Dataset Information

Examining Diabetes Management Apps Recommended From a Google Search: Content Analysis.

ABSTRACT:

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.

SUBMITTER: Jimenez G

PROVIDER: S-EPMC6352016 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Examining Diabetes Management Apps Recommended From a Google Search: Content Analysis.

Jimenez Geronimo G Lum Elaine E Car Josip J

JMIR mHealth and uHealth 20190116 1

<h4>Background</h4>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 t ...[more]

PMID: 30303485

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Project description:BackgroundMobile health interventions are widely used for self-management of diabetes, which is one of the most burdensome noncommunicable chronic diseases worldwide. However, little is known about the distribution of characteristics and functions of in-store mobile apps for diabetes.ObjectiveThis study aimed to investigate the distribution of characteristics and functions of the in-store mobile apps for self-management of diabetes in the United States and China using a predefined functional taxonomy, which was developed and published in our previous study.MethodsWe identified apps by searching diabetes in English or Chinese in the Apple iTunes Store and Android Markets (both in the United States and China) and included apps for diabetes self-management. We examined the validity and reliability of the predefined functional taxonomy with 3 dimensions: clinical module, functional module, and potential risk. We then classified all functions in the included apps according to the predefined taxonomy and compared the differences in the features of these apps between the United States and China.ResultsWe included 171 mobile diabetes apps, with 133 from the United States and 38 from China. Apps from both countries faced the challenges of evidence-based information, proper risk assessment, and declaration, especially Chinese apps. More Chinese apps provide app-based communication functions (general communication: Chinese vs US apps, 39%, 15/38 vs 18.0%, 24/133; P=.006 and patient-clinician communication: Chinese vs US apps, 68%, 26/38 vs 6.0%, 8/133; P<.001), whereas more US apps provide the decision-making module (Chinese vs US apps, 0%, 0/38 vs 23.3%, 31/133; P=.001), which is a high-risk module. Both complication prevention (Chinese vs US apps, 8%, 3/38 vs 3.8%, 5/133; P=.50) and psychological care (Chinese vs US apps, 0%, 0/38 vs 0.8%, 1/133; P>.99) are neglected by the 2 countries.ConclusionsThe distribution of characteristics and functions of in-store mobile apps for diabetes self-management in the United States was different from China. The design of in-store diabetes apps needs to be monitored closely.

Project description:BackgroundMobile health has become a major vehicle of support for people living with diabetes. Accordingly, the availability of mobile apps for diabetes has been steadily increasing. Most of the previous reviews of diabetes apps have focused on the apps' features and their alignment with clinical guidelines. However, there is a lack of knowledge on the actual compliance of diabetes apps with privacy and data security guidelines.ObjectiveThe aim of this study was to assess the levels of privacy of mobile apps for diabetes to contribute to the raising of awareness of privacy issues for app users, developers, and governmental data protection regulators.MethodsWe developed a semiautomatic app search module capable of retrieving Android apps' privacy-related information, particularly the dangerous permissions required by apps, with the aim of analyzing privacy aspects related to diabetes apps. Following the research selection criteria, the original 882 apps were narrowed down to 497 apps that were included in the analysis.ResultsApproximately 60% of the analyzed diabetes apps requested potentially dangerous permissions, which pose a significant risk to users' data privacy. In addition, 28.4% (141/497) of the apps did not provide a website for their privacy policy. Moreover, it was found that 40.0% (199/497) of the apps contained advertising, and some apps that claimed not to contain advertisements actually did. Ninety-five percent of the apps were free, and those belonging to the "medical" and "health and fitness" categories were the most popular. However, app users do not always realize that the free apps' business model is largely based on advertising and, consequently, on sharing or selling their private data, either directly or indirectly, to unknown third parties.ConclusionsThe aforementioned findings confirm the necessity of educating patients and health care providers and raising their awareness regarding the privacy aspects of diabetes apps. Therefore, this research recommends properly and comprehensively training users, ensuring that governments and regulatory bodies enforce strict data protection laws, devising much tougher security policies and protocols in Android and in the Google Play Store, and implicating and supervising all stakeholders in the apps' development process.

