The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532 · cited 1×
“Interclass correlation coefficients (ICCs) [16-18] were used, as they provide weighted values of rater agreement and assess proximity rather than equality of ratings.”
Flesch, R. (1948) · Journal of Applied Psychology · doi:10.1037/h0057532 · Cited by 5,391 · cited 1×
“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
Weir, J. P. (2005) · The Journal of Strength and Conditioning Research · doi:10.1519/15184.1 · Cited by 4,864 · cited 1×
“Interclass correlation coefficients (ICCs) [16-18] were used, as they provide weighted values of rater agreement and assess proximity rather than equality of ratings.”
Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial
Hallgren, K. A. (2012) · Tutorials in Quantitative Methods for Psychology · doi:10.20982/tqmp.08.1.p023 · Cited by 3,884 · cited 3×
“The uMARS total score demonstrated good [16] levels of ICC of .”
Kincaid, J. P., Fishburne, Jr., Robert P., R., Richard L., C., & Brad, S. (1975) · doi:10.21236/ada006655 · Cited by 3,497
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
Andersson, G., Cuijpers, P., Carlbring, P., Riper, H., & Hedman, E. (2014) · World Psychiatry · doi:10.1002/wps.20151 · Cited by 1,077 · cited 1×
“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].”
Mapping mHealth research: a decade of evolution
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].”
Review and evaluation of mindfulness-based iPhone apps
Mani, M., Kavanagh, D. J., Hides, L., & Stoyanov, S. R. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4328 · Cited by 495
Research works printed but not linked: 1
- SuWA preliminary survey of knowledge discovery on smartphone applications (apps): Principles, techniques and research directions for e-healtharXiv preprint arXiv20140626International Conference on Complex Medical EngineeringJune 26-29, 2014Taipei, Taiwan14077314
Cited by
Sorted by citations
Items 301–400 of 870
Minaei-Moghadam, S., Manzari, Z. S., Vaghee, S., & Mirhosseini, S. (2024) · BMC Public Health · doi:10.1186/s12889-023-17594-4 · Cited by 10
Kruzan, K. P., Biernesser, C. L., Hoffmann, J. A., & Meyerhoff, J. (2024) · Current Treatment Options in Psychiatry · doi:10.1007/s40501-024-00318-9 · Cited by 12
Hommel, K. A., Noser, A. E., Plevinsky, J. M., Gamwell, K., & Denson, L. A. (2024) · Journal of Pediatric Gastroenterology and Nutrition · doi:10.1002/jpn3.12229 · Cited by 10
Shetty, V. B., Fried, L., Roby, H. C., Soon, W. H. K., Nguyen, R. L., Ong, A., Jaimangal, M., Francis, J., Paramalingam, N., CROSS, D. S., et al. (2024) · JMIR Diabetes · doi:10.2196/51491 · Cited by 11
Pritwani, S., Girotra, S., Shrivastava, P., Kumar, A., Swamy, A. M., Batra, S., Sharma, N., John, R., Praveen, D., Gara, S., et al. (2024) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-024-08003-x · Cited by 10
“Following the principles of BDT [46], feedback on visual appeal and ease of navigation, comprehensibility of the icon names and menu layout was obtained from ten volunteers (patient = 4 and caregiver = 6; male = 7 and female = 3) aged 33–66 years.”
Bucher, E., Sharkey, C., Henderson, A., Basaran, B., Meyer, S., & Chen, C. X. (2025) · BMC Women s Health · doi:10.1186/s12905-025-03812-1 · Cited by 10
“Two authors independently scored each app’s functionality, inclusiveness, and health education information using our adapted version of the Mobile Application Rating Scale [23], a generic tool designed to evaluate mobile apps.”
Kruse, G. R., Park, E. R., Shahid, N. N., Abroms, L. C., Haberer, J. E., & Rigotti, N. A. (2018) · JMIR mhealth and uhealth · doi:10.2196/11498 · Cited by 10
“Use of a nonbinary rating instrument, changing the rating system to reflect the targeted behavioral constructs such as self-efficacy, or rating usability [50] may produce greater insight into message preferences and impact.”
