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The Persian Version of the Mobile Application Rating Scale (MARS-Fa): Translation and Validation Study

Convergent validity was deemed satisfactory when an item achieved a correlation above r=0.20 with the respective subscale, a threshold used in the Italian [34] and Japanese [38] validation studies. Discriminant validity was deemed satisfactory if more than 80% of the correlation coefficients were higher than those with other subscales [38].

Saeed Barzegari, Ali Sharifi Kia, Marco Bardus, Stoyan R Stoyanov, Marjan GhaziSaeedi, Mouna Rafizadeh

JMIR Form Res 2022;6(12):e42225

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Japanese Version of the Mobile App Rating Scale (MARS): Development and Validation

The original MARS was developed by Stoyanov and colleagues [13] to establish a multidimensional measure able to classify and evaluate the objective and subjective quality of m Health apps. The main part of this original version of MARS consisted of 23 items. The objective evaluation of m Health app quality included 4 subscales: engagement (items 1-5), functionality (items 6-9), aesthetics (items 10-12), and information (items 13-19). The subjective quality subscale consisted of 4 items (items 20-23).

Kazumichi Yamamoto, Masami Ito, Masatsugu Sakata, Shiho Koizumi, Mizuho Hashisako, Masaaki Sato, Stoyan R Stoyanov, Toshi A Furukawa

JMIR Mhealth Uhealth 2022;10(4):e33725

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A Web-Based Program for Cannabis Use and Psychotic Experiences in Young People (Keep It Real): Protocol for a Randomized Controlled Trial

Leanne Hides, Amanda Baker, Melissa Norberg, Jan Copeland, Catherine Quinn, Zoe Walter, Janni Leung, Stoyan R Stoyanov, David Kavanagh

JMIR Res Protoc 2020;9(7):e15803

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The Arabic Version of the Mobile App Rating Scale: Development and Validation Study

A cutoff point of r>0.80 was deemed a sufficient indication of the validity of the MARS-Ar instrument. All statistical tests were conducted using SPSS v21 [56] for mac OS (Apple Inc, Cupertino, California). The two reviewers completed the evaluation of 67 out of 69 selected apps, using MARS-Ar, and 66 apps, using the MARS English version. One app was incompatible with both test devices, and 2 apps were not working on one of the two devices used.

Marco Bardus, Nathalie Awada, Lilian A Ghandour, Elie-Jacques Fares, Tarek Gherbal, Tasnim Al-Zanati, Stoyan R Stoyanov

JMIR Mhealth Uhealth 2020;8(3):e16956

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Efficacy and Outcomes of a Music-Based Emotion Regulation Mobile App in Distressed Young People: Randomized Controlled Trial

Leanne Hides, Genevieve Dingle, Catherine Quinn, Stoyan R Stoyanov, Oksana Zelenko, Dian Tjondronegoro, Daniel Johnson, Wendell Cockshaw, David J Kavanagh

JMIR Mhealth Uhealth 2019;7(1):e11482

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The Quality and Accuracy of Mobile Apps to Prevent Driving After Drinking Alcohol

Both raters underwent MARS training, as suggested by Stoyanov and colleagues [12] and followed the steps presented in the You Tube training tutorial [17]. To address information-specific items, a researcher specializing in drink driving information and behavior provided a 1-hour structured information session to each rater before app evaluation. For item 19 relating to evidence base, raters conducted a literature search in Google Scholar utilizing the app name as a search term.

Hollie Jai Wilson, Stoyan R Stoyanov, Shailen Gandabhai, Alexander Baldwin

JMIR Mhealth Uhealth 2016;4(3):e98

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