Predicting HIV/STD risk level and substance use disorders among incarcerated adolescents.
Incarcerated adolescents are among the most vulnerable groups for
STD infection, and substance abuse is prevalent in over half of this
population. Substance abuse and HIV/STD-associated risk behaviors are
closely linked among juvenile justice-involved youth, but it is unclear
whether common antecedents explain these different problems. The current
study examined predictors of HIV/STD risk level and substance use
disorders, and investigated whether family variables added unique
predictive variance for these problems among incarcerated youth. The
sample included 154 substance-involved youth ages 13 to 17 recruited in
detention facilities in Miami and Tampa, FL and was primarily male (82%)
and African-American (58%). Using a comprehensive assessment strategy
with data obtained from youth report, parent report, and laboratory
confirmed STD testing, the results show that delinquency is a consistent
predictor of both HIV/STD risk level and substance use disorders, and
also that substance use directly predicts HIV/STD risk level among
incarcerated adolescents. Consistent with previous research, family
conflict is an important predictor of substance use disorders even after
controlling for other factors. The results suggest the need for
integrated family-based interventions addressing delinquency, substance
abuse, and HIV/STD-associated risk factors with juvenile
Keywords--adolescents, delinquency, drug abuse, families, HIV risk
Juvenile offenders (Drug use)
Juvenile offenders (Demographic aspects)
HIV infection (Risk factors)
HIV infection (Prevention)
Sexually transmitted diseases (Risk factors)
Sexually transmitted diseases (Prevention)
Drug addicts (Demographic aspects)
Drug addicts (Health aspects)
Rowe, Cynthia L.
Liddle, Howard A.
|Publication:||Name: Journal of Psychoactive Drugs Publisher: Haight-Ashbury Publications Audience: Academic Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2008 Haight-Ashbury Publications ISSN: 0279-1072|
|Issue:||Date: Dec, 2008 Source Volume: 40 Source Issue: 4|
|Product:||Product Code: E199610 Drug Addicts|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
Juvenile justice-involved youth have extraordinarily high rates of
substance abuse and HIV/STD-associated adverse health outcomes not only
during adolescence (CASA 2004) but into adulthood (Keyes, Iacono &
McGue 2007). An estimated 80% of juvenile justice-involved teens report
substance use (CASA 2004) and between 26% and 65% of young arrestees
test positive for drugs using urinalysis (Zhang 2004). Substance-abusing
youths in the juvenile justice system are also at extremely high risk
for acquiring HIV and STDs due to early age at first intercourse,
infrequent use of condoms, permissive attitudes about sex, and low
self-efficacy to practice safe sex (Teplin et al. 2005a; Canterbury et
al. 1995). Incarcerated adolescents represent the largest concentration
of youths infected with or at high risk for HIV and STDs due to drug use
and unsafe sexual behaviors (CDC 1996). Studies show that around 15% to
20% of detained youth test positive for an STD (Crosby et al. 2007;
Kelly et al. 2000), and an alarming 95% of these adolescents have
engaged in three or more HIV-associated risk behaviors (Teplin et al.
2003). When these teens move into adulthood, they carry significantly
elevated risks for chronic drug addiction, HIV infection, mental
illness, poor physical health, and a range of family problems (Golzari,
Hunt & Anoshiravani 2006; Romero et al. 2007). Thus, understanding
and decreasing substance abuse and HIV-associated risk behaviors among
juvenile justice-involved teens are urgent public health, policy, and
research priorities (Butts & Roman 2007; Ziedenberg 2006).
Delinquency, substance use, and high-risk sexual behaviors are often initiated in adolescence and co-occur at high rates (Guo et al. 2002; St. Lawrence et al. 2002). The close associations among these problems have emerged repeatedly in studies across adolescent samples, but are especially pronounced in high-risk subgroups such as runaway and homeless youth, adolescents in drug treatment or suffering from mental disorders, and those in the juvenile justice system (Malow et al. 2006). Many researchers assert that substance use in adolescence directly increases HIV/STD-associated risk behaviors due to impaired judgment, impulsivity, and unprotected sexual activity with multiple partners (Malow et al. 2006; Castrucci & Martin 2002; Devieux et al. 2002). In fact, there is evidence that the presence of substance abuse and conduct problems increases the likelihood of early and risky sexual behaviors (Lowry et al. 1994; Capaldi, Crosby & Stoolmiller 1996). One study showed that alcohol use increased youths' likelihood of engaging in sex by approximately 50% (Sikkema, Winett & Lombard 1995). Sequential analysis suggests that substance use and other problem behaviors precede and may influence the development of sexual risk behaviors (Elliott & Morse 1988). Patterns of risky sexual behavior that emerge in adolescence are particularly likely to persist into adulthood if substance abuse continues (Tapert et al. 2001; Bardone et al. 1998). However, the evidence linking substance use to HIV/STD-associated risk behaviors is not unequivocal; one diary study failed to find an association between event-based substance use and condom use (Bailey, Gao & Clark 2006). DiClemente and Crosby (2003) suggest that substance use and HIV/STD-associated risk factors may be correlated due to common antecedents.
The strong associations between substance use and HIV/ STD-associated risk level seen in juvenile justice-involved samples may also be explained by examining other factors that may predict both types of behaviors. Family context may be a common predictor of substance abuse and HIV/STD risk level. Family factors--including ineffective parental discipline and family conflict (Dishion & Medici-Skaggs 2000), parental permissiveness (Steinberg & Avenevoli 1998), ineffective communication (Guilamo-Ramos et al. 2006), and low levels of family support and control (Brook et al. 2001)--are among the strongest predictors of substance initiation and problem use throughout adolescence. Family factors are also among the strongest protective influences against adolescent problems, and mediate individual and peer risk factors for drinking and drug use (Garnier & Stein 2002). Similarly, there is evidence that family factors are related to adolescents' HIV/STD-associated risk behaviors. Donenberg and colleagues (2006) posit that families influence adolescents' HIV risk in four ways: (a) instrumental characteristics (parental monitoring, control); (b) affective parenting behavior (warmth, support); (c) parental attitudes about sex; and (d) parent-teen communication. Positive and supportive family relationships, effective parenting practices, and communication with parents may reduce HIV/STD-associated risk (Dittus & Jaccard 2000; Perrino et al. 2000). DiClemente and colleagues (2007) call for a more contextual and ecological approach to understanding HIV/STD-risk behaviors in adolescents that goes beyond recognized individual-level predictors. The current study will be among the first to examine the unique predictive role of family factors in HIV/STD risk level with incarcerated adolescents.
Mental health problems may also be a common predictor of both substance use disorders and HIV/STD risk level, and are a core part of the risk and impairment profile of adolescent offenders (Vermeiren, Jespers & Moffitt 2006). In the general population, comorbidity between substance abuse disorders and other psychiatric disorders has been estimated at around 50% (Kessler 2004), yet in the adolescent offender population, comorbidity is more the norm than the exception (Lederman et al. 2004; Teplin et al. 2002). There is also emerging evidence linking mental health symptoms to HIV/STD-associated risk behaviors among juvenile justice-involved youth (Tolou-Shams et al. 2008), particularly negative affect (Lucenko et al. 2003).
