Working packages and time table.

BackgroundThe advancement of Artificial Intelligence, particularly Large Language Models (LLMs), is rapidly progressing. LLMs, such as OpenAI’s GPT, are becoming vital in scientific and medical processes, including text production, knowledge synthesis, translation, patient communication and data analysis. However, the outcome quality needs to be evaluated to assess the full potential for usage in statistical applications. LLMs show potential for all research areas, including teaching. Integrating LLMs in research, education and medical care poses opportunities and challenges, depending on user competence, experience and attitudes.ObjectiveThis project aims at exploring the use of LLMs in supporting statistical consulting by evaluating the utility, efficiency and satisfaction related to the use of LLMs in statistical consulting from both advisee and consultant perspective. Within this project, we will develop, execute and evaluate a training module for the use of LLMs in statistical consulting. In this context, we aim to identify the strengths, limitations and areas for potential improvement. Furthermore, we will explore experiences, attitudes, fears and current practices regarding the use of LLMs of the staff at the Medical Center and the University of Freiburg.Materials and methodsThis multimodal study includes four study parts using qualitative and quantitative methods to gather data. Study part (I) is designed as mixed mode study to explore the use of LLMs in supporting statistical consulting and to evaluate the utility, efficiency and satisfaction related to the use of LLMs. Study part (II) uses a standardized online questionnaire to evaluate the training module. Study part (III) evaluates the consulting sessions using LLMs from advisee perspective. Study part (IV) explores experiences, attitudes, fears and current practices regarding the use of LLMs of the staff at the Medical Center and the University of Freiburg. This study is registered at the Freiburg Registry of Clinical Studies under the ID: FRKS004971.一、研究背景 人工智能领域，尤其是大语言模型（Large Language Models，LLMs），正快速演进。以OpenAI的GPT为代表的大语言模型，已在科研与医疗流程中发挥至关重要的作用，涵盖文本生成、知识合成、翻译、医患沟通与数据分析等多个环节。然而，当前仍需对其输出质量开展评估，以充分研判其在统计应用场景中的应用潜力。大语言模型在包括教学在内的所有科研领域均展现出应用潜力。将大语言模型融入科研、教育与医疗护理场景，既带来了发展机遇，也面临诸多挑战，这取决于使用者的能力、经验与使用态度。 二、研究目标 本项目旨在探索大语言模型在统计咨询中的辅助应用，通过从咨询方与被咨询方双视角，评估大语言模型应用于统计咨询时的效用性、效率与用户满意度。本项目将开发、实施并评估一套面向统计咨询场景的大语言模型使用培训模块。在此框架下，本研究旨在明确大语言模型的优势、局限及潜在优化方向。此外，本研究还将调研弗莱堡大学医学中心与弗莱堡大学教职员工对大语言模型的使用体验、态度、顾虑及当前实践情况。 三、材料与方法 本多模态研究包含四个研究模块，均采用定性与定量结合的方法采集数据。研究模块（I）采用混合研究设计，旨在探索大语言模型辅助统计咨询的应用场景，并评估其使用效用、效率与用户满意度。研究模块（II）通过标准化在线问卷对本项目开发的培训模块进行评估。研究模块（III）从被咨询方视角，对使用大语言模型的咨询会话开展评估。研究模块（IV）针对弗莱堡大学医学中心与弗莱堡大学教职员工，调研其使用大语言模型的体验、态度、顾虑及当前实践现状。本研究已在弗莱堡临床研究注册平台完成注册，注册编号为FRKS004971。