Therapeutic Gaming for Adolescent Anxiety
Barnes, S., & Prescott, J. (2021) · Advances in psychology, mental health, and behavioral studies (APMHBS) book series · doi:10.4018/978-1-7998-7991-6.ch009 · Cited by 10
Evidence of User-Expert Gaps in Health App Ratings and Implications for Practice
de Chantal, P., Chagnon, A., Cardinal, M., Faieta, J. M., & Guertin, A. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.765993 · Cited by 10
Tsoi, E. W. S., Mak, W. W. S., Ho, C. Y. Y., & Yeung, G. T. Y. (2022) · JMIR Human Factors · doi:10.2196/35057 · Cited by 12
“Notably, themes generated from our study were found to converge with the objective domains covered in the Mobile Application Rating Scale [39], namely, users’ engagement, functionality, esthetics, and information quality, which supports the validity of our findings.”
Su, L., & Anderson, P. L. (2022) · JMIR Formative Research · doi:10.2196/35538 · Cited by 10
Context-Aware Sleep Health Recommender Systems (CASHRS): A Narrative Review
Liang, Z. (2022) · Electronics · doi:10.3390/electronics11203384 · Cited by 10
“Along the quantitative spectrum, the mobile apps rating scale user version (uMARS) [97] and the system usability scale (SUS) [98] are the most widely used.”
Wootton, S. L., Dale, M., Alison, J. A., Brown, S., Rutherford, H., Chan, A. S. L., Varnfield, M., Yang, I. A., Cunich, M. M., Dennis, S. M., et al. (2023) · Physical Therapy · doi:10.1093/ptj/pzad044 · Cited by 10
“…The System Usability Scale, which is a 10-item scale giving a global view of subjective assessments of usability of digital systems 35 and (ii) The Mobile Application Rating Scale: User version, 36 which examines the engagement, functionality, esthetics, and information quality within the m-PR app.”
Wong, W., Ming, D. Y., Pateras, S., Fee, C. H., Coleman, C. L., Docktor, M., Shah, N., & Antonelli, R. C. (2023) · JMIR Formative Research · doi:10.2196/43993 · Cited by 10
Mareva, S., Thomson, D., Marenco, P., Muñoz, V., Ott, C. V., Schmidt, B., Wingen, T., & Kassianos, A. P. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.01086 · Cited by 10
“The MARS has been reliably used by end-users to assess the quality of mHealth apps and it has good internal consistency and test–retest reliability (Stoyanov et al., 2016).”
Development of an mHealth application for family carers of people with dementia: A study protocol
Rathnayake, S., Moyle, W., Jones, C., & Calleja, P. (2018) · Collegian Journal of the Royal College of Nursing Australia · doi:10.1016/j.colegn.2018.07.006 · Cited by 10
The Science of Behavior Change: The Road Ahead
Hagger, M. S., Cameron, L. D., Hamilton, K., Hankonen, N. E., & Lintunen, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.046 · Cited by 13
Human–Technology Interaction Considerations in Hearing Health Care: An Introduction for Audiologists
Convery, E., Heeris, J., Ferguson, M., & Edwards, B. (2020) · American Journal of Audiology · doi:10.1044/2020_aja-19-00068 · Cited by 10
Pouls, B. P. H., Bekker, C. L., Gaffo, A., van den Bemt, B. J. F., & Flendrie, M. (2021) · Rheumatology Advances in Practice · doi:10.1093/rap/rkab100 · Cited by 10
Giebel, G. D., Speckemeier, C., Abels, C., Börchers, K., Wasem, J., Blase, N., & Neusser, S. (2022) · JMIR Research Protocols · doi:10.2196/32702 · Cited by 9
Yuan, N. P., Brooks, A. J., Burke, M. K., Crocker, R. L., Stoner, G. M., Cook, P., Chen, M., Bautista, J., Petralba, P., Whitewater, S., et al. (2022) · Translational Behavioral Medicine · doi:10.1093/tbm/ibac015 · Cited by 10
Gordon, B. R., Qiu, L., Doerksen, S. E., Kanski, B., Lorenzo, A., Truica, C. I., Vasekar, M. K., Wang, M., Winkels, R. M., Abdullah, S., et al. (2023) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2023.101058 · Cited by 10
Geissler, J. M., Buchholz, H., Meerson, R., Kammerer, K., Göster, M., Schobel, J., Ratz, C., Taurines, R., Pryss, R. C., & Romanos, M. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.984618 · Cited by 9
Nicholas, J., Mills, B., Hansen, S. S., Bright, S. J., Scott, J. J., Ridout, I., Watson, J., Boyd, H., Brook, L., & Hopper, L. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107774 · Cited by 9
Cho, E., Yang, M., Jang, J., Cho, J., Kang, B., Jang, Y., & Kim, M. J. (2024) · Digital Health · doi:10.1177/20552076241249277 · Cited by 9
“34,35 Like the expert version of the MARS-K, the user version has the same scoring system with a fi ve-point Likert scale from inadequate to excellent .”
