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Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS)
Open accessAbstract
BACKGROUND: The Mobile Application Rating Scale (MARS) provides a reliable method to assess the quality of mobile health (mHealth) apps. However, training and expertise in mHealth and the relevant health field is required to administer it. OBJECTIVE: This study describes the development and reliability testing of an end-user version of the MARS (uMARS). METHODS: The MARS was simplified and piloted with 13 young people to create the uMARS. The internal consistency and test-retest reliability of the uMARS was then examined in a second sample of 164 young people participating in a randomized controlled trial of a mHealth app. App ratings were collected using the uMARS at 1-, 3,- and 6-month follow up. RESULTS: The uMARS had excellent internal consistency (alpha = .90), with high individual alphas for all subscales. The total score and subscales had good test-retest reliability over both 1-2 months and 3 months. CONCLUSIONS: The uMARS is a simple tool that can be reliably used by end-users to assess the quality of mHealth apps.
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“The internal consistency and test–retest reliability of the uMARS total score and subscales were shown as excellent in the RCT (Cronbach’s alpha = 0.90) (46).”
From Improving mental well-being in psychocardiology—a feasibility trial for a non-blended web application as a brief metacognitive-based intervention in cardiovascular disease patients (2023) · cites this paper as [46]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Overall, the uMARS demonstrates good internal reliability (α = 0.90), and the subscales demonstrate moderate reliability (α = 0.71 and 0.80) (Stoyanov et al., 2016).”
From Pilot study of a well-being app to support New Zealand young people during the COVID-19 pandemic (2021) · cites this paper as Stoyanov et al., 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The usability and acceptability of the technology were assessed using qualitative methods and standard measures, such as the survey based on the Unified Theory of Acceptance and Use of Technology [27], the Mobile Application Rating Scale [28], and the System Usability and After-Scenario Questionnaire [29].”
From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [28]
In the citing paper
“Both MARS and uMARS included some usability components such as engagement, functionality, and information quality; however, they were not specifically designed to study usability with end users.”
From The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study (2019) · cites this paper as [37]
In the citing paper
“Shortly thereafter, a simpler user version of MARS (uMARS) was created for the general population for the same purpose [37].”
From The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study (2019) · cites this paper as [37]
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Citations
Cites
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“Readability of the MARS and the draft uMARS was then determined using the Flesch Reading Ease test [12,13], which has a score range of 0-100, with higher scores indicating easier readability.”
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Mobile app rating scale: a new tool for assessing the quality of health mobile apps
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“In response to these issues, we developed the Mobile App Rating Scale (MARS) to provide researchers, professionals, and clinicians with a brief tool for classifying and assessing the quality of mHealth apps [11].”
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“There are currently more than 165,000 mHealth apps (free and paid) publicly available [1], yet the accuracy of the health information contained in these apps is not scrutinized by regulatory bodies [2], which could compromise user health and safety [3-5].”
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Pazo, P. G., Fornés‐Vives, J., & Sesé, A. (2024) · Nursing Research and Practice · doi:10.1155/2024/8836672 · Cited by 4
Lessons Learned in Selection and Review of Depression Apps for Primary Care Settings
Emerson, M. R., Watanabe‐Galloway, S., Dinkel, D. M., Kotcherlakota, S., & Fok, L. (2020) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-020-00156-5 · Cited by 4
Wiemker, V., Bunova, A., Neufeld, M., Gornyi, B., Yurasova, E., Konigorski, S., Калинина, А. М., Васильевна, К. А., Ferreira‐Borges, C., & Probst, C. (2022) · Digital Health · doi:10.1177/20552076211074491 · Cited by 4
“Three modes of data collection were used (Figure 2): (i) Data recorded during patients ’ completion of the AAA-Tool, (ii) patients ’ and practitioners ’ perspective on region-speci fi c content as evaluated in brief semi-structured interviews; and (iii) patients ’ and practitioners ’ acceptability ratings of the tool a…”
Promoting Mental Wellbeing in Young People Aged 12–18 Years: Opportunities for Design
Taylor, A., Leslie, S., & Boddie, K. (2017) · Electronic workshops in computing · doi:10.14236/ewic/hci2017.33 · Cited by 4
Usability Test of Serious Game Robot App for Hospitalized Children
Jinmeiling, & Kim, J. (2019) · Journal of the Korea Academia-Industrial cooperation Society · doi:10.5762/kais.2019.20.2.228 · Cited by 4
“4 연구도구 개발된 앱의 사용성 평가는 Stoyanov et al.[13-14]가 개발한 전문가용 Mobile Application Rating Scale (MARS)와 사용자용 Mobile Application Rating Scale: user version (uMARS)의 한국판 연구도구를 사용하였 다.”