While substance abuse and HIV/STD-associated risk behaviors may be explained in part by similar factors, there also appear to be important differences at least in terms of demographic factors in predicting these problem behaviors. For instance, girls tend to have higher risk for HIV/STD infection (DiClemente et al. 2004), whereas boys have traditionally had higher rates of problem substance use (Johnston et al. 2008). In terms of race/ethnicity, African-American and Hispanic adolescents may be at higher risk for HIV/STDs than White non-Hispanic youths (Teplin et al. 2005a), yet research consistently shows that White non-Hispanic youths use substance at higher rates than either African American or Hispanic youths (Hlaing, de la Rosa & Niyonsega 2007). The current research attempts to shed light on the possible shared and unique predictors of HIV/STD-associated risk and substance use disorders among an incarcerated sample of adolescents.
This study tested two critical research questions. First, are there direct relationships among delinquency, substance use and HIV/STD-associated risk behaviors among detained youth? Second, can common antecedents of HIV/STD risk level and substance use disorders (SUDs) be identified, particularly in the family environment? The hypotheses guiding the analyses were that:
1. Delinquency would predict SUDs, and substance use would predict HIV/STD risk level;
2. Predictors of HIV/STD risk level and substance use disorders would vary by gender and ethnicity such that female gender and minority ethnicity would predict HIV/STD risk level and male gender and White non-Hispanic ethnicity would predict SUDs;
3. Mental health problems would predict both problems after adjusting for demographics; and
4. Family factors would add unique predictive variance over demographics in predicting both HIV/STD risk level and substance use disorders.
The study recruited adolescents from two juvenile detention centers in Florida as part of a randomized controlled trial with drug-involved juvenile offenders. Study participants were screened in detention for the following inclusion criteria: (1) ages 13 to 17; (2) self-reported substance use in the 90 days before incarceration; and (3) at least one parent figure willing/able to participate in the study. Adolescents were excluded from the study based on the following criteria: (1) mental retardation/pervasive developmental disorders, psychotic symptoms, or acute suicidality requiring immediate mental health intervention; and (2) high risk to receive immediate long-term residential placement as determined by Department of Juvenile Justice screening instrument (e.g., chronic violent offending, sexual offenses). Ninety one percent of youths and families who were eligible and were invited to participate provided consent/assent for the study.
The sample was 154 primarily male (82%) adolescents, 58% of whom were African-American, 19% White, non-Hispanic, 22% Hispanic, and 1% other. Average age was 15. Over 96% came from single-parent homes with average family income of $15,000. Participants averaged 3.9 lifetime arrests (SD = 3.3), with 2.3 (SD = 2.1) in the last year. They were primarily marijuana users, with 32% meeting DSMIV diagnostic criteria for cannabis dependence and 29% meeting criteria for cannabis abuse (20% had an alcohol use disorder and 10% met criteria for other drug dependence or abuse). Comorbid psychiatric diagnoses were also common: 43% had conduct disorder, 14% had generalized anxiety disorder, 20% had ADHD, and 9% had major depressive disorder.
Participants were recruited from the population of juvenile detainees in the Miami-Dade County and Pinellas County juvenile detention centers between April, 2006 and December, 2007. The research coordinator at each site met daily with detention intake workers to review files of all youths entering detention who would be detained for at least 48 hours (enough time to assess and begin intervention in the randomized trial before detention release). Those deemed to be at imminent risk for long-term placement according to the Florida Department of Juvenile Justice PACT Pre-Screen (Positive Achievement Change Tool; FDJJ 2006-07) were not screened for the study because these youths would most likely be sent to a long-term residential facility directly following release from detention and would not be able to participate in the outpatient clinical phase of the randomized trial. The research coordinators then individually met with potentially eligible teens to screen them to determine substance involvement in the 90 days before their detention stay. Youths ineligible because psychotic symptoms or suicide risk were determined by the PACT Pre-Screen were provided immediate mental health intervention consistent with detention guidelines and practices. The research coordinator asked eligible and interested youths for their permission to contact their parents regarding the study, and set up an interview in the parents' homes to obtain consent. Youths provided informed assent in detention only after parents consented.
Assessments were administered to adolescents in the detention facilities and parents in their homes by trained assessors who were blind to study hypotheses. Assessments were conducted within 48 hours of the youths' entry into detention. Most measures asked about behaviors within the previous 90 days before adolescents were detained, however certain instruments (as indicated below) asked about the entire year since the previous assessment (e.g., psychiatric and substance use diagnoses). Adolescents were tested for STDs immediately upon detention release because FDJJ policies did not allow testing in facilities.
The following measures were collected based on a multimethod, multiperspective measurement strategy that included the use of adolescent report, parent report, and biochemical data.
Parent Interview (CTRADA 1998) gathered information on demographic and background variables, such as the adolescent's age, gender, and ethnicity, and previous arrests.
Substance use was measured using the Timeline Follow-Back Method of Drug and Alcohol Use. The TLFB has been adapted for adolescent samples (Bry & Krinsley 1992; Bry, Conboy & Bisgay 1986), obtaining retrospective reports of daily substance use for specific substances within the previous 90-day period using a calendar and memory prompts to stimulate recall. It yields consistently high test-retest correlations over periods of up to one year (Carey 1997; Maisto & Connors 1992), and been shown to correlate with other self-reports as well as with collateral reports (Sobell & Sobell 1992). The Personal Experience Inventory (PEI; Winters & Henly 1989) is a well-validated self-report measure designed to assess problems associated with adolescent substance use in the previous 90-day period rather than frequency of use. The Personal Involvement with Chemicals Scale in the PEI measures global problem severity in terms of the adolescent's psychological involvement with substances. The Adolescent Diagnostic Interview--Light (Winters & Henly 1993), which has been validated with a range of clinical samples of substance-using teens, was used to determine DSM-IV criteria for substance use disorders in the year prior to detainment.
Delinquency was assessed using the National Youth Survey Self-Report Delinquency Scale (Elliot et al. 1983), measuring criminal behavior for the previous 90-day period using the Total Delinquency Scale. It is a well-validated instrument (Henggeler 1989) with similar juvenile justice-involved samples. In addition, we used the Delinquency Scale of both the Child Behavior Checklist (CBCL), administered to parents, and the Youth Self Report Form (YSR) (Achenbach & Edelbrock 1983). Both have excellent reliability and validity (Kazdin 1990). Parents also reported the number of youths' arrests on the Parent Interview.
