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Title: Attention and cognitive bias modification apps: review of the literature and of commercially available apps
Authors: Zhang, Melvyn
Ying, JiangBo
Song, Guo
Fung, Daniel Shuen Sheng
Smith, Helen
Keywords: Cognitive Bias
Attention Bias
Issue Date: 2018
Source: Zhang, M., Ying, J., Song, G., Fung, D. S., & Smith, H. (2018). Attention and Cognitive Bias Modification Apps: Review of the Literature and of Commercially Available Apps. JMIR mHealth and uHealth, 6(5), e10034-. doi:10.2196/10034
Series/Report no.: JMIR mHealth and uHealth
Abstract: Background: Automatic processes, such as attentional biases or interpretative biases, have been purported to be responsible for several psychiatric disorders. Recent reviews have highlighted that cognitive biases may be modifiable. Advances in eHealth and mHealth have been harnessed for the delivery of cognitive bias modification. While several studies have evaluated mHealth-based bias modification intervention, no review, to our knowledge, has synthesized the evidence for it. In addition, no review has looked at commercial apps and their functionalities and methods of bias modification. A review is essential in determining whether scientifically validated apps are available commercially and the proportion of commercial apps that have been evaluated scientifically. Objective: The objective of this review was primarily to determine the proportion of attention or cognitive bias modification apps that have been evaluated scientifically and secondarily to determine whether the scientifically evaluated apps were commercially available. We also sought to identify commercially available bias modification apps and determine the functionalities of these apps, the methods used for attention or cognitive bias modification, and whether these apps had been evaluated scientifically. Methods: To identify apps in the published literature, we searched PubMed, MEDLINE, PsycINFO, and Scopus for studies published from 2000 to April 17, 2018. The search terms used were “attention bias” OR “cognitive bias” AND “smartphone” OR “smartphone application” OR “smartphone app” OR “mobile phones” OR “mobile application” OR mobile app” OR “personal digital assistant.” To identify commercial apps, we conducted a manual cross-sectional search between September 15 and 25, 2017 in the Apple iTunes and Google Play app stores. The search terms used to identify the apps were “attention bias” and “cognitive bias.” We also conducted a manual search on the apps with published evaluations. Results: The effectiveness of bias modification was reported in 7 of 8 trials that we identified in the published literature. Only 1 of the 8 previously evaluated apps was commercially available. The 17 commercial apps we identified tended to use either an attention visual search or gamified task. Only 1 commercial app had been evaluated in the published literature. Conclusions: This is perhaps the first review to synthesize the evidence for published mHealth attention bias apps. Our review demonstrated that evidence for mHealth attention bias apps is inconclusive, and quite a few commercial apps have not been validated scientifically.
DOI: 10.2196/10034
Rights: © 2018 Melvyn Zhang, JiangBo Ying, Guo Song, Daniel SS Fung, Helen Smith. Originally published in JMIR Mhealth and Uhealth (, 24.05.2018. This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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