LeukaemiaNCT07305337
Randomised Controlled Trial of Artificial Intelligence-assisted Health Education
A study testing Artificial Intelligence Health Education and Artificial health education in people with Leukaemia and Multiple Myeloma (MM), Lymphoma, Large B-Cell, Diffuse (DLBCL), Lymphoma, run by Zhongnan Hospital at 1 site in China.
Trial summary
With the rapid advancement of biopharmaceutical technology, clinical trials have become the crucial bridge connecting new drugs from the laboratory to clinical application. Despite the increasing number of clinical trial projects being conducted, nearly all such projects face the common challenge of recruitment… Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Leukaemia, Multiple Myeloma (MM), Lymphoma, Large B-Cell, Diffuse (DLBCL), Lymphoma, Lymphoma
- What is being tested?
- Artificial Intelligence Health Education and Artificial health education
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 196 participants
- Where
- 1 siteChina
- Study dates
- 28 Jun 2025to 30 Aug 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 18 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
None listed.
Who cannot join
- Patients with concomitant cognitive impairment, psychiatric disorders, or other conditions severely affecting comprehension; (2) Anticipated hospital stay of less than 3 days, rendering completion of the intervention unfeasible; (3) End-of-life palliative care; (4) Previous participation in other clinical trial education programmes.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Zhongnan Hospital of Wuhan University
Wuhan, Hubei, 430071
About this study
Official title: The Impact of Artificial Intelligence-Assisted Health Education on Patients' Intention to Participate in Clinical Trials: A Cluster-Randomised Controlled Trial
With the rapid advancement of biopharmaceutical technology, clinical trials have become the crucial bridge connecting new drugs from the laboratory to clinical application. Despite the increasing number of clinical trial projects being conducted, nearly all such projects face the common challenge of recruitment difficulties. Subject recruitment constitutes a pivotal stage in clinical trials; the ability to recruit a sufficient number of subjects meeting the trial requirements significantly impacts trial quality and also serves as a key factor influencing trial progress. Hematologic cancers constitute a highly heterogeneous group of malignant diseases originating in the haematopoietic organs and primarily affecting the haematopoietic system. They encompass acute and chronic leukaemias, malignant lymphomas, multiple myeloma, myelodysplastic syndromes, and related disorders. For patients facing treatment decisions, clinical trials represent not only a vital avenue for accessing cutting-edge therapies but also impose heightened demands on their capacity for informed decision-making. Conversational artificial intelligence (AI) based on large language models is rapidly advancing in health education and public health communication. Medical chatbots offer scalable and personalised advantages in delivering health information, promoting behavioural change, and enhancing patient engagement, providing a viable pathway for improving trial literacy and decision support. Accordingly, this study proposes to conduct a clinical trial literacy intervention using AI-powered chatbots among haematological malignancy patients. Through a randomised controlled trial (RCT), it aims to evaluate the impact of AI-assisted health education on patients' understanding of clinical trials and intention to participate. This research seeks to validate the application value of AI technology in health education and explore scalable AI-assisted health education intervention models.
Read the detailed description
This study aims to evaluate the effectiveness of artificial intelligence technology in health education, focusing on haematological cancer patients' awareness of and intention to participate in clinical trials. Through an AI-robot-mediated clinical trial science communication intervention, the research will systematically assess its impact on patients' cognitive levels, attitudes, and participation intentions, exploring a scalable new model for AI-assisted health interventions.
Specific objectives include: (1) Investigating current levels of clinical trial awareness and participation attitudes among haematological malignancy patients; (2) Assessing the practical impact of AI-bot-delivered clinical trial awareness interventions on patients' understanding and intention to participate; (3) Exploring the feasibility and scalability of AI-assisted health education in promoting patient engagement in clinical trials.
- Conditions
- Leukaemia, Multiple Myeloma (MM), Lymphoma, Large B-Cell, Diffuse (DLBCL), Lymphoma, Lymphoma
- Being tested
- Artificial Intelligence Health Education, Artificial health education
- Keywords
- Leukaemia, Multiple Myeloma, Lymphoma, health education, artificial intelligence
- Medical subject headings
- Leukemia, Multiple Myeloma, Lymphoma, Health Education
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence Health EducationDevice
In addition to receiving standard health education, participants underwent clinical trial-specific education delivered via an AI robot. This educational content was designed around fundamental concepts of clinical trials, implementation procedures, clarification of common misconceptions, ethical safeguards, and potential benefits of participation. Its aim was to enhance patients' overall understanding of clinical trials and willingness to participate. The AI robot featured voice interaction capabilities and integrated text-image displays with video materials to enhance the interactivity and comprehensibility of information delivery.
