Predictors of higher education dropout intention in the post-pandemic era: The mediating role of academic exhaustion - Bárbara Gonzalez; Teresa P. Mendes; Ricardo Pinto; Sónia V. Correia; Sara Albuquerque; Paula Paulino (PLoS ONE, 2025)
Introduction The phenomenon of dropout in higher education needs the acknowledging of its multi-domain complexity. In the post-pandemic era, exhaustion may be a relevant feature affecting students. This cross-sectional study aimed primarily to test a predictive model of five domains of variables (background, academic, social, psychological, and economic) on dropout intention, in a relation mediated by academic exhaustion. Secondarily, it aimed to assess the structural invariance of this model across working status (working vs. non-working students) and residence status (living away from family’s residence vs. living in family residence). If these groups are differently affected by dropout determinants, specific dropout prevention measures should be implemented. Method A stratified sample of 1402 Portuguese university students aged between 19 and 45 years ( M = 22.87, SD = 3.64), selected through a convenience quota method, was assessed for background, academic, social, psychological, and economic variables using self-report instruments. Structural equation modelling was used. Results The predictive model explained 51% of the variance in dropout intention. Academic exhaustion was the stronger predictor (β = 0.523, p < .001), followed by social connecteness to the campus (β = −31, p < .001), vocational difficulties (β = 0.274, p < .001), and course value (β = −0.256, p < .001). Except for the course value, and family educational level, all significant predictors had their effect on dropout intention through academic exhaustion. The model was invariant across working and residence status. Discussion This study shows the relevance of students’ academic exhaustion experiences as a pathway through which different types of factors exert their influence on students´ dropout intentions. The invariance of the predictive model of dropout intention across different groups points the robustness of the model and the relevance of the integrated variables. The results emphasize the importance of student´s individual factors (e.g., academic exhaustion, lack of fit with the course) in dropout decisions, also stressing the role of academic institutions and of the education system in addressing this phenomenon, concerning academic workload, vocational orientation, social environment, and financing.