and assisted individuals in implementing health behavior changes. Provider recommendations were an important way for individuals to gain awareness of mHealth interventions that can benefit their health, and individuals were much more likely to initiate use of an mHealth intervention when it was recommended by their providers. Individuals appreciated interventions that provided highly tailored health plans that took into account their health needs, limitations, and available resources and supports. Across all three studies, inconvenient timing and frequency of text message or app notification delivery often lowered individual acceptance of mHealth. Other key barriers noted included insufficient personalization of health behavior change plans and health reminders, limited support for technology use, and lack of culturally responsive content and recommendations that aligned with cultural preferences and social circumstances.Conclusions: While a plethora of apps exist for various health issues, there are numerous barriers that continue to impede mHealth use and adoption. Rather than continuing to expand the digital health market, a key focus of the mHealth sector should be on improving existing apps and platforms to offer more inclusive content and features that address diverse users’ needs. The reach of mHealth can be furthered by developing more culturally relevant content, incorporating multilingual support, and partnering with medical providers, healthcare organizations, and insurance companies to increase awareness of mHealth programs. Platforms need to put forth evidence-based content and recommendations, maintain robust privacy and security measures, and improve timing and relevance of text messages and app notifications. Just-in-time adaptive interventions and machine learning approaches like reinforcement learning may be a useful way to optimize the content and delivery of text messages. Findings from this study contribute to our understanding of how to design mHealth programs to both supplement standard healthcare provision and act as standalone behavioral change interventions. This dissertation highlights the significance of including diverse users and medical providers in design, implementation, and evaluation processes in order to put forth equitable interventions that are widely applicable in different contexts and address the needs and preferences of users of varying levels of advantage, especially underserved populations. This dissertation contributes to the field’s understanding of how to utilize mHealth to expand access to health care and reduce health disparities.