Development and validation of a digital burnout scale in artificial intelligence era

Area of Science:

• Educational Technology
• Psychology
• Higher Education

Background:

• AI adoption in higher education increases digital demands on students.
• Digital burnout risk is rising due to these demands.
• Existing instruments lack validation for AI-enhanced learning contexts.

Purpose of the Study:

• Develop and validate a comprehensive Digital Burnout Scale for college students.
• Ground the scale in the Stressor-Strain-Outcome (SSO) model and Conservation of Resources (COR) theory.
• Provide a psychometrically robust tool for assessing digital burnout.

Main Methods:

• Multi-stage mixed-methods design.
• Qualitative interviews for item generation.
• Large-scale surveys for quantitative validation using exploratory and confirmatory factor analyses.
• Reliability testing and model comparison.

Main Results:

• A six-dimension structure of digital burnout was supported: Digital Aging, Emotional Exhaustion, Cognitive Overload, Cognitive Dissonance, Digital Deprivation, and Behavioral Addictions.
• The scale demonstrated satisfactory convergent and discriminant validity.
• The scale exhibits strong psychometric robustness.

Conclusions:

• The validated Digital Burnout Scale is a reliable, theory-driven instrument for assessing student digital burnout in the AI era.
• The scale offers practical value for identifying at-risk students and designing interventions.
• This research addresses a critical gap in measuring digital burnout in evolving educational landscapes.