Langan Andrew, Gorzig Marina Mileo
Mathematica, 600 Alexander Park, Suite 100, Princeton, NJ 08540, USA.
Child Youth Serv Rev. 2024 Jan;156. doi: 10.1016/j.childyouth.2023.107247. Epub 2023 Oct 21.
To identify characteristics and behaviors among teenagers that predict sexual initiation or sexual activity and to evaluate alternative methods for predicting sexual behavior among teenagers.
We used longitudinal data from an evaluation of the Making Proud Choices! teen pregnancy prevention program. The evaluation, funded by the Office of Population Affairs, assessed academic years 2016-2017 through 2018-2019 and examined 2,138 Grade 9 and 10 students of all genders. We used ordinary least squares (OLS), least absolute shrinkage and selection operator (lasso), and stratified OLS to identify behaviors and characteristics at baseline that predict sexual initiation, recent sex, and sex without a condom.
OLS and lasso regression show that pre-sexual behaviors and substance use are the most powerful predictors of sexual initiation among teens. Lasso additionally identified higher-order interactions between predictors of sexual activity, including variation in predictors' influence across population subgroups. Stratified OLS regression predicted behavior most accurately for sexual initiation, recent sex, and sex without a condom. However, stratified OLS also reduces the sample size, and therefore precision, for each regression.
Current behavior, not knowledge or beliefs about sex, best predicts future behavior. It can be difficult to evaluate the impact of programs designed to delay sexual initiation among younger adolescents because sexual behaviors often occur at older ages. Our results suggest that pre-sexual behaviors are strongly predictive of subsequent sexual initiation and having sex without a condom, so these could be used as outcome measures for identifying high-risk students or evaluating interventions among younger adolescents. Additionally, our results show that lasso can be a useful technique to identify subgroup differences in the relationship between predictors and future sexual activity and for prioritizing variables to collect in a survey.
确定青少年中预测首次性行为或性活动的特征和行为,并评估预测青少年性行为的替代方法。
我们使用了对“做出自豪选择!”青少年怀孕预防项目评估的纵向数据。该评估由人口事务办公室资助,评估了2016 - 2017学年至2018 - 2019学年,研究了2138名九、十年级的所有性别的学生。我们使用普通最小二乘法(OLS)、最小绝对收缩和选择算子(lasso)以及分层OLS来确定基线时预测首次性行为、近期性行为和无保护性行为的行为和特征。
OLS和lasso回归表明,性前行为和物质使用是青少年首次性行为最有力的预测因素。Lasso还识别了性活动预测因素之间的高阶相互作用,包括预测因素在不同人群亚组中的影响差异。分层OLS回归对首次性行为、近期性行为和无保护性行为的行为预测最为准确。然而,分层OLS也会减少每个回归的样本量,从而降低精度。
当前行为,而非关于性的知识或信念,最能预测未来行为。评估旨在延迟青少年首次性行为的项目影响可能很困难,因为性行为往往发生在年龄较大时。我们的结果表明,性前行为强烈预测随后的首次性行为和无保护性行为,因此这些可作为识别高危学生或评估青少年干预措施的结果指标。此外,我们的结果表明,lasso可作为一种有用的技术,用于识别预测因素与未来性活动之间关系的亚组差异,以及确定调查中要收集的优先变量。