Necessary, But Not Sufficient: The Importance of

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Journal of Social Work Practice in the Addictions, 10:377–392, 2010 Copyright © Taylor & Francis Group, LLC ISSN: 1533-256X print/1533-2578 online DOI: 10.1080/1533256X.2010.498743

Necessary, But Not Sufficient: The Importance of Family and School for Youth at Risk of Heavy Episodic Drinking LYNN MILGRAM MAYER, MSW, PHD Assistant Professor, National Catholic School of Social Service, The Catholic University of America, Washington, DC, USA

WENDY WHITING BLOME, MSW, PHD Associate Professor, National Catholic School of Social Service, The Catholic University of America, Washington, DC, USA

Adolescent heavy episodic drinking is of significant concern to social workers. This secondary analysis uses the 2007 National Survey on Drug Use and Health to explore the relationship of family and school factors to adolescent heavy episodic drinking. The sample included 17,727 adolescents between the ages of 12 and 17. The findings indicate that family and school factors are protective on the bivariate level. Yet, the hypotheses were only partially supported on the multivariate level, demonstrating that risk is cumulative. The data suggest that social work interventions must be sustained, implemented within multiple environments, and begun prior to adolescence. KEYWORDS adolescents, alcohol abuse, heavy episodic drinking, prevention, protective factors, risk factors The majority of teenagers (72%) have consumed some alcohol by the end of their high school years (Johnston, O’Malley, Bachman, & Schulenberg, 2009). Alcohol is the drug of choice for adolescents, with 45% of high school seniors, 34% of tenth graders, and 17% of eighth graders reporting the use of alcohol in the past month—more than cigarettes and marijuana combined

Received January 5, 2010; accepted April 19, 2010. Address correspondence to Lynn Milgram Mayer, National Catholic School of Social Service, The Catholic University of America, 620 Michigan Ave NE, Washington, DC 20064, USA. E-mail: [email protected] 377

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(National Institute on Alcohol Abuse and Alcoholism, 2009). Of particular concern are teens who drink heavily. The definition of binge drinking, adopted by the Substance Abuse and Mental Health Services Administration (SAMHSA, 2005), refers to drinking five or more drinks on the same occasion on at least 1 day in the past 30 days. Excessive consumption has been related to negative outcomes, including higher risk for injuries and death in accidents, academic problems, legal troubles, and sexual assaults and early sexual behavior (Kodjo & Klein, 2002; Office of the Surgeon General, 2007). The Office of the Surgeon General (2007) issued a call to action asking every member of society to recognize that “Underage alcohol use remains a major public health and safety problem in the United States, creating serious personal, social, and economic consequences for adolescents, their families, communities, and the Nation as a whole” (p. 75). The purpose of this research is to explore how family and school factors influence the likelihood that an adolescent will engage in heavy episodic drinking. This research is a secondary analysis of data from the 2007 National Survey on Drug Use and Health (NSDUH; U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of Applied Studies, 2007).

LITERATURE REVIEW Levels of heavy episodic drinking increased modestly in the early and mid1990s and then leveled off until 2002 when a decline in drinking and drunkenness began to appear in all grades (Johnston et al., 2009). The risk and protective factors that affect the drinking behavior of teenagers are important to policy and service delivery. It might be that the number of risk factors present in the life of an individual is a more powerful predictor than the presence of a specific risk factor (Sameroff et al., 1998, in Arthur, Hawkins, Pollard, Catalano, & Baglioni, 2002). A five-state sample of sixth- through twelfth-grade students reiterated the interactive relationship between overall levels of risk and protection. The effects of protective factors were greatest at the highest levels of risk exposure, yet high levels of protection did not eliminate problem behaviors among those exposed to high levels of risk (Pollard, Hawkins, & Arthur, 1999). “For example, easy home access to substances is a risk factor associated with adolescent substance use. However, low access to substances at home is not inevitably a protective factor” (Meschke & Patterson, 2003, p. 490). A review of demographic, family, school, and individual risk factors suggests a complicated interrelationship among issues. Using an ecological approach to review the multiple systems affecting the lives of a sample of youths, Hilarski (2005) found exposure to violence to be related to substance

