A Multimodal Messaging App (MAAN) for Adults With Autism Spectrum Disorder: Mixed Methods Evaluation Study

Area of Science:

• Assistive Technology
• Autism Spectrum Disorder Research
• Human-Computer Interaction

Background:

• Individuals with autism spectrum disorder (ASD) often face challenges in social interaction and communication.
• Existing communication support techniques are not integrated into current social media applications for ASD.
• There is a need for technology-driven solutions to enhance communication for adults with ASD.

Purpose of the Study:

• To investigate the impact of integrating accessibility features (text-to-speech, speech-to-text, communication symbols) into a messaging app (MAAN) for adults with ASD.
• To assess the potential of these features in improving social and communication skills.
• To evaluate the app's effectiveness in reducing social loneliness among adults with ASD.

Main Methods:

• Expert interviews were conducted to inform the app's design.
• Seven adults with ASD participated in a 10-16 week usage study.
• Data collected included app interaction logs, user questionnaires (SELSA-S, MARS-US), and post-study interviews.

Main Results:

• The social loneliness subscale of the SELSA-S showed a statistically significant increase post-study (P=.04).
• Usage of text-to-speech and communication symbol features strongly correlated with changes in social loneliness.
• Grounded theory analysis of interviews revealed key themes in app support, feature relevance, and user interface design.

Conclusions:

• Mobile messaging apps with specialized features can enhance communication and social skills for adults with ASD.
• The integration of text-to-speech, speech-to-text, and communication symbols is crucial for improving social interaction and reducing loneliness.
• The developed app demonstrates potential for fostering inclusion and supporting the independent living of adults with ASD.