STD incidence was determined using laboratory-confirmed biological specimens. Research assistants collected urine screens immediately upon the youths' release from detention. The Becton Dickinson ProbeTec assay was used for the detection of Chlamydia trachomatis and Neisseria gonorrhoeae. Both tests use amplified DNA technology to improve sensitivity and allow detection of these organisms from the urine. Sensitivity in male urine ranges from 93% to 97% and in female urine sensitivity ranges from 80.5% to 84.9%. Specificity in male urine ranges from 95% to 96% and in female urine from 96% to 98%.
HIV/STD-associated risk level was determined using the POSIT HIV/STD Risk Screen. The POSIT HIV/STD Risk Questionnaire was designed to be the first developmentally appropriate HIV/STD-risk screen for use in a wide range of settings (Rahdert & Czechowicz 1995) and has been validated with diverse samples across the country (Rahdert 1997). Additionally, a Timeline Follow Back of Sexual Risk Behaviors determined the extent of risky sexual activity for the 90 days prior to detainment. This method has been adapted to measure many high-risk behaviors among adolescents, including sexual activity (Malow et al. 1998). The TLFB method obtained retrospective reports of sexual activity by using a calendar and other memory prompts to stimulate recall. It gathered daily information on sexual experiences while intoxicated or high and use of condoms.
Mental health problems were measured using the Diagnostic Interview Schedule for Children Predictive Scales (DISC-PS), which identify psychiatric disorders according to DSM-IV criteria. This measure asks about adolescents about their symptoms in the year prior to detainment. It has demonstrated excellent sensitivity and specificity as compared to the full Diagnostic Interview Schedule for Children (sensitivity = .86, specificity = .98; Lucas et al. 2001).
Family functioning was measured using the Family Environment Scale (FES), which has demonstrated adequate psychometric properties in numerous studies (Grotevant & Carlson 1989; Moos & Moos 1986). The Conflict and Cohesion Scales were administered to both the adolescent and parent. Parenting practices were measured using the Behavioral Affect Rating Scale (BARS; Conger et al. 2002), which assesses monitoring, warmth, and hostility between parents and teens. Both measures are well-validated with diverse samples. Teens and parents reported on both measures.
Two dichotomous outcomes were analyzed by using generalized linear model approach. Adolescents were categorized according to HIV/STD risk level (high or low) and substance use disorders (yes or no) respectively.
Adolescents with moderate to high risk as determined by POSIT norms as well as any adolescents testing positive for an STD (11% of sample) were grouped in the HIV/STD high risk outcome group for the regression analyses. The HIV/STD high-risk group comprised 67% (n = 103) of the sample; the group had a mean age of 15.53 years (SD = 1.06), and was 78% male, 20% White non-Hispanic, 53% African American, 26% Hispanic, and 1% other race/ethnicity. The HIV/STD low-risk group had a mean age of 15.21 years, (SD = 1.23) and were 94% male, and 17% White non-Hispanic, 70% African American, and 13% Hispanic.
Adolescents meeting criteria for any alcohol or drug abuse or dependence disorder on the ADI-Light were grouped in the Substance Use Disorder (SUD) group for the regression analyses. The SUD group (yes/no to any SUD) comprised 62% (n = 95) of the sample and were 15.35 (SD = 1.09) average years of age, 79% male, and 30% White non-Hispanic, 47% African American, 22% Hispanic, and 1% other race/ethnicity. The group with no SUDs had a mean age of 15.51 (SD = 1.18), were 90% male, and 3% White non-Hispanic, 75% African American, and 22% Hispanic.
Logistic regression analysis was used to test the significance of the risk factors in predicting the two outcomes: HIV/STD risk level and SUDs. For each outcome, the analyses proceeded in a series of three steps. First, all of the demographic variables (age, gender, and ethnicity) were entered into the logistic regression to control for any differences in outcome that might be attributable to participant characteristics. Next, each potential risk predictor was entered into the model, one at a time (17 total variables to predict HIV/STD risk level and 18 variables to predict SUDs). Variables examined as potential predictors of both HIV/STD risk level and SUD included total number of arrests (Parent Interview), total delinquency (NYS), parent- and youth-reported delinquency (CBCL and YSR), parent- and youth-reported cohesion and conflict (FES), parent- and youth-reported monitoring, warmth, and hostility (BARS), and number of psychiatric diagnoses (DISC-PS). Additionally, days used alcohol or other drugs in the previous 90 (TLFB) and psychological involvement with substances (PEI) were added to the models predicting HIV/STD risk level. Number of sexual encounters while drunk/high and proportion of protected sexual acts (TLFB of Sexual Risk Behaviors) and total HIV/STD risk score (POSIT) were added to the models predicting SUDs. In this way, it was possible to measure the total variance associated with each predictor after controlling for demographic variables. At the final step, all of the predictors that were at least marginally significant (p < .10) earlier, when entered into the model univariately, were entered simultaneously into the model. This final multivariate predictor model provided estimates of the unique variance associated with each factor after adjusting for the variance accounted for by all factors. The stepwise model selection method was used and we only reported the final model.
Predicting HIV/STD High Risk Level
Demographic predictors. From the demographic only model, we found that age, gender, and race\ethnicity were all significant predictors of HIV/STD risk level. Older adolescents were at higher risk ([beta] = 0.34, p < .05) as were females ([beta] = -1.74, p < .01). With regard to race/ethnicity, Hispanic adolescents had higher HIV/STD risk level than African Americans ([beta] = 1.14, p < .05), but neither group differed significantly from non-Hispanic White adolescents (p > .05).
HIV/STD risk level predictors. When the 17 separate predictors for HIV/STD risk level were added to the model univariately (after controlling for demographic variables), five predictors were found to be significant. Three of the predictors were delinquency variables (total delinquency from the NYS and delinquency scale scores from both the CBCL and the YSR). The other two significant predictors were two different measures of substance use (number of days used alcohol or other drugs in the past 90 from the TLFB and psychological involvement with substances from the PEI). We present two multivariate models in Tables 1 and 2. Table 1 contains all of the predictors that were significant after controlling for demographic variables when entered into the model univariately. Table 2 lists only significant predictors after a step-wise model selection procedure (total delinquency from the NYS and delinquency scale scores from the CBCL). In both models, the demographics were retained.
Predicting Substance Use Disorders
Demographic predictors. Among the demographic variables entered into the model initially, only race/ethnicity was a significant predictor. White non-Hispanic adolescents had a significantly higher SUD rate than did African American or Hispanic adolescents ([beta] = 2.62, p < .001; [beta] = 2.09, p < .012). Although the rate for Hispanic adolescents was somewhat higher than for African Americans, the difference was not significant (p > .19). Age and gender did not significantly predict SUDs.
SUD predictors. At the next step, each of the 18 risk factors was added to the logistic model. Four of the variables were significantly associated with SUDs. Two of the four predictors were measures of adolescent delinquent behavior (total delinquency from the NYS and the delinquency scale scores from the YSR) and one was a measure of psychiatric comorbidity (number of psychiatric disorders). Adolescent-reported family conflict from the FES was also a significant predictor. We presented two multivariate models in Tables 3 and 4 below. Table 3 contains all of the predictors that were at least marginally significant (p < .10) when entered into the model univariately, and Table 4 presents only significant predictors after a step-wise model selection procedure (total delinquency and adolescent-reported family conflict). In both models, the demographics were retained.
