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Soc Psychol Educ (2013) 16:23–43 DOI 10.1007/s11218-012-9206-2

Academic achievement and behavioral health among Asian American and African American adolescents: testing the model minority and inferior minority assumptions Arthur L. Whaley · La Tonya Noel

Received: 22 June 2012 / Accepted: 18 October 2012 / Published online: 27 November 2012 © Springer Science+Business Media Dordrecht 2012

Abstract The present study tested the model minority and inferior minority assumptions by examining the relationship between academic performance and measures of behavioral health in a subsample of 3,008 (22 %) participants in a nationally representative, multicultural sample of 13,601 students in the 2001 Youth Risk Behavioral Survey, comparing Asian Americans (N = 408) and African Americans (N = 2,600). Specifically, the study examined associations of students’ self-reported grades with suicide risk, substance abuse, and violent behaviors. The findings revealed that high academic performance is a protective factor against behavioral health problems for both ethnic groups. The results raise questions about the focus on high achievement among Asian Americans versus academic underachievement among African Americans. Implications for theory, research, training and practice in addressing the mental health implications of achievement behavior in Asian American and African American youth are discussed. Keywords Asian Americans · African Americans · Academic achievement · Behavioral health · Disidentification · Sociocultural theories 1 Introduction Conceptual models applied to Asian American achievement consider them a “model minority” positing superior academic performance linked to family socialization and

A. L. Whaley (B) Department of Psychology, Texas Southern University, 3100 Cleburne Street, PAB 320E, Houston, TX 77004, USA e-mail: [email protected] L. Noel College of Social Work, Florida State University, Tallahassee, FL, 32306-2570, USA

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A. L. Whaley, L. Noel

other cultural attributes (e.g., Steinberg et al. 1992). This view of Asian American students is often held by various ethnic/racial groups including Asians themselves (Kao et al. 2000; Wong et al. 1998). In contrast, sociocultural theories about African American’s academic achievement or schooling behavior often emphasize low performance as a function of opposition in the culture of origin or reaction to the prejudices of the dominant culture (see Fordham and Ogbu 1986; Ogbu 2004; Steele 1997; Steele and Aronson 1995). The group-specific focus of these cultural perspectives accommodates the stereotypic views of ethnic/racial differences in academic achievement. Specifically, cultural stereotypes in research addressing the academic performance of various ethnic groups are the reason for the differential paradigms in the study of Asian American students versus African American students. Slaughter-Defoe et al. (1990) review of the history of research on Asian American and African American youth shows evidence of racial bias in the study of ethnic/racial differences in academic achievement. An example is the study by Steinberg et al. (1992) which attempts to examine multiple psychosocial factors across various ethnic/racial groups. However, their hypothesis regarding family socialization and achievement stems from the model minority stereotype. In the Steinberg et al. (1992) study, Latino and White students scored higher on “authoritative parenting” than Black and Asian American students which contradicted the common assumption that family socialization is a major contributor to Asian American high achievement. Thus their results revealed that Asian American and African American students are more similar on the factor that they consider a cultural difference to account for the disparity in academic performance between these two ethnic/racial groups. One implication of these findings is that multifaceted psychological processes underlie ethnic/differences in academic performance, especially as it is reflected in GPAs during high school. Museus (2008) pointed out that these stereotypic views of Asian American students and their African American counterparts reflect, respectively, the “model minority” and “inferior minority” assumptions about ethnic differences in academic achievement. There are a number of empirical studies that challenge the validity of these cultural perspectives on the academic achievement of Asian Americans versus African Americans (e.g., Choi 2007; Choi and Lahey 2006; Lee and Rotheram-Borus 2009; Kawai 2005; Lew 2006; Steinberg et al. 1992; Stricker and Ward 2004; Wing 2007; Wong et al. 1998). Nevertheless, research on the academic achievement of different ethnic/racial groups in the U.S. tends to focus on high achievement in Asian Americans and low achievement in African Americans (Slaughter-Defoe et al. 1990). These studies often fail to distinguish between a phenomenon and the factors underlying it. In other words, ethnic differences in academic performance may not reflect cultural differences in beliefs about the value of education. In a study of the role of individual, family, and peer factors in academic achievement of a multicultural sample of 15,000 Asian American, African American, Hispanic, and White students from select cities around the country, Steinberg et al. (1992) found that Asian American high school students had higher grades, and African American students had lower grades, than the remaining ethnic/racial groups. Studies utilizing data from the National Education Longitudinal Study (NELS) revealed ethnic/racial differences in school grades and/or standardized test scores with Asian Americans

