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- Title
Digital assessment of cognitive-affective biases related to mental health.
- 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
- Abstract
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. Author summary: This study aimed to provide a scientific basis for digital therapeutic tools assessing and monitoring affective and cognitive health using user-friendly tasks. We developed three emotional cognitive tasks (eFlanker, eGoNoGo, and eSocial) on a wide range of participants (children, young adults, older adults, and depression patients). Abstract scores were extracted from a large set of behavioral features such as reaction time and accuracy to positive, negative, and neutral animated face stimuli; a subset of these scores were found to be strongly associated with emotional bias and mental health. Two weeks of training with gamified versions of the tasks decreased the emotional bias, which was also related to the reduction of anxiety symptoms. Using a wearable EEG system, we found that changes in emotional bias after training were related to changes in frontal alpha and gamma activity. These results demonstrated the potential effectiveness of digital gamified applications for the monitoring and reduction of emotional bias in cognition, which was related to mental health measures such as anxiety and depression.
- Subjects
BRAIN physiology; COMPETENCY assessment (Law); DIGITAL technology; SELF-esteem testing; STATISTICAL correlation; REPEATED measures design; COGNITIVE testing; DELUSIONS; TASK performance; CENTER for Epidemiologic Studies Depression Scale; DATA analysis; RESEARCH funding; QUESTIONNAIRES; EXECUTIVE function; ELECTROENCEPHALOGRAPHY; ANXIETY; DESCRIPTIVE statistics; STATE-Trait Anxiety Inventory; GAMES; MEMORY; ANALYSIS of variance; STATISTICS; PSYCHOLOGICAL tests; AFFECT (Psychology); FACTOR analysis; MENTAL depression; SELF-perception
- Publication
PLoS Digital Health, 2024, Vol 3, Issue 8, p1
- ISSN
2767-3170
- Publication type
Article
- DOI
10.1371/journal.pdig.0000595