gpa, depression, and drinking: a longitudinal comparison of high school boys and girls

http://spx.sagepub.com/Sociological Perspectives

http://spx.sagepub.com/content/54/3/351The online version of this article can be found at:

DOI: 10.1525/sop.2011.54.3.351

2011 54: 351Sociological PerspectivesNathan D. Shippee and Timothy J. Owens

GirlsGPA, Depression, and Drinking: A Longitudinal Comparison of High School Boys and

Published by:

http://www.sagepublications.com

On behalf of:

PSA

can be found at:Sociological PerspectivesAdditional services and information for

http://spx.sagepub.com/cgi/alertsEmail Alerts:

http://spx.sagepub.com/subscriptionsSubscriptions:

http://www.sagepub.com/journalsReprints.navReprints:

http://www.sagepub.com/journalsPermissions.navPermissions:

http://spx.sagepub.com/content/54/3/351.refs.htmlCitations:

What is This?

- Sep 1, 2011Version of Record >>

at Library - Periodicals Dept on October 6, 2014spx.sagepub.comDownloaded from at Library - Periodicals Dept on October 6, 2014spx.sagepub.comDownloaded from

http://spx.sagepub.com/

http://spx.sagepub.com/content/54/3/351

http://www.sagepublications.com

http://pacificsoc.org

http://spx.sagepub.com/cgi/alerts

http://spx.sagepub.com/subscriptions

http://www.sagepub.com/journalsReprints.nav

http://www.sagepub.com/journalsPermissions.nav

http://spx.sagepub.com/content/54/3/351.refs.html

http://spx.sagepub.com/content/54/3/351.full.pdf

http://online.sagepub.com/site/sphelp/vorhelp.xhtml



Address correspondence to: Timothy J. Owens, 700 West State Street, West Lafayette, IN 47906; e-mail: [email protected].

Adolescence is among the most thrilling life course periods, but also one of the most challenging: A teen’s actions, decisions, and milieu become more consequen-tial for his or her well-being as adulthood approaches (see Mortimer and Shanahan 2003). Among the noteworthy concerns of adolescence, and the foci of our study, are academic success, emotional distress, and the use of alcohol. Indeed, school achievement is a central normative pursuit for many teens, but adolescence is also a critical stage in the development of alcohol use (Bachman, Wadsworth, O’Malley, Johnston, and Schulenberg 1997) and depressed mood (McLeod and Owens 2004).

GPA, DEPRESSION, AND DRINKING: A LONGITUDINAL COMPARISON OF

HIGH SCHOOL BOYS AND GIRLS

NATHAN D. SHIPPEEMayo Clinic

TIMOTHY J. OWENSKent State University

ABSTRACT: Employing general strain theory, the authors examine gender differences in the dynamic strain-and-coping relations between GPA, depression, and drinking. Using longitudinal high school data from the Youth Development Study, the authors test five hypotheses. GPA negatively affects drinking (confirming Hypothesis 1), but without consistent gender differences (Hypothesis 1a). GPA also negatively affects depression (Hypothesis 2), and more strongly for girls (Hypothesis 2a). Depression’s positive effect on drinking supports Hypothesis 3, but gender comparisons refute Hypothesis 3a. Conversely, drinking positively affects lagged depression (Hypothesis 4), and more strongly for girls (Hypothesis 4a). Finally, drinking’s largely absent effect on GPA rejects Hypothesis 5a, whereas depression’s negative effect on lagged GPA, stronger among girls, supports Hypothesis 5b and Hypothesis 5c. A deleterious chain of effects occurs across high school, but mostly for girls only, possibly implicating gendered behavioral norms and socialization. This study informs general strain theory by suggesting that alcohol may provide divergent behavioral and emotional coping functions, respectively, for boys and girls.Keywords: depression, drinking, GPA, adolescence

Sociological Perspectives, Vol. 54, Issue 3, pp. 351–376, ISSN 0731-1214, electronic ISSN 1533-8673. © 2011 by Pacific Sociological Association. All rights reserved. Please direct all requests for permission to photo-copy or reproduce article content through the University of California Press’s Rights and Permissions website, at http://www.ucpressjournals.com/reprintinfo.asp. DOI: 10.1525/sop.2011.54.3.351.

Sageis collaborating with JSTOR to digitize, preserve, and extend access to

Sociological Perspectives

www.jstor.org

® at Library - Periodicals Dept on October 6, 2014spx.sagepub.comDownloaded from


352 SOCIOLOGICAL PERSPECTIVES Volume 54, Number 3, 2011

According to general strain theory (GST; Agnew 1992), the links between achievement, distress, and alcohol/substance use are multifaceted and dynamic. Strain arising from negative relationships and experiences can lead to various types of coping strategies, including behavioral or emotional responses (Agnew 1992). In turn, these responses may have short- and long-term effects on well-being and further strain (Brezina 1996). Hence, teens’ school success, emotions, and drinking are intertwined such that troubles in one tend to affect the others (Cooper, Frone, Russell, and Mudar 1995; Crosnoe 2006; Poulin, Hand, Boudreau, and Santor 2005). This complexity is further compounded by gender, which has a vital impact on coping, emotions, and behavior (Broidy and Agnew 1997; Duck-worth and Seligman 2006; Nolen-Hoeksema 1990).

Yet, although GST identifies varied coping responses, studies have rarely acknowledged or tested the potential for multiple causal paths linking school strain, emotional distress, and alcohol use (e.g., via behavioral versus emotional coping, and their consequences). As such, GST may be more flexible in its appli-cability than prior studies have indicated: the links may be more complex and varied than simply strain-distress-drinking. Furthermore, though GST asserts that gender has a key role in shaping responses to strain (Broidy and Agnew 1997), research on gender and GST remains limited (Jennings, Piquero, Gover, and Pérez 2009:406)—especially on topics other than aggression and crime. What are the specific coping patterns linking school achievement to distress and drinking, and what are the consequences of these coping responses over time? Furthermore, how does gender shape these associations?

Our study advances conceptions of GST, and of adolescent strain and coping, by (a) using structural equation models to assess the concurrent and lagged effects between school success, drinking, and depression; (b) identifying the direct or indirect strain-and-coping relations therein; and (c) specifically testing for gender differences. This builds upon prior reciprocal effects analyses, which have either not studied all three variables in tandem (e.g., Hansell and White 1991; Schul-enberg, Bachman, O’Malley, and Johnston 1994) or not tested gender differences (e.g., Crosnoe 2006). Using gender comparisons within a community-based sam-ple of teens, we (1) study the distinct effects of school grades on concurrent drink-ing and depression, (2) observe how depression affects concurrent drinking, (3) assess drinking’s effect on lagged depression, and (4) measure the distinct effects of drinking and depression on grades 1 year later.

BACKGROUND

Considering success norms in American secondary education, it is useful to view them both broadly and specifically (Covington 1992; 1998). Broadly, success may reflect intrinsic or extrinsic motivations, such as a love of learning versus main-taining a C average in order to play school sports. More specifically, success may express acceptance of authority and achievement orientations (Dumais 2002; Owens 2005). School success also has implications for students’ mental health and well-being—via self-esteem, self-worth, and other factors (e.g., Owens 1994)—such that poor academic performance can lead to greater depression (Poulin et al. 2005; Resnick, Bearman, Blum, Bauman, Harris, Jones, Tabor, Beuhring, Sieving, Shew,

at Library - Periodicals Dept on October 6, 2014spx.sagepub.comDownloaded from


GPA, Depression, and Drinking 353

Ireland, Bearinger, and Udry 1997). Conversely, good grades can instill positive self-evaluations and a sense of fulfillment. Bidwell and Friedkin (1988:461) capture this impact by arguing that “school social structure make[s] school work a potent inter-personal source of punishment and reward [through] the authoritative relationship between teacher and student and the public nature of academic work.” Further-more, though not specifically addressed in our study, Owens, Mortimer, and Finch (1996) found that parents grant greater autonomy to teens who get good grades. For many parents, good grades symbolize problem-solving, time management, and dedication. Then again, autonomy, and the parental trust and freedoms that accom-pany it, can make drinking easier for teens. After all, teens may have interests and priorities beyond school achievement, including building social networks and hav-ing fun—which may occur amidst parties or drinking (Allen, Porter, McFarland, Marsh, and McElhaney 2005; Diego, Field, and Sanders 2003).

Of course, even without school trouble, everyone experiences at least occasional depressed mood, thus making it a common though unwanted mood state (Com-pas, Ey, and Grant 1993). It is also an important signal of possible trouble within one’s internal world, external environment, or both (Aneshensel and Phelan 1999; Rosenfield, Vertefuille, and McAlpine 2000). Within a given 6-month period, 25 to 49 percent of girls report experiencing the affective symptoms of depressed mood (e.g., feeling sad, blue, or downhearted), compared to 20 to 35 percent of boys (Compas et al. 1993:325; Scheidt, Overpeck, Wyatt, and Aszmann 2000).

Teen drinking is also prevalent. On average, American teens take their first drink around age 14 (Warner and White 2003), and over 10 million regularly drink alcohol (Substance Abuse and Mental Health Services Administration 2009). Over 19 percent of eighth graders, 42 percent of tenth graders, and 57 percent of twelfth graders report having gotten drunk at least once (Johnston, O’Malley, Bachman, and Schulenberg 2008:42). Concerning gender, girls tend to have fewer drinks, whereas boys start drinking earlier, drink more often, and have more associ-ated problems with alcohol (Johnston et al. 2008; Leadbeater, Kuperminc, Blatt, and Hertzog 1999; Locke and Newcomb 2001). These differences may be due to girls’ socialization toward greater interpersonal sensitivity and tighter behav-ioral norms (Leadbeater et al. 1999; Nolen-Hoeksema and Corte 2004). After all, the vast majority of teen drinking involves group settings (Crosnoe, Muller, and Frank 2004; Sieving, Perry, and Williams 2000), and it carries an aspect of recipro-cal socialization (Gaughan 2006; Windle 1999). Thus, due to peer judgments and gender norms, girls may wish to avoid the social hazards of drinking.