Tong, F., Lederman, R., D’Alfonso, S., Berry, K., & Bucci, S. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2469672 · Cited by 9
“It assesses six aspects of health apps including engagement, functionality, aesthetics, information, subjective quality, and perceived impact (Stoyanov et al. 2016).”
Ravichandran, A., Ferguson, M., Mulders, W. H. A. M., Choi, R. S. M., & Bennett, R. J. (2025) · Translational Behavioral Medicine · doi:10.1093/tbm/ibaf028 · Cited by 9
Asadollahi, F., Zagami, S. E., & Roudsari, R. L. (2025) · Scientific Reports · doi:10.1038/s41598-025-05609-6 · Cited by 9
“The uMARS was validated by Stoyanov et al. (2016) with high internal consistency (α = 0.90) across all subscales 38 . uMARS has been widely used in previous studies 39,40 highlighting its reliability and applicability in assessing mobile health applications.”
InfluentialNguyen, M. T. H., Krause, G., Keller‐Stanislawski, B., Glöckner, S., Mentzer, D., & Ott, J. J. (2021) · JMIR mhealth and uhealth · doi:10.2196/26289 · Cited by 9
Pouls, B. P. H., Bekker, C. L., van Dulmen, S., Vriezekolk, J. E., & van den Bemt, B. J. F. (2021) · JMIR Serious Games · doi:10.2196/31570 · Cited by 9
Turkish Validation of the User Version of the Mobile Application Rating Scale
Çalık, G., Kartal, B. B., Stoyanov, S. R., Othman, L., de la Rosette, J. J. M. C. H., Albayrak, S., Laguna, M. P., & Gravas, S. (2022) · Urology Research and Practice · doi:10.5152/tud.2022.21324 · Cited by 9
“A later simplified version was developed and validated, resulting in the User Version of the Mobile Application Rating Scale (uMARS), which can be used in large-scale trials, or research with end-users.(18) The usefulness of the uMARS in the evaluation of mobile apps incorporated in the clinical setting has been recen…”
InfluentialMichalak, E. E., Barnes, S. J., Morton, E. E., O'Brien, H. L., Murray, G., Hole, R., & Meyer, D. (2022) · JMIR Research Protocols · doi:10.2196/36213 · Cited by 9
Yu, H. X., Tan, L., Teng, Y., Xu, Z., Xiao, K., Yin, J. Y., Zuo, Y., Zhu, T., & Deng, X. (2022) · JMIR Research Protocols · doi:10.2196/37084 · Cited by 9
Gralha, S. R., & Bittencourt, O. N. D. S. (2023) · Research Society and Development · doi:10.33448/rsd-v12i6.42056 · Cited by 9
Yu, H. X., Tan, L., Zhu, T., & Deng, X. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02275-4 · Cited by 8
“Leanne Hides and colleagues developed the user version of the Mobile App Rating Scale (uMARS) which derived from the former Mobile App Rating Scale (MARS) to classify and evaluate the quality of mHealth apps [18, 19].”
Goh, C., Zheng, K., Wen, Y.-C., Nguyen, T., Liu, C.-S., Koh, C. K., Lee, G. K. Y., Tay, C., Ooi, B., & Wong, M. (2024) · Digital Health · doi:10.1177/20552076241228433 · Cited by 10
“33 uMARS has similar questions to MARS but with improved readability, and an additional subscale that evaluates the users ’ perceived impact of the evaluated app (6 items) (Appendix).”
