Judgment behaviors differentiate depression from anxiety

Area of Science:

• Psychiatry
• Psychology
• Computational Psychiatry

Background:

• Depression and anxiety often present with overlapping symptoms, complicating diagnosis.
• Standard screening tools may lack specificity, hindering accurate differential diagnosis.
• Judgment alterations are observable in both conditions and can be quantified.

Purpose of the Study:

• To investigate if quantifiable judgment features from a picture rating task can distinguish between anxiety and depression.
• To assess the diagnostic utility of these judgment variables in a large adult population.

Main Methods:

• A cross-sectional study of 3476 US adults (ages 18-70) using the State Trait Anxiety Inventory (STAI) and Patient Health Questionnaire 9 (PHQ-9).
• Random forest classification was employed, utilizing 15 judgment variables and demographic data as predictors.
• Analysis focused on differentiating moderate-to-severe anxiety and depression symptom levels.

Main Results:

• Judgment variables achieved an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.798, demonstrating strong discriminative ability.
• These judgment features accounted for 83% of predictive importance, significantly outperforming demographic variables.
• Judgment features showed meaningful variations across different severities of anxiety and depression symptoms.

Conclusions:

• Quantifiable judgment features derived from a picture rating task can effectively differentiate anxiety from depression.
• These findings suggest a potential for a quick, low-cost, and unbiased tool to enhance diagnostic accuracy for these common mental health disorders.
• The identified judgment variations may reflect underlying motivational deficits and emotional blunting characteristic of these conditions.