Validation of the Mobile Application Rating Scale (MARS)
Standard
Validation of the Mobile Application Rating Scale (MARS). / Terhorst, Yannik; Philippi, Paula; Sander, Lasse B; Schultchen, Dana; Paganini, Sarah; Bardus, Marco; Santo, Karla; Knitza, Johannes; Machado, Gustavo C; Schoeppe, Stephanie; Bauereiß, Natalie; Portenhauser, Alexandra; Domhardt, Matthias; Walter, Benjamin; Krusche, Martin; Baumeister, Harald; Messner, Eva-Maria.
In: PLOS ONE, Vol. 15, No. 11, e0241480, 2020.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - Validation of the Mobile Application Rating Scale (MARS)
AU - Terhorst, Yannik
AU - Philippi, Paula
AU - Sander, Lasse B
AU - Schultchen, Dana
AU - Paganini, Sarah
AU - Bardus, Marco
AU - Santo, Karla
AU - Knitza, Johannes
AU - Machado, Gustavo C
AU - Schoeppe, Stephanie
AU - Bauereiß, Natalie
AU - Portenhauser, Alexandra
AU - Domhardt, Matthias
AU - Walter, Benjamin
AU - Krusche, Martin
AU - Baumeister, Harald
AU - Messner, Eva-Maria
PY - 2020
Y1 - 2020
N2 - 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. 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.OBJECTIVE: This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.METHODS: 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.RESULTS: 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).CONCLUSION: 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.
AB - 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. 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.OBJECTIVE: This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.METHODS: 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.RESULTS: 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).CONCLUSION: 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.
KW - Factor Analysis, Statistical
KW - Humans
KW - Mobile Applications/standards
KW - Models, Theoretical
KW - Reproducibility of Results
KW - Telemedicine
U2 - 10.1371/journal.pone.0241480
DO - 10.1371/journal.pone.0241480
M3 - SCORING: Journal article
C2 - 33137123
VL - 15
JO - PLOS ONE
JF - PLOS ONE
SN - 1932-6203
IS - 11
M1 - e0241480
ER -
