Impact of Cognitive Load on Clinical Decision-Making in UAE Undergraduate Health Science Students

Clinical training demands integration of theoretical knowledge with practical skills, but high cognitive load may impair decision-making in health science students. Despite its significance, limited research from the United Arab Emirates (UAE) has examined this relationship. This study assessed how cognitive load impacts clinical decision-making among undergraduate health science students.

This cross-sectional study examined 743 undergraduate health science students in United Arab Emirates during February-March 2025. Cognitive load was assessed using the Cognitive Load Scale (CLS), while clinical decision-making skills were measured using the Clinical Decision-Making in Nursing Scale-Patient Version (CDMNS-PT). Data were analyzed using IBM SPSS Statistics (Version 29). Bivariate analyses included Pearson's correlations, independent samples t-tests, and Kruskal-Wallis tests with post-hoc analyses were performed. Regression analysis using generalized linear model (GLM) was employed. A p-value of < 0.05 was considered statistically significant in all the analyses.

Participants reported moderate cognitive load (Intrensic cognitive load: M = 11.50; extraneous cognitive load: M = 11.68) and decision-making skills (M = 124.35), with 90.6% showing low confidence. Females had higher cognitive load (p < .001), but no gender differences in decision-making. Higher extraneous cognitive load (ECL) predicted poorer decision-making (β=-0.19, p < .001), especially in "Search for Alternatives" (r = - .261). Top academically performing students (GPA = 3.1-4.0) scored 3.81 points higher in decision-making (p = .002) with 12-15% lower cognitive load (p < .001). Year 3 students excelled in decision-making (p = .007) and had the lowest cognitive load (p < .001). Pharmacy students outperformed peers (p = .014). Regression analysis confirmed ECL and academic performance as key predictors for clinical decision making (p < .001).

Extraneous cognitive load and academic performance critically influence clinical decision-making skills. Reducing unnecessary cognitive demands and supporting academic performance may enhance competence. Interventions should target at-risk groups (e.g., females, early-year students) to optimize training outcomes.