A new method for identifying and evaluating depressive disorders in young people based on cognitive neurocomputing:...

Area of Science:

• Neuroscience
• Computational Psychiatry
• Digital Health

Background:

• Depressive disorders are prevalent in youth, yet objective diagnostic tools are lacking.
• Cognitive impairment is a core feature of depression, offering potential for objective assessment.
• Current methods for identifying and evaluating depression in young people are limited.

Purpose of the Study:

• To develop and validate a novel cognitive neurocomputing method for identifying and evaluating depressive disorders in young people.
• To assess cognitive impairments including attention, executive dysfunction, and information processing speed.
• To identify digital biomarkers for these cognitive impairments.

Main Methods:

• Development of a digital evaluation paradigm to assess cognitive functions.
• Mining of digital biomarkers associated with cognitive impairments in youth depression.
• Inclusion of 50 young patients with depressive disorders and 47 healthy controls for validation.

Main Results:

• Significant differences in digital biomarkers for attention, executive function, and information processing speed were found between patients and controls.
• Four key digital biomarkers were identified through stepwise regression analysis.
• The combined biomarkers achieved an area under the curve of 0.927 for distinguishing depressive disorders.

Conclusions:

• The proposed method offers a rapid and objective way to characterize and quantify cognitive impairment in young people with depressive disorders.
• This approach provides a novel tool for organizations like schools to identify at-risk youth.
• Human-computer interaction-based digital biomarkers can aid in early detection and evaluation of youth depression.