Method of App Selection based on Users Needs (MASUN) : Randomized Controlled Trial of Dysmenorrhea and PMS

Abstract

Although several mobile apps are available for health management, many healthcare providers are hesitant to utilize them, particularly given that there is no definite method of selecting the best app based on users needs. The aim of this study is to create a Method of App Selection based on the Users Needs (MASUN). For this study, women suffering from dysmenorrhea and premenstrual syndrome were the target users. First, related apps were searched on the Apple iTunes and Google Play stores. Brainstorming, mind mapping, and persona and scenario techniques were adopted to create a checklist of the relevant criteria, which was then used to score the apps. After app experts, clinical experts, and potential users evaluated the apps, an intervention aimed at verifying MASUN was designed. To be able to apply the MASUN to a clinical or research setting, this study evaluated an intervention based on the results of the MASUN with a randomized controlled trial (RCT). Of the 2,784 apps found, 369 were quantitatively analyzed. Of those, the top five candidate apps in terms of scoring (App A–E) were evaluated by three groups: app experts, clinical experts, and potential users. All three groups ranked App A the highest

however, their opinions differed for the remaining ranks. The RCT was implemented using App A (the best app according to the MASUN), and App E (the app with the largest number of users worldwide). The intervention was performed over four months so that at least three menstrual cycles could be included. As a result, the 16-week intervention was completed by 61 app users. For personal outcomes, there were non-significant main effects of app on app self-efficacy. For the app quality rating and overall satisfaction, there was a significant main effect of app. There was also a significant main effect of app on app outcome expectancy, while there was a significant main effect of time on the number of menus used. Moreover, there were statistically significant differences in the number of days with records per month between the groups. As for environmental outcomes, there was a significant main effect of app on app social influences and intent to recommend. Regarding the dysmenorrhea and PMS-related outcomes, there were no statistically significant differences in dysmenorrhea and PMS score but there were significant differences in the likelihood of behavioral and cognitive changes in dysmenorrhea and PMS management. Furthermore, the number of dysmenorrhea relief methods used showed a significant increase in the experimental group. Our results indicate that the MASUN is useful, as it not only considers the needs of various users but also draws on the knowledge of app and clinical experts. In deriving a way to find and utilize the best app for a given purpose, this study highlights how healthcare providers can understand and combine the opinions of users and app and clinical experts.