Randomised Controlled Trial of Artificial Intelligence-assisted Health Education

December 12, 2025 updated by: Fuling Zhou, Zhongnan Hospital

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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 Type

Interventional

Enrollment (Estimated)

196

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Hubei
      • Wuhan, Hubei, China, 430071
        • Recruiting
        • Zhongnan Hospital of Wuhan University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria (1) Aged ≥18 years with clear consciousness; (2) Diagnosed with haematological malignancy meeting clinical treatment criteria (WHO criteria); (3) Capable of understanding health education content and possessing basic communication skills; (4) Willing to participate in this study and sign an informed consent form.

Exclusion Criteria

(1) 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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Artificial Intelligence Health Education
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.
Device: Artificial Intelligence Health Education
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.
Active Comparator: Artificial health education
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.
Other: Artificial health education
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
The first day of patient enrolment and the seventh day following completion of the one-week intervention

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
User experience
Time Frame: The seventh day following completion of the one-week intervention
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.
The seventh day following completion of the one-week intervention

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Zhongnan Hospital

Investigators

  • Study Director: Fuling Fu Zhou, Zhongnan Hospital of Wuhan Universty

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 28, 2025

Primary Completion (Estimated)

August 28, 2026

Study Completion (Estimated)

August 30, 2026

Study Registration Dates

First Submitted

June 3, 2025

First Submitted That Met QC Criteria

December 12, 2025

First Posted (Actual)

December 26, 2025

Study Record Updates

Last Update Posted (Actual)

December 26, 2025

Last Update Submitted That Met QC Criteria

December 12, 2025

Last Verified

December 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 0603

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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