ArticleJournal of medical Internet research2024
Comparing GPT-4 and Human Researchers in Health Care Data Analysis: Qualitative Description Study.
Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of Chatbots in Mental Health Screening and Assessment: Systematic Review.JMIR mental health · 2026Pooled it
- Comparing AI-Assisted Coding and Traditional Qualitative Analysis: a Study Examining Differences in Methods and Results of AI-Assisted Coding and Traditional Content Coding Using Community Engagement Data Collected During the Development of a Municipal Food Plan.Prevention science : the official journal of the Society for Prevention Research · 2026Article
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- Applications of generative artificial intelligence in chronic pain: a scoping review.Journal of anesthesia · 2026Review
- Generative Artificial Intelligence for Qualitative Methods in Health Research: Rapid Review.Journal of medical Internet research · 2026Review
- Analyzing Nurse Sentiment in a Dutch Regional Newspaper During the COVID-19 Pandemic: Comparative Content Analysis of GPT-5, Gemini 2.5 Pro, and Human Coding.Journal of medical Internet research · 2026Article
- Large Language Model-Assisted Annotation Framework for Cross-Platform Analysis of Online Autism Communities: Implications for Parent Education and Digital Support.Journal of medical Internet research · 2026Article
- 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
- Integrating Large Language Models into Qualitative Methods in Health Services Research: A Proof-of-Concept Study.Research square · 2026Article
- Large language models for thematic analysis in healthcare research: A blinded mixed-methods comparison with human analysts.PLOS digital health · 2026Article
- Human Analysis vs. Artificial Intelligence: Analyzing of Qualitative Medical Students' Narratives.Qualitative health research · 2026Article
- Comparing human vs. machine-assisted analysis to develop a new approach for Big Qualitative Data Analysis.PLOS digital health · 2026Article
- A framework for generative AI-driven extraction of clinical user needs in pediatric device development.Frontiers in digital health · 2026Article
- Diagnostic Constructs of Major Depression in DSM-5: Current Critiques and Future Directions.Advances in experimental medicine and biology · 2026Review
- ChatGPT as therapy: A qualitative and network-based thematic profiling of shared experiences, attitudes, and beliefs on Reddit.Journal of psychiatric research · 2025Article
- Leveraging open-source large language models for clinical information extraction in resource-constrained settings.JAMIA open · 2025Article
- Application of Large Language Models in Stroke Rehabilitation Health Education: 2-Phase Study.Journal of medical Internet research · 2025Article
- When investigator meets large language models: a qualitative analysis of cancer patient decision-making journeys.NPJ digital medicine · 2025Article
- Is Tree-of-Thought Prompting Strategy Better than Chain-of-Thought? Vaping Cessation Analysis Using Large Language Models.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
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8 authors.
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Abstract
backgroundLarge language models including GPT-4 (OpenAI) have opened new avenues in health care and qualitative research. Traditional qualitative methods are time-consuming and require expertise to capture nuance. Although large language models have demonstrated enhanced contextual understanding and inferencing compared with traditional natural language processing, their performance in qualitative analysis versus that of humans remains unexplored.
objectiveWe evaluated the effectiveness of GPT-4 versus human researchers in qualitative analysis of interviews with patients with adult-acquired buried penis (AABP).
methodsQualitative data were obtained from semistructured interviews with 20 patients with AABP. Human analysis involved a structured 3-stage process-initial observations, line-by-line coding, and consensus discussions to refine themes. In contrast, artificial intelligence (AI) analysis with GPT-4 underwent two phases: (1) a naïve phase, where GPT-4 outputs were independently evaluated by a blinded reviewer to identify themes and subthemes and (2) a comparison phase, where AI-generated themes were compared with human-identified themes to assess agreement. We used a general qualitative description approach.
resultsThe study population (N=20) comprised predominantly White (17/20, 85%), married (12/20, 60%), heterosexual (19/20, 95%) men, with a mean age of 58.8 years and BMI of 41.1 kg/m
conclusionsLarge language models including GPT-4 can effectively identify key themes in analyzing qualitative health care data, showing moderate agreement with human analysis. While human analysis provided a richer diversity of subthemes, the consistency of AI suggests its use as a complementary tool in qualitative research. With AI rapidly advancing, future studies should iterate analyses and circumvent token limitations by segmenting data, furthering the breadth and depth of large language model-driven qualitative analyses.
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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.