Gamification of a Stress Management App: Results of a User Study
Hoffmann, A., Christmann, C. A., Zolynski, G., & Bleser, G. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-23538-3_23 · Cited by 9
Autonomy-Supportive Interventions
Reeve, J., & Cheon, S. H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.035 · Cited by 13
PSIXPORT: Mobile App for Ecological Momentary Assessment of Psychological Dimensions in Sport Injury
González-Barato, L. J., Rubio, V. J., Hernández, J. M., & Sánchez‐Iglesias, I. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.697293 · Cited by 9
Hearing From You: Design Thinking in Audiological Research
Young, T., Pang, J., & Ferguson, M. (2022) · American Journal of Audiology · doi:10.1044/2022_aja-21-00222 · Cited by 11
Gupta, K., Roy, S., Altameem, A., Kumar, R., Saudagar, A. K. J., & Poonia, R. C. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19126999 · Cited by 9
“MARS is a methodology for assessing the effectiveness of medical applications and comprises five subscales: engagement, functionality, aesthetics, and information quality, along with the application’s subjective quality [10,15].”
Kabacińska, K., McLeod, K. E. R., MacKenzie, A., Vu, K., Cianfrone, M., Tugwell, A., & Robillard, J. M. (2022) · Digital Health · doi:10.1177/20552076221102775 · Cited by 11
Implementation Science and Translation in Behavior Change
Łuszczyńska, A., Łobczowska, K., & Horodyska, K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.023 · Cited by 10
Horváth, M., Grutman, A. J., O’Malley, S. S., Gueorguieva, R. V., Khan, N., Brewer, J. A., & Garrison, K. A. (2021) · JMIR Research Protocols · doi:10.2196/32521 · Cited by 9
Donawa, A., Powell, C., Wang, R., Chih, M.-Y., Patel, R., Zinner, R., Aronoff-Spencer, E., & Baker, C. E. (2024) · JMIR Formative Research · doi:10.2196/57801 · Cited by 8
“This further supported our choice to use the SUS versus a more in-depth questionnaire, such as the Mobile Application Rating Scale [109], the Health Information Technology Usability Evaluation Scale [110], or the mHealth App Usability Questionnaire [111].”
Popular post‐separation parenting smartphone apps: An evaluation
Smyth, B., Payne, J., Irving, M. A., & Heard, G. (2023) · Family Court Review · doi:10.1111/fcre.12738 · Cited by 8
Jin, J. Q., Hong, J. A., Elhage, K. G., Braun, M., Spencer, R. K., Chung, M., Yeroushalmi, S., Hadeler, E. K., Mosca, M., Bartholomew, E., et al. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1228503 · Cited by 8
Melanoma prevention using an augmented reality-based serious game
Ribeiro, N., Tavares, P., Ferreira, C., & Coelho, A. F. (2024) · Patient Education and Counseling · doi:10.1016/j.pec.2024.108226 · Cited by 9
Chung, K. C. W., Takemura, N., Lam, W., Ho, M. M., Lee, A. M., Chan, W. Y. Y., & Fong, D. (2025) · JMIR mhealth and uhealth · doi:10.2196/65505 · Cited by 9
“Both scales rate app quality based on domains including engagement, functionality, aesthetics, information, app subjective quality, and perceived app use impact, with individual items rated on a 5-point scale, in which “1” indicates inadequate and “5” represents excellent [45,46].”
Shin, J. H., Jung, S. O., & Lee, J. (2023) · International Journal of Nursing Knowledge · doi:10.1111/2047-3095.12419 · Cited by 8
Ting, A., & McLachlan, C. (2023) · PeerJ · doi:10.7717/peerj.15366 · Cited by 6
Najavits, L. M., Cha, E., Demce, M. G., Gupta, M., Haney, A. M., Logounov, G., Miket, A., Morency, M., & Schulhof, A. (2023) · Substance Use & Misuse · doi:10.1080/10826084.2023.2280540 · Cited by 10
“The control app being strong on content would also help explain why the control participants improved significantly by time (pre to post) on most measures; and why their satisfaction ratings for the control app were so high on the Mobile App Rating Scale.”
InfluentialLukka, L., Karhulahti, V., Bergman, V.-R., & Palva, J. M. (2024) · Internet Interventions · doi:10.1016/j.invent.2023.100706 · Cited by 11
“…intervention should be perceived as appealing, easy to adopt, interesting to use, and encouraging in fostering behavioral change (Baumel et al., 2017; Graham et al., 2021; Stoyanov et al., 2016), and positive perceptions may be associated with intervention effectiveness (Graham et al., 2021).”
Three cycles of mobile app design to improve HIV self-management: A development and evaluation study
Kim, G. S., Kim, L., Baek, S., Shim, M., Lee, S., Kim, J. M., Yoon, J. Y., Kim, J., Choi, J. Y., & Choi, J. (2024) · Digital Health · doi:10.1177/20552076241249294 · Cited by 8
“They used the app for seven days and then evaluated the uMARS 32 and provided feedback to the research team.”
