Participatory Development and Psychometric Evaluation of the Introspective Predictive Processing Inventory: A...

Area of Science:

• Neuroscience
• Psychology
• Autism Research

Background:

• Traditional autism measures often lack authentic autistic perspectives.
• Predictive processing theory provides a framework for understanding autism, but lacks subjective assessment tools.
• Existing tools do not comprehensively capture the lived experiences of predictive processing differences in autism.

Purpose of the Study:

• To develop and validate the Introspective Predictive Processing Inventory (IPPI), a self-report measure for subjective predictive processing experiences in autism.
• To create a tool that reflects authentic autistic experiences and their daily consequences.
• To bridge predictive processing theory with lived autistic experiences.

Main Methods:

• Community-led participatory research to develop the IPPI (65-item initial version).
• Five-stage validation across three samples (N=790) using network optimization, factor analyses, and measurement invariance testing.
• Convergent validity assessment with established measures and independence from general cognitive abilities.

Main Results:

• Network optimization reduced the IPPI to 18 items with excellent reliability and discriminative power.
• A stable two-factor structure emerged: 'Prediction Integration and Interpretation' and 'Prediction Error Sensitivity and Stability Needs'.
• The IPPI demonstrated exceptional discriminative validity (AUC >0.97), strong convergent validity, and measurement invariance.

Conclusions:

• The IPPI is a reliable and valid self-report measure for assessing subjective predictive processing in autistic individuals.
• This tool advances autism research by integrating theory with lived experiences.
• The IPPI can inform the development of better support strategies and improve quality of life for autistic people.