• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Scopus
  4. Understanding Health Care Students’ Perceptions, Beliefs, and Attitudes Toward AI-Powered Language Models: Cross-Sectional Study
 
  • Details
  • Full
Options
2024
Journal Article
Title

Understanding Health Care Students’ Perceptions, Beliefs, and Attitudes Toward AI-Powered Language Models: Cross-Sectional Study

Abstract
Background: ChatGPT was not intended for use in health care, but it has potential benefits that depend on end-user understanding and acceptability, which is where health care students become crucial. There is still a limited amount of research in this area. Objective: The primary aim of our study was to assess the frequency of ChatGPT use, the perceived level of knowledge, the perceived risks associated with its use, and the ethical issues, as well as attitudes toward the use of ChatGPT in the context of education in the field of health. In addition, we aimed to examine whether there were differences across groups based on demographic variables. The second part of the study aimed to assess the association between the frequency of use, the level of perceived knowledge, the level of risk perception, and the level of perception of ethics as predictive factors for participants’ attitudes toward the use of ChatGPT.Methods: A cross-sectional survey was conducted from May to June 2023 encompassing students of medicine, nursing, dentistry, nutrition, and laboratory science across the Americas. The study used descriptive analysis, chi-square tests, and ANOVA to assess statistical significance across different categories. The study used several ordinal logistic regression models to analyze the impact of predictive factors (frequency of use, perception of knowledge, perception of risk, and ethics perception scores) on attitude as the dependent variable. The models were adjusted for gender, institution type, major, and country. Stata was used to conduct all the analyses. Results: Of 2661 health care students, 42.99% (n=1144) were unaware of ChatGPT. The median score of knowledge was “minimal” (median 2.00, IQR 1.00-3.00). Most respondents (median 2.61, IQR 2.11-3.11) regarded ChatGPT as neither ethical nor unethical. Most participants (median 3.89, IQR 3.44-4.34) “somewhat agreed” that ChatGPT (1) benefits health care settings, (2) provides trustworthy data, (3) is a helpful tool for clinical and educational medical information access, and (4) makes the work easier. In total, 70% (7/10) of people used it for homework. As the perceived knowledge of ChatGPT increased, there was a stronger tendency with regard to having a favorable attitude toward ChatGPT. Higher ethical consideration perception ratings increased the likelihood of considering ChatGPT as a source of trustworthy health care information (odds ratio [OR] 1.620, 95% CI 1.498-1.752), beneficial in medical issues (OR 1.495, 95% CI 1.452-1.539), and useful for medical literature (OR 1.494, 95% CI 1.426-1.564; P<.001 for all results). Conclusions: Over 40% of American health care students (1144/2661, 42.99%) were unaware of ChatGPT despite its extensive use in the health field. Our data revealed the positive attitudes toward ChatGPT and the desire to learn more about it. Medical educators must explore how chatbots may be included in undergraduate health care education programs.
Author(s)
Chérrez, Ivan
Universidad Espíritu Santo
Gallardo-Bastidas, Juan Carlos
Universidad Catolica de Santiago de Guayaquil
Robles-Velasco, Karla
Universidad Espíritu Santo
Osorio, María F.
Universidad Espíritu Santo
Vélez-León, Eleonor Maria
Universidad Católica de Cuenca
Leon Velastegui, Manuel
Universidad Nacional de Chimborazo
Pauletto, Patrícia
Universidad de las Americas - Ecuador
Aguilar-Díaz, Fatima Del Carmen
Universidad Nacional Autónoma de México
Squassi, Aldo F.
Universidad de Buenos Aires
Gonzalez Eras, Susana Patricia
Universidad Nacional de Loja
Cordero Carrasco, Erita
Universidad de Chile
Chavez Gonzalez, Karol Leonor
Universidad Politécnica Salesiana
Calderón, Juan Carlos
Universidad Espíritu Santo
Bousquet, Jean J.
Fraunhofer-Institut für Translationale Medizin und Pharmakologie ITMP  
Bedbrook, Anna
MASK-air
Faytong-Haro, Marco
Respiralab Research Group
Journal
Jmir Medical Education
Funder
Universidad de Especialidades Espíritu Santo
Open Access
DOI
10.2196/51757
Additional link
Full text
Language
English
Fraunhofer-Institut für Translationale Medizin und Pharmakologie ITMP  
Keyword(s)
  • artificial intelligence

  • ChatGPT

  • education

  • health care

  • students

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024