(1) Background: Research on patterns of risky driving behaviors (RDBs) in adolescents is scarce. This study aims to identify distinctive patterns of RDBs and to explore their characteristics in a representative sample of adolescents. (2) Methods: this is a cross-sectional study of a representative sample of Tuscany Region students aged 14–19 years (n = 2162). The prevalence of 11 RDBs was assessed and a cluster analysis was conducted to identify patterns of RDBs. ANOVA, post hoc pairwise comparisons and multivariate logistic regression models were used to characterize cluster membership. (3) Results: four distinct clusters of drivers were identified based on patterns of RDBs; in particular, two clusters—the Reckless Drivers (11.2%) and the Careless Drivers (21.5%)—showed high-risk patterns of engagement in RDBs. These high-risk clusters exhibited the weakest social bonds, the highest psychological distress, the most frequent participation in health compromising and risky behaviors, and the highest risk of a road traffic accident. (4) Conclusion: findings suggest that it is possible to identify typical profiles of RDBs in adolescents and that risky driving profiles are positively interrelated with other risky behaviors. This clustering suggests the need to develop multicomponent prevention strategies rather than addressing specific RDBs in isolation.

中文翻译：

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青少年驾驶员的危险驾驶行为概况：来自托斯卡纳地区（意大利）的代表性样本的聚类分析

(1) 背景：关于青少年危险驾驶行为 (RDB) 模式的研究很少。本研究旨在确定 RDB 的独特模式，并在具有代表性的青少年样本中探索其特征。(2) 方法：这是对托斯卡纳地区 14-19 岁学生的代表性样本进行的横断面研究（n= 2162）。评估了 11 个 RDB 的流行情况，并进行了聚类分析以确定 RDB 的模式。方差分析、事后成对比较和多元逻辑回归模型用于表征集群成员资格。(3) 结果：根据 RDB 的模式确定了四个不同的驱动程序集群；特别是，鲁莽司机 (11.2%) 和粗心司机 (21.5%) 两个集群显示出参与 RDB 的高风险模式。这些高风险集群表现出最弱的社会联系、最高的心理压力、最频繁地参与危害健康和危险行为以及最高的道路交通事故风险。（4。结论：研究结果表明，可以识别青少年 RDB 的典型特征，并且危险驾驶特征与其他危险行为呈正相关。这种聚类表明需要制定多组件预防策略，而不是孤立地解决特定的 RDB。