0
Article |

The Relationship Between Early Age of Onset of Initial Substance Use and Engaging in Multiple Health Risk Behaviors Among Young Adolescents FREE

Robert H. DuRant, PhD; Jeffrey A. Smith, PhD; Shelley R. Kreiter, MD; Daniel P. Krowchuk, MD
[+] Author Affiliations

From the Department of Pediatrics, Brenner Children's Hospital and the Brenner Center for Child and Adolescent Health, (Drs DuRant, Kreiter, and Krowchuk), and the Department of Psychiatry (Dr Smith), Wake Forest University School of Medicine, Winston-Salem, NC.


Arch Pediatr Adolesc Med. 1999;153(3):286-291. doi:10.1001/archpedi.153.3.286.
Text Size: A A A
Published online

Background  Previous research based on problem-behavior theory has found that early age of onset of substance use is associated with engaging in multiple health risk behaviors among high school students. It is unknown whether these relationships begin during early adolescence.

Objective  To examine the relationships between early age of onset of cigarette, alcohol, marijuana, and cocaine use and engaging in multiple risk behaviors among middle school students.

Methods  A modified version of the Centers for Disease Control and Prevention Youth Risk Behavior Survey was administered to 2227 sixth through eighth grade students attending 53 randomly selected middle schools in North Carolina. A Health Risk Behavior Scale was constructed from 16 behaviors, including indicators of violence and weapon carrying; current substance use; nonuse of helmets when biking, in-line skating or skateboarding; not wearing a seat belt; riding with a driver who had been drinking; and suicide plans. Among this sample of middle school students, the scale had a mean (SD) of 4.1 (2.7) (range=0-15), and had a high internal reliability coefficient (α=0.74). The independent variables included first time use of cigarettes, alcohol, marijuana, and cocaine at age 11 years or earlier; actual age of onset of each substance; race and ethnicity; family composition; sex; school grade; academic ranking; and older age for school grade. These data were analyzed with analysis of variance, Spearman r, and multiple linear regression.

Results  All the independent variables were found to be associated (P<.005) with the Health Risk Behavior Scale during the bivariate analyses. When each of these significant variables were entered into a multiple regression model, having smoked at age 11 years or younger accounted for 21.9% of the variation in the Health Risk Behavior Scale. Male sex, early marijuana or cocaine use, older age, lower academic rank, white race, and living in a 1-parent family explained an additional 19.1% of variation in the model (adjustedR2=0.41, P<.001). When the actual ages of onset of the use of substances were analyzed, in order of magnitude; age of onset of smoking; male sex; age of onset of alcohol and marijuana use; age; lower academic ranking; age of onset of cocaine use; white race; and lower academic rating accounted for 52.8% (P<.001) of the variation in the Health Risk Behavior Scale.

Conclusion  Even when considering sociodemographic factors, early age of onset of cigarette use was the strongest correlate of the number of health risk behaviors in which these young adolescents had engaged. Early onset of use of other substances was also associated with a clustering of health risk behaviors among this sample of middle school students. The findings suggest that screening for early experimentation with tobacco and other substance use will help identify young adolescents at increased risk for engaging in multiple health risk behaviors.

PREVIOUS STUDIES have found that health risk and problem behaviors tend to cluster among adolescents, with the strongest associations occurring between substance use and other health risk behaviors.116 Problem-Behavior Theory provides an explanation for why substance use behaviors cluster with one another and with other health risk behaviors.17,18 First, the social ecology of adolescent life provides socially organized opportunities to learn risk and problem behaviors and normative expectations that they be performed together.17 Second, health risk and problem behaviors cluster because different risk behaviors serve the same social and/or psychological developmental functions for adolescents, such as affirming individuation from parents, trying to achieve adult status, and seeking acceptance from peers. Third, health risk behaviors cluster because they are the manifestations of similar underlying factors.18 In addition, Jessor et al17 have posited that some adolescents develop a "risk behavior syndrome" that is caused by a general latent variable of unconventionality combined with exposure to risk factors from 5 risk domains. The degree of clustering is dependent on the adolescent's exposure to multiple risk domains from 5 broad areas: biological and genetics, social environment, perceived environment, personality, and behavior. Jessor also argues that an early age of onset of health risk behaviors is associated with an increased likelihood that adolescents will engage in multiple risk behaviors as they progress through adolescence.18 In support of this hypothesis, several studies have found that an early age of onset of substance use is associated with engaging in other health risk behaviors during middle and late adolescence5,7,9,15,16; however, it is not known if early age of onset of substance use is associated with engaging in multiple health risk behaviors during early adolescence.

