U.S., April 30 -- ClinicalTrials.gov registry received information related to the study (NCT06949462) titled 'Effectiveness of Large Language Model for Anaesthesia and Procedural Consent' on April 22.
Brief Summary: Patient understanding of anaesthesia risks remains inconsistent due to time constraints, language barriers, and variable clinician communication styles. Traditional verbal consent may not consistently ensure comprehension or reduce preoperative anxiety. PEAR (Patient Education of Anesthesia Risks) is a multilingual, AI-driven chatbot developed to enhance patient education and improve the quality of anaesthesia risk counselling.
Study Objective:
To compare PEAR's performance in delivering anaesthesia risk consent against the s...