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|Title:||Emotional bias modification in youths with attention deficit hyperactivity disorder (ADHD) : new research vista||Authors:||Zhang, Melvyn
Fung, Daniel Shuen Sheng
|Keywords:||Social sciences::Psychology||Issue Date:||2020||Source:||Zhang, M., Chow, A., Vallabhajosyula, R., & Fung, D. S. S. (2020). Emotional bias modification in youths with attention deficit hyperactivity disorder (ADHD) : new research vista. International Journal of Environmental Research and Public Health, 17(11), 4028-. doi:10.3390/ijerph17114028||Project:||NMRC/Fellowship/0048/2017||Journal:||International Journal of Environmental Research and Public Health||Abstract:||Whilst cognitive bias modification was initially used in the treatment of anxiety disorders, it is also currently being used for the treatment of other psychopathologies. In fact, cognitive bias modification has been especially well-investigated amongst children and adolescents. A recent review suggests some evidence for the modification of interpretative biases amongst children with neurodevelopment disorders. There have since been other studies reporting of the existence of other cognitive biases, such as emotional biases, amongst individuals with attention deficit hyperactivity disorder (ADHD). This perspective article will discuss the epidemiology of ADHD and the nature of emotional biases that are present amongst individuals with ADHD. This perspective article also reviewed some of the studies that have assessed and modified emotional biases in individuals with ADHD. A total of three studies have been identified from the published literature that provide evidence for targeting emotional biases amongst individuals with ADHD. These studies provide us with preliminary evidence for the effectiveness of modifying emotional biases and how it could help in ameliorating symptoms related to emotional dysregulation. There needs to be future research in this area with further evidence supporting the effectiveness of modifying emotional biases. It is also crucial for future research to determine which of these tools is best at detecting such biases, and which of these tools are versatile enough and non-invasive that they could safely be implemented for both research and clinical needs.||URI:||https://hdl.handle.net/10356/145741||ISSN:||1661-7827||DOI:||10.3390/ijerph17114028||Rights:||© 2020 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||LKCMedicine Journal Articles|
Updated on Nov 29, 2021
Updated on Nov 29, 2021
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