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Model minority and inferior minority assumptions

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performing higher, and African Americans (and Latinos) underperforming, relative to European American students (Ainsworth-Darnell and Downey 1998; Harris and Robinson 2007; Lundy and Firebaugh 2005; Osborne 1997). Thus a number of studies show the phenomenon and appear to be consistent with the model minority assumption. It is important to note that these studies involve high school students, and these ethnic/racial differences in academic performance may not occur at the college level. For example, Wong et al. (1998) found no differences between Asian Americans and African Americans, as well as other ethnic/racial groups, in terms of academic performance in their college sample. To date, few studies employ a research paradigm that critically evaluates the model minority and inferior minority assumptions in a single investigation. 2 The model minority assumption Although past research ostensibly supports the model minority perspective, at least at the secondary school level, there are a number of additional factors that must be considered. The broad category of “Asian” obscures ethnic subgroup and individual differences in academic and psychosocial outcomes. Like other ethnic/racial groups, Asian Americans are not a monolithic group, but represent diverse ethnic subgroups varying with regard to demographic background, culture, and other social factors (Choi and Lahey 2006; Lee and Rotheram-Borus 2009; Yoo et al. 2010). The model minority assumption is also used to argue that racism is not a barrier to minority progress (Kawai 2005; Yoo et al. 2010). This argument is contradicted by studies demonstrating that Asian Americans report significant experiences with racism (Alvarez et al. 2006; Lee et al. 2009; Wing 2007). Finally, a corollary of the superior academic performance, attributed to the model minority stereotype, is higher psychosocial adjustment and well-being among Asian American students. Studies comparing Asian Americans to other ethnic/racial groups do not indicate consistently better mental health and well-being for the former group. In fact, Asian American students have been found to exhibit poorer outcomes during some mental health evaluations (Choi and Lahey 2006; Lee and Rotheram-Borus 2009). Moreover, Lee et al. (2009) found that racial discrimination is a significant source of stress and poor mental health among Asian American young adults. Most mental health studies, unfortunately, do not include academic performance. Nevertheless, such findings challenge the basic tenets of the model minority perspective. 3 The inferior minority assumption Sociocultural theories related to the inferiority model of African American academic achievement have also been called into question by the bulk of empirical research (Whaley and Noel 2011, 2012). For example, African American students report very favorable educational outlooks like other ethnic/racial groups, but their pro-school attitudes usually do not translate into better study habits or skills (Ainsworth-Darnell and Downey 1998; Lundy and Firebaugh 2005; Morgan and Mehta 2004; Steinberg et al. 1992). These findings challenge a basic assumption of sociocultural theories

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that low achievement or poor academic performance among Black students reflects negative attitudes toward schooling, education, or academic success. Academic disidentification or academic disengagement is a concept at the core of major sociocultural theories reflecting the inferiority model of Black achievement (Morgan and Mehta 2004; Whaley and Noel 2011). The main premise is that African American students do not invest themselves in academic pursuits to avoid failure experiences or same-race peer sanctions (Fordham and Ogbu 1986; Ogbu 2004; Steele 1997; Steele and Aronson 1995). Empirical tests of the academic disidentification hypothesis have yielded mixed results. Some research indicates that global self-esteem in African American students is not linked to school grades or standardized test performance like it is for European American students (Osborne 1997). Other research indicates that GPA is correlated with academic self-concept but not global self-esteem in African American students (Awad 2007; Cokley 2002; Jonson-Reid et al. 2005; Morgan and Mehta 2004; Witherspoon et al. 1997). In their comprehensive review of the literature, Gray-Little and Hafdahl (2000) found that Black students report higher self-esteem than White students despite lower academic performance for measures of both global self-esteem and academic self-esteem. Osborne (1995, 1997) interpreted such findings as evidence in support of sociocultural theories that portray African American students as lacking interest in academic achievement. Black students’ academic self-evaluations may have a weaker association with their measured academic performances than their White counterparts, but this discounting of performance evaluations does not lead to a more complete disidentification with the schooling process or with academic achievement in general (Morgan and Mehta 2004). In addition, Cokely (2003) found intrinsic motivation (to learn) to be associated with self-esteem but not academic self-concept in a sample of African American college students. Taken together, these empirical studies contradict the notion that lack of correlation between global selfesteem and GPA is a reflection of disinterest in learning and achievement among Black students.