As noted, school problems, depression, and drinking are intertwined (Poulin et al. 2005; Roeser, Eccles, and Sameroff 1998; Windle 1999). In general, depressed mood and drinking positively affect each other, likely due to self-medication motives and the psychosocial consequences of alcohol use (Cooper et al. 1995; Diego et al. 2003). Also, because they may reflect school-based stress and also dis-rupt academic achievement, drinking and depression tend to be negatively associ-ated with school performance (Crosnoe 2006; Kostelecky 2005; Needham, Crosnoe, and Muller 2004). Furthermore, these effects may interact: Crosnoe (2006) found that depression and other distress measures mediated the lagged effect of drinking frequency on class failure. Below, we discuss our conception of the mechanisms operating in these relationships.




THEORY

General strain theory (GST; Agnew 1992; 2001), with its focus on psychosocial strains and subsequent emotional and behavioral coping responses, is germane to our concerns. GST asks how strain arising from various sources may trigger responses such as delinquency, anger, or here, depressed mood and drinking. Strain develops out of negative relationships between an individual and another person (e.g., girl/boyfriend) or a class of others (e.g., teachers). It appears in three main forms: failed or blocked achievement of personally or socially valued goals, loss or removal of positive stimuli, and introduction of negative stimuli.

Responses to strain may entail coping strategies that are (a) cognitive, (b) behav-ioral, or (c) emotional in nature (Agnew 1992). Respectively, these are aimed at (a) reinterpreting stressors, (b) controlling positive and negative outcomes to limit strains, or (c) acting directly on the negative emotions that flow from the strain. Thus, particularly in behavioral and emotional coping, delinquent or “problem” behaviors may represent purposeful, problem-solving efforts at managing, com-pensating for, or retaliating against strains and distress (Brezina 1996; 2000).

School marks are a typically valued normative priority and a source of positive or negative evaluation, and so receiving poor grades is likely to create strain. This is supported by experimental work showing that emotional distress is especially likely to arise from negative evaluations by authority figures or higher-status peo-ple because their actions carry greater consequences (Lovaglia and Houser 1996; Robinson and Smith-Lovin 1992). Thus, low-achieving students may experience or anticipate negative emotions. In turn, alcohol is common in emotional coping to alleviate or prevent distress via self-medication and affect regulation (Aneshensel and Huba 1983; Cooper et al. 1995; Peirce, Frone, Russell, and Cooper 1994).

Yet beyond emotional coping, drinking may also signify behavioral coping (Agnew 1992). Specifically, it may reflect efforts at creating positive outcomes to obtain fulfillment, approval, or enjoyment, perhaps to offset lacking norma-tive success. This is especially sensible if one considers that teen drinking mainly entails group processes (Gaughan 2006; Sieving et al. 2000; Windle 1999). Peers offer an avenue of social achievement outside of school (Allen et al. 2005) and have a conditioning influence that shapes responses to strain (Mazerolle and Maahs 2000). Thus, teen drinking may function as behavioral coping and compensation (Brezina 1996) for negative experiences; that is, strain may affect drinking fre-quency directly, rather than operating via increased distress. Of course, drinking behavior may offset strain or distress initially, but it can also increase problems over the long term (Brezina 1996; 2000; Crosnoe 2006).

Gender and Adolescent Problems

Much literature indicates that girls tend to be more vulnerable than boys to internalizing problems such as depression and anxiety, whereas boys are more sus-ceptible to externalizing problems such as aggression, delinquency, and substance use (Nolen-Hoeksema 1990; Rosenfield et al. 2000). These differences echo their divergent socialization experiences; girls’ socialization emphasizes self-regulation and interpersonal relations, which can make them more sensitive to negative feedback. Conversely, boys’ socialization places more emphasis on self-assertion




and autonomy while underemphasizing empathy and self-regulation (Leadbeater et al. 1999). This literature would suggest that drinking is an externalized, behav-ioral response. Yet within GST, Broidy and Agnew (1997) noted that substance use may serve as an inward-focused response utilized by girls in the vein of emo-tional coping (Agnew 1992) to reduce or prevent distress. Thus, depending on the circumstances, boys and girls may use alcohol in either behavioral or emotional coping. This conceptual duality implies a need for caution in modeling and inter-pretation, as well as further inquiry into GST, adolescence, and coping responses.

These externalizing and internalizing tendencies have implications for school-based strain, and for responses to it. Whereas boys have more problems in school and other normative arenas, girls exhibit greater school commitment and self-discipline and lower academic failure rates, are influenced more by teachers, join more school organizations, and earn higher GPAs (Crosnoe 2006; Crosnoe et al. 2004; DiMaggio 1982; Duckworth and Seligman 2006; Dumais 2002; Roeser et al. 1998). With this greater commitment to academic success, school problems (e.g., low GPA) may result in greater strain for girls than for boys. Teachers’ evaluations may also impact girls’ emotions more than boys’, given the above-noted differ-ences in socialization.

To the extent that poor grades contribute to distress (Poulin et al. 2005; Resnick et al. 1997), boys’ and girls’ responses may also reflect externalizing and inter-nalizing differences, which may result in even greater differences in depression. In a theory of response styles, Nolen-Hoeksema (1990) states that girls are more likely to ruminate on their emotional states when depressed—an inward-focused, cognitive/emotional strategy that can exacerbate or prolong negative affect. Boys more often respond to distress with avoidant, behavioral strategies. On this topic, Brezina (1996; 2000) suggests that in the short term, at least, behavioral avoidance and delinquency may be more “successful” coping strategies, and so girls may be more likely to face continued emotional distress due to their focus on ruminative and emotional coping. Also, to the extent that girls do drink to cope with distress, they may face relatively greater social and mental consequences. This is captured by a generalized female vulnerability hypothesis: compared to boys, girls who drink frequently may experience more emotional distress through the violation of internalized gender norms and higher standards of behavior; heightened parental monitoring; and stronger negative reflected appraisals from parents, teachers, and peers (Bartusch and Matsueda 1996; Locke and Newcomb 2003; Nolen-Hoeksema and Corte 2004; Svensson 2003).

HYPOTHESES

Based on the varied coping responses and outcomes noted by GST, and the role of gender in shaping them, we posit five main hypotheses and five gender-difference sub-hypotheses.

Hypothesis 1: Normative success (grade point average, or GPA) will have a direct and negative—inhibitory—impact on contemporaneous monthly drinking occasions. We predicate this, in part, on the fact that school-oriented teenagers (via GPA) may limit drinking so it will not disrupt




their academic goals. Conversely, poor GPA is expected to increase the frequency of drinking, per behavioral and emotional coping in GST (see also Diego et al. 2003). Hypothesis 1a: We expect that the effect will be sig-nificantly stronger for girls because poor achievement may be a greater strain for them, and they may use alcohol to prevent distress as a pre-emptive form of emotional coping.

Hypothesis 2: GPA will have a direct and negative—salutatory—impact on concurrent depressed mood. This is predicated on a GST-based belief that poor GPA (a blocked avenue of normative achievement and nega-tive stimulus) will increase depressed mood. Moreover, it may reflect authority-based negative reflected appraisals by one’s teachers (the evaluators), and possibly one’s parents. Hypothesis 2a: The association will be significantly stronger for girls, per school gender norms and because of girls’ greater sensitivity to negative reflected appraisals.

Hypothesis 3: Depressed mood will have a direct and positive—catalytic—impact on contemporaneous drinking occasions. This is predicated on emotional coping within GST and the self-medication and affect-regulation hypoth-eses regarding the use of alcohol to attenuate negative affect. Hypothesis 3a: The effect will be stronger for boys; girls may drink to reduce distress, but they might also engage in other forms of emotional coping (rumina-tion, deep breathing, etc.; Agnew 1992; Nolen-Hoeksema 1990) that carry less potential for stigma. By contrast, response styles theory and behav-ioral coping in GST indicate that boys will externalize their distress.

Hypothesis 4: Drinking occasions will have a positive—deleterious—effect on lagged depressed mood. This is partly informed by literature on the long-term consequences of drinking to cope, including increased dis-tress (Aneshensel and Huba 1983; Brezina 2000; Crosnoe 2006; Hallfors, Waller, Bauer, Ford, and Halpern 2005). Hypothesis 4a: The effect will be stronger for girls, in part due to gender norms and socialization, which may stigmatize girls.

Hypothesis 5a: Drinking occasions will negatively affect lagged GPA, due to the potential long-term complications of drinking (Crosnoe 2006; see also Brezina 2000). Hypothesis 5b: Depressed mood will have a similar effect, due to its tendency to disrupt school success over time (Crosnoe 2006; Needham et al. 2004; Roeser et al. 1998). Hypothesis 5c: Both rela-tions will be stronger for girls, based on notions of female vulnerability and response styles (Nolen-Hoeksema 1990; Svensson 2003).

