Dataset Information

The Arabic Version of the Mobile App Rating Scale: Development and Validation Study.

ABSTRACT: BACKGROUND:With 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. OBJECTIVE:This 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. METHODS:We 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. RESULTS:MARS-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). CONCLUSIONS:MARS-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.

SUBMITTER: Bardus M

PROVIDER: S-EPMC7078658 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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The Arabic Version of the Mobile App Rating Scale: Development and Validation Study.

Bardus Marco M Awada Nathalie N Ghandour Lilian A LA Fares Elie-Jacques EJ Gherbal Tarek T Al-Zanati Tasnim T Stoyanov Stoyan R SR

JMIR mHealth and uHealth 20200303 3

<h4>Background</h4>With 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, Sp ...[more]

PMID: 32130183

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Project description:BackgroundIn the recent decades, the number of apps promoting health behaviors and health-related strategies and interventions has increased alongside the number of smartphone users. Nevertheless, the validity process for measuring and reporting app quality remains unsatisfactory for health professionals and end users and represents a public health concern. The Mobile Application Rating Scale (MARS) is a tool validated and widely used in the scientific literature to evaluate and compare mHealth app functionalities. However, MARS is not adapted to the French culture nor to the language.ObjectiveThis study aims to translate, adapt, and validate the equivalent French version of MARS (ie, MARS-F).MethodsThe original MARS was first translated to French by two independent bilingual scientists, and their common version was blind back-translated twice by two native English speakers, culminating in a final well-established MARS-F. Its comprehensibility was then evaluated by 6 individuals (3 researchers and 3 nonacademics), and the final MARS-F version was created. Two bilingual raters independently completed the evaluation of 63 apps using MARS and MARS-F. Interrater reliability was assessed using intraclass correlation coefficients. In addition, internal consistency and validity of both scales were assessed. Mokken scale analysis was used to investigate the scalability of both MARS and MARS-F.ResultsMARS-F had a good alignment with the original MARS, with properties comparable between the two scales. The correlation coefficients (r) between the corresponding dimensions of MARS and MARS-F ranged from 0.97 to 0.99. The internal consistencies of the MARS-F dimensions engagement (ω=0.79), functionality (ω=0.79), esthetics (ω=0.78), and information quality (ω=0.61) were acceptable and that for the overall MARS score (ω=0.86) was good. Mokken scale analysis revealed a strong scalability for MARS (Loevinger H=0.37) and a good scalability for MARS-F (H=0.35).ConclusionsMARS-F is a valid tool, and it would serve as a crucial aid for researchers, health care professionals, public health authorities, and interested third parties, to assess the quality of mHealth apps in French-speaking countries.

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:BackgroundMobile 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.ObjectiveThis study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.MethodsData 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.ResultsIn 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).ConclusionThe 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.

Project description:BackgroundSelecting and integrating health-related apps into patient care is impeded by the absence of objective guidelines for identifying high-quality apps from the many thousands now available.ObjectiveThis study aimed to evaluate the App Rating Inventory, which was developed by the Defense Health Agency's Connected Health branch, to support clinical decisions regarding app selection and evaluate medical and behavioral apps.MethodsTo enhance the tool's performance, eliminate item redundancy, reduce scoring system subjectivity, and ensure a broad application of App Rating Inventory-derived results, inventory development included 3 rounds of validation testing and 2 trial periods conducted over a 6-month interval. The development focused on content validity testing, dimensionality (ie, whether the tool's criteria performed as operationalized), factor and commonality analysis, and interrater reliability (reliability scores improved from 0.62 to 0.95 over the course of development).ResultsThe development phase culminated in a review of 248 apps for a total of 6944 data points and a final 28-item, 3-category app rating system. The App Rating Inventory produces scores for the following three categories: evidence (6 items), content (11 items), and customizability (11 items). The final (fourth) metric is the total score, which constitutes the sum of the 3 categories. All 28 items are weighted equally; no item is considered more (or less) important than any other item. As the scoring system is binary (either the app contains the feature or it does not), the ratings' results are not dependent on a rater's nuanced assessments.ConclusionsUsing predetermined search criteria, app ratings begin with an environmental scan of the App Store and Google Play. This first step in market research funnels hundreds of apps in a given disease category down to a manageable top 10 apps that are, thereafter, rated using the App Rating Inventory. The category and final scores derived from the rating system inform the clinician about whether an app is evidence informed and easy to use. Although a rating allows a clinician to make focused decisions about app selection in a context where thousands of apps are available, clinicians must weigh the following factors before integrating apps into a treatment plan: clinical presentation, patient engagement and preferences, available resources, and technology expertise.

