Technology-based health promotion: Current state and perspectives in emerging gig economy

Abstract

It has been a decade since smartphone application stores started allowing developers to post their own applications. This paper presents a narrative review on the state-of-the-art and the future of technology used by researchers in the field of mobile health promotion. Researchers build high cost, complex systems with the purpose of promoting health and collecting data. These systems promote health by using a feedback component that "educates" the subject. Other researchers instead use platforms which provide them with data collected by others, which allows for no communication with subjects, but may be cheaper than building a system to collect the data. This second type of systems cannot be used directly for health promotion. However, both types of systems are relevant to the field of health promotion, because they are precursors to a third type of systems that are emerging, the gig economy systems for mobile health data collection, which are low cost, globally available, and provide limited communication with subjects. If such systems evolve to include more channels for communication with the data-generating subjects, and also bring developers into the economy, they may eventually revolutionize the field of mobile health promotion and data collection by giving researchers new capabilities, such as the ability to replicate existing health promotion campaigns with the click of a button and the appropriate licenses. In this paper we present a review of state-of-the-art systems for mobile health promotion and data collection and a model for what these systems may look like in the future.

Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review

“… 83 , 93 Lastly, many digital public interventions were said not to be guided by known theory and lack sufficient documentation of their processes, making them difficult to replicate. 43 , 94 …”

A Digital Health Intervention for Weight Management for Latino Families Living in Rural Communities: Perspectives and Lessons Learned During Development

“…As the third step of the development process, the RT team conducted a review of the literature on the application of digital technologies in health promotion and disease management from the perspectives of health promotion practices and computer engineering. Furthermore, the team conducted a state-of-the-art review on modern health data collection and sharing approaches in the context of an emerging gig economy [ 23 ]. The goal was to understand the progress, best practices, and challenges in digital health intervention and provide guidance in designing a theory-driven RT intervention.…”

“…Research indicates that exposure is extended by (1) minimizing time-consuming data input and output activities, (2) automating delivery of task reminders and reinforced messages, (3) providing frequent and real-time feedback to intervention participants and staff, (4) offering the ability to tailor the intervention based on baseline information as well as ongoing changes of the behavior targets and the environment, and (5) leveraging the interactive capabilities of mHealth devices to incorporate BCTs [ 10 , 24 ]. By contrast, lack of structured social interactions and social support was a noted weakness of current digital technologies [ 23 , 24 ]. For example, studies have demonstrated that incorporating IP contact enhanced program compliance and participant engagement in mHealth interventions [ 25 , 26 ].…”

“…Applying the principles of a user-centered approach has contributed to increases in acceptance and usability of digital technology-based interventions [ 35 , 36 ]. From a computer engineering perspective, the RT team concluded that a blended approach, combining digital technologies with limited human high-touch, may be most efficacious to advance the field of digital health interventions while awaiting the next generation of artificial intelligence-based solutions to address weaknesses associated with inability to provide personalized social support [ 23 , 37 ].…”

“…However, the use of tablets, wearable trackers, and other technologies for digital health interventions introduces additional complexity for participant’s data security and privacy [ 55 ]. One should carefully evaluate security issues, conforming to rules and regulations in the settings where these interventions are implemented [ 23 ]. Participants signed a consent form, which informs them about the heterogeneous RT environment and the type of data collected.…”