RESUMO
The impact of ChatGPT and other large language model-based applications on scientific work is being debated across contexts and disciplines. However, despite ChatGPT's inherent focus on language generation and processing, insights regarding its potential for supporting qualitative research and analysis remain limited. In this article, we advocate for an open discourse on chances and pitfalls of AI-supported qualitative analysis by exploring ChatGPT's performance when analyzing an interview transcript based on various prompts and comparing results to those derived by an experienced human researcher. Themes identified by the human researcher and ChatGPT across analytic prompts overlapped to a considerable degree, with ChatGPT leaning toward descriptive themes but also identifying more nuanced dynamics (e.g., 'trust and responsibility' and 'acceptance and resistance'). ChatGPT was able to propose a codebook and key quotes from the transcript which had considerable face validity but would require careful review. When prompted to embed findings into broader theoretical discourses, ChatGPT could convincingly argue how identified themes linked to the provided theories, even in cases of (seemingly) unfitting models. In general, despite challenges, ChatGPT performed better than we had expected, especially on identifying themes which generally overlapped with those of an experienced researcher, and when embedding these themes into specific theoretical debates. Based on our results, we discuss several ideas on how ChatGPT could contribute to but also challenge established best-practice approaches for rigorous and nuanced qualitative research and teaching.
RESUMO
Objective: According to the WHO, anthropogenic climate change poses the greatest threat to human health in the 21st century. However, the link between climate change and human health is not an integral part of medical education in Germany. Within a student-led project, an elective clinical course was designed and successfully implemented, which has been made accessible to undergraduate medical students at the Universities of Giessen and Marburg. The implementation and didactic concept are explained in this article. Methodology: In a participatory format, knowledge is imparted using an action-based, transformative approach. Topics discussed are, amongst others, interactions of climate change and health, transformative action, and health behavior, as well as "green hospital" and the simulation of a "climate-sensitive health counselling". Lecturers from different disciplines within and beyond medicine are invited as speakers. Results: Overall, the elective was evaluated positively by the participants. The fact that there is a high demand among students for participation in the elective, as well as for the transfer of concepts underlines the need for including this topic into medical education. The implementation and further development of the concept at two universities with different study regulations demonstrates its adaptability. Conclusion: Medical education can raise awareness of the multiple health consequences of the climate crisis, can have a sensitizing and transformative effect on various levels, and can promote climate-sensitive action ability in patient care. In the long term, however, these positive consequences can only be guaranteed by including mandatory education on climate change and health in medical curricula.