Project description:BackgroundThe usability of mobile health (mHealth) apps needs to be effectively evaluated before they are officially approved to be used to deliver health interventions. To this end, the mHealth App Usability Questionnaire (MAUQ) has been designed and proved valid and reliable in assessing the usability of mHealth apps. However, this English questionnaire needs to be translated into other languages, adapted, and validated before being utilized to evaluate the usability of mHealth apps.ObjectiveThis study aims to improve, further adapt, and validate the Chinese version of the MAUQ (C-MAUQ; interactive for patients) on Left-handed Doctor, one of the most popular "reaching out to patients" interactive mHealth apps with chatbot function in China, to test the reliability and cross-cultural adaptability of the questionnaire.MethodsThe MAUQ (interactive for patients) has been translated into Chinese and validated for its reliability on Good Doctor, one of the most influential "reaching out to patients" mHealth apps without chatbot function in China. After asking for the researchers' approval to use this Chinese version, we adjusted and further adapted the C-MAUQ by checking it against the original English version and improving its comprehensibility, readability, idiomaticity, and cross-cultural adaptability. Following a trial survey completed by 50 respondents on wenjuanxing, the most popular online questionnaire platform in China, the improved version of the C-MAUQ (I-C-MAUQ) was finally used to evaluate the usability of Left-handed Doctor through an online questionnaire survey (answered by 322 participants) on wenjuanxing, to test its internal consistency, reliability, and validity.ResultsThe I-C-MAUQ still retained the 21 items and 3 dimensions of the original MAUQ: 8 items for usability and satisfaction, 6 items for system information arrangement, and 7 items for efficiency. The translation problems in the C-MAUQ, including (1) redundancy, (2) incompleteness, (3) misuse of parts of speech, (4) choice of inappropriate words, (5) incomprehensibility, and (6) cultural difference-induced improper translation, were improved. As shown in the analysis of data obtained through the online survey, the I-C-MAUQ had a better internal consistency (ie, the correlation coefficient between the score of each item and the total score of the questionnaire determined within the range of 0.861-0.938; P<.01), reliability (Cronbach α=.988), and validity (Kaiser-Meyer-Olkin=0.973), compared with the C-MAUQ. It was effectively used to test the usability of Left-handed Doctor, eliciting over 80% of informants' positive attitudes toward this mHealth app.ConclusionsThe I-C-MAUQ is highly reliable and valid for Left-handed Doctor, and suitable for testing the usability of interactive mHealth apps used by patients in China. This finding further confirms the cross-cultural validity, reliability, and adaptability of the MAUQ. We identified certain factors influencing the perceived usability of mHealth apps, including users' age, gender, education, profession, and possibly previous experience with mHealth apps and the chatbot function of such apps. Most notably, we found a wider acceptance of this new technology among young Chinese female college students who were more engaged in the interaction with health care chatbots. The age-, gender-, and profession-induced preference for new digital health interventions in China aligns with the findings in other similar studies in America and Malaysia. This preference identifies areas for further research on the social, cultural, and gender adaptation of health technologies.

Project description:BackgroundThe success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity.ObjectiveWe aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring.MethodsA systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent).ResultsOverall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6).ConclusionsThe quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.

Dataset Information

The Arabic Version of the Mobile App Rating Scale: Development and Validation Study.

Publications

The Arabic Version of the Mobile App Rating Scale: Development and Validation Study.

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