SAMPLE

Data come from the longitudinal Youth Development Study (YDS) of 1,139 ran-domly selected ninth graders (age ≈ 14) enrolled in the St. Paul (Minnesota) Public School System in 1988. Annual school-based, group-administered, pencil-and-paper surveys were conducted throughout high school (those who moved were mailed




surveys). By twelfth grade (age ≈ 18), retention was 93 percent. St. Paul, a racially and socioeconomically diverse city of 272,000 in a metropolitan area of 2,500,000, is the country’s fourteenth-largest city (U.S. Bureau of the Census 1997:42,47). Further-more, regional data have been used in several studies (e.g., Cooper et al. 1995—Buf-falo and Erie County, New York; Gore and Aseltine 2003—Boston, Massachusetts; Jang and Thornberry 1998—Rochester, New York). Still, in using regional rather than national data, caution must be exercised in generalizing to the United States, especially the country’s poorest enclaves and rural areas (Barrett and Turner 2005; Spoth, Goldberg, Neppl, Trudeau, and Ramisetty-Mikler 2001; see Mortimer 2003 for other comparisons). However, the quality of the YDS methods and its detailed prospective data gathering, plus its close tracking of a large cohort across the entire high school experience, make it well-suited for our purposes.

Demographically, 63.3 percent of participants identified themselves as white, 8.6 percent as black, 4 percent as Hispanic, 11.3 percent as Hmong, 1.1 percent as other Asian, 0.8 percent as Native American, and 6.2 percent as multiracial or other. Another 4.8 percent are unknown. Many Hmong were fresh refugees from the uplands of Cambodia and Laos who had until quite recently been preliterate horticulturists. Because of their lingual and cultural differences and limited Eng-lish, they are not included in these analyses. The effective sample size is 856 (e.g., excluding Hmong and attriters), which includes 648 whites (75.7 percent) and 208 other races/ethnicities (24.3 percent), and 466 girls (54.4 percent) and 390 boys (45.6 percent).

MEASURES

There are fifteen variables in the models, three exogenous and three sets of four endogenous (see Table 1 for descriptive statistics). The exogenous variables, mea-sured in the ninth grade, were family composition, family socioeconomic status, and race/ethnicity. The endogenous variables, each measured in ninth through twelfth grades, are number of drinking occasions, depressed mood, and grade point average (see the Appendix for details on wording and response options).

Exogenous Variables

Family socioeconomic status (SES-9), a latent variable measured by parent/guard-ians’ self-reported education and annual household income, is controlled because of its links to substance use (e.g., Stewart and Power 2003), emotional distress (Barrett and Turner 2005; Miech and Shanahan 2000), and academic achievement (Farkas 2003). For instance, SES can affect the type and quality of housing and neighborhoods in which one can afford to live and the quality of the schools one’s children attend. It can also influence stability or instability in the family’s daily life (e.g., frequent moving, wholesome diets). Race/ethnicity (Race-9) (1 = white, 0 = non-white) is controlled because it is associated with depressed mood (Gore and Aseltine 2003), drinking (Stewart and Power 2003), and academic achievement (Farkas 2003). Finally, family composition (Famcomp-9) is a dummy variable: 1 = two-parent family (68 percent), 0 = other family types (32 percent). Composition can




influence children through the time and energy their parents have to supervise and be involved in their daily affairs, and through family stress and tension. Com-position may thus affect substance use (Broman, Li, and Reckase 2008), academic achievement (McLanahan and Sandefur 1994), and depression (Barrett and Turner 2005).

TABLE 1 Means, Standard Deviations, and Ranges of Variables in Structural Modela

MeanStandard Deviation α

Range Boys GirlsGender

Comparisons Boys Girls Boys Girls

9th GradeSES (latent

family SES)2–21 8.79 9.13 ns 3.39 3.46 — —

Race (race/ ethnicity)

1 = white, 0 = other

.71 .71 — .45 .45 — —

Famcomp (family composition)

1 = two-parent, 0 = other

.69 .68 ns .47 .46 — —

Drinking (monthly drinking occasions)

0–6 1.26 .92 * 1.52 1.22 — —

Depression (depressed mood scale)b

4–20 9.36 10.58 * 3.01 3.38 .80 .88

GPA (academic achievement)

1–12 5.88 5.42 * 2.65 2.39 — —

10th GradeDrinking 0–6 1.61 .99 * 1.43 1.20 — —Depression 4–20 9.61 10.78 * 3.12 3.37 .83 .90GPA 1–12 5.40 5.14 * 2.38 2.31 —

11th Grade —Drinking 0–6 1.71 .97 * 1.59 1.23 — —Depression 4–20 9.80 10.69 * 3.25 3.39 .86 .90GPA 1–12 5.33 4.95 * 2.42 2.19 — —

12th GradeDrinking 0–6 1.73 .93 * 1.49 1.10 — —Depression 4–20 9.79 10.76 * 3.13 3.12 .87 .88GPA 1–12 5.05 4.38 * 2.37 2.16 — —

a. Variable labels: SES (latent family socioeconomic status), Famcomp (family composition), Drinking (monthly alco-hol use), Depression (Depressed Mood Scale), and GPA (academic achievement).b. Depression, a latent construct, is displayed as a summated ratings scale for illustration and description purposes; see the Appendix for individual items and factor loadings.*p < .05; ns (not significant); — (not applicable).




Endogenous Variables

Monthly alcohol use (Drinking–9 through 12) is a single-item variable of how many times a teen drank alcoholic beverages in the past 30 days. Responses range from 0 = none to 6 = 40+. Because the alcohol measure has a skewed distribution, its natural logarithm is used in our models, after first adding a constant (1) so non-drinkers’ reports of zero drinking occasions can be taken into consideration. Some studies use different measures of drinking, such as quantity or rate (Aneshensel and Huba 1983; Peirce et al. 1994) or binge drinking (defined as 4+ drinks during a single occasion for females and 5+ for males; Centers for Disease Control and Prevention 2008). However, our measure is a widely used benchmark (Bachman et al. 1997; Crosnoe 2006; Windle 1999) and is thus appropriate for our research agenda. Furthermore, Crosnoe (2006) found that there were few differences between a measure of drinking frequency and a measure of binge drinking in their associations with academic performance and depressed mood. In fact, drinking frequency actually predicted class failure slightly better than did binge drinking. Finally, confidence in our sample and the validity of our drinking frequency mea-sure is bolstered by noting that 53.5 percent of our participants reported drinking in the past month, compared to 48.4 percent of Monitoring the Future participants (Johnston et al. 2008:219) and 55.7 percent of Add Health participants (Broman et al. 2008:1635) who had done so.

Depressed mood (Depression–9 through 12) is a latent construct consisting of four indicators drawn from the Depression subscale developed for the feder-ally funded RAND Health Insurance Study (HIS) Mental Health Battery (Brook, Ware, Davies-Avery, Stewart, Donald, Rogers, Williams, and Johnston 1979; Ware, Johnston, Davies-Avery, and Brook 1987). The battery was designed to measure mental health in persons age 14 and older, thus making it appropriate for our study. Analyses of the battery have consistently found acceptable reli-ability and validity (Brook et al. 1979:31–40; Shin 2005). Our participants, like those in other studies using the battery, reported how often in the past month they felt downhearted, blue, and so forth. Response options range from 1 = no time to 5 = all of the time (see Table 1 for descriptive statistics and the Appendix for item wording and factor loadings). The Depression subscale, as developed, is consistent with other measures of depressed mood (Costello and Angold 1988) and has been employed in numerous publications (see Mortimer 2003). A multi-group confirmatory factor analysis of the measurement models shows structural invariance between genders and across time: No statistically signifi-cant differences exist (p < .36) between the constrained model’s χ2-to-degrees-of-freedom (477.8 and 194, respectively) and the unconstrained model’s (490.9 and 206, respectively). Structural invariance exists when the dimensions of a latent construct and the pattern of relations among its measured attributes per-sist across measurement points.

Academic achievement (GPA–9 through 12), our measure of normative success, is measured via each student’s self-reported grade point average (GPA) at the time of the survey. Responses, including pluses/minuses, range from A (12) to F (1). Dorn-busch, Ritter, and Steinberg (1991) discuss the appropriateness of self-reported grades in comparison to ones obtained from school records, finding a correlation of




.79 between the two. We consider GPA an objective measure of academic achieve-ment inasmuch as it is generally independent of the adolescent’s perceptions.

ANALYTIC STRATEGY

The analyses occur in two stages using EQS 6.1 (Bentler 2007). We first estimate the measurement model for the latent depression construct. Second, and most impor-tantly, we estimate a multi-group (“stacked”) full-information maximum likelihood structural equation model for the boys and for the girls. That is, the measurement and causal parameters are estimated simultaneously, as are the boys’ and girls’ models. This allows us to test our hypotheses and to accurately compare boys’ and girls’ structural parameters (β-coefficients).

The conceptual model (Figure 1) shows our labeling convention for the paths associated with each parameter estimate. The labels go from left (a1, the exogenous variables’ covariances) to right (h4, the endogenous variables’ β-coefficients for the path from Depression-12 to Drinking-12). Concerning measurement, because Race-9, Famcomp-9, Drinking–9 to 12, and GPA–9 to 12 are single-indicator con-structs, measured error is not assumed, per standard measurement nomenclature and practice. However, because the latent depression construct is measured across high school, contiguous error terms for the same indicator are allowed to correlate (e.g., the indicators for feeling downhearted in ninth through tenth grade).

