Research Article
An Analysis of Usage and Reporting Patterns in a Mobile Health Application
@INPROCEEDINGS{10.1007/978-3-031-32029-3_18, author={Ana Gonz\^{a}lez Berm\^{u}dez and Ana M. Bernardos}, title={An Analysis of Usage and Reporting Patterns in a Mobile Health Application}, proceedings={Wireless Mobile Communication and Healthcare. 11th EAI International Conference, MobiHealth 2022, Virtual Event, November 30 -- December 2, 2022, Proceedings}, proceedings_a={MOBIHEALTH}, year={2023}, month={5}, keywords={Mobile Health personal health application adherence reminders notifications behaviour}, doi={10.1007/978-3-031-32029-3_18} }- Ana González Bermúdez
Ana M. Bernardos
Year: 2023
An Analysis of Usage and Reporting Patterns in a Mobile Health Application
MOBIHEALTH
Springer
DOI: 10.1007/978-3-031-32029-3_18
Abstract
The use of mobile applications (apps) as a tool to monitor health-related parameters is now a common practice. Connected to wearables or stand-alone, these apps usually track the user by retrieving relevant information from mobile embedded sensors but also may serve to get self-reported data. To make sense, these apps require that the user remains active in the use of the application, to get the most complete data records. Different aspects may affect the user’s adherence level to the app, both personal characteristics (personality, motivation, etc.) and app design and technical features (attractiveness, usability, perceived usefulness, etc.). The aim of this paper is to explore user’s adherence by analyzing users’ behavior on the use case of an app which aims at helping track emotional states by using emoticons. The adherence analysis focuses on evaluate the real impact of notifications, which is the main strategy to incentive adherence in this case. The study analyzes four weeks of data from 20 young users, that have volunteered to use the app within the framework of a study on mental health. Based on a selected set of behaviour-related features, a clustering analysis shows two well differentiated adherence groups: the first one that use the app several times a day, while the second is less regular. Regarding notifications, they reveal to have different impact depending on the user group, being much more effective for very active users. Other adherence incentives must be designed to improve the continuous use of the application.
