NCT06015178

Enhancing Medical Researchers' Self-learning With an Intelligent Language Model

A Superiority Randomized Controlled Trial of the Effect of a Novel Intelligent Language Model on the Self-learning Ability of Medical Researchers

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 60 (estimated)
• Sponsor: Zhongshan Ophthalmic Center, Sun Yat-sen University · Academic / Other
• Sex: All
• Age: 20 Years – 28 Years
• Healthy volunteers: Accepted

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. 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.

Conditions

• Medical Artificial Intelligence
• Interdisciplinary Research
• Self-Directed Learning

Interventions

Type	Name	Description
OTHER	Intelligent Language Model	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.
OTHER	control	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.

Timeline

• Start date: 2023-08-30
• Primary completion: 2023-10-31
• Completion: 2024-04-30
• First posted: 2023-08-29
• Last updated: 2023-11-13

Locations

1 site across 1 country: China