These results uncover new and clinically important findings regarding the unique and shared predictors of substance use disorders and HIV/STD risk level among incarcerated adolescents. First, as hypothesized, delinquency was a predictor of substance use disorders. While the role of delinquency in predicting substance abuse has been well established (Dierker et al. 2007; Becker & Grilo 2006), the strength of delinquency in predicting HIV/STD risk level is somewhat unexpected. In fact, self-reported delinquency was the only consistent predictor of both HIV/STD risk level and SUDs in this study. It remained a significant predictor of both outcomes after accounting for the variance of all other variables in the final multivariate model. There are few published studies that have linked specific indicators of delinquency directly to high-risk sexual behaviors. One study examining arrest histories with a community-based sample (Tolou-Shams et al. 2007), a second study of multiple admissions in a detained sample (Harwell et al. 1999), and a third study of psychopathy with a juvenile justice-involved sample (Malow et al. 2007) linked these indicators of delinquency to high-risk sexual behaviors, including earlier initiation of sex, unprotected sex acts, sex while drunk or high, STDs, less favorable attitudes towards condoms and safer sex practices, and less favorable intentions to practice safer sex. These findings suggest that interventions to reduce HIV/STD risk and substance abuse must be comprehensive enough to address the delinquent behaviors that are so closely linked to substance abuse and HIV/STD-associated risk behaviors among juvenile justice-involved adolescents.
Substance abuse also predicted HIV/STD risk level after adjusting for demographic variables (frequency of use and psychological involvement with substances), although in the final multivariate model, delinquency was the only variable that contributed unique variance to HIV/STD risk level. The direct link between substance abuse and HIV/STD-associated risk behaviors shown in this study is supported by an impressive body of evidence with community, clinical, and juvenile justice samples. Both marijuana (Kingree, Braithwaite & Woodring 2000) and alcohol use (Malow et al. 2006) have been linked to a range of high-risk sexual behaviors among youths, including unprotected sex and multiple sex partners.
The results also shed light on the subgroups most vulnerable for each outcome. As hypothesized based on previous research, HIV/STD risk level was predicted by female gender. Research has consistently shown that female adolescents are more susceptible to HIV and STD infection than males even at lower levels of other problem behaviors and known HIV/STD-associated risk behaviors (Halpern et al. 2004; DiClemente & Crosby 2003; Canterbury et al. 1995). Older age was also a significant predictor, consistent with findings from other high-risk samples (Fisher et al. 2008). In terms of ethnicity, Hispanic ethnicity was a predictor of HIV/STD risk level in comparison to African-American ethnicity, consistent with results of research with a similar sample in the same geographic region (Devieux et al. 2005). Contrary to hypotheses, however, neither minority group had significantly elevated risk compared to White non-Hispanic youth. This contradicts research showing that White non-Hispanics and African Americans had higher HIV/STD risk relative to Hispanic teens in Florida (Hlaing, de la Rosa & Niyonsenga 2007), and that African-American youths were at highest risk for HIV and STDs using nationally representative data (Halpern et al. 2004). There is a large body of research documenting health disparities in terms of higher rates of STDs among African-American youths even at lower levels of other well-established risk factors (DiClemente & Crosby 2003). Demographic variables were not strongly predictive of SUDs; only ethnicity (White non-Hispanic ethnicity) was significantly related to SUD status, yet this was in the expected direction and consistent with previous research (Hlaing, de la Rosa & Niyonsenga 2007).
Mental health problems were also investigated as common antecedents of both HIV/STD risk level and SUDs. Mental health problems were predictors of SUDs after adjusting for demographic variables, yet in the final multivariate model did not contribute unique variance to SUDs. Mental health problems have been strongly linked to SUDs in a host of other research studies with community, clinical, and criminal justice samples with adults and adolescents (Cocozza & Skowyra 2000; Leshner 1997). The limited predictive relationship between mental health problems and HIV/STD risk level can be reconciled with previous research findings that show substance abuse to be a stronger determinant of sexual risk taking than mental health problems. Teplin and colleagues (2005a) showed that among juvenile detainees, the presence of mental disorders did not substantially increase HIV/STD-associated risk levels; in fact, the group of detainees with SUDs and comorbid mental health problems had similar patterns of sexual risk behaviors as compared to the SUD-only group. Similarly, Deas-Nesmith and colleagues (1999) demonstrated that the "knowledge-behavior gap" (the dissonance between what is known about HIV/AIDS and the extent of sexual risk taking) was largest in youths with SUDs, whereas adolescents with psychiatric disorders were not significantly different from community controls.
This study examined several aspects of family relationships as potential predictors of HIV/STD risk level and SUDs, including overall family environment variables of cohesion and conflict, as well as specific parent-adolescent relationship dimensions of hostility and warmth, and parental monitoring. Consistent with previous research, the findings support the important role of family environment in adolescents' substance abuse, particularly family conflict as perceived by the adolescent. Adolescents' reports of family conflict contributed unique predictive variance to SUDs after controlling for demographics and all other factors. Similarly, family conflict (Dishion & Medici-Skaggs 2000) and low levels of family support (van der Vorst et al. 2006) are reliable predictors of adolescent delinquency and substance abuse across clinical, community, and juvenile justice samples. While these family variables were not significant predictors of HIV/STD risk level, it is possible that other family factors not measured in this study but linked to HIV/ STD-associated risk behaviors in large-scale school samples, particularly parent-adolescent communication (Dilorio et al. 2003; DiClemente & Crosby 2003), maternal education level (Dye & Upchurch 2006), and parents' self-efficacy and risk behaviors (Wilder & Watt 2002) might have a more direct impact on sexual risk taking.
Certain limitations in the current study need to be acknowledged. First, the study relied on teens' self-reports of substance use. The case could be made that since these adolescents were involved with the courts, they might have been less than candid about their drug and antisocial activities. At the same time, self reports remain a standard and accepted way of collecting treatment outcome data, particularly the Time Line Follow Back (TLFB; Fals-Stewart et al. 2000). In addition, the conditions designed to maximize response accuracy were incorporated into the study's methodology. Data were collected by trained research staff independent and separate from detention personnel and teens were made aware that their responses constituted privileged information and would not be shared with parents or juvenile justice authorities.
A second limitation concerns generalizability. Our sample was incarcerated, low-income and urban, composed of primarily males from ethnic minorities. Thus, it is not known whether the results would generalize to adolescents in the community with other demographic characteristics. The sample was also recruited for a randomized clinical trial in which youths and parents were willing to participate in ongoing research and assessment, thus it is possible that adolescents with no motivation for treatment would show different risk profiles. These results need to be replicated with other populations, and with larger samples.
