Cargando…
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
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-moni...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468343/ https://www.ncbi.nlm.nih.gov/pubmed/30942693 http://dx.doi.org/10.2196/11671 |
_version_ | 1783411412394049536 |
---|---|
author | Hartmann, Ralf Sander, Christian Lorenz, Noah Böttger, Daniel Hegerl, Ulrich |
author_facet | Hartmann, Ralf Sander, Christian Lorenz, Noah Böttger, Daniel Hegerl, Ulrich |
author_sort | Hartmann, Ralf |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6468343 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-64683432019-05-08 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 Hartmann, Ralf Sander, Christian Lorenz, Noah Böttger, Daniel Hegerl, Ulrich JMIR Ment Health Original Paper 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. JMIR Publications 2019-04-03 /pmc/articles/PMC6468343/ /pubmed/30942693 http://dx.doi.org/10.2196/11671 Text en ©Ralf Hartmann, Christian Sander, Noah Lorenz, Daniel Böttger, Ulrich Hegerl. Originally published in JMIR Mental Health (http://mental.jmir.org), 03.04.2019. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Hartmann, Ralf Sander, Christian Lorenz, Noah Böttger, Daniel Hegerl, Ulrich 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468343/ https://www.ncbi.nlm.nih.gov/pubmed/30942693 http://dx.doi.org/10.2196/11671 |
work_keys_str_mv | AT hartmannralf utilizationofpatientgenerateddatacollectedthroughmobiledevicesinsightsfromasurveyonattitudestowardmobileselfmonitoringandselfmanagementappsfordepression AT sanderchristian utilizationofpatientgenerateddatacollectedthroughmobiledevicesinsightsfromasurveyonattitudestowardmobileselfmonitoringandselfmanagementappsfordepression AT lorenznoah utilizationofpatientgenerateddatacollectedthroughmobiledevicesinsightsfromasurveyonattitudestowardmobileselfmonitoringandselfmanagementappsfordepression AT bottgerdaniel utilizationofpatientgenerateddatacollectedthroughmobiledevicesinsightsfromasurveyonattitudestowardmobileselfmonitoringandselfmanagementappsfordepression AT hegerlulrich utilizationofpatientgenerateddatacollectedthroughmobiledevicesinsightsfromasurveyonattitudestowardmobileselfmonitoringandselfmanagementappsfordepression |