InfluentialProstate Cancer Risk Calculator Apps in a Taiwanese Population Cohort: Validation Study
Chen, I., Chu, C., Lin, J., Tsai, J., Yu, C., Sridhar, A. N., Sooriakumaran, P., Loureiro, R. C. V., & Chand, M. (2020) · Journal of Medical Internet Research · doi:10.2196/16322 · Cited by 4
Stress and job satisfaction of clinical laboratory scientists.
Rogers, D. A. (1983) · PubMed · Cited by 4
Sathe, C. M., Raghunathan, R. R., Ulene, S. R., McAuley, F. M., Bhatt, K. A., McGuinness, J. E., Trivedi, M. S., Vasan, N., Kalinsky, K. M., Crew, K. D., et al. (2024) · JCO Oncology Practice · doi:10.1200/op.24.00187 · Cited by 3
Applying the uMars Scale to Evaluate a Mindfulness-based mHealth App
Panguluri, L., Vigil-Hayes, M., & Amresh, A. (2024) · SeGAH ... IEEE ... International Conference on Serious Games and Applications for Health/IEEE International Conference on Serious Games and Applications for Health · doi:10.1109/segah61285.2024.10639604 · Cited by 3
Mobile health apps: Current state, barriers, and future directions
Kao, C., Moawad, A., & Bhargava, A. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-15728-8.00019-7 · Cited by 3
Haley, J. A., Rhind, D. J. A., & Maidment, D. W. (2025) · PLoS ONE · doi:10.1371/journal.pone.0321109 · Cited by 4
“The first phase began by creating a formative categorisation matrix with four pre-set categories based on components within the User Version of the Mobile Application Rating Scale (uMARS) [54] to identify patterns of meaning in the data and support researcher understanding.”
Syam, A., Dewi, I., Firawati, F., Darwis, D., & Iskandar, I. (2025) · SAGE Open Nursing · doi:10.1177/23779608251337122 · Cited by 4
Salvi, D., Olsson, C. M., Molloy, J., & Orchard, E. (2025) · JMIR Formative Research · doi:10.2196/70495 · Cited by 4
van Beurden, S. B., Cross, R., McDonagh, S. T. J., Clark, L., Thomas, C. R., Greaves, C. J., Doherty, P., Taylor, R. S., & Dalal, H. M. (2025) · Digital Health · doi:10.1177/20552076251406545 · Cited by 3
Quality Assessment of Smartphone Medication Management Apps in France: Systematic Search
Toïgo, M., Marc, J., Hayot, M., Moulis, L., & Carbonnel, F. (2024) · JMIR mhealth and uhealth · doi:10.2196/54866 · Cited by 3
“App evaluation by patients with the user version of the MARS [52] would be relevant, even though there is currently no validated French version of this scale.”
Chen, T. H., Lee, S., & Ma, W. (2024) · JMIR Formative Research · doi:10.2196/51076 · Cited by 3
“Stoyanov et al [20] developed the uMARS in 2016, which showed excellent internal consistency (Cronbach α =0.90).”
InfluentialOrellano-Colón, E. M., Fernández-Torres, A. M., Figueroa-Alvira, N., Ortiz-Vélez, B., Rivera-Rivera, N. L., Torres-Ferrer, G. A., & Martín‐Payo, R. (2024) · Disabilities · doi:10.3390/disabilities4020020 · Cited by 3
“One of the most comprehensive and multidimensional tools to evaluate app quality is the User Mobile App Rating Scale (uMARS) [23].”
