Dataset Information

Validation of the Mobile Application Rating Scale (MARS).

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. 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.

SUBMITTER: Terhorst Y

PROVIDER: S-EPMC7605637 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Validation of the Mobile Application Rating Scale (MARS).

Terhorst Yannik Y Philippi Paula P Sander Lasse B LB Schultchen Dana D Paganini Sarah S Bardus Marco M Santo Karla K Knitza Johannes J Machado Gustavo C GC Schoeppe Stephanie S Bauereiß Natalie N Portenhauser Alexandra A Domhardt Matthias M Walter Benjamin B Krusche Martin M Baumeister Harald H Messner Eva-Maria EM

PloS one 20201102 11

<h4>Background</h4>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 co ...[more]

PMID: 33137123

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Project description:BackgroundApproximately 110 million Farsi speakers worldwide have access to a growing mobile app market. Despite restrictions and international sanctions, Iran's internal mobile health app market is growing, especially for Android-based apps. However, there is a need for guidelines for developing health apps that meet international quality standards. There are also no tools in Farsi that assess health app quality. Developers and researchers who operate in Farsi could benefit from such quality assessment tools to improve their outputs.ObjectiveThis study aims to translate and culturally adapt the Mobile Application Rating Scale in Farsi (MARS-Fa). This study also evaluates the validity and reliability of the newly developed MARS-Fa tool.MethodsWe used a well-established method to translate and back translate the MARS-Fa tool with a group of Iranian and international experts in Health Information Technology and Psychology. The final translated version of the tool was tested on a sample of 92 apps addressing smartphone addiction. Two trained reviewers completed an independent assessment of each app in Farsi and English. We reported reliability and construct validity estimates for the objective scales (engagement, functionality, aesthetics, and information quality). Reliability was based on the evaluation of intraclass correlation coefficients, Cronbach α and Spearman-Brown split-half reliability indicators (for internal consistency), as well as Pearson correlations for test-retest reliability. Construct validity included convergent and discriminant validity (through item-total correlations within the objective scales) and concurrent validity using Pearson correlations between the objective and subjective scores.ResultsAfter completing the translation and cultural adaptation, the MARS-Fa tool was used to assess the selected apps for smartphone addiction. The MARS-Fa total scale showed good interrater reliability (intraclass correlation coefficient=0.83, 95% CI 0.74-0.89) and good internal consistency (Cronbach α=.84); Spearman-Brown split-half reliability for both raters was 0.79 to 0.93. The instrument showed excellent test-retest reliability (r=0.94). The correlations among the MARS-Fa subdomains and the total score were all significant and above r=0.40, suggesting good convergent and discriminant validity. The MARS-Fa was positively and significantly correlated with subjective quality (r=0.90, P<.001), and so were the objective subdomains of engagement (r=0.85, P<.001), information quality (r=0.80, P<.001), aesthetics (r=0.79, P<.001), and functionality (r=0.57, P<.001), indicating concurrent validity.ConclusionsThe MARS-Fa is a reliable and valid instrument to assess mobile health apps. This instrument could be adopted by Farsi-speaking researchers and developers who want to evaluate the quality of mobile apps. While we tested the tool with a sample of apps addressing smartphone addiction, the MARS-Fa could assess other domains or issues since the Mobile App Rating Scale has been used to rate apps in different contexts and languages.

Project description:BACKGROUND:Chronic rheumatic diseases need long-term treatment and professional supervision. Mobile apps promise to improve the lives of patients and physicians. In routine practice, however, rheumatology apps are largely unknown and little is known about their quality and safety. OBJECTIVE:The aim of this study was to provide an overview of mobile rheumatology apps currently available in German app stores, evaluate app quality using the Mobile Application Rating Scale (MARS), and compile brief, ready-to-use descriptions for patients and rheumatologists. METHODS:The German App Store and Google Play store were systematically searched to identify German rheumatology mobile apps for patient and physician use. MARS was used to independently assess app quality by 8 physicians, 4 using Android and 4 using iOS smartphones. Apps were randomly assigned so that 4 apps were rated by all raters and the remaining apps were rated by two Android and two iOS users. Furthermore, brief app descriptions including app developers, app categories, and features were compiled to inform potential users and developers. RESULTS:In total, 128 and 63 apps were identified in the German Google Play and App Store, respectively. After removing duplicates and only including apps that were available in both stores, 28 apps remained. Sixteen apps met the inclusion criteria, which were (1) German language, (2) availability in both app stores, (3) targeting patients or physicians as users, and (4) clearly including rheumatology or rheumatic diseases as subject matter. Exclusion criteria were (1) congress apps and (2) company apps with advertisements. Nine apps addressed patients and 7 apps addressed physicians. No clinical studies to support the effectiveness and safety of apps could be found. Pharmaceutical companies were the main developers of two apps. Rheuma Auszeit was the only app mainly developed by a patient organization. This app had the highest overall MARS score (4.19/5). Three out of 9 patient apps featured validated questionnaires. The median overall MARS score was 3.85/5, ranging from 2.81/5 to 4.19/5. One patient-targeted and one physician-targeted app had MARS scores >4/5. No significant rater gender or platform (iOS/Android) differences could be observed. The overall correlation between app store ratings and MARS scores was low and inconsistent between platforms. CONCLUSIONS:To our knowledge, this is the first study that systematically identified and evaluated mobile apps in rheumatology for patients and physicians available in German app stores. We found a lack of supporting clinical studies, use of validated questionnaires, and involvement of academic developers. Overall app quality was heterogeneous. To create high-quality apps, closer cooperation led by patients and physicians is vital.