Thøgersen‐Ntoumani, C., Grunseit, A. C., Holtermann, A., Steiner, S., Tudor‐Locke, C., Koster, A., Johnson, N. A., Maher, C. A., Ahmadi, M. N., Chau, J. Y., et al. (2024) · BMC Public Health · doi:10.1186/s12889-024-19549-9 · Cited by 8
“Evidence of the scale’s internal and test-retest reliability has been provided in previous studies (24).”
InfluentialFurlonger, B., Ostojic, M., Chung, J., Phillips, K. J., Busacca, M. L., Moore, D. W., & Anderson, A. (2018) · Journal of Psychologists and Counsellors in Schools · doi:10.1017/jgc.2018.15 · Cited by 8
“Of the15 content analyses reviewed, the BCTTv1 was identified as one of the most effective taxonomies for evaluating health related apps (Ostojic et al., 2018). uMARS The uMARS is a version of the MARS (Mobile App Rating Scale; Stoyanov et al., 2016a).”
mHealth 101: an Introductory Guide for Mobile Apps in Clinical Practice
Perry, K., Shearer, E. M., Sylvers, P. D., Carlile, J. A., & Felker, B. L. (2019) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-019-00108-8 · Cited by 8
“Alternatively, the user version of the MARS (uMARS) is shorter and more simplistic, and it does not require training for administration (Stoyanov et al. 2016).”
Davis, A., & Ellis, R. (2019) · Digital Health · doi:10.1177/2055207619891347 · Cited by 8
“Stoyanov et al. 15 developed the Mobile App Rating Scale (MARS), a multi-dimensional scale for rating the quality of mobile apps, in response to this need.”
de Ridder, D. T. D., Gillebaart, M., & Friese, M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.040 · Cited by 9
Epton, T., & Armitage, C. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.038 · Cited by 8
Krishna, M., Sybil, D., Shrivastava, P. K., Premchandani, S., Kumar, H., & Kumar, P. (2021) · JMIR Perioperative Medicine · doi:10.2196/31852 · Cited by 9
Seok, Y., & Suh, E. E. (2022) · Asian Nursing Research · doi:10.1016/j.anr.2022.01.002 · Cited by 8
Information Resources Among Flemish Pregnant Women: Cross-sectional Study
Lanssens, D., Thijs, I. M. V., Dreesen, P., Hecke, A. V., Coorevits, P. L., Gaethofs, G., Derycke, J., & Tency, I. (2022) · JMIR Formative Research · doi:10.2196/37866 · Cited by 8
Ullrich, G., Bäuerle, A., Jahre, L. M., Paldán, K., Rosemeyer, J., Kalaitzidis, C., Rammos, C., Teufel, M., Rassaf, T., & Lortz, J. (2025) · npj Digital Medicine · doi:10.1038/s41746-024-01423-y · Cited by 7
“At the fi nal follow-up visit after twelve months, an interviewwas conducted which contained the uMars questionnaire 28 .”
Ivanitskaya, L. V., Zikos, D., & Erzikova, E. V. (2025) · Journal of Medical Internet Research · doi:10.2196/60071 · Cited by 11
Nieto-Casado, F. J., Gómez‐Gómez, I., Aznar‐Lou, I., Barquero‐Jimenez, C., Cáceres, I., Carretero, S., de-Juan-Iglesias, P., Domínguez‐Salas, S., Gil-Cosano, J. J., Goossens, L., et al. (2025) · Open Research Europe · doi:10.12688/openreseurope.20386.1 · Cited by 7
“App quality and user experience will be measured using the User Version of the Mobile Application Rating Scale (u-MARS; Martin-Payo et al ., 2021; Stoyanov et al ., 2016), a 26-item self-reported questionnaire assessing engagement, functionality, aesthetics, information quality, and perceived…”
Lin, Y., & Neuschaefer‐Rube, C. (2021) · JMIR Medical Education · doi:10.2196/27901 · Cited by 9
Gosak, L., Pajnkihar, M., & Štiglic, G. (2022) · JMIR Research Protocols · doi:10.2196/31652 · Cited by 10
Chandler, J., Christon, L., Benfield, K., Pairet, S., Hoffman, M., Treiber, F. A., Mueller, M., & James, W. E. (2023) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2023.101062 · Cited by 7
Evaluating mobile mental health apps using the mobile application rating scale (MARS) in the U.S.
