%0 Journal Article
%@ 2368-7959
%I JMIR Publications
%V 6
%N 10
%P e14166
%T Conversational Agents in the Treatment of Mental Health Problems: Mixed-Method Systematic Review
%A Gaffney,Hannah
%A Mansell,Warren
%A Tai,Sara
%+ , School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, 2nd Floor, Zochonis Building, Manchester, M13 9PL, United Kingdom, 44 161 306 0400, hannah.gaffney-2@postgrad.manchester.ac.uk
%K artificial intelligence
%K mental health
%K stress, pychological
%K psychiatry
%K therapy, computer-assisted
%K conversational agent
%K chatbot
%K digital health
%D 2019
%7 18.10.2019
%9 Review
%J JMIR Ment Health
%G English
%X Background: The use of conversational agent interventions (including chatbots and robots) in mental health is growing at a fast pace. Recent existing reviews have focused exclusively on a subset of embodied conversational agent interventions despite other modalities aiming to achieve the common goal of improved mental health. Objective: This study aimed to review the use of conversational agent interventions in the treatment of mental health problems. Methods: We performed a systematic search using relevant databases (MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane library). Studies that reported on an autonomous conversational agent that simulated conversation and reported on a mental health outcome were included. Results: A total of 13 studies were included in the review. Among them, 4 full-scale randomized controlled trials (RCTs) were included. The rest were feasibility, pilot RCTs and quasi-experimental studies. Interventions were diverse in design and targeted a range of mental health problems using a wide variety of therapeutic orientations. All included studies reported reductions in psychological distress postintervention. Furthermore, 5 controlled studies demonstrated significant reductions in psychological distress compared with inactive control groups. In addition, 3 controlled studies comparing interventions with active control groups failed to demonstrate superior effects. Broader utility in promoting well-being in nonclinical populations was unclear. Conclusions: The efficacy and acceptability of conversational agent interventions for mental health problems are promising. However, a more robust experimental design is required to demonstrate efficacy and efficiency. A focus on streamlining interventions, demonstrating equivalence to other treatment modalities, and elucidating mechanisms of action has the potential to increase acceptance by users and clinicians and maximize reach. 
%M 31628789
%R 10.2196/14166
%U https://mental.jmir.org/2019/10/e14166
%U https://doi.org/10.2196/14166
%U http://www.ncbi.nlm.nih.gov/pubmed/31628789