Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2014 Dec 1.
Published in final edited form as: J Prim Prev. 2013 Dec;34(6):10.1007/s10935-013-0326-z. doi: 10.1007/s10935-013-0326-z

The Association Between Problematic Parental Substance Use and Adolescent Substance Use in an Ethnically Diverse Sample of 9th and 10th Graders

Ryan C Shorey 1, Paula J Fite 2, Sara R Elkins 3, Kevin C Frissell 4, Susan R Tortolero 5, Gregory L Stuart 6, Jeff R Temple 7
PMCID: PMC3856214  NIHMSID: NIHMS521558  PMID: 24006209

Abstract

Adolescents of parents who use substances are at an increased risk for substance use themselves. Both parental monitoring and closeness have been shown to mediate the relationship between parents’ and their adolescents’ substance use. However, we know little about whether these relationships vary across different substances used by adolescents. Using structural equation modeling, we examined these associations within a racially and ethnically diverse sample of 9th and 10th graders (N = 927). Path analyses indicated that maternal closeness partially mediated the association between maternal problematic substance use and adolescent alcohol use. Parental monitoring partially mediated the relationship between paternal problematic substance use and adolescent alcohol, cigarette, marijuana, inhalant, and illicit prescription drug use. These results were consistent across gender and race/ethnicity. These findings suggest that parental interventions designed to increase closeness and monitoring may help to reduce adolescent substance use.

Keywords: Substance use, Adolescents, Parental monitoring, Parental closeness

Introduction

Adolescent substance use is a serious public health concern with negative individual and societal consequences (Chassin, Ritter, Trim, & King, 2003). Rates of substance use among youths aged 12–17 are high, with current (i.e., past month) alcohol use at almost 15 %, tobacco use at almost 12 %, and overall illicit drug use at 10 % (SAMHSA, 2012). The typical age of substance use onset occurs between 13 and 15 (Johnston, O'Malley, & Bachman, 1999). As such, it is important to understanding the risk and protective factors that affect substance use in adolescence, which may inform the content and timing of intervention programs designed to reduce substance use in this vulnerable population.

A substantial body of research has established that parental substance use affects their children's risk for alcohol and drug use (Chassin, Curran, Hussong, & Colder, 1996; Epstein, Williams, & Botvin, 2002). Children of parents who abuse alcohol are at high risk for early alcohol initiation (Hill, Shen, Lowers, & Locke, 2000) and greater alcohol consumption (Chassin & Barrera, 1993). Research also indicates a strong association between parental drug use and the development of drug use among their adolescents (Brook et al., 2001; Miller, Alberts, Hecht, Trost, & Krizek, 2009).

The relationship between parents’ and their children's substance use may operate through both biological or heritable (Kendler, Karkowski, & Prescott, 1999; Schuckit, 2009) and psychosocial, mechanisms (Kerr & Stattin, 2000; Rutherford, Cacciola, Alterman, McKay, & Cook, 1997). Social learning theory suggests that parental substance use may have a modeling effect (Bandura, 1977), by which parents’ substance use behaviors encourage imitation by adolescents. Parental substance use may also impair parenting (Van der Vorst, Engels, Meeus, Dekovic, & Vermulst, 2006), which may also affect the development of adolescent substance use. However, the theory of social control suggests that in the presence of parental substance use behaviors, adolescents will be less likely to use substances themselves if they experience high levels of parental support (e.g., closeness) and control (e.g., monitoring; Hirschi, 1969).

One particularly important parental influence on adolescent substance use is closeness. Parental closeness or family cohesion and bonding (Bahr, Marcos, & Maughan, 1995; Farrell, Barnes, & Barerjee, 1995), have been conceptualized as sharing discussion and leisure time (Zhang, Welte, & Wieczorek, 1999), and include nurturance, acceptance, and warmth (Schinke, Fang, & Cole, 2008). Researchers have demonstrated that adolescent children of alcohol-abusing parents receive less emotional support from their parents (Rutherford et al., 1997), and that adolescents who do not feel close to their parents are at greater risk for substance use and substance-related problems (Kandel, 1996; Kelly et al., 2011). Further, studies indicate that parents’ closeness to their adolescents may prevent early substance initiation and decrease adolescents’ frequency and amount of heavy drinking (Bahr et al., 1995; Zhang et al., 1999).

The relationship between parental monitoring and adolescent substance use is widely documented. Effective monitoring is typically based on parents’ knowledge of their children's activities both in and outside of their home (Kerr, Stattin, & Burk, 2010), as well as acquaintance with their adolescents’ friends or dating partners, and may include limits or restrictions on their activities and associations (Laird, Pettit, Bates, & Dodge, 2003). Parental substance use decreases the amount of monitoring parents provide to adolescents (Chassin et al., 1996; Dishion, Patterson, & Reid, 1988), which is a cause for concern since monitoring in turn reduces the likelihood of adolescent substance use and heavy use (Clark, Shamblen, Ringwalt, & Hanley, 2012; Engels & Van der Vorst, 2003; Kerr & Stattin, 2000; Lockman, 2003; Van der Vorst et al., 2006).

Research thus suggests a relationship between adolescent substance use and both parental substance use and parental closeness and monitoring. However, few studies have examined whether parental monitoring or closeness mediates the relationship between parental and adolescent substance use. Two prospective studies have demonstrated that a father's participation in monitoring and discipline mediated the relationship between paternal alcoholism and adolescent alcohol use (King & Chassin, 2004), and one study explicitly tested a mediational model, but did not find a significant relationship between parental problem drinking and parenting behaviors (van der Zwaluw et al., 2008). While these studies examined mediational models of the relationship between parental and adolescent substance use, the authors focused only on parental alcohol use but did not also address the effects of parental drug use.

To date, only one study has examined the potential mediating role of parental closeness on the relationship between parental and adolescent substance use, finding no evidence for mediation (Zhang et al., 1999). No study has examined both parental closeness and monitoring as mediators of the relationship between parental and adolescent substance use within the same predictive model. Such a model has the potential to advance our knowledge of the significance of each variable relative to the other, and may have implications for more targeted parent- or family-based intervention programs.

Differential effects have been noted of the impact of maternal and paternal closeness on adolescents’ substance use (Padilla-Walker, Nelson, Madsen, & McNamara-Barry, 2008), and on the relationship between parental substance use and closeness on adolescent drinking (Zhang et al., 1999). Much of the previous literature has been conducted with substance-using mothers of adolescents (Barnard & McKeganey, 2004), and there is a dearth of research on the impact of fathers’ substance use on parenting and subsequent adolescent substance use. It is thus important to examine mothers and fathers separately when examining whether monitoring and closeness mediate the relation between parental and adolescent use.

