Digital assessment of cognitive-affective biases related to mental health

With an increasing societal need for digital therapy solutions for poor mental health, we face a corresponding rise in demand for scientifically validated digital contents. In this study we aimed to lay a sound scientific foundation for the development of brain-based digital therapeutics to assess a...

Full description

Saved in:
Bibliographic Details
Published in:PLOS digital health Vol. 3; no. 8; p. e0000595
Main Authors: Park, Sang-Eon, Chung, Jisu, Lee, Jeonghyun, Kim, Minwoo Jb, Kim, Jinhee, Jeon, Hong Jin, Kim, Hyungsook, Woo, Choongwan, Kim, Hackjin, Lee, Sang Ah
Format: Journal Article
Language:English
Published: United States Public Library of Science 01-08-2024
Public Library of Science (PLoS)
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With an increasing societal need for digital therapy solutions for poor mental health, we face a corresponding rise in demand for scientifically validated digital contents. In this study we aimed to lay a sound scientific foundation for the development of brain-based digital therapeutics to assess and monitor cognitive effects of social and emotional bias across diverse populations and age-ranges. First, we developed three computerized cognitive tasks using animated graphics: 1) an emotional flanker task designed to test attentional bias, 2) an emotional go-no-go task to measure bias in memory and executive function, and 3) an emotional social evaluation task to measure sensitivity to social judgments. Then, we confirmed the generalizability of our results in a wide range of samples (children (N = 50), young adults (N = 172), older adults (N = 39), online young adults (N=93), and depression patients (N = 41)) using touchscreen and online computer-based tasks, and devised a spontaneous thought generation task that was strongly associated with, and therefore could potentially serve as an alternative to, self-report scales. Using PCA, we extracted five components that represented different aspects of cognitive-affective function (emotional bias, emotional sensitivity, general accuracy, and general/social attention). Next, a gamified version of the above tasks was developed to test the feasibility of digital cognitive training over a 2-week period. A pilot training study utilizing this application showed decreases in emotional bias in the training group (that were not observed in the control group), which was correlated with a reduction in anxiety symptoms. Using a 2-channel wearable EEG system, we found that frontal alpha and gamma power were associated with both emotional bias and its reduction across the 2-week training period.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
SAL, HaK, and CW hold a patent pending (PCT/KR2023/015263 filed April 10, 2023) entitled “Finding Blue Integrated Depression Screening Application”. The authors declare no other potential conflicts of interest with respect to research, authorship, financial relationships, and/or publication of the article.
ISSN:2767-3170
2767-3170
DOI:10.1371/journal.pdig.0000595