Consent FormsPEARNCT06949462
Effectiveness of Large Language Model for Anaesthesia and Procedural Consent
A study testing PEAR in people with Consent Forms and Anesthesia, run by Singapore General Hospital at 2 sites in Singapore.
Trial 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. Read more about this study
- Who is it for?
- Ages 21 to 99 yearsHealthy volunteers can take part
- Conditions the study is for
- Consent Forms, Anesthesia, Artificial Intelligence (AI)
- What is being tested?
- PEAR
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 120 participants
- Where
- 2 sitesSingapore
- Study dates
- 7 Jan 2026to 27 Apr 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 21 to 99 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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)
Who cannot join
- 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)
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Singapore2 sites, 2 recruiting
- Recruiting
Singapore General Hospital
Singapore, Singapore, 249094
Yuhe Ke, 81022852, yuhe.ke36@gmail.com
- Not yet recruiting
Singapore General Hospital
Singapore, Singapore, 751126
Ke Yuhe, 81022852, guardian.angel898@gmail.com
About this study
Official title: Evaluating the Effectiveness of Large Language Models in Anaesthesia and Procedural Consent: A Comparative Analysis With Traditional Patient Consent Methods
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.
Read the 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.
- Conditions
- Consent Forms, Anesthesia, Artificial Intelligence (AI)
- Being tested
- PEAR
- Keywords
- Anaesthesia, Informed Consent, Large Language Model, Artificial Intelligence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
PEAROther
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Other: PEAR |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Immediately post-interaction with the PEAR Chatbot
Secondary outcomes (5)
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).
Measured: 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.
Measured: 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).
Measured: 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).
Measured: 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).
Measured: Immediately pre-consent and immediately post-consent (within the same clinic visit).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Apr 2025
- Study start7 Jan 2026
- Primary completion27 Apr 2026
- Study completion27 Apr 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Consent FormsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 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.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Singapore General Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ke Yuhe, Singapore General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06949462
- Sponsor's protocol ID
- 2025-04-22
- Acronym
- PEAR
- Status last verified
- Apr 2026
- First submitted
- 22 Apr 2025
- Last updated
- 7 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: 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.
Publications
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.
PubMed 40185842
Study at a glance
From the registry record, last updated by the sponsor on 7 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluating the Effectiveness of Large Language Models in Anaesthesia and Procedural Consent: A Comparative Analysis With Traditional Patient Consent Methods
- ClinicalTrials.gov ID
- NCT06949462
- Acronym / sponsor ID
- PEAR / 2025-04-22
- Conditions
- Consent Forms, Anesthesia, Artificial Intelligence (AI)
- Keywords
- Anaesthesia, Informed Consent, Large Language Model, Artificial Intelligence
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- Singapore General HospitalUniversity, hospital or other
- Study start
- 7 Jan 2026 (actual)
- Primary completion
- 27 Apr 2026 (actual)
- Study completion
- 27 Apr 2026 (estimated)
- First posted
- 29 Apr 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- 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.
| Arm | Type | Receives |
|---|---|---|
| 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 | Other: PEARParticipants 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. |
Who may qualify
- Ages
- 21 to 99 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- 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)
Key exclusion criteria (5 listed)
- 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)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| PEARParticipants 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. | Other | PEAR |
Primary outcome
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.
5 secondary outcomes
Perceived Usefulness
Time frame: Immediately pre-consent and post-consent (within the same clinic visit)
Cost effectiveness
Time frame: Immediately post-chatbot use (same clinic visit)
Perceived Ease of Use (PEOU)
Time frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).
Attitude Toward Using (ATT)
Time frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).
Behavioral Intention to Use (BI)
Time frame: Immediately pre-consent and immediately post-consent (within the same clinic visit).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 May 2026.
- Background: PubMed 40185842Ke 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.
- Individual participant dataSharing planned: Yes. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing PEAR in people with Consent Forms and Anesthesia, run by Singapore General Hospital at 2 sites in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 7 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yuhe Ke, MMED (ANES) (+6581022852, yuhe.ke36@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Patient self-reported understanding of anaesthesia risks (time frame: Immediately post-interaction with the PEAR Chatbot). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06949462, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 May 2026; AzTrials last refreshed its copy on 26 Oct 2026.