Use of a Fully Automated Internet-Based Cognitive Behavior Therapy Intervention in a Community Population of Adults With Depression Symptoms: Randomized Controlled Trial
Author
Schure, Mark BLindow, Janet C
Greist, John H
Nakonezny, Paul A
Bailey, Sandra J
Bryan, William L
Byerly, Matthew J
Affiliation
Univ Arizona, Coll Med, Dept PsychiatIssue Date
2019-11-16Keywords
CBTRCT
depression symptoms
iCBT
internet-based cognitive behavior therapy
randomized controlled trial
rural populations
Metadata
Show full item recordPublisher
JMIR PUBLICATIONS, INCCitation
Schure MB, Lindow JC, Greist JH, Nakonezny PA, Bailey SJ, Bryan WL, Byerly MJ Use of a Fully Automated Internet-Based Cognitive Behavior Therapy Intervention in a Community Population of Adults With Depression Symptoms: Randomized Controlled Trial J Med Internet Res 2019;21(11):e14754 URL: http://www.jmir.org/2019/11/e14754/ doi: 10.2196/14754Rights
©Mark B Schure, Janet C Lindow, John H Greist, Paul A Nakonezny, Sandra J Bailey, William L Bryan, Matthew J Byerly. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.11.2019. 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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Background: Although internet-based cognitive behavior therapy (iCBT) interventions can reduce depression symptoms, large differences in their effectiveness exist. Objective: The aim of this study was to evaluate the effectiveness of an iCBT intervention called Thrive, which was designed to enhance engagement when delivered as a fully automated, stand-alone intervention to a rural community population of adults with depression symptoms. Methods: Using no diagnostic or treatment exclusions, 343 adults with depression symptoms were recruited from communities using an open-access website and randomized 1:1 to the Thrive intervention group or the control group. Using self-reports, participants were evaluated at baseline and 4 and 8 weeks for the primary outcome of depression symptom severity and secondary outcome measures of anxiety symptoms, work and social adjustment, psychological resilience, and suicidal ideation. Results: Over the 8-week follow-up period, the intervention group (n=181) had significantly lower depression symptom severity than the control group (n=162; P<.001), with a moderate treatment effect size (d=0.63). Moderate to near-moderate effect sizes favoring the intervention group were observed for anxiety symptoms (P<.001; d=0.47), work/social functioning (P<.001; d=0.39), and resilience (P<.001; d=0.55). Although not significant, the intervention group was 45% less likely than the control group to experience increased suicidal ideation (odds ratio 0.55). Conclusions: These findings suggest that the Thrive intervention was effective in reducing depression and anxiety symptom severity and improving functioning and resilience among a mostly rural community population of US adults. The effect sizes associated with Thrive were generally larger than those of other iCBT interventions delivered as a fully automated, stand-alone intervention.Note
Open access journalISSN
1438-8871PubMed ID
31738173DOI
10.2196/14754Version
Final published versionSponsors
National Institute of General Medical Sciences of the National Institutes of Health, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) [P20GM103474, U54GM115371, 5P20GM104417]ae974a485f413a2113503eed53cd6c53
10.2196/14754
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