Atrial Fibrillation (AF)NCT06684457
Patient Perceived Empathy of an AI Chatbot for Atrial Fibrillation Education
A study testing Atrial Fibrillation Education in people with Atrial Fibrillation (AF), run by University of Pittsburgh at 1 site in United States.
Trial summary
Atrial Fibrillation is a chronic disease with significant health consequences like increased risk of stroke, heart failure, heart attack and death. Educating patients about the disease is important for them to be able to understand the condition better, feel empowered and take an active part in their care plan. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Atrial Fibrillation (AF)
- What is being tested?
- Atrial Fibrillation Education
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 40 participants
- Where
- 1 siteUnited States
- Study dates
- 25 Nov 2024to 2 May 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age greater than18 yrs
- Known diagnosis of atrial fibrillation
Who cannot join
- Inability to text/use an electronic device
- Inability to read English
Trial locations and contacts
1 site in 1 country.
United States1 site
UPMC Heart and Vascular Institute
Pittsburgh, Pennsylvania, 15213
About this study
Official title: Patient Perceived Degree of Empathy Exhibited by Physician Guided, Prompt Engineered, Generative AI Chatbot Designed for Atrial Fibrillation Education
Atrial Fibrillation is a chronic disease with significant health consequences like increased risk of stroke, heart failure, heart attack and death. Educating patients about the disease is important for them to be able to understand the condition better, feel empowered and take an active part in their care plan. AI technology can potentially be used to impart such education. However, doing so with care and empathy is equally important.
Therefore, it is necessary to ensure when AI technology is used to impart education about atrial fibrillation to patients, the humane aspects of the interaction are rigorously tested. This study examines a way to impart atrial fibrillation education through interaction with an AI chatbot, that uses text and links to educational videos. To participate in this study, people need to be age 18 or older and have a history of newly diagnosed atrial fibrillation. Approximately 40 individuals will be asked to take part in this study.
The first step to the study will be reading through, understanding, and signing an informed consent. People who then agree to join the study will have a one-time interaction with the AI chatbot and structured educational material by using an iPad provided to them for the approximately 1 hour duration of the study. People in the study will obtain atrial fibrillation education by typing one by one on the iPad, up to 10 questions about the disease. Answers will include text and links to videos. Before and after atrial fibrillation education, people who join this study will be asked to fill out a survey. The study team will teach patients how to use the iPad and type in questions.
Read the detailed description
Background:
Atrial fibrillation is a the most common arrhythmic disorder in the United States, with significant morbidity and healthcare cost burden. The number of patients with atrial fibrillation is expected to reach 12.1 million in 2030. AFib related annual incremental healthcare costs were estimated to be $6 to $26 billion based on 2010AF prevalence projections.
Lifestyle modification is one of the four primary pillars of atrial fibrillation care, and patient education is paramount to foster behavioral change. There is also evidence that early rhythm control using medications and ablation therapy can mitigate the overall burden of atrial fibrillation and improve patient quality of life among patients with other cardiovascular risk factors and/or heart failure. However, social determinants of health including health literacy significantly impact patient management, referral practices for procedural interventions, and ultimately patients' clinical outcomes. Anticoagulation prescription for prevention of thromboembolic complications, and adherence to anticoagulation are also known to be correlated with patients' medical literacy and disease awareness. These data point to three important unmet needs. First, there is a need for more robust and intentional patient education to foster behavioral change including lifestyle modification. Second, patient awareness and understanding of the disease is paramount to facilitate anticoagulation adherence and seeking specialist referral which in turn could mitigate AFib related morbidity and healthcare costs. Third, patient education must be delivered in empathetic language, at a (6th-8th) grade reading level, and translated to languages other than English per patient preference.
