App Rating Research Articles

Health Internet Technology for Chronic Conditions: Review of Diabetes Management Apps.

BackgroundMobile health (mHealth) smartphone apps have shown promise in the self-management of chronic disease. In today’s oversaturated health app market, selection criteria that consumers are employing to choose mHealth apps for disease self-management are of paramount importance. App quality is critical in monitoring disease controls but is often linked to consumer popularity rather than clinical recommendations of effectiveness in disease management. Management of key disease variances can be performed through these apps to increase patient engagement in disease self-management. This paper provides a comprehensive review of features found in mHealth apps frequently used in the self- management of diabetes.ObjectiveThe purpose of this study was to review features of frequently used and high consumer-rated mHealth apps used in the self-management of diabetes. This study aimed to highlight key features of consumer-favored mHealth apps used in the self-management of diabetes.MethodsA 2-fold approach was adopted involving the Apple iOS store and the Google search engine. The primary search was conducted on the Apple iOS store using the term “diabetes apps” (device used: Apple iPad). The top 5 most frequently used mHealth apps were identified and rated by the number of consumer reviews, app ratings, and the presence of key diabetes management features, such as dietary blood glucose, A1C, insulin, physical activity, and prescription medication. A subsequent Google search was conducted using the search term “best Apple diabetes apps.” The top 3 search results—“Healthline,” “Everyday Health,” and “Diabetes Apps–American Diabetes Association”—were explored.ResultsIn total, 12 mHealth apps were reviewed due to their appearing across 4 evaluated sources. Only 1 health app—Glucose Buddy Diabetes Tracker—appeared as the most frequently used within the Apple iOS store and across the other 3 sources. The OneTouch Reveal app ranked first on the list in the iOS store with 39,000 consumer reviews and a rating of 4.7 out of 5.0 stars but only appeared in 1 of the other 3 sources. Blood glucose tracking was present across all apps, but other disease management features varied in type with at least 3 of the 5 key features being present across the 12 reviewed apps. Subscription cost and integration needs were present in the apps which could impact consumers’ decision to select apps. Although mobile app preference was assessed and defined by the number of consumer reviews and star ratings, there were no scientific standards used in the selection and ranking of the health apps within this study.ConclusionsmHealth apps have shown promise in chronic disease management, but a surge in development of these nonregulated health solutions points to a need for regulation, standardization, and quality control. A governing body of health IT professionals, clinicians, policymakers, payors, and patients could be beneficial in defining health app standards for effective chronic disease management. Variabilities in features, cost, and other aspects of management could be reduced by regulatory uniformity, which would increase patient engagement and improve disease outcomes.

Promoting Health via mHealth Applications Using a French Version of the Mobile App Rating Scale: Adaptation and Validation Study.

BackgroundIn the recent decades, the number of apps promoting health behaviors and health-related strategies and interventions has increased alongside the number of smartphone users. Nevertheless, the validity process for measuring and reporting app quality remains unsatisfactory for health professionals and end users and represents a public health concern. The Mobile Application Rating Scale (MARS) is a tool validated and widely used in the scientific literature to evaluate and compare mHealth app functionalities. However, MARS is not adapted to the French culture nor to the language.ObjectiveThis study aims to translate, adapt, and validate the equivalent French version of MARS (ie, MARS-F).MethodsThe original MARS was first translated to French by two independent bilingual scientists, and their common version was blind back-translated twice by two native English speakers, culminating in a final well-established MARS-F. Its comprehensibility was then evaluated by 6 individuals (3 researchers and 3 nonacademics), and the final MARS-F version was created. Two bilingual raters independently completed the evaluation of 63 apps using MARS and MARS-F. Interrater reliability was assessed using intraclass correlation coefficients. In addition, internal consistency and validity of both scales were assessed. Mokken scale analysis was used to investigate the scalability of both MARS and MARS-F.ResultsMARS-F had a good alignment with the original MARS, with properties comparable between the two scales. The correlation coefficients (r) between the corresponding dimensions of MARS and MARS-F ranged from 0.97 to 0.99. The internal consistencies of the MARS-F dimensions engagement (ω=0.79), functionality (ω=0.79), esthetics (ω=0.78), and information quality (ω=0.61) were acceptable and that for the overall MARS score (ω=0.86) was good. Mokken scale analysis revealed a strong scalability for MARS (Loevinger H=0.37) and a good scalability for MARS-F (H=0.35).ConclusionsMARS-F is a valid tool, and it would serve as a crucial aid for researchers, health care professionals, public health authorities, and interested third parties, to assess the quality of mHealth apps in French-speaking countries.