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Project description:BACKGROUND:The emergence and advancement of mobile technologies offer a promising opportunity for people with diabetes to improve their self-management. Despite the proliferation of mobile apps, few studies have evaluated the apps that are available to the millions of people with diabetes in China. OBJECTIVE:This study aimed to conduct a systematic search of Chinese mobile apps for diabetes self-management and to evaluate their quality, functionality, and features by using validated rating scales. METHODS:A systematic search was conducted to identify Chinese apps for diabetes self-management in the four most popular Chinese language mobile app stores. Apps were included if they were designed for diabetes self-management and contained at least one of the following components: blood glucose management, dietary and physical activity management, medication taking, and prevention of diabetes-related comorbidities. Apps were excluded if they were unrelated to health, not in Chinese, or the targeted users are health care professionals. Apps meeting the identified inclusion criteria were downloaded and evaluated by a team of 5 raters. The quality, functionalities, and features of these apps were assessed by using the Mobile App Rating Scale (MARS), the IMS Institute for Healthcare Informatics Functionality score, and a checklist of self-management activities developed based on the Chinese diabetes self-management guideline, respectively. RESULTS:Among 2072 apps searched, 199 were eligible based on the inclusion criteria, and 67 apps were successfully downloaded for rating. These 67 apps had an average MARS score of 3.42 out of 5, and 76% (51/67) of the apps achieved an acceptable quality (MARS score >3.0). The scores for the four subdomains of MARS were 3.97 for functionality, 3.45 for aesthetics, 3.21 for information, and 3.07 for engagement. On average, reviewed apps applied five out of the 19 examined behavior change techniques, whereas the average score on the subjective quality for the potential impact on behavior change is 3 out of 5. In addition, the average score on IMS functionality was 6 out of 11. Functionalities in collecting, recording, and displaying data were mostly presented in the reviewed apps. Most of the apps were multifeatured with monitoring blood glucose and tracking lifestyle behaviors as common features, but some key self-management activities recommended by clinical guidelines, such as stress and emotional management, were rarely presented in these apps. CONCLUSIONS:The general quality of the reviewed apps for diabetes self-management is suboptimal, although the potential for improvement is significant. More attention needs to be paid to the engagement and information quality of these apps through co-design with researchers, public health practitioners, and consumers. There is also a need to promote the awareness of the public on the benefit and potential risks of utilizing health apps for self-management.

Project description:BackgroundPhysical inactivity is a major contributor to the development and persistence of chronic diseases. Mobile health apps that foster physical activity have the potential to assist in behavior change. However, the quality of the mobile health apps available in app stores is hard to assess for making informed decisions by end users and health care providers.ObjectiveThis study aimed at systematically reviewing and analyzing the content and quality of physical activity apps available in the 2 major app stores (Google Play and App Store) by using the German version of the Mobile App Rating Scale (MARS-G). Moreover, the privacy and security measures were assessed.MethodsA web crawler was used to systematically search for apps promoting physical activity in the Google Play store and App Store. Two independent raters used the MARS-G to assess app quality. Further, app characteristics, content and functions, and privacy and security measures were assessed. The correlation between user star ratings and MARS was calculated. Exploratory regression analysis was conducted to determine relevant predictors for the overall quality of physical activity apps.ResultsOf the 2231 identified apps, 312 met the inclusion criteria. The results indicated that the overall quality was moderate (mean 3.60 [SD 0.59], range 1-4.75). The scores of the subscales, that is, information (mean 3.24 [SD 0.56], range 1.17-4.4), engagement (mean 3.19 [SD 0.82], range 1.2-5), aesthetics (mean 3.65 [SD 0.79], range 1-5), and functionality (mean 4.35 [SD 0.58], range 1.88-5) were obtained. An efficacy study could not be identified for any of the included apps. The features of data security and privacy were mainly not applied. Average user ratings showed significant small correlations with the MARS ratings (r=0.22, 95% CI 0.08-0.35; P<.001). The amount of content and number of functions were predictive of the overall quality of these physical activity apps, whereas app store and price were not.ConclusionsApps for physical activity showed a broad range of quality ratings, with moderate overall quality ratings. Given the present privacy, security, and evidence concerns inherent to most rated apps, their medical use is questionable. There is a need for open-source databases of expert quality ratings to foster informed health care decisions by users and health care providers.

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Project description:BACKGROUND:Home blood pressure monitoring (HBPM) is one component of effective supported self-management, which may potentially be mediated by mobile apps. OBJECTIVE:The aim of this study was to identify the self-management features (HBPM and broader support strategies) offered by currently available apps and to determine the features associated with download frequency and user ratings. METHODS:We searched Google Play store, Apple App store, National Health Services Apps Library and myhealthapps.net (first search on February 1, 2018; updated August 18, 2018). We included high blood pressure apps available in the United Kingdom and extracted their features, number of downloads, and the average users' rating from the app stores. We mapped the features to the holistic Practical Reviews In Self-Management Support (PRISMS) taxonomy of self-management support. We employed a regression analysis to determine if any features were associated with download frequency or user rating. RESULTS:We included 151 apps. The 3 most common features were as follows: monitoring blood pressure (BP) and charting logs; lifestyle (exercise or dietary) advice; and providing information about hypertension. The other 11 components of the PRISMS taxonomy were rarely featured. There was little evidence to support associations between specific features and the download statistics and rating scores, with only 2 uncommon features achieving borderline significant associations. The presence of social support features, such as a forum, was weakly but significantly (R2=.04, P=.02) correlated with the number of downloads. Apps designed specifically for particular BP monitors/smart watches were weakly associated with a higher rating score (R2=.05, P<.001). Apps with more ratings were associated with more downloads (R2=.91, P<.001). CONCLUSIONS:The functionality of currently available apps is limited to logging BP, offering lifestyle advice, and providing information about hypertension. Future app development should consider broadening the remit to produce a system that can respond flexibly to the diversity of support that enables people to self-manage their hypertension.

