Teaching Children with Autism Spectrum Disorder Desire-Based Emotion Prediction and Cause.

Area of Science:

• Developmental Psychology
• Clinical Psychology
• Special Education

Background:

• Perspective-taking, specifically predicting others' emotions, is crucial for social interaction.
• Children with autism spectrum disorder (ASD) often face challenges in understanding and inferring others' emotional states.
• Existing research highlights the need for effective teaching strategies to improve emotion prediction skills in this population.

Purpose of the Study:

• To evaluate a behavioral teaching procedure designed to enhance emotion prediction and causal inference skills in children with ASD.
• To investigate the ability of children with ASD to predict emotions based on met or unmet desires.
• To assess the generalization of learned emotion prediction skills to novel scenarios.

Main Methods:

• A training package incorporating multiple-exemplar training, rules, modeling, prompting, and reinforcement was implemented.
• The study included three children with autism spectrum disorder who did not possess the target skill at baseline.
• Participants were presented with scenarios involving met or unmet desires to predict emotional responses.

Main Results:

• The behavioral teaching procedure resulted in the acquisition of emotion prediction and causal inference skills.
• Learned skills generalized to untrained, novel scenarios.
• Generalization to in-vivo play activities required direct, in-person training.

Conclusions:

• The evaluated behavioral teaching procedure is effective in teaching children with autism spectrum disorder to predict others' emotions based on desires.
• While generalization to novel scenarios was observed, direct in-vivo training is necessary for application in play-based contexts.
• This research provides valuable insights for developing targeted interventions to improve social-emotional understanding in children with ASD.