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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.”
QUANTIFYING TEST-RETEST RELIABILITY USING THE INTRACLASS CORRELATION COEFFICIENT AND THE SEM
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“Interclass correlation coefficients (ICCs) [16-18] were used, as they provide weighted values of rater agreement and assess proximity rather than equality of ratings.”
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“The uMARS total score demonstrated good [16] levels of ICC of .”
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Mobile app rating scale: a new tool for assessing the quality of health mobile apps
Stoyanov, S. R., Hides, L., Kavanagh, D. J., Zelenko, O., Tjondronegoro, D., & Mani, M. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.3422 · Cited by 2,233 · cited 2×
“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].”
Self-citationFree, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001363 · Cited by 1,187
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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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Fiordelli, M., Diviani, N., & Schulz, P. J. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2430 · Cited by 570 · cited 1×
“While meta-analytic studies have demonstrated the efficacy of mHealth apps targeting physical activity and weight loss [6,7], the evidence base for other types of mHealth apps is poor at best [8-10].”
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Guo, Y., Yang, F., Hu, F., Li, W., Ruggiano, N., & Lee, H. Y. (2020) · JMIR Aging · doi:10.2196/18754 · Cited by 23
Children's Oncology Group KidsCare smartphone application for parents of children with cancer
Landier, W., González, P. D. C., Henneberg, H., York, J. M., Wadhwa, A., Adams, K., Madan‐Swain, A., Wolfson, J. A., Benton, B., Seidel, C., et al. (2023) · Pediatric Blood & Cancer · doi:10.1002/pbc.30288 · Cited by 22
“Median (range) 14 (2-32) 25 (20-32) 10 (2-30)”
Palmer, K. M., & Burrows, V. (2020) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-020-00160-9 · Cited by 26
“However, MARS requires training and expertise in the mental health field to administer it; therefore, Stoyanov et al. (2016) developed a simpler user version, uMARS.”
Tsang, K. C. H., Pinnock, H., Wilson, A. M., Salvi, D., & Shah, S. A. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-064166 · Cited by 23
“The survey combines validated questionnaires on usability and acceptance (SUS 40 and uMARS 41 ) with questions about motivations to use technology (mTEI 42 ) and desired features in an asthma management system.”
Quifer‐Rada, P., Aguilar‐Camprubí, L., Gómez-Sebastià, I., Padró‐Arocas, A., & Tudela, D. M. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105062 · Cited by 24
Liu, P., Li, X., & Zhang, X. M. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1220160 · Cited by 22
“Scales and questionnaires include the Mobile App Rating Scale (MARS) (17), the user version of the Mobile App Rating Scale (uMARS) (18), the System Usability Scale (SUS) (19), and self-designed questionnaires based on the Technology Acceptance Model (TAM) (20).”
Patient-Centered Chronic Wound Care Mobile Apps: Systematic Identification, Analysis, and Assessment
Dege, T., Glatzel, B., Borst, V., Grän, F., Goller, S. G., Glatzel, C. M., Goebeler, M., & Schmieder, A. (2024) · JMIR mhealth and uhealth · doi:10.2196/51592 · Cited by 22
“The user version of the MARS (uMARS) [12] was designed for users to evaluate the quality of mHealth apps.”
Khoury, C. F. E., Crutzen, R., Schols, J. M. G. A., Halfens, R. J. G., & Karavetian, M. (2020) · Journal of Medical Internet Research · doi:10.2196/17817 · Cited by 22
Imagery, Visualization, and Mental Simulation Interventions
Hagger, M. S., & Conroy, D. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.033 · Cited by 23
Changing Behavior Using the Common-Sense Model of Self-Regulation
Cameron, L. D., Fleszar‐Pavlović, S. E., & Khachikian, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.005 · Cited by 29
Laranjeira, C., Dixe, M. D. A., Martinho, R., Rijo, R., & Querido, A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.862347 · Cited by 21
The Interactive Mobile App Review Toolkit (IMART): a Clinical Practice-Oriented System
Maheu, M. M., Nicolucci, V., Pulier, M. L., Wall, K. M., Frye, T. J., & Hudlická, E. (2016) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-016-0005-z · Cited by 21
“Encouragingly, major progress towards generation of scientifically verifiable assessments was recently made by the Mobile Application Rating Scale (MARS) (Stoyanov et al., 2015; Stoyanov et al., 2016).”
Method of App Selection for Healthcare Providers Based on Consumer Needs
Lee, J., & JeongEun, K. (2017) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000000399 · Cited by 21
Knowledge Is Power: Improving Outcomes for Patients, Partners, and Professionals in the Digital Age
Ferguson, M., Maidment, D. W., Henshaw, H., & Gomez, R. (2019) · Perspectives of the ASHA Special Interest Groups · doi:10.1044/2018_pers-sig7-2018-0006 · Cited by 21
Dinkel, D. M., Caspari, J. H., Fok, L., Notice, M. R., Johnson, D. J., Watanabe‐Galloway, S., & Emerson, M. R. (2021) · Translational Behavioral Medicine · doi:10.1093/tbm/ibab075 · Cited by 21
“Patient participants were allowed 10-15 minutes to explore the app and then completed the user version of the Mobile Application Rating Scale (uMARS) [21].”