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use. The social stress model equates “the likelihood of an adolescent engaging in drug usage is a function of the stress level and the extent to which it is offset by stress moderators, social networks, social competencies, and resources” (Rhodes & Jason, 1990, p. 396). Testing the model supported the notion that weak parental relationships, a perceived lack of support, and significant family problems were related to a high level of usage (Rhodes & Jason, 1990). A more recent analysis, using structural equation modeling, of risk and protective factors found major risk factors for substance use included peer pressure, negative family atmosphere, school difficulties, and psychopathology. Knowledge about substance use was a protective factor (Rumpold et al., 2006). The transition to early adolescence and the movement to emerging adulthood have been shown to be periods of vulnerability for youth. Adolescence is a critical time of development in social, physical, and psychological areas. “Given the intense level of instability and change associated with adolescence, the potential effect of a particular risk or protective factor is likely to be intensified” (Meschke & Patterson, 2003, p. 490).

Family Factors A classic article reviewing risk and protective factors associated with alcohol use reviewed the impact of family modeling of substance use behavior and parental attitudes toward drug and alcohol use of children. Poor parenting practices, high levels of conflict in the family, and parent–child relationships characterized by a lack of closeness increased the risk for adolescent problem behaviors including the abuse of alcohol (Brook, Brook, Gordon, Whiteman, & Cohen, 1990, in Hawkins, Catalano, & Miller, 1992). The importance of families as protective factors has been documented in the literature for years. Recently, Wang, Matthew, Bellamy, and James (2005) used structural equation modeling to identify direct effects among variables and found that family involvement was a significant predictor of self-control skills and that family supervision was most effective in enhancing the self-control of girls. Adolescents who recount healthy relationships and open communication with parents and who receive emotional support report less substance use (Patton, 1995). Families with established routines, such as dinners together and sports and school activities, experience more parental supervision and support (Patton, 1995). How parents talk about alcohol use with their adolescents is also an important component of open communication. Analyzed narratives of parent–offspring pairs found two thirds reported integrating opinions and information into the fabric of everyday lives rather than relying on a targeted one-time talk on substance use (Miller-Day & Dodd, 2004).

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School Factors Schools are a significant force in the lives of youth. High levels of school connectedness have been associated with less frequent alcohol use for a nationwide group of students in Grades 7 through 12 (Resnick et al., 1997, in Meschke & Patterson, 2003). Another study showed that a high sense of community at school was related to less substance use (Battistich & Horn, 1997). Studies have confirmed that supportive school environments that hold high expectations for achievement protect against youth drinking (National Center on Addiction and Substance Abuse, 2003b). School peers have long been recognized as a pervasive force in the behavior and attitudes of adolescents. Having friends who use drugs is a strong predictor of substance use (Kodjo & Klein, 2002). Of the youths’ primary socialization sources—peers, family, and school—the peer cluster has been identified as the dominant socialization force directly affecting substance use and other risky behaviors (Kim, Zane, & Hong, 2002). A moderate correlation was found between having peers who have favorable attitudes toward drug use and consuming alcohol in the past 30 days (Arthur et al., 2002). When friends use alcohol, there is a greater likelihood that an individual adolescent will use or abuse alcohol according to a study that related parental, sibling, and peer influences on behaviors (Windle, 2000).

Other Factors Gender differences in alcohol use in the United States have changed over time. An annual, long-term study initiated in 1975 has tracked usage patterns as well as attitudes. The findings revealed that males generally engaged in more heavy drinking; however, the usage by girls increased in the high school years (Johnston et al., 2009). “High school girls drink alcohol at rates close to those of boys (45 percent vs. 49.2 percent) and rates of drinking among the youngest high school girls and boys—ninth graders—are almost the same (40 percent vs. 42.2 percent)” (National Center on Addiction and Substance Abuse, 2003a, p. 3). Excessive drinking is found in all ethnic and racial groups. Mexican American youth were found to use alcohol less frequently than non-Hispanic White students, but were more likely to drink excessively (Swaim, Wayman, & Chen, 2004). Asian and Black/African American youth reported less heavy drinking than Hispanics, American Indians, or Whites (SAMHSA, Office of Applied Studies, 2002). Ethnicity is also a protective factor. In Hispanic families, for example, family connectedness, family supervision, and parental disapproval of use were related to less alcohol use, regardless of gender or age (Sale et al., 2005). Protective factors within African American families also support resiliency in children. Exhibiting nurturing, caring parental behaviors; setting high expectations for children in academics,