All three exogenous variables are considered prior stable phenomena (see Owens et al. 1996) that directly influence the initial endogenous variables (Drink-ing-9, etc.), whereas their effects on the later endogenous variables are specified as indirect. Because the specification of relationships among the endogenous con-structs could take several forms, we note some statistical constraints. Due to multi-collinearity, it is quite hazardous to estimate both lagged effects and fully recipro-cal contemporaneous effects simultaneously. For example, if GPA-9 and GPA-10 are allowed to influence Depression-11, the strong relationship between the prior two variables will likely cause biased and unstable parameter estimates (the cor-relation of GPA-9 and GPA-10 is .64; see Figure 2, parameter d1). Second, due to severe identification problems posed by the absence of appropriate instrumen-tal variables needed to estimate concurrent reciprocal effects, coupled with our chief desire to assess multiple lagged effects, we do not estimate reciprocal effects within grades. Consequently, each variable is permitted to influence another only once, either through contemporaneous or lagged one-way causation.

As for the hypothesis-driven model specifications, we propose multiple paths by which GPA affects depression and drinking, and vice versa, based on the cop-ing and response patterns suggested within GST. First, teenagers’ GPAs are argu-ably the most direct sign of educational success and commitment. School success, as a normatively valued goal and an evaluation by authority figures, is a potential source of either fulfillment or strain. As such, low-achieving teens may engage in drinking to find alternative enjoyment, via behavioral coping, or prevent distress, via emotional coping (Agnew 1992; Brezina 2000; Cooper et al. 1995). Thus, based on GST and prior literature (Diego et al. 2003), GPA-9 is allowed to directly influ-ence Drinking-9 (Hypothesis 1) and indirectly influence later Drinking-10 and




Blue

Brood

Depress

Depression-9

Famcomp-9

SES-9

Depression-10

Depression-11

Depression-12

Drinking-9

Parental

Education

Family

Income

Drinking-10

Drinking-11

Drinking-12

Low

Blue

Brood

Depress

Low

Blue

Brood

Depress

Low

Blue

Brood

Depress

Low

z4z3b9

b3

b8

b5

b2

b1 b4b7

f1h1

f2f3

d1d2 k2

d3

k1 i1

h2h3

f4h4

a3a2

a1

g1g2

g3g4

b6

z5z6

z7z8

z9z10

z11

z12

z13

z14

z15

z16

z17

z18

GPA

-9GPA

-10

GPA

-11

GPA

-12

z1z2

Race-9

1

56

78

23

4

1211

109

e1e2i2

e3

i3

k3c3c2

c1

j2j1

FIG

UR

E 1

C

once

ptua

l Mod

el o

f Fre

quen

cy o

f Mon

thly

Alc

ohol

Use

(Dri

nkin

g), D

epre

ssed

Moo

d (D

epre

ssio

n), a

nd A

cad

emic

Ach

ieve

men

t (G

PA)

in G

rad

es 9

thro

ugh

11




GPA-10, with the same specifications applied in later paths. Likewise, poor grades can garner negative self-esteem or self-worth (Owens 1994), which may increase emotional distress via internalization (Rosenfield et al. 2000). In short, GPA-9 is allowed to influence Depression-9 directly (Hypothesis 2), similar to analyses in prior work (Diego et al. 2003; Poulin et al. 2005; Resnick et al. 1997).

Reflecting Hypothesis 3, and the fact that self-medication, affect regulation, and emotional coping would suggest alcohol use as a “quick fix” for distress (Agnew 1992; Aneshensel and Huba 1983; Cooper et al. 1995; Crosnoe 2006; Peirce et al. 1994), we propose that depression directly affects concurrent drinking occasions. This is shown in the h paths, where Depression-9 affects Drinking-9 (Hypothesis 1) and so forth across the model. Concerning Hypothesis 4’s lagged effects, because the effects of drinking on depression may be shaped by prohibitory social norms, negative peer evaluations, and other social consequences (Nolen-Hoeksema and Corte 2004; Svensson 2003), those effects may evolve over a period of time (see Crosnoe et al. 2004; Hallfors et al. 2005; Hansell and White 1991). Thus, our model assumes that depression will respond to shifts in drinking occasions over 1 year, as in the i paths—Drinking-9’s lagged effect on Depression-10 (i1), and so on. Finally, in Hypothesis 5, our concern with the lagged effects of drinking and depression on GPA (j and k paths, respectively) reflects their ability to disrupt school perfor-mance over 1 year (Crosnoe 2006; Crosnoe et al. 2004; Needham et al. 2004; Roeser et al. 1998), as well as Brezina’s (1996; 2000) call to consider the long-term conse-quences of responses to strain.

FINDINGS

The standardized β-coefficients for the multi-group causal model are shown in Figure 2, and the complete results, including unstandardized coefficients and model fit statistics, appear in Table 2. Aiding Figure 2 gender comparisons, boys’ coefficients are in regular type and girls’ are underlined. Concerning the overall model, there are no signs of underidentification since convergence was achieved after only fourteen iterations. More importantly, the theoretically posed model, with both genders estimated simultaneously, fits the data quite well. The com-parative fit index (CFI) and the normed fit index (NFI) are acceptable at .97 and .96, respectively, and the root mean square error of approximation (RMSEA) is a desirably low .01.

Because we are interested in gender distinctions, a χ2-to-degrees-of-freedom dif-ference test is used to assess statistically significant gender differences for specific parameters. Specifically, when a model with a specific parameter is constrained to be equal for both genders (c) and it is compared to the freely estimated base model (f) with no constraints, significance is obtained from the resulting χ2

d/degree-of-freedom (df) ratio (see equation below):

χ2c - χ2

f χ2d

dfc - dffdfc

= .

Gerber and Malhotra (2008) have recently criticized sociology’s overreliance on conventional significance levels rather than allowing p < .1 in certain circumstances. Based on this, and on work by Pedhazur (1997:563) and Turner and Avison (1992),




we use the p < .1 threshold for testing gender differences, which accounts for four of the seventeen total gender differences we find.

Exogenous Variables

The SES-9-to-Drinking-9 association is significant and positive for girls only (β = .14, p < .05; b1, see Figure 2 and Table 2), which echoes the oft-noted posi-tive association between SES and drinking. Although race is not significant, Fam-comp-9 (1 = two-parent family, 0 = other) is positive and significant for boys only (β = .14, p < .05; b7). The SES-9-to-GPA-9 link is positive and significant for boys and girls alike (β = .35 and .25, respectively, p < .05; b2), a finding also consistent with the literature (Farkas 2003). The Race-9-to-GPA-9 link is also positive for both boys and girls (β = .13 and .08, respectively, p < .05; b5). Famcomp-9-to-GPA-9 is significant for girls only (β = .10, p < .05; b8), suggesting that two-parent families may benefit girls’ grades. Moreover, significant effects appear for girls only in both SES-9-to-Depression-9 (β = –.11, p < .05; b3) and Race-9-to-Depression-9 (β = .16, p < .05; b6). Finally, the Famcomp-9-to-Depression-9 link is significantly negative only for boys (β = –.14, p < .05; b9), with a significant gender difference noted (χ2

d, p <

.05; see Table 2). Two-parent families somewhat adversely affect boys’ emotional well-being.

Concerning the inter-grade stability coefficients, the coefficients for drinking-to-drinking (c1–3) and depression-to-depression (e1–3) comport with other longitudi-nal findings of moderate stability in adolescent drinking (Bachman et al. 1997) and depression (Rosenberg, Schooler, and Schoenbach 1989) over time. However, GPA is quite stable (d1–3) for both genders (i.e., prior GPA strongly predicts later GPA), as others report (Owens 2005).

Hypothesis Tests

Hypothesis 1 (f paths): GPA is expected to have a direct and negative—inhibi-tory—impact on monthly drinking occasions. We find support for the hypothesis in ninth and tenth grade (all coefficients significant at p < .05), but mixed support in eleventh and twelfth grade (where one gender or the other is significant at p < .05). Overall, good grades—and their asso-ciated values (success-orientation) and behaviors (diligence)—modestly limit drinking frequency. With the exception of eleventh grade, GPA’s impact on boys’ drinking is negative across high school (the ninth, tenth, and twelfth grade coefficients are –.17, –.11, and –.21, respectively; p < .05). For girls, the effect is moderate in ninth grade (β = –.29, p < .05), weaker in tenth and eleventh grades (β = –.11 and –.16, respectively; p < .05), but non-significant in twelfth grade. Hypothesis 1a (stronger asso-ciations for girls versus boys) has only mixed support. Although girls’ coefficients are stronger in ninth and eleventh grade (p < .05 for both; see Table 2), gender differences are non-significant in tenth grade and actually stronger for boys in twelfth (p < .05). Thus, although the effects of GPA on drinking are consistently negative for both genders, the com-parative strengths (and significance levels) of those associations do vary.




Drin

king

-9

GPA

-9

b1 S

ES-9

>DK-

9 =

.03;

.14*

b4 R

ace-

9>DK

-9 =

-.04

; .07

b7 F

amco

mp-

9>DK

-9 =

.14*

; -.0

5;

b2 S

ES-9

>GPA

-9 =

.35*

; .18

*b5

Rac

e-9>

GPA

-9 =

.13*

; .03

b8 F

amco

mp-

9>G

PA-9

= -.

04; .

10*

b3 S

ES-9

>DP-

9 =

.07;

-.11

*b6

Rac

e-9>

DP-9

= -.

02; .

16*

b9 F

amco

mp-

9>DP

-9 =

-.14

*; -.0

1

GPA

-11

GPA

-12

.43*

.33*

b1,b

4,b7

b3,b

6,b9

b2 b5 b8

f 1h 1

h 2h 3

h 4f 2

f 3f 4

1.4

6*.4

4*2

.42*

.43*

3D

rinki

ng-1

0D

rinki

ng-1

1D

rinki

ng-1

2 .11*

.08

†.0

7.1

2*−.