In that context, LLMs (large language models) such as ChatGPT (Open AI, San Francisco), with built in capabilities for language simplification and translation could play a foundational role in modern medicine. Current data show that LLMs(Chat GPT) are capable of answering patient queries in an empathetic and knowledgeable manner. Data showing improved readability of surgical consent forms simplified using ChatGPT, while maintaining medical information and medicolegal integrity demonstrate the potential of using LLMs for consent processes and shared decision making. However, it is important to note that providing appropriate guardrails to minimize probabilistic guess responses and fine tune the content for accuracy and empathy requires human interaction with the software. The availability of such prompt-engineered technology for patient education could have a profound impact on patient behavior, clinical outcomes and provider-patient relationship.
- Conditions
- Atrial Fibrillation (AF)
- Being tested
- Atrial Fibrillation Education
- Keywords
- education, lifestyle modification, atrial fibrillation, generative AI, chatbot, artificial intelligence
- Medical subject headings
- Atrial Fibrillation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Atrial Fibrillation EducationBehavioural
Atrial fibrillation education rendered through a generative AI chatbot, using an iPAD. The intervention itself is an approximately 1 hour long interaction with the chatbot or approximately 10 questions about atrial fibrillation, for 1 single interaction.
| Study group | Role | What they receive |
|---|---|---|
| Pilot interventional arm | Experimental | Single arm, wherein all consenting participants undergoing interaction with chatbot for atrial fibrillation education. Receives: Behavioral: Atrial Fibrillation Education |
What is being measured
The primary outcome is the main question the study is designed to answer.
Empathy
Assess patient perceived degree of empathy exhibited by chatbot responses. The degree of empathy will be measured using a pre- and post- chatbot interaction 7 point Likert scale survey, with a higher score suggesting a higher level of perceived empathy. The title of the survey will be "Likert scale based survey for perceived empathy and trust," with the lowest score being 4 and the highest score being 28. Survey form available upon reasonable request.
Measured: From enrollment to end of interaction with chatbot, approximately an hour
Secondary outcomes (2)
Knowledge
Assess knowledge about AFib imparted by chatbot based on patient survey questions. Knowledge will be measured by administering a pre- and post- bot interaction survey, titled "Jessa Atrial Fibrillation Knowledge Questionnaire," with a minimum score of 0 and a maximum score of 16. A higher score reflects that the patient is more knowledgeable about atrial fibrillation. Survey form available upon reasonable request.
Measured: From enrollment to end of interaction with chatbot, approximately an hour
Trust
Assess impact of chatbot interaction on patient perceived trust in the provider. The degree of trust will be measured using a pre- and post- chatbot interaction 7 point Likert scale survey, with a higher score suggesting a higher level of perceived empathy. The title of the survey will be "Likert scale based survey for perceived empathy and trust," with the lowest score being 4 and the highest score being 28. Survey form available upon reasonable request.
Measured: From enrollment to end of interaction with chatbot, approximately an hour
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Nov 2024
- Study start25 Nov 2024
- Primary completion2 May 2025
- Study completion2 May 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Atrial Fibrillation (AF)Studies of the same condition, open and under way.
- More trials run by University of PittsburghThe sponsor's other registered studies.
- 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
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- Study design: A single center, cross sectional, uncontrolled, open-label, non-randomized, single arm, experimental pilot study using an LLM based prompt-engineered education chatbot, to impart a Q and A format atrial fibrillation education to patients, prior to their first appointment with a cardiologist or a cardiac electrophysiologist. The prompt-engineered chatbot is built on LLM capabilities yet tailored with the help of physician provided, vetted, open source atrial fibrillation educational material as well as empathy enhancing scripts, and simplified language to a 6th-8th grade reading level. The chatbot would be utilized to enhance the patient-provider interaction by providing empathetic education to patients regarding atrial fibrillation, and empower them with the knowledge they would need to ask informed questions during their patient visit. The chatbot will also be able to direct patients to Heart Rhythm Society's open source educational videos for atrial fibrillation (UpBeat
- Masking
- None (open label)
- Enrolment
- 40 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Pittsburgh
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Samir Saba, University of Pittsburgh
- Investigators
- Samir Saba, MD, Principal investigator, UPMC Heart and Vascular Institute
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06684457
- Sponsor's protocol ID
- STUDY24010018
- Status last verified
- Nov 2024
- First submitted
- 8 Nov 2024
- Last updated
- 8 Jul 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Deidentified IPD may be shared at the discretion of investigators, upon reasonable request.
