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Adolescent At-Risk Behaviors: A Multi-Level Analysis of Family, Neighborhood and School Factors Affecting Adolescent Behavioral Outcomes
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Title
Adolescent At-Risk Behaviors: A Multi-Level Analysis of Family, Neighborhood and
School Factors Affecting Adolescent Behavioral Outcomes
Authors
Andrew A. Beveridge, Queens College and Graduate Center -- CUNY
Sophia Catsambis, Queens College CUNY/ National Center for Education Statistics
A recent focus on possible effects of neighborhood and school on adolescent
outcomes seems warranted, including by our own work (Catsambis and Beveridge, 2001
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, Sampson, et al, 2002.) The addition of students’ residential locations to the
National Educational Longitudinal Survey, 1988 (NELS: 88) data along with demographic (Census) and other variables allow us to nationally assess the extent to which the different spheres of adolescents’ lives affect their behaviors and academic achievements. Preliminary analyses of dropping out of school (Catsambis and Beveridge, 2002) indicate a robust clustering at the neighborhood level. Indeed, the addition of the neighborhood effects reduces and dwarfs any remaining variance among schools. Early dropouts are highly concentrated in neighborhoods with high levels of African Americans, high concentrations of neighborhood disadvantage and high levels of high school dropouts. At the school level, clustering of dropouts is small but schools with high ratios of students to teachers and schools with high levels of absenteeism do contribute to dropping out. The analyses controlled for the likelihood or “propensity” that the respondent lived in neighborhoods with high levels of dropouts.
This paper will generalize that analysis to a larger variety of behavioral outcomes
in the 10
th
grade, such as chronic absenteeism, disengagement from school activities,
disciplinary problems and drug and alcohol use. All of these adolescent behaviors may place adolescents at risk of educational failure. Surprisingly, there seems to be little literature that examines neighborhood level effects for such outcomes. A few scholars have investigated neighborhood effects on adolescent behaviors, such as, dropping out of school (Crane 1991), childbearing (Crane 1991, Sucoff and Upchurch 1998), problem drinking (Cokers and Borders (2001), and adolescent substance abuse (Crum, et al. 1996, Denton and Kampfe 1994, Skager and Fisher 1989, Jang and Johnson 2001). However, a recent review by Sampson, Morenoff and Gannon-Rowley (2002) concludes that little research on neighborhood effects uses multi-level analyses, and especially those that bring to bear non-demographic factors. A recent addition of student residential locations to the National Educational Longitudinal Study of 1988 (NELS) makes such analyses at the national level possible for the first time.
DATA AND METHODS
Out proposed paper uses data from the Base Year and First Follow-Up surveys of
the National Educational Longitudinal Study of 1988(NELS). We have constructed a file from restricted-use data, which consists of 13,547 students from 798 public schools. This sub-sample consists of all cases with valid data from the base year parent, student and school administrator surveys and the first Follow-Up student and school survey. We
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A longer version is available on the web at http://www.csos.jhu.edu/crespar/Reports/report54.pdf
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| | Authors: Beveridge, Andrew. and Catsambis, Sophia. |
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1
Title
Adolescent At-Risk Behaviors: A Multi-Level Analysis of Family, Neighborhood and
School Factors Affecting Adolescent Behavioral Outcomes
Authors
Andrew A. Beveridge, Queens College and Graduate Center -- CUNY
Sophia Catsambis, Queens College CUNY/ National Center for Education Statistics
A recent focus on possible effects of neighborhood and school on adolescent
outcomes seems warranted, including by our own work (Catsambis and Beveridge, 2001
1
, Sampson, et al, 2002.) The addition of students’ residential locations to the
National Educational Longitudinal Survey, 1988 (NELS: 88) data along with demographic (Census) and other variables allow us to nationally assess the extent to which the different spheres of adolescents’ lives affect their behaviors and academic achievements. Preliminary analyses of dropping out of school (Catsambis and Beveridge, 2002) indicate a robust clustering at the neighborhood level. Indeed, the addition of the neighborhood effects reduces and dwarfs any remaining variance among schools. Early dropouts are highly concentrated in neighborhoods with high levels of African Americans, high concentrations of neighborhood disadvantage and high levels of high school dropouts. At the school level, clustering of dropouts is small but schools with high ratios of students to teachers and schools with high levels of absenteeism do contribute to dropping out. The analyses controlled for the likelihood or “propensity” that the respondent lived in neighborhoods with high levels of dropouts.
This paper will generalize that analysis to a larger variety of behavioral outcomes
in the 10
th
grade, such as chronic absenteeism, disengagement from school activities,
disciplinary problems and drug and alcohol use. All of these adolescent behaviors may place adolescents at risk of educational failure. Surprisingly, there seems to be little literature that examines neighborhood level effects for such outcomes. A few scholars have investigated neighborhood effects on adolescent behaviors, such as, dropping out of school (Crane 1991), childbearing (Crane 1991, Sucoff and Upchurch 1998), problem drinking (Cokers and Borders (2001), and adolescent substance abuse (Crum, et al. 1996, Denton and Kampfe 1994, Skager and Fisher 1989, Jang and Johnson 2001). However, a recent review by Sampson, Morenoff and Gannon-Rowley (2002) concludes that little research on neighborhood effects uses multi-level analyses, and especially those that bring to bear non-demographic factors. A recent addition of student residential locations to the National Educational Longitudinal Study of 1988 (NELS) makes such analyses at the national level possible for the first time.
DATA AND METHODS
Out proposed paper uses data from the Base Year and First Follow-Up surveys of
the National Educational Longitudinal Study of 1988(NELS). We have constructed a file from restricted-use data, which consists of 13,547 students from 798 public schools. This sub-sample consists of all cases with valid data from the base year parent, student and school administrator surveys and the first Follow-Up student and school survey. We
1
A longer version is available on the web at http://www.csos.jhu.edu/crespar/Reports/report54.pdf
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