Similarly, it is important to examine how these mediational pathways differ between male and female adolescents. For instance, boys display slightly higher rates of alcohol, tobacco, and marijuana use than girls (York, Welte, Hirsch, Hoffman, & Barnes, 2004). Research suggests that parental monitoring tends to impact boys’ alcohol use more strongly than girls’ (e.g., van der Vorst et al., 2006), and girls’ cigarette and marijuana use more strongly than boys’ (Griffin, Botvin, Scheier, Diaz, & Miller, 2000; Lac & Crano, 2009). Other studies indicate that parental closeness may have a stronger effect on substance use for girls (Choquet, Hassler, Morin, Falissard, & Chau, 2008; Kelly et al., 2011). We thus examined whether parental closeness and monitoring mediated the association between parental and adolescent substance use. Further, we examined whether these pathways varied between male and female adolescents and by the gender of the parent.

Given the racial and ethnic variations in rates and timing of onset of adolescent substance use (Ellickson & Morton, 1999; Hawkins, Catalano, & Miller, 1992; Jackson, 1997; SAMHSA, 2012; Wu, Temple, Shokar, Nguyen-Oghalai, & Grady, 2010), it is also important to consider racial and ethnic differences in the proposed meditational model. Although rates of substance use in adolescence are well-defined, racial and ethnic differences in the association between parental and adolescent substance use, and mediators of this relationship, have received little empirical attention and pertinent findings have been inconsistent (Barnes, Farrell, & Banerjee, 1994; Turner & Wallace, 2003; Vega, Zimmerman, Warheit, Apospori, & Gil, 1993). We thus examined whether the proposed mediated pathways varied among Hispanic/Latino, African American, and Caucasian adolescents.

In addition to considering gender and race/ethnicity in the mediational model, our study makes several other contributions to the literature. First, we examined relationships among 9th and 10th graders, during a developmental period in which substance use has typically already been initiated but has not yet reached its peak (Johnston, O'Malley, Bachman, & Schulenberg, 2010). Second, we examine within our mediational model adolescents’ use of a variety of substances, including alcohol, cigarette, marijuana, inhalant, ecstasy, and illicit prescription drug use; previous studies have often examined only a single substance (e.g., Ryan, Jorm, & Lubman, 2010). Third, while much of the empirical literature has reported relationships between parental and adolescent substance use based on frequency counts of parental substance use, we examined adolescents’ perceptions of problematic parental substance use (i.e., the consequences associated with parental use), which may be a better predictor of both poorer parenting and greater subsequent adolescent substance use (Barnard & McKeganey, 2004). Fourth, we examined whether the proposed mediational model differed for adolescents who lived in a two- versus single-parent household, as previous studies suggest the latter is associated with greater risk for substance use (Breivik & Olweus, 2006).

We thus hypothesized that (1) parental closeness and monitoring would mediate the relationship between problematic parental substance use and adolescent substance use, and (2) parental closeness and monitoring would be a stronger predictor for female than male adolescents of the use of all substances except alcohol. Due to limited research on racial/ethnic differences in these relationships, we developed no specific hypotheses regarding the role of race/ethnicity in our mediational model.

Methods

Participants

We recruited 1,702 students from seven high schools in five school districts in southeast Texas for the current study. A total of 1,215 returned a parental permission form (71 %), of whom 1,119 gave their children permission to participate (66 % of those approached; 92 % of those who returned their permission forms); and 1,049 completed the survey (62 % of those approached; 94 % of those who received parental permission). We discarded seven surveys due to severely inconsistent responses, which yielded a total of 1,042 study participants. Because of the low number of students in the 11th grade (n = 11) and of those who reported their race or ethnicity as Asian (n = 38), American Indian (n = 5), multi-racial (n = 20), or “other” (n = 40), these students were also excluded from the present analyses, leaving those students who were in the 9th or 10th grade and who were Caucasian, African American, or Hispanic/Latino. This resulted in a final sample size of 927 students, of whom the majority were female (56 %, n = 519), 36.2 % were Hispanic/Latino, 32.5 % were Caucasian, and 31.3 % were African American. Most participants were between the ages of 14 and 16 (96.8 %) and in the 9th grade (75.4 %). As detailed elsewhere (Temple, Shorey, Fite, Stuart, & Le, 2013; Temple, Shorey, Tortolero, Wolfe, & Stuart, 2013) and below, this sample is representative of the larger student body from which they were recruited.

Procedures

In order to secure a representative sample of adolescents, we recruited students during normal school hours in required classes stratified by grade level (e.g., English). Students completed all measures during the spring semester of 2010, between the months of February and May. All students were eligible to participate in the study. We used a multi-stage approach to obtain active written parental permission. A member of the research staff attended each class period twice prior to the assessment to describe to the students the purpose and general design of the study and to answer any questions. Students were sent home with detailed information about the study in both English and Spanish, along with a parental consent form for their parents to review, sign, and return. Regardless of whether parental permission was granted, students who returned a parental permission form received a $5 gift card to a local retailer.

Students who obtained written and informed parental/guardian permission provided their assent on the day of the assessment. To this end, we “pulled” students from the class from which they were recruited and escorted them to a room on campus, where they completed the 35–45 min survey questionnaire in small groups. We gave participants another $5 gift card for taking the survey. All study procedures were approved by the Institutional Review Board of UTMB.

Measures

Parental Problematic Substance Use

We asked students if their mother's (or mother figure's) “drinking or drug use had ever caused problems with her health, family, job, or police.” We then asked this same question for their fathers (or father figures). Students responded to these questions with a yes or no.

Parental Monitoring

We used three questions to assess parental monitoring. Students indicated how important it was for their parents (or parental figures) to know (1) who their friends are, (2) where they are, and (3) whom they are dating. We adapted these questions from the Parental Supervision scale, which has good internal consistency and validity (Bjerregaard & Smith, 1993). Students indicated their responses on a 4-point scale (1 = Very Important to 4 = Not at all important). This questionnaire did not distinguish between maternal and paternal monitoring. We calculated a total score by reverse coding and then taking the mean of score on all three items. Higher scores thus corresponded to greater parental monitoring. The internal consistency (α) of this scale was .74.

Parental Closeness

We used two items to examine parental closeness for mothers and fathers (or parental figures) separately. These two questions were (1) “Do you feel close to your mother [father],” and (2) “Do you share your thoughts and feelings with your mother [father].” We adapted these items from the Attachment to Parents scale, which has good internal consistency and validity (Arthur, Hawkins, Pollard, Catalano, & Baglioni, 2002). Students rated their answers on a 4-point scale (1 = very true to 4 = very false). We secured a total score for maternal and paternal closeness by reverse coding and then taking the mean of scores on both items, so that higher scores corresponded to greater parental closeness. The internal consistency (α) was .70 for maternal and .83 for paternal closeness, respectively.