4 Academic performance and behavioral health across ethnic/racial groups Self-esteem may not be the best measure of psychological adjustment. Martin et al. (2005) conducted a longitudinal study of perceived academic performance as a predictor of suicide risk over a three-year period among students in 27 high schools. Students who reported that they were failing academically in the second year were at significantly higher suicide risk in the third year independent of self-esteem (Martin et al. 2005). Other studies examining suicide risk, substance abuse, or violent behavior have also found greater risk among students with failing grades (Bry et al. 1982; Godley 2006; Herrenkohl et al. 2000; Kaplan et al. 1999). These studies, however, did not consider the potential moderating effects of ethnic/racial background. A number of studies have addressed mental health functioning of Asian American students, yet little attention has been devoted to behavioral health variables in terms of their association with academic achievement among African American students. The lack of research on behavioral health correlates of Black academic achievement

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may also be a consequence of the biased view that education is unimportant to African Americans. Empirical study of model minority and inferior minority perspectives on academic achievement should explore within-group variations in academic and psychosocial outcomes in a multiethnic or multicultural sample. Ethnic/racial group differences are more likely to be discovered by within-group comparisons than across-group comparisons (Gordon Rouse and Austin 2002). Cultural factors are more likely to be implicated, if between-group variation is greater than within-group variation. Indeed Gordon Rouse and Austin (2002) found that within-group analyses yielded important differences across ethnic/racial groups in terms of academic motivation. The purpose of the current study was to examine the association between academic performance and measures of behavioral health in a subsample of 3,008 (22 %) of the 13,601 high school students who participated in the 2001 Youth Risk Behavior Survey. Specifically, the association of self-reported grades with suicide risk, substance abuse, and violent behaviors were examined for Asian American and African American students. These behavioral health variables were selected to reflect severe problems. For example, the measure of substance abuse focused on illicit substances instead of alcohol or tobacco. According to hypotheses based on the model minority and inferior model perspectives: 1) Asian American students will report fewer behavioral health problems than their African American counterparts; and 2) the negative association between academic performance and behavioral health problems is less likely to occur for African American students compared to Asian American students. In other words, academic performance or self-reported GPA will be negatively correlated with scores on the behavioral health measures and the strength of the association will be moderated by ethnicity/race.

5 Method 5.1 Data source This study used public-use data from the 2001 Youth Risk Behavioral Survey (YRBS). The YRBS is a national school-based survey that is conducted every two years by the Center for Disease Control and Prevention (CDC). The YRBS focuses on surveying adolescent students concerning priority health-risk behaviors that are most significant among this age group such as alcohol and drug use, tobacco use, sexually transmitted diseases, as well as mental health variables. The YRBS utilizes a multistage sampling procedure to produce a nationally representative sample of high school students. The first stage sampling frame consists of large counties, sub-area of very large counties, or groups of small adjacent counties. The second stage consists of randomly selecting high schools within the first sampling units (CDC 2004). A weighting factor was applied to each student record after the third stage of sampling, classes (English or social studies), to adjust for the oversampling of African American and Hispanic/Latino students. The 2001 survey was selected over the 2003 YRBS and subsequent years for the following reasons: First, there was a change in 2003 which may have influenced the

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experimental demand characteristics. Before 2003, state and local education agencies had to use part of their CDC funds for prevention services to conduct the YRBS, but now they can apply for extra funds to serve as a study site (CDC 2004). Secondly, self-reported GPA was not included after the 2003 YRBS. Thirdly, the reliability of the YRBS instrument was established during the 1999 survey (Brener et al. 2002), so the population and instrument used in the current study are the closest to the cohort used to establish reliability. A final consideration was the fact that Whaley and Frances (2006) study of multiracial identity and these behavioral health variables established the utility of the 2001 YRBS data in research on ethnicity/race. 5.2 Sample The 2001 YRBS unweighted sample contains 13,601 adolescents representing an overall response rate of 63 % to the national school-based survey. The unweighted (weighted) subsample was 3,008 (2,192) which is approximately 22 % of the original sample. The ethnic/racial distribution of the study subsample is 2,600 (1,739) African Americans and 408 (453) Asian Americans. The total sample size for different variables does not add up to the original sample because of missing data and the exclusion of cases that do meet criteria for the study. Missing data have not changed ethnic/racial response patterns on the YRBS in past research (CDC 2004). Similarly, there was no significant difference among African Americans (M = 3.74 %) and Asian Americans (M = 3.03 %) in the percentage of missing data for variables used in the current study. The criteria for inclusion are that the individual case has to be a member of one of the age groups (7 students under age 14 were excluded) and ethnic/racial groups mentioned above and cannot have missing or unknown values for any of the variables in statistical analyses. The distribution of behavioral health and demographic variables across ethnicity/race are presented in Table 1. High and low categories for the measures of behavioral health were derived by dividing scores at the median. 5.3 Measures 5.3.1 Academic performance Academic performance was measured by students’ self-reported grades. Students responded to the following question: “During the past 12 months, how would you describe your grades in school?” The responses were on a scale ranging from 1 to 7, with 1 being “mostly A’s,” 2 “mostly B’s,” 3 “mostly C’s,” 4 “mostly D’s,” 5 “mostly F’s” 6 “none of these grades” and 7 “not sure”. Respondents who selected 6 or 7 were eliminated from the sample. Those who reported “mostly D’s” and “mostly F’s” were combined into one group because of the small numbers in the two groups. 5.3.2 Suicide risk The measure of suicide risk consists of three items that tap depressed mood and thoughts of suicide. A sample item is: “During the past 12 months, did you ever