Rohde, J., Marciniak, M. A., Henninger, M., Homan, S., Ries, A., Paersch, C., Friedman, O. B., Brown, A. D., & Kleim, B. (2024) · PLoS ONE · doi:10.1371/journal.pone.0305103 · Cited by 20
Engagement of Stakeholders in the Design, Evaluation, and Implementation of Complex Interventions
Hudson, J. L., Moon, Z., Hughes, L. D., & Moss-Morris, R. E. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.024 · Cited by 20
Kruglova, K., O’Connell, S. B. L., Dawadi, S., Gelgoot, E. N., Miner, S. A., Robins, S., Schinazi, J., & Zelkowitz, P. (2021) · JMIR Formative Research · doi:10.2196/28136 · Cited by 20
German Mobile Apps for Patients With Psoriasis: Systematic Search and Evaluation
Lull, C., von Ahnen, J. A., Groß, G., Olsavszky, V., Knitza, J., Leipe, J., & Schmieder, A. (2022) · JMIR mhealth and uhealth · doi:10.2196/34017 · Cited by 20
Potzel, A. L., Gar, C., Banning, F., Sacco, V., Fritsche, A., Fritsche, L., Müssig, K., Dauben, L., Seissler, J., & Lechner, A. (2022) · PLOS ONE · doi:10.1371/journal.pone.0267258 · Cited by 20
Digital tools in allergy and respiratory care
Verhoeven, E. W. M., Rouadi, P. W., Abou-Jaoude, E. A., Abouzakouk, M., Ansotegui, I. J., Al-Ahmad, M. S., Al‐Nesf, M. A., Azar, C. R., Bahna, S. L., Cuervo‐Pardo, L., et al. (2022) · World Allergy Organization Journal · doi:10.1016/j.waojou.2022.100661 · Cited by 20
“Where the MARS rating scale requires training and expertise in mHealth in a particular relevant health field, the uMARS rating scale is a simplified version that can be reliable used by endusers without expertise.(33) The committee members feel that the existing (u)MARS scoring system is insufficient to determine the…”
Mental Health Mobile Apps in the French App Store: Assessment Study of Functionality and Quality
Carrouel, F., de Vigneulles, B. D. S., Bourgeois, D. M., Kabuth, B., Baltenneck, N., Nusbaum, F., Burge, V., Roy, S., Buchheit, S., Carrion-Martinaud, M.-L., et al. (2022) · JMIR mhealth and uhealth · doi:10.2196/41282 · Cited by 20
Technology-based supportive care for metastatic breast cancer patients
Schmitz, K. H., Kanski, B., Gordon, B. R., Caru, M., Vasakar, M., Truica, C. I., Wang, M., Doerksen, S. E., Lorenzo, A., Winkels, R., et al. (2023) · Supportive Care in Cancer · doi:10.1007/s00520-023-07884-3 · Cited by 20
Yaman, N. E., Zeitoun, J., Diab, R., Mdaihly, M., Diab, R., Kobeissi, L., Ljoud, S. A., Antoun, J., & Bardus, M. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02252-x · Cited by 22
“A total uMARS score is calculated as the mean of the scores of all sub-domains [47, 50].”
InfluentialUri Gneezy, B., Kajackaite, A., & Meier, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.036 · Cited by 20
Marshall, J. M., Dunstan, D. A., & Bartik, W. (2020) · JMIR Research Protocols · doi:10.2196/17159 · Cited by 24
“The Mobile Application Rating Scale-user version (uMARS) [54] is a 20-item questionnaire that records an individual’s rating on the quality of a mobile app.”
Mobile Apps for Wound Assessment and Monitoring: Limitations, Advancements and Opportunities
Kabir, M. A., Samad, S., Ahmed, F., Naher, S., Featherston, J., Laird, C., & Ahmed, S. F. (2024) · Journal of Medical Systems · doi:10.1007/s10916-024-02091-x · Cited by 19
“We developed a rating scale for evaluating wound apps by building upon and extending existing rating scales such as the Mobile Application Rating Scale (MARS) [32], uMARS [36], a mobile app rating tool for foot measurement (FootMARS) [34], FinMARS [37], and oth - ers [38–41].”
Feldman, A. G., Moore, S. L., Bull, S. S., Morris, M. A., Wilson, K. R., Bell, C., Collins, M. M., Denize, K. M., & Kempe, A. (2022) · JMIR Formative Research · doi:10.2196/32273 · Cited by 22
Shinohara, Y., Yamamoto, K., Ito, M., Sakata, M., Koizumi, S., Hashisako, M., Sato, M., Wannous, M., Stoyanov, S. R., Nakajima, J., et al. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2022.104809 · Cited by 19
Guan, V. X., Zhou, C., Wan, H., Zhou, R., Zhang, D., Zhang, S., Yang, W., Voutharoja, B. P., Wang, L., Win, K. T., et al. (2023) · JMIR Formative Research · doi:10.2196/46839 · Cited by 22
Sinclair, R., Nodi, S. S., & Kabir, M. A. (2023) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2023.108527 · Cited by 19
Ymeri, G., Salvi, D., Olsson, C. M., Wassenburg, M., Tsanas, A., & Svenningsson, P. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-077766 · Cited by 19
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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