Medical Artificial IntelligenceNCT06015178
Enhancing Medical Researchers' Self-learning With an Intelligent Language Model
A study testing Intelligent Language Model in people with Medical Artificial Intelligence and Interdisciplinary Research, run by Zhongshan Ophthalmic Center, Sun Yat-sen University at 1 site in China.
Trial summary
Solving medical scientific problems is a crucial driving force behind the advancement of medical disciplines. As the complexity of scientific questions increases, an increasing number of problems require interdisciplinary collaboration to be resolved. Read more about this study
- Who is it for?
- Ages 20 to 28 yearsHealthy volunteers can take part
- Conditions the study is for
- Medical Artificial Intelligence, Interdisciplinary Research, Self-Directed Learning
- What is being tested?
- Intelligent Language Model
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 60 participants
- Where
- 1 siteChina
- Study dates
- 30 Aug 2023to 30 Apr 2024
- 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 20 to 28 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Junior ophthalmologist with 1-3 years of clinical experience
- 20-28 years old, regardless of gender
- No prior experience in interdisciplinary research involving digital medicine
- Self-reported a minimum of 20 hours of participation in this study during the trial period
- Agree to participate in this study and sign informed consent
Who cannot join
- Individuals with reading difficulties or reading disabilities
- Reluctance to participate in this study
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, 510060
Haotian Lin, M.D., Ph.D, 8613802793086, haot.lin@hotmail.com
Xun Wang, M.D., Ph.D, 8615017541549, wangx48@mail2.sysu.edu.cn
About this study
Official title: A Superiority Randomized Controlled Trial of the Effect of a Novel Intelligent Language Model on the Self-learning Ability of Medical Researchers
Solving medical scientific problems is a crucial driving force behind the advancement of medical disciplines. As the complexity of scientific questions increases, an increasing number of problems require interdisciplinary collaboration to be resolved. However, most medical researchers lack interdisciplinary background knowledge and require substantial time to systematically learn relevant knowledge and skills. Furthermore, the continuous emergence of new knowledge and skills emphasizes the importance of researchers' ability for autonomous learning in the medical field. Therefore, to promote the development of medical disciplines, there is an urgent need for an effective method to enhance researchers' self-directed learning abilities for conducting interdisciplinary research.
The next-generation artificial intelligence language models, exemplified by ChatGPT, hold great potential in assisting researchers to access knowledge and information from various domains. Whether researchers can leverage such AI tools to enhance their self-directed learning abilities for conducting interdisciplinary research remains to be further explored. Additionally, concerns have been raised regarding the potential degradation of cognitive abilities through their use, although valid evidence is currently lacking.
To investigate whether AI tools, represented by ChatGPT, can effectively assist medical researchers in conducting interdisciplinary research and whether their usage may negatively impact researchers' cognitive abilities, a randomized controlled trial is warranted. This trial aims to ascertain the potential benefits and risks associated with utilizing AI tools in the medical research domain.
- Being tested
- Intelligent Language Model, control
- Keywords
- medical artificial intelligence, Large Language Model, superiority randomized controlled trial, Self-Directed Learning
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Intelligent Language ModelOther
Subjects must use the intelligent language model to complete the retrieval and protocol design execution of an interdisciplinary task, in addition to Google search, literature search and book query.
controlOther
Subjects can only use Google search, literature retrieval and book query, and cannot use any AI-driven conversational natural language processing tools to complete the retrieval and protocol design execution of an interdisciplinary task.
| Study group | Role | What they receive |
|---|---|---|
| Intelligent Language Model Group | Experimental | Subjects must use the intelligent language model to complete the retrieval and protocol design execution of an interdisciplinary task, in addition to Google search, literature search and book query. Receives: Other: Intelligent Language Model |
| Control Group | Placebo comparator | Subjects can only use Google search, literature retrieval and book query, and cannot use any AI-driven conversational natural language processing tools to complete the retrieval and protocol design execution of an interdisciplinary task. Receives: Other: control |
What is being measured
The primary outcome is the main question the study is designed to answer.
completion rate
The number of people who completed the task within the given time / the total number of people in the group
Measured: through study completion, an average of 9 months
Secondary outcomes (1)
Feasibility of the research program
The feasibility of the scheme is scored by a scoring group composed of experts. The feasibility is divided into 1-5 points according to the correctness and integrity of the key steps and details of the test. The higher the score, the higher the feasibility. The 1 point represents more than half of the key steps are missing or wrong, and the 5 point represents all the key steps and the details are appropriate.
Measured: through study completion, an average of 9 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Aug 2023
- Study start30 Aug 2023
- Primary completion31 Oct 2023 (estimated)
- Study completion30 Apr 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Medical Artificial IntelligenceStudies of the same condition, open and under way.
- More trials run by Zhongshan Ophthalmic Center, Sun Yat-sen UniversityThe sponsor's other registered studies.
