Generative AI in Qualitative Health Research: What the Emerging Evidence Shows.
This article examines the emerging role of generative artificial intelligence (GenAI), particularly large language models like GPT-4, in assisting qualitative nursing research, which traditionally involves labor-intensive tasks such as coding transcripts, developing themes, and synthesizing findings...
| Publicado en: | Nursing Inquiry Vol. 33; no. 3; pp. 1 - 5 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
Jul2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195655295&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195655295 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13207881 82C jtl: Nursing Inquiry issn: 13207881 maglogo: Y pubinfo: dt: Jul2026 vid: 33 iid: 3 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 195655295 195655295 195655295 10.1111/nin.70140 195655295 ppf: 1 ppct: 4 formats: tig: atl: Generative AI in Qualitative Health Research: What the Emerging Evidence Shows. aug: au: Gupta, Pallavi Topaz, Maxim Connell, Kathryn A. Yu, Hyunmin Peltonen, Laura‐Maria affil: School of Nursing, Columbia University, New York New York,, USA sug: subj: Artificial Intelligence, Generative Evaluation Artificial Intelligence, Generative Utilization Research, Nursing Qualitative Studies Human Conceptual Framework Coding Methods Task Performance and Analysis Semantics Interrater Reliability Natural Language Processing Quality Assessment Thematic Analysis ab: This article examines the emerging role of generative artificial intelligence (GenAI), particularly large language models like GPT-4, in assisting qualitative nursing research, which traditionally involves labor-intensive tasks such as coding transcripts, developing themes, and synthesizing findings. Empirical studies indicate that GenAI can significantly accelerate initial coding, theme development, and summarization with substantial overlap to human analysis, though limitations remain—especially in accurate quote attribution, cultural and emotional nuance, and domain-specific precision—necessitating mandatory human oversight and verification. The authors propose a transparent framework for AI-assisted qualitative analysis that restricts AI roles to auditable, reversible, and verifiable tasks while reserving final interpretive authority exclusively for human researchers. They emphasize the need for standardized reporting of AI use in qualitative studies and call for further validation research within nursing contexts, highlighting that responsible AI integration may expand the scale and inclusivity of qualitative nursing research without replacing human judgment. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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