Psychometric evaluation of the Mobile Application Rating Scale (MARS) (Preprint)

Author:

Terhorst YannikORCID,Philippi PaulaORCID,Sander LasseORCID,Schultchen DanaORCID,Paganini SarahORCID,Bardus MarcoORCID,Santo KarlaORCID,Knitza JohannesORCID,Machado GustavoORCID,Schoeppe StephanieORCID,Bauereiß NatalieORCID,Portenhauser AlexandraORCID,Domhardt MatthiasORCID,Walter BenjaminORCID,Krusche MartinORCID,Baumeister HaraldORCID,Messner Eva MariaORCID

Abstract

BACKGROUND

Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Consequently, instruments of high psychometric quality for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA in various health domains. Only few validation studies investigating its psychometric quality exist with selected samples of MHAs. No study has evaluated the construct validity of the MARS and concurrent validity to other instruments.

OBJECTIVE

This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.

METHODS

MARS scoring data was pooled from 15 international app quality reviews to evaluate the psychometric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. App quality is determined for each dimension and overall. Construct validity was evaluated by assessing related competing confirmatory models that were explored by confirmatory factor analysis (CFA). A combination of non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices was used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations between the MARS and 1) another quality assessment tool called ENLIGHT, and 2) user star-rating extracted from app stores were investigated. Reliability was determined using Omega. Objectivity was assessed in terms of intra-class correlation.

RESULTS

In total, MARS ratings from 1,299 MHA covering 15 different health domains were pooled for the analysis. Confirmatory factor analysis confirmed a bifactor model with a general quality factor and an additional factor for each subdimension (RMSEA=0.074, TLI=0.922, CFI=0.940, SRMR=0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC=0.82). The overall MARS rating was positively associated with ENLIGHT (r=0.91, P<0.01) and user-ratings (r=0.14, P<0.01).

CONCLUSIONS

he psychometric evaluation of the MARS demonstrated its suitability for the quality assessment of MHAs. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS.

Publisher

JMIR Publications Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3