Associations among Negative Urgency, Sensation Seeking, Alcohol Use, Self-Esteem, and Casual Sexual Behavior for College Students

Longo, Laura M.; Ertl, Melissa M.; Pazienza, Rena; Agiliga, Alexandra U.; Dillon, Frank R.; Martin, J. C.

doi:10.1080/10826084.2019.1703748

“…Casual sex and sex with multiple partners have also been regarded as RSBs [ 8 - 10 ]. Nearly half of the college students had casual sex experience [ 11 , 12 ], and approximately 50.7% of students were sexually active, with 42.3% of students having multiple sexual partners [ 13 ]. Thus, to help reduce the influence of RSB, it is important to intervene and prevent it among college students by identifying relevant risk factors and making RSB predictions.…”

Section: Introductionmentioning

confidence: 99%

Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China

Li¹,

Zhang²,

Zhao³

et al. 2023

JMIR Public Health Surveill

6

1

0

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Background Risky sexual behavior (RSB), the most direct risk factor for sexually transmitted infections (STIs), is common among college students. Thus, identifying relevant risk factors and predicting RSB are important to intervene and prevent RSB among college students. Objective We aim to establish a predictive model for RSB among college students to facilitate timely intervention and the prevention of RSB to help limit STI contraction. Methods We included a total of 8794 heterosexual Chinese students who self-reported engaging in sexual intercourse from November 2019 to February 2020. We identified RSB among those students and attributed it to 4 dimensions: whether contraception was used, whether the contraceptive method was safe, whether students engaged in casual sex or sex with multiple partners, and integrated RSB (which combined the first 3 dimensions). Overall, 126 predictors were included in this study, including demographic characteristics, daily habits, physical and mental health, relationship status, sexual knowledge, sexual education, sexual attitude, and previous sexual experience. For each type of RSB, we compared 8 machine learning (ML) models: multiple logistic regression (MLR), naive Bayes (BYS), linear discriminant analysis (LDA), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), deep learning (DL), and the ensemble model. The optimal model for both RSB prediction and risk factor identification was selected based on a set of validation indicators. An MLR model was applied to investigate the association between RSB and identified risk factors through ML methods. Results In total, 5328 (60.59%) students were found to have previously engaged in RSB. Among them, 3682 (41.87%) did not use contraception every time they had sexual intercourse, 3602 (40.96%) had previously used an ineffective or unsafe contraceptive method, and 1157 (13.16%) had engaged in casual sex or sex with multiple partners. XGBoost achieved the optimal predictive performance on all 4 types of RSB, with the area under the receiver operator characteristic curve (AUROC) reaching 0.78, 0.72, 0.94, and 0.80 for contraceptive use, safe contraceptive method use, engagement in casual sex or with multiple partners, and integrated RSB, respectively. By ensuring the stability of various validation indicators, the 12 most predictive variables were then selected using XGBoost, including the participants’ relationship status, sexual knowledge, sexual attitude, and previous sexual experience. Through MLR, RSB was found to be significantly associated with less sexual knowledge, more liberal sexual attitudes, single relationship status, and increased sexual experience. Conclusions RSB is prevalent among college students. The XGBoost model is an effective approach to predict RSB and identify corresponding risk factors. This study presented an opportunity to promote sexual and reproductive health through ML models, which can help targeted interventions aimed at different subgroups and the precise surveillance and prevention of RSB among college students through risk probability prediction.

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“…Many studies had reported that nearly half of college students had casual sexual behaviors during the university study [9][10][11], casual sexual behaviors may cause unexpected pregnancy or affect their studies [12,13]. Some studies have carried out researches on the casual sexual behaviors of college students and whether they drink alcohol, and the results found that drinking alcohol may increase the occurrence of casual sexual behaviors to a certain extent [11,14]. With the common occurrence of premarital sex among college students, the age of their first sexual encounter will be earlier, and the proportion of unprotected sexual contact will increase, which will increase the risk and impact of HIV transmission [15].…”

Section: Introductionmentioning

confidence: 99%

Analysis of factors influencing casual sexual behavior among male college students in Zhejiang Province, China

