Mobile App Rating Scale Score Research Articles

Consumer Mobile Apps for Potential Drug-Drug Interaction Check: Systematic Review and Content Analysis Using the Mobile App Rating Scale (MARS).

BackgroundGeneral consumers can now easily access drug information and quickly check for potential drug-drug interactions (PDDIs) through mobile health (mHealth) apps. With aging population in Canada, more people have chronic diseases and comorbidities leading to increasing numbers of medications. The use of mHealth apps for checking PDDIs can be helpful in ensuring patient safety and empowerment.ObjectiveThe aim of this study was to review the characteristics and quality of publicly available mHealth apps that check for PDDIs.MethodsApple App Store and Google Play were searched to identify apps with PDDI functionality. The apps’ general and feature characteristics were extracted. The Mobile App Rating Scale (MARS) was used to assess the quality.ResultsA total of 23 apps were included for the review—12 from Apple App Store and 11 from Google Play. Only 5 of these were paid apps, with an average price of $7.19 CAD. The mean MARS score was 3.23 out of 5 (interquartile range 1.34). The mean MARS scores for the apps from Google Play and Apple App Store were not statistically different (P=.84). The information dimension was associated with the highest score (3.63), whereas the engagement dimension resulted in the lowest score (2.75). The total number of features per app, average rating, and price were significantly associated with the total MARS score.ConclusionsSome apps provided accurate and comprehensive information about potential adverse drug effects from PDDIs. Given the potentially severe consequences of incorrect drug information, there is a need for oversight to eliminate low quality and potentially harmful apps. Because managing PDDIs is complex in the absence of complete information, secondary features such as medication reminder, refill reminder, medication history tracking, and pill identification could help enhance the effectiveness of PDDI apps.

Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques

BackgroundThe number of commercial apps to improve health behaviours in children is growing rapidly. While this provides opportunities for promoting health, the content and quality of apps targeting children and adolescents is largely unexplored. This review systematically evaluated the content and quality of apps to improve diet, physical activity and sedentary behaviour in children and adolescents, and examined relationships of app quality ratings with number of app features and behaviour change techniques (BCTs) used.MethodsSystematic literature searches were conducted in iTunes and Google Play stores between May–November 2016. Apps were included if they targeted children or adolescents, focused on improving diet, physical activity and/or sedentary behaviour, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. App inclusion, downloading and user-testing for quality assessment and content analysis were conducted independently by two reviewers. Spearman correlations were used to examine relationships between app quality, and number of technical app features and BCTs included.ResultsTwenty-five apps were included targeting diet (n = 12), physical activity (n = 18) and sedentary behaviour (n = 7). On a 5-point Mobile App Rating Scale (MARS), overall app quality was moderate (total MARS score: 3.6). Functionality was the highest scoring domain (mean: 4.1, SD: 0.6), followed by aesthetics (mean: 3.8, SD: 0.8), and lower scoring for engagement (mean: 3.6, SD: 0.7) and information quality (mean: 2.8, SD: 0.8). On average, 6 BCTs were identified per app (range: 1–14); the most frequently used BCTs were providing ‘instructions’ (n = 19), ‘general encouragement’ (n = 18), ‘contingent rewards’ (n = 17), and ‘feedback on performance’ (n = 13). App quality ratings correlated positively with numbers of technical app features (rho = 0.42, p < 0.05) and BCTs included (rho = 0.54, p < 0.01).ConclusionsPopular commercial apps to improve diet, physical activity and sedentary behaviour in children and adolescents had moderate quality overall, scored higher in terms of functionality. Most apps incorporated some BCTs and higher quality apps included more app features and BCTs. Future app development should identify factors that promote users’ app engagement, be tailored to specific population groups, and be informed by health behaviour theories.

Apps for People With Rheumatoid Arthritis to Monitor Their Disease Activity: A Review of Apps for Best Practice and Quality.

