Participatory Development and Psychometric Evaluation of the Introspective Predictive Processing Inventory: A Self-Report Measure for Autistic and Non-Autistic Adults.

Traditional self-report autism measures are often constructed from an "outside view" by non-autistic researchers rather than reflecting authentic autistic experiences. Predictive processing theory offers a framework for understanding autism, but comprehensive tools assessing the subjective manifestations of predictive processing differences and associated challenges have been lacking. This study aimed to develop and validate the Introspective Predictive Processing Inventory (IPPI), a self-report measure assessing predictive processing characteristics and their subjective consequences in everyday life. Through community-led, participatory research, we developed an initial 65-item version in German and English, and employed a five-stage validation approach across three samples (N = 790). We used network-based item optimization, exploratory and confirmatory factor analyses, measurement invariance testing, and convergent validity assessment. Network optimization reduced the scale to 18 items while maintaining excellent reliability and improved discriminative power. Exploratory factor analysis revealed a stable two-factor structure: "Prediction Integration and Interpretation" and "Prediction Error Sensitivity and Stability Needs". The IPPI demonstrated exceptional discriminative validity (area under the curve >0.97), strong convergent validity with established measures, measurement invariance across groups, and independence from general cognitive abilities. It provides a tool for assessing predictive processing experiences and their daily consequences, advancing autism research that bridges predictive processing theory with lived experiences.Lay AbstractMost questionnaires used to understand autism are created by non-autistic researchers who imagine what autism might be like, rather than capturing what autistic people actually experience. Scientists have a theory called "predictive processing" that suggests our brains are constantly trying to predict what will happen next in our environment. When these predictions don't match reality, it can cause stress and difficulties in daily life. However, there was no good way to measure these internal experiences and daily challenges that autistic people face. To address this gap, an autistic researcher worked with autistic community members and non-autistic researchers to create a questionnaire called the Introspective Predictive Processing Inventory (IPPI). They started with 65 questions, developed both German and English versions, and tested it with 790 autistic and non-autistic adults from mostly Germany and the United Kingdom. Using advanced statistical methods, they refined it down to 18 key questions that capture two main areas: difficulties understanding and integrating information from social situations and the environment, and sensitivity to unexpected changes with strong needs for predictability, causing distress when things don't go as expected. The final 18-question IPPI was highly reliable and could accurately distinguish between autistic and non-autistic people 97% of the time. Importantly, these differences were not related to intelligence levels. These findings provide researchers and clinicians with a new tool to understand the internal experiences of autistic people from their own perspective. This could help develop better support strategies, improve quality of life, and advance autism research that truly reflects autistic experiences rather than outside assumptions about autism.