Endodontic DiseasesGAI-ENDORDICNCT07731867
Generative AI-Based Immersive Training for Endodontic Risk Disclosure and Informed Consent Among Dental Students
A study testing Generative AI-Based Immersive Training and Conventional Case-Based Learning in people with Endodontic Diseases and Clinical Communication, run by The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine at 1 site in China.
Trial summary
The objective of this prospective, parallel-group, 1:1 randomized controlled trial is to evaluate the effectiveness of a generative artificial intelligence (AI)-based immersive training program, utilizing the Gemini platform, in improving endodontic risk disclosure and informed consent (RD-IC) quality, communication… Read more about this study
- Who is it for?
- Ages 18 to 25 yearsHealthy volunteers can take part
- Conditions the study is for
- Endodontic Diseases, Clinical Communication, Informed Consent
- What is being tested?
- Generative AI-Based Immersive Training and Conventional Case-Based Learning
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 96 participants
- Where
- 1 siteChina
- Study dates
- 1 Mar 2026to 31 May 2026
- 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 to 25 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Fifth-year undergraduate dental students undergoing clinical clerkship at the Department of Stomatology, Hunan University of Chinese Medicine.
- Completed all core didactic and theoretical courses in endodontics.
- Entered the early stage of clinical rotation.
- Provided signed voluntary informed consent to participate in the trial.
Who cannot join
- Prior experience with specialized clinical communication simulation or specialized AI communication training.
- Presence of unavoidable schedule conflicts during the study period.
- Factors affecting student eligibility to complete the full training and evaluation process.
Trial locations and contacts
1 site in 1 country.
China1 site
The First Affiliated Hospital of Hunan University of Chinese Medicine
Changsha, Hunan, 410007
About this study
Official title: Generative AI-Based Immersive Training for Endodontic Risk Disclosure and Informed Consent Among Dental Students: A Randomized Controlled Trial
The objective of this prospective, parallel-group, 1:1 randomized controlled trial is to evaluate the effectiveness of a generative artificial intelligence (AI)-based immersive training program, utilizing the Gemini platform, in improving endodontic risk disclosure and informed consent (RD-IC) quality, communication competence, self-efficacy, and reducing communication anxiety among undergraduate dental students during their clinical clerkship.
Traditional pedagogical methods in dental education, such as case-based learning (CBL) and peer role-playing, often struggle to simulate the high-stakes interpersonal tension and technical complexity involved in specialized endodontic risk disclosure. Complications like instrument separation, pulp floor perforation, and acute flare-ups require clear, empathetic, and legally sound communication. While standardized patients (SPs) are effective, they pose severe logistical and financial constraints for large student cohorts.
Read more
To address this gap, 96 fifth-year undergraduate dental students undergoing clinical rotation were recruited and randomly allocated to either the experimental group (1-month generative AI-based immersive training via the Gemini platform) or the control group (1-month conventional case-based learning). The AI intervention provided interactive, real-time conversational simulations across six high-stakes endodontic clinical scenarios, delivering instantaneous, personalized feedback on technical accuracy and empathetic delivery.
The primary outcome evaluated was the RD-IC completeness score. Secondary outcomes included SEGUE communication framework scores, Self-Efficacy in Clinical Communication Scale (SCS) scores, Communication Anxiety Scale (CAS) scores, blinded standardized patient (SP) ratings, user satisfaction, and long-term clinical skill retention assessed at 1-month (T2-1m) and 2-month (T2-2m) post-intervention follow-ups.
Read the detailed description
BACKGROUND AND RATIONALE:
Endodontic treatments-including root canal therapy, retreatment, and periradicular surgery-are technically demanding procedures that carry inherent risks of irreversible complications, such as instrument separation, canal ledging, pulp floor perforation, and acute flare-ups. Effective risk disclosure and informed consent (RD-IC) processes are essential ethical and legal safeguards that ensure patient autonomy, foster collaborative doctor-patient trust, and minimize medicolegal hazards. However, traditional dental education relying on passive lectures or case-based learning (CBL) fails to recreate the real-world psychological pressure and conversational fluidity needed during challenging consultations. Generative AI large language models (LLMs), such as Gemini, offer an innovative, highly scalable "safe-to-fail" platform capable of simulating adaptive patient personas with diverse emotional profiles and health literacy levels.
