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The Depressed Teenage Brain: Chatbot Psychoeducation

Authors :
Kim K. Dysthe, MD
Jan I. Røssberg, MD, PhD
Petter B. Brandtzaeg, PhD
Marita Skjuve, MA
Asbjørn Følstad, PhD
Ole R. Haavet, MD, PhD
Atle Klovning, MD, PhD
Source :
Mayo Clinic Proceedings: Digital Health, Vol 1, Iss 3, Pp 334-342 (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Objective: To gain the knowledge needed to develop a cognitive behavioral intervention and reliable psychoeducation applicable for conversational artificial intelligence models, we investigated the underlying constructs of thoughts common to cognitive distortions found in online questions written by adolescents with symptoms of depression. Methods: From June 30, 2020, to October 30, 2020, we analyzed a sample of 100 written questions from adolescents about depression posted on an online information service using a qualitative analysis guided by cognitive behavioral theory and informed by the neuroscience of adolescence. Results: Four types of cognitive distortions (CDs) were found: (1) emotional reasoning, (2) mind reading, (3) catastrophizing, and (4) labeling. Our analysis suggested 3 underlying constructs common to the different CDs: (1) emotional states appearing as reality, (2) experiencing this emotional reality as something others think, and (3) generalizing such beliefs to every relation and the future. These constructs may signify events leading to a ruminative state that seems hard to escape. Conclusion: The 4 different CDs originate from 3 underlying constructs possibly associated with adolescent neurodevelopment. This study indicates a potential to reveal the underlying constructs of thought common to different CDs, thus making CDs more useful as a target point in artificial intelligence–based technological information and intervention tools.

Details

Language :
English
ISSN :
29497612
Volume :
1
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Mayo Clinic Proceedings: Digital Health
Publication Type :
Academic Journal
Accession number :
edsdoj.237e004efd4343bf970cb1e78f4edd49
Document Type :
article
Full Text :
https://doi.org/10.1016/j.mcpdig.2023.03.008