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Table 1 Weighted distribution of dependent and independent variables by ethnicity/race Asians Americans

African Americans

Weighted N

Percent

Weighted N

Percent

Low

276

61

1,141

66

High

177

39

598

34

Depressed/suicidal

Substance abuse Low

345

76

1,284

74

High

109

24

455

26

Low

367

81

1,252

72

High

86

19

487

28

Violent behavior

Grades A’s

186

51

235

17

B’s

119

33

593

43

C’s

39

11

430

31

D’s or F’s

20

5

128

9

Male

229

51

888

51

Female

223

49

845

49

14

46

10

191

11

15

112

25

482

28

16

99

22

438

25

17

132

29

399

23

18

65

14

229

13

Northeast

50

11

244

14

Midwest

68

15

256

15

South

111

25

1,061

61

West

224

49

178

10

Gender

Age

Geographic region

Metropolitan status Urban

197

44

855

49

Suburban

245

54

856

49

10

1

25

2

Rural

seriously consider attempting suicide?” The items are scored on a “yes-no” response format. “Yes” responses are coded “1” and “no” responses are coded 0. Composite scores were the sum of all items divided by the number of items with scores ranging from 0 to 1 so that higher scores reflect greater suicide risk. The internal consistency of the scale was alpha =.73.

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5.3.3 Substance abuse The use of illicit substances was measured with a five item scale. The substances included marijuana, cocaine, inhalants, heroin, and methampethamines. A sample item is: “During the past 30 days, how many times did you use marijuana?” Each item is scored on a 6-point scale from 1 “0 times” to 6 “40 or more times” in terms of frequency of use. Total scores are computed by summing the items and dividing by the number of items to yield a range from 1 to 6 with higher scores representing more substance abuse. The scale has an internal consistency of alpha =.79. 5.3.4 Violent behavior A scale was developed from the questions about weapon carrying and fighting behavior. A sample item is: “During the past 12 months, how many times were you in a fight on school property?” The scale contained seven items, each with a response range from 1 “0 times” to 6 “12 or more times” on a 5-point scale or 1 “0 times” to 8 “12 or more times” on an 8-point scale. Total scores range from 1 to 8 derived from totaling the item scores and dividing by the number of items. The internal consistency reliability for this scale is alpha =.77.

5.4 Statistical analysis For all analyses, the appropriate weights were applied to the data to account for the complex sampling in the survey design of the YRBS. The Complex Sample module of the statistical program IBM SPSS 19 was used to accommodate the complex survey design and to ensure the accurate estimation of standard errors. The alpha criterion was set at .05 to minimize Type I error. The ethnic/racial distribution of categorical variables of depressed/suicidal, substance abuse, violent/dangerous behavior, self-reported grades, gender, age group, geographic region, and metropolitan status was subjected to chi-square analyses to determine whether there were significant ethnic/racial differences. The adjusted F test is a variant of the Rao-Scott correction to chi-square test of complex survey data (Scott 2007). Statistical significance is based on adjusted Fand its degrees of freedom. Regression analyses were conducted with the dependent continuous variables of suicide risk, substance abuse, and violent behavior and the independent variable of self-reported grades adjusting for gender, age group, geographic region, and metropolitan status. Although suicide risk is a binary variable, the dichotomous scores can be converted to proportions with standard deviations to estimate between-group differences. Geographic region and metropolitan status were not treated as hierarchical variables because they did not represent multiple levels in the sampling frame, so their inclusion as multilevel variables would provide relatively less precision in the estimation of their effects. For each behavioral health outcome, withingroup variation in academic performance was estimated for each ethnic/racial group via comparisons of “A” students with the remaining grade categories of self-reported GPA with a Bonferroni correction for multiple comparisons. Finally, between-group

