Measuring the quality of mobile applications for the management of pain: a standardised review using the mobile app rating scale (MARS)

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2018-10-25Department
Enfermería y FisioterapiaSource
JMIR Mhealth Uhealth 2018 , vol. 6 n. 10Abstract
Background: Chronic pain is a major health issue requiring an approach that not only considers medication, but also many other factors included in the Bio-Psycho-Social model of pain. New technologies, such as mobile applications, are tools to address these factors, although in many cases they lack proven quality or are not based on scientific evidence, so it is necessary to review and measure their quality. Objective: The aim is to review and measure the quality of mobile applications for the management of pain using the mobile app rating scale (MARS). Methods: This review included 18 pain related mobile apps from App Store and Android Market. The MARS was administered to measure their quality. We list the scores (of each section and the final score) of every app and we report the mean score (and standard deviation) for an overall vision of the quality of the pain related apps. We compare the section scores between the groups defined according to the tertiles via ANOVA analyses, after checking for normality (Kolmogorov-Smirnov test). Results: The global quality ranged from 1.74 (worst app) to 4.35 (best app). The 18 apps, as a whole, obtained an average score of 3.17 (SD=0.75). The best rated sections were “Functionality” (Mean=3.92;SD=0.72), “Aesthetics” (Mean=3.3;SD=1.05), and “Engagement” (Mean=2.87;SD=1.14), while the worst rated were “App specific” (Mean=2.48;SD=1), “Information” (Mean=2.52;SD=0.82), and “App subjective quality” (Mean=2.68;SD=1.22). The main differences between tertiles were found on “app subjective quality”, “Engagement”, “Aesthetics”, and “App specific”. Conclusions: Current pain related apps are of a certain quality, mainly regarding their technical aspects, although they fail to offer information and have an impact on the user. Most apps are not based on scientific evidence, have not been rigorously tested, and the confidentiality of the information collected is not guaranteed. Future apps would need to improve these aspects and exploit the capabilities of current devices.
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