A review of attentional bias modification trainings for depression

Abstract

The major depressive disorder (MDD) is a common mental disability, characterized by persistent low mood, reduced vitality and interest, worse sleep, and high suicidal tendency. 1,2 It affects more than 350 million people throughout the world. 3,4 It is predicted that MDD would rank the first cause of disease burden by 2030. 5 The severe impact of MDD on human beings raised the necessity for its treatment. Accordingly, various therapeutic methods have been applied, including antidepressants, psychotherapy, and physical therapy. Antidepressants were the dominant method in MDD treatment, although it was accompanied by side effects such as insomnia, weight gain, loss of appetite, drug dependence, and other physiological responses that would have dramatic influences on people's daily life. [6][7][8] Besides that, the uncertainty of which medicine works well for a particular patient took a lot of time, effort, and money for treatment, resulting in unnecessary side effects and low medication adherence. 7,9 These weaknesses

Deployment of attention to facial expressions varies as a function of emotional quality—but not in alexithymic individuals

“…Beyond introspective differences in emotion perception ( 14 ) and poor emotion regulation ( 15 , 69 , 70 ), the lack of spontaneous attention deployment during the perception of positive stimuli could add to the vulnerability for depressive disorders in alexithymia. It is an interesting question whether attentional bias modification training ( 87 ) might be a useful therapeutic tool to promote gaze behavior toward positive social stimuli in alexithymic individuals.…”

Application of attentional bias modification to reduce attentional bias and emotional reactivity to stress in mildly depressed individuals

“…Using experimental paradigms to measure attention, such as the dot-probe task, the visual search task, and the spatial cueing task, ABM repeatedly trains participants to have a more appropriate attentional pattern. It intentionally places a target probe, which they must detect, in the location of the positive or neutral affective stimulus, causing participants to direct more attention to positive affective stimuli than negative affective stimuli (Lazarov et al, 2018 ; Li et al, 2023 ). Additionally, some studies found that ABM redirected toward neutral stimuli rather than negative stimuli enhances the ability to disengage from negative attentional biases (Yang et al, 2015 ; Klawohn et al, 2020 ).…”

“…Previous studies were found to be inconsistent regarding the stage of attention affected by ABM. It has been suggested that, although ABM is intended to modify the attentional bias in early attention (Sears et al, 2011 ), its effects are primarily focused on enhancing general attentional control (Bar-Haim, 2010 ; Sallard et al, 2018 ; Li et al, 2023 ). For example, ABM training in depression altered the functional connectivity of attentional network, including the anterior cingulate cortex and the middle frontal gyrus, a region of ventral lateral PFC (Beevers et al, 2015 ; Li et al, 2016 ).…”

Neural activations to loss anticipation mediates the association between difficulties in emotion regulation and screen media activities among early adolescent youth: A moderating role for depression

“…Excessive SMAs may be more likely to develop in people with depressed states ( Kiraly et al, 2020 ), possibly as SMAs could potentially be used as a maladaptive coping way to relieve depressive symptoms or negative emotional stress ( Wegmann and Brand, 2022 ). Studies have suggested that compared to adolescents with low levels of depressive symptoms, DER may be more likely to prevent adolescents with high levels of depressive symptoms from immediately disengaging from negative emotions in response to negative stimuli ( Lazarov et al, 2018 , Li et al, 2022 ). Difficulties disengaging could further increase adolescents’ motivations to engage in SMAs ( Kardefelt-Winther, 2014 ), and could also lead to higher risk for maladaptively using SMAs ( Teng et al, 2021 ).…”