Large Language Models in Nursing Education: State-of-the-Art DOI Creative Commons
Daniel Rodrigues, Ricardo Cruz‐Correia

Studies in health technology and informatics, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 22, 2024

This study explores the integration of Large Language Models (LLMs) into nursing education, highlighting a paradigm shift towards interactive learning environments. We aimed to analyze literature identify how large language models are being implemented in as well key opportunities and limitations that need be addressed. English records published since 2022 were retrieved from 4 databases including LLMs education. A total 19 eligible. As advanced natural processing capabilities enable experiences, educators presented with unique enhance curriculum delivery, foster critical thinking, simulate complex clinical scenarios. Through comprehensive analysis current applications, future research, this paper navigates complexities adopting (eg ChatGPT) concludes call for action advance AI nursing, enhancing educational outcomes while ensuring ethical, effective use.

Language: Английский

A systematic review of large language models and their implications in medical education DOI Creative Commons

Harrison C. Lucas,

Jeffrey S. Upperman, Jamie R. Robinson

et al.

Medical Education, Journal Year: 2024, Volume and Issue: unknown

Published: April 19, 2024

Abstract Introduction In the past year, use of large language models (LLMs) has generated significant interest and excitement because their potential to revolutionise various fields, including medical education for aspiring physicians. Although students undergo a demanding educational process become competent health care professionals, emergence LLMs presents promising solution challenges like information overload, time constraints pressure on clinical educators. However, integrating into raises critical concerns educators, professionals students. This systematic review aims explore LLM applications in education, specifically impact students' learning experiences. Methods A search was performed PubMed, Web Science Embase articles discussing using selected keywords related from ChatGPT's debut until February 2024. Only available full text or English were reviewed. The credibility each study critically appraised by two independent reviewers. Results identified 166 studies, which 40 found be relevant study. Among key themes included capabilities, benefits such as personalised regarding content accuracy. Importantly, 42.5% these studies evaluated novel way, ChatGPT, contexts exams clinical/biomedical information, highlighting replicating human‐level performance knowledge. remaining broadly discussed prospective role reflecting keen future despite current constraints. Conclusions responsible implementation offers opportunity enhance ensuring accuracy, emphasising skill‐building maintaining ethical safeguards are crucial. Continuous evaluation interdisciplinary collaboration essential appropriate integration education.

Language: Английский

Citations

46
Bibliometric and content analysis of ChatGPT research in nursing education: The rabbit hole in nursing education DOI
Turgay Yalcinkaya, Şebnem Çınar Yücel

Nurse Education in Practice, Journal Year: 2024, Volume and Issue: 77, P. 103956 - 103956

Published: April 10, 2024

Language: Английский

Citations

14
Large Language Models in Worldwide Medical Exams: Platform Development and Comprehensive Analysis (Preprint) DOI Creative Commons
Hui Zong, Rongrong Wu, Jiaxue Cha

et al.

Journal of Medical Internet Research, Journal Year: 2024, Volume and Issue: 26, P. e66114 - e66114

Published: Dec. 10, 2024

Background Large language models (LLMs) are increasingly integrated into medical education, with transformative potential for learning and assessment. However, their performance across diverse exams globally has remained underexplored. Objective This study aims to introduce MedExamLLM, a comprehensive platform designed systematically evaluate the of LLMs on worldwide. Specifically, seeks (1) compile curate data worldwide exams; (2) analyze trends disparities in LLM capabilities geographic regions, languages, contexts; (3) provide resource researchers, educators, developers explore advance integration artificial intelligence education. Methods A systematic search was conducted April 25, 2024, PubMed database identify relevant publications. Inclusion criteria encompassed peer-reviewed, English-language, original research articles that evaluated at least one exams. Exclusion included review articles, non-English publications, preprints, studies without performance. The screening process candidate publications independently by 2 researchers ensure accuracy reliability. Data, including exam information, model performance, availability, references, were manually curated, standardized, organized. These curated MedExamLLM platform, enabling its functionality visualize geographic, linguistic, characteristics. web developed focus accessibility, interactivity, scalability support continuous updates user engagement. Results total 193 final analysis. comprised information 16 198 28 countries 15 languages from year 2009 2023. United States accounted highest number related English being dominant used these Generative Pretrained Transformer (GPT) series models, especially GPT-4, demonstrated superior achieving pass rates significantly higher than other LLMs. analysis revealed significant variability different linguistic contexts. Conclusions is an open-source, freely accessible, publicly available online providing evaluation evidence knowledge about around world. serves as valuable fields clinical medicine intelligence. By synthesizing capabilities, provides insights Limitations include biases source exclusion literature. Future should address gaps methods enhance

Language: Английский

Citations

9
Facilitators and Barriers of Large Language Model Adoption Among Nursing Students: A Qualitative Descriptive Study DOI Creative Commons

Yingzhuo Ma,

Tong Liu,

Jianwei Qi

et al.