The study has several strengths that give confidence to the validity of the findings. The study used standardized assessments tapping different symptom and prosocial domains of functioning with different respondents, and supported STD/HIV risk profiles with biological confirmation of STD infection. Because neither self report nor biological measures can wholly substitute for the other, we combined them to assess HIV/STD risk level in a reliable and valid way (Fishbein & Pequegnat 2000). While this type of correlational research does not lend itself to making causal relationships about the risk factors for either HIV/STD or substance use disorders (Leigh & Stall 1993), these findings shed new light on unique and common antecedents for these problems among juvenile justice-involved adolescents.
The clinical implications of these findings are clear: interventions for youths in the juvenile justice system must comprehensively target HIV/STD-associated risk factors, substance abuse, and delinquency. In the substance abuse and delinquency fields, family-based interventions have shown impressive results in significantly reducing drug use, criminal behavior, and mental health problems (Liddle et al. In press, 2001; Henggeler, Pickrel & Brondino 1999), and decreasing recidivism not only in the short-term but over many years (Schaeffer & Borduin 2005). However, effective interventions that systematically and concurrently target the interrelated problem areas of substance abuse, delinquency, and HIV/STD risk with adolescents in the juvenile justice system are nonexistent. Rigorous study of HIV prevention for juvenile offenders lags far behind research with other samples (DiClemente, Salazar & Crosby 2007). Even with lower-risk adolescent samples, existing evidence-based HIV prevention approaches are generally delivered in a group format with little attention to contextual or systems factors (Malow et al. 2007). In clinical practice, intervention programs typically target "individual" problem areas separately, perpetuating well-documented problems of service fragmentation in juvenile justice, addictions, and health systems (IOM 2006). Given the empirically established interdependence of shared risk factors for HIV-associated sexual behaviors, substance abuse, and delinquency (Donenberg, Paikoff & Pequenat 2006; McClelland et al. 2002), the need for effective and efficient service delivery systems that can deliver comprehensive interventions targeting all of these problems with juvenile offenders is an urgent public health and research priority (DiClemente, Salazar & Crosby 2007; Teplin et al. 2005b).
Achenbach, T.M. & Edelbrock, C. 1983. Manual for the Child Behavior Checklist and Revised Child Behavior Profile. Burlington, VT: University of Vermont Department of Psychiatry.
Bailey S.L.; Gao, W. & Clark D.B. 2006. Diary study of substance use and unsafe sex among adolescents with substance use disorders. Journal of Adolescent Health 38 (3): 13-20.
Bardone, A.M.; Moffitt, T.E.; Caspi, A.; Dickson, N.; Stanton, W.R. & Silva, P.A. 1998. Adult physical health outcomes of adolescent girls with conduct disorder, depression, and anxiety. Journal of the American Academy of Child & Adolescent Psychiatry 37 (6): 594-601.
Becker, D.F. & Grilo, C.M. 2006. Prediction of drug and alcohol abuse in hospitalized adolescents: Comparisons by gender and substance type.
Behaviour Research and Therapy 44 (10): 1431-40. Brook, J.S.; Brook, D.W.; De la Rosa, M.; Whiteman, M.; Johnson, E. & Montoya, I. 2001. Adolescent illegal drug use: The impact of personality, family, and environmental factors. Journal of Behavioral Medicine 24: 183--203.
Bry, B.H. & Krinsley, K.E. 1992. Booster sessions and long-term effects of behavioral family therapy on adolescent substance use and school performance. Journal of Behavior Therapy and Experimental Psychiatry 23 (3): 183-89.
Bry, B.H.; Conboy, C. & Bisgay, K., 1986. Decreasing adolescent drug use and school failure: Long-term effects of targeted family problem-solving training. Child and Family Behavior Therapy 8: 43--59.
Butts, J.A. & Roman, J. 2007. Changing Systems: Outcomes from the RWJF Reclaiming Futures Initiative on Juvenile Justice and Substance Abuse. A Reclaiming Futures National Evaluation Report. Portland, OR: Reclaiming Futures National Program Office, Portland State University.
Canterbury, R.J.; McGarvey, E.L.; Sheldon-Keller, A.E.; Waite, D.; Reams, P. & Koopman, C. 1995. Prevalence of HIV-related risk behaviors and STDs among incarcerated adolescents. Journal of Adolescent Health 17 (3): 173-77.
Capaldi, D.M.; Crosby, L. & Stoolmiller, M. 1996. Predicting the timing of first sexual intercourse for at-risk adolescent males. Child Development 67 (2): 344-59.
Carey, K.B. 1997. Reliability and validity of the Time-Line Follow-Back Interview among psychiatric outpatients: A preliminary report. Psychology of Addictive Behaviors 11 (1): 26-33.
CASA. 2004. Criminal Neglect: Substance Abuse, Juvenile Justice and the Children Left Behind. New York: The National Center on Addiction and Substance Abuse at Columbia University.
Castrucci, B.C. & Martin, S.L. 2002. The association between substance use and risky sexual behaviors among incarcerated adolescents. Maternal and Child Health Journal 6 (1): 43-47.
Center for Treatment Research on Adolescent Drug Abuse (CTRADA). 1998. Parent and Adolescent Interview. Miami, FL: University of Miami.
Centers for Disease Control and Prevention (CDC). 1996. HIV/AIDS education and prevention programs for adults in prisons and jails and juveniles in confinement and facilities--United States, 1994. Morbidity and Mortality Weekly Report 45 (13): 268-71.
Cocozza, J. & Skowyra, K. 2000. Youth with mental health disorders: Issues and emerging responses. Juvenile Justice and Delinquency Prevention 7 (1): 3-13.
Conger, R.D.; McLoyd, V.C.; Wallace, L.E.; Sun, Y.; Simons, R.L. & Grody, G.H. 2002. Economic pressure in African American families: A replication and extension of the Family Stress Model. Developmental Psychology 38: 179-93.
Crosby, R.A.; Salazar, L.F.; DiClemente, R.J.; Yarber, W.L.; Caliendo, A.L. & Staples-Horne, M. 2007. Condom misuse among adjudicated girls: Associations with laboratory-confirmed chlamydia and gonorrhea. Journal of Pediatric and Adolescent Gynecology 20 (6): 339-43.
Deas-Nesmith, D.; Brady, K T.; White, R. & Campbell, S. 1999. HIV-risk behaviors in adolescent substance abusers. Journal of Substance Abuse Treatment 16 (2): 169-72.
Devieux, J.; Malow, R.; Ergon-Perez, E.; Samuels, D.; Rojas, P.; Khushal, S.R. & Jean-Gilles, M. 2005. A comparison of African American and Cuban American adolescent juvenile offenders: Risky sexual and drug use behaviors. Journal of Social Work Practice in the Addictions 5 (1-2): 69-83.
Devieux, J.; Malow, R.; Stein, J.A.; Jennings, T.E.; Lucenko, B.A.; Averhart, C. & Kalichman, S. 2002. Impulsivity and HIV risk among adjudicated alcohol and other drug-abusing adolescent offenders. AIDS Education & Prevention 14 (5 Suppl B): 24-35.
