Literature DB >> 28414042

Promising technological innovations in cognitive training to treat eating-related behavior.

Evan M Forman1, Stephanie P Goldstein2, Daniel Flack2, Brittney C Evans2, Stephanie M Manasse2, Cara Dochat2.   

Abstract

One potential reason for the suboptimal outcomes of treatments targeting appetitive behavior, such as eating and alcohol consumption, is that they do not target the implicit cognitive processes that may be driving these behaviors. Two groups of related neurocognitive processes that are robustly associated with dysregulated eating and drinking are attention bias (AB; selective attention to specific stimuli) and executive function (EF; a set of cognitive control processes such as inhibitory control, working memory, set shifting, that govern goal-directed behaviors). An increasing body of work suggests that EF and AB training programs improve regulation of appetitive behaviors, especially if trainings are frequent and sustained. However, several key challenges, such as adherence to the trainings in the long term, and overall potency of the training, remain. The current manuscript describes five technological innovations that have the potential to address difficulties related to the effectiveness and feasibility of EF and AB trainings: (1) deployment of training in the home, (2) training via smartphone, (3) gamification, (4) virtual reality, and (5) personalization. The drawbacks of these innovations, as well as areas for future research, are also discussed. The above-mentioned innovations are likely to be instrumental in the future empirical work to develop and evaluate effective EF and AB trainings for appetitive behaviors.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Alcohol; Computer training; Digital health behavior change; Eating; Executive function

Mesh:

Year:  2017        PMID: 28414042      PMCID: PMC5641227          DOI: 10.1016/j.appet.2017.04.011

Source DB:  PubMed          Journal:  Appetite        ISSN: 0195-6663            Impact factor:   3.868


  95 in total

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