Explainable AI in Medical Education: CerViD-MultiModal Framework Trial (CerViD-MM)
July 29, 2026 updated by: Prince L. Fully, University of Liberia
Explainable Artificial Intelligence (XAI) in Medical Education: A Multi-Modal Framework for Enhancing Human-AI Collaboration
This study evaluates whether Explainable Artificial Intelligence (XAI) explanations integrated into medical training improve AI literacy, reduce cognitive workload, and enhance learner trust compared to traditional lecture methods.
Third-year medical students participated in a randomized controlled trial assessing the CerViD-MultiModal diagnostic framework during a neuroimaging diagnostic module focused on fornix atrophy in early and late mild cognitive impairment
Study Overview
Status
Completed
Conditions
Intervention / Treatment
Detailed Description
The study utilized a two-phase sequential explanatory design with mixed methodologies.
In Phase 1 (Technical Development), the CerViD-MultiModal model was developed and validated using neuroimaging data from 100 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects to classify early vs. late mild cognitive impairment via fornix morphometry features.
In Phase 2 (Educational Intervention), a randomized controlled trial was conducted with 120 third-year medical students enrolled in the clinical neuroscience rotation at the University of Liberia.
Participants were randomized into two equal groups (n=60 per group): Control Group: Completed a 45-minute traditional lecture module using static text and bar charts.
XAI-Enhanced Group: Completed an interactive 45-minute module featuring SHAP summary charts, LIME patient-specific explanations, and interactive force graphs.
Post-intervention electronic assessments evaluated four primary outcomes: AI Literacy Score (0-100 scale), System Usability Scale (SUS, 0-100 scale), perceived cognitive workload using the NASA Task Load Index (NASA-TLX, 0-100 scale), and Confidence in AI Interpretation (1-5 scale)
Study Type
Interventional
Enrollment (Actual)
120
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 Locations
-
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Montserrado County
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Monrovia, Montserrado County, Liberia, 1000
- University of Liberia Medical School
-
-
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
Yes
Description
Inclusion Criteria:
- Enrolled as a third-year medical student in the clinical neuroscience rotation at the University of Liberia.
- Willing and able to complete the 45-minute educational module and post-intervention evaluations.
- Provided informed consent to participate in the study.
Exclusion Criteria:
- Prior formal coursework, professional training, or specialized technical degree in artificial intelligence, machine learning, or computer science.
- Inability to complete the post-intervention assessment.
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: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Active Comparator: Control Group
Participants complete a 45-minute traditional lecture module on AI in neuroimaging using static text and bar charts
|
Standard educational instruction delivered via traditional slides and static charts explaining neuroimaging AI outputs.
|
|
Experimental: XAI-Enhanced Group
Participants complete an interactive 45-minute lecture module supplemented with CerViD-MultiModal visual XAI explanations (SHAP summary charts and LIME patient-specific explanations
|
Standard educational instruction delivered via traditional slides and static charts explaining neuroimaging AI outputs.
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
AI Literacy Score
Time Frame: Immediately post-intervention (Day 1)
|
Continuous score (0-100 scale) measuring conceptual knowledge, practical application, ethical awareness, and critical evaluation of AI systems in medicine
|
Immediately post-intervention (Day 1)
|
|
System Usability Scale (SUS) Score
Time Frame: Immediately post-intervention (Day 1)
|
Standardized 10-item scale assessing user perception of system usability, converted to a 0-100 overall score
|
Immediately post-intervention (Day 1)
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Lundberg SM, Lee SI. A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems (NeurIPS). 2017;30:4765-4774.
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)
May 30, 2026
Primary Completion (Actual)
May 30, 2026
Study Completion (Actual)
June 15, 2026
Study Registration Dates
First Submitted
July 29, 2026
First Submitted That Met QC Criteria
July 29, 2026
First Posted (Actual)
August 4, 2026
Study Record Updates
Last Update Posted (Actual)
August 4, 2026
Last Update Submitted That Met QC Criteria
July 29, 2026
Last Verified
July 1, 2026
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- UL-IRB-2026-XAI-MED
- U01AG024904 (U.S. NIH Grant/Contract)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
YES
IPD Plan Description
De-identified individual participant data collected during the study, including post-intervention assessment scores for AI literacy, System Usability Scale (SUS) ratings, NASA Task Load Index (NASA-TLX) workload metrics, and confidence scores, will be made available upon reasonable request.
All direct and indirect identifiers will be removed prior to data sharing to preserve participant privacy.
IPD Sharing Time Frame
De-identified individual participant data and supporting documents will become available within 6 months following publication of the study results in a peer-reviewed journal and will remain accessible for up to 3 years.
IPD Sharing Access Criteria
Data and supporting materials will be shared with qualified academic researchers and clinical educators whose formal proposal has been approved by the research team.
Access is granted solely for scientific research and meta-analytic purposes.
Requests should be submitted via email directly to the Principal Investigator.
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ANALYTIC_CODE
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.