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and encouraging participation in recreational and family activities were identified as protective factors related to resiliency in African American adolescents (Calvert, 1997). Questionnaires completed by African American and Hispanic youth were analyzed to determine if substance-abusing behavior could be predicted by multiple factors: individual (depression, anxiety, gender, age, ethnicity), microsystem (life events, support, attachment), and exosystem (violence exposure; Hilarski, 2005). The results indicated that youth with higher depression scores, problems with caregivers, and exposure to violence tended to report more substance use. Additionally, males who reported more difficulties with primary caregivers reported more substance use (Hilarski, 2005). Analysis of binge drinking by grade and race shows African American eighth-, tenth-, and twelfth-grade youth were less likely to drink to excess than their White counterparts. Specifically, “while up to a third of white young people are binge drinkers by their senior year in high school, less than 15 percent of African American seniors drink at this level” (Wallace & Muroff, 2002, p. 247).

HYPOTHESES Based on the review of the literature, this study posits two hypotheses. First, adolescents who miss more days of school, have lower grades, have more peers who drink alcohol regularly, have poor relationships with teachers, and have less commitment to school will engage in more heavy episodic drinking. Second, adolescents who expect their parents to moderately disapprove of substance use, have more parent–child conflict, have less parent involvement, and have less communication with parents about substance use will engage in more heavy episodic drinking.

METHOD This research is a secondary data analysis of the 2007 NSDUH publically available from SAMHSA. Since its inception in 1971, NSDUH data have been used by policymakers to monitor alcohol and drug use in the United States (Jordan, Karg, Batts, Epstein, & Wiesen, 2008). NSDUH uses an ongoing, multistage probability survey design to gather data on substance use and abuse in the U.S. population. The questionnaires are administered to a representative sample of the population through face-to-face interviews. For the 2007 NSDUH survey, 158,411 eligible households were sampled, 141,487 addresses were screened, and 67,870 completed interviews were obtained from individuals 12 and older, yielding a weighted screening response rate of 89.5% (SAMHSA, Office of Applied Studies, 2008). The weighted interview response rate was 73.9%, and specifically for adolescents aged

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12 to 17, the weighted interview rate was 85.4% (SAMHSA, Office of Applied Studies, 2008). Data were weighted to yield estimates of the U.S. population. The sample size of the 2007 public use file was 67,870 (SAMSHA, 2008). The study sample for this analysis included 17,727 respondents who were between 12 and 17 years of age. This analysis of heavy episodic drinking among adolescents was approved by the Committee for the Protection of Human Subjects at The Catholic University of America.

Measurement DEPENDENT

VARIABLE

The dependent variable was heavy episodic drinking. The NSDUH asked respondents to self-report whether they have had five or more drinks on the same occasion on at least 1 day in the past 30 days. Occasion was defined as having the drinks at the same time or within a couple of hours of each other (SAMSHA, 2008). NSDUH labeled this variable binge drinking, but for this study, it was renamed heavy episodic drinking. INDEPENDENT

VARIABLES

The covariates were grouped into three categories: demographic, family, and school characteristics. These categories were then used to build multivariate models. Demographic characteristics included four variables: respondent age, gender, race, and family income. Respondent age was recoded from a categorical to a continuous variable, ranging from 12 to 17. Gender was scored as male (0) or female (1), with missing values excluded from the analysis. Race was recoded into four groups: White, Black, Hispanic, and other. Native Hawaiian and Pacific Islander, Asian, Native American, and more than one race were included in the other group. Family income was not included as a continuous variable in the NSDUH data set; it was scored as less than $20,000, $20,000 to $49,999, $50,000 to $74,999, and $75,000 or more. Family characteristics included four variables: parental attitudes about substance use, parent involvement, parent–child communication about substance use, and parent–child conflict. Parental attitudes about substance use was constructed by combining four NSDUH items into a scale: parents’ feelings about smoking, parents’ feelings about trying marijuana, parents’ feelings about using marijuana monthly, and parents’ feelings about daily drinking. Each of these items asked the youth to report whether her or his parent neither approved nor disapproved (0), somewhat disapproved (1), or strongly disapproved (2). This scale demonstrated adequate internal consistency (Cronbach’s α = .85). A parent involvement scale was created using seven items. Each of the seven items used a 4-point Likert scale, ranging from