Artificial health educationOther
Received only routine health education delivered by departmental healthcare staff, covering fundamental disease knowledge, treatment protocols, nursing management, and discharge instructions. This education forms part of the hospital's standard clinical practice and typically does not systematically incorporate content related to clinical trials or dedicated educational modules.
| Study group | Role | What they receive |
|---|---|---|
| Artificial Intelligence Health Education | Experimental | In addition to receiving standard health education, participants underwent clinical trial-specific education delivered via an AI robot. This educational content was designed around fundamental concepts of clinical trials, implementation procedures, clarification of common misconceptions, ethical safeguards, and potential benefits of participation. Its aim was to enhance patients' overall understanding of clinical trials and willingness to participate. The AI robot featured voice interaction capabilities and integrated text-image displays with video materials to enhance the interactivity and comprehensibility of information delivery. Receives: Device: Artificial Intelligence Health Education |
| Artificial health education | Active comparator | Received only routine health education delivered by departmental healthcare staff, covering fundamental disease knowledge, treatment protocols, nursing management, and discharge instructions. This education forms part of the hospital's standard clinical practice and typically does not systematically incorporate content related to clinical trials or dedicated educational modules. Receives: Other: Artificial health education |
What is being measured
The primary outcome is the main question the study is designed to answer.
intention to participate
Measurement via a questionnaire on patients' intention to participate in clinical trials and influencing factors.
Measured: The first day of patient enrolment and the seventh day following completion of the one-week intervention
Secondary outcomes (1)
User experience
Through questionnaires on intention to use and satisfaction with robots, alongside interview guidelines, we gathered patients' willingness to use intelligent robots and their satisfaction, perceptions, and feedback regarding the robots' role in supporting health education.
Measured: The seventh day following completion of the one-week intervention
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Dec 2025
- Study start28 Jun 2025
- Primary completion28 Aug 2026 (estimated)
- Study completion30 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for LeukaemiaStudies 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
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 196 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Zhongnan Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Fuling Zhou, Zhongnan Hospital
- Investigators
- Fuling Fu Zhou, Study director, Zhongnan Hospital of Wuhan Universty
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07305337
- Sponsor's protocol ID
- 0603
- Status last verified
- Dec 2025
- First submitted
- 3 Jun 2025
- Last updated
- 26 Dec 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 26 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Impact of Artificial Intelligence-Assisted Health Education on Patients' Intention to Participate in Clinical Trials: A Cluster-Randomised Controlled Trial
- ClinicalTrials.gov ID
- NCT07305337
- Acronym / sponsor ID
- 0603
- Conditions
- Leukaemia, Multiple Myeloma (MM), Lymphoma, Large B-Cell, Diffuse (DLBCL), Lymphoma, Lymphoma
- Keywords
- Leukaemia, Multiple Myeloma, Lymphoma, health education, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 196 participants (estimated)
- Lead sponsor
- Zhongnan HospitalUniversity, hospital or other
- Study start
- 28 Jun 2025 (actual)
- Primary completion
- 28 Aug 2026 (estimated)
- Study completion
- 30 Aug 2026 (estimated)
- First posted
- 26 Dec 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.
With the rapid advancement of biopharmaceutical technology, clinical trials have become the crucial bridge connecting new drugs from the laboratory to clinical application. Despite the increasing number of clinical trial projects being conducted, nearly all such projects face the common challenge of recruitment difficulties. Subject recruitment constitutes a pivotal stage in clinical trials; the ability to recruit a sufficient number of subjects meeting the trial requirements significantly impacts trial quality and also serves as a key factor influencing trial progress. Hematologic cancers constitute a highly heterogeneous group of malignant diseases originating in the haematopoietic organs and primarily affecting the haematopoietic system. They encompass acute and chronic leukaemias, malignant lymphomas, multiple myeloma, myelodysplastic syndromes, and related disorders. For patients facing treatment decisions, clinical trials represent not only a vital avenue for accessing cutting-edge therapies but also impose heightened demands on their capacity for informed decision-making. Conversational artificial intelligence (AI) based on large language models is rapidly advancing in health education and public health communication. Medical chatbots offer scalable and personalised advantages in delivering health information, promoting behavioural change, and enhancing patient engagement, providing a viable pathway for improving trial literacy and decision support. Accordingly, this study proposes to conduct a clinical trial literacy intervention using AI-powered chatbots among haematological malignancy patients. Through a randomised controlled trial (RCT), it aims to evaluate the impact of AI-assisted health education on patients' understanding of clinical trials and intention to participate. This research seeks to validate the application value of AI technology in health education and explore scalable AI-assisted health education intervention models.