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analyses for ethnicity/race will be conducted separately within high-achieving and low-achieving groups. 6 Results 6.1 Descriptive analyses The distribution of participants in terms of suicide/depressed, substance abuse, violent behavior, self-reported grades, age group, gender, geographic region, and metropolitan status by ethnicity/race are presented in Table 1. The only behavioral health variable on which Asian Americans and African Americans differed significantly was violent or dangerous behavior with larger percentage of the former group scoring high, χ 2 = 22.38, adjusted F(1, 40) = 11.78, p < .0001. There was significant variation in self-reported grades as a function of ethnic/racial group membership, χ 2 = 282.37, adjusted F(2, 77) = 31.03, p < .0001. This variation is largely due to the extreme grade categories of “mostly A’s” and “mostly D’s or F’s” where African American students are underrepresented in the highest grade category and overrepresented in the failing grades category. In contrast, Asian Americans are overrepresented in the “mostly A’s” category and underrepresented in the “mostly D’s or F’s” categories. The ethnic/racial distribution across the geographic regions in which respondents reside was statistically significant, χ 2 = 489.05, adjusted F(1, 40) = 11.78, p < .0001. African Americans were overrepresented in the South, and Asian Americans were predominant in the West. 6.2 Multivariate analyses For each ethnic/racial group, separate regression analyses were conducted for the dependent variables of suicide risk, substance abuse, and violent behavior with selfreported grades as the independent variables controlling for age group, gender, geographic region, and metropolitan status. The unstandardized betas and standard errors from regression analyses are presented in Table 2. 6.2.1 Suicide risk The overall model effects for self-reported GPA on depressed/suicidal scores were statistically significant for Asian Americans, R 2 = .13, F(10, 23) = 7.00, p < .001 and African Americans, R 2 = .05F (10, 27) = 31.74, p < .001. Self-reported GPA also yielded a significant model effect for Asian Americans, F(3, 30) = 2.68, p < .03 and African Americans, F(3, 34) = 7.17, p < .002, Table 2 presents the parameter estimates from the regression models for suicide risk. The mean scores on the measure of depressed/suicidal risk by self-reported grades and ethnicity/race are depicted in Fig. 1. For Asian American students, there were significantly higher depressed/suicidal scores among “mostly D’s and F’s” students than among “mostly A’s” students, t = 2.79, d f = 32, p < .05. African American students reporting “mostly D’s or

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Table 2 Parameter estimates from regression models for behavioral health variables by ethnicity/race Grades

Asian Americans B

African Americans SE

B

SE

Depressed/suicidal Intercept

−.11

.10

−.00

.03

A’s

0

0

0

0

B’s

.07

.05

00

.02

C’s

.14

.08

.04

.04

.24*

.09

.10*

.03 .05

D’s or F’s

Substance abuse Intercept

.69*

.23

.92*

A’s

0

0

0

0

B’s

.00

.04

.05

.03

C’s

.22

.15

.17*

.04

D’s or F’s

1.29*

.42

.45*

10

Violent behavior Intercept

1.04*

.10

1.03*

.05

A’s

0

0

0

0

B’s

−.00

.04

−.01

.06

C’s

.29

.13

.06

.05

D’s or F’s

1.35*

.38

.34*

.10

All unstandardized betas with an asterisk are significant at p < .05. The regression models were adjusted for gender, age group, geographic region, and metropolitan status

F’s” scored significantly higher on suicide risk than those reporting “mostly A’s,” t = 3.80, df = 36, p < .002.

6.2.2 Substance abuse The overall model effects for self-reported GPA on substance abuse scores was statistically significant among Asian American students, R 2 = .29, F (10, 23) = 3.90, p < .02 and African American students, R 2 = .05, F(10, 27) = 31.74, p < .001. Self-reported GPA also yielded a significant model effect for Asian Americans, F (3, 30) = 5.87, p < .02 and African Americans, F (3, 34) = 12.32, p < .001. Table 2 also presents the parameter estimates from the regression model for substance abuse. The mean scores on the measure of substance abuse by self-reported grades and ethnicity/race are depicted in Fig. 2. For Asian Americans, there were significantly higher scores on the substance abuse scale among “mostly D’s or F’s” students than “mostly A’s” students, t = 2.16, p < .05. African American students with “mostly A’s” reported lower substance abuse scores than those with “mostly C’s,” t = 4.67, df = 36, p < .001, and “mostly D’s or F’s,” t = 4.56, df = 36, p < .001.

