The use of CRISP-DM methodology to support data analysis in the mHealth IUProst application

• Noelí Antonia Pimentel Vaz UFG / UEG
• Deborah Silva Alves Fernandes UFG
• Sergio T. Carvalho UFG

DOI: https://doi.org/10.5753/sbcas.2024.2640

Abstract

The use of mobile devices in healthcare aims to assist in the control and monitoring of diseases and clinical conditions. Mobile health applications (mHealth) contribute to individuals’ self-care. IUProst is a mHealth application that aids patients during the treatment of urinary incontinence and comorbidity resulting from prostate removal surgery in cancer patients. Despite the potential of mHealth applications like IUProst to assist in the treatment of urinary incontinence, the low adherence of users underscores the urgency of implementing effective engagement mechanisms. The objective of this article is to report on a study that employs the CRISP-DM methodology to identify patterns, trends, and insights in IUProst data, aiming to uncover demands to support the application’s future development cycles. Analyses of the results obtained in the business understanding and data understanding phases reveal a significant number of users and exercises performed but with low participation in the proposed cognitive behavioral treatment.

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