16*

−.05

.13*

.30*

−.21

*−.

07†

−.10

†−.

08† g

.13*

.55*

.48*

.45*

.36*

2.4

7*.5

4*e

1e3e

.09*

.01

.03

.12*

.04

ii

12

2

gg

i 34

31

†

1

.61*

−.06

−

.03

−.05

−

.01

−.10

*

−.0

3j 1

j 2j 3

.64*

d 1

−.09

†−.

17*

k 1k 2

k 3

dd

.62*

.65*

2.6

8*.7

2*3

−.17

*−.

29*

.12*

.09*

−.11

*−.

11*

GPA

-10

Dep

ress

ion-

9D

epre

ssio

n-12

Dep

ress

ion-

10D

epre

ssio

n-11

−.04

−.13

*−.

04−.

10*

−.02

−.14

*

−.02

−.

14*

−.01

−.

13*

cc

c

g

Not

e: T

o ex

ped

ite

gend

er c

ompa

riso

ns, b

oys’

coe

ffici

ents

are

in r

egul

ar ty

pe a

nd g

irls

’ coe

ffici

ents

are

und

erlin

ed. S

ee T

able

2 fo

r co

mpl

ete

resu

lts,

incl

udin

g m

odel

fit s

tati

stic

s an

d

gend

er c

ompa

riso

n st

atis

tics

. Par

amet

er la

bels

are

at t

he a

rrow

hea

ds.

* p

< .0

5; †

p <

.10.

FIG

UR

E 2

St

ruct

ural

Mod

el o

f Fre

quen

cy o

f Mon

thly

Alc

ohol

Use

(Dri

nkin

g), D

epre

ssed

Moo

d (D

epre

ssio

n), a

nd A

cad

emic

Ach

ieve

men

t (G

PA) i

n G

rad

es 9

thro

ugh

12




(con

tinu

ed)

TAB

LE

2

Para

met

er E

stim

ates

for

Path

s am

ong

Exo

geno

us a

nd E

ndog

enou

s V

aria

bles

Uns

tand

ardi

zed

Coe

ffici

ent

Stan

dard

E

rror

Stan

dard

C

oeffi

cien

tG

ende

r C

ompa

riso

nV

aria

bles

Gra

deP

aram

eter

Boy

sG

irls

Boy

sG

irls

Boy

sG

irls

Exo

geno

us V

aria

bles

SES

↔ F

amco

mp

9a 1

.13

.12

.02

.02

.35*

.45*

SES

↔ R

ace

9a 2

.09

.08

.02

.01

.26*

.30*

Rac

e ↔

Fam

com

p9

a 3.0

3.0

2.0

1.0

1.1

4*.0

9*E

xoge

nous

to E

ndog

enou

s V

aria

bles

SES

→ D

rink

ing

9b 1

.05

.11

.65

.01

.03

.14*

SES

→ G

PA9

b 21.

11.4

7.1

6.0

7.3

5*.2

5*SE

S →

Dep

ress

ion

9b 3

.04

–.03

.06

.03

.04

–.11

*R

ace

→ D

rink

ing

9b 4

.43

.23

.16

.12

–.04

.04

Rac

e →

GPA

9b 5

–.24

.19

.26

.23

.13*

.08*

Rac

e →

Dep

ress

ion

9b 6

–.04

.31

.09

.09

–.02

.16*

*Fa

mco

mp

→ D

rink

ing

9b 7

–.24

–.13

.17

.12

.14*

–.05

Fam

com

p →

GPA

9b 8

–.20

.59

.17

.22

–.04

.10*

Fam

com

p →

Dep

ress

ion

9b 9

–.14

–.04

.17

.09

–.14

*–.

01*

End

ogen

ous

Var

iabl

esD

rink

ing

Stab

ility

Coe

ffici

ents

9–10

c 1.3

1.4

3.0

4.0

4.3

3*.4

3**

10–1

1c 2

.46

.47

.05

.04

.44*

.46*

11–1

2c 3

.42

.37

.04

.04

.43*

.42*

GPA

Sta

bilit

y C

oeffi

cien

ts9–

10d

1.5

6.6

2.0

4.0

3.6

1*.6

4*10

–11

d2

.64

.65

.04

.04

.62*

.65*

11–1

2d

3.6

6.7

1.0

4.0

3.6

8*.7

2*D

epre

ssio

n St

abili

ty C

oeffi

cien

ts9–

10e 1

.17

.48

.03

.05

.36*

.45*

*10

–11

e 21.

18.5

2.1

4.0

4.4

8*.5

5*11

–12

e 3.4

9.4

2.0

5.0

4.5

4*.4

7*G

PA →

Dri

nkin

g9

f 1–.

10–.

15.0

3.0

2–.

17*

–.29

**

10f 2

–.07

–.04

.03

.07

–.11

*–.

11*

11f 3

–.03

–.07

.13

.02

–.05

–.16

**



366 SOCIOLOGICAL PERSPECTIVES Volume 54, Number 3, 2011TA

BL

E 2

Pa

ram

eter

Est

imat

es fo

r Pa

ths

amon

g E

xoge

nous

and

End

ogen

ous

Var

iabl

es

(Con

tinu

ed)

Uns

tand

ardi

zed

Coe

ffici

ent

Stan

dard

E

rror

Stan

dard

C

oeffi

cien

tG

ende

r C

ompa

riso

nV

aria

bles

Gra

deP

aram

eter

Boy

sG

irls

Boy

sG

irls

Boy

sG

irls

12f 4

–.14

–.13

.03

.09

–.21

*–.

07†

GPA

→ D

epre

ssio

n9

g 1–.

03–.

03.0

2.0

2–.

10†

–.08

†

10g 2

–.02

–.07

.01

.02

–.09

†–.

17*

*

11g 3

–.01

–.05

.17

.02

–.02

–.14

**

12g 4

–.01

–.04

.18

.02

–.01

–.13

*†

Dep

ress

ion

→ D

rink

ing

9h 1

.24

.13

.11

.06

.12*

.09*

†10

h 2.1

0.0

7.0

2.0

6.1

3*.3

0**

11h 3

.11

.08

.02

.06

.12*

.07†

12h 4

.13

.10

.04

.08

.11*

.08†

Dri

nkin

g →

Dep

ress

ion

9–1

0i 1

.00

.06

.08

.03

.01

.13*

*10

–11

i 2.0

2.0

5.0

6.0

3.0

3.0

9*†

11–1

2i 3

.02

.12

.02

.03

.04

.12*

*D

rink

ing

→ G

PA 9

–10

j 1–.

07.0

1.0

6.0

3–.

05–.

0110

–11

j 2–.

10–.

06.0

7.0

3–.

06–.

0311

–12

j 3–.

11–.

04.0

6.0

6–.

10*

–.03

Dep

ress

ion

→ G

PA9–

10k 1

–.02

–.19

.14

.06

–.04

–.13

**

10–1

1k 2

–.03

–.18

.28

.05

–.04

–.10

*†

11–1

2k 3

–.02

–.40

.39

.02

–.02

–.14

**

Goo

dnes

s of

Fit

Mea

sure

sχ2

1,20

9.07

*df

574

CFI

.97

NFI

.96

RM

SEA

.01

† p

< .1

0; *

p <

.05.




Hypothesis 2 (g paths): GPA is expected to have a direct and negative impact on depressed mood. The hypothesis is broadly supported for girls only, but only after the ninth grade: their tenth through twelfth grade coeffi-cients are –.17, –.14, and –.13, respectively (p < .05). Hypothesis 2a (stron-ger associations for girls) is also moderately supported. In every grade but ninth, girls’ coefficients are significantly larger than boys’ (p < .05 or .1; g2–g4).

Hypothesis 3 (h paths): Depressed mood is expected to have a direct and positive impact on drinking occasions. The hypothesis is supported for boys across high school: Their modest yet significant values range between .11 and .13 (p < .05). Girls’ values are only significant in ninth and tenth grade (β = .09 and β = .30 in h1 and h2, respectively; p < .05). Yet the gender coef-ficients have relatively close magnitudes in most grades (and are actually larger for girls in tenth grade, p < .05), resulting in a rejection of Hypoth-esis 3a (stronger associations for boys versus girls).

Hypothesis 4 (i paths): Drinking frequency is expected to have a lagged and positive effect on depressed mood. The hypothesis is supported for girls only. Drinking has a small yet significant (p < .05) and positive (deleteri-ous) impact on girls’ depression in all three intervals: ninth to tenth (β = .13; i1), tenth to eleventh (β = .09; i2), and eleventh to twelfth (β = .12; i3). Hypothesis 4a (stronger associations for girls) is confirmed: Girls’ coef-ficients are larger (p < .05 or .1) across high school.

Hypothesis 5a (j paths): Drinking occasions will negatively affect GPA after 1 year. The hypothesis is not supported; drinking has no lagged influence on GPA except for Drinking-11 to GPA-12 for boys (β = –.10, p < .05; j3). Hypothesis 5b (k paths): Depressed mood will negatively affect lagged GPA. The hypothesis is supported for girls only: The effect of depressed mood on GPA is small yet significant (p < .05) for girls for all intervals—ninth to tenth (β = –.13; k1), tenth to eleventh (β = –.10; k2), and eleventh to twelfth (β = –.14; k3)—but is not significant for boys at any point. Hypothesis 5c (stronger associations for girls) is only partially supported: No differ-ences are significant for Hypothesis 5a, but girls’ coefficients are signifi-cantly larger for Hypothesis 5b at all intervals (p < .05 or .1).

