Sağlık bilimleri lisansüstü öğrencilerinde yapay zekâ kullanımının e-sağlık okuryazarlığına etkisi: GAMLSS yaklaşımı

Abstract

Aim: Postgraduate education in health sciences is of great importance in terms of increasing the quality of health services and training professionals who are experts in their fields. As artificial intelligence technologies gain increasing importance in healthcare, their interaction with e-health literacy becomes highly critical. This study aims to determine the e-health literacy levels of postgraduate students in the field of health sciences and to investigate the complex effects of their use of artificial intelligence applications, such as ChatGPT, on their e-health literacy levels using advanced statistical methods. Methods: In this cross-sectional study, a total of 82 postgraduate students enrolled in all health science-related departments of the graduate school were included. Students' e-health literacy levels were measured using the e-Health Literacy Scale. Comparisons of e-health literacy scores based on artificial intelligence usage habits were examined using univariate statistical analyses, and generalized additive models for location, scale, and shape were applied to analyze more complex effects. Results: All students demonstrated high levels of e-health literacy (30.00; IQR = 5.25). Students who were familiar with artificial intelligence applications used in the healthcare field had significantly higher scores (33.50; IQR = 6.75) compared to those who were not (29.00; IQR = 3.00), and similarly, those who reported using such applications scored higher (32.00;I QR = 7.50) than those who did not (29.00; IQR=5.00) (p0.05). However, the interactions among these variables became statistically significant in the advanced statistical model (p

Ähnliche Arbeiten