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always to never, to ask the youths if their parents did the following in the past 12 months: made the youth do chores, limited television, limited time out with friends on school nights, checked homework, helped with homework, let the youth know that she or he had “done a good job,” and said they were proud of the youth. These items were recoded before constructing the scale to 0 (never), 1 (seldom), 2 (sometimes), and 3 (always). This scale demonstrated adequate internal consistency (Cronbach’s α = .66). Parent– child communication about substance use was measured by the response to one item: “During the past 12 months, have you talked with at least one of your parents about the dangers of tobacco, alcohol, or drug use?” The item was recoded so that no = 0 and yes = 1. Parent–child conflict was measured by the number of arguments with parents in the past 12 months, with possible responses of 1 (no arguments), 1 (one or two arguments), 2 (three to five arguments), 3 (six to nine arguments), and 4 (10 or more arguments). School characteristics included five variables: days missed from school, grades, peers who drink alcohol, teacher–student relationship, and attitude toward school. Days missed from school was measured by one ratio level item that asked the youth to self-report during the past 30 days, “How many whole days did you miss because you skipped or ‘cut’ or just didn’t want to be there?” Grades was measured by asking youth to report their grade average for the last semester and was recoded such that A+, A, or A− = 3; B+, B, or B− = 2; C+, C, or C− = 1; D or less than D = 0; and school does not give these grades = missing data. Peers who drink alcohol was measured by “How many of the students in your grade at school would you say drink alcoholic beverages?” Responses were recoded 0 (none of them), 1 (a few of them), 2 (most of them), and 3 (all of them). Teacher–student relationship was measured by “During the past 12 months, how often did your teachers at school let you know when you were doing a good job with your school work?” Responses ranged from 0 (never), 1 (seldom), 2 (sometimes), and 3 (always). Attitude toward school was measured by a four-item scale: overall feeling about attending school, feeling that school was meaningful, feeling that things learned in school were important, and feeling that school was interesting. Each of these items was scored on a 4-point Likert scale and was recoded so that the most positive response was 3 and the most negative response was 0. The attitude toward school scale demonstrated adequate internal consistency (Cronbach’s α = .76).

Statistical Analysis SPSS version 16 was used to conduct all of the analyses (Statistical Package for the Social Sciences, 2008). The multivariate hypotheses were analyzed using binary logistic regression. Binary logistic regression was appropriate for this analysis because the dependent variable, heavy episodic drinking, was coded as a dichotomous variable (no = 0 yes = 1). A stepwise

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multivariate model was developed for analyzing heavy episodic drinking: demographic characteristics were entered on the first step, followed by family characteristics and then school characteristics.

RESULTS Demographic Characteristics Table 1 contains the descriptive data on the demographic characteristics, including weighted and unweighted percentages. The sample was fairly evenly distributed by gender, with 52% male and 48% female. The ethnicity was predominately White (60%) with 14% Black, 17% Hispanic, and 9% other. The sample was evenly distributed by age: 31.7% were young teens aged 12 and 13, 33.6% were middle teens, and 34.7% were older teens ages 16 and 17. Family income was bimodal with 32.2% in the $20,000 to $49,999 income level and 30.5 % in the $75,000 or more level; less than $20,000 was reported by 17.7% of the sample. An income of between $50,000 and $74,999 was reported for 19.6%. TABLE 1 Demographic Characteristics Among Heavy Episodic Drinkers and Non-Heavy Episodic Drinkers Heavy episodic drinkers

Total n All study sample 17,727 Gender Male 9,160 Female 8,567 Age of respondent 12 2,716 13 2,911 14 2,865 15 3,079 16 3,124 17 3,032 Race/ethnicity White 10,599 Black 2,437 Hispanic 3,063 Other 1,628 Family income Less than $20,000 3,133 $20,000 to $49,999 5,713 $50,000 to $74,999 3,481 $75,000 or more 5,400 a

Unweighted. b Weighted.