DISCUSSION AND CONCLUSION

Concerning our core expectations, school-based strain did indeed stimulate diver-gent patterns of coping responses, which in turn had their own consequences—and gender was a key factor in these processes. Results implicated behavioral and emotional coping as distinct, parallel mechanisms linking strain, distress, and drinking, and furthermore indicated that girls may be especially vulnerable in these associations (possibly due to their socialization experiences).

The proposition that GPA would be negatively related to drinking occasions, or Hypothesis 1, was generally confirmed: lower grades predicted more frequent drinking. If one concedes that a lack of school success may cause strain, then its




impact on drinking frequency fits GST (Agnew 1992; Brezina 1996; 2000). That is, poor grades may have increased drinking frequency because of the strain from a blocked normative pursuit or the associated negative stimuli, presumably at the hands of an institution or person (teacher) empowered to judge teens’ per-formances. In GST, “problem” behaviors may reflect problem-solving responses (Brezina 2000) aimed at alternative avenues of fulfillment (see Allen et al. 2005). Thus, lower-achieving teens may compensate by looking for alternative attention or enjoyment, as in behavioral coping (Agnew 1992). Conversely, it may also rep-resent an effort to preempt anticipated distress, as in emotional coping and affect regulation (Peirce et al. 1994). These divergent coping paths to drinking (i.e., find-ing enjoyment or preventing distress; Cooper et al. 1995) may partially explain the lack of consistent gender differences—a lack which suggests that GPA’s undif-ferentiated effect on drinking is not tied more to one gender than another. This is contrary to response style theories (Rosenfield et al. 2000) and more in line with GST (Broidy and Agnew 1997), depending on the style of coping or response a teen chooses. Still, it would be worthwhile for future studies to test other explana-tions for the GPA–alcohol use connection, as it may reflect underlying impulsivity or self-control issues (Baker 2010; Duckworth and Seligman 2006) or other factors.

Turning to Hypothesis 2, GPA did have a direct and negative—salutary—impact on emotional distress, but only among girls. Our data thus support prior research on the particular emotional importance of doing well in school for girls (e.g., DiMaggio 1982; Dumais 2002). These findings appeared more conclusively in gen-der comparisons, and here, viewing the association in terms of low GPA is also revealing. Specifically, finding that poor grades adversely impacted girls’ emo-tional well-being more than boys’ supports Hypothesis 2a and response theory’s assertion regarding girls’ greater propensity to internalize their problems (Nolen-Hoeksema 1990). Depression may also signify girls’ greater sensitivity to negative reflected appraisals and interpersonal feedback (Leadbeater et al. 1999), and espe-cially authority-based evaluations.

Evidence supporting our expectation that depressed mood would increase con-current drinking occasions (Hypothesis 3) appeared consistently across high school for boys, but only in Grades 9 and 10 for girls. This finding supports the idea that boys tend to externalize their problems, but challenges the presumption that girls generally do not (Aneshensel and Huba 1983; Rosenfield et al. 2000). The latter also raises an interesting development issue. The transition from middle school to high school is often accompanied by academic and psychological difficulties (Cavanagh, Riegle-Crumb, and Crosnoe 2007; Roeser et al. 1998), and girls are susceptible to peer influence vis-à-vis drinking (Gaughan 2006). Yet drinking in response to depression (paths h1 and h2) was especially counterproductive for girls because it increased later depressed mood (paths i1–i3; see discussion below). Thus, the non-significant effect of depression on drinking among girls in later grades may simply suggest a logical reaction to these harmful effects, but also a turn toward other means of emotional coping—particularly the possibility of rumination, a well-documented response to distress among women (Nolen-Hoeksema and Corte 2004).

Regarding our expectation that greater drinking occasions would increase sub-sequent emotional distress (Hypothesis 4), evidence appeared among girls (but




not boys) in every interval (i1–i3), with Hypothesis 4a (stronger effects for girls versus boys) also confirmed. This supports existing notions of female vulnerabil-ity, with gendered social norms and reflected appraisals putting girls who drink at higher risk of emotional distress (Bartusch and Matsueda 1996; Svensson 2003).

Our final expectations—that greater drinking (Hypothesis 5a) and depression (Hypothesis 5b) would significantly lower GPA—received limited support; only depression’s effect on GPA was consistently significant, and that only among girls. This indicates that emotional distress does have long-term implications for social functioning (see Needham et al. 2004) and that girls’ greater tendency to rumi-nate may be part of the problem (Nolen-Hoeksema 1990). Yet it also brings fur-ther questions regarding the longer-term consequences of drinking for normative achievement, especially considering prior work that suggests such consequences are hazardous (Brezina 2000; Crosnoe 2006; Crosnoe et al. 2004).

The preceding evidence also reveals a chain of causality that involves all five hypotheses, but only among girls. Most of this cause-and-effect cycle can be illus-trated in a heuristic:

Depression-9 & GPA-9 → Drinking-9 & GPA-10 → Depression-10 → Drinking-10 & GPA-11 → Depression-11 → GPA-12 → Depression-12.

Stated briefly, this means that for girls, early poor grades and depression set in motion a series of negative emotional, behavioral, and achievement outcomes run-ning throughout high school. From a theoretical and empirical standpoint, this chain unites conceptions of school performance and strain, coping and affect regu-lation, and female vulnerability into a picture of cumulative psychosocial risk for girls who begin high school with academic and/or emotional difficulties.

In conclusion, our study began with the proposition that normative adolescent pursuits, emotional distress, and potential problem behaviors are interconnected via strain, multiple coping responses, and long-term consequences for well-being. Five main hypotheses and five parallel gender comparison sub-hypotheses were tested with a panel of 856 American teenagers followed from ninth through twelfth grade using multi-group structural equation modeling. Certain theoretical findings are especially notable. First, our findings indicate that coping, via behav-ioral or emotional adaptations (Agnew 1992), may shape alcohol use along mul-tiple, parallel causal paths. On a related note, Brezina’s (1996; 2000) assertions that “problem” behavior may reflect a purposive effort at strain reduction, and that it may have consequences for well-being, are borne out by the teens in our study. Also, there is some evidence of Bidwell and Friedkin’s (1988) thesis that school may be a psychologically punishing experience—and perhaps especially for girls. Signs of the female vulnerability hypothesis and female drinking norms also sur-faced in the depressed mood outcomes. Perhaps the most telling empirical and theoretical finding appeared in the causal chain of GPA and depression on drink-ing and GPA, drinking and GPA on depression, and so on among girls throughout high school. It would appear that the GPA-depression-drinking nexus, although modest, appears as a consequential and potentially harmful cycle for girls.

Some limitations are worth noting. First, in consideration of GST and our review of the literature, we have tested a model in which poor school grades instigate




concurrent distress and drinking, which in turn have lagged effects on grades. Yet alternative configurations also deserve attention, for example, in which depression or related negative self-perceptions are reciprocally related to concurrent grades (see Owens 1994), or the effects of grades on other problems are lagged (Crosnoe 2006). Second, in order to perform more conclusive tests of general strain theory, the disparity between students’ aspirations and their actual performance would offer a more accurate measure of strain than GPA (Agnew 1992:51–2). Likewise, tests of female vulnerability could benefit from direct measures of girls’ attitudes and perceptions of gender norms, including their specific experiences with peer, school, or parental sanctions. Third, our drinking frequency variable could under-estimate cause-and-effect relations. Using quantity, bingeing, and teens’ drinking settings (social or solitary) could aid assessment of the short- and long-term effects of drinking on depression and academic achievement. Drinking attitudes and related variables, however, are not in our dataset. Fourth, it would be worthwhile to follow teens into college and young adulthood (Schulenberg et al. 1994), also a potentially turbulent time, although we did not do so here. Fifth, given our urban sample, our findings may not be generalizable to poorer or more rural areas. This is an important caveat, given the stress and social-adjustment effects that low SES and minority status can have on mental health and grades (Barrett and Turner 2005; Dornbusch et al. 1991; McLeod and Owens 2004) and the higher cumulative risk for substance use among rural youth (Spoth et al. 2001). Similarly, our older data may limit generalizability to contemporary teenage drinking trends, includ-ing gender convergence in drinking behaviors (Johnston et al. 2008).

Limitations notwithstanding, our results demonstrate the flexibility of GST in guiding assessments of academic troubles, drinking, and distress. The diver-gent paths by which GPA influenced depression and drinking imply that teens’ responses to strain can manifest in direct effects alongside indirect chains of cau-sality, possibly via distinct behavioral and emotional adaptations. Further, the long-term effects of drinking on depression, and of depression on GPA, show that responses to strain (including coping) carry potential risks in their own right (see Brezina 1996). Also, the use of multi-group structural equation models allowed us to locate gender differences in these effects, including girls’ potentially social-ization-based vulnerability. Although some coefficients were small and provided limited support for certain hypotheses, the fact that they were significant after controlling for SES, race/ethnicity, and prior measures of the three key variables is noteworthy. Our analysis highlights the role of a key status characteristic (gender) in shaping normative achievement, health-risk behavior, and psychological well-being during a key period of the life course: mid- to late adolescence. The article thus supports continued exploration of gender differences in strain, coping, and psychosocial development.

