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行为风险筛查:在社交、学业和情绪行为风险筛查工具(SAEBRS)中确定高风险临界分数。

Screening for behavioral risk: Identification of high risk cut scores within the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS).

作者信息

Kilgus Stephen P, Taylor Crystal N, von der Embse Nathaniel P

机构信息

Department of Educational, School, and Counseling Psychology, University of Missouri.

Department of Educational and Psychological Studies, University of South Florida.

出版信息

Sch Psychol Q. 2018 Mar;33(1):155-159. doi: 10.1037/spq0000230.

Abstract

The purpose of this study was to support the identification of Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) cut scores that could be used to detect high-risk students. Teachers rated students across two time points (Time 1 n = 1,242 students; Time 2 n = 704) using the SAEBRS and the Behavioral and Emotional Screening System (BESS), the latter of which served as the criterion measure. Exploratory receiver operating characteristic (ROC) curve analyses of Time 1 data detected cut scores evidencing optimal levels of specificity and borderline-to-optimal levels of sensitivity. Cross-validation analyses of Time 2 data confirmed the performance of these cut scores, with all but one scale evidencing similar performance. Findings are considered particularly promising for the SAEBRS Total Behavior scale in detecting high-risk students. (PsycINFO Database Record

摘要

本研究的目的是支持确定社会、学业和情绪行为风险筛查工具(SAEBRS)的临界值,该临界值可用于检测高危学生。教师在两个时间点对学生进行评分(时间1:n = 1242名学生;时间2:n = 704名学生),使用SAEBRS和行为与情绪筛查系统(BESS),后者作为标准测量工具。对时间1数据进行的探索性接受者操作特征(ROC)曲线分析检测到了临界值,这些临界值显示出最佳的特异性水平和接近最佳的敏感性水平。对时间2数据的交叉验证分析证实了这些临界值的性能,除一个量表外,所有量表的表现都相似。研究结果对于SAEBRS总行为量表在检测高危学生方面被认为特别有前景。(PsycINFO数据库记录)

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