关键词: 艾滋病, 暴露后预防, 青年学生, 随机森林算法, 决策树

Abstract: Objective To analyze the willingness and influencing factors of taking post-exposure prophylaxis （PEP） among young students in Guangzhou. Methods A cross-sectional study was conducted among five universities in Guangzhou from September to November 2021. Using PEP as predictive variable, logistic regression model, Decision Tree algorithm model, as well as Random Forest algorithm model were constructed respectively. ROSE algorithm was used to handle data imbalance problems. Evaluated the predictive performance of the three models through AUC （area under ROC curve） and confusion matrix. Results A total of 7 346 valid questionnaires were collected, during which 67.63% reported ever heard of PEP, 92.49% reported willing to take PEP and 7.51% reported unwilling. Based on the results of the three models, the willingness to take PEP was affected by individual factors （gender, age）, school factors （school type, major）, HIV-related factors （HIV knowledge, testing knowledge, attitude of testing, acceptance period of HIV education, sexual behavior）, and economic conditions etc. The predictive performance AUC （95% CI） for logistic regression, Decision Tree, and Random Forest model were 0.77 （0.75-0.79）, 0.74（0.72-0.76）, and 0.90 （0.89-0.92）, respectively, among which Random Forest algorithm model showed the best prediction than the other two models. Conclusions Knowledge of PEP among young students in Guangzhou still need to be strengthened. The willingness to take PEP is mainly affected by PEP knowledge, individual factors, school factors, HIV-related factors, economic conditions and so on. The Random Forest algorithm model is suitable for predicting the willingness to take PEP among young students.

Key words: AIDS, Post-exposure prophylaxis, Young student, Random Forest algorithm, Decision Tree