MedDataX Logo

Randomised Controlled Trial of Artificial Intelligence-assisted Health Education

NCT ID: NCT07305337

Last Updated: 2025-12-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

196 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-06-28

Study Completion Date

2026-08-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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

See the medical conditions and disease areas that this research is targeting or investigating.

Leukaemia Multiple Myeloma (MM), Lymphoma, Large B-Cell, Diffuse (DLBCL), Lymphoma Lymphoma

Keywords

Explore important study keywords that can help with search, categorization, and topic discovery.

Leukaemia Multiple Myeloma Lymphoma health education artificial intelligence

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

SINGLE

Outcome Assessors

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

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.

Group Type EXPERIMENTAL

Artificial Intelligence Health Education

Intervention Type DEVICE

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 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.

Group Type ACTIVE_COMPARATOR

Artificial health education

Intervention Type OTHER

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.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

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.

Intervention Type DEVICE

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.

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Zhongnan Hospital

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Fuling Zhou

Dean, School of Nursing, Wuhan University; Tenured Full Professor, Director of Department of Hematology, zhongnan Hospital,Wuhan University

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Fuling Fu Zhou

Role: STUDY_DIRECTOR

Zhongnan Hospital of Wuhan Universty

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Zhongnan Hospital of Wuhan University

Wuhan, Hubei, China

Site Status RECRUITING

Countries

Review the countries where the study has at least one active or historical site.

China

Central Contacts

Reach out to these primary contacts for questions about participation or study logistics.

Fuling Zhou

Role: CONTACT

Phone: 027-67813137

Email: [email protected]

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

0603

Identifier Type: -

Identifier Source: org_study_id