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Fig. 1 Mean Suicide Risk Scores by self-reported grades and ethnicity/race

Fig. 2 Mean Substance Abuse Scores by self-reported grades and ethnicity/race

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Fig. 3 Mean Violent Behavior Scores by self-reported grades and ethnicity/race

6.2.3 Violent behavior The overall model effects for self-reported GPA on violent behavior scores was statistically significant for Asian Americans, R 2 = .30, F (10, 20) = 4.37, p < .02 and African Americans, R 2 = .07, F (10, 24) = 16.63, df = p < .001. Self-reported GPA also yielded significant model effects for Asian Americans, F (3, 27) = 9.07, p < .0005 and African Americans, F (3, 31) = 5.15, p < .005. Table 2 also presents the parameter estimates from the regression models for violent behavior. The mean scores on the measure of violent behavior by self-reported grades and ethnicity/race are depicted in Fig. 3. Asian American students reporting “mostly D’s or F’s” scored significantly higher on the violent behavior scale than those reporting “mostly A’s,” t = 3.56, df = 29, p < .005. African American students with “mostly A’s” report lower scores on the violent behavior scale than those reporting “mostly D’s or F’s,” t = 3.41, df = 33, p < .005. 6.2.4 Ethnic/racial group differences within educational status groups As can be seen in Figs. 1, 2 and 3, there are very little ethnic/racial difference among high-achieving students on the behavioral health measures, so supplemental analyses were not performed. There are differences among students receiving most D’s and F’s. The differences between Asian American and African American students within the low-achieving group were tested for statistical significance. No significant ethnic/racial differences were found for depressed/suicidal and substance abuse scores,

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Unadjusted analyses revealed a significant difference between the two ethnic/racial groups for violence/dangerous behavior, R 2 = .08, F(1, 36) = 4.79, d f = p < .05. Analyses adjusting for gender, age, metropolitan status, and geographic region yielded an overall model effect that was significant, R 2 = .15, F(8, 28) = 2.42, d f = p < .05, but reduced the ethnic/racial effect to marginal significance, F(1, 35) = 3.83, p < .06. Asian American students (M = 2.41) scored significantly higher on the measure of violent behavior than African American students (M = 1.82).

7 Discussion The purpose of the present study was to test the model minority and inferior minority assumptions by examining the association between academic performance and behavioral health in a national probability sample of Asian American and African American high school students. Poor academic performance was associated with higher scores on measures of depressed/suicidal, substance abuse, and violent/dangerous behavior. These findings are consistent with past research indicating that poor academic performance is a risk factor for adverse mental health outcomes among high school students (Bry et al. 1982; Godley 2006; Herrenkohl et al. 2000; Kaplan et al. 1999; Martin et al. 2005). However, the predictions from the sociocultural theories that ethnicity/race would moderate this association was not supported. The first hypothesis that African American students would report more behavioral health problems than Asian American students was not supported. Contrary to the hypothesis, Asian American students had similar distributions across categories of suicide risk and substance abuse, and significantly higher scores on violent or dangerous behaviors. This latter finding is at odds with those of Choi and Lahey (2006) who reported significantly more aggressive behaviors among African Americans. It is likely that sociodemographic factors are responsible for the disparities, because the gap between the two ethnic/racial groups closes in both studies when these factors are controlled. The second hypothesis also did not receive support. Previous studies have suggested that academic disidentification, operationalized as poor academic performance and high self-esteem, was unique to Black students, especially African American males (Cokley 2002; Osborne 1995, 1997). Not only does the current study demonstrate that poor academic performance is associated with higher scores on measures of behavioral health problems, but it also shows that this correlation is consistent across the two ethnic/racial groups. For both Asian Americans and African Americans, higher scores indicating more behavioral health problems were found among students who reported failing grades. Choi (2007) also conducted a population-based study of the association between GPA and problem behaviors in a multiethnic sample including Asian American and African American students. Her findings were similar to the ones reported here. Specifically, poor academic performance was associated with more problem behaviors regardless of ethnic/racial background of the adolescent. Our two studies complement each other. Our data comes from the YRBS and Choi analyzed data from the National Longitudinal Study of Adolescent Health (ADD Health). The current study focused exclusively on Asian American and African Americans, while Choi also included

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Hispanic/Latino, European American, multiracial adolescents. Finally, the current study was only able to control for age, gender, metropolitan status, and geographic region. Choi was able to control for parental education. The fact that our findings were similar despite methodological differences suggests a robustness to the phenomenon. Conversely, regardless of ethnic/racial group membership, reports of the highest grades were associated with lower scores on these behavioral health measures. High achievement may be associated with more similarities than differences among students from different ethnic/racial groups. Gordon Rouse and Martin (2002) found that highGPA students had more cognitive motivation than low-GPA students in three different ethnic/racial groups. In the current study, Asian American and African American students in the high achievement category were more similar than their counterparts in the low academic performance category. Indeed Choi found a similar pattern in comparing Black adolescents to Asian American adolescents on risk of having been drunk. Her Fig. 2 has a similar pattern as the figures in this study. These findings suggest that there may be shared meaning among the different ethnic/racial groups’ view of academic achievement and educational attainment as social capital. Both the model minority and inferior minority assumptions are challenged by the present findings, so the argument that Asian Americans’ cultural capital is more relevant to educational gains than that of African Americans becomes immaterial.

