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Abstract
The aims of this study were i) to analyze and compare the physical self-concept in university students considering possible differences between sexes and associations with socioeconomic status and age, and ii) to generate student profiles using unsupervised machine learning algorithms. A total of 230 Colombian students between 18 and 38 years of age from the Physical Education (n = 118) and Psychology (n = 112) majors participated in this cross-sectional study. The physical self-concept questionnaire (PSQ) was applied. Significant differences were found between men and women. No differences were found in physical self-concept among men in the academic programs; however, women's values were significantly different between the two programs (p< .05). A low inverse association was evident between physical self-concept and socioeconomic stratum and age. Following hierarchical clustering analysis on principal components, two statistically different profiles with large effect sizes were identified (Profile 1 [n = 138] versus Profile 2 [n = 92]; p< .05; η2< .45). Although physical self-concept contributed most to the principal component, with higher values for profile 2, ≈73% of females (n = 101) were clustered in profile 1 and there were a greater number of Psychology (85/112) than Physical Education (27/118) students in profile 2. The results show different behaviors of physical self-concept between men and women in the two academic programs, so the profiles generated could help universities, counselors and professors to plan interventions within the institutions to favor its development while evaluating other potential associations.