Meidani, Z., Omidvar, A., Akbari, H., Asghari, F., Khajouei, R., Nazemi, Z., Nabovati, E., & Holl, F. (2024) · JMIR Human Factors · doi:10.2196/55790 · Cited by 3
“MARS is the most popular scale and a highly reliable tool designed to assist researchers, professionals, and clinicians in classifying and assessing the quality of mHealth apps [25].”
Usability Assessment Methods for Mobile Apps for Physical Rehabilitation: Umbrella Review
Hach, S., Alder, G., Stavric, V., Taylor, D., & Signal, N. (2024) · JMIR mhealth and uhealth · doi:10.2196/49449 · Cited by 6
“%) instruments [56,57,64,70-72, 83,84] were included in the Further, 8 (67”
Williams, C. J., Varnfield, M., Stott, A., & Duff, J. S. (2024) · Perioperative Care and Operating Room Management · doi:10.1016/j.pcorm.2024.100415 · Cited by 3
Fischer, A., Aguayo, G., Pinker, I., Oustric, P., Lachaise, T., Wilmes, P., Larche, J., Benoy, C., & Fagherazzi, G. (2024) · Digital Health · doi:10.1177/20552076241272671 · Cited by 3
Borsoi, L., Listorti, E., & Ciani, O. (2024) · PharmacoEconomics - Open · doi:10.1007/s41669-024-00519-1 · Cited by 3
“The questionnaire was developed starting from two previously validated questionnaires, namely the standalone version of the mHealth Apps Usability Questionnaire (MAUQ) for patients [48] and the user version of the Mobile App Rating Scale (uMARS) [49].”
Usability of a Mobile Application for Patients with Parkinson’s Disease
Ymeri, G., Maus, B., Wassenburg, M., Olsson, C. M., Svenningsson, P., & Salvi, D. (2024) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc53108.2024.10782276 · Cited by 3
“Through a combination of the User Version of the Mobile Application Rating Scale (uMARS) questionnaire [13] and semi-structured interviews, our study reports on the usability of a smartphone app for collecting data from patients using smartphones in home environments.”
Toh, S. H., Davis, C., Khaider, K. B., Ong, Z. Q., Lim, E. J. K., & Chew, C. S. E. (2025) · JMIR Research Protocols · doi:10.2196/59238 · Cited by 3
“Specifically, the usability and acceptability of the mHealth app will be assessed using the validated Mobile App Rating Scale (uMARS) [5] and by self-monitoring of patient-centric outcome measures as determined in the primary aim.”
Ourang, S. A., Sohrabniya, F., Sadr, S., Kahler, B., & Ha, W. N. (2025) · International Endodontic Journal · doi:10.1111/iej.14219 · Cited by 3
“The mean app quality score was determined based on these ratings, while subjective quality and perceived impact scores were reported separately (Stoyanov et al., 2016).”
Kavanagh, M. E., Chiavaroli, L., Quibrantar, S. M., Viscardi, G., Ramboanga, K., Amlin, N., Paquette, M. A., Sahye‐Pudaruth, S., Patel, D., Grant, S., et al. (2025) · JMIR Cardio · doi:10.2196/58124 · Cited by 3
“…to mHealth apps, future evaluations of the PortfolioDiet.app administering questionnaires could include the user-oriented Mobile Application Rating Scale or the recently validated mHealth App Usability Questionnaire, which includes additional questions to integrate feedback on app features [55,56].”
Eisner, E., Agass, R., Camacho, E. M., Falana, A., Hann, M., Ifezue, A., Lemetyinen, H., Myers, H., Stockton-Powdrell, C., Tower, C. L., et al. (2025) · Pilot and Feasibility Studies · doi:10.1186/s40814-025-01631-7 · Cited by 3
Martínez‐García, L., Mendizabal, J. B., Santos-Goñi, M. A., Miralles, I., & Osma, J. (2025) · Digital Health · doi:10.1177/20552076251334442 · Cited by 3
“Thus, participants completed MARS, 48,49 uMARS, 50,51 and SUS 52,53 scales, and two focus groups were carried out.”