The purpose of our study is to examine the relationships between early age of onset of cigarette, alcohol, marijuana, and cocaine use and engaging in multiple health risk behaviors among middle school students.

SAMPLE

The Centers for Disease Control and Prevention developed the Youth Risk Behavior Survey (YRBS) to assess the prevalence of health risk behaviors among 9th through 12th grade students across the United States. The National YRBS has been approved by the Centers for Disease Control and Prevention Institutional Review Board. The Centers for Disease Control and Prevention considers the state YRBS as surveillance, thus not requiring Institutional Review Board approval. Secondary data analyses of state YRBS data do not need Institutional Review Board approval because the survey is anonymous. In the spring of 1995, a modified and shortened version of the YRBS was administered to 2231 randomly selected sixth though eighth grade students attending 53 randomly selected public middle schools in North Carolina. Within schools, classrooms are randomly selected and all students in the class who were present on the day the YRBS was administered were surveyed. This represented the 463 public middle schools and 261,309 students in the state. The response rate for schools was 74% and the response rate for students was 86%. Student participation was voluntary, and students were assured of anonymity during administration of the survey. Passive parental consent was used for the North Carolina YRBS. Demographic data on age, grade, sex, family type, greater than 1 year older for school grade, and self-report of the academic level of the student are presented in Table 1.

Table Graphic Jump LocationTable 1. Demographic and Descriptive Variables of Middle School Students in North Carolina

Using an approach that we have described previously,15 we constructed a Health Risk Behavior Scale (HRBS) from 16 health risk behaviors. The percentage of students engaging in each of these 16 behaviors is presented in Table 2. An item analysis was conducted to determine the effect of removing any item from the scale on the internal consistency or reliability (Cronbach α) of the scale. All items contributed to the internal reliability of the scale. The scale had a Cronbach α of 0.74, indicating good internal reliability. When the 16 items were divided into 2 scales similar to the clustering of behaviors described by Basen-Engquish et al19 the α levels dropped to an unacceptable level. Complete data were available on 2075 students.

Table Graphic Jump LocationTable 2. Number of Students Engaging in Each Behavior for the Variables Included in the Health Risk Behavior Scale*

The YRBS also measured the age of onset of smoking a whole cigarette, the first drink of alcohol for other than religious reasons, marijuana use, and any form of cocaine use. Each question was measured on 8-point scales ranging from never having used the substance to "15 years or older." The scales were recoded so that "9 years or younger" was coded as a "1" and nonuse was coded as an "8." The age distributions of these 4 variables are presented in Table 3.

Table Graphic Jump LocationTable 3. Age of Onset of Cigarette, Alcohol, Marijuana, and Cocaine Use
STATISTICAL ANALYSIS

Bivariate associations between the HRBS and age of onset of substance use, age, school grade, and type of student were tested using Spearman ρ (r) correlation coefficients. Age of onset of substance use variables were also recoded as age of onset 11 years or younger vs 12 years or older or never used. Age 11 years was chosen because 91.4% of the students were age 12 years or older at the time of the survey. Bivariate analyses of early age of onset of substance use and the HRBS were conducted with analysis of variance tests. Variables significantly (P≤.01) associated with the HRBS and demographic variables were then entered into a stepwise, multiple linear regression model with a forward inclusion of the independent variables. Two regression models were constructed; 1 including early age of onset of substance use and 1 including actual age of onset of substance use.

All analyses were conducted on weighted data. Weighting procedures were to used to correct for the sampling scheme in the data collection. Westat Inc (Rockville, Md) performed the data cleaning and the computation of the weights under contract by the Centers for Disease Control and Prevention. Weighting compensated for nonresponse and reflected the likelihood of sampling each student so the sample represents all middle school students in North Carolina. The weight used for estimation is given by the following: W indicates W1*W2*f1*f2*f3; W1, inverse of the probability of school selection; W2, inverse of the probability of classroom selection; f1, a school-level nonresponse of adjustment factor calculated by school size; f2, a student-level nonresponse adjustment factor calculated by school size; and f3, a poststratification adjustment factor by sex and grade.

