| dc.description.abstract | Objective: This study investigated the knowledge, perceptions, attitudes, and
practices (KPAP) regarding Artificial Intelligence (AI) among healthcare
professionals to identify factors influencing technological adoption in clinical
settings.
Methods: A quantitative cross-sectional study was conducted at Bethesda Hospital,
Yogyakarta, involving 118 healthcare providers, including physicians, dentists,
nurses, and pharmacists. Data were collected using a validated online questionnaire.
The instrument’s internal consistency and validity were established through a pilot
study (n=30), utilizing Pearson correlation (r > 0.361) and Cronbach’s Alpha (α >
0.80). Statistical analysis included univariate, bivariate, and multivariate analyses
to determine the predictors of AI integration.
Results: Although the majority of participants demonstrated high knowledge levels
and positive attitudes toward AI, actual clinical utilization remained minimal, with
only 6.78% reporting high usage. Demographic analysis revealed that the 35–49
age cohort was significantly associated with positive perceptions (ρ=0.002) and
attitudes (ρ=0.008), while the nursing profession emerged as a primary factor for
higher practice levels (ρ=0.018). While a significant correlation was found between
knowledge and practice (r=0.199; ρ=0.030), multivariate analysis indicated that
knowledge, perception, and attitude were not statistically significant predictors of
AI practice (p > 0.05), despite positive trends for high knowledge (OR = 1.918) and
positive perception (OR = 2.435).
Conclusions: A distinct "readiness-practice gap" exists where high individual
awareness and positive intent do not effectively translate into clinical application.
This suggests that the successful integration of AI in healthcare settings depends
more heavily on institutional infrastructure and standardized policy frameworks
than on individual professional readiness alone. | en_US |