Acknowledgments: The authors thank the principal investigator of the Youth Development Study, Jeylan T. Mortimer, for use of the data. The Youth Develop-ment Study is supported by a grant (titled “Work Experience and Mental Health: A Panel Study of Youth”) from the National Institute of Child Health and Human Development (HD44138); it was previously supported by the National Institute of




Mental Health (MH42843). Also, the present project was supported in part by the Mayo Foundation for Medical Education and Research. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health and Human Development, the National Institutes of Health, or the Mayo Clinic. We are also grateful to Sarah A. Mustillo, Susan B. Owens, William A. Powell, Diane E. Lentsch, and Tetyana P. Shippee for helpful comments and advice. Comments and suggestions by the editors and anonymous reviewers are also gratefully acknowledged.

APPENDIX

Items and Scaling

EXOGENOUS VARIABLESSocioeconomic Status—9th grade (asked of child’s parents/guardians via mailed questionnaire)1. How much schooling did you complete? Responses: 1 = < high school graduations, 8 = PhD or professional degree2. What was your total household income in 1987 before taxes? Responses: 1 = < $5,000 … 13 = $100,000+ENDOGENOUS VARIABLES (all measured in 9th, 10th, 11th, and 12th grades)Depression 9th 10th 11th 12th

During the past month, how much of the time: (Standardized factor loadings)1. Have you felt downhearted and blue? B = .67

G = .72B = .62 G = .84

B = .77 G = .83

B = .80 G = .81

2. Have you been moody or brooded over things? B = .59 G = .71

B = .40 G = .77

B = .60 G = .72

B = .69 G = .71

3. Have you felt depressed? B = .78 G = .81

B = .98 G = .89

B = .88 G = .91

B = .87 G = .89

4. Have you been in low or very low spirits? B = .76 G = .84

B = .41 G = .86

B = .84 G = .88

B = .81 G = .82

Responses: 1 = no time, 2 = a little time, 3 = some time, 4 = most of the time, 5 = all of the timeDrinking Frequency (natural log transformation in analyses)How many times have you had alcoholic beverages to drink during the past 30 days?Responses: 0 = none, 1 = 1–2, 2 = 3–5, 3 = 6–9, 4 = 10–19, 5 = 20–39, 6 = 40+Grade Point Average (reverse coded)What is your grade point average so far this year?Responses: 1 = A, 2 = A–, 3 = B+, 4 = B, 5 = B–, 6 = C+, 7 = C, 8 = C–, 9 = D+, 10 = D,

11 = D–, 12 = F




REFERENCES

Agnew, Robert. 1992. “Foundation for a General Strain Theory of Crime and Delinquency.” Criminology 30(1):47–87.

———. 2001. “Building on the Foundation of General Strain Theory: Specifying the Types of Strain Most Likely to Lead to Crime and Delinquency.” Journal of Research in Crime and Delinquency 38(4):319–61.

Allen, Joseph P., F. Christy McFarland, Maryfrances R. Porter, Penny Marsh, and Kathleen Boykin McElhaney. 2005. “The Two Faces of Adolescents’ Success with Peers: Ado-lescent Popularity, Social Adaptation, and Deviant Behavior.” Child Development 76(3):747–60.

Aneshensel, Carol S. and George J. Huba. 1983. “Depression, Alcohol Use, and Smoking over One Year: A Four-Wave Longitudinal Causal Model.” Journal of Abnormal Psychology 92(2):134–50.

——— and Jo C. Phelan, Eds. 1999. Handbook of the Sociology of Mental Health. New York: Klu-wer Academic/Plenum Publishers.

Bachman, Jerald G., Katherine N. Wadsworth, Patrick M. O’Malley, Lloyd D. Johnston, and John E. Schulenberg. 1997. Smoking, Drinking, and Drug Use in Young Adulthood: The Impacts of New Freedoms and New Responsibilities. Mahwah, NJ: Erlbaum.

Baker, Joseph O. 2010. “The Expression of Low Self-Control as Problematic Drinking in Ado-lescents: An Integrated Control Perspective.” Journal of Criminal Justice 38(3):237–44.

Barrett, Anne E. and R. Jay Turner. 2005. “Family Structure and Mental Health: The Mediat-ing Effects of Socioeconomic Status, Family Process, and Social Stress.” Journal of Health and Social Behavior 46(2):156–69.

Bartusch, Dawn J. and Ross L. Matsueda. 1996. “Gender, Reflected Appraisals, and Label-ing: A Cross-Group Test of an Interactionist Theory of Delinquency.” Social Forces 75(1):145–76.

Bentler, Peter M. 2007. EQS 6.1 for Windows. Encino, CA: Multivariate Software, Inc.Bidwell, Charles E. and Noah E. Friedkin. 1988. “The Sociology of Education.” Pp. 449–509 in

Handbook of Sociology, edited by N. J. Smelser. Newbury Park, CA: Sage.Brezina, Timothy. 1996. “Adapting to Strain: An Examination of Delinquent Coping

Responses.” Criminology 34(1):39–60.———. 2000. “Delinquent Problem-Solving: An Interpretive Framework for Criminological

Theory and Research.” Journal of Research in Crime and Delinquency 37(1):3–30.Broidy, Lisa and Robert Agnew. 1997. “Gender and Crime: A General Strain Theory Perspec-

tive.” Journal of Research in Crime and Delinquency 34(3):275–306.Broman, Clifford L., Xin Li, and Mark Reckase. 2008. “Family Structure and Mediators of

Adolescent Drug Use.” Journal of Family Issues 29(12):1625–49.Brook, Robert H., John E. Ware, Jr., Allyson Davies-Avery, Anita L. Stewart, Cathy A. Donald,

William H. Rogers, Kathleen N. Williams, and Shawn A. Johnston. 1979. “Overview of Adult Health Status Measures Fielded in Rand’s Health Insurance Study.” Medical Care 17(7):i–131.

Cavanagh, Shannon E., Catherine Riegle-Crumb, and Robert Crosnoe. 2007. “Puberty and the Education of Girls.” Social Psychology Quarterly 70(2):186–98.

Centers for Disease Control and Prevention, Department of Health and Human Services. 2008. “Alcohol Terms.” Retrieved September 7, 2008 from http://www.cdc.gov/alcohol/terms.htm.

Compas, Bruce E., Sydney Ey, and Kathryn Grant. 1993. “Taxonomy, Assessment, and Diag-nosis of Depression during Adolescence.” Psychological Bulletin 114(2):323–44.




Cooper, M. Lynne, Michael R. Frone, Marcia Russell, and Pamela Mudar. 1995. “Drinking to Regulate Positive and Negative Emotions: A Motivational Model of Alcohol Use.” Journal of Personality & Social Psychology 69(5):990–1005.

Costello, Elizabeth and Adrian Angold. 1988. “Scales to Assess Child and Adolescent Depres-sion: Checklists, Screens, and Nets.” Journal of the American Academy of Child and Ado-lescent Psychiatry 27(6):726–37.

Covington, Martin V. 1992. Making the Grade: A Self-Worth Perspective on Motivation and School Reform. Cambridge, UK: Cambridge University Press.

———. 1998. The Will to Learn: A Guide for Motivating Young People. New York: Cambridge University Press.

Crosnoe, Robert. 2006. “The Connection between Academic Failure and Adolescent Drinking in Secondary School.” Sociology of Education 79(1):44–60.

———, Chandra Muller, and Kenneth Frank. 2004. “Peer Context and the Consequences of Adolescent Drinking.” Social Problems 51(2):288–304.

Diego, Miguel A., Tiffany M. Field, and Christopher E. Sanders. 2003. “Academic Perfor-mance, Popularity, and Depression Predict Adolescent Substance Use.” Adolescence 38(149):35–42.

DiMaggio, Paul. 1982. “Cultural Capital and School Success: The Impact of Status Culture Participation on the Grades of U.S. High School Students.” American Sociological Review 47(2):189–201.

Dornbusch, Sanford M., Philip L. Ritter, and Laurence Steinberg. 1991. “Community Influ-ences on the Relation of Family Statuses to Adolescent School Performance: Differ-ences between African Americans and Non-Hispanic Whites.” American Journal of Edu-cation 99(4):543–67.

Duckworth, Angela L. and Martin E. P. Seligman. 2006. “Self-Discipline Gives Girls the Edge: Gender in Self-Discipline, Grades, and Achievement Test Scores.” Journal of Educational Psychology 98(1):198–208.

Dumais, Susan A. 2002. “Cultural Capital, Gender, and School Success: The Role of Habitus.” Sociology of Education 75(1):44–68.

Farkas, George. 2003. “Cognitive Skills and Noncognitive Traits and Behaviors in Stratifica-tion Processes.” Annual Review of Sociology 29:541–62.

Gaughan, Monica. 2006. “The Gender Structure of Adolescent Peer Influence on Drinking.” Journal of Health and Social Behavior 47(1):47–61.

Gerber, Alan S. and Neil Malhotra. 2008. “Publication Bias in Empirical Sociological Research: Do Arbitrary Significance Levels Distort Published Results?” Sociological Methods & Research 37(1):3–30.

Gore, Susan and Robert H. Aseltine, Jr. 2003. “Race and Ethnic Differences in Depressed Mood Following the Transition from High School.” Journal of Health and Social Behavior 44(3):370–89.

Hallfors, Denise D., Martha W. Waller, Daniel Bauer, Carol A. Ford, and Carolyn T. Halpern. 2005. “Which Comes First in Adolescence—Sex and Drugs or Depression?” American Journal of Preventive Medicine 29(3):163–70

Hansell, Stephen and Helene Raskin White. 1991. “Adolescent Drug Use, Psychological Dis-tress, and Physical Symptoms.” Journal of Health and Social Behavior 32(3):288–301.