What Do People Want in a Smoking Cessation App? An Analysis of User Reviews and App Quality.

Mobile smoking cessation (mCessation) apps have the potential to complement and enhance existing interventions, but many are of low quality. Exploring app reviews can provide a broader understanding of user experiences and engagement, to enhance the quality, acceptability, and effectiveness of future developments. Publicly available user reviews and ratings of smoking cessation apps were mined from Google Play and the App Store via a targeted two-stage search strategy. English language smoking cessation apps with at least 20 consumer reviews between 2011 and 2020 were included. User reviews were thematically analyzed using Braun and Clarke's framework. Apps were independently scored using the Mobile Apps Rating Scale (MARS) and compared to average user star ratings. Forty-eight versions of 42 apps, encompassing 1414 associated reviews, met eligibility criteria. Inductive coding of reviews produced 1084 coding references including reviews coded across multiple nodes. Themes generated included: (1) supportive characteristics/tools; (2) useability; (3) influence on smoking behavior; (4) benefits of quitting; and (5) role as a supplementary tool for quitting. The mean MARS score of 36 free and accessible apps was 3.10 (SD 0.71) with mean scores ranging from 2.00 to 4.47. An inverse relationship between MARS scores and average user star ratings was observed. App personalization, relationality, functionality, and credibility were important to users, and should be considered as key design components for future apps. Differences between user star ratings and MARS scores may illustrate competing priorities of consumers and researchers, and the importance of a codesign development method. This is the first study to use unsolicited user reviews from a large population to understand the general mCessation user experience in relation to making a quit attempt. Our findings highlight specific features favored and disliked by users, including their influence on engagement, and supports previous findings that mCessation applications need to be highly tailorable, functional, credible, and supportive. We recommend a consumer-driven, co-design approach for future mCessation app developments to optimize user acceptability and engagement.

Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis

Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, the social and non-social engagement features that are present in current smoking cessation apps and the effectiveness of these features in engaging users remain understudied. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps was conducted to examine (a) the presence of social features (i.e., social support, social announcement, and social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting, progress tracking, reinforcement tracking, self-monitoring, and personalized recommendations) and (b) their relationships with user engagement scores measured by the Mobile App Rating Scale. In this study, 28.2% of the smoking cessation apps enable social announcement and 8.1% offered the social support feature. Only two apps provided a social referencing feature (1.3%). No app included reinforcement tracking, with the percentage of other non-social engagement features ranging from 9.4% to 49.0%. Social support (β = 0.30, p < 0.001), social announcement (β = 0.21, p < 0.05), and social referencing (β = 0.18, p < 0.05) were significant predictors of user engagement. Regarding the non-social engagement features, personal environment changes (β = 0.38, p < 0.001), progress tracking (β = 0.18, p < 0.05), and personalized recommendations (β = 0.37, p < 0.001) significantly predicted user engagement. The findings not only contribute to the mobile communication literature by applying and extending the theory-based mobile health apps engagement typology, but also inform the future architecture design of smoking cessation mobile apps.

Personalized and Self-Management: Systematic Search and Evaluation Quality Factors and User Preference of Drug Reference Apps in Taiwan.

Background: Drug reference apps promote self-management and improve the efficiency and quality of work for physicians, nurses, pharmacists, and patients. This study aimed to describe a systematic and stepwise process to identify drug reference apps in Taiwan, assess the quality of these apps, and analyze the influential factors for user ratings. Methods: A two-step algorithm (KESS) consisting of keyword growing and systematic search was proposed. Seven independent reviewers were trained to evaluate these apps using Mobile App Rating Scale (MARS). A logistic regression model was fitted and average marginal effects (AME) were calculated to identify the effects of factors for higher user ratings. Results: A total of 23 drug reference apps in Taiwan were identified and analyzed. Generally, these drug reference apps were evaluated as acceptable quality with an average MARS score of 3.23. Higher user engagement, more functionality, better aesthetics, and more information associated with higher user ratings. Navigation is the most influential factor on higher user ratings (AME: 13.15%) followed by performance (AME: 11.03%), visual appeal (AME: 10.87%), credibility (AME: 10.67%), and quantity of information (AME: 10.42%). Conclusions: User experience and information clearly affect user ratings of drug reference apps. Five key factors should be considered when designing drug reference apps.