STUDY DESIGN AND PARTICIPANT RECRUITMENT:
This prospective, parallel-group, 1:1 randomized controlled trial was conducted at the Department of Stomatology, The First Affiliated Hospital of Hunan University of Chinese Medicine, from March to May 2026. The trial protocol strictly adhered to the CONSORT 2010 statement and CONSORT-EHEALTH 2023 extension guidelines, with ethical approval granted by the Institutional Review Board (Ethics File No. MR-43-26-046512).
A total of 96 eligible fifth-year undergraduate dental students in their clinical clerkship who had completed core endodontic didactic courses were enrolled. Participants were randomly assigned via a computer-generated random sequence to either:
- Experimental Group (n=48): Generative AI-based Immersive Training.
- Control Group (n=48): Conventional Case-Based Learning (CBL).
EDUCATIONAL INTERVENTIONS:
- Experimental Group: Participants completed a 1-month simulation program using the Gemini platform. The curriculum comprised six standardized, high-stakes endodontic clinical scenarios (including acute pain management, instrument separation disclosure, and pulp floor perforation). Students engaged in 10-15 minute adaptive dialogue sessions every 3-4 days. The platform utilized standardized prompt templates to deliver real-time, objective feedback on both technical completeness (risk disclosure) and humanistic communication (empathy, tone, and clarity).
- Control Group: Participants underwent conventional CBL targeting the exact same six endodontic scenarios over the same 1-month duration. Learning involved structured group case discussions, faculty lectures, and standard informed consent document reviews. Both groups had equal access to standard clinical guidelines.
OUTCOME MEASURES AND DATA COLLECTION:
Assessments were conducted at four distinct time points: Baseline (T0), Immediately Post-Intervention (T1), 1-Month Follow-Up (T2-1m), and 2-Month Follow-Up (T2-2m).
- Primary Outcome: RD-IC Completeness Score, measured via a validated 10-item checklist covering core indications, intraoperative complications, post-op pain, prognosis, alternative plans, and compliance.
- Secondary Outcomes:
- SEGUE Framework Scores: Assessing systematic communication competence (Set the stage, Elicit info, Give info, Understand perspective, End encounter).
- Communication Self-Efficacy Scale (SCS) Scores: Evaluating confidence across clinical communication domains.
- Communication Anxiety Scale (CAS) Scores: Assessing psychological tension and situational anxiety.
- Blinded Standardized Patient (SP) Global Ratings: External validation of clinical communication performance.
- Training Satisfaction Questionnaire: Evaluating platform authenticity, feedback quality, and user experience.
- Longitudinal Retention: Skill retention and clinical transferability evaluated at T2-1m and T2-2m.
STATISTICAL ANALYSIS:
Data analysis was conducted using SPSS 26.0 following Intention-To-Treat (ITT) and Per-Protocol (PP) principles. Group differences were evaluated using t-tests, Mann-Whitney U tests, chi-square tests, and repeated-measures ANOVA, with Bonferroni corrections applied for multiple comparisons.
- Being tested
- Generative AI-Based Immersive Training, Conventional Case-Based Learning
- Keywords
- Generative artificial intelligence, Immersive simulation, Endodontics, Risk disclosure, Informed consent
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Generative AI-Based Immersive TrainingOther
1-month generative AI-based immersive training program utilizing the Gemini platform. Participants engage in 10-15 minute adaptive conversational simulations every 3-4 days covering six high-stakes endodontic clinical scenarios (such as acute pain management, instrument separation disclosure, and pulp floor perforation), receiving immediate personalized feedback on risk disclosure completeness and empathetic communication.