DiClemente, R.J. & Crosby, R. 2003. Sexually transmitted diseases among adolescents: Risk factors, antecedents and prevention strategies. In: G. Adams & M. Berzonsky (Eds.) The Blackwell Handbook of Adolescence. Oxford, UK: Blackwell Publishers, Ltd.
DiClemente, R.J.; Salazar, L.F. & Crosby, R.A. 2007. A review of STD/ HIV preventive interventions for adolescents: Sustaining effects using an ecological approach. Journal of Pediatric Psychology 32 (8): 888--906.
DiClemente, R.J.; Wingood, G.M.; Harrington, K.F.; Lang, D.L.; Davis, S.L. & Hook, E.W. 2004. Efficacy of an HIV prevention intervention for African American adolescent girls: A randomized controlled trial. Journal of the American Medical Association 292: 171-79.
Dierker, L.C.; Donny, E.; Tiffany, S.; Colby, S.M.; Perrine, N. & Clayton, R.R. 2007. The association between cigarette smoking and DSM-IV nicotine dependence among first year college students. Drug and Alcohol Dependence 86: 106--14.
Dilorio, C.; Pluhar, E. & Belcher, L. 2003. Parent-child communication about sexuality: A review of the literature from 1980-2002. Journal of HIV/AIDS Prevention & Education Adolescents & Children 5 (3/4): 7-32.
Dishion, T.J. & Medici-Skaggs, N. 2000. An ecological analysis of monthly "bursts" in early adolescent substance use. Applied Developmental Science 4 (2): 89-97.
Dittus, P. & Jaccard, J. 2000. The relationship of adolescent perceptions of maternal disapproval of sex and of the mother-adolescent relationship to sexual outcomes. Journal of Adolescent Health 26: 268-78.
Donenberg, G.R.; Paikoff, R. & Pequenat, W. 2006. Introduction to the special section of families, youth, and HIV: Family-based intervention studies. Journal of Pediatric Psychology 31 (9): 869-73.
Dye, C. & Upchurch, D.M. 2006. Moderating effects of gender on alcohol use: Implications for condom use at first intercourse, Journal of School Health 76 (3): 111-16.
Elliott, D.S.; Ageton, S.S.; Huizinga, D.; Knowles, B.A. & Cantor, R.J. 1983. The Prevalence and Incidence of Delinquent Behavior: 1976-1980. NYS Report 26. Boulder, CO: Behavioral Research Institute.
Elliott, D.S. & Morse, B. 1988. Delinquency and Drug Use as Risk Factors in Teenage Sexual Activity and Pregnancy. Boulder, CO: Institute of Behavioral Science, University of Colorado.
Fals-Stewart, W.; O'Farrell, T.J.; Freitas, T.T.; McFarlin, S.K. & Rutigliano, P. 2000. The Timeline Followback reports of psychoactive substance use by drug-abusing patients: Psychometric properties. Journal of Consulting & Clinical Psychology 68: 134-44.
Fishbein, M. & Pequegnat, W. 2000. Evaluating AIDS prevention interventions using behavioral and biological outcome measures. Sexually Transmitted Diseases 27 (2): 101-10.
Fisher, H.H.; Eke, A.N.; Cance, J.D.; Hawkins, S.R. & Lam, W.K.K. 2008. Correlates of HIV-related risk behaviors in African American adolescents from substance-using families: Patterns of adolescent-level factors associated with sexual experience and substance use. Journal of Adolescent
Health 42 (2): 161-69.
Florida Department of Juvenile Justice (FDJJ). 2006-07. Positive Achievement Change Tool (PACT). FDJJ Office of Probation and Community Intervention.
Garnier, H.E. & Stein, J.A. 2002. An 18-year model of family and peer effects on adolescent drug use and delinquency. Journal of Youth and Adolescence 31: 45-56.
Golzari, M.; Hunt, S.J. & Anoshiravani, A. 2006. The health status of youth in juvenile detention facilities. Journal of Adolescent Health 38 (6): 776-82.
Grotevant, H.D. & Carlson, C.I. 1989. Family Assessment: A Guide to Methods and Measures. New York: Guilford Press.
Guilamo-Ramos, V.; Jaccard, J.; Turrisi, R.; Johannson, M. & Bouris, A. 2006. Maternal perceptions of alcohol use by adolescents who drink alcohol. Journal of Studies on Alcohol 57 (5): 730-37.
Guo, J.; Chung, I.J.; Hill, K.G.; Hawkins, J.D.; Catalano, R.F. & Abbott, R.D. 2002. Developmental relationships between adolescent substance use and risky sexual behavior in young adulthood. Journal of Adolescent Health 31 (4): 354-62.
Halpern, C.T.; Hallfors, D.; Bauer, D.J.; Iritani, B.; Waller, M.W. & Cho, H. 2004. Implications of racial and gender differences in patterns of adolescent risk behavior for HIV and other sexually transmitted diseases. Perspectives on Sexual and Reproductive Health 36 (6): 239-47.
Harwell, T.S.; Trino, R.; Rudy, B.; Yorkman, S. & Gollub, E.L. 1999. Sexual activity substance use and HIV/STD knowledge among detained male adolescents with multiple versus first admission. Sexually Transmitted Diseases 26 (5): 265-71.
Henggeler, S.W. 1989. Delinquency in Adolescence. Newbury Park, CA: Sage.
Henggeler, S.W.; Pickrel, S.G. & Brondino, M.J. 1999. Multisystemic treatment of substance-abusing and dependent delinquents: Outcomes, treatment fidelity, and transportability. Mental Health Service Research 1 (3): 171-84.
Hlaing, W.M.; De la Rosa, M. & Niyonsenga, T. 2007. Human immunodeficiency virus (HIV) and substance use risk behaviors among tri-ethnic adolescents of Florida. AIDS and Behavior 11 (2): 239-51.
Institute of Medicine (IOM). 2006. Improving the Quality of Health Care for Mental and Substance-Use Conditions. Washington, DC: National Academy Press.
Johnston, L.D.; O'Malley, P.M.; Bachman, J.G. & Schulenberg, J.E. 2008. Monitoring the Future National Results on Adolescent Drug Use: Overview of Key Findings, 2007. NIH Publication No. 08-6418. Bethesda, MD: National Institute on Drug Abuse.
Kazdin, A.E. 1990. Premature termination from treatment among children referred for antisocial behavior. Journal of Child Psychology and Psychiatry 31: 415-25.
Kelly, P.J.; Bair, R.M.; Baillaergeon, J. & German, V. 2000. Risk behaviors and the prevalence of chlamydia in a juvenile detention facility. Clinical Pediatrics 39 (9): 521-27.
Kessler, R.C. 2004. Impact of substance abuse on the diagnosis, course, and treatment of mood disorders: The epidemiology of dual diagnosis. Biological Psychiatry 56 (10): 730-37.
