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Social Stories™ is one of the most popular interventions for autistic children and has been researched extensively. However, effectiveness data has been gathered mainly through single-participant designs which generate outcomes which can lack generalizability and social validity. Stories Online For Autism (SOFA) is a digital application which supports the development and delivery of Social Stories in a real-world setting and has the potential to contribute toward furthering (1) Social Stories research and (2) research on digital applications for autism by gathering large data sets from multiple participants. Three data sets ( N  = 856) were gathered through the SOFA app and were analyzed to investigate three key variables: What predicted closeness-to-goal of the Social Stories (as rated by an adult/parent/guardian, n  = 568); the child's comprehension of the Social Stories (assessed by story comprehension questions, n  = 127); and the child's rating of the enjoyability of the Social Stories ( n  = 161). A merged data set then investigated correlations between these three key variables. Age range (≤15), gender, autism diagnosis, and the child's level of language understanding were the potential predictors for these three key variables. Regression analysis indicated that parental closeness-to-goal ratings for their children were highest for children who were younger and more verbal. Regression analysis also indicated that older children scored higher in comprehension assessment, and autistic children rated the Social Stories as more enjoyable. Closeness-to-goal, comprehension scores and enjoyment ratings did not significantly correlate with each other. This is the largest study of Social Stories effectiveness, which was enabled through the collection of data through a digital app from multiple participants. The results indicate that digital social stories are particularly effective for younger verbal children. While this was the case for all children, it was particularly true for autistic children and female (and gender-diverse) children. For the first time, the gathering of large digital data sets has highlighted that while digital Social Stories can be effective for autistic males, they can be more effective for autistic females and gender-diverse autistic individuals. Thus, the SOFA app can support the investigation of the factors which influence Social Stories outcomes that are generalizable and with high social validity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Camilleri, Maras and Brosnan.)

Social Stories™ (SS) is one of the most popular and researched interventions for autistic children. To date, research that focuses on outcomes has been prioritized over the investigation of the psychological mechanisms that inform the intervention. In this article we consider theoretical accounts proposed thus far which could underpin SS. We argue that mechanisms that are based on social deficit theories lack validity, and propose a rule-based theoretical account to inform a strengths-based approach toward conceptualizing the mechanisms that underpin SS. We apply this account to the 'double-empathy problem' to propose that SS can be adapted to involve all parties in the development and delivery of SS support by adopting a rule-based perspective. We use the example of systemizing (the drive to analyze and explore systems in terms of 'if-and-then' rules), which is proposed to be a relative autistic strength, as a form of rule-based thinking that can provide a theoretical account of SS and a framework to address the double-empathy problem., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Camilleri, Maras and Brosnan.)