Conventional Case-Based LearningOther
1-month conventional case-based learning curriculum targeting the exact same six high-stakes endodontic clinical scenarios. Learning involves structured case discussions, faculty-led lectures, and review of standardized informed consent templates without adaptive conversational immersion or real-time AI feedback.
| Study group | Role | What they receive |
|---|---|---|
| Experimental Group | Experimental | Participants received a 1-month generative AI-based immersive training program using the Gemini platform, engaging in standardized interactive simulations of six high-stakes endodontic clinical scenarios with immediate personalized feedback. Receives: Other: Generative AI-Based Immersive Training |
| Control Group | Active comparator | Participants underwent conventional case-based learning (CBL) targeting the same six endodontic scenarios over 1 month, involving group case discussions, faculty lectures, and standard informed consent reviews. Receives: Other: Conventional Case-Based Learning |
What is being measured
The primary outcome is the main question the study is designed to answer.
Endodontic Risk Disclosure and Informed Consent (RD-IC) Completeness Score
Evaluated via a validated 10-dimensional risk-disclosure checklist (10 major dimensions, each containing 10 binary scored sub-items; total possible score: 0-100). The 10 dimensions cover core treatment indications, intraoperative complications, postoperative pain, long-term structural defects, poor prognosis, anatomical variations, sequential restorative treatments, anesthetic \& material allergies, systemic-disease-related complications, and treatment-failure risks from poor patient compliance. Higher total scores represent greater technical accuracy and comprehensiveness of endodontic preoperative risk disclosure and informed-consent documentation.
Measured: Immediately post-intervention (T1, at 1 month after study baseline)
Secondary outcomes (7)
SEGUE Framework Doctor-Patient Communication Competence Score
Evaluated using the SEGUE framework checklist, assessing 5 communication domains: Set the Stage, Elicit Information, Give Information, Understand Patient Perspective, and End the Encounter. Total median scores range from 0 to 25, with higher scores reflecting superior systematic doctor-patient interaction skills.
Measured: Immediately post-intervention (T1, at 1 month after study baseline)
Clinical Communication Self-Efficacy Scale (SCS) Score
Measures students' confidence across 4 domains: Information Gathering, Clinical Information Delivery, Emotional Empathy, and Conflict Management/Closing. Scores range from 20 to 100, with higher scores indicating higher self-efficacy.
Measured: Immediately post-intervention (T1, at 1 month after study baseline)
Communication Anxiety Scale (CAS) Score
Evaluates clinical communication anxiety across 4 sub-domains: Situational Tension and Physical Anxiety, Professional Self-Doubt and Worry, Endodontic Risk Disclosure Anxiety, and Communication Burden and Avoidance Tendency. Scores range from 20 to 100, with lower scores indicating reduced clinical communication anxiety.
Measured: Immediately post-intervention (T1, at 1 month after study baseline)
Blinded Standardized Patient (SP) Core Clinical Communication Competence Score
External assessment rated by blinded standardized patients across 5 core clinical domains: Reception Etiquette, Standardized Inquiry, Risk Informed Consent Communication, Emotional Empathy, and Closed-loop Guidance. Total scores range from 0 to 100, with higher scores reflecting better clinical communicative performance.
Measured: Immediately post-intervention (T1, at 1 month after study baseline)
AI Simulation Teaching Experience Scale Score
Assesses student satisfaction with the educational intervention across 5 sub-scales: Platform Operation, Simulation Scene Authenticity, AI Real-time Feedback Quality, Perceived Ability Improvement, and Recognition of New Teaching Mode. Total scores range from 20 to 100, evaluated against a theoretical neutral midpoint of 50.
Measured: Immediately post-intervention (T1, at 1 month after study baseline)
Long-term Retention Score of Endodontic Risk Disclosure (1-Month Follow-Up)
Evaluates retention of communication skills 1 month post-intervention (T2-1m) across 5 sub-items: Basic Disease Communication, Intraoperative Risk Disclosure, Postoperative Risk Communication, Empathetic Alternative Plan Communication, and Closed-loop Consent Procedure. Total scores range from 0 to 100.
