DRINK-DRIVING & RISKY DRIVING IN ADOLESCENTS & YOUTH

这项拟议的研究旨在促进对风险的理解 驾驶，包括酒后驾驶和药物驾驶，其中 青少年和青壮年。该计划的主要目标是 研究是为了确定这些行为在多大程度上 反映行为和心理社会的更大生活方式的一部分 传统--非传统。这项研究将建立 酒驾和毒驾在较大范围内的分布 危险驾驶行为的结构，如也遵循 接近、超速和不安全通过；它将决定 这种危险驾驶行为与其他各种行为的关系 问题行为，包括问题饮酒、使用大麻和 其他非法药物和犯罪行为；它将 从总体上考察危险驾驶与饮酒的关系- 驾驶，特别是毒品驾驶，变得常规起来-- 由问题的变量所代表的非常规- 行为理论，以及反映冒险倾向的衡量标准 以及对敌意/攻击性的总体倾向。这项研究 还将考察男女关系中的年龄和性别差异 从酒后驾车和药物驾车到传统的- 不同寻常。 危险驾驶行为、其他问题行为的衡量标准，以及 心理社会常规--非常规将通过以下方式获得 向1350名16岁的科罗拉多州持证司机邮寄了调查问卷- 24.参加者将以分层随机抽样方式选出。 来自科罗拉多州机动车辆分部的技术 全州司机数据库。两个分开但平行的抽样 将使用帧来建立两个完全独立的样本 ，它可用于提供 分析。此外，还将使用正式的司机记录数据 验证自报告驱动数据并作为受抚养人 使用自我报告复制分析的变量。两者都有 数据中将使用单变量和多变量方法 分析，包括相关分析、多元回归 分析、结构方程建模技术和验证性 因子分析。

The proposed study is designed to advance understanding of risky driving, including drink-driving and drug-driving, among adolescents and young adults. The primary objective of the research is to determine the extent to which these behaviors are part of a larger lifestyle reflecting behavioral and psychosocial conventionality-unconventionality. The research will establish the location of drink-driving and drug-driving in the larger structure of risky driving practices, such as following too closely, speeding, and unsafe passing; it will determine the relationship of such risky driving practices to a variety of other problem behaviors, including problem drinking, use of marijuana and other illicit drugs, and delinquent-type behavior; and it will examine the relationship of risky driving in general, and drink- driving and drug-driving in particular, to conventionality-- unconventionality as represented by the variables of Problem- Behavior Theory, and by measures reflecting risk-taking propensity and a general orientation to hostility/aggression. The research will also examine age and gender differences in the relationship of drink-driving and drug-driving to conventionality- unconventionality. Measures of risky driving behavior, other problem behaviors, and psychosocial conventionality-unconventionality will be obtained by questionnaires mailed to 1,350 licensed Colorado drivers aged 16- 24. Participants will be selected by stratified random sampling techniques from the Colorado State Division of Motor Vehicles statewide driver database. Two separate but parallel sampling frames will be used to establish two completely independent samples that can be used to provide replications and confirmations of the analyses. In addition, official driver record data will be used to validate the self-report driving data and to serve as dependent variables to replicate analyses using self-reports. Both univariate and multivariate methods will be used in the data analyses, including correlational analysis, multiple regression analysis, structural equation modeling techniques, and confirmatory factor analysis.