Of the 16 variables in the HRBS, middle school students in this sample reported engaging in an average of 4 health risk behaviors (Table 2). The percentage of students who reported engaging in substance use at age 11 years or younger was 45.9% for alcohol, 25% for cigarettes, 5.8% for marijuana, and 1.7% for cocaine (Table 3). Students reporting cigarette, alcohol, marijuana, or cocaine use at age 11 years or younger also reported engaging in a significantly greater number of health risk behaviors than students whose age of onset of these substances was 12 years or older or students who reported never using these substances (Table 4). Higher mean HRBS scores were also found for students whose ages were greater than 1 year older than expected for school grade, not living in a 2-parent home, white, non-Hispanic race, male sex, and in the seventh or eighth grades (Table 4).

Table Graphic Jump LocationTable 4. Analyses of Variance Tests of the Health Risk Behavior Scale*

When each of these variables were entered into a multiple regression model, early age of onset of cigarette use accounted for 21.9% of the variation in the HRBS. Male sex accounted for an additional 8.2% of the variation in the scale when entered as the second variable in the model. Early onset of marijuana use accounted for 5.3% of the variation in the HRBS as the third variable in the model. Age, student type, early onset of cocaine use, minority ethnicity, and living in a 2-parent home accounted for an additional 5.6% of variation in the model, with 41% of the variation in the HRBS being explained by these 8 variables (Table 5).

Table Graphic Jump LocationTable 5. Regression Analyses of the Effects of the Early Age of Onset (≤11 Years of Age) of Substance Use on the Health Risk Behavior Scale

Age of onset of cigarette, alcohol, and marijuana use were moderately inversely correlated with the HRBS (Table 6). Age of onset of cocaine use was weakly inversely correlated with the number of health risk behaviors in which these students reported engaging. When analyzed with linear regression, age of onset of cigarettes use accounted for 32.3% of the variance in the HRBS (Table 7). Male sex and age of onset of alcohol use accounted for 7.6% and 7% of additional variance, respectively, in the scale as the second and third variables in the model. Age of onset of the initial marijuana use accounted for an additional 3.9% of variance as the fourth variable in the model. These 4 variables and age, age of onset of cocaine use, minority ethnicity, and student type accounted for a total of 52.8% of the variance in the HRBS (Table 7).

Table Graphic Jump LocationTable 6. Spearman Correlation Coefficients Between the Health Risk Behavior Scale and Age of Onset of Substance Use and Demographic Variables
Table Graphic Jump LocationTable 7. Regression Analysis of the Associations Between Age of Onset of Substance Use and the Health Risk Behavior Scale

Research has clearly documented that many adolescents in this country are at significant risk for health-compromising problems resulting from early initiation of health risk behaviors. The middle school students in this study reported engaging in 4 health risk behaviors and there was a clustering of health risk behaviors. Similarly, studies of older adolescents have found that health risk behaviors cluster121 and, in some adolescents, the clustering is sufficiently strong to create a "risk behavior syndrome."17,18

Some investigators have questioned the unidimensional clustering of both health risk and problem behaviors and have proposed that the clustering of health risk behaviors may be multidimensional.19 In an analysis of the Texas high school YRBS, Basen-Engquist et al19 found 4 different dimensions to the clustering of health risk behaviors. The first cluster consisted of perceived poor academic performance, no participation in sports, and low fruit and vegetable consumption. The second cluster included injection drug, cocaine, crack, and anabolic steroid use, suicidal behavior, fighting, and carrying a weapon. The third cluster included not participating in aerobic activity and eating a high-fat diet. Unsupervised swimming, using smokeless tobacco, riding a motorcycle without a helmet, and unsafe dieting comprised the fourth cluster. The HRBS, developed for our study, contained many of the behaviors in the second and fourth dimensions of the study by Basen-Engquist et al19; however, an item analysis performed on the HRBS indicated that dividing the 16-item scale into 2 separate scales, similar to the aforementioned dimensions 2 and 4, sharply reduced the internal reliability coefficients. These 16 risk behaviors composed a single dimension for the middle school students in our study.

