Research Article
Toward Understanding Users’ Interactions with a Mental Health App: An Association Rule Mining Approach
@INPROCEEDINGS{10.1007/978-3-031-34586-9_32, author={Alaa Alslaity and Gerry Chan and Richard Wilson and Rita Orji}, title={Toward Understanding Users’ Interactions with a Mental Health App: An Association Rule Mining Approach}, proceedings={Pervasive Computing Technologies for Healthcare. 16th EAI International Conference, PervasiveHealth 2022, Thessaloniki, Greece, December 12-14, 2022, Proceedings}, proceedings_a={PERVASIVEHEALTH}, year={2023}, month={6}, keywords={Mental health Mobile health app mHealth Mood tracker Mobile app Association Rule Mining}, doi={10.1007/978-3-031-34586-9_32} }- Alaa Alslaity
Gerry Chan
Richard Wilson
Rita Orji
Year: 2023
Toward Understanding Users’ Interactions with a Mental Health App: An Association Rule Mining Approach
PERVASIVEHEALTH
Springer
DOI: 10.1007/978-3-031-34586-9_32
Abstract
Mental health apps are gaining increasing research attention. One reason for this is that many users find mental health apps a good alternative for self-management of mental conditions, especially in the last two years when access to physicians was limited because of the COVID-19 pandemic. Despite the existence of several mobile apps targeting mental health, studies show the need to explore and enhance existing mobile health (mHealth) apps to better serve patients and health practitioners. This work aims at analyzing data generated from users of a mobile app to enhance mHealth apps for improving mental health. Particularly, this paper aims to extract knowledge about the relationship between different activities (e.g., sport, home, school, etc.) that affect users’ moods. To achieve this goal, an association rule mining technique was applied on a dataset collected in the wild from 232 users of a mental health app called the FeelingMoodie app. They used the app from September 2021 to May 2022. Our results revealed interesting associations between various daily life activities. Based on these association rules, we provide insights and recommendations for building better mHealth apps and a more personalized user experience.