%uwta %wtb 100

100

n

%uwta %wtb

Non-heavy episodic drinkers n

%wtb

89.6

90.2

1,841

10.4

51.7 48.3

51.1 1,037 48.9 804

56.3 43.7

55.0 45.0

8,123 7,763

51.1 48.9

50.6 49.4

15.3 16.4 16.2 17.4 17.6 17.1

16.1 16.3 16.3 17.5 17.5 16.4

26 69 157 352 504 733

1.4 3.7 8.5 19.1 27.4 39.8

1.5 3.6 7.8 19.7 26.9 40.5

2,690 2,842 2,708 2,727 2,620 2,299

16.9 17.9 17.0 17.2 16.5 14.5

17.6 17.7 17.2 17.3 16.5 13.8

59.8 13.7 17.3 9.2

59.6 1,267 15.2 109 18.5 333 6.6 132

68.8 5.9 18.1 7.2

70.1 6.7 18.1 5.1

9,332 2,328 2,730 1,496

58.7 14.7 17.2 9.4

58.5 16.2 18.5 6.8

17.7 32.2 19.6 30.5

17.0 30.6 18.2 34.2

16.2 31.3 20.0 32.4

15.9 30.9 17.4 35.8

2,834 5,137 3,112 4,803

17.8 32.3 19.6 30.2

17.1 30.5 18.2 34.1

299 576 369 597

9.8 15, 886

%uwta

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Adolescent Heavy Episodic Drinking

Of the 17,727 total youth in the sample, 10.4% met the criteria for heavy episodic drinking. Males were more likely to drink heavily (56.3%) compared to 43.7% of the female sample. Older adolescents were more likely to engage in heavy episodic drinking than younger adolescents, with 67% of 16- and 17-year-olds compared to 33% of 12- to 15-year-olds. The majority of heavy episodic drinkers were White youth (68.8%), compared to all the others in the sample (31.2%). The distribution of youth in the sample who drink follows the bimodal family income distributions. Specifically, close to a third with family incomes of $20,000 to $49,999 and those over $75,000 reported excessive drinking (31.3% and 32.4%, respectively). Less heavy episodic drinking (16.2%) was reported in the below $20,000 family income category and the $50,000 to $74,999 (20%) family income category.

Bivariate Analysis Bivariate results are presented in Table 2. Because of the large sample size of 17,727 adolescents, all of the coefficients were significant. Heavy episodic drinking was found to have significant, positive linear relationships with parent–child conflict, days missed from school, and school peers who drink alcohol. Youth who had more parent–child conflict (r = .13) and peers who drink (r = .26) were more likely to engage in heavy episodic drinking; these youth were also more likely to report more days missed TABLE 2 Correlations Among Family Characteristics, School Characteristics, and Heavy Episodic Drinking 1 Family characteristics 1. Parent attitude substance use 2. Parent involvement 3. Communication substance use 4. Parent–child conflict School characteristics 5. Days missed school 6. Grades 7. School peers drink alcohol 8. Teacher–student relationship 9. Attitude toward school Alcohol use 10. Heavy episodic drinking ∗

p ≤ .05.

2

3

— .25∗



4

5

6

7

8

9

10

— .18∗ .08∗

−.01 −.18∗ −.00



−.11∗ −.12∗ −.03∗ .06∗ — .13∗ .15∗ .13∗ −.03∗ −.16∗ — −.11∗ −.25∗ −.02∗ .24∗ .11∗ −.11∗



.04∗

.25∗

.12∗ −.17∗ −.07∗

.23∗ −.15∗



.09∗

.31∗

.15∗ −.28∗ −.11∗

.24∗ −.23∗

.43∗

−.20∗ −.17∗ −.02∗

.13∗

.16∗ −.13∗



.26∗ −.08∗ −.16∗



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from school (r = 16). Heavy episodic drinking was found to have significant negative linear relationships with parent attitude toward substance use, parent involvement, parent–child communication about substance use, grades, teacher–student relationship, and attitude toward school. Youth who had parents who were perceived to be more negative about substance use (r = −.20), who were more involved in their lives (r = −.17), and who talked with their children about substance abuse (r = −.02) were less likely to engage in heavy episodic drinking. Youth who had better grades (r = −.13), positive relationships with their teachers (r = −.08), and better attitudes toward school (r = −.16) were also less likely to engage in excessive drinking.