BackgroundRheumatoid arthritis (RA) is a chronic inflammatory arthritis requiring long-term treatment with regular monitoring by a rheumatologist to achieve good health outcomes. Since people with RA may wish to monitor their own disease activity with a smartphone app, it is important to understand the functions and quality of apps for this purpose.ObjectiveThe aim of our study was to assess the features and quality of apps to assist people to monitor their RA disease activity by (1) summarizing the available apps, particularly the instruments used for measurement of RA disease activity; (2) comparing the app features with American College of Rheumatology and European League against Rheumatism (ACR and EULAR) guidelines for monitoring of RA disease activity; and (3) rating app quality with the Mobile App Rating Scale (MARS).MethodsSystematic searches of the New Zealand iTunes and Google Play app stores were used to identify all apps for monitoring of RA disease activity that could be used by people with RA. The apps were described by both key metadata and app functionality. App adherence with recommendations for monitoring of RA disease activity in clinical practice was evaluated by identifying whether apps included calculation of a validated composite disease activity measure and recorded results for future retrieval. App quality was assessed by 2 independent reviewers using the MARS.ResultsThe search identified 721 apps in the Google Play store and 216 in the iTunes store, of which 19 unique apps met criteria for inclusion (8 from both app stores, 8 iTunes, and 3 Google Play). In total, 14 apps included at least one validated instrument measuring RA disease activity; 7 of 11 apps that allowed users to enter a joint count used the standard 28 swollen and tender joint count; 8 apps included at least one ACR and EULAR-recommended RA composite disease activity (CDA) measure; and 10 apps included data storage and retrieval. Only 1 app, Arthritis Power, included both an RA CDA measure and tracked data, but this app did not include the standard 28 tender and swollen joint count. The median overall MARS score for apps was 3.41/5. Of the 6 apps that scored ≥4/5 on the overall MARS rating, only 1 included a CDA score endorsed by ACR and EULAR; however, this app did not have a data tracking function.ConclusionsThis review found a lack of high-quality apps for longitudinal assessment of RA disease activity. Current apps fall into two categories: simple calculators primarily for rheumatologists and data tracking tools for people with RA. The latter do not uniformly collect data using validated instruments or composite disease activity measures. There is a need for appropriate, high-quality apps for use by rheumatologists and patients together in co-management of RA.

Assessing app quality through expert peer review: a case study from the gray matters study.

Health apps focused on inciting behavior change are becoming increasingly popular. Nevertheless, many lack underlying evidence base, scientific credibility and have limited clinical effectiveness. It is therefore important that apps are well-informed, scientifically credible, peer reviewed and evidence based. This paper presents the use of the Mobile App Rating Scale (MARS) to assess the quality of the Grey Matters app, a cross platform app to deliver health education material and track behavior change across multi-domains with the aim of reducing the risk of developing Alzheimer's disease. The Gray Matters app shows promising results following reviews from 5 Expert raters, achieving a mean overall MARS score of 4.45 ± 0.14. Future work will involve undertaking of a detailed content analysis of behavior change apps to identify common themes and features which may lead to the successful facilitation of sustained behavior change.

A review and content analysis of engagement, functionality, aesthetics, information quality, and change techniques in the most popular commercial apps for weight management.

BackgroundThere are thousands of apps promoting dietary improvement, increased physical activity (PA) and weight management. Despite a growing number of reviews in this area, popular apps have not been comprehensively analysed in terms of features related to engagement, functionality, aesthetics, information quality, and content, including the types of change techniques employed.MethodsThe databases containing information about all Health and Fitness apps on GP and iTunes (7,954 and 25,491 apps) were downloaded in April 2015. Database filters were applied to select the most popular apps available in both stores. Two researchers screened the descriptions selecting only weight management apps. Features, app quality and content were independently assessed using the Mobile App Rating Scale (MARS) and previously-defined categories of techniques relevant to behaviour change. Inter-coder reliabilities were calculated, and correlations between features explored.ResultsOf the 23 popular apps included in the review 16 were free (70 %), 15 (65 %) addressed weight control, diet and PA combined; 19 (83 %) allowed behavioural tracking. On 5-point MARS scales, apps were of average quality (Md = 3.2, IQR = 1.4); “functionality” (Md = 4.0, IQR = 1.1) was the highest and “information quality” (Md = 2.0, IQR = 1.1) was the lowest domain. On average, 10 techniques were identified per app (range: 1–17) and of the 34 categories applied, goal setting and self-monitoring techniques were most frequently identified. App quality was positively correlated with number of techniques included (rho = .58, p < .01) and number of “technical” features (rho = .48, p < .05), which was also associated with the number of techniques included (rho = .61, p < .01). Apps that provided tracking used significantly more techniques than those that did not. Apps with automated tracking scored significantly higher in engagement, aesthetics, and overall MARS scores. Those that used change techniques previously associated with effectiveness (i.e., goal setting, self-monitoring and feedback) also had better “information quality”.ConclusionsPopular apps assessed have overall moderate quality and include behavioural tracking features and a range of change techniques associated with behaviour change. These apps may influence behaviour, although more attention to information quality and evidence-based content are warranted to improve their quality.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-016-0359-9) contains supplementary material, which is available to authorized users.