Literature DB >> 32357368

A systematic review of mobile health technologies to support self-management of concurrent diabetes and hypertension.

Wonchan Choi1, Shengang Wang1, Yura Lee2, Hyunkyoung Oh3, Zhi Zheng4.   

Abstract

OBJECTIVE: This article reports results from a systematic literature review of the current state of mobile health (mHealth) technologies that have the potential to support self-management for people with diabetes and hypertension. The review aims to (a) characterize mHealth technologies used or described in the mHealth literature and (b) summarize their effects on self-management for people with diabetes and hypertension from the clinical and technical standpoints.
MATERIALS AND METHODS: A systematic literature review was conducted following PRISMA guidelines. Online databases were searched in September 2018 to identify eligible studies for review that had been published since 2007, the start of the smartphone era. Data were extracted from included studies based on the PICOS framework.
RESULTS: Of the 11 studies included for in-depth review, 5 were clinical research examining patient health outcomes and 6 were technology-focused studies examining users' experiences with mHealth technologies under development. The most frequently used mHealth technology features involved self-management support (n = 11) followed by decision support (n = 6) and shared decision-making (n = 6). Most clinical studies reported benefits associated with mHealth interventions. These included reported improvements in objectively measured patient health outcomes (n = 3) and perceptual or behavioral outcomes (n = 4). DISCUSSION: Although most studies reported promising results in terms of the effects of mHealth interventions on patient health outcomes and experience, the strength of evidence was limited by the study designs.
CONCLUSION: More randomized clinical trials are needed to examine the promise and limitations of mHealth technologies as assistive tools to facilitate the self-management of highly prevalent comorbidity of chronic conditions, such as diabetes and hypertension.
© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  diabetes mellitus; hypertension; mHealth; mobile health; multiple chronic conditions

Mesh:

Year:  2020        PMID: 32357368      PMCID: PMC7647310          DOI: 10.1093/jamia/ocaa029

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  21 in total

1.  Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature.

Authors:  Sara Belle Donevant; Robin Dawson Estrada; Joan Marie Culley; Brian Habing; Swann Arp Adams
Journal:  J Am Med Inform Assoc       Date:  2018-10-01       Impact factor: 4.497

2.  A Pharmacist Telephone Intervention to Identify Adherence Barriers and Improve Adherence Among Nonadherent Patients with Comorbid Hypertension and Diabetes in a Medicare Advantage Plan.

Authors:  Susan M Abughosh; Xin Wang; Omar Serna; Chris Henges; Santhi Masilamani; Ekere James Essien; Nancy Chung; Marc Fleming
Journal:  J Manag Care Spec Pharm       Date:  2016-01

3.  Low-health literacy flashcards & mobile video reinforcement to improve medication adherence in patients on oral diabetes, heart failure, and hypertension medications.

Authors:  Denise L Yeung; Kristin S Alvarez; Marissa E Quinones; Christopher A Clark; George H Oliver; Carlos A Alvarez; Adeola O Jaiyeola
Journal:  J Am Pharm Assoc (2003)       Date:  2016-11-03

4.  The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration.

Authors:  Alessandro Liberati; Douglas G Altman; Jennifer Tetzlaff; Cynthia Mulrow; Peter C Gøtzsche; John P A Ioannidis; Mike Clarke; P J Devereaux; Jos Kleijnen; David Moher
Journal:  PLoS Med       Date:  2009-07-21       Impact factor: 11.069

5.  Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control.

Authors:  Charlene C Quinn; Michelle D Shardell; Michael L Terrin; Erik A Barr; Shoshana H Ballew; Ann L Gruber-Baldini
Journal:  Diabetes Care       Date:  2011-07-25       Impact factor: 19.112

Review 6.  Mobile health applications for the most prevalent conditions by the World Health Organization: review and analysis.

Authors:  Borja Martínez-Pérez; Isabel de la Torre-Díez; Miguel López-Coronado
Journal:  J Med Internet Res       Date:  2013-06-14       Impact factor: 5.428

Review 7.  Behavioral functionality of mobile apps in health interventions: a systematic review of the literature.

