German Short Version of the Athlete Burnout Questionnaire – Application of the Ant Colony Optimization Algorithm

Abstract: To address the absence of a validated short form of the German Athlete Burnout Questionnaire, the present study employed an Ant Colony Optimization (ACO) algorithm to create a validated short form of the German Athlete Burnout Questionnaire. Data from 821 competitive athletes from different sports and performance levels ( M _age = 22.24, age range = 16–40; 449 women, 371 men, 1 diverse) were stratified into two samples. The ACO algorithm was applied in Sample 1, and the results were cross-validated in Sample 2 using confirmatory factor analysis. The 6-item solution retained the original three-factor structure, yielded a good model fit in both samples (Sample 1: CFI = 1.000, RMSEA < .001, SRMR = .017; Sample 2: CFI = 1.000, RMSEA = .021, SRMR = .020), and demonstrated significant correlations with stress and life satisfaction. Consequently, the shortened questionnaire represents a psychometrically sound and economic tool for assessing athletic burnout symptoms in research and applied sport psychology.