Literature DB >> 26888421

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, Mohamed Khadra4, Ralph Nanan5,6.   

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.

Entities:  

Keywords:  Incentive; diabetes; mHealth; motivation; self care

Mesh:

Year:  2016        PMID: 26888421     DOI: 10.1177/1357633X15625539

Source DB:  PubMed          Journal:  J Telemed Telecare        ISSN: 1357-633X            Impact factor:   6.184


  17 in total

1.  Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications.

Authors:  Martina Vettoretti; Giacomo Cappon; Giada Acciaroli; Andrea Facchinetti; Giovanni Sparacino
Journal:  J Diabetes Sci Technol       Date:  2018-05-22

2.  Self-Monitoring Utilization Patterns Among Individuals in an Incentivized Program for Healthy Behaviors.

Authors:  Ju Young Kim; Nathan E Wineinger; Michael Taitel; Jennifer M Radin; Osayi Akinbosoye; Jenny Jiang; Nima Nikzad; Gregory Orr; Eric Topol; Steve Steinhubl
Journal:  J Med Internet Res       Date:  2016-11-17       Impact factor: 5.428

3.  Feasibility Study of a Mobile Health Intervention for Older Adults on Oral Anticoagulation Therapy.

Authors:  Jung-Ah Lee; Lorraine S Evangelista; Alison A Moore; Vanessa Juth; Yuqing Guo; Sergio Gago-Masague; Carolyn G Lem; Michelle Nguyen; Parmis Khatibi; Mark Baje; Alpesh N Amin
Journal:  Gerontol Geriatr Med       Date:  2016-10-07

4.  Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy.

Authors:  Yuan Wu; Xun Yao; Giacomo Vespasiani; Antonio Nicolucci; Yajie Dong; Joey Kwong; Ling Li; Xin Sun; Haoming Tian; Sheyu Li
Journal:  JMIR Mhealth Uhealth       Date:  2017-03-14       Impact factor: 4.773

5.  Effectiveness of fixed-site high-frequency transcutaneous electrical nerve stimulation in chronic pain: a large-scale, observational study.

Authors:  Xuan Kong; Shai N Gozani
Journal:  J Pain Res       Date:  2018-04-09       Impact factor: 3.133

6.  Interventional study to improve diabetic guidelines adherence using mobile health (m-Health) technology in Lahore, Pakistan.

Authors:  Noreen Rahat Hashmi; Shazad Ali Khan
Journal:  BMJ Open       Date:  2018-05-31       Impact factor: 2.692

7.  Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews.

Authors:  Youfa Wang; Jungwon Min; Jacob Khuri; Hong Xue; Bo Xie; Leonard A Kaminsky; Lawrence J Cheskin
Journal:  JMIR Mhealth Uhealth       Date:  2020-04-28       Impact factor: 4.773

8.  Effective behavioral intervention strategies using mobile health applications for chronic disease management: a systematic review.

Authors:  Jung-Ah Lee; Mona Choi; Sang A Lee; Natalie Jiang
Journal:  BMC Med Inform Decis Mak       Date:  2018-02-20       Impact factor: 2.796

9.  Use of mobile health applications for health-promoting behavior among individuals with chronic medical conditions.

Authors:  Asos Mahmood; Satish Kedia; David K Wyant; SangNam Ahn; Soumitra S Bhuyan
Journal:  Digit Health       Date:  2019-10-10

10.  Foot thermometry with mHeath-based supplementation to prevent diabetic foot ulcers: A randomized controlled trial.

Authors:  Maria Lazo-Porras; Antonio Bernabe-Ortiz; Alvaro Taype-Rondan; Robert H Gilman; German Malaga; Helard Manrique; Luis Neyra; Jorge Calderon; Miguel Pinto; David G Armstrong; Victor M Montori; J Jaime Miranda
Journal:  Wellcome Open Res       Date:  2020-08-28
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