Determinants of organ donation knowledge and attitudes among university students in Oman: a secondary analysis using logistic regression and machine learning.

Background: Organ donation remains insufficient globally, particularly in settings where sociocultural and religious perceptions shape decisions. This study examined knowledge and attitudes toward organ donation among university students and identified determinants using multivariable logistic regression and machine learning (ML) models. Methods: This secondary cross-sectional study included 2,125 students. Knowledge and attitude scores were dichotomized at a 60% threshold. Variables with Results: Although awareness of organ donation was high (98.5%), only 17.6% demonstrated good knowledge and 28.6% exhibited a high attitude level. Multivariable logistic regression showed that a master's degree was associated with lower odds of good knowledge (OR = 0.39, Conclusion: Despite high awareness, notable gaps remain between knowledge, attitude, and behavioral intention. Logistic regression and ML modeling showed partially overlapping patterns, with both approaches identifying shared determinants of knowledge and attitudes toward organ donation. These findings suggest ML may complement conventional regression by supporting the predictive relevance and interpretability of key behavioral and perceptual factors.