7.1 Implications for theory and research The model minority and inferior model views of academic achievement derive from sociocultural perspectives based on ethnic and racial stereotypes (Museus 2008). These stereotypes have had a significant influence on the types of research questions generated for Asian American versus African American students with regard to academic achievement (Slaughter-Defoe et al. 1990). Although the valence (i.e., positive versus negative) of the model minority and inferior minority stereotypes are different, the consequences may be the same. Consistent with this assertion, Whaley and Noel (2011) reviewed articles which demonstrated that “stereotype threat” effects occur for the model minority stereotype just as it does for the inferior minority stereotype. Museus (2008) and Wing (2007) also noted that the stereotypes behind both the model minority and inferior minority perspectives can lead to performance decrements for Asian American and African American students, respectively, in accordance with stereotype threat theory. However, the stereotype threat paradigm is limited in its ability to account for the impact of ethnic/racial stereotypes on academic and behavioral adjustment in a broader sense. A missing element in stereotype threat research is measures of the internalization of stereotypes. Theoretical models are needed to address the impact of these stereotypes on psychosocial functioning. Research on the model minority perspective is beginning to address the issue of internalization of the model minority stereotype among Asian American students (Thompson and Kiang 2010; Yoo et al. 2010). There have not been parallel advances in the study of the internalization of the inferior model perspective among African American students.

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Another neglected area in the study of Asian American student achievement is experiences with racism (Alvarez et al. 2006; Tran and Birman 2010). Lee et al. (2009) conducted focus groups with Asian American young adults, and found that racial discrimination was a significant source of mental health problems for study participants. Alavarez et al. found that racism, especially vicarous exposure, was experienced by the vast majority of their study sample. Moreover, these researchers reported that racial socialization and racial identity were important mediators of participants’ perceptions of racism (Alvarez et al. 2006). However, they did not link experiences with racism to academic achievement. In contrast, theoretical and empirical arguments (Oyserman et al. 1995) identify “racism awareness” as an important factor in the academic success of African American students. Research suggests that academic disidentification in response to racism and discrimination may depend heavily on the Black students’ cultural identity, sense of community, and their socialization in terms of their families’ academic orientation (Ford 1993) and the degree to which they receive racial socialization messages at home (Bowman and Howard 1985) or in community programs (Tucker and Herman 2002; Whaley and McQueen 2004, 2010). Thus the literature is more developed for African Americans than Asian Americans in this area. The pattern of results across levels of self-reported grades and ethnic/racial groups also point to the need to use categorical approaches in the form of educational status groups to study academic achievement. Tran and Birman reviewed the literature on Asian American student achievement and found that the majority of studies use continuous measures of academic performance. Past studies of academic disidentification among African Americans used continuous measures of grade point average or standardized test scores (Cokley 2002; Osborne 1995, 1997). Such measures may obscure important differences that would emerge when academic achievement is defined by educational status group. As mentioned earlier, the literature indicates that academic success is the primary focus of research on Asian Americans, while academic failure is what receives the most attention in studies of African Americans (Slaughter-Defoe et al. 1990). One implicit assumption behind this approach is that nothing about academic excellence can be learned from the study of high-achieving African Americans, and, conversely the study of low-achieving Asian Americans is not fruitful. The validity of this notion is called into question because of insights gained from research that includes low-achieving Asian American students and gifted African Americans students. For example, quantitative and qualitative studies of Asian Americans with low-achieving students in the sample have revealed significant risk of behavior problems among this latter group (Choi 2007; Lee 1994), and differences between them and their high-achieving counterparts in terms of ethnic/racial identity and educational aspiriations (Lew 2006). High achieving African American adolescents are more likely to be in special programs and may have more complex peer relations than the average Black student (Ford and Harris 1996; Horvat and Lewis 2003; Steinberg et al. 1992; Witherspoon et al. 1997). Future research should consider high-achieving and low-achieving students of different ethnic/racial backgrounds and directly measure potential mediators such as racism awareness, academic disindentification, and internalization of achievement-related stereotypes.