Multivariate Analyses The results of multivariate analyses are presented in Table 3. For Model 1, demographic variables were entered in this order: age, gender, family income, White, Black, and Hispanic. Model 2 included the demographic variables in the first block and added family characteristics in the second. Family characteristics were added in this order: parent feelings about substance use, parent involvement, parent–child communication about substance abuse, and parent–child conflict. Model 3 entered the demographic characteristics, followed by the family characteristics, and then added the school characteristics. The school characteristics were entered in the order of days missed from school, grades, school peers who drink alcohol, teacher–student relationship, and attitude toward school. In Model 3, all demographic variables were significant. Youth who were older, White, and from families with higher incomes had higher odds of heavy episodic drinking. For each increase of a year in age, the odds of binge drinking increased by 51% (OR = 1.51, p < .001). White youth compared to others were 1.60 times more likely to binge drink (p < .001). Hispanic youth compared to others were 1.43 times more likely to binge drink (p < .05). Black youth were 52% less likely to binge drink (OR = .48, p < .001). Youth from more affluent families had higher odds of binge drinking (OR = 1.11, p < .01). Females were 30% less likely to binge drink (OR = .70, p < .001). In Model 3, all family characteristic variables were significant. Youth who communicated about substance use with their parents and who had more parent–child conflict had a higher odds of heavy episodic drinking (OR = 1.20, p < .01 and OR = 1.13, p < .001, respectively). Youth who reported negative parental attitudes toward substance use and who had more parent involvement had lower odds of heavy episodic drinking (OR = .79, p < .001 and OR = .87, p < .001, respectively). All school characteristic variables in Model 3 were significant. Youth who missed more days from school, had school peers who drink alcohol,

387



p ≤ .05.

∗∗

p ≤ .01.

∗∗∗

p ≤ .001.

Demographics Age Gender Family income White Black Hispanic Family characteristics Parent attitudes substance use Parent involvement Communication substance use Parent–child conflict School characteristics Days missed school Grades School peers drink alcohol Teacher–student relationship Attitude toward school Chi-square

1009.405∗∗∗

.612 −.199 −.038 .425 −.718 .323

B .019 .052 .025 .099 .138 .112

SE

Model 1

1.84∗∗∗ .82∗∗∗ .96 1.53∗∗∗ .49∗∗∗ 1.38∗∗

OR

.014 .016 .056 .020

−.260 −.174 .136 .223

485.030∗∗∗

.020 .055 .026 .103 .142 .116

SE

.556 −.320 .024 .413 −.632 .400

B

Model 2

.026 .019 .040 .057 .043 .015

.120 .128 −.311 .854 .134 −.058 435.477∗∗∗

1.25∗∗∗

.021 .070

.019

−.242 −.138 .178

.027 .069 .034 .130 .184 .147

SE

.414 −.354 .100 .471 −.742 .355

B

Model 3

.84∗∗∗ 1.15∗

.77∗∗∗

1.74∗∗∗ .73∗∗∗ 1.02 1.51∗∗∗ .53∗∗∗ 1.49∗∗∗

OR

TABLE 3 Summary of Logistic Regression Analysis of Factors That Protect Against Heavy Episodic Drinking

.94∗∗∗

1.14∗∗

1.14∗∗∗ .73∗∗∗ 2.35∗∗∗

1.13∗∗∗

.87∗∗∗ 1.20∗∗

.79∗∗∗

1.51∗∗∗ .70∗∗∗ 1.11∗∗ 1.60∗∗∗ .48∗∗∗ 1.43∗

OR

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and reported better relationships with teachers had a higher odds of heavy episodic drinking. For example, for each increase of 1 day missed from school, the adolescent was more likely to engage in heavy episodic drinking (OR = 1.14, p < .001). Students who indicated that their peers in school drank alcohol were 2.35 times more likely to binge drink (p < .001). Youth who reported stronger teacher–student relationships were 1.14 times more likely to engage in heavy episodic drinking (p < .01). Students with higher grades and more positive attitudes toward school had lower odds of excessive drinking (OR = .73, p < .001 and OR = .94, p < .001, respectively).

