JMIR Res Protoc. 2017 Jun 09;6(6):e110. doi: 10.2196/resprot.6919.
Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype.
JMIR research protocols
Talayeh Aledavood, Ana Maria Triana Hoyos, Tuomas Alakörkkö, Kimmo Kaski, Jari Saramäki, Erkki Isometsä, Richard K Darst
Affiliations
Affiliations
- Department of Computer Science, Aalto University, Espoo, Finland.
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
PMID: 28600276
PMCID: PMC5483244 DOI: 10.2196/resprot.6919
Abstract
BACKGROUND: Mental and behavioral disorders are the main cause of disability worldwide. However, their diagnosis is challenging due to a lack of reliable biomarkers; current detection is based on structured clinical interviews which can be biased by the patient's recall ability, affective state, changing in temporal frames, etc. While digital platforms have been introduced as a possible solution to this complex problem, there is little evidence on the extent of usability and usefulness of these platforms. Therefore, more studies where digital data is collected in larger scales are needed to collect scientific evidence on the capacities of these platforms. Most of the existing platforms for digital psychiatry studies are designed as monolithic systems for a certain type of study; publications from these studies focus on their results, rather than the design features of the data collection platform. Inevitably, more tools and platforms will emerge in the near future to fulfill the need for digital data collection for psychiatry. Currently little knowledge is available from existing digital platforms for future data collection platforms to build upon.
OBJECTIVE: The objective of this work was to identify the most important features for designing a digital platform for data collection for mental health studies, and to demonstrate a prototype platform that we built based on these design features.
METHODS: We worked closely in a multidisciplinary collaboration with psychiatrists, software developers, and data scientists and identified the key features which could guarantee short-term and long-term stability and usefulness of the platform from the designing stage to data collection and analysis of collected data.
RESULTS: The key design features that we identified were flexibility of access control, flexibility of data sources, and first-order privacy protection. We also designed the prototype platform Non-Intrusive Individual Monitoring Architecture (Niima), where we implemented these key design features. We described why each of these features are important for digital data collection for psychiatry, gave examples of projects where Niima was used or is going to be used in the future, and demonstrated how incorporating these design principles opens new possibilities for studies.
CONCLUSIONS: The new methods of digital psychiatry are still immature and need further research. The design features we suggested are a first step to design platforms which can adapt to the upcoming requirements of digital psychiatry.
©Talayeh Aledavood, Ana Maria Triana Hoyos, Tuomas Alakörkkö, Kimmo Kaski, Jari Saramäki, Erkki Isometsä, Richard K Darst. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.06.2017.
Keywords: big data; data collection framework; digital phenotyping; mental health
References
- Shanghai Arch Psychiatry. 2013 Apr;25(2):68-9 - PubMed
- Lancet. 2015 Jan 10;385(9963):117-71 - PubMed
- JAMA Psychiatry. 2016 Jan;73(1):3-4 - PubMed
- Oncologist. 2005 Sep;10(8):636-41 - PubMed
- J Med Internet Res. 2015 Jul 15;17(7):e175 - PubMed
- Nat Biotechnol. 2016 Mar;34(3):239-46 - PubMed
- JAMA Psychiatry. 2015 Apr;72(4):334-41 - PubMed
- J Behav Ther Exp Psychiatry. 1992 Dec;23(4):299-302 - PubMed
- Mol Psychiatry. 2011 Nov;16(11):1076-87 - PubMed
- JAMA Psychiatry. 2016 Feb;73(2):103-4 - PubMed
- Schizophr Bull. 2014 Nov;40(6):1244-53 - PubMed
- Curr Psychiatry Rep. 2015 Aug;17(8):602 - PubMed
- Br J Psychiatry. 2015 Apr;206(4):263-5 - PubMed
- Lancet. 2016 Oct 8;388(10053):1545-1602 - PubMed
- J Affect Disord. 2016 Nov 15;205:225-233 - PubMed
- J Med Internet Res. 2014 Jul 30;16(7):e181 - PubMed
- IEEE Trans Biomed Eng. 2012 Oct;59(10):2801-7 - PubMed
- J Psychiatry Neurosci. 2013 Mar;38(2):75-7 - PubMed
- Science. 2014 Jan 24;343(6169):373-4 - PubMed
- JMIR Ment Health. 2016 May 05;3(2):e16 - PubMed
- Diabetes Educ. 2011 Jan-Feb;37(1):59-66 - PubMed
- Nature. 2011 Jul 06;475(7354):27-30 - PubMed
- Int J Bipolar Disord. 2016 Dec;4(1):10 - PubMed
- Innov Clin Neurosci. 2016 Jun 01;13(5-6):31-77 - PubMed
- Psychiatr Rehabil J. 2015 Sep;38(3):218-26 - PubMed
- BMJ Open. 2013 Jul 24;3(7):null - PubMed
- JMIR Mhealth Uhealth. 2016 Sep 21;4(3):e111 - PubMed
- JMIR Ment Health. 2015 Mar 24;2(1):e8 - PubMed
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