GPT Models Can Perform Thematic Analysis in Public Health Studies,Akin to Qualitative ResearchersOA
GPT Models Can Perform Thematic Analysis in Public Health Studies,Akin to Qualitative Researchers
Yuyi Yang;Charles Alba;Chenyu Wang;Xi Wang;Jami Anderson;Ruopeng An
Division of Computational and Data Science's,Washington University in St.Louis,St.Louis 63130,MO,USADivision of Computational and Data Science's,Washington University in St.Louis,St.Louis 63130,MO,USASchool of Medicine,Washington University in St.Louis,St.Louis 63130,MO,USABrown School,Washington University in St.Louis,St.Louis 63130,MO,USAImplementation Science Center for Cancer Control,Washington University in St.Louis,St.Louis 63130,MO,USAConstance and Martin Silver Center on Data Science and Social Equity,Silver School of Social Work,New York University,New York 10003,NY,USA
social computing applications in healthcare and public healthethnographic and qualitative methodologiesmachine learningdata miningcomputational linguistics
social computing applications in healthcare and public healthethnographic and qualitative methodologiesmachine learningdata miningcomputational linguistics
《社会系统计算科学（英文）》 2024 (4)
293-312,20
This work was supported in part by the Washington University Center for Diabetes Translation Research(WU-CDTR)under Grant Number P30DK092950 from the National Institute of Diabetes and Digestive and Kidney Diseases(NIDDK).The content is solely the responsibility of the authors and does not necessarily represent the official views of the WU-CDTR or NIDDK.In addition,this work was supported in part by OpenAI in the form of token credits.The authors will like to acknowledge Meihua Li,who contributed to the data validation process.Y.Y.would like to acknowledge doctoral funding from the McDonnell Scholars Academy,and C.A.would like to acknowledge doctoral funding from the Danforth Scholarship.
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