Although previous research has found strong empirical evidence for a relationship between substance use and other health risk behaviors, the precise sequence of the relationship remains uncertain.7,22,23 Whether tobacco, alcohol, and other substance use is antecedent to or the consequence of other health risk behaviors, or if there is a reciprocal relationship, continues to be debated.7,2427 We found that early age of onset of tobacco, alcohol, and other substance use was associated with engaging in other health risk behaviors during early adolescence. The variable with the strongest association with the number of health risk behaviors that these young adolescents engaged in was onset of cigarette use at 11 years or younger. In addition, students whose age of onset of alcohol and marijuana use was at 11 years or younger also engaged in a greater number of health risk behaviors than has been reported previously.15,916

We also found that actual age of initiation of cigarette, alcohol, marijuana, and cocaine use were all associated with the number of risk behaviors in which these middle school students reported engaging. When these 4 variables were combined with male sex, age, white race, and self-assessment of academic level, 52.8% of the variation was accounted for in the HRBS. Although these results are consistent with previous studies of older adolescents,5,10,15,16 the amount of variation in the scale accounted for by our model is substantially higher than reported in other studies.

These findings should not be interpreted as implying that early onset of substance use causes other risk behaviors among young adolescents; however, it is likely that the same social, psychological, biological, and environmental casual factors responsible for early age of onset of substance use also increase the risk of young adolescents engaging in other health risk behaviors. Similar to the relationship between exposure to violence in the home and in the community and the use of violence by adolescents,28 these social environments provide both modeling and opportunities to engage in multiple health risk behaviors.17,18 Early age of onset of substance use may also contribute more directly to engaging in other health risk behaviors. For example, an adolescent who begins to use marijuana regularly may be rejected by conventional peer groups and increase his or her association with peer groups that approve of marijuana use. Social learning from the new group could result in engaging in other health risk behaviors and a weakening of bonds to conventional groups.20

A limitation of our study is that the YRBS is a cross-sectional survey and causality cannot be implied. We also do not know the validity of the students' responses.7 We adjusted our P value from .05 to .01 to control for the cluster sampling of the YRBS; however, most of the bivariate relationships had P values of .0001 or less.

The findings from this study have several implications for primary health care providers. Screening for substance use is important even as young as 9 years. If tobacco, alcohol, marijuana, or cocaine use are discovered in preadolescents or young adolescents, patients are at an increased risk of engaging in multiple other behaviors that can compromise their health and that these patients are at risk of developing a risk behavior syndrome. Appropriate intervention should not only focus on helping patients discontinue their use of the substance, but also address those factors in children's lives that are associated with the substance use. This often requires the help of mental health care professionals.

The findings from this study also have implications for public health professionals and health educators who are developing and implementing prevention programs. Due to the strength of the associations among the early age of onset of substance use variables and other health risk behaviors among these middle school students, prevention programs should be initiated during elementary school and continued at least through middle school.20,2931 Also, programs should focus on the clustering of health risk behaviors, address multiple risk factors, and incorporate multiple protective factors.17,18,20 Focusing on behaviors, such as violence or weapon carrying, without also addressing other related behaviors, such as substance use, is likely to be less effective than health education or prevention programs that are comprehensive.

Tobacco, alcohol, and other drug use and engaging in other health compromising behaviors remain important public health problems in this country.20 Research is still needed to better understand the causes and prevention of health risk behaviors, particularly of young adolescents. Pediatricians and other health care professionals have a responsibility to advocate for children and adolescents at the local, state, and national levels concerning the prevention of early age of onset of substance use and its association with engaging in other behaviors that threaten the health of our youth. Physicians and other primary health care providers can be instrumental in screening their pediatric and adolescent patients for early substance use and other health risk behaviors and help or refer them to appropriate services that will assist in the discontinuation of behaviors that will compromise their health.

Accepted for publication August 11, 1998.

Presented in part at the Society for Pediatric Research, New Orleans, La, May 3, 1998.

Corresponding author: Robert H. DuRant, PhD, Department of Pediatrics, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 25157-1081 (e-mail: rdurant@wfubmc.edu).

