CONSTRUCTING A SAMPLE SELECTION MODEL OF HIGH RISK YOUTH

构建高危青少年样本选择模型

• 批准号: 2013250
• 负责人: JERALD R HERTING
• 金额: $ 7.86万
• 依托单位: BATTELLE CENTERS/PUB HLTH RES & EVALUATN
• 依托单位国家: 美国
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-09-30 至 1998-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2013250
• 关键词: academic achievement; adolescence (12-20); classification; drug abuse; drug abuse information system; gender difference; high risk behavior /lifestyle; human subject; mathematical model; mental disorder diagnosis; mental disorder prevention; model design /development; psychotherapy; racial /ethnic difference; secondary schools; student dropouts; suicide

APPLICANT'S ABSTRACT: The focus of this study is on testing techniques that facilitate the identification of youth at-high risk for drug involvement, school disengagement, and suicide risk behaviors. The proposal addresses a fundamental and pragmatic need to identify accurately high-risk youth for prevention efforts without creating costs of additional data gathering or complicated procedures for screening youth. Developing and testing simple models for accurately and efficiently finding high-risk youth among school populations is a neglected area of study; and yet, this is a critical first step in any preventive intervention research. The research aims are to (1)test an existing high-risk youth selection model currently used to identify youth at-high risk of school failure, and thereby, drug involvement; (2)evaluate alternative models of selection which maximize efficiency of data collection and accuracy of classification; (3)explore the ability of the models to screen for degree of risk; and (4)to test models of selection for specific population subgroups: a)male/female, b)ethnic minorities and c)age-based subgroups (aged 14-15 & 16-18 years). An existing data base will be used for this study; i.e., previously collected data from (five) years of school district records and individual student surveys which contain basic information on drug involvement, school performance, and suicide risk behaviors. Measures of these behaviors have high reliability and validity and form the basis for classifying the student population. The research design calls for splitting the data into subsamples, using part of the data to derive the selection models (primarily based on Classification and Regression Tree, CART, procedures) and, then, using the remaining samples to test the accuracy of the derived models. This design is analagous to typical split-half designs. The CART procedures are specifically designed to (1)find a limited number of classifiers from a larger set of variables and (2)minimize error rates in classification. Variables that were systematically gathered in the school district files will be used as the independent factors or classifiers of the individual cases; these classifiers stand as proxies for well-known risk factors. The expressed interest is to work within an extant dataset typically and systematically available in a school setting to produce a model that accurately selects youth of high-risk status. The value of this study is to test and to identify a simple means for classifying risk status in a typical site for preventive intervention programs, the schools. If such a procedure is successful, the high-risk youth sample selection model will provide a building block in future studies, providing a simple and pragmatic means for : (1) assessing prevalence of risk in school populations; (2) linking high risk youth to interventions and (3) implementing intervention programs across school settings.

申请人摘要： 这项研究的重点是测试技术，促进 识别高危青少年及学校 脱离接触和自杀风险行为。 该提案涉及一个 准确识别高危青少年的基本和实际需要， 在不增加数据收集成本的情况下开展预防工作 或是复杂的青少年筛查程序 开发和测试 准确有效地发现高危青少年的简单模型 这是一个被忽视的研究领域;然而，这是 这是任何预防性干预研究的关键第一步。 本研究的目的是（1）测试现有的高风险青年选择 目前用于确定学业失败风险高的青年的模式， 因此，药物参与;（2）评估替代模型， 最大化的选择 数据收集的效率和分类的准确性;（3）探索 模型筛选风险程度的能力;（4）测试 特定群体亚组的选择模型：a）男性/女性， B）少数民族和c）基于年龄的亚组（14-15岁和16-18岁）。 本研究将使用现有数据库;即，先前 从（五）年的学区记录中收集数据， 载有药物基本资料的个别学生调查 参与，学校表现和自杀风险行为。 措施 这些行为具有较高的信度和效度，并形成了基础 对学生群体进行分类 研究设计要求 将数据分割成子样本，使用部分数据导出 选择模型（主要基于分类和回归树， CART，程序），然后使用剩余的样品测试 衍生模型的准确性。 这种设计类似于典型的 分半设计 CART程序专门设计用于 （1）从一个较大的变量集合中找到有限数量的分类器 和（2）最小化分类中的错误率。 在学区档案中系统收集的变量 将被用作个体的独立因素或分类器 这些分类器代表众所周知的风险因素。 所表达的兴趣是在现有数据集内工作， 系统地在学校环境中提供，以产生一个模型， 准确地选择处于高危状态的青年。 这项研究的价值在于测试和确定一种简单的方法， 对典型场所的风险状况进行分类，以便采取预防性干预措施 项目学校 如果这种手术成功， 青年抽样选择模式将为今后的工作提供基础 研究，提供了一个简单而实用的方法：（1）评估 学校人口中的风险流行率;（2）将高风险青年 干预措施和（3）在整个学校实施干预计划 设置.