High-risk sexual behaviors of HIV/AIDS and related factors in young students in Guangzhou

Abstract

Objective: To explore high-risk sexual behaviors of HIV/AIDS and related factors in young students in Guangzhou. Methods: A cross-sectional survey was conducted in 5 different types of Guangzhou colleges by convenience sampling with minimum number of classes per grade and 600 samples per school from September to November 2021. The R 4.2.2 software was used to consolidate databases. Simultaneously, a logistic regression model and a decision tree algorithm model, stratifying by whether sexual behaviors had occurred before, were constructed. In each layer, the prediction performance of the two models was evaluated through area under receiver operating characteristic and the confusion matrix, and then the model with high prediction performance was retained. Results: A total of 7 346 students were surveyed. The proportion of the respondents reporting sexual experience were 9.08% (667/7 346), in whom 26.24% (175/667) had risky sexual activity in the past year. The decision tree algorithm model performs well in predicting whether high-risk sexual behaviors have occurred in the past year. When the complexity parameter value is 0.018, and nsplit reaches 4, which means there are 5 leaf nodes in the model, the cross error of the tree will be the smallest. The first best grouping variable in the decision tree was whether to use condoms throughout the first sexual behavior. If condoms were used at their sexual debut, but homosexual practices have occurred in the past year, the probability of risky sexual behavior will increase. If homosexual practices have not occurred in the past year, but the age of sexual debut was below 18 years old while the period of HIV education was after high school, the probability of risk sexual behavior will also increase. Conclusions: AIDS-related risky behaviors of young students still deserved attention. The experience of sexual debut and whether AIDS-related health education has been received before the sexual debut were significant predictors for the occurrence of high-risk sexual behavior. The decision tree algorithm model has particular applicability for predicting and screening potential risk populations.