ArticleJMIR medical education2025
Global Health care Professionals' Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study.
Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Attitudes Toward Large Language Models in Health Care and Preferences for Their Adoption and Oversight Among Health Care Professionals: Cross-Sectional Survey.Journal of medical Internet research · 2026Article
- LLM research on public biosignals data is needed to protect patients.NPJ digital medicine · 2026Review
- Clinician Use of a General-Purpose Large Language Model in Hospital Medicine: A Mixed-Methods Pilot Study.Cureus · 2026Article
- Evaluating ChatGPT-5 for Detection of Barrett's Esophagus and Grading of Esophagitis: A Multiclass Endoscopic Image Analysis.JGH open : an open access journal of gastroenterology and hepatology · 2026Article
- Diagnostic Performance of a Large Language Model (ChatGPT-4o) in Chronic Rhinosinusitis CT Scan Interpretation.Laryngoscope investigative otolaryngology · 2026Article
- The Utility of ChatGPT for Medical Students on Plastic and Reconstructive Surgery Rotations.Aesthetic plastic surgery · 2026Article
- Governance for safe and responsible AI in healthcare organisations: a scoping review of frameworks.NPJ digital medicine · 2026Article
- Evaluation of GPT-5 in Periodontitis Staging and Grading: Retrospective Observational Study.JMIR formative research · 2026Observational
- An Exploratory Evaluation of GPT-5 in Periodontitis Staging and Grading Using Published Clinical Cases.Research square · 2026Article
- K-anonymity decay in multi-turn clinical large language model conversations.Frontiers in digital health · 2026Article
- Evaluation of GPT-5.2 for melanoma detection across skin tones.Frontiers in medicine · 2026Article
- Evaluating GPT-5 for Melanoma Detection Using Dermoscopic Images.Diagnostics (Basel, Switzerland) · 2025Article
- Nurses' Perspectives on Evidence Dissemination Barriers and Large Language Model-Based Support: Qualitative Study Using Focus Groups and Nominal Group Technique.Journal of medical Internet research · 2025Article
- Promoting trust and intention to adopt health information generated by ChatGPT among healthcare customers: An empirical study.Digital healthArticle
- A Performance-Based Rubric for Generative AI use in Medical Students' Research Tasks: Development and Initial Psychometric Evaluation.Journal of medical education and curricular developmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: ChatGPT is a large language model-based chatbot developed by OpenAI. ChatGPT has many potential applications to health care, including enhanced diagnostic accuracy and efficiency, improved treatment planning, and better patient outcomes. However, health care professionals' perceptions of ChatGPT and similar artificial intelligence tools are not well known. Understanding these attitudes is important to inform the best approaches to exploring their use in medicine. Objective: Our aim was to evaluate the health care professionals' awareness and perceptions regarding potential applications of ChatGPT in the medical field, including potential benefits and challenges of adoption. Methods: We designed a 33-question online survey that was distributed among health care professionals via targeted emails and professional Twitter and LinkedIn accounts. The survey included a range of questions to define respondents' demographic characteristics, familiarity with ChatGPT, perceptions of this tool's usefulness and reliability, and opinions on its potential to improve patient care, research, and education efforts. Results: One hundred and fifteen health care professionals from 21 countries responded to the survey, including physicians, nurses, researchers, and educators. Of these, 101 (87.8%) had heard of ChatGPT, mainly from peers, social media, and news, and 77 (76.2%) had used ChatGPT at least once. Participants found ChatGPT to be helpful for writing manuscripts (n=31, 45.6%), emails (n=25, 36.8%), and grants (n=12, 17.6%); accessing the latest research and evidence-based guidelines (n=21, 30.9%); providing suggestions on diagnosis or treatment (n=15, 22.1%); and improving patient communication (n=12, 17.6%). Respondents also felt that the ability of ChatGPT to access and summarize research articles (n=22, 46.8%), provide quick answers to clinical questions (n=15, 31.9%), and generate patient education materials (n=10, 21.3%) was helpful. However, there are concerns regarding the use of ChatGPT, for example, the accuracy of responses (n=14, 29.8%), limited applicability in specific practices (n=18, 38.3%), and legal and ethical considerations (n=6, 12.8%), mainly related to plagiarism or copyright violations. Participants stated that safety protocols such as data encryption (n=63, 62.4%) and access control (n=52, 51.5%) could assist in ensuring patient privacy and data security. Conclusions: Our findings show that ChatGPT use is widespread among health care professionals in daily clinical, research, and educational activities. The majority of our participants found ChatGPT to be useful; however, there are concerns about patient privacy, data security, and its legal and ethical issues as well as the accuracy of its information. Further studies are required to understand the impact of ChatGPT and other large language models on clinical, educational, and research outcomes, and the concerns regarding its use must be addressed systematically and through appropriate methods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.