Editor's Note: I guess we can now say that early, early age of onset of substance abuse is associated with engaging in multiple health risk behaviors.—Catherine D. DeAngelis, MD

DuRant  RHRickert  VIAshworth,  CSNewman  CStevens  G Multiple substance use associated with anabolic steroid use among adolescents. N Engl J Med. 1993;329922- 926
Link to Article
DuRant  RHEscobedo  LGHeath  GW The relationship between anabolic steroid use, strength training, and multiple drug use among adolescents in the United States. Pediatrics. 1995;9623- 28
Resnick  MDBearman  PSBlum  RW  et al.  Protecting adolescents from harm. JAMA. 1997;278823- 832
Link to Article
Middleman  ABFaulkner  AHWoods  EREmans  SJDuRant  RH High-risk behaviors among high school students in Massachusetts who use anabolic steroids. Pediatrics. 1995;96268- 272
Spingarn  RWDuRant  RH Male adolescents who cause pregnancy associated health risk and problem behaviors. Pediatrics. 1996;98262- 268
Brener  NDCollins  JL Co-occurrence of health-risk behaviors among adolescents in the United States. J Adolesc Health. 1998;22209- 213
Link to Article
Warren  CWKarrn  LSmall  MLSantelli  JSCollins  JLKalbe  LJ Age of initiating selected health-risk behaviors among high school students in the United States. J Adolesc Health. 1997;21225- 231
Link to Article
DuRant  RHTreiber  FGoodman  EWoods  ER Intentions to use violence to resolve conflict in hypothetical situations among young adolescents. Pediatrics. 1996;981104- 1108
Escobedo  LGReddy  MDuRant  RH Relationship of cigarette smoking to health risk and problem behaviors among US adolescents. Arch Pediatr Adolesc Med. 1997;15166- 71
Link to Article
Shrier  LAEmans  SJWoods  ERDuRant  RH The association of sexual risk behaviors and problem drug behaviors in high school students. J Adolesc Health. 1997;20377- 383
Link to Article
DuRant  RHKahn  JBeckford  PHWoods  ER The association of weapon carrying and fighting on school property and other health risk and problem behaviors among high school students. Arch Pediatr Adolesc Med. 1997;151360- 366
Link to Article
Woods  ERLin  VGMiddleman  ABeckford  PChase  LDuRant  RH The association of suicide attempts with other risk behaviors in adolescents in Massachusetts. Pediatrics. 1997;99791- 796
Link to Article
DuRant  RHKnight  JGoodman  E Factors associated with aggressive and delinquent behaviors among patients attending an adolescent medicine clinic. J Adolesc Health. 1997;21303- 308
Link to Article
Shrier  LAPierce  JDEmans  SJDuRant  RH Gender differences in risk behaviors associated with reported forced sex. Arch Pediatr Adolesc Med. 1998;15257- 63
Garofolo  RWolf  CKessle  SPalfrey  JDuRant  RH The association between health risk behaviors and sexual orientation among a school-based sample of adolescents. Pediatrics. 1998;101895- 902
Link to Article
DuRant  RHKrowchuk  DPSinal  SH The relationship between number of male sexual partners of male adolescents, victimization, use of violence, and drug use at school, and other violence and victimization. J Pediatr. 1998;132113- 118
Jessor  R Risk behavior in adolescence: a psychosocial framework for understanding and action. J Adolesc Health. 1992;21597- 605
