Department of Research Methods, Institute of Psychology and Education, University Ulm, Ulm, Germany.
Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University Ulm, Ulm, Germany.
PLoS One. 2020 Nov 2;15(11):e0241480. doi: 10.1371/journal.pone.0241480. eCollection 2020.
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. Instruments 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. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity.
This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.
Data was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation.
In total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (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). MARS correlated with ENLIGHT (ps<.05).
The metric evaluation of the MARS demonstrated its suitability for the quality assessment. 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.
移动健康应用（MHA）有改善医疗保健的潜力。商业 MHA 市场正在迅速增长，但可用 MHA 的内容和质量尚不清楚。因此非常需要用于评估 MHA 质量和内容的工具。移动应用程序评级量表（MARS）是评估 MHA 质量的最广泛使用的工具之一。只有少数验证研究调查了其度量质量。没有研究评估其构建有效性和同时有效性。
本研究评估 MARS 的构建有效性、同时有效性、可靠性和客观性。
数据来自 15 项国际应用程序质量评估，以评估 MARS 的度量属性。MARS 通过四个维度评估应用程序质量：参与度、功能性、美观性和信息质量。通过验证性因子分析（CFA）评估相关竞争的确认性模型来评估构建有效性。非中心性（RMSEA）、增量（CFI、TLI）和残差（SRMR）拟合指数用于评估拟合度。作为同时有效性的衡量标准，研究了与另一种质量评估工具（ENLIGHT）的相关性。可靠性通过 Omega 确定。客观性通过组内相关系数评估。
共纳入了 1,299 种涵盖 15 种不同健康领域的 MHA 的 MARS 评分。验证性因子分析证实了具有一般因素和每个维度因素的双因素模型（RMSEA = 0.074，TLI = 0.922，CFI = 0.940，SRMR = 0.059）。可靠性良好到优秀（Omega 0.79 到 0.93）。客观性高（ICC = 0.82）。MARS 与 ENLIGHT 相关（p<.05）。
MARS 的度量评估表明其适合于质量评估。因此，MARS 可以用于使医疗保健利益相关者和患者了解 MHA 的质量。未来的研究可以通过调查 MARS 的重测可靠性和预测有效性来扩展本研究结果。