Characterisation and assessment of the most popular mobile apps designed for neck pain self-management: A systematic search in app stores.

This study aimed to assess commonly downloaded apps targeting neck pain (NP) using the Mobile Apps Rating Scale (MARS), to characterise the interventions described in the apps and to correlate the ratings of quality retrieved from app stores against the ratings of quality assessed using MARS. A systematic search was conducted at the Apple App Store, Google Play, Windows Phone Store and Huawei App Gallery. Mobile apps with 100 or more ratings, a user rating of 4 or higher and which were available for free were retrieved for assessment. A total of 17 apps met the inclusion criteria. The mean user rating was 4.4±0.28, the mean MARS score was 4.0±0.58 and the correlation between user ratings and MARS total scores and subdomains varied between a maximum of 0.41 (p>0.05) and a minimum of -0.11 (p>0.05). All apps included exercise but only 5 (29%) included an educational component. The most downloaded apps on NP available for free in app stores are, generally, of acceptable quality as assessed by the MARS total score, target exercise, but fail to include an appropriate educational component. The user rating available in app stores is not an indicator of the quality of the apps. Therefore, health professionals should carefully assess the mobile apps before recommending them to the patients.

An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation.

This study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results’ description, established by the apps’ quality assessment, using the Mobile App Rating Scale (MARS) tool. However, because of the restrictions of MARS outputs, the identification of critical quality factors could not be established, requiring the search for an answer for a new rule. Finally, the explanation of the case (the last component of the abductive approach) to test the rule’s new hypothesis. This problem was solved by applying a new quantitative model, compounding data mining techniques, which identified MARS’ most relevant quality items. Hence, this research defines a much-needed theoretical and practical tool for academics and also practitioners. Academics can experiment utilizing the abduction reasoning procedure as an alternative to achieve positivism in research. This study is a first attempt to improve the MARS tool, aiming to provide specialists relevant data, reducing noise effects, accomplishing better predictive results to enhance their investigations. Furthermore, it offers a concise quality assessment of disability-related apps.

Feature Availability Comparison in Free and Paid Versions of Popular Smartphone Weight Management Applications

ObjectiveCharacterize capabilities of nutrition applications (apps) for weight management and associations between features, ratings, and app installations. DesignCalorie tracking apps with weight management as a primary outcome were selected from the Apple App Store and Google Play Store using keywords “diet” and “weight loss.” MethodsReviewers assessed free and upgraded versions of nutrition apps (n = 15) for features within 4 categories: (1) dietary intake, (2) anthropometrics, (3) physical activity, and (4) behavior change strategies. Outcome MeasuresPresence of specific app features, app ratings, and app installations. AnalysisDescriptive statistics of free and paid app versions. Spearman rank-order correlations were used to determine associations between feature inclusion, app ratings, and installations. ResultsThe apps had the greatest number of features in the dietary intake category. Additional dietary intake features were those most likely obtained through a subscription purchase. Behavior change content was absent from most apps. The macronutrient adjustment feature was strongly associated with average app ratings (rs = 0.74; P < 0.002) and with subscription costs (rs = 0.60; P < 0.019). Conclusions and ImplicationsThis study found most nutrition apps possess an abundance of features dedicated to dietary intake, anthropometric, and physical activity tracking while also being notably devoid of behavior change content features.

Quality of a Supporting Mobile App for Rheumatic Patients: Patient-Based Assessment Using the User Version of the Mobile Application Scale (uMARS).

