Paper
Friday, July 23, 2004
Clusters of Problem Behaviors in Adolescents
Robin Bartlett, PhD, RN, BC, Community Practice Department, University of North Carolina at Greensboro, Greensboro, NC, USA, Diane Holditch-Davis, RN, PhD, School of Nursing, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA, and Michael Belyea, N/A, School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| Learning Objective #1: Identify three clusters of problem behaviors in a sample that is representative of U.S. adolescents |
| Learning Objective #2: Discuss the behaviors for which all U.S. adolescents are at risk |
Objective: Problem behaviors during adolescence can result in morbidity and mortality for the individual, strife for the family, and huge costs to society. The purpose of this study was to determine how problem behaviors cluster within individuals and how stable individual cluster membership was over time. Several demographic factors were also examined for their relationship to the clusters. Concepts: Problem behaviors in adolescents include behaviors that are socially disruptive and distressing to others. Examples of these include stealing, engaging in unprotected sex, running away, alcohol use and marijuana use. Sample: This study is a secondary data analysis of the National Longitudinal Study of Adolescent Health (Add Health). The Add Health study is probability-based and representative of U.S. adolescents, grades 7-12. Two waves of data were available for this analysis so this study has a longitudinal component. Methods: A cluster analytic technique, Ward’s method, was used to identify how the adolescents clustered into groups based on their self-reported problem behaviors. ANOVA and discriminant function analysis were used to aid in understanding, confirming and naming the clusters. Findings: When the 12,617 adolescents were submitted to cluster analysis, 3 clusters were identified, a “normal” behaviors cluster of adolescents reporting few problem behaviors, a “problematic” behaviors cluster whose adolescents reported more problems than those in the “normal” cluster but fewer than those in the third cluster, the “deviant” behaviors cluster. Those in the “deviant” behaviors cluster were distinguished by selling drugs and weapon use. The 3 clusters were stable over time. The “deviant” cluster contained the fewest adolescents and had more males than females. Conclusions: These findings suggest that different adolescents are at risk for different problem behaviors. Although many adolescents report engaging in few, if any problem behaviors, many report alcohol use. Different intervention strategies will be needed to address different problem behaviors.
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July 22-24, 2004