Detailed description
This study aims to evaluate the effectiveness of artificial intelligence technology in health education, focusing on haematological cancer patients' awareness of and intention to participate in clinical trials. Through an AI-robot-mediated clinical trial science communication intervention, the research will systematically assess its impact on patients' cognitive levels, attitudes, and participation intentions, exploring a scalable new model for AI-assisted health interventions.
Specific objectives include: (1) Investigating current levels of clinical trial awareness and participation attitudes among haematological malignancy patients; (2) Assessing the practical impact of AI-bot-delivered clinical trial awareness interventions on patients' understanding and intention to participate; (3) Exploring the feasibility and scalability of AI-assisted health education in promoting patient engagement in clinical trials.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Artificial Intelligence Health Education | Experimental | Device: Artificial Intelligence Health EducationIn addition to receiving standard health education, participants underwent clinical trial-specific education delivered via an AI robot. This educational content was designed around fundamental concepts of clinical trials, implementation procedures, clarification of common misconceptions, ethical safeguards, and potential benefits of participation. Its aim was to enhance patients' overall understanding of clinical trials and willingness to participate. The AI robot featured voice interaction capabilities and integrated text-image displays with video materials to enhance the interactivity and comprehensibility of information delivery. |
| Artificial health education | Active comparator | Other: Artificial health educationReceived only routine health education delivered by departmental healthcare staff, covering fundamental disease knowledge, treatment protocols, nursing management, and discharge instructions. This education forms part of the hospital's standard clinical practice and typically does not systematically incorporate content related to clinical trials or dedicated educational modules. |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (0 listed)
Key exclusion criteria (1 listed)
- Patients with concomitant cognitive impairment, psychiatric disorders, or other conditions severely affecting comprehension; (2) Anticipated hospital stay of less than 3 days, rendering completion of the intervention unfeasible; (3) End-of-life palliative care; (4) Previous participation in other clinical trial education programmes.
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 |
|---|---|---|
| Artificial Intelligence Health EducationIn addition to receiving standard health education, participants underwent clinical trial-specific education delivered via an AI robot. This educational content was designed around fundamental concepts of clinical trials, implementation procedures, clarification of common misconceptions, ethical safeguards, and potential benefits of participation. Its aim was to enhance patients' overall understanding of clinical trials and willingness to participate. The AI robot featured voice interaction capabilities and integrated text-image displays with video materials to enhance the interactivity and comprehensibility of information delivery. | Device | Artificial Intelligence Health Education |
| Artificial health educationReceived only routine health education delivered by departmental healthcare staff, covering fundamental disease knowledge, treatment protocols, nursing management, and discharge instructions. This education forms part of the hospital's standard clinical practice and typically does not systematically incorporate content related to clinical trials or dedicated educational modules. | Other | Artificial health education |
Primary outcome
intention to participate
Time frame: The first day of patient enrolment and the seventh day following completion of the one-week intervention
Measurement via a questionnaire on patients' intention to participate in clinical trials and influencing factors.
1 secondary outcome
User experience
Time frame: The seventh day following completion of the one-week intervention
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 26 Dec 2025.
- Individual participant dataSharing planned: No
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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.
Fuling Fu Zhou study director
Zhongnan Hospital of Wuhan Universty
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence Health Education and Artificial health education in people with Leukaemia and Multiple Myeloma (MM), Lymphoma, Large B-Cell, Diffuse (DLBCL), Lymphoma, run by Zhongnan Hospital at 1 site in China.
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 0 inclusion and 1 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 26 Dec 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 China. 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 Fuling Zhou (027-67813137, zhoufuling@163.com.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
intention to participate (time frame: The first day of patient enrolment and the seventh day following completion of the one-week intervention). 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 26 Dec 2025; AzTrials last refreshed its copy on 7 Nov 2026.