Keyes, M.A.; Iacono, W.G. & McGue, M. 2007. Early onset problem behavior, young adult psychopathology, and contextual risk. Twin Research and Human Genetics 10 (1): 45-53.
Kingree, J.; Braithwaite, R. & Woodring, T. 2000. Unprotected sex as a function of alcohol and marijuana use among adolescent detainees. Journal of Adolescent Health 27: 179--85.
Lederman, C.S.; Dakof, G.A.; Larrea, M.A. & Li, H. 2004. Characteristics of adolescent females in juvenile detention. International Journal of Law and Psychiatry 27 (4): 321-37.
Leigh, B.C. & Stall, R. 1993. Substance use and risky sexual behavior for exposure to HIV: Issues in methodology, interpretation, and prevention. American Psychologist 48: 1035-45.
Leshner, A.I. 1997. Drug abuse and addiction treatment research. Archives of General Psychiatry 54: 691-94.
Liddle, H.A.; Dakof, G.A.; Turner, R.M.; Henderson, C.E. & Greenbaum, P.E. In press. Treating adolescent drug abuse: A randomized trial comparing Multidimensional Family Therapy and Cognitive Behavior Therapy. Addiction.
Liddle, H.A.; Dakof, G.A.; Parker, K.; Diamond, G.S.; Barrett, K. & Tejeda, M. 2001. Multidimensional family therapy for adolescent drug abuse: Results of a randomized clinical trial. American Journal of Drug and Alcohol Abuse 27 (4): 651-88.
Lowry, R.; Holtzman, D.; Truman, B.I.; Kann, L.; Collins, J.L. & Kolbe, L.J. 1994. Substance use and HIV-related sexual behaviors among US high school students: Are they related? American Journal of Public Health 84 (7): 1116-20.
Lucas, C.P.; Zhang, H.; Fisher, P.W.; Shaffer, D.; Regier, D.A. & Narrow, W.E. 2001. The DISC predictive scales (DPS): Efficiently screening for diagnoses. Journal of the American Academy of Child and Adolescent Psychiatry 40: 443-49.
Lucenko, B.A.; Malow, R.M.; Sanchez-Martinez, M.; Jennings, T. & Devieux, J.G. 2003. Negative affect and HIV risk in alcohol and other drug (AOD) abusing adolescent offenders. Journal of Child & Adolescent Substance Abuse 13 (1): 1-16.
Maisto, S.A. & Connors, G.J. 1992. Using subject and collateral reports to measure alcohol consumption (pp. 73-96). In: R.Z. Litten & J.P. Allen (Eds.) Measuring Alcohol Consumption: Psychosocial and Biochemical Methods. Totowa, NJ, US: Humana Press.
Malow, R.M.; Devieux, J.; Rosenberg, R.; Nair, M.; McMahon, R.; Brown, E.J. & Kalichman, S.C. 2007. Antisocial psychopathy and HIV risk among alcohol and other drug (AOD) abusing adolescent offenders. American Journal of Infectious Diseases 3 (4): 230-38.
Malow, R.M.; Rosenberg, R.; Donenberg, G. & Devieux, J.G. 2006. Interventions and patterns of risk in adolescent HIV/AIDS prevention. American Journal of Infectious Diseases 2 (2): 80-89.
Malow, R.; Gustman, S.; Ziskind, D.; McMahon, R. & St. Lawrence, S. 1998. Evaluating HIV prevention interventions among drug abusers: Validity issues. Journal of HIV/AIDS Prevention & Education for Adolescents & Children 2: 21-40.
McClelland, G.M.; Teplin, L.A.; Abram, K.M. & Jacobs, N. 2002. HIV/ AIDS risk behaviors among female jail detainees: Implications for public health policy. American Journal of Public Health 92: 818-25.
Moos, R.H. & Moos, B.S. 1986. Family Environment Scale Manual. Second Ed. Palo Alto, CA: Consulting Psychologists Press.
Perrino, T.; Gonzalez-Soldevilla, A.; Pantin, H. & Szapocznik, J. 2000. The role of families in adolescent HIV prevention: A review. Clinical Child & Family Psychology Review 3 (2): 81-96.
Rahdert, E. 1997. Problem Oriented Screening Instrument for Teenagers (POSIT), Special Report, Development of a POSIT-Related HIV/STD Risk of Exposure Scale. Bethesda, MD: National Institute on Drug Abuse, National Institutes of Health.
Rahdert, E. & Czechowicz, D. (Eds.) 1995. Adolescent Drug Abuse: Clinical Assessment and Therapeutic Interventions. NIDA Research Monograph 156, Rockville, MD: U.S. Government Printing.
Romero, E.G.; Teplin, L.A.; McClelland, G.M.; Abram, K.M.; Welty, L.J. & Washburn, J.J. 2007. A longitudinal study of the prevalence, development, and persistence of HIV/sexually transmitted infection risk behaviors in delinquent youth: Implications for health care in the community. Pediatrics 119: 1126-41.
Schaeffer, C.M. & Borduin, C.M. 2005. Long-term follow-up to a randomized clinical trial of multisystemic therapy with serious and violent juvenile offenders. Journal of Consulting and Clinical Psychology 73 (3): 445-53.
Sikkema K.J.; Winett R.A. & Lombard, D.N. 1995. Development and evaluation of an HIV-risk reduction program for female college students. AIDS Education and Prevention 7 (2): 145-59.
Sobell, L.C. & Sobell, M.B. 1992. Timeline follow-back: A technique for assessing self-reported alcohol consumption. In: R.Z. Litten & J.P. Allen (Eds.) Measuring Alcohol Consumption: Psychosocial and Biochemical Methods. Totowa, NJ: Humana Press.
Steinberg, L. & Avenevoli, S. 1998. Disengagement from school and problem behavior in adolescence: A developmental-contextual analysis of the influences of family and part-time work. In: R. Jessor & M. Chase (Eds.) New Perspectives on Adolescent Risk Behavior. New York: Cambridge.
St. Lawrence, J.S.; Montano, D.E.; Kasprzyk, D.; Phillips, W.R.; Armstrong, K. & Leichliter, J.S. 2002. STD screening, testing, case reporting, and clinical and partner notification practices: A national survey of US physicians. American Journal on Public Health 92: 1784-88.
Tapert, S.F.; Aarons, G.A.; Sedlar, G.R. & Brown, S.A. 2001. Adolescent substance use and sexual risk taking behavior. Journal of Adolescent Health 28 (3): 181-89.
Teplin, L.A.; Elkington, K.S.; McClelland, G.M.; Abram, K.M.; Mericle, A.A. & Washburn, J.J. 2005a. Major mental disorders, substance use disorders, comorbidity, and HIV-AIDS risk behaviors in juvenile detainees. Psychiatric Service 56 (7): 823-28.
Teplin, L.A.; McClelland, G.M.; Abram, K.M. & Mileusnic, D. 2005b. Early violent death among delinquent youth: A prospective longitudinal study. Pediatrics 115 (6): 1586-93.
