Effectiveness of Large Language Model for Anaesthesia and Procedural Consent

Not Applicable

Not yet recruiting

• Conditions: Consent Forms; Artificial Intelligence (AI); Anesthesia

• Registration Number: NCT06949462
• Lead Sponsor: Singapore General Hospital

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 standard face-to-face verbal method.

Detailed Description

This study evaluates the effectiveness of PEAR (Patient Education of Anaesthesia Risks), a conversational AI-based chatbot designed to deliver anaesthesia risk education to patients in a personalized, interactive, and multilingual format. The goal is to support informed consent by improving patient comprehension, satisfaction, and reducing anxiety, while also streamlining clinician workflow.

Participants undergoing elective surgery will be randomly assigned to either receive anaesthesia counselling via PEAR before their consultation with the anaesthetist (intervention group) or undergo the standard face-to-face verbal consent process (control group). The PEAR chatbot is accessed through a secure digital interface and presents information aligned with institutional anaesthesia protocols.

The study will be conducted at hospitals within the SingHealth cluster in Singapore. Following the consent process, patients will complete a short quiz to assess understanding, a survey to evaluate satisfaction, and an anxiety scale. Clinicians will record time taken and perceived workload.

All patients will still meet their anaesthetist, ensuring clinical oversight is maintained. This study does not alter standard care but evaluates a digital adjunct to enhance it. Data will be collected electronically, anonymised, and stored securely. Insights from this trial may inform the wider implementation of digital tools in perioperative patient education.

Study Timeline

• Status Verified: 2025-04
• Study First Submitted: 2025-04-22
• Study First Submitted QC: 2025-04-28
• Last Update Submitted: 2025-04-28
• Study First Posted: 2025-04-29
• Last Update Posted: 2025-05-01
• Study Start: 2025-07-01
• Primary Completion: 2026-07-01
• Study Completion: 2026-07-01

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 120

Inclusion Criteria

• Adults (≥21 years old) undergoing elective surgery requiring anaesthesia

Classified as ASA Physical Status I to III

• Able to provide informed consent
• Able to communicate effectively in English, Chinese (Mandarin), Malay, or Tamil
• Willing and able to complete questionnaires and interact with the PEAR chatbot (intervention arm)

Exclusion Criteria

• ASA Physical Status IV or above
• Cognitive impairment or psychiatric conditions that may limit comprehension or communication
• Non-literate patients or those unable to understand English, Chinese, Malay, or Tamil
• Emergency surgery cases
• Prior participation in the study (to prevent bias)

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Patient Understanding of Anaesthesia Risks	Immediately post-consent (within 30 minutes of completing the counselling session)	Patient understanding will be measured using a structured, validated multiple-choice questionnaire immediately after the consent process, specifically the Deaconess Informed Consent Comprehension Test (DICCT). The DICCT evaluates knowledge of key anaesthesia-related risks, safety information, and patient-specific considerations discussed during the counselling session. The DICCT scores range from 0 to 20, with higher scores indicating better understanding and comprehension. This outcome measures the effectiveness of the chatbot (PEAR) compared to traditional verbal consent in conveying critical information and supporting informed decision-making.

Secondary Outcome Measures

Name	Time	Method
Reduction in Patient Anxiety Related to Anaesthesia	Immediately pre-consent and post-consent (within the same clinic visit)	Patient anxiety levels will be measured using the State-Trait Anxiety Inventory (STAI-S), a validated tool widely used in clinical research. The STAI-S evaluates how anxious a patient feels "right now" (state anxiety) in the context of their upcoming surgery and anaesthesia. The tool includes 20 items rated on a 4-point Likert scale, with higher scores indicating greater anxiety.; Participants will complete the questionnaire immediately before and after the anaesthesia consent session. Change in anxiety scores will be compared between the intervention (PEAR chatbot) and control (standard verbal consent) groups to evaluate PEAR's effectiveness in reducing preoperative anxiety.
Usability of the PEAR Chatbot Assessed via System Usability Scale (SUS)	Immediately post-chatbot use (same clinic visit)	Usability of the PEAR chatbot will be assessed using the System Usability Scale (SUS), a validated 10-item questionnaire that measures perceived ease of use, user satisfaction, and learnability of digital tools. Each item is rated on a 5-point Likert scale and results in a score ranging from 0 to 100, with higher scores indicating better usability.; Patients in the intervention arm (PEAR) will complete the SUS immediately after using the chatbot. This measure will help determine whether the tool is user-friendly and acceptable for perioperative patient education.

Trial Locations

Locations (1)

Singapore General Hospital; 🇸🇬 Singapore, Singapore