THE RELIABILITY OF A TIMELINE METHOD FOR ASSESSING NORMAL DRINKER COLLEGE-STUDENTS RECENT DRINKING HISTORY - UTILITY FOR ALCOHOL RESEARCH

THE RELIABILITY OF A TIMELINE METHOD FOR ASSESSING NORMAL DRINKER COLLEGE-STUDENTS RECENT DRINKING HISTORY - UTILITY FOR ALCOHOL RESEARCH
复制标题

DOI:
10.1016/0306-4603(86)90040-7
复制
发表时间:
1986-01-01
影响因子:
4.4
通讯作者:
BASIAN, E
BASIAN, E
中科院分区:
医学2区
文献类型:
--
作者:
SOBELL, MB;SOBELL, LC;BASIAN, E

文献摘要

被引文献

相似文献

采用时间轴(TL)方法对40名男女大学生饮酒行为报告的重测信度进行了研究。学生们还完成了一份量-频(QF)问卷(Cahalan,Cisin和Crossley,1969),该问卷通常用于对酒精研究中的受试者饮酒史进行分类。发现TL导出的数据通常具有高可靠性(通常r ≥ 1)。.87),男性和女性,男性具有略高的可靠性整体。根据QF问卷回答,将受试者分为饮酒者类别,并使用TL导出的数据对饮酒的数量、频率和数量X频率(每个饮酒日的平均饮酒次数)进行比较。受试者的饮酒行为(由TL评估)在QF类别中具有很大的变异性,并且由QF方法分类为重度、中度和轻度饮酒者的受试者之间存在广泛的重叠。因此,QF分类提供了一个相对不敏感的措施相比,TL衍生的数据在饮酒行为的个体差异。TL方法也可用于生成各种潜在有用的因变量,而QF方法生成单个变量。
The test-retest reliability of male (n=40) and female (n=40) college students'' reports of recent drinking behavior was evaluated using a timeline (TL) procedure. The students also completed a quantity-frequency (QF) questionnaire (Cahalan, Cisin, and Crossley, 1969) often used to categorize subjects'' drinking histories in alcohol research studies. The TL-derived data were found to have generally high reliability (usually r''s .gtoreq. .87) for both males and females, and males having slightly higher reliabilities overall. Subjects were classified into drinker categories based on the QF questionnaire answers, and the resulting groups were compared using their TL-derived data on quantity, frequency, and quantity X frequency (mean number of drinks per drinking day) measures of drinking. The drinking behavior of subjects (as assessed by the TL) had great variability within the QF categories, and there was extensive overlap between subjects classified by the QF method as heavy, moderate and light drinkers. Thus, QF categorization provides a relatively insensitive measure of individual differences in drinking behavior as compared to TL-derived data. The TL method also can be used to generate a variety of potentially useful dependent variables, whereas the QF method generates a single variable.