Adolescent Substance Use

Students indicated (yes or no) their lifetime use of alcohol, cigarettes, marijuana, inhalants, ecstasy, or illicit prescription drugs that were not prescribed by a health professional. We instructed students that alcohol use referred to “more than just a few sips.” We also provided students with examples of inhalants (e.g., sniffed glue) and prescription drugs (e.g., Xanax, Oxycontin, Ritalin) not prescribed to them by a doctor. Previous research has generally found that adolescents are reliable and valid reporters of their substance use behaviors (Johnston et al., 2010).

Data Analysis Strategy

We performed statistical analyses using two programs. We first examined gender and racial/ethnic differences on key variables of interest in SPSS 18.0, and then used structural equation modeling (SEM) in Mplus Version 5.0 to examine the proposed mediation model. Prior to analyses, we mean-centered all predictor variables to aid in the interpretation of findings (Aiken & West, 1991). We estimated SEMs with full information estimation (FIE), which uses all available data to estimate parameters and does not exclude observations with missing data (Kline, 2005). When compared to pairwise and listwise deletion, FIE is more efficient and less biased for handling missing data (Arbuckle, 1996). In addition, we used the bias-corrected bootstrap method to test the significance of mediated paths. As detailed by MacKinnon, Lockwood, and Williams (2004), the bias-corrected bootstrap method provides a more favorable balance between Type 1 and 2 errors than do other methods used to test the significance of mediated paths. Altogether, we used 500 bootstrap samples and 95 % bias-corrected confidence intervals (CIs) to estimate the significance of the mediated paths.

We also calculated the percentage of the total association between parental problematic substance use and adolescent substance use that was explained by parental monitoring and closeness (MacKinnon & Dwyer, 1993). To do so, we divided the estimated indirect effect (%IE) for parental monitoring and closeness by the total direct effect for the relationship between problematic parental substance use and adolescent substance use.

Due to the dichotomous nature of the outcome variable (adolescent lifetime substance use), we employed weighted least squares estimate with a mean and variance (WLSMV) adjusted χ2 statistic for all SEM path analyses. WLSMV supplies standard errors, unbiased estimates, and model fit tests for dichotomous outcome variables and for non-normal data in general (Muthén, 1984; Muthén & Muthén, 2006). We evaluated model fit using the weighted root-mean square residual (WRMR) statistic; values falling below .90 indicated a good model fit (Muthén & Muthén, 2006; Yu & Muthén, 2001). The WRMR is the only model fit statistic available when examining dichotomous outcome variables (Muthén & Muthén, 2006).

After evaluating the initial mediational model, we examined whether any structural path varied as a function of gender, race/ethnicity (Caucasian, Hispanic/Latino, or African American), and adolescents’ living arrangement, using a multiple group model approach (Muthén & Muthén, 2006). This approach entailed two steps, the first of which involved estimating an unrestricted model where all structural paths were free to vary across gender, race/ethnicity, or living arrangement. The second step involved estimating a model in which we constrained the structural paths among variables to be equal across gender, race/ethnicity, and living arrangement. We then used a χ2 difference test (Δχ2), as described by Muthén and Muthén (2006), for use with WLSMV, to determine whether constraining paths across gender, race/ethnicity, or living arrangement resulted in a significant decrement in the model χ2. If constraining the paths to be equal across these variables resulted in a significant decrement to the model χ2, we could then assume that the relationships among them differed.

Results

Sample Characteristics and Group Comparisons

For parental problematic substance use, 9.6 % of students indicated that their mother's use was problematic and 26.9 % indicated their father's use was problematic. The lifetime prevalence of adolescent substance use for the entire sample was 65.7 % for alcohol, 22.1 % for cigarettes, 31.3 % for marijuana, 4.8 % for inhalants, 4.1 % for ecstasy, and 10.5 % for prescription drugs. These rates are similar to those found in nationally representative samples of 9th and 10th grade adolescents (e.g., Johnston et al., 2010). In addition, at the time of the study, 44.4 % of adolescents were living with their mother and father, 25 % with their mother only, 20.7 % with one parent and a step-parent, 3.5 % with their father only, 3 % with grandparents, and 3.3 % with someone else (i.e., “other”). The lifetime prevalence of substance use, as well as parental problematic substance use, did not differ between 9th and 10th grade students. We also created a sum variable of all types of lifetime substance use to examine the correlation between adolescent and problematic parental substance use. Results demonstrated that adolescent substance use was positively associated with both maternal (r = .18, p < .001) and paternal (r = .27, p < .001) problematic substance use.

Table 1 presents descriptive statistics for study variables for males, females, and each racial/ethnic group. Males had a higher prevalence rate of cigarette [χ2 (2) = 7.64, p < .05] and marijuana [χ2 (2) = 14.82, p < .01] use. Racial/ethnic groups differed for cigarettes [χ2 (4) = 35.14, p < .001] and prescription drug [χ2 (4) = 26.16, p < .001] use. Follow-up analyses showed that Caucasian adolescents had a higher lifetime prevalence of prescription drug use than Hispanic/Latino youth [χ2 (2) = 6.56, p < .05] and a higher lifetime prevalence rate of both cigarette [χ2 (2) = 33.96, p < .001] and prescription drug use [χ2 (2) = 25.66, p < .001] than African American youth. Hispanic/Latino adolescents had a higher lifetime prevalence of both cigarette [χ2 (2) = 23.20, p < .001] and prescription drug use [χ2 (2) = 8.18, p < .05] than African American youth.

Table 1.

