Effective digital support for autism: digital social stories

Area of Science:

• Autism Spectrum Disorder Interventions
• Digital Health Applications
• Educational Psychology

Background:

• Social Stories™ are a popular intervention for autistic children, but effectiveness data often lacks generalizability due to reliance on single-participant designs.
• Existing research has limitations in social validity and broad applicability.
• Digital applications offer a novel approach to gather large-scale, real-world data for autism interventions.

Purpose of the Study:

• To investigate the effectiveness of digital Social Stories using the Stories Online For Autism (SOFA) app.
• To identify predictors of Social Stories' closeness-to-goal, child comprehension, and enjoyability.
• To explore correlations between these key variables in a large, multi-participant dataset.

Main Methods:

• Analysis of three datasets (N=856) collected via the SOFA app.
• Investigated closeness-to-goal (n=568), comprehension (n=127), and enjoyability (n=161) of Social Stories.
• Regression analysis examined predictors including age, gender, autism diagnosis, and language level.

Main Results:

• Younger, more verbal children had higher parental closeness-to-goal ratings.
• Older children showed higher comprehension scores.
• Autistic children rated Social Stories as more enjoyable.
• Closeness-to-goal, comprehension, and enjoyment did not significantly correlate.
• Digital Social Stories were more effective for younger, verbal, autistic, female, and gender-diverse children.

Conclusions:

• The SOFA app facilitates large-scale data collection for autism research, enhancing generalizability and social validity.
• Digital Social Stories show particular effectiveness for younger, verbal autistic children, especially females and gender-diverse individuals.
• Findings highlight the potential of digital tools to refine and personalize autism interventions.