- 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
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 60 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06015178
- Sponsor's protocol ID
- 2023KYPJ222
- Status last verified
- Jul 2023
- First submitted
- 21 Aug 2023
- Last updated
- 13 Nov 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Shang Y, Lin Y, Li R, Shang Y, Li M, Zhao L, Jin L, Xu A, Liu D, Wu Q, Luo M, Pang J, Bi S, He Y, Xu M, Chen X, Cao Z, Yu S, Zhao J, Lai Y, Chen W, Lin H. The effectiveness of large language models in medical AI research for physicians: A randomized controlled trial. Cell Rep Med. 2025 Dec 16;6(12):102469. doi: 10.1016/j.xcrm.2025.102469. Epub 2025 Nov 26.
PubMed 41308643
Study at a glance
From the registry record, last updated by the sponsor on 13 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Superiority Randomized Controlled Trial of the Effect of a Novel Intelligent Language Model on the Self-learning Ability of Medical Researchers
- ClinicalTrials.gov ID
- NCT06015178
- Acronym / sponsor ID
- 2023KYPJ222
- Keywords
- medical artificial intelligence, Large Language Model, superiority randomized controlled trial, Self-Directed Learning
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 60 participants (estimated)
- Lead sponsor
- Zhongshan Ophthalmic Center, Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 30 Aug 2023 (actual)
- Primary completion
- 31 Oct 2023 (estimated)
- Study completion
- 30 Apr 2024 (estimated)
- First posted
- 29 Aug 2023 (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.
Solving medical scientific problems is a crucial driving force behind the advancement of medical disciplines. As the complexity of scientific questions increases, an increasing number of problems require interdisciplinary collaboration to be resolved. However, most medical researchers lack interdisciplinary background knowledge and require substantial time to systematically learn relevant knowledge and skills. Furthermore, the continuous emergence of new knowledge and skills emphasizes the importance of researchers' ability for autonomous learning in the medical field. Therefore, to promote the development of medical disciplines, there is an urgent need for an effective method to enhance researchers' self-directed learning abilities for conducting interdisciplinary research.
The next-generation artificial intelligence language models, exemplified by ChatGPT, hold great potential in assisting researchers to access knowledge and information from various domains. Whether researchers can leverage such AI tools to enhance their self-directed learning abilities for conducting interdisciplinary research remains to be further explored. Additionally, concerns have been raised regarding the potential degradation of cognitive abilities through their use, although valid evidence is currently lacking.
To investigate whether AI tools, represented by ChatGPT, can effectively assist medical researchers in conducting interdisciplinary research and whether their usage may negatively impact researchers' cognitive abilities, a randomized controlled trial is warranted. This trial aims to ascertain the potential benefits and risks associated with utilizing AI tools in the medical research domain.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Intelligent Language Model Group | Experimental | Other: Intelligent Language ModelSubjects must use the intelligent language model to complete the retrieval and protocol design execution of an interdisciplinary task, in addition to Google search, literature search and book query. |
| Control Group | Placebo comparator | Other: controlSubjects can only use Google search, literature retrieval and book query, and cannot use any AI-driven conversational natural language processing tools to complete the retrieval and protocol design execution of an interdisciplinary task. |
Who may qualify
- Ages
- 20 to 28 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (5 listed)
- Junior ophthalmologist with 1-3 years of clinical experience
- 20-28 years old, regardless of gender
- No prior experience in interdisciplinary research involving digital medicine
- Self-reported a minimum of 20 hours of participation in this study during the trial period
- Agree to participate in this study and sign informed consent
Key exclusion criteria (2 listed)
- Individuals with reading difficulties or reading disabilities
- Reluctance to participate in this study
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 |
|---|---|---|
| Intelligent Language ModelSubjects must use the intelligent language model to complete the retrieval and protocol design execution of an interdisciplinary task, in addition to Google search, literature search and book query. | Other | Intelligent Language Model Group |
| controlSubjects can only use Google search, literature retrieval and book query, and cannot use any AI-driven conversational natural language processing tools to complete the retrieval and protocol design execution of an interdisciplinary task. | Other | Control Group |
Primary outcome
completion rate
Time frame: through study completion, an average of 9 months
The number of people who completed the task within the given time / the total number of people in the group
1 secondary outcome
Feasibility of the research program
Time frame: through study completion, an average of 9 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Nov 2023.
- Derived from this study: PubMed 41308643Shang Y, Lin Y, Li R, Shang Y, Li M, Zhao L, Jin L, Xu A, Liu D, Wu Q, Luo M, Pang J, Bi S, He Y, Xu M, Chen X, Cao Z, Yu S, Zhao J, Lai Y, Chen W, Lin H. The effectiveness of large language models in medical AI research for physicians: A randomized controlled trial. Cell Rep Med. 2025 Dec 16;6(12):102469. doi: 10.1016/j.xcrm.2025.102469. Epub 2025 Nov 26.
- 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. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Intelligent Language Model in people with Medical Artificial Intelligence and Interdisciplinary Research, run by Zhongshan Ophthalmic Center, Sun Yat-sen University 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 5 inclusion and 2 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: status not confirmed, as of the sponsor's last update on 13 Nov 2023. 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. Some participants in this study may receive a placebo. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact wenben chen, Doctor (+8618819472798, weberchan@foxmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
completion rate (time frame: through study completion, an average of 9 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06015178, which also lists 1 linked publication.
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 13 Nov 2023.