Descriptive statistics among study variables

Male (n = 408) Female (n = 519) White (n = 301) Hispanic/Latino (n = 336) African American (n = 290)
Lifetime use
Alcohol 65.4 % (n = 266) 66.0 % (n = 342) 69.8 % (n = 210) 65.8 % (n = 221) 61.0 % (n = 177)
Cigarettes 26.3 % (n = 107)* 18.8 % (n = 97)* 29.6 % (n = 89)* 25.3 % (n = 85)* 10.3 % (n = 30)*
Marijuana 37.9 % (n = 154)* 26.1 % (n = 135)* 36.2 % (n = 109) 30.7 % (n = 103) 26.6 % (n = 77)
Inhalant 4.7 % (n = 19) 4.8 % (n = 25) 7.3 % (n = 22) 2.4 % (n = 8) 4.8 % (n = 14)
Ecstasy 4.7 % (n = 19) 3.7 % (n = 19) 4.7 % (n = 14) 5.1 % (n = 17) 2.4 % (n = 7)
Prescription 11.6 % (n = 47) 9.7 % (n = 50) 16.9 % (n = 51)* 10.1 % (n = 34)* 4.1 % (n = 12)*
Parental substance use
Mother 9.3 % (n = 38) 9.8 % (n = 51) 15.6 % (n = 47)* 4.9 % (n = 18)* 8.3 % (n = 24)*
Father 28.4 % (n = 116) 25.6 % (n = 133) 28.2 % (n = 85) 25.6 % (n = 94) 24.1 % (n = 70)
Parental monitoring/closeness M (SD)
Parental monitoring 1.89 (.66)* 1.59 (.59)* 1.79 (.64) 1.70 (.66) 1.67 (.61)
Mother closeness 1.86 (.87) 1.89 (.92) 1.91 (.99) 1.90 (.82) 1.82 (.88)
Father closeness 1.98 (1.14)* 2.17 (1.31)* 2.17 (1.14) 2.03 (1.25) 2.08 (1.31)
Open in a new tab
*

p < .05 difference between groups

Males and females did not differ in the lifetime prevalence of either their mothers’ [χ2 (1) = .82, p > .05) or fathers’ (χ2 (1) = .34, p > .05] problematic substance use. However, the three racial/ethnic groups did differ as to problematic maternal substance use, [χ2 (2) = 20.23, p < .001], insofar as Caucasian adolescents reported a higher prevalence than either Hispanic/Latino [χ2 (1) = 18.37, p < .001] or African American adolescents [χ2 (1) = 7.52, p < .05]. Males and females also differed on parental monitoring and father closeness; females scored lower on parental monitoring, [t(921) = 7.23, p < .001], and higher on paternal closeness [t(922) = 2.33, p < .05]. The three racial/ethnic groups did not significantly differ on parental monitoring or closeness.

We also examined whether adolescents with a lifetime history of substance use reported a greater prevalence of parental problematic substance use than youth who had never used substances. As evident in Table 2, female adolescents with a lifetime history of alcohol, cigarettes, and prescription drug use reported a greater prevalence of maternal problematic substance use than adolescents who had never used these substances. Further, females with a lifetime history of alcohol, cigarettes, marijuana, ecstasy, and prescription drug use reported a higher prevalence of paternal problematic use than females who had never used these substances. For males, adolescents with a lifetime history of cigarettes, marijuana, ecstasy, and prescription drug use reported a greater prevalence of maternal problematic substance use than those who had never used these substances. Moreover, males with a lifetime history of alcohol, cigarettes, marijuana, ecstasy, and prescription drug use reported a higher prevalence of paternal problematic use than males without lifetime use of these substances.

Table 2.

Differences in prevalence of problematic parental substance use by prevalence of lifetime adolescent substance use

Males
 Females
Lifetime alcohol (n = 262) (%) No lifetime alcohol (n = 141) (%) χ2, p Lifetime alcohol (n = 342) (%) No lifetime alcohol (n = 175) (%) χ2, p
Problematic mother substance use 11.4 5.6 3.58, >.05 12.5 3.4 8.34, <.01
Problematic father substance use 34.3 17.7 12.74, <.001 30.1 17.1 9.40, <.01
Lifetime cigarette (n = 104) (%) No lifetime cigarette (n = 299) (%) χ2, p Lifetime cigarette (n = 97) (%) No lifetime cigarette (n = 388) (%) χ2, p
Problematic mother substance use 16.3 7 7.85, <.01 19.5 7.9 13.37, <.001
Problematic father substance use 43.2 23.4 14.61, <.001 47.4 22.4 29.09, <.001
Lifetime marijuana (n = 129) (%) No lifetime marijuana (n = 235) (%) χ2, p Lifetime marijuana (n = 118) (%) No lifetime marijuana (n = 348) (%) χ2, p
Problematic mother substance use 16.3 7.2 5.78, <.05 14.4 9.4 1.76, >.05
Problematic father substance use 52.7 20 33.06, <.001 39.8 24.7 7.91, <.01
Lifetime inhalant (n = 19) (%) No lifetime inhalant (n = 383) (%) χ2, p Lifetime inhalant (n = 20) (%) No lifetime inhalant (n = 446) (%) χ2, p
Problematic mother substance use 15.7 9.1 .94, >.05 25 10 3.19, >.05
Problematic father substance use 47.3 27.4 3.48, >.05 32 28 .46, >.05
Lifetime ecstasy (n = 19) (%) No lifetime ecstasy (n = 381) (%) χ2, p Lifetime ecstasy (n = 17) (%) No lifetime ecstasy (n = 449) (%) χ2, p
Problematic mother substance use 31.5 8.4 11.31, <.01 11.7 10.6 .02, >.05
Problematic father substance use 63.1 26.7 11.63, <.01 70.5 26.9 15.88, <.001
Lifetime prescription (n = 47) (%) No lifetime prescription (n = 355) (%) χ2, p Lifetime prescription (n = 38) (%) No lifetime prescription (n = 427) (%) χ2, p
Problematic mother substance use 23.4 7.6 12.10, <.01 31.5 8.9 12.90, <.001
Problematic father substance use 51.1 25.3 13.31, <.001 60.5 25.5 12.38, <.001
Open in a new tab

Percentages represent number of adolescents who endorsed problematic parental substance use

Mediation

To investigate mediation, we used SEM to examine the relationships maternal and paternal problematic substance use, parental monitoring, maternal and paternal closeness, and adolescent lifetime substance use. To provide a more conservative test of the relationship between parental problematic substance use and adolescent substance use, as mediated by parental monitoring and closeness, we also included direct paths from parental problematic substance use to adolescent substance use (see Fig. 1). As mentioned above, this first model did not take into account any potential gender, racial/ethnic, or living arrangement differences. This model fit the data well (WRMR = .152). As shown by the standardized path coefficients for this model (Table 3), paternal problematic substance use was positively associated with adolescent lifetime alcohol, cigarette, marijuana, ecstasy, and prescription drug use, and negatively associated with parental monitoring and closeness. Paternal closeness was unrelated to any of the substances. Maternal problematic substance use was positively associated with lifetime alcohol, cigarette, and prescription drug use, as well as decreased closeness. Maternal closeness was negatively related to alcohol use. Parental monitoring was associated with a decreased likelihood of all types of substance use except ecstasy.

Fig. 1.

Fig. 1

Open in a new tab

Parental monitoring and closeness as potential mediators of the associations between problematic parental substance use and adolescent substance use. Single-headed arrows represent proposed unidirectional pathways and lines with double-headed arrows represent unanalyzed (correlational) associations. For the sake of clarity, disturbances and endogenous covariances were included in the model but not presented

Table 3.

