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dc.contributor.author
Wahle, Fabian
dc.contributor.author
Bollhalder, Lea
dc.contributor.author
Kowatsch, Tobias
dc.contributor.author
Fleisch, Elgar
dc.date.accessioned
2017-12-07T11:00:30Z
dc.date.available
2017-12-06T22:35:08Z
dc.date.available
2017-12-07T11:00:30Z
dc.date.issued
2017-05-31
dc.identifier.issn
1438-8871
dc.identifier.other
10.2196/jmir.7381
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/218660
dc.identifier.doi
10.3929/ethz-b-000218660
dc.description.abstract
Background: Existing research postulates a variety of components that show an impact on utilization of technology-mediated mental health information systems (MHIS) and treatment outcome. Although researchers assessed the effect of isolated design elements on the results of Web-based interventions and the associations between symptom reduction and use of components across computer and mobile phone platforms, there remains uncertainty with regard to which components of technology-mediated interventions for mental health exert the greatest therapeutic gain. Until now, no studies have presented results on the therapeutic benefit associated with specific service components of technology-mediated MHIS for depression. Objective: This systematic review aims at identifying components of technology-mediated MHIS for patients with depression. Consequently, all randomized controlled trials comparing technology-mediated treatments for depression to either waiting-list control, treatment as usual, or any other form of treatment for depression were reviewed. Updating prior reviews, this study aims to (1) assess the effectiveness of technology-supported interventions for the treatment of depression and (2) add to the debate on what components in technology-mediated MHIS for the treatment of depression should be standard of care. Methods: Systematic searches in MEDLINE, PsycINFO, and the Cochrane Library were conducted. Effect sizes for each comparison between a technology-enabled intervention and a control condition were computed using the standard mean difference (SMD). Chi-square tests were used to test for heterogeneity. Using subgroup analysis, potential sources of heterogeneity were analyzed. Publication bias was examined using visual inspection of funnel plots and Begg’s test. Qualitative data analysis was also used. In an explorative approach, a list of relevant components was extracted from the body of literature by consensus between two researchers. Results: Of 6387 studies initially identified, 45 met all inclusion criteria. Programs analyzed showed a significant trend toward reduced depressive symptoms (SMD –0.58, 95% CI –0.71 to –0.45, P<.001). Heterogeneity was large (I2≥76). A total of 15 components were identified. Conclusions: Technology-mediated MHIS for the treatment of depression has a consistent positive overall effect compared to controls. A total of 15 components have been identified. Further studies are needed to quantify the impact of individual components on treatment effects and to identify further components that are relevant for the design of future technology-mediated interventions for the treatment of depression and other mental disorders.
en_US
dc.format
application/pdf
dc.language.iso
en
en_US
dc.publisher
JMIR Publications
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Depression
en_US
dc.subject
Design feature
en_US
dc.subject
Information Systems
en_US
dc.subject
Literature review
en_US
dc.subject
Mental Health
en_US
dc.title
Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Journal of Medical Internet Research
ethz.journal.volume
19
en_US
ethz.journal.issue
5
en_US
ethz.journal.abbreviated
J Med Internet Res
ethz.pages.start
e191
en_US
ethz.size
32 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.scopus
ethz.publication.place
Toronto
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03681 - Fleisch, Elgar / Fleisch, Elgar
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03681 - Fleisch, Elgar / Fleisch, Elgar
en_US
ethz.date.deposited
2017-12-06T22:35:09Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-12-07T11:00:37Z
ethz.rosetta.lastUpdated
2021-02-14T21:15:17Z
ethz.rosetta.versionExported
true
ethz.COinS
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