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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control | No Intervention | Participants in the control arm will receive the standard anaesthesia risk counselling conducted face-to-face by a licensed anaesthetist. This process follows institutional protocols and includes a verbal explanation of anaesthesia procedures, associated risks, benefits, and potential complications, tailored to the patient's specific surgical context. Patients are encouraged to ask questions and engage in discussion during the session. No digital tools or chatbot assistance will be used in this arm. | |
| PEAR | Experimental | Participants in this arm will receive anaesthesia risk counselling through the PEAR (Patient Education of Anaesthesia Risks) chatbot, a multilingual, AI-powered conversational tool. The chatbot provides personalized education on anaesthesia risks, procedures, and post-operative expectations. Patients interact with the chatbot prior to meeting the anaesthetist, enhancing their understanding and preparing them for the face-to-face consultation. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Patient self-reported understanding of anaesthesia risks | 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. | Immediately post-interaction with the PEAR Chatbot |
| Measure | Description | Time Frame |
|---|---|---|
| Perceived Usefulness | 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). |
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Inclusion Criteria:
- Adults (≥21 years old) undergoing elective surgery requiring anaesthesia
Classified as ASA Physical Status I to III
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yuhe Ke, MMED (ANES) | Contact | +6581022852 | yuhe.ke36@gmail.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Singapore General Hospital | Recruiting | Singapore | Singapore | 249094 | Singapore |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40185842 | Background | Ke YH, Jin L, Elangovan K, Abdullah HR, Liu N, Sia ATH, Soh CR, Tung JYM, Ong JCL, Kuo CF, Wu SC, Kovacheva VP, Ting DSW. Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness. NPJ Digit Med. 2025 Apr 5;8(1):187. doi: 10.1038/s41746-025-01519-z. |
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De-identified individual participant data (IPD) that underlie the results reported in the publication (including primary and secondary outcomes, baseline characteristics, and questionnaire scores) will be made available to qualified researchers upon reasonable request.
Data will be shared beginning 6 months after publication and will be accessible for up to 3 years post-publication. Requests must include a methodologically sound proposal and be submitted to the Principal Investigator. A data access agreement will be required to ensure ethical use and protection of participant confidentiality.
1st July 2025 - 1st july 2028
Access to de-identified individual participant data (IPD) will be granted to qualified academic researchers, healthcare professionals, or institutions conducting methodologically sound research that aligns with ethical standards and scientific purpose.
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This study uses a parallel-group, randomized controlled trial (RCT) design to evaluate the effectiveness of PEAR, a conversational AI chatbot for anaesthesia risk counselling.
Participants are randomly assigned in a 1:1 allocation ratio to one of two arms:
Intervention Group: Receives anaesthesia risk information through the PEAR chatbot prior to their consultation with an anaesthetist.
Control Group: Receives anaesthesia counselling through the standard, face-to-face verbal consent process by a clinician.
Randomisation is stratified by surgical specialty to ensure balanced representation across different clinical settings.
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There will be no blinding of the participants and investigators due to the impracticality. The outcome assessor will be blinded.
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| Immediately pre-consent and post-consent (within the same clinic visit) |
| Cost effectiveness | 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. | Immediately post-chatbot use (same clinic visit) |
| Perceived Ease of Use (PEOU) | 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). | Immediately pre-consent and immediately post-consent (within the same clinic visit). |
| Attitude Toward Using (ATT) | 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). | Immediately pre-consent and immediately post-consent (within the same clinic visit). |
| Behavioral Intention to Use (BI) | 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). | Immediately pre-consent and immediately post-consent (within the same clinic visit). |
| Singapore General Hospital | Not yet recruiting | Singapore | Singapore | 751126 | Singapore |
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