Study at a glance
From the registry record, last updated by the sponsor on 8 Jul 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Patient Perceived Degree of Empathy Exhibited by Physician Guided, Prompt Engineered, Generative AI Chatbot Designed for Atrial Fibrillation Education
- ClinicalTrials.gov ID
- NCT06684457
- Acronym / sponsor ID
- STUDY24010018
- Conditions
- Atrial Fibrillation (AF)
- Keywords
- education, lifestyle modification, atrial fibrillation, generative AI, chatbot, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 40 participants (actual)
- Lead sponsor
- University of PittsburghUniversity, hospital or other
- Study start
- 25 Nov 2024 (actual)
- Primary completion
- 2 May 2025 (actual)
- Study completion
- 2 May 2025 (actual)
- First posted
- 12 Nov 2024 (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.
Atrial Fibrillation is a chronic disease with significant health consequences like increased risk of stroke, heart failure, heart attack and death. Educating patients about the disease is important for them to be able to understand the condition better, feel empowered and take an active part in their care plan. AI technology can potentially be used to impart such education. However, doing so with care and empathy is equally important.
Therefore, it is necessary to ensure when AI technology is used to impart education about atrial fibrillation to patients, the humane aspects of the interaction are rigorously tested. This study examines a way to impart atrial fibrillation education through interaction with an AI chatbot, that uses text and links to educational videos. To participate in this study, people need to be age 18 or older and have a history of newly diagnosed atrial fibrillation. Approximately 40 individuals will be asked to take part in this study.
The first step to the study will be reading through, understanding, and signing an informed consent. People who then agree to join the study will have a one-time interaction with the AI chatbot and structured educational material by using an iPad provided to them for the approximately 1 hour duration of the study. People in the study will obtain atrial fibrillation education by typing one by one on the iPad, up to 10 questions about the disease. Answers will include text and links to videos. Before and after atrial fibrillation education, people who join this study will be asked to fill out a survey. The study team will teach patients how to use the iPad and type in questions.
Detailed description
Background:
Atrial fibrillation is a the most common arrhythmic disorder in the United States, with significant morbidity and healthcare cost burden. The number of patients with atrial fibrillation is expected to reach 12.1 million in 2030. AFib related annual incremental healthcare costs were estimated to be $6 to $26 billion based on 2010AF prevalence projections.
Lifestyle modification is one of the four primary pillars of atrial fibrillation care, and patient education is paramount to foster behavioral change. There is also evidence that early rhythm control using medications and ablation therapy can mitigate the overall burden of atrial fibrillation and improve patient quality of life among patients with other cardiovascular risk factors and/or heart failure. However, social determinants of health including health literacy significantly impact patient management, referral practices for procedural interventions, and ultimately patients' clinical outcomes. Anticoagulation prescription for prevention of thromboembolic complications, and adherence to anticoagulation are also known to be correlated with patients' medical literacy and disease awareness. These data point to three important unmet needs. First, there is a need for more robust and intentional patient education to foster behavioral change including lifestyle modification. Second, patient awareness and understanding of the disease is paramount to facilitate anticoagulation adherence and seeking specialist referral which in turn could mitigate AFib related morbidity and healthcare costs. Third, patient education must be delivered in empathetic language, at a (6th-8th) grade reading level, and translated to languages other than English per patient preference.
In that context, LLMs (large language models) such as ChatGPT (Open AI, San Francisco), with built in capabilities for language simplification and translation could play a foundational role in modern medicine. Current data show that LLMs(Chat GPT) are capable of answering patient queries in an empathetic and knowledgeable manner. Data showing improved readability of surgical consent forms simplified using ChatGPT, while maintaining medical information and medicolegal integrity demonstrate the potential of using LLMs for consent processes and shared decision making. However, it is important to note that providing appropriate guardrails to minimize probabilistic guess responses and fine tune the content for accuracy and empathy requires human interaction with the software. The availability of such prompt-engineered technology for patient education could have a profound impact on patient behavior, clinical outcomes and provider-patient relationship.
