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153. The Relationship Between School Disengagement And Substance Use Among Summer School Attending Youth: A Latent Class Analysis
... However, the traditional methods cannot obtain the changes of various indicators of obese adolescents before aerobic exercise, which reduces the accuracy of the model. An improved ant colony algorithm was proposed to model the relationship between aerobic exercise and adolescent obesity reduction [9]. ...
In order to solve the relationship between youth aerobic exercise and obesity reduction, an improved ant colony algorithm-oriented aerobic exercise method was proposed. Firstly, the changes in body shape, weight, BMI, body fat, body circumference, and other indicators of obese adolescents before and after aerobic exercise were used as the initial pheromone distribution matrix, and the random evolution factor and evolutionary drift threshold were introduced to establish the target function of reducing obesity caused by aerobic exercise in adolescents. The constraint conditions of the relationship between aerobic exercise and adolescent obesity reduction were explained, and the particle algorithm was introduced to establish the optimal model of aerobic exercise for adolescent obesity reduction. The experimental results show that with the increasing number of experiments, the advantages of this method are more obvious. From the overall level, the average modeling error of this method is about 0.053%, while the average error of the traditional method is about 0.186%, which shows that this method can control the error within a reasonable range, and it is proved that the improved ant colony algorithm can have a good correlation with the method of aerobic exercise.
A number of studies on rural students have addressed the issue of discernible school dropout; however, information on hidden dropout is relatively obscure. To fill this gap, this study examines the data of 2045 rural adolescents (regular students: 1770, hidden dropouts: 275) in Chinese middle schools. This study also theoretically differentiated the two groups via assessing environmental dynamics, including school, parental, and peer factors, in addition to considering the individual. We ascertained that these four domains are significant class disengagement predictors in rural adolescents. However, our results also showed that self-educational expectation, belief in the law, and positive peer relationships lost their correlative power with hidden dropout. In the individual, parental, peer, and school domains, almost all factors were significantly correlated with disengaged hidden dropout. Thus, school maladaptation, father’s alienation, and isolation in interpersonal relationships may be more important for explaining hidden school dropout. Our conclusions also credibly assert that similar analytical predictors could be applied to both actual and hidden school dropouts.
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