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A systematic review on incentive-driven mobile health technology: As used in diabetes management
Michael de Ridder1,2, Jinman Kim1,2,3, Yan Jing1,2
11 Personal Digital Assistant, Biomedical and Multimedia Information Technology (BMIT) Research Group, The University of Sydney, Australia.
Abstract:
Introduction Mobile health (mHealth) technologies have been shown to improve self-management of chronic diseases, such as diabetes. However, mHealth tools, e.g. apps, often have low rates of retention, eroding their potential benefits. Using incentives is a common mechanism for engaging, empowering and retaining patients that is applied by mHealth tools. We conducted a systematic review aiming to categorize the different types of incentive mechanisms employed in mHealth tools for diabetes management, which we defined as incentive-driven technologies (IDTs). As an auxiliary aim, we also analyzed barriers to adoption of IDTs. Methods Literature published in English between January 2008-August 2014 was identified through searching leading publishers and indexing databases: IEEE, Springer, Science Direct, NCBI, ACM, Wiley and Google Scholar. Results A total of 42 articles were selected. Of these, 34 presented mHealth tools with IDT mechanisms; Education was the most common mechanism ( n = 21), followed by Reminder ( n = 11), Feedback ( n = 10), Social ( n = 8), Alert ( n = 5), Gamification ( n = 3), and Financial ( n = 2). Many of these contained more than one IDT ( n = 19). The remaining eight articles, from which we defined barriers for adoption, were review papers and a qualitative study of focus groups and interviews. Discussion While mHealth technologies have advanced over the last five years, the core IDT mechanisms have remained consistent. Instead, IDT mechanisms have evolved with the advances in technology, such as moving from manual to automatic content delivery and personalization of content. Conclusion We defined the concept of IDT to be core features designed to act as motivating mechanisms for retaining and empowering users. We then identified seven core IDT mechanisms that are used by mHealth tools for diabetes management and classified 34 articles into these categories.
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