DISCUSSION AND APPLICATION TO PRACTICE Social work interventions are based on a person-in-environment perspective. The two key environments for adolescents are family and school. This study explored how both of these environments serve as protective factors against heavy episodic drinking among adolescents. The first hypothesis posited that adolescents who miss more days of school, have lower grades, have more peers who drink alcohol regularly, have poor relationships with teachers, and have less commitment to school will engage in more heavy episodic drinking. The bivariate analysis fully supported this hypothesis. These findings suggest that social work prevention efforts in the schools should be targeted at adolescents who are most at risk, as these adolescents might benefit from additional knowledge regarding the dangers of heavy episodic drinking and from activities designed to help them develop the skills to abstain from heavy episodic drinking. The results indicating absence from school is related to heavy episodic drinking might also suggest that social workers need to coordinate efforts with truancy officials to identify and track youth who consistently miss school. However, the first hypothesis was only partially supported by the binary logistic regression analysis as a positive teacher–student relationship increased the odds of heavy episodic drinking rather than decreasing the odds as might be expected (OR = 1.14, p < .01). The National Center on Addiction and Substance Abuse (2003b) found that supportive school environments that expect high levels of achievement protect against drinking in youth, and that school has a positive effect. Although the findings of this study confirm the importance of positive teacher feedback on the bivariate level, that element was not sufficient to protect against heavy episodic drinking among adolescents when the adolescent peer group supported a culture of alcohol use. As such, school connectedness is important, but not sufficient to override the influence of peers. This finding is consistent with previous research (Arthur et al., 2002; Kim & Zane, 2002; Kodjo & Klein, 2002). Practice implications from this finding include the need for school social work interventions to work on building connectedness to the

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school for adolescents at risk. The intervention also needs to include skillbuilding activities for managing peer relationships to help these adolescents better navigate relationships with peers who use alcohol. Additionally, as heavy episodic drinking occurs in nearly 44% of young women, it might be important to plan programs related to the unique needs of females. The second hypothesis proposed that adolescents who expect their parents to moderately disapprove of substance use, have more parent–child conflict, have less parent involvement, and have less communication with parents about substance use will engage in more heavy episodic drinking. Similar to the first hypothesis, the second hypothesis was fully supported by the bivariate analysis and partially supported by the multivariate analysis as parent communication with the youth about substance abuse increased the odds of heavy episodic drinking rather than decreasing the odds of heavy episodic drinking (OR = 1.20, p < .01). Generally, family served the predicted function of providing protection for adolescents against heavy episodic drinking. This finding is consistent with research by Wang et al. (2005). The implications of this finding for social work practice with families include the need to encourage increased parent involvement and decreased family conflict. Additionally, interventions might need to recognize the bimodal distribution of heavy episodic drinking among families and plan interventions accordingly. However, in the second hypothesis, adolescent–parent communication about substance use did not have the expected effect in the multivariate analysis; instead of protecting against heavy episodic drinking, it appeared to have increased the odds of heavy episodic drinking. This finding might indicate the importance of the contextual factors in the conversations of parents and youth as found by Miller-Day and Dodd (2004). The NSDUH data set only asks one question: “During the past 12 months, have you talked with at least one of your parents about the dangers of tobacco, alcohol, or drug use?” This question does not capture the content or context of the conversation or conversations between parents. For example, adolescents who had only one brief discussion on this topic with their parents will have the same response as adolescents who had continuous conversations integrated into the fabric of family life. Additionally, youth who affirmed that they had spoken with their parents about substances were not asked to clarify the reason for the communication; from the data, it is not clear if the parent was talking to the youth to prevent experimentation or if the parent was talking to the youth as an intervention after the youth had already been identified as using substances. Furthermore, NSDUH study documentation is not clear whether or not parents were present during the interview with the adolescents; therefore, some adolescents might have been influenced by social desirability bias in their responses. The demographic characteristics related to heavy episodic drinking support previous research that indicates that White male adolescents are at

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greater risk and that risk increases as the adolescent ages (Hilarski, 2005; Wallace & Muroff, 2002). Higher family income was also related to greater risk of heavy drinking. These findings confirm the importance of targeting prevention activities at youth and parents in these at-risk demographic groups. For example, these findings support engaging in prevention activities beginning in early adolescence and increasing the intensity as youth move toward middle and later adolescence when they are at greater risk.

CONCLUSION The findings of this study support the theoretical framework that risk is cumulative and interactive. They also support the use of the ecological perspective to better understand adolescent heavy episodic drinking. As such, social work interventions need to be sustained, implemented within multiple environments, and started prior to adolescence. These data add to the body of literature that asserts that ongoing intervention is necessary at both the family and school environmental levels. The importance of the person-in-environment approach is supported by these findings and reiterates the interactive nature of school and family for adolescents. Interventions to prevent heavy episodic alcohol use must recognize the relevance of targeting the quality and context of family interactions as well as the influence of peers on the decision-making capacities of adolescents.

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