Journal of Advanced Nursing, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 4, 2025

ABSTRACT Aim To explore nursing students' perceptions and experiences of using large language models identify the facilitators barriers by applying Theory Planned Behaviour. Design A qualitative descriptive design. Method Between January June 2024, we conducted individual semi‐structured online interviews with 24 students from 13 medical universities across China. Participants were recruited purposive snowball sampling methods. Interviews in Mandarin. Data analysed through directed content analysis. Results Analysis revealed 10 themes according to 3 constructs Behaviour: (a) attitude: perceived value expectations facilitators, while caution posed barriers; (b) subjective norm: media effects role model effectiveness described as whereas organisational pressure exerted universities, research institutions hospitals acted a barrier usage; (c) behavioural control: design free access strong incentives for use, geographic restrictions digital literacy deficiencies key factors hindering adoption. Conclusion This study explored attitudes, norms control regarding use models. The findings provided valuable insights into that hindered or facilitated Implications Profession Through lens this study, have enhanced knowledge journey models, which contributes implementation management these tools education. Impact There is gap literature views influence their usage, addresses. These could provide evidence‐based support nurse educators formulate strategies guidelines. Reporting adheres consolidated criteria reporting (COREQ) checklist. Public Contribution No patient public contribution.

Language: Английский

Citations

1
Toward Clinical Generative AI: Conceptual Framework DOI Creative Commons
Nicola Luigi Bragazzi, Sergio Garbarino

JMIR AI, Journal Year: 2024, Volume and Issue: 3, P. e55957 - e55957

Published: May 6, 2024

Clinical decision-making is a crucial aspect of health care, involving the balanced integration scientific evidence, clinical judgment, ethical considerations, and patient involvement. This process dynamic multifaceted, relying on clinicians’ knowledge, experience, intuitive understanding to achieve optimal outcomes through informed, evidence-based choices. The advent generative artificial intelligence (AI) presents revolutionary opportunity in decision-making. AI’s advanced data analysis pattern recognition capabilities can significantly enhance diagnosis treatment diseases, processing vast medical identify patterns, tailor treatments, predict disease progression, aid proactive management. However, incorporation AI into raises concerns regarding reliability accuracy AI-generated insights. To address these concerns, 11 “verification paradigms” are proposed this paper, with each paradigm being unique method verify nature paper also frames concept “clinically explainable, fair, responsible, clinician-, expert-, patient-in-the-loop AI.” model focuses ensuring comprehensibility, collaborative nature, grounding, advocating for serve as an augmentative tool, its processes transparent understandable clinicians patients. should enhance, not replace, clinician’s judgment involve continuous learning adaptation based real-world legal compliance. In conclusion, while holds immense promise enhancing decision-making, it essential ensure that produces evidence-based, reliable, impactful knowledge. Using outlined paradigms approaches help communities harness potential maintaining high care standards.

Language: Английский

Citations

8
The potential of ChatGPT in medicine: an example analysis of nephrology specialty exams in Poland DOI Creative Commons
Jan Nicikowski, Mikołaj Szczepański, Miłosz Miedziaszczyk

et al.

Clinical Kidney Journal, Journal Year: 2024, Volume and Issue: 17(8)

Published: June 21, 2024

In November 2022, OpenAI released a chatbot named ChatGPT, product capable of processing natural language to create human-like conversational dialogue. It has generated lot interest, including from the scientific community and medical science community. Recent publications have shown that ChatGPT can correctly answer questions exams such as United States Medical Licensing Examination other specialty exams. To date, there been no studies in which tested on field nephrology anywhere world.

Language: Английский

Citations

8
Attitude and utilization of ChatGPT among registered nurses: A cross‐sectional study DOI
Hui‐Ling Lin, Li‐Ling Liao, Yani Wang

et al.

