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      Attention and Cognitive Bias Modification Apps: Review of the Literature and of Commercially Available Apps

      review-article
      , MBBS, MRCPsych 1 , , , MMed, MRCPsych 1 , , PhD 1 , , MBBS, MMed 2 , , DM, FFPHM 3
      (Reviewer), (Reviewer), (Reviewer)
      JMIR mHealth and uHealth
      JMIR Publications
      attention bias, cognitive bias, smartphone, mHealth, psychiatry, telemedicine, mobile applications

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          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.

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          Most cited references35

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          Attentional bias in addictive behaviors: a review of its development, causes, and consequences.

          A wealth of research from the past two decades shows that addictive behaviors are characterized by attentional biases for substance-related stimuli. We review the relevant evidence and present an integration of existing theoretical models to explain the development, causes, and consequences of addiction-related attentional biases. We suggest that through classical conditioning, substance-related stimuli elicit the expectancy of substance availability, and this expectancy causes both attentional bias for substance-related stimuli and subjective craving. Furthermore, attentional bias and craving have a mutual excitatory relationship such that increases in one lead to increases in the other, a process that is likely to result in substance self-administration. Cognitive avoidance strategies, impulsivity, and impaired inhibitory control appear to influence the strength of attentional biases and subjective craving. However, some measures of attentional bias, particularly the addiction Stroop, might reflect multiple underlying processes, so results need to be interpreted cautiously. We make several predictions that require testing in future research, and we discuss implications for the treatment of addictive behaviors.
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            Cognitive bias modification: A review of meta-analyses.

            Cognitive bias modification (CBM) is a novel, but controversial intervention with considerable divergence amongst conclusions in individual studies and reviews. This systematic review synthesizes meta-analyses of CBM to determine whether CBM is effective, and what parameters most reliably evoke the process of CBM.
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              There is an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders.

              Mental health apps are viewed as a promising modality to extend the reach of mental health care beyond the clinic. They do so by providing a means of assessment, tracking, and treatment through a smartphone. Given that nearly 2/3 of the American population owns a smartphone, mental health apps offer the possibility of overcoming treatment barriers such as geographic location or financial barriers. Unfortunately, the excitement surrounding mental health apps may be premature as the current supporting literature regarding their efficacy is limited. The app marketplace is littered with apps claiming to treat or assess symptoms, but even those created by reputable organizations or those incorporating components of evidence-based treatments have not yet been validated in terms of their efficacy. This review aims to provide a comprehensive review of the current state of the mental health app literature by examining published reports of apps designed for DSM-5 anxiety and mood disorders, OCD, and PTSD. The breadth of apps reviewed includes those oriented around assessment, symptom tracking, and treatment as well as "multipurpose" apps, which incorporate several of these components. This review will also present some of the most popular mental health apps which may have clinical utility and could be prescribed to clients. While we discuss many potential benefits of mental health apps, we focus on a number of issues that the current state of the app literature presents. Overall there is a significant disconnect between app developers, the scientific community and health care, leaving the utility of existing apps questionable.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                May 2018
                24 May 2018
                : 6
                : 5
                : e10034
                Affiliations
                [1] 1 National Addictions Management Service Institute of Mental Health Singapore Singapore
                [2] 2 Medical Board / Department of Development Psychiatry Institute of Mental Health Singapore Singapore
                [3] 3 Department of Family Medicine and Primary Care Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore Singapore
                Author notes
                Corresponding Author: Melvyn Zhang melvynzhangweibin@ 123456gmail.com
                Author information
                http://orcid.org/0000-0001-8385-2345
                http://orcid.org/0000-0001-8503-8240
                http://orcid.org/0000-0002-6672-404X
                http://orcid.org/0000-0003-0718-9363
                http://orcid.org/0000-0003-1883-6124
                Article
                v6i5e10034
                10.2196/10034
                5992457
                29793899
                877551f4-05cf-47b0-ad46-a39fdf9f482a
                ©Melvyn Zhang, JiangBo Ying, Guo Song, Daniel SS Fung, Helen Smith. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 24.05.2018.

                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 mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 4 February 2018
                : 13 April 2018
                : 19 April 2018
                : 10 May 2018
                Categories
                Review
                Review

                attention bias,cognitive bias,smartphone,mhealth,psychiatry,telemedicine,mobile applications

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