# A Big Data Approach Toward the Development of a New Quantitative Measure of Restricted and Repetitive Behaviors > **NIH NIH R21** · STANFORD UNIVERSITY · 2020 · $236,550 ## Abstract Project Summary Restricted and repetitive behaviors (RRB) are a core feature of autism spectrum disorder (ASD) and also occur across a range of other neurodevelopmental disorders. RRB present a major barrier to learning and adaptation, interfere with family functioning and present a source of considerable stress for parents. Despite their clinical significance, underlying mechanisms behind this complex behavioral domain are poorly understood and effective, targeted, individually tailored treatment options are currently lacking. One of the major barriers to moving the RRB research agenda forward has been the lack of clarity around the structure and conceptualization of RRB and the limitations of the currently available measures, particularly in terms of their (i) inability to comprehensively capture the full range of RRB and (ii) lack of sensitivity to treatment-related change. Therefore, the overarching aim of this project is to develop a parent report measure for comprehensive and quantitative RRB assessment applicable across clinical populations and across the life- span and useful in both etiological- and treatment-related research. In order to achieve this goal, we will first conduct advanced statistical analyses of multiple, large, high-quality datasets containing a range of currently available measures in order to achieve fine-grained differentiation between distinct RRB domains (Specific Aim 1) and to identify domains not adequately captured by the current measures (Specific Aim 2). The implementation of this initial phase of the project will ensure that robustness and generalizability of the factor structures for each individual measure across age, developmental level, gender, and diagnostic status, is established and that generalizable core RRB structure across the currently available RRB instruments is identified. Neither of these two different aspects have been comprehensively addressed before. Robust derived RRB factor structure, together with the identification of potential RRB domains that might be under- represented and not adequately depicted by the current instruments, together with the systematic review of the literature will inform the development of items of the new scale to capture the full range of RRB. The pilot version of the new scale will be psychometrically evaluated online within a large sample of children and adolescents with ASD (Specific Aim 3). This project will lay the foundation for future investigations aimed at further refinement of the newly developed informant-based scale and the development of a clinician interview and objective instrument, as well as their validation across ASD ansd neurodevelopmental disorders, and the testing of their utility as a clinical outcome measure. ## Key facts - **NIH application ID:** 9874787 - **Project number:** 1R21MH121876-01 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** ANTONIO HARDAN - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $236,550 - **Award type:** 1 - **Project period:** 2019-12-06 → 2021-10-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9874787 ## Citation > US National Institutes of Health, RePORTER application 9874787, A Big Data Approach Toward the Development of a New Quantitative Measure of Restricted and Repetitive Behaviors (1R21MH121876-01). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/9874787. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*