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

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Τίτλος: Participatory Development and Psychometric Evaluation of the Introspective Predictive Processing Inventory: A Self-Report Measure for Autistic and Non-Autistic Adults
Γλώσσα: English
Συγγραφείς: Marik Roos, Hannah Storm, Lucie Zimmer, Tobias Schuwerk (ORCID 0000-0003-3720-7120)
Πηγή: Autism: The International Journal of Research and Practice. 2026 30(6):1593-1607.
Διαθεσιμότητα: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 15
Ημερομηνία έκδοσης: 2026
Τύπος εγγράφου: Journal Articles
Reports - Research
Tests/Questionnaires
Descriptors: Psychometrics, Measures (Individuals), Autism Spectrum Disorders, Adults, Measurement Techniques, Foreign Countries, Test Construction, Prediction
Γεωγραφικοί όροι: Germany, United Kingdom
DOI: 10.1177/13623613261443728
ISSN: 1362-3613
1461-7005
Περίληψη: 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.
Abstractor: As Provided
Entry Date: 2026
Αριθμός Καταχώρησης: EJ1506516
Βάση Δεδομένων: ERIC
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  Data: Participatory Development and Psychometric Evaluation of the Introspective Predictive Processing Inventory: A Self-Report Measure for Autistic and Non-Autistic Adults
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  Data: <searchLink fieldCode="AR" term="%22Marik+Roos%22">Marik Roos</searchLink><br /><searchLink fieldCode="AR" term="%22Hannah+Storm%22">Hannah Storm</searchLink><br /><searchLink fieldCode="AR" term="%22Lucie+Zimmer%22">Lucie Zimmer</searchLink><br /><searchLink fieldCode="AR" term="%22Tobias+Schuwerk%22">Tobias Schuwerk</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3720-7120">0000-0003-3720-7120</externalLink>)
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 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.
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