Ki, E., Jang, J., & Kang, D.-Y. (2024) · Advances in Mental Health · doi:10.1080/18387357.2024.2388680 · Cited by 8
“In particular, individuals can easily receive health-related services through smartphones due to their portability and capabilities (Stoyanov et al., 2016).”
Paglialonga, A., Pinciroli, F., & Tognola, G. (2018) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-5225-8191-8.ch007 · Cited by 7
Mobistudy: An Open Mobile-Health Platform for Clinical Research
Salvi, D., Lee, J., Velardo, C., Goburdhun, A. R., & Tarassenko, L. (2019) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2019.00172 · Cited by 7
Evaluation of Behavior Change Interventions
Matthews, L., & Simpson, S. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.022 · Cited by 8
Sabeena, S., Swathi, M., Abdulmajeed, J., Pattanaik, S., Dsa, O. C., Shubha, H. S., Varma, M. D., Bhatt, P., Ravishankar, N., & Arunkumar, G. (2020) · Indian Journal of Community Medicine · doi:10.4103/ijcm.ijcm_510_19 · Cited by 7
“[13] The reliability of the questionnaire was assessed by Cronbach’s alpha.”
Manning, J. B., BLANDFORD, A. E., & Edbrooke-Childs, J. H. (2021) · JMIR Formative Research · doi:10.2196/32312 · Cited by 10
Korkmaz, S., & ARIKAN, G. (2021) · Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi · doi:10.26745/ahbvuibfd.884734 · Cited by 7
Proposal of a New Rating Concept for Digital Health Applications in Orthopedics and Traumatology
Scherer, J. N., Youssef, Y., Dittrich, F., Albrecht, U., Tsitsilonis, S., Jung, J., Pförringer, D., Landgraeber, S., Beck, S., & Back, D. A. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192214952 · Cited by 7
Approaches to Mobile Health Evaluation: A Comparative Study
Dick, S., O’Connor, Y., & Heavin, C. (2019) · Information Systems Management · doi:10.1080/10580530.2020.1696550 · Cited by 10
Kelly, P., Beck, A., Baker, A., Deane, F., Hides, L., Manning, V., Shakeshaft, A., Larance, B., Neale, J., Kelly, J., et al. (2020) · JMIR Research Protocols · doi:10.2196/15113 · Cited by 6
“The Mobile Application Rating Scale–User Version (uMARS [53]) is a simplified, end-user version.”
Motivational Interviewing Interventions
Berman, A. H., Beckman, M., & Lindqvist, H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.045 · Cited by 12
An Overview of the Mobile App Rating Scale (MARS) in Health Care Application Assessment
Klug, B. (2023) · Journal of Hospital Librarianship · doi:10.1080/15323269.2023.2289804 · Cited by 6
“Researchers have noted the importance of including end-users in the mHealth app evaluation process to improve overall app design, efficacy, and adherence (22,23).”
Daehn, D., Meyer, C., Loew, V., Wabiszczewicz, J., Pohl, S., Böttche, M., Pawils, S., & Renneberg, B. (2024) · Trials · doi:10.1186/s13063-024-08304-5 · Cited by 9
“The User Version of the Mobile Application Rating Scale (uMARS, [48]) will be used by end-users to assess the quality of mHealth apps.”
Rana, R., Ibrahim, B., Huri, H. Z., Wahab, I. A., Govindaraju, K., Shukeri, M. S. M., Ng, C. K., & Ong, S. C. (2024) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2024.07.004 · Cited by 7
Usability of an augmented reality bedtime routine application for autistic children
Ahmadian, P., Cardy, R. E., Luca, G. D., & Kushki, A. (2024) · Assistive Technology · doi:10.1080/10400435.2024.2338277 · Cited by 8
“The uMARS is an adapted version of the MARS (Mobile Application Rating Scale) and has shown excellent internal consistency (alpha = .90) (Stoyanov et al., 2016).”
Shenoy, R., Nickels, L., & Krishnan, G. (2024) · Technology and Disability · doi:10.1177/10554181241299972 · Cited by 8
Ko, S., & Woo, H. (2025) · JMIR mhealth and uhealth · doi:10.2196/64622 · Cited by 6
“For each of the final selected apps, we assessed quality using the Korean-translated version of the user version of the Mobile Application Rating Scale (uMARS) [26]. uMARS is a 5-point scale developed from the original Mobile Application Rating Scale to enable users to evaluate mHealth apps [27,28].”