Project description:BACKGROUND:The large number of available cancer apps and their impact on the population necessitates a transparent, objective, and comprehensive evaluation by app experts, health care professionals, and users. To date, there have been no analyses or classifications of apps for patients with genitourinary cancers, which are among the most prevalent types of cancer. OBJECTIVE:The objective of our study was to analyze the quality of apps for patients diagnosed with genitourinary cancers using the Mobile Application Rating Scale (MARS) and identify high-quality apps. METHODS:We performed an observational cross-sectional descriptive study of all smartphone apps for patients diagnosed with genitourinary cancers available on iOS and Android platforms. In July 2019, we searched for all available apps for patients with genitourinary cancers (bladder, prostate, cervical, uterine, endometrial, kidney, testicular, and vulvar) or their caregivers. Apps were downloaded and evaluated, and the general characteristics were entered into a database. The evaluation was performed by 2 independent researchers using the MARS questionnaire, which rates 23 evaluation criteria clustered in 5 domains (Engagement, Functionality, Esthetics, Information, and Subjective Quality) on a scale from 1 to 5. RESULTS:In total, 46 apps were analyzed. Of these, 31 (67%) were available on Android, 6 (13%) on iOS, and 9 (20%) on both platforms. The apps were free in 89% of cases (41/46), and 61% (28/46) had been updated in the previous year. The apps were intended for prostate cancer in 30% of cases (14/46) and cervical cancer in 17% (8/46). The apps were mainly informative (63%, 29/46), preventive (24%, 11/46), and diagnostic (13%, 6/46). Only 7/46 apps (15%) were developed by health care organizations. The mean MARS score for the overall quality of the 46 apps was 2.98 (SD 0.77), with a maximum of 4.63 and a minimum of 1.95. Functionality scores were quite similar for most of the apps, with the greatest differences in Engagement and Esthetics, which showed acceptable scores in one-third of the apps. The 5 apps with the highest MARS score were the following: "Bladder cancer manager," "Kidney cancer manager," "My prostate cancer manager," "Target Ovarian Cancer Symptoms Diary," and "My Cancer Coach." We observed statistically significant differences in the MARS score between the operating systems and the developer types (P<.001 and P=.01, respectively), but not for cost (P=.62). CONCLUSIONS:MARS is a helpful methodology to decide which apps can be prescribed to patients and to identify which features should be addressed to improve these tools. Most of the apps designed for patients with genitourinary cancers only try to provide data about the disease, without coherent interactivity. The participation of health professionals in the development of these apps is low; nevertheless, we observed that both the participation of health professionals and regular updates were correlated with quality.

Project description:BackgroundOver the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being.ObjectiveThis paper presents an Artificial Intelligence (AI)-enabled mHealth app rating tool, called ACCU3RATE, which takes multidimensional measures such as user star rating, user review and features declared by the developer to generate the rating of an app. However, currently, there is very little conceptual understanding on how user reviews affect app rating from a multi-dimensional perspective. This study applies AI-based text mining technique to develop more comprehensive understanding of user feedback based on several important factors, determining the mHealth app ratings.MethodBased on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user star rating, user text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users' sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer's statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score.Results and conclusionsACCU3RATE concentrates on heart related Apps found in the play store and App gallery. The findings indicate the efficacy of the proposed method as opposed to the current device scale. This study has implications for both App developers and consumers who are using mHealth Apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has also been noticed that the fuzzy based rating scale, as in ACCU3RATE, matches more closely to the rating performed by experts.

Project description:BackgroundWith thousands of health apps in app stores globally, it is crucial to systemically and thoroughly evaluate the quality of these apps due to their potential influence on health decisions and outcomes. The Mobile App Rating Scale (MARS) is the only currently available tool that provides a comprehensive, multidimensional evaluation of app quality, which has been used to compare medical apps from American and European app stores in various areas, available in English, Italian, Spanish, and German. However, this tool is not available in Arabic.ObjectiveThis study aimed to translate and adapt MARS to Arabic and validate the tool with a sample of health apps aimed at managing or preventing obesity and associated disorders.MethodsWe followed a well-established and defined "universalist" process of cross-cultural adaptation using a mixed methods approach. Early translations of the tool, accompanied by confirmation of the contents by two rounds of separate discussions, were included and culminated in a final version, which was then back-translated into English. Two trained researchers piloted the MARS in Arabic (MARS-Ar) with a sample of 10 weight management apps obtained from Google Play and the App Store. Interrater reliability was established using intraclass correlation coefficients (ICCs). After reliability was ascertained, the two researchers independently evaluated a set of additional 56 apps.ResultsMARS-Ar was highly aligned with the original English version. The ICCs for MARS-Ar (0.836, 95% CI 0.817-0.853) and MARS English (0.838, 95% CI 0.819-0.855) were good. The MARS-Ar subscales were highly correlated with the original counterparts (P<.001). The lowest correlation was observed in the area of usability (r=0.685), followed by aesthetics (r=0.827), information quality (r=0.854), engagement (r=0.894), and total app quality (r=0.897). Subjective quality was also highly correlated (r=0.820).ConclusionsMARS-Ar is a valid instrument to assess app quality among trained Arabic-speaking users of health and fitness apps. Researchers and public health professionals in the Arab world can use the overall MARS score and its subscales to reliably evaluate the quality of weight management apps. Further research is necessary to test the MARS-Ar on apps addressing various health issues, such as attention or anxiety prevention, or sexual and reproductive health.

Dataset Information

Validation of the Mobile Application Rating Scale (MARS).

Publications

Validation of the Mobile Application Rating Scale (MARS).

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