Development and Validation of a Depression Scale for Online Assessment: Cross-Sectional Observational Study

Area of Science:

• Psychological assessment
• Digital mental health
• Computational linguistics

Background:

• Depression is often underrecognized due to limitations in traditional assessment tools.
• Digital environments offer novel ways to express emotional distress.
• Existing scales may not capture the nuances of online depressive symptom articulation.

Purpose of the Study:

• To develop and validate the Depression Scale for Online Assessment (DSO).
• To create a tool that captures ecologically valid expressions of depressive symptoms in digital contexts.

Main Methods:

• A cross-sectional study of 1151 adults.
• Exploratory and confirmatory factor analyses to determine scale structure.
• Assessed internal consistency and convergent validity with established depression measures.

Main Results:

• A 5-factor structure (social disconnection, suicide risk, depressed mood, negative self-concept, cognitive/somatic distress) was identified.
• The DSO demonstrated acceptable model fit and high internal consistency (Cronbach's α=0.95).
• Significant correlations with established scales (CESD-R, PHQ-9) supported convergent validity.

Conclusions:

• The DSO is a psychometrically sound tool for assessing depression.
• It captures both core and emerging expressions of depressive symptoms.
• Its digital adaptability is valuable for mobile and remote care settings.