Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial

被引:1075
作者
Fitzpatrick, Kathleen Kara [1 ]
Darcy, Alison [2 ]
Vierhile, Molly [1 ]
机构
[1] Stanford Sch Med, Dept Psychiat & Behav Sci, Stanford, CA USA
[2] Woebot Labs Inc, 55 Fair Ave, San Francisco, CA 94110 USA
关键词
conversational agents; mobile mental health; mental health; chatbots; depression; anxiety; college students; digital health; MENTAL-HEALTH; WORKING ALLIANCE; INTERVENTIONS; VALIDATION; DISORDER; APPS;
D O I
10.2196/mental.7785
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Background: Web-based cognitive-behavioral therapeutic (CBT) apps have demonstrated efficacy but are characterized by poor adherence. Conversational agents may offer a convenient, engaging way of getting support at any time. Objective: The objective of the study was to determine the feasibility, acceptability, and preliminary efficacy of a fully automated conversational agent to deliver a self-help program for college students who self-identify as having symptoms of anxiety and depression. Methods: In an unblinded trial, 70 individuals age 18-28 years were recruited online from a university community social media site and were randomized to receive either 2 weeks (up to 20 sessions) of self-help content derived from CBT principles in a conversational format with a text-based conversational agent (Woebot) (n=34) or were directed to the National Institute of Mental Health ebook, "Depression in College Students," as an information-only control group (n=36). All participants completed Web-based versions of the 9-item Patient Health Questionnaire (PHQ-9), the 7-item Generalized Anxiety Disorder scale (GAD-7), and the Positive and Negative Affect Scale at baseline and 2-3 weeks later (T2). Results: Participants were on average 22.2 years old (SD 2.33), 67% female (47/70), mostly non-Hispanic (93%, 54/58), and Caucasian (79%, 46/58). Participants in the Woebot group engaged with the conversational agent an average of 12.14 (SD 2.23) times over the study period. No significant differences existed between the groups at baseline, and 83% (58/70) of participants provided data at T2 (17% attrition). Intent-to-treat univariate analysis of covariance revealed a significant group difference on depression such that those in the Woebot group significantly reduced their symptoms of depression over the study period as measured by the PHQ-9 (F=6.47; P=.01) while those in the information control group did not. In an analysis of completers, participants in both groups significantly reduced anxiety as measured by the GAD-7 (F1,54=9.24; P=.004). Participants' comments suggest that process factors were more influential on their acceptability of the program than content factors mirroring traditional therapy. Conclusions: Conversational agents appear to be a feasible, engaging, and effective way to deliver CBT.
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页数:11
相关论文
共 29 条
[1]  
Andersson Gerhard, 2009, Cognitive Behaviour Therapy, V38, P196, DOI 10.1080/16506070903318960
[2]  
[Anonymous], 2017, APP EV MOD
[3]   Internet-Delivered Psychological Treatments for Mood and Anxiety Disorders: A Systematic Review of Their Efficacy, Safety, and Cost-Effectiveness [J].
Arnberg, Filip K. ;
Linton, Steven J. ;
Hultcrantz, Monica ;
Heintz, Emelie ;
Jonsson, Ulf .
PLOS ONE, 2014, 9 (05)
[4]   Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments [J].
Bakker, David ;
Kazantzis, Nikolaos ;
Rickwood, Debra ;
Rickard, Nikki .
JMIR MENTAL HEALTH, 2016, 3 (01)
[5]   A Comprehensive Review and a Meta-Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions [J].
Barak, Azy ;
Hen, Liat ;
Boniel-Nissim, Meyran ;
Shapira, Na'ama .
JOURNAL OF TECHNOLOGY IN HUMAN SERVICES, 2008, 26 (2-4) :109-160
[6]   Establishing the computer-patient working alliance in automated health behavior change interventions [J].
Bickmore, T ;
Gruber, A ;
Picard, R .
PATIENT EDUCATION AND COUNSELING, 2005, 59 (01) :21-30
[7]   MAINTAINING ENGAGEMENT IN LONG-TERM INTERVENTIONS WITH RELATIONAL AGENTS [J].
Bickmore, Timothy ;
Schulman, Daniel ;
Yin, Langxuan .
APPLIED ARTIFICIAL INTELLIGENCE, 2010, 24 (06) :648-666
[8]  
Braun V, 2006, QUAL RES PSYCHOL, V3, DOI [DOI 10.1191/1478088706QP063OA, 10.1191/1478088706qp063oa]
[9]   Harnessing Context Sensing to Develop a Mobile Intervention for Depression [J].
Burns, Michelle Nicole ;
Begale, Mark ;
Duffecy, Jennifer ;
Gergle, Darren ;
Karr, Chris J. ;
Giangrande, Emily ;
Mohr, David C. .
JOURNAL OF MEDICAL INTERNET RESEARCH, 2011, 13 (03) :e55
[10]   Psychoeducation for depression, anxiety and psychological distress: a meta-analysis [J].
Donker, Tara ;
Griffiths, Kathleen M. ;
Cuijpers, Pim ;
Christensen, Helen .
BMC MEDICINE, 2009, 7