Measured: 1-month post-intervention follow-up (T2-1m, at 2 months after study baseline)
Long-term Retention Score of Endodontic Risk Disclosure (2-Month Follow-Up)
Evaluates long-term durability and resistance to skill decay 2 months post-intervention (T2-2m) across the same 5 risk disclosure sub-items. Total scores range from 0 to 100.
Measured: 2-month post-intervention follow-up (T2-2m, at 3 months after study baseline)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jul 2026
- Study start1 Mar 2026
- Primary completion1 Apr 2026
- Study completion31 May 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Endodontic DiseasesStudies 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
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- A prospective, parallel-group, 1:1 randomized controlled trial comparing a 1-month generative AI-based immersive training intervention (experimental group) with conventional case-based learning (control group).
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 96 participants (actual)
Sponsor and investigators
- Lead sponsor
- The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Qun li, The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07731867
- Sponsor's protocol ID
- MR-43-26-046512
- Other IDs
- 2023-JG048, 2026-JG060
- Acronym
- GAI-ENDORDIC
- Status last verified
- Oct 2026
- First submitted
- 23 Jul 2026
- Last updated
- 15 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The de-identified individual participant data collected during the trial will be made available from the corresponding author upon reasonable academic request.
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Generative AI-Based Immersive Training for Endodontic Risk Disclosure and Informed Consent Among Dental Students: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07731867
- Acronym / sponsor ID
- GAI-ENDORDIC / MR-43-26-046512
- Keywords
- Generative artificial intelligence, Immersive simulation, Endodontics, Risk disclosure, Informed consent
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 96 participants (actual)
- Lead sponsor
- The First Affiliated Hospital of Hunan University of Traditional Chinese MedicineUniversity, hospital or other
- Study start
- 1 Mar 2026 (actual)
- Primary completion
- 1 Apr 2026 (actual)
- Study completion
- 31 May 2026 (actual)
- First posted
- 28 Jul 2026 (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.
The objective of this prospective, parallel-group, 1:1 randomized controlled trial is to evaluate the effectiveness of a generative artificial intelligence (AI)-based immersive training program, utilizing the Gemini platform, in improving endodontic risk disclosure and informed consent (RD-IC) quality, communication competence, self-efficacy, and reducing communication anxiety among undergraduate dental students during their clinical clerkship.
Traditional pedagogical methods in dental education, such as case-based learning (CBL) and peer role-playing, often struggle to simulate the high-stakes interpersonal tension and technical complexity involved in specialized endodontic risk disclosure. Complications like instrument separation, pulp floor perforation, and acute flare-ups require clear, empathetic, and legally sound communication. While standardized patients (SPs) are effective, they pose severe logistical and financial constraints for large student cohorts.
To address this gap, 96 fifth-year undergraduate dental students undergoing clinical rotation were recruited and randomly allocated to either the experimental group (1-month generative AI-based immersive training via the Gemini platform) or the control group (1-month conventional case-based learning). The AI intervention provided interactive, real-time conversational simulations across six high-stakes endodontic clinical scenarios, delivering instantaneous, personalized feedback on technical accuracy and empathetic delivery.
The primary outcome evaluated was the RD-IC completeness score. Secondary outcomes included SEGUE communication framework scores, Self-Efficacy in Clinical Communication Scale (SCS) scores, Communication Anxiety Scale (CAS) scores, blinded standardized patient (SP) ratings, user satisfaction, and long-term clinical skill retention assessed at 1-month (T2-1m) and 2-month (T2-2m) post-intervention follow-ups.