Introduction: Mobile applications promise to improve current health care. However, current mobile app quality ratings are mostly physician-based. The aim of this study was (1) to assess the quality of the self-management app Rheuma Auszeit using the validated uMARS (User Version of the Mobile App Rating Scale) app quality assessment tool and (2) to evaluate the association between uMARS scores and patients' characteristics.Materials and Methods: Consecutive patients with rheumatoid arthritis, psoriatic arthritis and spondyloarthritis were seen at the rheumatology clinic at university hospital Erlangen, Germany. They were asked to test Rheuma Auszeit, evaluate its quality using uMARS and complete a paper-based survey evaluating the individual preferences, attitudes and ehealth literacy. The association between uMARS scores and patients' characteristics was further explored.Results: Between December 2018 and January 2019, a total of 126 patients evaluated Rheuma Auszeit using uMARS and filled out the paper-based survey. The median uMARS score was 3.9, IQR 0.7. Functionality was the domain with the highest rating (median 4.8, IQR 0.8), followed by aesthetics (median 4.0, IQR 0.7), information (median 3.5, IQR 0.8), and engagement (median 3.2, IQR 1.0). Subjective quality was average (median 3.0, IQR 1.0). The lowest scoring individual item was customization with a median of 2.5/5. Lower functionality scores were reported among older female rheumatic patients (P < 0.004). Older male rheumatic patients reported a higher subjective quality score (P < 0.024). Perceived disease activity and disease duration did not significantly correlate with any uMARS subdomain scores. eHealth literacy significantly correlated with functionality uMARS subdomain ratings (Rho = 0.18; P < 0.042). Preferred time of app usage significantly correlated with engagement (Rho = 0.20; P < 0.024), functionality (Rho = 0.19; P < 0.029), total uMARS score (Rho = 0.21; P < 0.017) and subjective quality score (Rho = 0.21; P < 0.017). The vast majority of rheumatic patients would consider recommending Rheuma Auszeit to other patients (117/126; 92.9%).Conclusion: Rheuma Auszeit was well-accepted by German patients suffering from rheumatoid arthritis, psoriatic arthritis and ankylosing spondyloarthritis. Lacking customization could lead to low app compliance and should be improved. Lower functionality scores among older female rheumatic patients highlight the need for patient education. The study underlines the potential and feasibility of therapeutic complementary digital solutions in rheumatology.

User Engagement and Usability of Suicide Prevention Apps: Systematic Search in App Stores and Content Analysis.

BackgroundPeople with suicidal thoughts are more inclined to seek technology-delivered interventions than in-person forms of treatment, making mobile apps for suicide prevention an ideal platform for treatment delivery. This review examines apps designed for suicide prevention, with a specific focus on user engagement.ObjectiveThis study aims to update the literature and broadly evaluate the landscape of mobile health apps for suicide prevention; examine apps with key features and primary approaches to suicide prevention; and systematically evaluate the engagement, functionality, aesthetics, and information of the apps.MethodsAll apps related to suicidal thoughts and behaviors were identified in the Google Play and iOS app stores and were systematically reviewed for their content and quality. The mobile app rating scale (MARS) was used to evaluate app usability and engagement.ResultsOf the 66 apps identified, 42 (64%) were specifically designed for people with suicidal ideation, and 59 (89%) had at least one best practice feature for suicide risk reduction. The mean overall MARS score of all apps was 3.5 (range 2.1-4.5), with 83% (55/66) of apps having a minimum acceptability score of 3. The total MARS score was not associated with the user app rating (r=−0.001; P=.99) or the number of features (r=0.24; P=.09).ConclusionsThis study identified many usable and engaging apps in app stores designed for suicide prevention. However, there are only limited apps for clinicians. Thus, mobile apps for suicide prevention should be carefully developed and clinically evaluated.

Evaluating Chinese Mobile Health Apps for Ankylosing Spondylitis Management: Systematic App Search.