Teplin, L.A.; Mericle, A.A.; McClelland, G.M. & Abram, K.M. 2003. HIV and AIDS risk behaviors in juvenile detainees: Implications for public health policy. American Journal of Public Health 93 (6): 906-12.
Teplin, L.A.; Abram, K.M.; McClelland, G.M.; Dulcan, M.K. & Mericle, A.A. 2002. Psychiatric disorders in youth in juvenile detention. Archives of General Psychiatry 59 (12): 1133-43.
Tolou-Shams, M.; Brown, L.K.; Houck, C.; Lescano, C.M. & Project Shield Study Group. 2008. The association between depressive symptoms, substance use and HIV risk among youth with an arrest history. Journal of Studies on Alcohol and Drugs 69 (1): 58-64.
Tolou-Shams, M.; Brown, L.K.; Gordon, G. & Fernandez, I. 2007. Arrest history as an indicator of adolescent/young adult substance use and HIV risk. Drug and Alcohol Dependence 88 (1): 87-90.
Vermeiren, R.; Jespers, I. & Moffitt, T. 2006. Mental health problems in juvenile justice populations. Child and Adolescent Psychiatric Clinic 15: 333--51.
Wilder, E.I. & Watt, T.T. 2002. Risky parental behavior and adolescent sexual activity at first coitus. Milbank Quarterly 80 (3): 481-524.
Winters, K.C. & Henly, G.A. 1993. Adolescent Diagnostic Interview Schedule and Manual. Los Angeles: Western Psychological Services.
Winters, K.C. & Henly, G.A. 1989. Personal Experience Inventory and Manual. Los Angeles: Western Psychological Services.
Van der Vorst, H.; Engels, R.C.; Meeus, W.; Dekovic, M. & Vermulst, A. 2006. Parental attachment, parental control, and early development of alcohol use: A longitudinal study. Psychology of Addictive Behaviors 20 (2): 107-16.
Zhang, Z. 2004. Drug and Alcohol Use and Related Matters Among Arrestees, 2003. Chicago: National Opinion Research Center, University of Chicago.
Ziedenberg, J. (in partnership with MacArthur Models for Change). 2006. Models for Change: Building Momentum for Juvenile Justice Reform: A Justice Policy Institute Report. MacArthur Foundation. Report available at: http://www.justicepolicy.org/images/upload/0612_REP_ModelsForChange_JJ.pdf
([dagger]) This study was funded under Criminal Justice Drug Abuse Treatment Studies (CJ-DATS), a cooperative agreement from the National Institute on Drug Abuse, National Institutes of Health (NIDA/NIH), with support from the Center for Substance Abuse Treatment of the Substance Abuse and Mental Health Services Administration, the Centers for Disease Control and Prevention (CDC), the National Institute on Alcohol Abuse and Alcoholism (all part of the U.S. Department of Health and Human Services); and from the Bureau of Justice Assistance of the U.S. Department of Justice. The authors gratefully acknowledge the collaborative contributions of NIDA, the Coordinating Center (George Mason University/University of Maryland at College Park), and the Research Centers participating in CJ-DATS (Brown University, Lifespan Hospitals and Memorial Hospital of Rhode Island; Connecticut Department of Mental Health and Addiction Services; National Development and Research Institutes, Inc.[NDRI] Center for Therapeutic Community Research; the NDRI Center for the Integration of Research and Practice; Texas Christian University, Institute of Behavioral Research; University of Delaware, Center for Drug and Alcohol Studies; University of Kentucky, Center on Drug and Alcohol Research; University of California at Los Angeles, Integrated Substance Abuse Programs; and University of Miami, Center for Treatment Research on Adolescent Drug Abuse). The contents are solely the responsibility of the authors and do not necessarily represent the views of the Department of Health and Human Services, the Department of Justice, NIDA, or other CJ-DATS participants.
Cynthia L. Rowe, Ph.D., Associate Professor, Center for Treatment Research on Adolescent Drug Abuse, Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, FL.
Wei Wang, Ph.D., Assistant Professor, College of Public Health, University of South Florida, Tampa, FL.
Paul Greenbaum, Ph.D., Professor; Department of Child and Family Studies, Florida Mental Health Institute, University of South Florida,[Tampa, FL.
& Howard A. Liddle, Ed.D., Professor and Director; Center for Treatment Research on Adolescent Drug Abuse, Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, FL.
Please address correspondence and reprint requests to Cynthia Rowe, Center for Treatment Research on Adolescent Drug Abuse, Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, 1120 N.W. 14th Street, Suite 1014, Miami, FL 33136. Email: email@example.com.
TABLE 1 Predictors of HIV/STD High Risk Level Group Entered Univariately with Demographic Variables Controlled Std. Beta Error t Value p Value Total Delinquency (NYS) 0.011 0.005 2.35 0.02 Parent Reported Delinquency (CBCL) 0.098 0.042 2.33 0.02 Adolescent Reported Delinquency (YSR) 0.151 0.059 2.57 0.01 Days Used Alcohol or Drugs (TLFB) 0.010 0.005 2.11 0.04 Involvement w/Substances (PEI) 0.036 0.016 2.32 0.02 TABLE 2 Final Predictors of HIV/STD High Risk Level Group: Step-Wise Model Selection Procedure Std. Beta Error t Value p Value Intercept -3.841 3.036 -1.27 0.21 Age 0.412 0.182 2.26 0.03 Gender -1.619 0.666 -2.43 0.02 White Non-Hispanic Ethnicity -0.150 0.534 -0.28 0.78 Hispanic Ethnicity 1.145 0.533 2.15 0.03 Total Delinquency (NYS) 0.011 0.005 2.17 0.03 Parent Reported Delinquency (CBCL) 0.085 0.040 2.12 0.04 TABLE 3 Predictors of Substance Use Disorders Entered Univariately with Demographic Variables Controlled Beta Std. Error t Value p Value Number Lifetime Arrests 0.167 0.089 1.89 0.06 Total Delinquency (NYS) 0.009 0.004 2.45 0.02 Adolescent Reported Delinquency (YSR) 0.117 0.054 2.19 0.03 Adolescent Reported Conflict (FES) 0.181 0.077 2.36 0.02 Number of Psychiatric Diagnoses (DISC) 0.305 0.104 2.92 0.00 Having Sex when Drunk or High 0.125 0.07 1.79 0.08 TABLE 4 Final Predictors of Substance Use Disorders: Step-Wise Model Selection Procedure Beta Std. Error t Value p Value Intercept 1.711 2.791 0.61 0.54 Age -0.091 0.168 -0.54 0.59 Gender -0.512 0.575 -0.89 0.37 White non-Hispanic Ethnicity 2.293 0.783 2.93 0.00 Hispanic Ethnicity 0.467 0.444 1.05 0.29 Total Delinquency (NYS) 0.008 0.004 2.24 0.03 Adolescent Reported Conflict (FES) 0.152 0.078 1.94 0.06
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