Detailed description
BACKGROUND AND RATIONALE:
Endodontic treatments-including root canal therapy, retreatment, and periradicular surgery-are technically demanding procedures that carry inherent risks of irreversible complications, such as instrument separation, canal ledging, pulp floor perforation, and acute flare-ups. Effective risk disclosure and informed consent (RD-IC) processes are essential ethical and legal safeguards that ensure patient autonomy, foster collaborative doctor-patient trust, and minimize medicolegal hazards. However, traditional dental education relying on passive lectures or case-based learning (CBL) fails to recreate the real-world psychological pressure and conversational fluidity needed during challenging consultations. Generative AI large language models (LLMs), such as Gemini, offer an innovative, highly scalable "safe-to-fail" platform capable of simulating adaptive patient personas with diverse emotional profiles and health literacy levels.
STUDY DESIGN AND PARTICIPANT RECRUITMENT:
This prospective, parallel-group, 1:1 randomized controlled trial was conducted at the Department of Stomatology, The First Affiliated Hospital of Hunan University of Chinese Medicine, from March to May 2026. The trial protocol strictly adhered to the CONSORT 2010 statement and CONSORT-EHEALTH 2023 extension guidelines, with ethical approval granted by the Institutional Review Board (Ethics File No. MR-43-26-046512).
A total of 96 eligible fifth-year undergraduate dental students in their clinical clerkship who had completed core endodontic didactic courses were enrolled. Participants were randomly assigned via a computer-generated random sequence to either:
- Experimental Group (n=48): Generative AI-based Immersive Training.
- Control Group (n=48): Conventional Case-Based Learning (CBL).
EDUCATIONAL INTERVENTIONS:
- Experimental Group: Participants completed a 1-month simulation program using the Gemini platform. The curriculum comprised six standardized, high-stakes endodontic clinical scenarios (including acute pain management, instrument separation disclosure, and pulp floor perforation). Students engaged in 10-15 minute adaptive dialogue sessions every 3-4 days. The platform utilized standardized prompt templates to deliver real-time, objective feedback on both technical completeness (risk disclosure) and humanistic communication (empathy, tone, and clarity).
- Control Group: Participants underwent conventional CBL targeting the exact same six endodontic scenarios over the same 1-month duration. Learning involved structured group case discussions, faculty lectures, and standard informed consent document reviews. Both groups had equal access to standard clinical guidelines.
OUTCOME MEASURES AND DATA COLLECTION:
Assessments were conducted at four distinct time points: Baseline (T0), Immediately Post-Intervention (T1), 1-Month Follow-Up (T2-1m), and 2-Month Follow-Up (T2-2m).
- Primary Outcome: RD-IC Completeness Score, measured via a validated 10-item checklist covering core indications, intraoperative complications, post-op pain, prognosis, alternative plans, and compliance.
- Secondary Outcomes:
- SEGUE Framework Scores: Assessing systematic communication competence (Set the stage, Elicit info, Give info, Understand perspective, End encounter).
- Communication Self-Efficacy Scale (SCS) Scores: Evaluating confidence across clinical communication domains.
- Communication Anxiety Scale (CAS) Scores: Assessing psychological tension and situational anxiety.
- Blinded Standardized Patient (SP) Global Ratings: External validation of clinical communication performance.
- Training Satisfaction Questionnaire: Evaluating platform authenticity, feedback quality, and user experience.
- Longitudinal Retention: Skill retention and clinical transferability evaluated at T2-1m and T2-2m.
STATISTICAL ANALYSIS:
Data analysis was conducted using SPSS 26.0 following Intention-To-Treat (ITT) and Per-Protocol (PP) principles. Group differences were evaluated using t-tests, Mann-Whitney U tests, chi-square tests, and repeated-measures ANOVA, with Bonferroni corrections applied for multiple comparisons.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- A prospective, parallel-group, 1:1 randomized controlled trial comparing a 1-month generative AI-based immersive training intervention (experimental group) with conventional case-based learning (control group).
| Arm | Type | Receives |
|---|---|---|
| Experimental Group | Experimental | Other: Generative AI-Based Immersive TrainingParticipants received a 1-month generative AI-based immersive training program using the Gemini platform, engaging in standardized interactive simulations of six high-stakes endodontic clinical scenarios with immediate personalized feedback. |
| Control Group | Active comparator | Other: Conventional Case-Based LearningParticipants underwent conventional case-based learning (CBL) targeting the same six endodontic scenarios over 1 month, involving group case discussions, faculty lectures, and standard informed consent reviews. |
Who may qualify
- Ages
- 18 to 25 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (4 listed)
- Fifth-year undergraduate dental students undergoing clinical clerkship at the Department of Stomatology, Hunan University of Chinese Medicine.