Yang

¹

,

Chen

²

,

Jin

³

et al. 2021

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Objective The purpose of this study was to explore the situations and factors influencing casual sexual behavior among male college students, in order to provide scientific evidences and measures of the prevention and control for HIV/AIDS. Method Using the stratified cluster sampling method, male college students who self-reported sexual behavior were selected as survey subjects in 13 colleges and universities in 11 cities of Zhejiang Province from October to November 2018. We used a custom online questionnaire to collect information on the demographic characteristics, sexual attitudes, sexual behaviors, and HIV interventions of the respondents. The χ2 test was performed on the composition ratios between different groups. With the occurrence of casual sexual behavior as the dependent variable, logistic regression was used to analyze the factors influencing casual male sexual behavior. Results A total of 2734 male college students were surveyed, aged 20.20±1.41 years, of which 595 had casual sex, accounting for 21.7%. The rate of HIV prevention awareness among the participants was 85.1%. Multivariate analysis showed that receiving a self-assessment of HIV risk conducted by the school (Ajusted OR = 1.45, 95% CI = 1.14–1.84), knowing that HIV self-test kits were available at school (Ajusted OR = 2.02, 95% CI = 1.56–2.62), accepting one-night stands (Ajusted OR = 2.82, 95% CI = 2.18–3.66), accepting commercial sex (Ajusted OR = 1.95, 95% CI = 1.53–2.48), being a man who has sex with men (Ajusted OR = 1.81, 95% CI = 1.37–2.39), being a senior (Ajusted OR = 0.46, 95% CI = 0.30–0.71), having knowledge of HIV/AIDS prevention and treatment (Ajusted OR = 0.66, 95% CI = 0.51–0.86), and knowing that the CDC provides HIV testing services (Ajusted OR = 0.56, 95% CI = 0.41–0.77) were factors influencing male college students’ casual sexual behavior. Conclusion Male college students who have causal sexual behaviors have a high degree of openness in sexual attitudes, insufficient knowledge of AIDS prevention, and knowledge of HIV testing-related information but low testing rates. For male college students’ HIV prevention education intervention, it is necessary to emphasize the establishment of correct sexual attitudes and concepts and promote safe sexual behaviors to prevent the spread of HIV.

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“…Commercial sex behavior accounted for 26.42% (112/424) of temporary sex. In recent years, studies have suggested that the incidence of selfreported male sex and commercial sex behavior has been increasing [12,13], suggesting that with the further openness of sexual concepts, college students have a higher incidence of unsafe sex, which poses risk of contracting HIV or STDs.…”

Section: Discussionmentioning

confidence: 99%

Factors Associated with Commercial Sex Behavior among Male College Students Who Engaged in Temporary Heterosexual Behavior in Zhejiang Province, China

Yang

¹

,

Chen

²

,

Ma

³

et al. 2022

BioMed Research International

9

0

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Objective. This study explored the characteristics and associated factors of commercial sex behavior among male college students who engaged in temporary heterosexual behaviors in Zhejiang Province, China. Methods. The participants were male college students with temporary heterosexual behaviors. We developed an online questionnaire to collect information on demographic characteristics, sexual attitudes, sexual behaviors, and HIV/AIDS interventions through stratified cluster sampling. Chi-square ( χ 2 ) tests were performed for the different groups of participants. The occurrence of commercial sex behavior among participants was taken as the dependent variable, and logistic regression was used to analyze the factors associated with the participants’ commercial sex behavior. Results. This study investigated the temporary heterosexual behavior of 424 male college students. Among them were 112 students who reported commercial sex behavior (26.42%), whose average age was 20.25 ± 1.27 years, and whose household registration of Zhejiang Province accounted for 63.39%. The results of the multivariate logistic regression analysis indicated that acceptance of commercial sex behavior (Adjusted (a) OR = 3.53 , 95% CI = 1.94 ~6.40) and feeling at risk of contracting HIV ( aOR = 6.44 , 95% CI = 2.98 ~13.94), seeking temporary sexual partners through the Internet ( aOR = 2.58 , 95% CI = 1.27 ~5.25), consistently using condoms during sex ( aOR = 0.34 , 95% CI = 0.16 ~0.70), or using condoms sometimes/frequently during sex ( aOR = 0.30 , 95% CI = 0.13 ~0.68) were independent factors associated with male college students with temporary heterosexual behavior engaging in commercial sex behavior. Conclusion. Open sexual attitudes, seeking temporary sexual partners through the Internet, high awareness of HIV infection risk, and low condom use are associated factors for male college students engaging in commercial sex behavior. For college students’ HIV/AIDS prevention and education interventions, it is necessary to strengthen the prevention of network influence, increase peer education, increase teacher participation in education, enhance college students’ risk awareness, advocate for the use of condoms, and promote HIV/AIDS prevention and treatment.

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Associations among Negative Urgency, Sensation Seeking, Alcohol Use, Self-Esteem, and Casual Sexual Behavior for College Students

Cited by 11 publications

References 71 publications

Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China

Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China

Analysis of factors influencing casual sexual behavior among male college students in Zhejiang Province, China

Factors Associated with Commercial Sex Behavior among Male College Students Who Engaged in Temporary Heterosexual Behavior in Zhejiang Province, China

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