An Open-Source Privacy-Preserving Large-Scale Mobile Framework for Cardiovascular Health Monitoring and Intervention Planning With an Urban African American Population of Young Adults: User-Centered Design Approach

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are increasingly affecting younger populations, particularly African Americans in the southern United States. Access to preventive and therapeutic services, biological factors, and social determinants of health (ie, structural racism, resource limitation, residential segregation, and discriminatory practices) all combine to exacerbate health inequities and their resultant disparities in morbidity and mortality. These factors manifest early in life and have been shown to impact health trajectories into adulthood. Early detection of and intervention in emerging risk offers the best hope for preventing race-based differences in adult diseases. However, young-adult populations are notoriously difficult to recruit and retain, often because of a lack of knowledge of personal risk and a low level of concern for long-term health outcomes.

OBJECTIVE

This study aims to develop a system design for the MOYO mobile platform. Further, we seek to addresses the challenge of primordial prevention in a young, at-risk population (ie, Southern-urban African Americans).

METHODS

Urban African Americans, aged 18 to 29 years (n=505), participated in a series of co-design sessions to develop MOYO prototypes (ie, HealthTech Events). During the sessions, participants were orientated to the issues of CVD risk health disparities and then tasked with wireframing prototype screens depicting app features that they considered desirable. All 297 prototype screens were subsequently analyzed using NVivo 12 (QSR International), a qualitative analysis software. Using the grounded theory approach, an open-coding method was applied to a subset of data, approximately 20% (5/25), or 5 complete prototypes, to identify the dominant themes among the prototypes. To ensure intercoder reliability, 2 research team members analyzed the same subset of data.

RESULTS

Overall, 9 dominant design requirements emerged from the qualitative analysis: customization, incentive motivation, social engagement, awareness, education, or recommendations, behavior tracking, location services, access to health professionals, data user agreements, and health assessment. This led to the development of a cross-platform app through an agile design process to collect standardized health surveys, narratives, geolocated pollution, weather, food desert exposure data, physical activity, social networks, and physiology through point-of-care devices. A Health Insurance Portability and Accountability Act-compliant cloud infrastructure was developed to collect, process, and review data, as well as generate alerts to allow automated signal processing and machine learning on the data to produce critical alerts. Integration with wearables and electronic health records via fast health care interoperability resources was implemented.

CONCLUSIONS

The MOYO mobile platform provides a comprehensive health and exposure monitoring system that allows for a broad range of compliance, from passive background monitoring to active self-reporting. These study findings support the notion that African Americans should be meaningfully involved in designing technologies that are developed to improve CVD outcomes in African American communities.

Preventing Cardiovascular Disease Among Urban African Americans With a Mobile Health App (the MOYO App): Protocol for a Usability Study

BACKGROUND

Cardiovascular disease (CVD) disparities are a particularly devastating manifestation of health inequity. Despite advancements in prevention and treatment, CVD is still the leading cause of death in the United States. Additionally, research indicates that African American (AA) and other ethnic-minority populations are affected by CVD at earlier ages than white Americans. Given that AAs are the fastest-growing population of smartphone owners and users, mobile health (mHealth) technologies offer the unparalleled potential to prevent or improve self-management of chronic disease among this population.

OBJECTIVE

To address the unmet need for culturally tailored primordial prevention CVD-focused mHealth interventions, the MOYO app was cocreated with the involvement of young people from this priority community. The overall project aims to develop and evaluate the effectiveness of a novel smartphone app designed to reduce CVD risk factors among urban-AAs, 18-29 years of age.

METHODS

The theoretical underpinning will combine the principles of community-based participatory research and the agile software development framework. The primary outcome goals of the study will be to determine the usability, acceptability, and functionality of the MOYO app, and to build a cloud-based data collection infrastructure suitable for digital epidemiology in a disparity population. Changes in health-related parameters over a 24-week period as determined by both passive (eg, physical activity levels, sleep duration, social networking) and active (eg, use of mood measures, surveys, uploading pictures of meals and blood pressure readings) measures will be the secondary outcome. Participants will be recruited from a majority AA "large city" school district, 2 historically black colleges or universities, and 1 urban undergraduate college. Following baseline screening for inclusion (administered in person), participants will receive the beta version of the MOYO app. Participants will be monitored during a 24-week pilot period. Analyses of varying data including social network dynamics, standard metrics of activity, percentage of time away from a given radius of home, circadian rhythm metrics, and proxies for sleep will be performed. Together with external variables (eg, weather, pollution, and socioeconomic indicators such as food access), these metrics will be used to train machine-learning frameworks to regress them on the self-reported quality of life indicators.