- Completed all core didactic and theoretical courses in endodontics.
- Entered the early stage of clinical rotation.
- Provided signed voluntary informed consent to participate in the trial.
Key exclusion criteria (3 listed)
- Prior experience with specialized clinical communication simulation or specialized AI communication training.
- Presence of unavoidable schedule conflicts during the study period.
- Factors affecting student eligibility to complete the full training and evaluation process.
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 |
|---|---|---|
| Generative AI-Based Immersive Training1-month generative AI-based immersive training program utilizing the Gemini platform. Participants engage in 10-15 minute adaptive conversational simulations every 3-4 days covering six high-stakes endodontic clinical scenarios (such as acute pain management, instrument separation disclosure, and pulp floor perforation), receiving immediate personalized feedback on risk disclosure completeness and empathetic communication. | Other | Experimental Group |
| Conventional Case-Based Learning1-month conventional case-based learning curriculum targeting the exact same six high-stakes endodontic clinical scenarios. Learning involves structured case discussions, faculty-led lectures, and review of standardized informed consent templates without adaptive conversational immersion or real-time AI feedback. | Other | Control Group |
Primary outcome
Endodontic Risk Disclosure and Informed Consent (RD-IC) Completeness Score
Time frame: Immediately post-intervention (T1, at 1 month after study baseline)
Evaluated via a validated 10-dimensional risk-disclosure checklist (10 major dimensions, each containing 10 binary scored sub-items; total possible score: 0-100). The 10 dimensions cover core treatment indications, intraoperative complications, postoperative pain, long-term structural defects, poor prognosis, anatomical variations, sequential restorative treatments, anesthetic \& material allergies, systemic-disease-related complications, and treatment-failure risks from poor patient compliance. Higher total scores represent greater technical accuracy and comprehensiveness of endodontic preoperative risk disclosure and informed-consent documentation.
7 secondary outcomes
SEGUE Framework Doctor-Patient Communication Competence Score
Time frame: Immediately post-intervention (T1, at 1 month after study baseline)
Clinical Communication Self-Efficacy Scale (SCS) Score
Time frame: Immediately post-intervention (T1, at 1 month after study baseline)
Communication Anxiety Scale (CAS) Score
Time frame: Immediately post-intervention (T1, at 1 month after study baseline)
Blinded Standardized Patient (SP) Core Clinical Communication Competence Score
Time frame: Immediately post-intervention (T1, at 1 month after study baseline)
AI Simulation Teaching Experience Scale Score
Time frame: Immediately post-intervention (T1, at 1 month after study baseline)
Long-term Retention Score of Endodontic Risk Disclosure (1-Month Follow-Up)
Time frame: 1-month post-intervention follow-up (T2-1m, at 2 months after study baseline)
Long-term Retention Score of Endodontic Risk Disclosure (2-Month Follow-Up)
Time frame: 2-month post-intervention follow-up (T2-2m, at 3 months after study baseline)
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 15 Oct 2026.
- Individual participant dataSharing planned: Yes. The de-identified individual participant data collected during the trial will be made available from the corresponding author upon reasonable academic request.
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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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Generative AI-Based Immersive Training and Conventional Case-Based Learning in people with Endodontic Diseases and Clinical Communication, run by The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine 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 4 inclusion and 3 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 15 Oct 2026. 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?
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?
Endodontic Risk Disclosure and Informed Consent (RD-IC) Completeness Score (time frame: Immediately post-intervention (T1, at 1 month after study baseline)). 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 15 Oct 2026.