Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Monday, March 11, 2019 at 4:00 PM to 4:30 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?


Currently submitted to: Journal of Medical Internet Research

Date Submitted: Dec 27, 2019
Open Peer Review Period: Dec 27, 2019 - Feb 21, 2020
(currently open for review)

Finding the best app for patients with genitourinary tumors: analysis of quality using the Mobile Application Rating Scale (MARS)

  • Miguel Angel Amor Garcia; 
  • Roberto Collado-Borrell; 
  • Vicente Escudero-Vilaplana; 
  • Alejandra Melgarejo Ortuño; 
  • Ana Herranz; 
  • JosĂ© Ángel Arranz; 
  • MarĂ­a Sanjurjo; 



The large number of available cancer mobile applications (apps) and their impact on the population necessitates a transparent, objective, and comprehensive evaluation by app experts, healthcare professionals, and users. To date, there have been no analyses or classifications of apps for patients with genitourinary cancers, one of the most prevalent types of cancer.


The objective of our study was to analyze the quality of apps for patients diagnosed with genitourinary cancers using MARS in order to identify the highest-quality apps.


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 conducted a search of all the apps for patients with genitourinary cancers (bladder, prostate, cervix, uterus, endometrium, kidney, testicular, and vulvar) and/or their caregivers. Applications were downloaded and evaluated, and the general characteristics were entered into a database. The evaluation was performed by 2 independent researchers with the MARS questionnaire, which rates 23 evaluation criteria clustered in 5 domains (Engagement, Functionality, Aesthetics, Information, and Subjective Quality) with a score of 1 to 5.


Forty-six apps were analyzed. Thirty-one (67%) were available in Android, 6 (13%) in iOS, and 9 (20%) in 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% (14/46) of cases and for 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 healthcare 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 Aesthetics, which showed acceptable scores in a third of the apps. The 5 apps with the highest MARS score were: “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 among the operative systems and the developers (P < .001 and P = .01, respectively), but not by cost (P = .62).


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 poor; nevertheless, we observed that both participation of health professionals and updating were correlated with quality.


Please cite as:

Amor Garcia MA, Collado-Borrell R, Escudero-Vilaplana V, Melgarejo Ortuño A, Herranz A, Arranz JĂ, Sanjurjo M

Finding the best app for patients with genitourinary tumors: analysis of quality using the Mobile Application Rating Scale (MARS)

JMIR Preprints. 27/12/2019:17609

DOI: 10.2196/preprints.17609


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.