RESULTS

This 5-year study (2015-2020) is currently in the implementation phase. We believe that MOYO can build upon findings of classical epidemiology and longitudinal studies like the Jackson Heart Study by adding greater granularity to our knowledge of the exposures and behaviors that affect health and disease, and creating a channel for outreach capable of launching interventions, clinical trials, and enhancements of health literacy.

CONCLUSIONS

The results of this pilot will provide valuable information about community cocreation of mHealth programs, efficacious design features, and essential infrastructure for digital epidemiology among young AA adults.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/16699.

Emerging Issues of Intelligent Assistive Technology Use Among People With Dementia and Their Caregivers: A U.S. Perspective

The increasing number of older adults with cognitive deficits, including dementia, poses a major challenge for public health in the United States. At the same time, the limited number of informal and professional caregivers available to support this rapidly growing population is of mounting concern. Not only does population aging limit the number of potential caregivers, but extant caregivers often lack skills to provide quality care. The integration of intelligent assistive technologies (IAT), including devices, robotics and sensors in many forms, into eldercare, may offer opportunities to reduce caregiver burden and enhance healthcare services while improving the quality of life among older adults with mild to severe cognitive deficits. However, many caregivers and their care recipients lack access to these technologies. The reasons for this reduced access are multifactorial, including the digital divide, sociocultural factors, and technological literacy. This mini review investigates the emerging use of IAT available to caregivers and older adults with cognitive deficits and explores the challenges in socioeconomic status and technological literacy as well as ethical and legal implications that should be considered in the design and development of IAT for older adults with cognitive deficits. Drawing from existing literature, it will suggest frameworks for design and adoption aimed at increased and equitable access for this vulnerable population.

Understanding the Acceptance of an eHealth Technology in the Early Stages of Development: An End-User Walkthrough Approach and Two Case Studies

Background

Studies that focus on the acceptance of an electronic health (eHealth) technology generally make use of surveys. However, results of such studies hold little value for a redesign, as they focus only on quantifying end-user appreciation of general factors (eg, perceived usefulness).

Objective

We present a method for understanding end-user acceptance of an eHealth technology, early in the development process: The eHealth End-User Walkthrough.

Methods

During a walkthrough, a participant is guided by using the technology via a scenario, a persona, and a low-fidelity protoype. A participant is questioned about factors that may affect acceptance during and after the demonstration. We show the value of the method via two case studies.

Results

During the case studies, participants commented on whether they intend to use a technology and why they would (not) use its main features. They also provided redesign advice or input for additional functions. Finally, the sessions provide guidance for the generation of business models and implementation plans.

Conclusions

The eHealth End-User Walkthrough can aid design teams in understanding the acceptance of their eHealth application in a very early stage of the design process. Consequently, it can prevent a mismatch between technology and end-users’ needs, wishes and context.

Understanding messaging preferences to inform development of mobile goal-directed behavioral interventions

Background

Mobile messaging interventions have been shown to improve outcomes across a number of mental health and health-related conditions, but there are still significant gaps in our knowledge of how to construct and deliver the most effective brief messaging interventions. Little is known about the ways in which subtle linguistic variations in message content can affect user receptivity and preferences.

Objective

The aim of this study was to determine whether any global messaging preferences existed for different types of language content, and how certain characteristics moderate those preferences, in an effort to inform the development of mobile messaging interventions.

Methods

This study examined user preferences for messages within 22 content groupings. Groupings were presented online in dyads of short messages that were identical in their subject matter, but structurally or linguistically varied. Participants were 277 individuals residing in the United States who were recruited and compensated through Amazon’s Mechanical Turk (MTurk) system. Participants were instructed to select the message in each dyad that they would prefer to receive to help them achieve a personal goal of their choosing.

Results

Results indicate global preferences of more than 75% of subjects for certain types of messages, such as those that were grammatically correct, free of textese, benefit-oriented, polite, nonaggressive, and directive as opposed to passive, among others. For several classes of messages, few or no clear global preferences were found. There were few personality- and trait-based moderators of message preferences, but subtle manipulations of message structure, such as changing “Try to…” to “You might want to try to…” affected message choice.

Conclusions

The results indicate that individuals are sensitive to variations in the linguistic content of text messages designed to help them achieve a personal goal and, in some cases, have clear preferences for one type of message over another. Global preferences were indicated for messages that contained accurate spelling and grammar, as well as messages that emphasize the positive over the negative. Research implications and a guide for developing short messages for goal-directed behaviors are presented in this paper.