Standardized path estimates for overarching model

Mediators Mother substance use → Mediator Father substance use → Mediator Substance use outcomes
Alcohol Cigarettes Marijuana Inhalants Ecstasy Prescription drugs
Mother closeness –.36 (.13)** – –.13 (.05)** –.06 (.05) –.03 (.05) –.12 (.08) .00 (.09) –.05 (.06)
Father closeness – –.24 (.10)* .01 (.03) –.01 (.03) .06 (.03) .00 (.05) –.02 (.06) –.01 (.05)
Parental monitoring –.12 (.08) –.20 (.05)*** –.13 (.06)* –.23 (.07)** –.39 (.06)*** –.22 (.10)* .17 (.12) –.19 (.09)*
Mother substance use – – .38 (.16)* .42 (.14)** .17 (.14) .25 (.23) .26 (.21) .53 (.15)***
Father substance use – – .39 (.09)*** .51 (.09)*** .46 (.08)*** .17 (.16) .65 (.14)*** .45 (.11)***
Open in a new tab

Standard errors are in parentheses

*

p < .05

**

p < .01

***

p < .001

The association between maternal problematic substance use and their adolescents’ lifetime alcohol use was partially mediated by maternal closeness (B = .05, 95 % CI .01–.12, % IE = 11.1). The associations between paternal problematic substance use and adolescent alcohol (B = .03, 95 % CI .00–.07, % IE = .07), cigarette (B = .05, 95 % CI .02–.09, % IE = .08), marijuana (B = .08, 95 % CI .04–.13, % IE = .15) prescription drug (B = .04, 95 % CI .00–.09, % IE = .08), and inhalant (B = .04, 95 % CI .01–.11, % IE = .20) use were partially mediated by parental monitoring.

Multiple Group Model

To determine whether any of the structural paths, indirect effects, and covariances varied as a function of gender, race/ethnicity, or living arrangement, we employed a multiple group model approach. We first permitted paths to vary across gender (then race/ethnicity, and then living arrangement), and then constrained them to be equal across gender. Paths did not vary either by gender [Δχ2(35) = 26.256, p > .05] or race/ethnicity [Δχ2(59) = 73.56, p > .05]. For living arrangement, we conducted a multiple group model comparing adolescents who lived with two parents to those living with anyone else (e.g., one parent, step-parent, grandparents), and found no differences in this regard [Δχ2(36) = 32.36, p > .05]. We attempted to run a multiple group model comparing adolescents who lived with two parents, one parent and a step-parent, one parent only, or “other” (i.e., grandparents). However, this model would not converge due to the small number of adolescents in the “other” group.

Discussion

We used a racially/ethnically diverse sample of 9th and 10th grade males and females to examine the relationships between maternal and paternal problematic substance use and adolescent substance use and to determine whether parental monitoring and parental closeness mediated these relationships. We also examined parental monitoring and parental closeness as mediators in the same model, taking into consideration their unique impact on adolescent substance use for mothers and fathers separately. We also examined six different substances that adolescents may have used in their lifetime, and determined whether these relationships differed on gender, race/ethnicity, or living arrangement.

Our findings were consistent with previous research showing that adolescents with substance using parents are at a heightened risk for substance use themselves, and that a portion of this risk is attributable to parenting factors. Specifically, maternal problematic substance use was associated with adolescent alcohol, cigarette, and illicit prescription drug use, and paternal problematic substance use was associated with adolescent alcohol, cigarette, marijuana, ecstasy, and illicit prescription drug use. These findings suggest that paternal problematic substance use may be more important than maternal problematic substance use in predicting a range of substances used by adolescents. However, due to the low prevalence of maternal problematic substance use reported in this study, we believe that this finding should be replicated before firm conclusions can be drawn. Further, this is one of the first studies to show the association between problematic parental substance use and adolescent prescription drug use across different racial/ethnic groups. This is an especially important finding given the increase in illicit use of prescription drugs among adolescents in recent years (Johnston et al., 2010).

Our findings demonstrate the importance of parenting practices as contributors to the transmission of substance use from parents to their offspring. Findings showed that, for mothers, closeness played an important role in adolescent alcohol use, and partially accounted for the association between maternal problematic substance use and adolescent alcohol use. However, we did not find any differences with regard to gender, race/ethnic or living arrangement in the relationship between closeness and adolescent substance use. These findings speak to the importance of adolescents’ connectedness to their mothers, who are often regarded as the parent who is most likely to provide emotional support and nurturance, as well as to engage in conversation and shared activities during early childhood and adolescence (Crouter & McHale, 1993; Waizenhofer, Buchanan, & Jackson-Newsom, 2004). Having a reduced sense of closeness with their mothers, above and beyond the influence of parental monitoring, may contribute to adolescents’ experimentation with substances as a method of coping with their lack of connection. Alternatively, substance-using adolescents may distance themselves emotionally from their mother in order to conceal their risky behavior.

Maternal closeness only partially accounted for the association between maternal problematic substance use and adolescent alcohol use, and did not affect the use of any other substances. There are a few possible explanations for this finding. First, the most prevalent substance used by females is alcohol (Johnston et al., 2010), and it is therefore possible that adolescents were modeling the substance used most often by their mothers. Similarly, alcohol is a readily available substance, making it easier for adolescents to use as a coping mechanism or with their peers. However, maternal problematic substance use may also have less of an impact on adolescents’ substance use, regardless of potential mediators. In our study, maternal problematic substance use was only directly associated with three of the six substances assessed.

Our findings also showed that parental monitoring partially accounted for the relationship between paternal problematic substance use and adolescent alcohol, cigarette, marijuana, prescription drug, and inhalant use. These findings stand in contrast to that of mothers, which showed that maternal closeness, not monitoring, played an important role in adolescent substance use. Most previous studies have failed to disentangle the effects of parental monitoring from both parents (e.g., Cleveland, Feinberg, & Greenberg, 2010), and these findings indicate that the ability of parents to effectively monitor their children's behavior may reduce the chances that paternal problematic substance use will impact adolescents’ use of substances. It is possible that paternal problematic substance use leads to more adverse personal and family consequences that hinder the ability of fathers, and the family unit as a whole, to effectively monitor their adolescents’ behavior. Again, we did not find any gender, racial/ethnic or living arrangement differences in the relation between monitoring and adolescent substance use. However, it is possible that the lack of significant differences may have been due to insufficient power in some of the subgroup analyses.