Jang, Sung Joon and Terence P. Thornberry. 1998. “Self-Esteem, Delinquent Peers, and Delin-quency: A Test of the Self-Enhancement Thesis.” American Sociological Review 63(4): 586–98.

Jennings, Wesley G., Nicole L. Piquero, Angela R. Gover, and Deanna M. Pérez. 2009. “Gen-der and General Strain Theory: A Replication and Exploration of Broidy and Agnew’s




Gender/Strain Hypothesis among a Sample of Southwestern Mexican American Ado-lescents.” Journal of Criminal Justice 37(4):404–17.

Johnston, Lloyd D., Patrick M. O’Malley, Jerald G. Bachman, and John E. Schulenberg. 2008. Monitoring the Future National Survey Results on Drug Use, 1975–2007, Vol. I: Secondary School Students, NIH Publication No. 08-6418A. Bethesda, MD: National Institute on Drug Abuse.

Kostelecky, Kyle L. 2005. “Parental Attachment, Academic Achievement, Life Events and Their Relationship to Alcohol and Drug Use During Adolescence.” Journal of Adoles-cence 28(5):665–69.

Leadbeater, Bonnie J., Gabriel P. Kuperminc, Sidney J. Blatt, and Christopher Hertzog. 1999. “A Multivariate Model of Gender Differences in Adolescents’ Internalizing and Exter-nalizing Problems.” Developmental Psychology 35(5):1268–82.

Locke, Thomas F. and Michael D. Newcomb. 2001. “Alcohol Involvement and Dysphoria: A Longitudinal Examination of Gender Differences from Late Adolescence to Adult-hood.” Psychology of Addictive Behaviors 15(3):227–36.

——— and Michael D. Newcomb. 2003. “Gender Differences and Psychosocial Factors Asso-ciated with Alcohol Involvement and Dysphoria in Adolescence.” Journal of Child & Adolescent Substance Abuse 12(3):45–70.

Lovaglia, Michael J. and Jeffrey A. Houser. 1996. “Emotional Reaction and Status in Groups.” American Sociological Review 61(5):867–83.

Mazerolle, Paul and Jeff Maahs. 2000. “General Strain and Delinquency: An Alternative Examination of Conditioning Influences.” Justice Quarterly 17(4):753–78.

McLanahan, Sara and Gary Sandefur. 1994. Growing up with a Single Parent: What Hurts, What Helps. Cambridge, MA: Harvard University Press.

McLeod, Jane D. and Timothy J. Owens. 2004. “Psychological Well-Being across the Early Life Course: Variations by Socioeconomic Status, Gender, and Race.” Social Psychology Quarterly 67(3):257–78.

Miech, Richard Allen and Michael J. Shanahan. 2000. “Socioeconomic Status and Depression over the Life Course.” Journal of Health and Social Behavior 41(2):162–76.

Mortimer, Jeylan T. 2003. Working and Growing up in America. Cambridge, MA: Harvard Uni-versity Press.

——— and Michael J. Shanahan, Eds. 2003. Handbook of the Life Course. New York: Kluwer Academic/Plenum Publishers.

Needham, Belinda L., Robert Crosnoe, and Chandra Muller. 2004. “Academic Failure in Sec-ondary School: The Inter-Related Role of Health Problems and Educational Context.” Social Problems 51(4):569–86.

Nolen-Hoeksema, Susan. 1990. Sex Differences in Depression. Stanford, CA: Stanford Univer-sity Press.

——— and Colleen Corte. 2004. “Gender and Self-Regulation.” Pp. 411–21 in Handbook of Self-Regulation: Research, Theory, and Applications, edited by R. F. Baumeister and K. D. Vohs. New York: Guilford.

Owens, Timothy J. 1994. “Two Dimensions of Self-Esteem: Reciprocal Effects of Positive Self-Worth and Self-Deprecation on Adolescent Problems.” American Sociological Review 59(3):391–407.

———. 2005. From Adolescence to Adulthood in the Vietnam Era. New York: Springer.———, Jeylan T. Mortimer, and Michael D. Finch. 1996. “Self-Determination as a Source of

Self-Esteem in Adolescence.” Social Forces 74(4):1377–404.Pedhazur, Elazar J. 1997. Multiple Regression in Behavioral Research: Explanation and Prediction.

Fort Worth, TX: Harcourt Brace.




Peirce, Robert S., Michael R. Frone, Marcia Russell, and M. Lynne Cooper. 1994. “Relation-ship of Financial Strain and Psychosocial Resources to Alcohol Use and Abuse: The Mediating Role of Negative Affect and Drinking Motives.” Journal of Health and Social Behavior 35(4):291–308.

Poulin, Christiane, Denise Hand, Brock Boudreau, and Darcy Santor. 2005. “Gender Differ-ences in the Association between Substance Use and Elevated Depressive Symptoms in a General Adolescent Population.” Addiction 100(4):525–25.

Resnick, Michael D., Peter S. Bearman, Robert W. Blum, Karl E. Bauman, Kathleen M. Harris, Jo Jones, Joyce Tabor, Trish Beuhring, Renee E. Sieving, Marcia Shew, Marjorie Ireland, Linda H. Bearinger, and J. Richard Udry. 1997. “Protecting Adolescents from Harm. Findings from the National Longitudinal Study on Adolescent Health.” Journal of the American Medical Association 278(10):823–32.

Robinson, Dawn T. and Lynn Smith-Lovin. 1992. “Selective Interaction as a Strategy for Iden-tity Maintenance: An Affect Control Model.” Social Psychology Quarterly 55(1):12–28.

Roeser, Robert W., Jacquelynne S. Eccles, and Arnold J. Sameroff. 1998. “Academic and Emo-tional Functioning in Early Adolescence: Longitudinal Relations, Patterns, and Predic-tion by Experience in Middle School.” Development and Psychopathology 10(2):321–52.

Rosenberg, Morris, Carmi Schooler, and Carrie Schoenbach. 1989. “Self-Esteem and Ado-lescent Problems: Modeling Reciprocal Effects.” American Sociological Review 54(6): 1004–18.

Rosenfield, Sarah, Jean Vertefuille, and Donna D. McAlpine. 2000. “Gender Stratification and Mental Health: An Exploration of Dimensions of the Self.” Social Psychology Quarterly 63(3):208–23.

Scheidt, Peter, Mary D. Overpeck, Wendy Wyatt, and Anna Aszmann. 2000. “Adolescents’ General Health and Well-Being.” Pp 24–38 in Health and Health Behaviour among Young People. WHO Policy Series: Health Policy for Children and Adolescents, Issue 1, edited by C. Currie, K. Hurrelmann, W. Settertobulte, R. Smith, and J. Todd. Retrieved May 3, 2010 from http://www.hbsc.org/downloads/Int_Report_00.pdf

Schulenberg, John, Jerald G. Bachman, Patrick M. O’Malley, and Lloyd D. Johnston. 1994. “High School Educational Success and Subsequent Substance Use: A Panel Analysis Following Adolescents into Young Adulthood.” Journal of Health and Social Behavior 35(1):45–62.

Shin, Sunny Hyucksun. 2005. “Need for and Actual Use of Mental Health Service by Adoles-cents in the Child Welfare System.” Children and Youth Services Review 27(10):1071–1083.

Sieving, Renee E., Cheryl L. Perry, and Carolyn L. Williams. 2000. “Do Friendships Change Behaviors, or Do Behaviors Change Friendships? Examining Paths of Influence in Young Adolescents’ Alcohol Use.” Journal of Adolescent Health 26(1):27–35.

Spoth, Richard, Catherine Goldberg, Tricia Neppl, Linda Trudeau, and Suhasini Ramisetty-Mikler. 2001. “Rural–Urban Differences in the Distribution of Parent-Reported Risk Factors for Substance Use among Young Adolescents.” Journal of Substance Abuse 13(4):609–23.

Stewart, Cindy and Thomas G. Power. 2003. “Ethnic, Social Class, and Gender Differences in Adolescent Drinking: Examining Multiple Aspects of Consumption.” Journal of Adoles-cent Research 18(6):575–98.

Substance Abuse and Mental Health Services Administration. 2009. Results from the 2008 National Survey on Drug Use and Health: National Findings, Office of Applied Studies, NSDUH Series H-36, HHS Publication No. SMA 09-4434. Rockville, MD: U.S. Depart-ment of Health and Human Services.

Svensson, Robert. 2003. “Gender Differences in Adolescent Drug Use: The Impact of Parental Monitoring and Peer Deviance.” Youth & Society 34(3):300–29.




Turner, R. Jay and William R. Avison. 1992. “Innovations in the Measurement of Life Stress: Crisis Theory and the Significance of Event Resolution.” Journal of Health and Social Behavior 33(1):36–50.

U.S. Bureau of the Census. 1997. Statistical Abstract of the United States. Washington, DC: U.S. Government Publishing Printing Office.

Ware, John E. Jr., Shawn A. Johnston, Allyson Davies-Avery, and Robert H. Brook. 1987. “Cur-rent HIS Mental Health Battery.” Pp. 94–105 in Conceptualization and Measurement of Health Habits for Adults in the Health Insurance Study: Volume III: Mental Health. Santa Monica, CA: Rand Corporation.

Warner, Lynn A. and Helene R. White. 2003. “Longitudinal Effects of Age at Onset and First Drinking Situations on Problem Drinking.” Substance Use & Misuse 38(14):1983–2016.

Windle, Michael. 1999. Alcohol Use among Adolescents. Thousand Oaks, CA: Sage.



gpa, depression, and drinking: a longitudinal comparison of high school boys and girls

Documents