International Nursing Review, Journal Year: 2024, Volume and Issue: unknown

Published: July 9, 2024

Abstract Aim This study explores the influencing factors of attitudes and behaviors toward use ChatGPT based on Technology Acceptance Model among registered nurses in Taiwan. Background The complexity medical services nursing shortages increases workloads. swiftly answers questions, provides clinical guidelines, assists with patient information management, thereby improving efficiency. Introduction To facilitate development effective training programs, it is essential to examine nurses’ utilization across diverse workplace settings. Methods An anonymous online survey was used collect data from over 1000 recruited through social media platforms between November 2023 January 2024. Descriptive statistics multiple linear regression analyses were conducted for analysis. Results Among respondents, some unfamiliar ChatGPT, while others had before, higher usage males, higher‐educated individuals, experienced nurses, supervisors. Gender work settings influenced perceived risks, those familiar recognized its impact. Perceived risk usefulness significantly adoption. Discussion Nurse vary gender, education, experience, role. Positive perceptions emphasize usefulness, concerns affect insignificant role ease highlights ChatGPT's user‐friendly nature. Conclusion Over half surveyed or showed positive use. Establishing rigorous guidelines enhance their interaction crucial future training. Implications health policy managers should understand integrate into in‐service education tailored support training, including appropriate prompt formulation advanced decision‐making, prevent misuse.

Language: Английский

Citations

7
Evaluating the application of ChatGPT in China’s residency training education: An exploratory study DOI

Luxiang Shang,

Rui Li,

Mingyue Xue

et al.

Medical Teacher, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 7

Published: July 12, 2024

The purpose of this study was to assess the utility information generated by ChatGPT for residency education in China.

Language: Английский

Citations

7
From Optimism to Concern: Unveiling Sentiments and Perceptions Surrounding ChatGPT on Twitter DOI
Sadettin Demirel, Elif Kahraman-Gokalp, Uğur Gündüz

et al.

International Journal of Human-Computer Interaction, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: Aug. 27, 2024

Artificial intelligence (AI) technologies, as a product of processes aimed at imitating human through computers and software, affect our daily lives in various aspects, including cultural, technological, economic. The advent ChatGPT, developed by OpenAI, signifies pivotal AI advancement language comprehension generation, heralding profound implications across societal, economic, cultural dimensions. However, notable gap exists scholarly literature concerning the examination perceptions discussions surrounding ChatGPT. This study aims to address this analyzing Twitter conversations, comprising 1.1 million tweets containing "ChatGPT" or "#ChatGPT" between December 1 2022 June 2023, with geolocation data. Employing text data approach encompassing text, sentiment, semantic network analyses, sentiment polarity lexical patterns were explained, while analysis revealed central expressions prominent themes discussions. highlights social effects technologies from perspective users reveals sentimental tendency geographical economic findings reflect prevalence positive hype toward ChatGPT there are also concerns regarding privacy, cybersecurity, misuse tools. More importantly, content technical business applications, educational use, competitors among main ChatGPT-related on Twitter.

Language: Английский

Citations

5
Generative artificial intelligence in higher education learning: A review based on academic databases DOI Open Access
Daniel Andrade-Girón, William Joel Marín Rodriguez, Juana Sandivar

et al.

Iberoamerican Journal of Science Measurement and Communication, Journal Year: 2024, Volume and Issue: 4(1), P. 1 - 16

Published: April 5, 2024

Objective. The rapid integration of Generative Artificial Intelligence (AI), especially tools like ChatGPT, into educational sectors has spurred significant academic interest. This review article provides a systematic examination the current scholarly landscape concerning use ChatGPT within higher education. Design/Methodology/Approach. Drawing from range databases between 2022 and 2024, we meticulously adhere to PRISMA guidelines, evaluating final set 28 out 1740 initial articles based on predetermined inclusion exclusion criteria. Results/Discussion. Our analysis reveals diverse global contributions predominantly Asia identifies prevalent quantitative research approach among studies. We delve selected articles' geographical distribution, methodologies, thematic outcomes, highlighting notable lack Latin America. critically assesses validity, utility, time optimization aspects in settings, uncovering positive impact student learning management. However, pinpoint gap rigorous experimental research, underscoring need for studies with random sampling controlled settings enhance external validity findings. Additionally, call attention ethical considerations necessity education institutions adapt teaching methodologies incorporate AI effectively. Conclusion. concludes recommendations future address identified gaps optimize generative technologies ChatGPT.

Language: Английский

Citations

4