The study was witbdrawn due to funding and resource limitations.

Previous studies have demonstrated that patients frequently undergo significant decision conflict regarding major medical decisions in otolaryngology. There lack validated tools available for decision support for patients. While limited evidence has demonstrated that clinical decision support tools can alleviate decision conflict for patients with diagnosis in otolaryngology, conversational language models were not employed in these studies and may provide additional benefit in this context. This study seeks to evaluate the efficacy of using ChatGPT, a conversational language model with basic clinical knowledge, in alleviating decision conflict for patients with new diagnosis in otolaryngology. For this pilot study, vestibular schwannoma, a benign tumor that develops on the vestibular nerve with known clinical equipoise, has been chosen for the initial study diagnosis. Efficacy will be evaluated by comparison of responses to the Decisional Conflict Scale (DCS) and Satisfaction with Decision (SWD) scores between a group given training in ChatGPT and a control group (no ChatGPT training).

Inclusion Criteria:

• 18 years or older
• Diagnosed with vestibular schwannoma
• Have access to internet-enabled device that is compatible with ChatGPT

Exclusion Criteria:

• < 18 years old
• patient without diagnosis of vestibular schwannoma
• patient does not have access to internet-enabled device
• patient who declines study participation