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NCT Number: NCT06949462

Effectiveness of Large Language Model for Anaesthesia and Procedural Consent

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.

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Key information

Conditions

Consent Forms Anesthesia Artificial Intelligence (AI)

Age range

21 year–99 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Singapore General Hospital, Singapore

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About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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)

Treatment and study plan

PEAR

Other

Participants in the intervention arm will receive anaesthesia risk counselling through the PEAR (Patient Education of Anaesthesia Risks) chatbot prior to their face-to-face consultation with an anaesthetist. PEAR is a multilingual, AI-powered conversational tool designed to provide personalized, interactive education on anaesthesia-related procedures, risks, and safety information.

The chatbot delivers content aligned with institutional guidelines and allows patients to explore topics at their own pace, ask questions in natural language, and revisit information as needed. After completing the chatbot interaction, patients proceed with their standard preoperative consultation, where any further questions are addressed by the anaesthetist.

This approach is designed to enhance patient understanding, reduce anxiety, and optimize the in-person consultation by preparing patients in advance.

Primary outcomes

  1. Patient self-reported understanding of anaesthesia risks

    Time frame: Immediately post-interaction with the PEAR Chatbot

    The primary outcome was assessed using a Patient-Reported Experience Measure (PREM) focused on subjective comprehension of anesthesia. This was measured via three validated 5-point Likert scale items (1 = strongly disagree, 5 = strongly agree) evaluating: (1) clarity of risks and procedures, (2) confidence in the anesthesia plan, and (3) self-reported ability to recall and explain key risks. While both groups completed these items following the clinician consultation, the intervention group underwent additional longitudinal assessments-at baseline and post-chatbot interaction-to facilitate a within-group analysis of the chatbot's independent educational impact.

Secondary outcomes

  1. Perceived Usefulness

    Time frame: Immediately pre-consent and post-consent (within the same clinic visit)

    Description: Evaluation of the user's subjective belief that using the PEAR chatbot enhanced their clinical experience. Measured using the mean score of three items: "The chatbot improved my understanding," "It was a useful addition to my consultation," and "It helped me make informed decisions."

    Unit of Measure: 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

    Time Frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).

  2. Cost effectiveness

    Time frame: Immediately post-chatbot use (same clinic visit)

    Participants were presented with a hypothetical choice scenario outlining explicit trade-offs between in-person clinic attendance (travel time 60-120 minutes, waiting time 60-180 minutes, travel cost $10-50 Singapore dollars, includes physical examination) versus chatbot use at home (zero travel time, zero waiting time, zero cost, no physical examination). Participants selected their preference, providing insight into patient values and priorities.

  3. Perceived Ease of Use (PEOU)

    Time frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).

    Description: Evaluation of the degree to which the user believes that using the chatbot was free of effort. Measured using the mean score of four items: "Easy to use," "Easy to learn," "Comfortable navigating," and "Language was easy to understand."

    Unit of Measure: 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

  4. Attitude Toward Using (ATT)

    Time frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).

    Description: Evaluation of the user's positive or negative feelings about performing the target behavior. Measured using the mean score of three items: "I enjoyed using the chatbot," "Using the chatbot was a good idea," and "I feel confident after using it."

    Unit of Measure: 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

  5. Behavioral Intention to Use (BI)

    Time frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).

    Description: Evaluation of the user's likelihood to engage with the PEAR chatbot in future clinical scenarios. Measured using a 5-point Likert scale.

    Unit of Measure: 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

Study contacts

Contact information is provided by the study sponsor or research team.

Yuhe Ke, MMED (ANES)

CONTACT

[email protected]

+6581022852

Sponsors and collaborators

Lead sponsor

Singapore General Hospital

Other

Registry information

Official study title

Evaluating the Effectiveness of Large Language Models in Anaesthesia and Procedural Consent: A Comparative Analysis With Traditional Patient Consent Methods

Acronym: PEAR

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Apr 29, 2025
Registry last updated
May 7, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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