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Clinical Application of LLM for Intervention Plan Development

What is it about?

This study investigates the speech and language intervention plan outputs generated by six different artificial intelligence (AI) tools powered by large language models (LLMs). Using both quantitative and qualitative analyses, this study compared the performance outputs of the six AI tools across three fictional clinical cases, each involving different types of speech and language disorders in 5-year-old children. Results revealed that the intervention plans generated by these AI tools were rated between Needs Improvement and Meets Expectations in terms of clinical knowledge and competency. Each AI tool demonstrated unique strengths and limitations in supporting the development of intervention plans.

Why is it important?

The results of this study may serve as foundational data to provide insights into how clinicians, educators, and students in the field of speech-language pathology can appropriately and responsibly utilize existing AI resources when implementing these technologies into the development of intervention plans.

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The following have contributed to this summary: Namhee Kim

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