Study design
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- Study design: A single center, cross sectional, uncontrolled, open-label, non-randomized, single arm, experimental pilot study using an LLM based prompt-engineered education chatbot, to impart a Q and A format atrial fibrillation education to patients, prior to their first appointment with a cardiologist or a cardiac electrophysiologist. The prompt-engineered chatbot is built on LLM capabilities yet tailored with the help of physician provided, vetted, open source atrial fibrillation educational material as well as empathy enhancing scripts, and simplified language to a 6th-8th grade reading level. The chatbot would be utilized to enhance the patient-provider interaction by providing empathetic education to patients regarding atrial fibrillation, and empower them with the knowledge they would need to ask informed questions during their patient visit. The chatbot will also be able to direct patients to Heart Rhythm Society's open source educational videos for atrial fibrillation (UpBeat
| Arm | Type | Receives |
|---|---|---|
| Pilot interventional arm | Experimental | Behavioral: Atrial Fibrillation EducationSingle arm, wherein all consenting participants undergoing interaction with chatbot for atrial fibrillation education. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Age greater than18 yrs
- Known diagnosis of atrial fibrillation
Key exclusion criteria (2 listed)
- Inability to text/use an electronic device
- Inability to read English
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 |
|---|---|---|
| Atrial Fibrillation EducationAtrial fibrillation education rendered through a generative AI chatbot, using an iPAD. The intervention itself is an approximately 1 hour long interaction with the chatbot or approximately 10 questions about atrial fibrillation, for 1 single interaction. | Behavioural | Pilot interventional arm |
Primary outcome
Empathy
Time frame: From enrollment to end of interaction with chatbot, approximately an hour
Assess patient perceived degree of empathy exhibited by chatbot responses. The degree of empathy will be measured using a pre- and post- chatbot interaction 7 point Likert scale survey, with a higher score suggesting a higher level of perceived empathy. The title of the survey will be "Likert scale based survey for perceived empathy and trust," with the lowest score being 4 and the highest score being 28. Survey form available upon reasonable request.
2 secondary outcomes
Knowledge
Time frame: From enrollment to end of interaction with chatbot, approximately an hour
Trust
Time frame: From enrollment to end of interaction with chatbot, approximately an hour
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Jul 2025.
- Individual participant dataSharing planned: No. Deidentified IPD may be shared at the discretion of investigators, upon reasonable request.
Related trials for Atrial Fibrillation (AF)
Active, not recruiting
Horizon 360 Protocol for the Treatment of Paroxysmal Atrial Fibrillation With the Sphere-360™ Catheter and Affera™ Mapping and Ablation System (Horizon 360)
Paroxysmal AF
Active, not recruiting
CONVERGE Post-Approval Study (PAS)
Chronic Atrial Fibrillation
RecruitingPhase 2
Safety in Adult Participants With Atrial Fibrillation Who Are Treated With Anticoagulation
Atrial Fibrillation (AF)
RecruitingPhase 3
Stroke and Systemic Embolism Prevention in Adult Participants With Atrial Fibrillation
Atrial Fibrillation (AF)
Not yet recruitingObservational study
Hummingbird ICE Study
ATRIAL APPENDAGE CLOSURE for ATRIAL FIBRILLATION, Atrial Fibrillation (AF)
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. This study is not recruiting at the moment.
Samir Saba, MD principal investigator
UPMC Heart and Vascular Institute
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Atrial Fibrillation Education in people with Atrial Fibrillation (AF), run by University of Pittsburgh at 1 site in United States.
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 2 inclusion and 2 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: finished, as of the sponsor's last update on 8 Jul 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Empathy (time frame: From enrollment to end of interaction with chatbot, approximately an hour). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 8 Jul 2025.