Web-based cognitive bias modification interventions for psychiatric disorders : scoping review

Background: Cognitive biases refer to automatic attentional or interpretational tendencies, which result in individuals with addictive disorders to automatically attend to substance-related stimuli and those with anxiety disorders to attend to threatening stimuli. To date, several studies have exami...

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Main Authors: Zhang, Melvyn, Ying, Jiangbo, Song, Guo, Fung, Daniel S. S., Smith, Helen
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142394
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spelling sg-ntu-dr.10356-1423942020-11-01T05:20:36Z Web-based cognitive bias modification interventions for psychiatric disorders : scoping review Zhang, Melvyn Ying, Jiangbo Song, Guo Fung, Daniel S. S. Smith, Helen Lee Kong Chian School of Medicine (LKCMedicine) Family Medicine and Primary Care Science::Medicine Cognitive Bias Attention Bias Background: Cognitive biases refer to automatic attentional or interpretational tendencies, which result in individuals with addictive disorders to automatically attend to substance-related stimuli and those with anxiety disorders to attend to threatening stimuli. To date, several studies have examined the efficacy of cognitive bias modification, and meta-analytical studies have synthesized the evidence for overall efficacy. The clinical utility of cognitive bias modification interventions has previously been limited to the confines of a laboratory, but recent advances in Web technologies can change this. Objective: This scoping review aimed to determine the scope of Web-based cognitive bias interventions and highlight their effectiveness. Methods: Databases (PubMed and MEDLINE, EMBASE, PsycINFO, ScienceDirect, and Cochrane Central) were searched from inception to December 5, 2017. The following search terminologies were used: (“attention bias” OR “cognitive bias” OR “approach bias” OR “avoidance bias” OR “interpretative bias”) AND (“Internet” OR “Web” OR “Online”). The methods for this scoping review are based on the previously published protocol. For the synthesis of the evidence, a narrative synthesis was undertaken, as a meta-analysis was not appropriate, given the lack of reported effect sizes and the heterogeneity in the outcomes reported. Results: Of the 2674 unique articles identified, we identified 22 randomized controlled studies that met our inclusion criteria: alcohol use disorder (n=2), tobacco use disorder (n=2), depressive disorder (n=3), anxiety and depressive symptoms in adolescents (n=3), obsessive-compulsive disorder (OCD; n=2), social anxiety disorder (n=9), and anxiety disorder (n=1). The sample sizes of these studies ranged from 16 to 434 participants. There is preliminary evidence to suggest that Web-based interventions could reduce biases among adolescents with heightened symptoms of anxiety and depression and among individuals with OCD. Conclusions: This is the first scoping review that mapped out the scope of cognitive bias modification interventions for psychiatric disorders. Web-based interventions have been applied predominantly for social anxiety and addictive disorders. Larger cohorts must be used in future studies to better determine the effectiveness of Web-based cognitive bias interventions. Published version 2020-06-22T01:13:20Z 2020-06-22T01:13:20Z 2018 Journal Article Zhang, M., Ying, J., Song, G., Fung, D. S. S., & Smith, H. (2019). Web-based cognitive bias modification interventions for psychiatric disorders : scoping review. JMIR Mental Health, 6(10), e11841-. doi:10.2196/11841 2368-7959 https://hdl.handle.net/10356/142394 10.2196/11841 31651410 10 6 en JMIR Mental Health © 2019 Melvyn Wb Zhang, Jiangbo Ying, Guo Song, Daniel S S Fung, Helen Smith. Originally published in JMIR Mental Health (http://mental.jmir.org), 26.10.2019. 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 JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Medicine
Cognitive Bias
Attention Bias
spellingShingle Science::Medicine
Cognitive Bias
Attention Bias
Zhang, Melvyn
Ying, Jiangbo
Song, Guo
Fung, Daniel S. S.
Smith, Helen
Web-based cognitive bias modification interventions for psychiatric disorders : scoping review
description Background: Cognitive biases refer to automatic attentional or interpretational tendencies, which result in individuals with addictive disorders to automatically attend to substance-related stimuli and those with anxiety disorders to attend to threatening stimuli. To date, several studies have examined the efficacy of cognitive bias modification, and meta-analytical studies have synthesized the evidence for overall efficacy. The clinical utility of cognitive bias modification interventions has previously been limited to the confines of a laboratory, but recent advances in Web technologies can change this. Objective: This scoping review aimed to determine the scope of Web-based cognitive bias interventions and highlight their effectiveness. Methods: Databases (PubMed and MEDLINE, EMBASE, PsycINFO, ScienceDirect, and Cochrane Central) were searched from inception to December 5, 2017. The following search terminologies were used: (“attention bias” OR “cognitive bias” OR “approach bias” OR “avoidance bias” OR “interpretative bias”) AND (“Internet” OR “Web” OR “Online”). The methods for this scoping review are based on the previously published protocol. For the synthesis of the evidence, a narrative synthesis was undertaken, as a meta-analysis was not appropriate, given the lack of reported effect sizes and the heterogeneity in the outcomes reported. Results: Of the 2674 unique articles identified, we identified 22 randomized controlled studies that met our inclusion criteria: alcohol use disorder (n=2), tobacco use disorder (n=2), depressive disorder (n=3), anxiety and depressive symptoms in adolescents (n=3), obsessive-compulsive disorder (OCD; n=2), social anxiety disorder (n=9), and anxiety disorder (n=1). The sample sizes of these studies ranged from 16 to 434 participants. There is preliminary evidence to suggest that Web-based interventions could reduce biases among adolescents with heightened symptoms of anxiety and depression and among individuals with OCD. Conclusions: This is the first scoping review that mapped out the scope of cognitive bias modification interventions for psychiatric disorders. Web-based interventions have been applied predominantly for social anxiety and addictive disorders. Larger cohorts must be used in future studies to better determine the effectiveness of Web-based cognitive bias interventions.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Zhang, Melvyn
Ying, Jiangbo
Song, Guo
Fung, Daniel S. S.
Smith, Helen
format Article
author Zhang, Melvyn
Ying, Jiangbo
Song, Guo
Fung, Daniel S. S.
Smith, Helen
author_sort Zhang, Melvyn
title Web-based cognitive bias modification interventions for psychiatric disorders : scoping review
title_short Web-based cognitive bias modification interventions for psychiatric disorders : scoping review
title_full Web-based cognitive bias modification interventions for psychiatric disorders : scoping review
title_fullStr Web-based cognitive bias modification interventions for psychiatric disorders : scoping review
title_full_unstemmed Web-based cognitive bias modification interventions for psychiatric disorders : scoping review
title_sort web-based cognitive bias modification interventions for psychiatric disorders : scoping review
publishDate 2020
url https://hdl.handle.net/10356/142394
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