ArticleJournal of medical Internet research2025
A Practical Guide and Assessment on Using ChatGPT to Conduct Grounded Theory: Tutorial.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Using Student-Reported Digital Daily Logs and Human-Verified AI-Assisted Reflection Coding to Describe Clinical Experiences in Community-Based Clerkships: Exploratory Observational Mixed Methods Study.JMIR formative research · 2026Observational
- Examining Increased Ritalin and Adderall Use Among Low-Income People Who Use Drugs: Mixed Methods Study.JMIR formative research · 2026Article
- Generative Artificial Intelligence for Qualitative Methods in Health Research: Rapid Review.Journal of medical Internet research · 2026Review
- Multimodule Human-Artificial Intelligence Collaboration Pipeline for Large Language Model-Assisted Thematic Analysis Across Digital Health Interview Studies: Comparative Evaluation Study.JMIR medical informatics · 2026Article
- The use and methodological reporting of large language models in qualitative research: a scoping review.BMC medical research methodology · 2026Article
- The overlooked threat of democratic neutrality in the USA.Nature human behaviour · 2026Article
- Outcomes from a STEM Education Program for Elementary School Students in Medically Underserved Areas and Populations.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026Article
- Impact of Community-Oriented Medical Education on Medical Students' Perceptions of Community Health Care: Qualitative Study.JMIR medical education · 2026Article
- Ambivalent Agents: The Social Mobility Industry and Civil Society Under Neoliberalism in England.The British journal of sociology · 2025Article
- A systematic review of the application of computational grounded theory method in healthcare research.Biology methods & protocols · 2025Article
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Authors and funding
5 authors.
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Abstract
Generative large language models (LLMs), such as ChatGPT, have significant potential for qualitative data analysis. This paper aims to provide an early insight into how LLMs can enhance the efficiency of text coding and qualitative analysis, and evaluate their reliability. Using a dataset of semistructured interviews with blind gamers, this study provides a step-by-step tutorial on applying ChatGPT 4-Turbo to the grounded theory approach. The performance of ChatGPT 4-Turbo is evaluated by comparing its coding results with manual coding results assisted by qualitative analysis software. The results revealed that ChatGPT 4-Turbo and manual coding methods exhibited reliability in many aspects. The application of ChatGPT 4-Turbo in grounded theory enhanced the efficiency and diversity of coding and updated the overall grounded theory process. Compared with manual coding, ChatGPT showed shortcomings in depth, context, connections, and coding organization. Limitations and recommendations for applying artificial intelligence in qualitative research were also discussed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.