Jessor  RDonovan  JECosta  FM Beyond Adolescence: Problem Behavior and Young Adult Development.  New York, NY Cambridge University Press1991;
Basen-Engquist  KEdmundson  EWParcel  GS Structure of health risk behavior among high school students. J Consult Clin Psychol. 1996;64764- 775
Link to Article
DuRant  RHBuchanan  C Tobacco, alcohol and other substance use among children and adolescents. Ripped  JMedTextbook of Medicine, Exercise, Nutrition, and Health. Cambridge, Mass Blackwell ScienceIn press.
Osgood  DWJohnson  LDO'Malley  PMBachman  JG The generality of deviance in late adolescence and early adulthood. Am Soc Rev. 1988;5381- 93
Link to Article
Greenwood  PW Substance abuse problems among high-risk youth and potential interventions. Crime Delinquency. 1992;38444- 458
Link to Article
Harrison  LGfroerer  J The intersection of drug use and criminal behavior. Crime Delinquency. 1992;38422- 443
Link to Article
Ellliott  DSHuizinga  DAgeton  SS Explaining Delinquency and Drug Use.  Beverly Hills, Calif Sage Publications1985;
Gottfredson  MRHirschi  T A General Theory of Crime.  Palo Alto, Calif Stanford University Press1990;
Huizinga  DLoeber  RThornberry  T Urban Delinquency and Substance Abuse: Technical Reports. Vols 1 and 2 Washington, DC Dept of Justice1991;
McCord  J Problem behaviors. Feldman  SSElliott  GRedsAt the Threshold: The Developing Adolescent. Cambridge, Mass Harvard University Press1990;414- 430
DuRant  RHCadenbread  CPendergrast  RASlavens  ALinder  CW Factors associated with the use of violence among black adolescents. Am J Public Health. 1994;84612- 617
Link to Article
Botvin  GJBaker  EBusenbury  LBotvin  EMDiaz  T Long-term follow-up results of a randomized drug abuse prevention trial in a white middle-class population. JAMA. 1995;2731106- 1112
Link to Article
Botvin  GJSchinke  SPEpstein  JADiaz  TBotvin  EM Effectiveness of culturally focused and generic skills training approaches to alcohol and drug abuse prevention among minority adolescents. Psychol Addict Behav. 1995;9183- 194
Link to Article
Botvin  GJSchinke  SPEpstein  JADiaz  T Effectiveness of culturally focused and generic skills training approaches to alcohol and drug abuse prevention among minority youth. Psychol Addict Behav. 1994;8116- 127
Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1. Demographic and Descriptive Variables of Middle School Students in North Carolina
Table Graphic Jump LocationTable 2. Number of Students Engaging in Each Behavior for the Variables Included in the Health Risk Behavior Scale*
Table Graphic Jump LocationTable 3. Age of Onset of Cigarette, Alcohol, Marijuana, and Cocaine Use
Table Graphic Jump LocationTable 4. Analyses of Variance Tests of the Health Risk Behavior Scale*
Table Graphic Jump LocationTable 5. Regression Analyses of the Effects of the Early Age of Onset (≤11 Years of Age) of Substance Use on the Health Risk Behavior Scale
Table Graphic Jump LocationTable 6. Spearman Correlation Coefficients Between the Health Risk Behavior Scale and Age of Onset of Substance Use and Demographic Variables
Table Graphic Jump LocationTable 7. Regression Analysis of the Associations Between Age of Onset of Substance Use and the Health Risk Behavior Scale