BackgroundPatients with ankylosing spondylitis (AS), a chronic systematic inflammatory disease, require long-term treatment and management. Mobile health (mHealth) apps can deliver health services through mobile devices, facilitate long-term disease management, support patient–health care provider communication, and enable patients to engage in disease management. There are some apps targeted at patients with AS, but the feature and quality of these apps have not been systematically examined.ObjectiveThe aim of this study was to identify existing, publicly available Chinese mHealth apps for AS management and to evaluate their features and quality.MethodsWe systematically searched potential apps for AS management on the Apple and Huawei App Stores, using 4 search terms: ankylosing spondylitis, spondyloarthritis, rheumatic disease, and arthritis. Apps were included if they were in the Chinese language, targeted at patients with AS, could be downloaded and run on Android and/or iOS operating systems, and incorporated elements of disease management and/or patient education. We excluded apps that were not for patient use, not relevant to AS, or had not been updated since 2018. Apps that met the inclusion criteria were downloaded for final analysis. We formulated a list of app quality measures from and consistent with international guidelines for mHealth apps and AS management to evaluate the features and quality of the included app. The user version of the Mobile App Rating Scale (uMARS) was also used to rate the apps’ quality.ResultsOf the 354 apps screened, 5 met the inclusion criteria and were included in our analysis. All apps were free, and most apps (4/5, 80%) had a privacy policy. Of the 5 apps, 1 (20%) involved medical professionals in the development process, 2 (40%) were developed by companies, and 2 (40%) were developed by medical institutions. All apps provided educational information about AS. Around half of the apps had functions like a basic information record (ie, users can input gender, age, disease history, etc) (n=3, 60%), patient–health care provider (and patient-patient) communication (n=2, 40%), symptom tracking (n=2, 40%), and information sharing (n=3, 60%). Only 1 (20%) app provided comprehensive functions that adhered to international guidelines for AS management and mHealth apps. The overall uMARS scores ranged from 2.7 to 4.2; only 1 app, with an overall uMARS score of 4.2, was considered as a high-quality app.ConclusionsMost apps lacked comprehensive functions for AS management. One high-quality app provided comprehensive functions to help patients manage their conditions. This study assessed and summarized the features and quality of the apps but did not evaluate their efficacy. Future studies should evaluate the feasibility and efficacy of these apps. International guidelines and regulations for the design, development, validation, and implementation of mHealth apps are needed in the future. Meanwhile, health care providers, patients with AS, and app developers should collaborate to develop high-quality, evidence-based apps that take into account patients’ needs and health care professionals’ perspectives.

Systematic Review and Scientific Rating of Commercial Apps Available in India for Diabetes Prevention

Objectives: We aimed to evaluate the quality of currently available health apps for prevention of type 2 diabetes among Asian Indians using validated rating scales. Materials and Methods: Using the keywords, “diabetes prevention,” “healthy lifestyle,” and “fitness,” a total of 1486 apps available in India via Google Play were assessed for eligibility by two independent reviewers. After initial screening using specific inclusion and exclusion criteria, 50 apps underwent a pre-specified rating based on user reviews, number of downloads, and app size. Sixteen apps that scored ≥ 9 were shortlisted for further review using the Mobile App Rating Scale (MARS). The mean MARS scores (for categories I and II) were used to identify the top ranked apps. Results: The mean score for Category I of MARS rating was highest for “Google Fit: Health and Activity Tracking” (4.55/5). This was followed by “Healthifyme—Diet Plan, Health, and Weight Loss” (4.45/5). For Category II of MARS, “Diabetes M,” “Google Fit: Health and Activity Tracking,” “Calorie Counter—My Fitness Pal,” and “Healthifyme—Diet Plan, Health, and Weight Loss” all scored equally well. On comparing the advantages and disadvantages of each of these applications, “Google Fit: Health and Activity Tracking” and “Healthifyme—Diet Plan, Health, and Weight Loss” again ranked the best. Conclusion: Our review identifies two commercially available apps “Google Fit: Health and Activity Tracking” and “Healthifyme—Diet Plan, Health, and Weight Loss” as being user friendly and good quality. Although encouraging, further research is needed to evaluate the efficacy of these apps for the prevention of diabetes.

PesTrapp mobile app: A trap setting application for real-time entomological field and laboratory study.