Authors:  Hannah E Payne; Cameron Lister; Joshua H West; Jay M Bernhardt
Journal:  JMIR Mhealth Uhealth       Date:  2015-02-26       Impact factor: 4.773

Review 8.  Do health information technology self-management interventions improve glycemic control in medically underserved adults with diabetes? A systematic review and meta-analysis.

Authors:  Elizabeth M Heitkemper; Lena Mamykina; Jasmine Travers; Arlene Smaldone
Journal:  J Am Med Inform Assoc       Date:  2017-09-01       Impact factor: 4.497

Review 9.  The use of mobile applications to support self-management for people with asthma: a systematic review of controlled studies to identify features associated with clinical effectiveness and adherence.

Authors:  Chi Yan Hui; Robert Walton; Brian McKinstry; Tracy Jackson; Richard Parker; Hilary Pinnock
Journal:  J Am Med Inform Assoc       Date:  2017-05-01       Impact factor: 4.497

10.  Lack of Adoption of a Mobile App to Support Patient Self-Management of Diabetes and Hypertension in a Federally Qualified Health Center: Interview Analysis of Staff and Patients in a Failed Randomized Trial.

Authors:  Kathleen Thies; Daren Anderson; Benjamin Cramer
Journal:  JMIR Hum Factors       Date:  2017-10-03
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  7 in total

1.  Estimating the impact of engagement with digital health interventions on patient outcomes in randomized trials.

Authors:  Lyndsay A Nelson; Andrew J Spieker; Lindsay S Mayberry; Candace McNaughton; Robert A Greevy
Journal:  J Am Med Inform Assoc       Date:  2021-12-28       Impact factor: 4.497

Review 2.  On-demand mobile health infrastructures to allow comprehensive remote atrial fibrillation and risk factor management through teleconsultation.

Authors:  Astrid N L Hermans; Rachel M J van der Velden; Monika Gawalko; Dominique V M Verhaert; Lien Desteghe; David Duncker; Martin Manninger; Hein Heidbuchel; Ron Pisters; Martin Hemels; Laurent Pison; Afzal Sohaib; Arian Sultan; Daniel Steven; Petra Wijtvliet; Robert Tieleman; Dhiraj Gupta; Dobromir Dobrev; Emma Svennberg; Harry J G M Crijns; Nikki A H A Pluymaekers; Jeroen M Hendriks; Dominik Linz
Journal:  Clin Cardiol       Date:  2020-10-08       Impact factor: 2.882

3.  Identification of the Most Suitable App to Support the Self-Management of Hypertension: Systematic Selection Approach and Qualitative Study.

Authors:  Tourkiah Alessa; Mark Hawley; Luc de Witte
Journal:  JMIR Mhealth Uhealth       Date:  2021-11-17       Impact factor: 4.773

Review 4.  Community Health Programs Delivered Through Information and Communications Technology in High-Income Countries: Scoping Review.

Authors:  Hannah Beks; Olivia King; Renee Clapham; Laura Alston; Kristen Glenister; Carol McKinstry; Claire Quilliam; Ian Wellwood; Catherine Williams; Anna Wong Shee
Journal:  J Med Internet Res       Date:  2022-03-09       Impact factor: 7.076

5.  Digital Patient Experience: Umbrella Systematic Review.

Authors:  Tingting Wang; Guido Giunti; Marijke Melles; Richard Goossens
Journal:  J Med Internet Res       Date:  2022-08-04       Impact factor: 7.076

Review 6.  Health information technology to improve care for people with multiple chronic conditions.

Authors:  Lipika Samal; Helen N Fu; Djibril S Camara; Jing Wang; Arlene S Bierman; David A Dorr
Journal:  Health Serv Res       Date:  2021-10-05       Impact factor: 3.734

7.  Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study.

Authors:  Eva-Maria Schomakers; Chantal Lidynia; Luisa Sophie Vervier; André Calero Valdez; Martina Ziefle
Journal:  JMIR Mhealth Uhealth       Date:  2022-01-18       Impact factor: 4.773

  7 in total

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