Project description:BackgroundUsing a mobile app for self-management could make it easier for patients to get insight into their blood pressure patterns. However, little is known about the availability, quality, and features of mobile apps targeting blood pressure.ObjectiveThe goal of the research was to determine the availability, functionality, and quality of mobile apps that could be used for blood pressure monitoring purposes.MethodsA systematic app search was performed based on the standards for systematic reviews. We searched the Dutch official app stores for Android and iOS platforms using predefined keywords and included all English and Dutch mobile apps targeting blood pressure. Two independent assessors determined eligibility and quality of the apps using the 5-point Mobile App Rating Scale (MARS). Quality scores of the apps with and without 17 a priori selected characteristics were compared using independent sample t tests.ResultsA total of 184 apps (104 Android, 80 iOS) met the inclusion criteria. The mean overall MARS score was 2.63 (95% CI 2.55-2.71) for Android and 2.64 (95% CI 2.56-2.71) for iOS. The apps Bloeddruk (4.1) and AMICOMED BP (3.6) had the highest quality scores on the Android and iOS platforms, respectively. Of the app characteristics recorded, only pricing, in-app advertisements, and local data storage were not associated with the quality scores. In only 3.8% (7/184) of the apps, involvement of medical experts in its development was mentioned, whereas none of the apps was formally evaluated with results published in a peer-reviewed journal.ConclusionsThis study provides an overview of the best apps currently available in the app stores and important key features for self-management that can be used by health care providers and patients with hypertension to identify a suitable app targeting blood pressure monitoring. However, the majority of the apps targeting blood pressure monitoring were of poor quality. Therefore, it is important to involve medical experts in the developmental stage of health-related mobile apps to improve the quality of these apps.

Project description:BackgroundThe wide use of mobile health apps has created new possibilities in social anxiety education and treatment. However, the content and quality of social anxiety apps have been quite unclear, which makes it difficult for people to choose appropriate apps to use on smartphones and tablets.ObjectiveThis study aims to identify the psychoeducational social anxiety apps in the two most popular Australian app stores, report the descriptive and technical information provided in apps exclusively for social anxiety, evaluate app quality, and identify whether any apps would be appropriate for people with social anxiety or others who know someone with social anxiety.MethodsThis systematic stepwise app search was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) standards and entailed searching for, identifying, and selecting apps in the Australian Apple App and Google Play Stores; downloading, using, and reviewing the identified apps; reporting technical and descriptive information in the app stores, an online app warehouse, and individual apps; evaluating app quality; and deciding whether to recommend the use of the apps.ResultsIn the app stores, 1043 apps were identified that contained the keywords social anxiety, social phobia, or shyness in their names or descriptions. Of these, 1.15% (12/1043) were evaluated (3 iOS apps and 9 Android apps). At the time of evaluation, the apps were compatible with smartphones and tablet devices; 9 were free to download from the app stores, whereas 3 were priced between US $2.95 (Aus $3.99) and US $3.69 (Aus $5.00). Among the evaluated apps, 3 were intended for treatment purposes, 3 provided supportive resources, 1 was intended for self-assessment, and the remaining 5 were designed for multiple purposes. At the time of downloading, app store ratings were available for 5 apps. The overall app quality was acceptable according to the Mobile App Rating Scale (MARS). On the basis of the MARS app quality rating subscale (sections A-D), the apps functioned well in performance, ease of use, navigation, and gestural design. However, app quality was less favorable when rated using the MARS app subjective quality subscale (section E).ConclusionsThe psychoeducational social anxiety apps evaluated in our study may benefit people with social anxiety, health professionals, and other community members. However, given that none of the apps appeared to contain empirical information or were shown to clinically reduce social anxiety (or aid in managing social anxiety), we cannot recommend their use. App accessibility could be improved by developing apps that are free and available for a wider range of operating systems, both between and within countries and regions. Information communication and technology professionals should collaborate with academics, mental health clinicians, and end users (ie, co-design) to develop current, evidence-based apps.

Dataset Information

Examining Diabetes Management Apps Recommended From a Google Search: Content Analysis.

Background

Objective

Methods

Results

Conclusions

Publications

Examining Diabetes Management Apps Recommended From a Google Search: Content Analysis.

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