Diseases such as malaria, dengue, Zika and chikungunya remain endemic in many countries. Setting and deploying traps to capture the host/vector species are fundamental to understand their density and distributions. Human effort to manage the trap data accurately and timely is an exhaustive endeavour when the study area expands and period prolongs. One stop mobile app to manage and monitor the process of targeted species trapping, from field to laboratory level is still scarce. Toward this end, we developed a new mobile app named "PesTrapp" to acquire the vector density index based on the mobile updates of ovitraps and species information in field and laboratory. This study aimed to highlight the mobile app's development and design, elucidate the practical user experiences of using the app and evaluate the preliminary user assessment of the mobile app. The mobile app was developed using mobile framework and database. User evaluation of the mobile app was based on the adjusted Mobile App Rating Scale and Standardized User Experience Percentile Rank Questionnaire. The process flows of system design and detailed screen layouts were described. The user experiences with and without the app in a project to study Aedes surveillance in six study sites in Selangor, Malaysia were elucidated. The overall mean user evaluation score of the mobile app was 4.0 out of 5 (SD=0.6), reflects its acceptability of the users. The PesTrapp, a one-stop solution, is anticipated to improve the entomological surveillance work processes. This new mobile app can contribute as a tool in the vector control countermeasure strategies.

Sticky apps, not sticky hands: A systematic review and content synthesis of hand hygiene mobile apps.

The study sought to identify smartphone apps that support hand hygiene practice and to assess their content, technical and functional features, and quality. A secondary objective was to make design and research recommendations for future apps. We searched the UK Google Play and Apple App stores for hand hygiene smartphone apps aimed at adults. Information regarding content, technical and functional features was extracted and summarized. Two raters evaluated each app, using the IMS Institute for Healthcare Informatics functionality score and the Mobile App Rating Scale (MARS). A total of 668 apps were identified, with 90 meeting the inclusion criteria. Most (96%) were free to download. The majority (78%) intended to educate or inform or remind users to hand wash (69%), using behavior change techniques such as personalization and prompting practice. Only 20% and 4% named a best practice guideline or had expert involvement in development, respectively. Innovative means of engagement were used in 42% (eg, virtual or augmented reality or geolocation-based reminders). Apps included an average of 2.4 out of 10 of the IMS functionality criteria (range, 0-8). The mean MARS score was 3.2 ± 0.5 out of 5, and 68% had a minimum acceptability score of 3. Two had been tested or trialed. Although many hand hygiene apps exist, few provide content on best practice. Many did not meet the minimum acceptability criterion for quality or were formally trialed or tested. Research should assess the feasibility and effectiveness of hand hygiene apps (especially within healthcare settings), including when and how they "work." We recommend that future apps to support hand hygiene practice are developed with infection prevention and control experts and align with best practice. Robust research is needed to determine which innovative methods of engagement create "sticky" apps.

Moving beyond Limitations: Designing the Helpdys App for Children with Dyslexia in Rural Areas

Dyslexia is a relatively common language disorder which is generally ignored in rural communities. It hinders children’s learning processes and, in some cases, is the cause of dropouts or violence in schools. The present work strives to create a web and mobile app as a preliminary step towards the diagnosis and treatment of dyslexic children. Apps providing didactic educational games and activities improve literacy skills for students with reading disabilities. The current work incorporates user experience and prototyping to fulfill app requirements. The authors evaluated the apps with the Mobile App Rating Scale (MARS) tool to assess engagement, functionality, aesthetics, and information. The app’s improvements were immediately implemented and tested in the “Escuela Linea Equinoccial” (Ecuador) school, proving its utility for future use in the education system. The app can be a valuable tool for children with dyslexia to progress successfully through school, raising their self-confidence and, thereby, helping them reach their full potential as adults able to make a positive contribution to society.

A Measurement Study of Wechat Mini-Apps

A new mobile computing paradigm, dubbed mini-app, has been growing rapidly over the past few years since being introduced by WeChat in 2017. In this paradigm, a host app allows its end-users to install and run mini-apps inside itself, enabling the host app to build an ecosystem around (much like Google Play and Apple AppStore), enrich the host's functionalities, and offer mobile users elevated convenience without leaving the host app. It has been reported that there are over millions of mini-apps in WeChat. However, little information is known about these mini-apps at an aggregated level. In this paper, we present MiniCrawler, the first scalable and open-source WeChat mini-app crawler that has indexed over 1,333,308 mini-apps. It leverages a number of reverse engineering techniques to uncover the interfaces and APIs in WeChat for crawling the mini-apps. With the crawled mini-apps, we then measure the resource consumption, API usage, library usage, obfuscation rate, app categorization, and app ratings at an aggregated level in this work.

Mobile Apps for Drug-Drug Interaction Checks in Chinese App Stores: Systematic Review and Content Analysis.

