Examining diabetes management apps recommended from a Google search : content analysis

Background: The availability of smartphone health apps empowers people to manage their own health. Currently, there are over 300,000 health apps available in the market targeting a variety of user needs from weight loss to management of chronic conditions, with diabetes being the most commonly targe...

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Main Authors: Jimenez, Geronimo, Lum, Elaine, Car, Josip
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Article
Language:English
Published: 2019
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Online Access:https://hdl.handle.net/10356/85508
http://hdl.handle.net/10220/49235
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-855082020-11-01T05:30:26Z Examining diabetes management apps recommended from a Google search : content analysis Jimenez, Geronimo Lum, Elaine Car, Josip Lee Kong Chian School of Medicine (LKCMedicine) Centre for Population Health Sciences Chronic Diseases Diabetes Science::Medicine Background: The availability of smartphone health apps empowers people to manage their own health. Currently, there are over 300,000 health apps available in the market targeting a variety of user needs from weight loss to management of chronic conditions, with diabetes being the most commonly targeted condition. To date, health apps largely fall outside government regulation, and there are no official guidelines to help clinicians and patients in app selection. Patients commonly resort to the internet for suggestions on which diabetes app to use. Objective: The objective of this study was to investigate apps identified through a Google search and characterize these apps in terms of features that support diabetes management. Methods: We performed a Google search for the “best diabetes apps 2017” and explored the first 4 search results. We identified and compiled a list of the apps recommended in the returned search results, which were Web articles. Information about each app was extracted from the papers and corresponding app store descriptions. We examined the apps for the following diabetes management features: medication management, blood glucose self-management, physical activity, diet and nutrition, and weight management. Results: Overall, 26 apps were recommended in 4 papers. One app was listed in all 4 papers, and 3 apps appeared on 3 of the 4 lists. Apart from one paper, there were no explicit criteria to justify or explain the selection of apps. We found a wide variation in the type and the number of diabetes management features in the recommended apps. Five apps required payment to be used. Two-thirds of the apps had blood glucose management features, and less than half had medication management features. The most prevalent app features were nutrition or diet-related (19/24, 79%) and physical activity tracking (14/24, 58%). Conclusions: The ambiguity of app selection and the wide variability in key features of the apps recommended for diabetes management may pose difficulties for patients when selecting the most appropriate app. It is critical to involve patients, clinicians, relevant professional bodies, and policy makers to define the key features an app should have for it to be classified as a “diabetes management” app. The lessons learned here may be extrapolated for the development and recommendation of apps for the management of other chronic conditions. Published version 2019-07-10T02:33:15Z 2019-12-06T16:05:10Z 2019-07-10T02:33:15Z 2019-12-06T16:05:10Z 2019 Journal Article Jimenez, G., Lum, E., & Car, J. (2019). Examining diabetes management apps recommended from a Google search : content analysis. JMIR mHealth and uHealth, 7(1), e11848-. doi:10.2196/11848 1439-4456 https://hdl.handle.net/10356/85508 http://hdl.handle.net/10220/49235 10.2196/11848 en JMIR mHealth and uHealth © 2019 Geronimo Jimenez, Elaine Lum, Josip Car. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 16.01.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. 8 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Chronic Diseases
Diabetes
Science::Medicine
spellingShingle Chronic Diseases
Diabetes
Science::Medicine
Jimenez, Geronimo
Lum, Elaine
Car, Josip
Examining diabetes management apps recommended from a Google search : content analysis
description Background: The availability of smartphone health apps empowers people to manage their own health. Currently, there are over 300,000 health apps available in the market targeting a variety of user needs from weight loss to management of chronic conditions, with diabetes being the most commonly targeted condition. To date, health apps largely fall outside government regulation, and there are no official guidelines to help clinicians and patients in app selection. Patients commonly resort to the internet for suggestions on which diabetes app to use. Objective: The objective of this study was to investigate apps identified through a Google search and characterize these apps in terms of features that support diabetes management. Methods: We performed a Google search for the “best diabetes apps 2017” and explored the first 4 search results. We identified and compiled a list of the apps recommended in the returned search results, which were Web articles. Information about each app was extracted from the papers and corresponding app store descriptions. We examined the apps for the following diabetes management features: medication management, blood glucose self-management, physical activity, diet and nutrition, and weight management. Results: Overall, 26 apps were recommended in 4 papers. One app was listed in all 4 papers, and 3 apps appeared on 3 of the 4 lists. Apart from one paper, there were no explicit criteria to justify or explain the selection of apps. We found a wide variation in the type and the number of diabetes management features in the recommended apps. Five apps required payment to be used. Two-thirds of the apps had blood glucose management features, and less than half had medication management features. The most prevalent app features were nutrition or diet-related (19/24, 79%) and physical activity tracking (14/24, 58%). Conclusions: The ambiguity of app selection and the wide variability in key features of the apps recommended for diabetes management may pose difficulties for patients when selecting the most appropriate app. It is critical to involve patients, clinicians, relevant professional bodies, and policy makers to define the key features an app should have for it to be classified as a “diabetes management” app. The lessons learned here may be extrapolated for the development and recommendation of apps for the management of other chronic conditions.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Jimenez, Geronimo
Lum, Elaine
Car, Josip
format Article
author Jimenez, Geronimo
Lum, Elaine
Car, Josip
author_sort Jimenez, Geronimo
title Examining diabetes management apps recommended from a Google search : content analysis
title_short Examining diabetes management apps recommended from a Google search : content analysis
title_full Examining diabetes management apps recommended from a Google search : content analysis
title_fullStr Examining diabetes management apps recommended from a Google search : content analysis
title_full_unstemmed Examining diabetes management apps recommended from a Google search : content analysis
title_sort examining diabetes management apps recommended from a google search : content analysis
publishDate 2019
url https://hdl.handle.net/10356/85508
http://hdl.handle.net/10220/49235
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