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

• Autores: Cherrez Ojeda, Iván; Gallardo Batidas, Juan C.; Robles Velasco, Karla; Osorio, María Valeria; Vélez León, Eleonor María; Leon Velastegui, Manuel; Pauletto, Patrícia; Aguilar Díaz, F. C.; Squassi, Aldo Fabian; González Eras, Susana Patricia; Cordero Carrasco, Erita; Chavez Gonzalez, Karol Leonor; Calderon, Juan C.; Bousquet, Jean; Bedbrook, Anna; Faytong Haro, Marco
• Año de publicación: 2024
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: artificial intelligence; chatgpt; education; health care
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Background: ChatGPT was not intended for use in health care, but it has potential benefits that depend on end-user understandingand 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, theperceived risks associated with its use, and the ethical issues, as well as attitudes toward the use of ChatGPT in the context ofeducation in the field of health. In addition, we aimed to examine whether there were differences across groups based ondemographic variables. The second part of the study aimed to assess the association between the frequency of use, the level ofperceived 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 assessstatistical significance across different categories. The study used several ordinal logistic regression models to analyze the impactof predictive factors (frequency of use, perception of knowledge, perception of risk, and ethics perception scores) on attitude asthe dependent variable. The models were adjusted for gender, institution type, major, and country. Stata was used to conduct allthe 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 ethicalnor 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 thework easier. In total, 70% (7/10) of people used it for homework. As the perceived knowledge of ChatGPT increased, there wasa stronger tendency with regard to having a favorable attitude toward ChatGPT. Higher ethical consideration perception ratingsincreased 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 extensiveuse in the health field. Our data revealed the positive attitudes toward ChatGPT and the desire to learn more about it. Medicaleducators must explore how chatbots may be included in undergraduate health care education programs.
Fil: Cherrez Ojeda, Iván. Universidad Espiritu Santo; Ecuador. Respiralab Research Group; Ecuador
Fil: Gallardo Batidas, Juan C.. Universidad Católica de Santiago de Guayaquil; Ecuador
Fil: Robles Velasco, Karla. Universidad Espiritu Santo; Ecuador
Fil: Osorio, María Valeria. Universidad de Buenos Aires. Rectorado. Instituto de Investigaciones en Salud Pública; Argentina. Universidad de Buenos Aires. Facultad de Odontología; Argentina
Fil: Vélez León, Eleonor María. Universidad Católica de Cuenca; Ecuador
Fil: Leon Velastegui, Manuel. Universidad Nacional de Chimborazo; Ecuador
Fil: Pauletto, Patrícia. Universidad de Las Américas; Ecuador
Fil: Aguilar Díaz, F. C.. Universidad Nacional Autónoma de México; México
Fil: Squassi, Aldo Fabian. Universidad de Buenos Aires. Facultad de Odontologia. Hospital Odontologico Universitario. Catedra de Odontologia Preventiva y Comunitaria.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: González Eras, Susana Patricia. Universidad Nacional de Loja; Ecuador
Fil: Cordero Carrasco, Erita. Universidad de Chile; Chile
Fil: Chavez Gonzalez, Karol Leonor. Universidad Politécnica Salesiana Sede Guayaquil; Ecuador
Fil: Calderon, Juan C.. Respiralab Research Group; Ecuador. Universidad Espiritu Santo; Ecuador
Fil: Bousquet, Jean. Universität zu Berlin; Alemania. Humboldt-Universität zu Berlin; Alemania
Fil: Bedbrook, Anna. MASK-air; Francia
Fil: Faytong Haro, Marco. Respiralab Research Group; Ecuador. Universidad Estatal de Milagro; Ecuador. Ecuadorian Development Research Lab; Ecuador