Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review
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Other documents of the author: Colombo, Desirée; Fernández-Álvarez, Javier; Patané, Andrea; Semonella, Michelle; Kwiatkowska, Marta; Díaz-García, Amanda; Cipresso, Pietro; Riva, Giuseppe; Botella, Cristina
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/8033
comunitat-uji-handle3:10234/8636
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Title
Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic ReviewAuthor (s)
Date
2019-04Publisher
MDPIBibliographic citation
COLOMBO, Desirée, et al. Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review. Journal of clinical medicine, 2019, 8.4: 465.Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/2077-0383/8/4/465Version
info:eu-repo/semantics/publishedVersionSubject
Abstract
Ecological momentary assessment (EMA) and ecological momentary intervention (EMI) are alternative approaches to retrospective self-reports and face-to-face treatments, and they make it possible to repeatedly assess ... [+]
Ecological momentary assessment (EMA) and ecological momentary intervention (EMI) are alternative approaches to retrospective self-reports and face-to-face treatments, and they make it possible to repeatedly assess patients in naturalistic settings and extend psychological support into real life. The increase in smartphone applications and the availability of low-cost wearable biosensors have further improved the potential of EMA and EMI, which, however, have not yet been applied in clinical practice. Here, we conducted a systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to explore the state of the art of technology-based EMA and EMI for major depressive disorder (MDD). A total of 33 articles were included (EMA = 26; EMI = 7). First, we provide a detailed analysis of the included studies from technical (sampling methods, duration, prompts), clinical (fields of application, adherence rates, dropouts, intervention effectiveness), and technological (adopted devices) perspectives. Then, we identify the advantages of using information and communications technologies (ICTs) to extend the potential of these approaches to the understanding, assessment, and intervention in depression. Furthermore, we point out the relevant issues that still need to be addressed within this field, and we discuss how EMA and EMI could benefit from the use of sensors and biosensors, along with recent advances in machine learning for affective modelling. [-]
Investigation project
Marie Curie EF-ST AffecTech, approved at call H2020-MSCA-ITN-2016 (project reference: 722022).Rights
info:eu-repo/semantics/openAccess
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