There are several limitations to this study. First, despite causal assumptions, its cross-sectional nature precludes determining the direction of causality. Longitudinal research is needed to replicate our findings in a prospective context, and to test competing models that provide similar patterns of results. For example, parents may have modified their parenting behavior in response to adolescent substance use. Second, since our measure of parental monitoring only contained three items and did not examine this construct for mothers and fathers separately, our results may have differed had we assessed monitoring individually for each parent. Our measure of parental closeness contained only two items, and future studies could employ better measures. Third, some of our subgroup analyses may have been underpowered, which could have limited our ability to detect significant effects.

In addition, our measure of parental substance use examined problematic use, not the frequency or intensity of parental substance use per se. Further, we did not examine the types of substances the parents used. Future studies should investigate whether parental alcohol and drug use affect adolescents differently. Finally, our assessment of lifetime adolescent substance use was limited to the prevalence, not the frequency or intensity, of use, which if measured may have yielded different results.

Despite these limitations, our study suggests that pathways from parental problematic substance use to adolescent substance use are largely similar for males, females, racial/ethnic groups, and adolescents who live with either both or a single parent. In combination with previous research, our study suggests that prevention efforts aimed at reducing or delaying the initiation of adolescent substance use should focus on adolescents at high risk for use, including those who perceive high problematic parental substance use, and low closeness and monitoring. Screening programs should be established to identify these adolescents. Parental prevention programs aimed at increasing positive parenting skills (e.g., Dishion & Kavanagh, 2003), such as increasing closeness and effective monitoring, could also be implemented to decrease the likelihood of adolescent substance use.

Acknowledgments

This study was made possible with Award Number K23HD059916 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development awarded to Dr. Temple. This work was also supported, in part, by Grants F31AA020131 (Ryan Shorey) and K24AA019707 (Dr. Stuart) from the National Institute on Alcohol Abuse and Alcoholism (NIAAA). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health and Human Development or the National Institutes of Health. This study was also made possible with funding to Dr. Temple by the Hogg Foundation for Mental Health (JRG-082) and the John Sealy Memorial Endowment Fund for Biomedical Research. This work could not have been conducted without the permission and assistance of the schools and school districts.

