Using neurocognitive profiles and common personality traits to predict academic success in written examination and growth trajectory in undergraduate medical education

Results suggest that identification of at-risk learners can be enhanced by including additional non-academic data, e.g. lower openness to experience. However, at-risk learner performance is difficult to identify solely on individual factors; thus, interventions should be sensitive to situational variation and systemic in nature.