Côté, J., Auger, P., Chicoine, G., Cheng, J., Cossette, S., Fontaine, G., Genest, C., Lal, S., Lapierre, J., Pagé, M. G., et al. (2025) · JMIR Formative Research · doi:10.2196/71924 · Cited by 3
“After each interview, participants were invited to complete a short online sociodemographic questionnaire and the uMARS [33].”
InfluentialMoungui, H. C., Iyawa, P. T., Nana-Djeunga, H. C., Ruiz-Postigo, J. A., & Carrión, C. (2025) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0013461 · Cited by 3
Veterans’ Insights on Heart Rate Variability Biofeedback to Treat Fibromyalgia-Related Pain
Reneau, M. G., & Nichols, M. G. (2021) · Pain Management Nursing · doi:10.1016/j.pmn.2021.06.003 · Cited by 3
Helseth, S. A., Guigayoma, J. P., Price, D., Spirito, A., Clark, M. A., Barnett, N. P., & Becker, S. J. (2022) · JMIR Research Protocols · doi:10.2196/35402 · Cited by 4
German Mobile Apps for Patients with Psoriatic Arthritis: Systematic App Search and Content Analysis
Groß, G., Lull, C., von Ahnen, J. A., Olsavszky, V., Knitza, J., Schmieder, A., & Leipe, J. (2022) · Health Policy and Technology · doi:10.1016/j.hlpt.2022.100697 · Cited by 3
Iqbal, M. N., Nurrahmawati, E. D., & Husin, H. (2023) · JTIM Jurnal Teknologi Informasi dan Multimedia · doi:10.35746/jtim.v5i1.330 · Cited by 4
Thematic analysis of google play reviews of lifestyle apps
Keller, V., & Ercsey, I. (2023) · Human Technology · doi:10.14254/1795-6889.2023.19-1.6 · Cited by 3
“…et al., 2013), error and user evaluation (Bavota et al., 2015), the features of nutrition apps in detail (Briggs et al., 2021), the quality factors (Stoyanov et al., 2015, 2016), gamification (Schmindt-Kraepelin et al., 2020), and the user-documented food consumption data (Maringer et al., 2018).”
Johnson, R. W., White, B. K., Gibson, N., Gucciardi, D. F., & Williams, S. A. (2023) · Physical & Occupational Therapy In Pediatrics · doi:10.1080/01942638.2023.2263576 · Cited by 3
“…was measured with the Mobile Application Rating Scale - User Version (uMARS) by the parents, therapists, and teachers of participating children (Stoyanov et al., 2016). uMARS was not used with participating children because the reading requirement exceeded that expected of children 6–12 years…”
Metadata
- Authors
- Stoyanov, S. R., Hides, L., Kavanagh, D. J., & Wilson, H.
- Affiliations
- Queensland University of Technology (AU)
- Corresponding author
- Hides, Leanne
- Venue
- JMIR mhealth and uhealth
- Publisher
- JMIR Publications Inc.
- Published
- 2016-06-10
- Volume
- 4
- Issue
- 2
- Pages
- e72
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC4920963
- OpenAlex
- W2415928823
- Cited by
- 872
- References
- 14
- Citations by year
- 2026: 95 · 2025: 135 · 2024: 138 · 2023: 108 · 2022: 107 · 2021: 89 · 2020: 103 · 2019: 51 · 2018: 28 · 2017: 14 · 2016: 3
- FWCI
- 59.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Faculty of Health; Institute of Health and Biomedical Innovation
- Funders
- Queensland University of Technology
- Young and Well Cooperative Research Centre
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- Mobile App Rating Scale, Umar, mobile health apps, app quality assessment, youth, internal consistency, test-retest reliability, scale development, app ratings
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