Drug Use and Military Plans of High School Seniors

1978 ◽  
Vol 10 (1) ◽  
pp. 65-77
Author(s):  
Patrick M. O'Malley ◽  
Jerald G. Bachman ◽  
Lloyd D. Johnston
Keyword(s):  
High School ◽  
Drug Use ◽  
High School Seniors

DRUG USE DECLINES IN U.S. HIGH SCHOOLS

PEDIATRICS ◽  
1989 ◽  
Vol 84 (4) ◽  
pp. A100-A100
Author(s):  
J. F. L.
Keyword(s):  
High School ◽  
High Schools ◽  
Drug Abuse ◽  
Drug Use ◽  
High School Seniors ◽  
High School Dropouts ◽  
School Dropouts ◽  
Second Year ◽  
High Level ◽  
Very High

The nation's high school seniors are using fewer drugs than any class since 1975, a report from the National Institute on Drug Abuse showed. Researchers said they were particularly encouraged by results showing a drop in cocaine use for the second year in a row, and the beginnings of a reversal in the soaring use of crack, an inexpensive, refined form of cocaine. However, the war against drugs is far from over, with more than half of all students using an illegal substance at least once before graduating, said Charles R. Schuster, NIDA director. Moreover, drug use remains at a very high level among high school dropouts, he said. The survey polled 16,300 high school seniors from 135 schools nationwide.

Using Association Models in Research on Drug Use: Some Examples

1983 ◽  
Vol 13 (4) ◽  
pp. 375-386 ◽  
Author(s):  
Clifford C. Clogg ◽  
James W. Shockey ◽  
Miles D. Harer
Keyword(s):  
High School ◽  
Drug Use ◽  
High School Seniors ◽  
Ordinal Variables ◽  
Association Models ◽  
Single Index ◽  
Cross Classification ◽  
Attitude Toward School ◽  
The Cross

This article shows how association models can be used to guide and simplify analysis of cross-classifications involving ordinal variables. To illustrate, we analyze three crosstables of high school seniors pertaining to the association between certain characteristics (e.g., attitude toward school) and drug use. These models can be used to answer several questions that arise naturally in analyses of such data: 1) Is there association between the variables? 2) If there is association, can it be summarized in terms of a single index, or must a set of indexes be used? 3) How can association be broken up into component sources? 4) Can the ordinal variables be scaled in a meaningful fashion using just the information available in the cross-classification? 5) How can association between two variables be studied in an across-group (e.g., across-time) context?

scholarly journals Adverse psychosocial outcomes associated with drug use among US high school seniors: a comparison of alcohol and marijuana

2014 ◽  
Vol 40 (6) ◽  
pp. 438-446 ◽  
Author(s):  
Joseph J. Palamar ◽  
Michael Fenstermaker ◽  
Dimita Kamboukos ◽  
Danielle C. Ompad ◽  
Charles M. Cleland ◽  
...  
Keyword(s):  
High School ◽  
Drug Use ◽  
High School Seniors ◽  
Psychosocial Outcomes

scholarly journals Unlicensed driving among California high school seniors

2008 ◽  
Vol 6 (2) ◽  
pp. 36-48 ◽  
Author(s):  
Katherine E. Heck ◽  
Carla Sousa ◽  
Christian L. Hanna ◽  
Keith Nathaniel
Keyword(s):  
High School ◽  
Drug Use ◽  
Risk Behaviors ◽  
Motor Vehicle ◽  
High School Seniors ◽  
Excess Risk ◽  
Lower Income ◽  
Driving Behaviors ◽  
Driver's License ◽  
Teenage Drivers

The driving behaviors and characteristics of unlicensed teenage drivers have been little explored. For this study of behaviors of unlicensed California teen drivers, 2,144 high school seniors at 13 school sites in California completed a written survey. Unlicensed driving was ascertained by combining survey questions about licensing and driving. Data were analyzed to examine characteristics of unlicensed drivers compared with licensed drivers, and to examine risk behaviors among the unlicensed drivers. A total of 12.4 percent (n = 265) of students reported driving a motor vehicle without a driver’s license or permit, while two-thirds of surveyed students had either a license or a permit, and the remainder did not drive. Unlicensed drivers were primarily male (56 percent) and Latino (67 percent); unlicensed drivers were more likely than others to attend a school with a lower-income population. Licensed and unlicensed drivers reported similar rates of driving after alcohol or other drug use. Licensed drivers were more likely than unlicensed drivers to report having been in a crash, but this difference was no longer significant after adjustment for risk behaviors. Unlicensed driving was fairly common in this sample, but did not appear to represent an excess risk relative to licensed drivers.

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