Contributor Information

Ryan C. Shorey, University of Tennessee, Knoxville, TN, USA

Paula J. Fite, University of Kansas, Lawrence, TN, USA

Sara R. Elkins, University of Tennessee, Knoxville, TN, USA

Kevin C. Frissell, Westat, Rockville, MD, USA

Susan R. Tortolero, University of Texas School of Public Health, Dallas, TX, USA

Gregory L. Stuart, University of Tennessee, Knoxville, TN, USA

Jeff R. Temple, UTMB Health, Galveston, TX, USA

References

  1. Aiken LS, West SG. Multiple regression: Testing and interpreting interactions. Sage; Thousands Oaks, CA: 1991. [Google Scholar]
  2. Arbuckle JL. Full information estimation in the presence of incomplete data. In: Marcoulides GA, Shumaker RE, editors. Advances structural equation modeling: Issues and techniques. Erlbaum; Mahwah, NJ: 1996. pp. 243–277. [Google Scholar]
  3. Arthur M, Hawkins JD, Pollard JA, Catalano RF, Baglioni AJ. Measuring risk and protective factors for substance use, delinquency, and other adolescent problem behaviors: The communities that care youth survey. Evaluation Review. 2002;26:575–601. doi: 10.1177/0193841X0202600601. doi:10.1177/019384102237850. [DOI] [PubMed] [Google Scholar]
  4. Bahr SJ, Marcos AC, Maughan SL. Family, educational and peer influences on the alcohol use of female and male adolescents. Journal of Studies on Alcohol. 1995;56:457–469. doi: 10.15288/jsa.1995.56.457. [DOI] [PubMed] [Google Scholar]
  5. Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review. 1977;84:191–215. doi: 10.1037//0033-295x.84.2.191. doi:10.1016/0146-6402(78)90002-4. [DOI] [PubMed] [Google Scholar]
  6. Barnard M, McKeganey N. The impact of parental problem drug use on children: What is the problem and what can be done to help? Addiction. 2004;99:552–559. doi: 10.1111/j.1360-0443.2003.00664.x. doi:10.1111/j.1360-0443.2003.00664.x. [DOI] [PubMed] [Google Scholar]
  7. Barnes GM, Farrell MP, Banerjee S. Family influences on alcohol abuse and other problem behaviors among black and white adolescents in a general population sample. Journal of Research on Adolescence. 1994;4:183–201. doi:10.1207/s15327795jra0402_2. [Google Scholar]
  8. Bjerregaard B, Smith C. Gender differences in gang participation, delinquency and substance use. Journal of Quantitative Criminology. 1993;9:329–355. doi:10.1007/BF01064108. [Google Scholar]
  9. Breivik K, Olweus D. Adolescents’ adjustment in four postdivorce family structures: Single mother, stepfather, joint physical custody and single father families. Journal of Divorce and Remarriage. 2006;44:99–124. [Google Scholar]
  10. Brook JS, Balka EB, Crossman AM, Dermatis H, Galanter M, Brook DW. The relationship between parental alcohol use, early and late adolescent alcohol use, and young adult psychological symptoms: A longitudinal study. The American Journal of Addictions. 2001;19:534–542. doi: 10.1111/j.1521-0391.2010.00083.x. doi:10.1111/j.1521-0391.2010.00083.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chassin L, Barrera M. Substance use escalation and substance use restraint among adolescent children of alcoholics. Psychology of Addictive Behaviors. 1993;7:3–20. doi:10.1037//0893-164X.7.1.3. [Google Scholar]
  12. Chassin L, Curran PJ, Hussong AM, Colder CR. The relation of parent alcoholism to adolescent substance use: A longitudinal follow-up study. Journal of Abnormal Psychology. 1996;105:70–80. doi: 10.1037//0021-843x.105.1.70. doi:10.1037//0021-843X.105.1.70. [DOI] [PubMed] [Google Scholar]
  13. Chassin L, Ritter J, Trim RS, King KM. Adolescent substance abuse disorders. In: Mash EL, Barkley RA, editors. Child psychopathology. 2nd ed. Guilford; New York: 2003. pp. 199–230. [Google Scholar]
  14. Choquet M, Hassler C, Morin D, Falissard B, Chau N. Perceived parenting styles and tobacco, alcohol and cannabis use among French adolescents: Gender and family structure differentials. Alcohol and Alcoholism. 2008;43:73–80. doi: 10.1093/alcalc/agm060. doi:10.1093/alcalc/agm060. [DOI] [PubMed] [Google Scholar]
  15. Clark HK, Shamblen SR, Ringwalt CL, Hanley S. Predicting high risk adolescents’ substance use over time: The role of parental monitoring. Journal of Primary Prevention. 2012;33:66–77. doi: 10.1007/s10935-012-0266-z. doi:10.1007/s10935-012-0266-z. [DOI] [PubMed] [Google Scholar]
  16. Cleveland MJ, Feinberg ME, Greenberg MT. Protective families in high—And low-risk environments: Implications for adolescent substance use. Journal of Youth and Adolescence. 2010;39:114–126. doi: 10.1007/s10964-009-9395-y. doi:10.1007/s10964-009-9395-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Crouter AC, McHale SM. Temporal rhythms in family life: Seasonal variation in the relation between parental work and family processes. Developmental Psychology. 1993;29:198–205. doi:10.1037//0012-1649.29.2.198. [Google Scholar]
  18. Dishion TJ, Kavanagh K. Intervening in adolescent problem behavior: A family-centered approach. Guilford Press; New York: 2003. [Google Scholar]
  19. Dishion TJ, Patterson GR, Reid JR. Parent and peer factors associated with drug sampling in early adolescence: Implications for treatment. In: Rahdert ER, Grabowski J, editors. Adolescent drug abuse: Analyses of treatment research. National Institute on Drug Abuse; Rockville, MD: 1988. pp. 69–93. NIDA Research Monograph No. 77, DHHS Publication No. ADM88-1523. [PubMed] [Google Scholar]
  20. Ellickson PL, Morton SC. Identifying adolescents at risk for hard drug use: Racial/ethnic variations. Journal of Adolescent Health. 1999;25:382–395. doi: 10.1016/s1054-139x(98)00144-x. doi:10.1016/S1054-139X(98)00144-X. [DOI] [PubMed] [Google Scholar]
  21. Engels RCME, Van der Vorst H. The roles of parents in adolescent and peer alcohol consumption. Netherlands’ Journal of Social Sciences. 2003;39:53–68. [Google Scholar]
  22. Epstein JA, Williams C, Botvin GJ. How universal are social influences to drink and problem behaviors for alcohol use? A test comparing urban African-American and Caribbean-American adolescents. Addictive Behaviors. 2002;27:75–86. doi: 10.1016/s0306-4603(00)00165-9. [DOI] [PubMed] [Google Scholar]
  23. Farrell MP, Barnes GM, Barerjee S. Family cohesion as a buffer against the effects of problem-drinking fathers on psychological distress, deviant behavior, and heavy drinking in adolescents. Journal of Health Social Behavior. 1995;36:377–385. doi:10.2307/2137326. [PubMed] [Google Scholar]
  24. Griffin KW, Botvin GJ, Scheier LM, Diaz T, Miller N. Parenting practices as predictors of substance use, delinquency, and aggression among urban minority youth: Moderating effects of family structure and gender. Psychology of Addictive Behaviors. 2000;14:174–184. doi: 10.1037//0893-164x.14.2.174. doi:10.1037//0893-164X.14.2.174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Hawkins JD, Catalano RF, Miller JY. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin. 1992;112:64–105. doi: 10.1037/0033-2909.112.1.64. doi:10.1037//0033-2909.112.1.64. [DOI] [PubMed] [Google Scholar]
  26. Hill SY, Shen S, Lowers L, Locke J. Factors predicting the onset of adolescent drinking in families at high risk for developing alcoholism. Biological Psychiatry. 2000;48:265–275. doi: 10.1016/s0006-3223(00)00841-6. doi:10.1016/S0006-3223(00)00841-6. [DOI] [PubMed] [Google Scholar]
  27. Hirschi T. Causes of delinquency. University of California Press; Berkeley: 1969. [Google Scholar]
  28. Jackson C. Initial and experimental stages of tobacco and alcohol use during late childhood: Relation to peer, parent, and personal risk factors. Addictive Behaviors. 1997;22:598–685. doi: 10.1016/s0306-4603(97)00005-1. doi:10.1016/S0306-4603(97)00005-1. [DOI] [PubMed] [Google Scholar]
  29. Johnston LD, O'Malley PM, Bachman JG. US Government Printing Office; Washington, DC: 1999. National survey results on drug use from the monitoring the future study, 1975–1998. Secondary school students. (Vol. 1, NIH Publication No. 99-4660) [Google Scholar]
  30. Johnston LD, O'Malley PM, Bachman JG, Schulenberg JE. Monitoring the future national survey results on drug use, 1975–2009. Secondary school students. I. National Institute on Drug Abuse; Bethesda, MD: 2010. NIH Publication No. 10-7584. [Google Scholar]
