Development and validation of the Italian version of the Mobile Application Rating Scale and its generalisability to apps targeting primary prevention

Domnich, Alexander, Arata, Lucia, Amicizia, Daniela, Signori, Alessio, Patrick, Bernard, Stoyanov, Stoyan, Hides, Leanne, Gasparini, Roberto, & Panatto, Donatella (2016) Development and validation of the Italian version of the Mobile Application Rating Scale and its generalisability to apps targeting primary prevention. BMC Medical Informatics and Decision Making, 16, Article number-83.

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  • A growing body of literature affirms the usefulness of mobile technologies, including mobile applications (apps), in the primary prevention field. The quality of health apps, which today number in the thousands, is a crucial parameter, as it may affect health-related decision-making and outcomes among app end-users. The mobile application rating scale (MARS) has recently been developed to evaluate the quality of such apps, and has shown good psychometric properties. Since there is no standardised tool for assessing the apps available in Italian app stores, the present study developed and validated an Italian version of MARS in apps targeting primary prevention.


  • The original 23-item version of the MARS assesses mobile app quality in four objective quality dimensions (engagement, functionality, aesthetics, information) and one subjective dimension. Validation of this tool involved several steps; the universalist approach to achieving equivalence was adopted. Following two backward translations, a reconciled Italian version of MARS was produced and compared with the original scale. On the basis of sample size estimation, 48 apps from three major app stores were downloaded; the first 5 were used for piloting, while the remaining 43 were used in the main study in order to assess the psychometric properties of the scale. The apps were assessed by two raters, each working independently. The psychometric properties of the final version of the scale was assessed including the inter-rater reliability, internal consistency, convergent, divergent and concurrent validities.


  • The intralingual equivalence of the Italian version of the MARS was confirmed by the authors of the original scale. A total of 43 apps targeting primary prevention were tested. The MARS displayed acceptable psychometric properties. The MARS total score showed an excellent level of both inter-rater agreement (intra-class correlation coefficient of .96) and internal consistency (Cronbach’s α of .90 and .91 for the two raters, respectively). Other types of validity, including convergent, divergent, discriminative, known-groups and scalability, were also established.


  • The Italian version of MARS is a valid and reliable tool for assessing the health-related primary prevention apps available in Italian app stores.

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ID Code: 97580
Item Type: Journal Article
Refereed: Yes
Keywords: mHealth; Mobile application; Mobile application rating scale; Mobile health; Prevention
DOI: 10.1186/s12911-016-0323-2
ISSN: 1472-6947
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > PUBLIC HEALTH AND HEALTH SERVICES (111700)
Australian and New Zealand Standard Research Classification > PSYCHOLOGY AND COGNITIVE SCIENCES (170000)
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Psychology & Counselling
Copyright Owner: 2016 The authors
Copyright Statement: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.
Deposited On: 21 Jul 2016 07:04
Last Modified: 17 Nov 2016 04:14

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