BackgroundAs a computerized drug–drug interaction (DDI) alert system has not been widely implemented in China, health care providers are relying on mobile health (mHealth) apps as references for checking drug information, including DDIs.ObjectiveThe main objective of this study was to evaluate the quality and content of mHealth apps supporting DDI checking in Chinese app stores.MethodsA systematic review was carried out in November 2020 to identify mHealth apps providing DDI checking in both Chinese iOS and Android platforms. We extracted the apps’ general information (including the developer, operating system, costs, release date, size, number of downloads, and average rating), scientific or clinical basis, and accountability, based on a multidimensional framework for evaluation of apps. The quality of mHealth apps was evaluated by using the Mobile App Rating Scale (MARS). Descriptive statistics, including numbers and percentages, were calculated to describe the characteristics of the apps. For each app selected for evaluation, the section-specific MARS scores were calculated by taking the arithmetic mean, while the overall MARS score was described as the arithmetic mean of the section scores. In addition, the Cohen kappa (κ) statistic was used to evaluate the interrater agreement.ResultsA total of 7 apps met the selection criteria, and only 3 included citations. The average rating score for Android apps was 3.5, with a minimum of 1.0 and a maximum of 4.9, while the average rating score for iOS apps was 4.7, with a minimum of 4.2 and a maximum of 4.9. The mean MARS score was 3.69 out of 5 (95% CI 3.34-4.04), with the lowest score of 1.96 for Medication Guidelines and the highest score of 4.27 for MCDEX mobile. The greatest variation was observed in the information section, which ranged from 1.41 to 4.60. The functionality section showed the highest mean score of 4.05 (95% CI 3.71-4.40), whereas the engagement section resulted in the lowest average score of 3.16 (95% CI 2.81-3.51). For the information quality section, which was the focus of this analysis, the average score was 3.42, with the MCDEX mobile app having the highest score of 4.6 and the Medication Guidelines app having the lowest score of 1.9. For the overall MARS score, the Cohen interrater κ was 0.354 (95% CI 0.236-0.473), the Fleiss κ was 0.353 (95% CI, 0.234-0.472), and the Krippendorff α was 0.356 (95% CI 0.237-0.475).ConclusionsThis study systematically reviewed the mHealth apps in China with a DDI check feature. The majority of investigated apps demonstrated high quality with accurate and comprehensive information on DDIs. However, a few of the apps that had a massive number of downloads in the Chinese market provided incorrect information. Given these apps might be used by health care providers for checking potential DDIs, this creates a substantial threat to patient safety.

Aplicaciones móviles para mejorar la adherencia a la medicación: revisión y análisis de calidad

ObjectiveTo review the mobile apps in the Spanish market to improve adherence to medications and evaluate their characteristics and quality to identify high-quality applications. MethodA review was carried out following a stepwise procedure similar to a systematic review of the scientific literature. Apple Apps Store and Google Play Store mobile application digital distribution platforms. Applications aimed at supporting self-management of treatment, which generate reminders, in Spanish, updated in the last 2 years and free. We evaluate the applications according to a set of characteristics considered desirable and the quality with the Mobile App Rating Scale tool. ResultsOut of 708 applications, 3 applications were selected. The Medisafe and Mytherapy applications had 89% and 78% of the desirable characteristics, respectively. Sergio Licea's application only had 56%. The highest global quality score was obtained by the MyTherapy application (3.79/5, IQR: 3-4), followed by Medisafe (3.72/5, (IQR: 3-4) and, finally, Sergio Licea (2.87/5, IQR: 2-4). The quality assessment coincides with the user assessment. There are many available applications, however, most did not meet the selection criteria. ConclusionsA systematic stepwise process was able to identify the quality application to be tested in a future study that will provide evidence on the use of a multicomponent intervention to improve medication adherence.

Quality of Physical Activity Apps: Systematic Search in App Stores and Content Analysis.

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.

Quality and Adoption of COVID-19 Tracing Apps and Recommendations for Development: Systematic Interdisciplinary Review of European Apps.

BackgroundSimulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps.ObjectiveThis study’s primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified.MethodsEligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human–computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted.ResultsWe discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9% (SD 12.5%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5% and 43.6%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity.ConclusionsEuropean national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app’s engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development.