  31. Kandel DB. The parental and peer contexts of adolescent deviance: An algebra of interpersonal influences. Journal of Drug Issues. 1996;26:289–315. [Google Scholar]
  32. Kelly AB, O'Flaherty M, Toumbourou JW, Connor JP, Hemphill SA, Catalano RF. Gender differences in the impact of families on alcohol use: A lagged longitudinal study of early adolescents. Addiction. 2011;106:1427–1436. doi: 10.1111/j.1360-0443.2011.03435.x. doi:10.1111/j.1360-0443.2011. 03435.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kendler KS, Karkowski LM, Prescott CA. Hallucinogen, opiate, sedative, and stimulant use and abuse in a population-based sample of female twins. Acta Psychiatrica Scandinavica. 1999;99:368–376. doi: 10.1111/j.1600-0447.1999.tb07243.x. [DOI] [PubMed] [Google Scholar]
  34. Kerr M, Stattin H. What parents know, how they know it, and several forms of adolescent adjustment: Further support for a reinterpretation of monitoring. Developmental Psychology. 2000;36:366–380. doi:10.1037//0012-1649.36.3.366. [PubMed] [Google Scholar]
  35. Kerr M, Stattin H, Burk WJ. A reinterpretation of parental monitoring in longitudinal perspective. Journal of Research on Adolescence. 2010;20:39–64. doi:10.1111/j.1532-7795.2009.00623.x. [Google Scholar]
  36. King KM, Chassin L. Mediating and moderated effects of adolescent behavioral undercontrol and parenting in the prediction of drug use disorders in emerging adulthood. Psychology of Addictive Behaviors. 2004;18:239–249. doi: 10.1037/0893-164X.18.3.239. doi:10.1037/0893-164X.18.3.239. [DOI] [PubMed] [Google Scholar]
  37. Kline RB. Principles and practice of structural equation modeling. 2nd ed. Guilford Press; New York: 2005. [Google Scholar]
  38. Lac A, Crano WD. Monitoring matters: Meta-analytic review reveals the reliable linkage of parental monitoring with adolescent marijuana use. Perspectives on Psychological Science. 2009;4:578–586. doi: 10.1111/j.1745-6924.2009.01166.x. doi:10.1111/j.1745-6924.2009.01166.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Laird RD, Pettit GS, Bates JE, Dodge KA. Parents’ monitoring-relevant knowledge and adolescents’ delinquent behavior: Evidence of correlated developmental changes and reciprocal influences. Child Development. 2003;74:752–768. doi: 10.1111/1467-8624.00566. doi:10.1111/1467-8624.00566. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lockman JE. Preventive intervention targeting precursors. In: Sloboda Z, Bukoski WJ, editors. Handbook of drug abuse prevention: Theory, science, and practice. Kluwer Academic/Plenum; New York: 2003. pp. 307–326. [Google Scholar]
  41. MacKinnon DP, Dwyer JH. Estimating mediated effects in previous studies. Evaluation Review. 1993;17:141–158. [Google Scholar]
  42. MacKinnon DP, Lockwood CM, Williams J. Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research. 2004;39:99–128. doi: 10.1207/s15327906mbr3901_4. doi:10.1207/s15327906mbr3901_4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Miller MA, Alberts JK, Hecht ML, Trost MR, Krizek RL. Adolescent relationships and drug use. Lawrence Erlbaum Associates; Mahwah, NJ: 2009. [Google Scholar]
  44. Muthén BO. A general structural equation model with dichotomous, ordered categorical and continuous latent variable indicator. Psychometrika. 1984;49:115–132. doi:10.1007/BF02294210. [Google Scholar]
  45. Muthén LK, Muthén B. Mplus: The comprehensive modeling program for applied researchers. Muthén & Muthén; Los Angeles, CA: 2006. [Google Scholar]
  46. Padilla-Walker LM, Nelson LJ, Madsen SD, McNamara-Barry CM. The role of perceived parental knowledge on emerging adults’ risk behaviors. Journal of Youth Adolescence. 2008;37:847–859. doi:10.1007/s10964-007-9268-1. [Google Scholar]
  47. Rutherford MJ, Cacciola JS, Alterman AI, McKay JR, Cook TJ. Young men's perceived quality of parenting based on familial history of alcoholism. Journal of Child and Adolescent Substance Abuse. 1997;6:43–56. doi:10.1300/J029v06n03_03. [Google Scholar]
  48. Ryan SM, Jorm AF, Lubman DI. Parenting factors associated with reduced adolescent alcohol use. A systematic review of longitudinal studies. Australian Journal of Psychiatry. 2010;44:774–783. doi: 10.1080/00048674.2010.501759. doi:10.1080/00048674.2010.501759. [DOI] [PubMed] [Google Scholar]
  49. Schinke SP, Fang L, Cole KCA. Substance use among early adolescent girls: Risk and protective factors. Journal of Adolescent Health. 2008;43:191–194. doi: 10.1016/j.jadohealth.2007.12.014. doi:10.1016/j.jadohealth.2007.12.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Schuckit MA. An overview of genetic influences in alcoholism. Journal of Substance Abuse Treatment. 2009;36:5–14. [PubMed] [Google Scholar]
  51. Substance Abuse and Mental Health Services Administration (SAMSHA) Results from the 2010–2011 national survey on drug use and health: Summary of national findings. Rockville, MD.: 2012. [Google Scholar]
  52. Temple JR, Shorey RC, Fite PJ, Stuart GL, Le VD. Substance use as a longitudinal predictor of the perpetration of teen dating violence. Journal of Youth and Adolescence. 2013a;42:596–606. doi: 10.1007/s10964-012-9877-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Temple JR, Shorey RC, Tortolero S, Wolfe DA, Stuart GL. Importance of attitudes about violence and gender in the relationship between exposure to interparental violence and the perpetration of teen dating violence. Child Abuse and Neglect. 2013b;37:343–352. doi: 10.1016/j.chiabu.2013.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Turner WL, Wallace B. African American substance use: Epidemiology, prevention, and treatment. Violence Against Women. 2003;9:576–589. doi:10.1177/1077801202250452. [Google Scholar]
  55. Van der Vorst H, Engels RCME, Meeus W, Dekovic M, Vermulst A. Parental attachment, parental control, and early development of alcohol use: A longitudinal study. Psychology of Addictive Behaviors. 2006;20:107–116. doi: 10.1037/0893-164X.20.2.107. doi:10.1037/0893-164X.20.2.107. [DOI] [PubMed] [Google Scholar]
  56. Van der Zwaluw CS, Scholte RHJ, Vermulst AA, Buitelaar JK, Verkes RJ, Engels RCME. Parental problem drinking, parenting, and adolescent alcohol use. Journal of Behavioral Medicine. 2008;31:189–200. doi: 10.1007/s10865-007-9146-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Vega WA, Zimmerman RS, Warheit GJ, Apospori E, Gil AG. Risk factors for early adolescent drug use in four ethnic and racial groups. American Journal of Public Health. 1993;83:185–189. doi: 10.2105/ajph.83.2.185. doi:10.1001/jama.294.22.2843-a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Waizenhofer RN, Buchanan CM, Jackson-Newsom J. Mothers’ and fathers’ knowledge of adolescents’ daily activities: Its sources and its links with adolescent adjustment. Journal of Family Psychology. 2004;18:348–360. doi: 10.1037/0893-3200.18.2.348. doi:10.1093/jpepsy/jsj087. [DOI] [PubMed] [Google Scholar]
  59. Wu ZH, Temple JR, Shokar NK, Nguyen-Oghalai TU, Grady JJ. Differential racial/ethnic patterns in substance use initiation among young, low-income women. American Journal of Drug and Alcohol Abuse. 2010;36:123–129. doi: 10.3109/00952991003718072. [DOI] [PubMed] [Google Scholar]
  60. York JL, Welte J, Hirsch J, Hoffman JH, Barnes G. Association of age at first drink with current alcohol drinking variables in a national general population sample. Alcoholism, Clinical and Experimental Research. 2004;28:1379–1387. doi: 10.1097/01.alc.0000139812.98173.a4. doi:10.1097/01.ALC.0000139812.98173.A4. [DOI] [PubMed] [Google Scholar]
  61. Yu CY, Muthén BO. Technical report. University of California, Los Angeles, Graduate School of Education and Information Studies; Los Angeles: 2001. Evaluation of model fit indices for latent variable models with categorical and continuous outcomes. [Google Scholar]
  62. Zhang L, Welte JW, Wieczorek WF. The influence of parental drinking and closeness on adolescent drinking. Journal of Studies on Alcohol. 1999;60:245–251. doi: 10.15288/jsa.1999.60.245. [DOI] [PubMed] [Google Scholar]

RESOURCES