References

DuRant  RHRickert  VIAshworth,  CSNewman  CStevens  G Multiple substance use associated with anabolic steroid use among adolescents. N Engl J Med. 1993;329922- 926
Link to Article
DuRant  RHEscobedo  LGHeath  GW The relationship between anabolic steroid use, strength training, and multiple drug use among adolescents in the United States. Pediatrics. 1995;9623- 28
Resnick  MDBearman  PSBlum  RW  et al.  Protecting adolescents from harm. JAMA. 1997;278823- 832
Link to Article
Middleman  ABFaulkner  AHWoods  EREmans  SJDuRant  RH High-risk behaviors among high school students in Massachusetts who use anabolic steroids. Pediatrics. 1995;96268- 272
Spingarn  RWDuRant  RH Male adolescents who cause pregnancy associated health risk and problem behaviors. Pediatrics. 1996;98262- 268
Brener  NDCollins  JL Co-occurrence of health-risk behaviors among adolescents in the United States. J Adolesc Health. 1998;22209- 213
Link to Article
Warren  CWKarrn  LSmall  MLSantelli  JSCollins  JLKalbe  LJ Age of initiating selected health-risk behaviors among high school students in the United States. J Adolesc Health. 1997;21225- 231
Link to Article
DuRant  RHTreiber  FGoodman  EWoods  ER Intentions to use violence to resolve conflict in hypothetical situations among young adolescents. Pediatrics. 1996;981104- 1108
Escobedo  LGReddy  MDuRant  RH Relationship of cigarette smoking to health risk and problem behaviors among US adolescents. Arch Pediatr Adolesc Med. 1997;15166- 71
Link to Article
Shrier  LAEmans  SJWoods  ERDuRant  RH The association of sexual risk behaviors and problem drug behaviors in high school students. J Adolesc Health. 1997;20377- 383
Link to Article
DuRant  RHKahn  JBeckford  PHWoods  ER The association of weapon carrying and fighting on school property and other health risk and problem behaviors among high school students. Arch Pediatr Adolesc Med. 1997;151360- 366
Link to Article
Woods  ERLin  VGMiddleman  ABeckford  PChase  LDuRant  RH The association of suicide attempts with other risk behaviors in adolescents in Massachusetts. Pediatrics. 1997;99791- 796
Link to Article
DuRant  RHKnight  JGoodman  E Factors associated with aggressive and delinquent behaviors among patients attending an adolescent medicine clinic. J Adolesc Health. 1997;21303- 308
Link to Article
Shrier  LAPierce  JDEmans  SJDuRant  RH Gender differences in risk behaviors associated with reported forced sex. Arch Pediatr Adolesc Med. 1998;15257- 63
Garofolo  RWolf  CKessle  SPalfrey  JDuRant  RH The association between health risk behaviors and sexual orientation among a school-based sample of adolescents. Pediatrics. 1998;101895- 902
Link to Article
DuRant  RHKrowchuk  DPSinal  SH The relationship between number of male sexual partners of male adolescents, victimization, use of violence, and drug use at school, and other violence and victimization. J Pediatr. 1998;132113- 118
Jessor  R Risk behavior in adolescence: a psychosocial framework for understanding and action. J Adolesc Health. 1992;21597- 605
Jessor  RDonovan  JECosta  FM Beyond Adolescence: Problem Behavior and Young Adult Development.  New York, NY Cambridge University Press1991;
Basen-Engquist  KEdmundson  EWParcel  GS Structure of health risk behavior among high school students. J Consult Clin Psychol. 1996;64764- 775
Link to Article
DuRant  RHBuchanan  C Tobacco, alcohol and other substance use among children and adolescents. Ripped  JMedTextbook of Medicine, Exercise, Nutrition, and Health. Cambridge, Mass Blackwell ScienceIn press.
Osgood  DWJohnson  LDO'Malley  PMBachman  JG The generality of deviance in late adolescence and early adulthood. Am Soc Rev. 1988;5381- 93
Link to Article
Greenwood  PW Substance abuse problems among high-risk youth and potential interventions. Crime Delinquency. 1992;38444- 458
Link to Article
Harrison  LGfroerer  J The intersection of drug use and criminal behavior. Crime Delinquency. 1992;38422- 443
Link to Article
Ellliott  DSHuizinga  DAgeton  SS Explaining Delinquency and Drug Use.  Beverly Hills, Calif Sage Publications1985;
Gottfredson  MRHirschi  T A General Theory of Crime.  Palo Alto, Calif Stanford University Press1990;
Huizinga  DLoeber  RThornberry  T Urban Delinquency and Substance Abuse: Technical Reports. Vols 1 and 2 Washington, DC Dept of Justice1991;
McCord  J Problem behaviors. Feldman  SSElliott  GRedsAt the Threshold: The Developing Adolescent. Cambridge, Mass Harvard University Press1990;414- 430
DuRant  RHCadenbread  CPendergrast  RASlavens  ALinder  CW Factors associated with the use of violence among black adolescents. Am J Public Health. 1994;84612- 617
Link to Article
Botvin  GJBaker  EBusenbury  LBotvin  EMDiaz  T Long-term follow-up results of a randomized drug abuse prevention trial in a white middle-class population. JAMA. 1995;2731106- 1112
Link to Article
Botvin  GJSchinke  SPEpstein  JADiaz  TBotvin  EM Effectiveness of culturally focused and generic skills training approaches to alcohol and drug abuse prevention among minority adolescents. Psychol Addict Behav. 1995;9183- 194
Link to Article
Botvin  GJSchinke  SPEpstein  JADiaz  T Effectiveness of culturally focused and generic skills training approaches to alcohol and drug abuse prevention among minority youth. Psychol Addict Behav. 1994;8116- 127
Link to Article

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Topics
PubMed Articles