Utilization of Patient-Generated Data Collected Through Mobile Devices: Insights From a Survey on Attitudes Toward Mobile Self-Monitoring and Self-Management Apps for Depression

Ralf Hartmann; Christian Sander; Noah Lorenz; Daniel Böttger; Ulrich Hegerl

doi:10.2196/11671

Utilization of Patient-Generated Data Collected Through Mobile Devices: Insights From a Survey on Attitudes Toward Mobile Self-Monitoring and Self-Management Apps for Depression

JMIR Ment Health. 2019 Apr 3;6(4):e11671. doi: 10.2196/11671.

Authors

Ralf Hartmann¹, Christian Sander¹, Noah Lorenz¹, Daniel Böttger¹, Ulrich Hegerl²

Affiliations

¹ Research Center of the German Depression Foundation, Leipzig, Germany.
² Department of Psychiatry, University of Leipzig, Leipzig, Germany.

PMID: 30942693
PMCID: PMC6468343
DOI: 10.2196/11671

Abstract

Background: Depression is a severe psychiatric disease with high prevalence and an elevated risk for recurrence and chronicity. A substantial proportion of individuals with a diagnosis of unipolar depressive disorder do not receive treatment as advised by national guidelines. Consequently, self-monitoring and self-management become increasingly important. New mobile technologies create unique opportunities to obtain and utilize patient-generated data. As common adherence rates to mobile technologies are scarce, a profound knowledge of user behavior and attitudes and preferences is important throughout any developmental process of mobile technologies and apps.

Objective: The aim of this survey was to provide descriptive data upon usage and anticipated usage of self-monitoring and self-management of depression and preferences of potential users in terms of documented parameters and data-sharing options.

Methods: A Web-based survey comprising 55 questions was conducted to obtain data on the usage of mobile devices, app usage, and participant's attitudes and preferences toward mobile health apps for the self-monitoring and self-management of depression.

Results: A total of 825 participants provided information. Moreover, two-thirds of the sample self-reported to be affected by depressive symptoms, but only 12.1% (81/668) of those affected by depression have ever used any mobile self-monitoring or self-management app. Analysis showed that people want personally relevant information and feedback but also focus on handling sensitive data.

Conclusions: New mobile technologies and smartphone apps, especially in combination with mobile sensor systems, offer unique opportunities to overcome challenges in the treatment of depression by utilizing the potential of patient-generated data. Focus on patient-relevant information, security and safe handling of sensitive personal data, as well as options to share data with self-selected third parties should be considered mandatory throughout any development process.

Keywords: adherence; depression; mHealth; mobile applications, self-management.

©Ralf Hartmann, Christian Sander, Noah Lorenz, Daniel Böttger, Ulrich Hegerl. Originally published in JMIR Mental Health (http://mental.jmir.org), 03.04.2019.