Swallow, V. M., Horsman, J. M., Mazlan, E., Campbell, F., Zaidi, R., Julian, M., Branchflower, J., Martin-Kerry, J., Monks, H., Soni, A., et al. (2025) · JMIR Diabetes · doi:10.2196/74032 · Cited by 6
Boggiss, A. L., Babbott, K. M., Milford, Ā., Ellett, S. G., Consedine, N. S., Reid, S., Cao, N., Cavadino, A., Hopkins, S. A., Jefferies, C., et al. (2025) · Diabetic Medicine · doi:10.1111/dme.70115 · Cited by 8
Engagement With Meditation Apps: Cross-Sectional Survey of Use and Associations
Adams, J., Davies, J. N., Wattanatakulchat, P., Galante, J., Miller, F., D’Alfonso, S., & Dam, N. T. V. (2025) · Journal of Medical Internet Research · doi:10.2196/71960 · Cited by 4
“The user Mobile Application Rating Scale (uMARS) is a 27-item instrument for assessing the quality of mobile apps [69].”
Rosenfeld, E. A., Lyman, C., & Roberts, J. E. (2022) · JMIR Formative Research · doi:10.2196/40045 · Cited by 8
Mateo‐Orcajada, A., Abenza‐Cano, L., & Vaquero‐Cristóbal, R. (2024) · International Journal of Adolescence and Youth · doi:10.1080/02673843.2024.2389310 · Cited by 9
“The subjective part includes 10 questions scored using a Likert scale of 1 to 5 points, in which usability and perceived impact are evaluated (Stoyanov et al., 2016).”
Bernard, R. M., Seijas, V., Davis, M., Volkova, A., Diviani, N., Lüscher, J., & Sabariego, C. (2024) · JMIR mhealth and uhealth · doi:10.2196/53677 · Cited by 6
Economic and Behavioral Economic Approaches to Behavior Change
Brown, P. M., Cameron, L. D., Wilkinson, M., & Taylor, D. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.042 · Cited by 7
Home safety evaluation – getting it right
Pickens, N. D., Mendonca, R. J., Burns, S. P., & Smith, R. O. (2020) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2020.1805033 · Cited by 6
Applications mobiles pour soutenir la santé mentale des jeunes : opportunités et défis
Ouellet‐Morin, I., Robitaille, M.-P., & Juster, R. (2021) · Santé mentale au Québec · doi:10.7202/1081508ar · Cited by 6
Strauss, J., Zhang, J., Jarrett, M. L., Patterson, B. A., & Ameringen, M. V. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822201-0.00006-x · Cited by 8
Beauvais, C., Pham, T., Montagu, G., Gleizes, S., Madrisotti, F., Lafourcade, A., Vidal, C., Dervin, G., Baudard, P., Desouches, S., et al. (2022) · PLoS ONE · doi:10.1371/journal.pone.0272235 · Cited by 6
“We are aware that this is very broad information that poorly reflects the true app quality as compared with other evaluation tools, the Mobile Application Rating Scale (MARS) being the most commonly used [61, 62].”
Roberts, C. M., Plevinsky, J. M., Gamwell, K. L., Noser, A. E., Denson, L. A., & Hommel, K. A. (2023) · Health Care Transitions · doi:10.1016/j.hctj.2023.100031 · Cited by 6
Laboe, A. A., McGinnis, C. G., Fennig, M., Zucker, K., Wu, E., Shah, J., Levitan, J., Firebaugh, M., Bardone‐Cone, A. M., Pike, K. M., et al. (2024) · Eating Behaviors · doi:10.1016/j.eatbeh.2024.101865 · Cited by 6
“…a 23-item validated scale that assesses the quality of health apps and includes one subjective quality rating—a reflection of the user’s overall satisfaction—and four objective quality subscales: engagement, functionality, aesthetics, and information (Stoyanov et al., 2015; Stoyanov et al., 2016).”
Panatto, D., Domnich, A., Gasparini, R., Bonanni, P., Icardi, G., Amicizia, D., Arata, L., Carozzo, S., Signori, A., Bechini, A., et al. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6205 · Cited by 6
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