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7.2 Implications for training and practice The apparent similarity among high-achieving members of the various ethnic/racial groups with regard to behavioral health outcomes suggests that teacher and counselor training address ethnic/racial stereotypes to minimize differential treatment. A possible consequence of the influence of ethnic/racial stereotypes is that guidance counselors and teachers may invest more in Asian American students than their Black counterparts with the same academic potential. In line with this notion, Rosenbloom and Way (2004) found that some high school teachers subscribed to the model minority stereotype of Asian American students and tended to emphasize their academic ability but questioned that of African American students. Similarly, they are likely to overlook the problems of Asian American students. Teachers’ stereotypic views of Asian American students may cause them to overlook or underestimate problems in need of service (Chang and Sue 2003; Wing 2007). Asian American students may not seek help that they need because of the expectations of teachers and counselors. Lee (1994) interviewed low-achieving Asian American students who reported experiencing mental health difficulties but did not reach out for either educational or psychological support in order to protect the public image of the model minority. A different manifestation of in-school bias for African American students is that teachers and counselors may communicate to African Americans who excel academically that they are different from the Black norm (Peterson-Lewis and Bratton 2004). This subtle form of racism may pressure Black students to interpret upward mobility as diametrically opposed to strong connections to their community. The compromise for Black students may be the development of a racelessness persona which emphasizes individual achievement over collective responsibility (Fordham 1988, 1992), which has been found to be associated with mental health problems for academically successful African American students (Arroyo and Zigler 2005). Training in cultural sensitivity, racism awareness, and cultural competence for counselors, teachers and administrators in high schools may prevent such situations for Asian American and African American students. The fact that low achieving students scored poorly on the measures of behavioral health suggests that underachievement should be viewed as a potential sign of mental health problems in addition to a learning or motivational problem. This study adds to a small literature identifying low academic performance as a risk factor for serious behavioral health problems of suicide risk, substance abuse, and violence among adolescents (Bry et al. 1982; Choi 2007; Godley 2006; Herrenkohl et al. 2000; Kaplan et al. 1999; Martin et al. 2005). Counselors and teachers may want to consider mental health assessments for students who are not performing at their academic potential. Of course, learning deficits should be ruled out, and if present must be addressed before or along with mental health problems. Moreover, the variability in behavioral health outcomes among underachieving Asian American and African American students suggests that counseling interventions may need to be culturally tailored.

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7.3 Limitations of current study A major limitation of this study is the absence of direct measures of internalization of stereotypes, academic disidentification and ethnic/racial identity. This is a shortcoming that we share with past studies testing the academic disidentification hypothesis among African Americans (Cokley 2002; Osborne 1995, 1997). Self-reported grades are another methodological concern because of their susceptibility to social desirability bias. However, the variation in self-reported grades by ethnicity/race suggests that such bias is unlikely. Why would African American students be underrepresented in the high-achieving group and overrepresented in the low-achieving group if social desirability was operating? Studies of academic achievement among Asian Americans are often based on self-reported grades with as many as 33 % of the studies using it as the measure of academic performance (Tran and Birman 2010). In addition, Osborne (1997) and Cullen et al. (2004) both found that use of grades and standardized tests produced parallel outcomes in their analyses of ethnic/racial differences in academic achievement. Next, there is no information on the family, school environment, or local community characteristics of the YRBS respondents. Again, this limitation is also inherent in the earlier studies of academic disidentification (Cokley 2002; Osborne 1995, 1997). Slaughter-Defoe et al. (1990) have advocated for a cultural-ecological approach to the study of academic achievement. The current study is a case in point where complex relationships between academic performance and behavioral health emerged from the study of a multicultural sample of Asian American and African American high school students. Finally, although the study uses a nationally representative of students, it is important to highlight a continual problem found in the YRBS and similar public use datasets with regard to ethnicity/race groupings. When we use categories such as Asian American, we lose valuable information concerning the cultural diversity or ethnic variation within the group. The pattern of academic performance is consistent with the model minority hypothesis, but the extent to which ethnic subgroups of Asian descent with different backgrounds and educational experiences are represented in the sample is unclear. The same argument could be made for the use of “Black” to classify African Americans which includes other groups (from the Caribbean or Africa) in this broad category. Also, as previously mentioned, the current findings were similar to those of Choi (2007) who used another national public use dataset with broad ethnic/racial categories. Nevertheless, we acknowledge the apparent double-bind of using these types of datasets to test stereotypical notions about various ethnic/racial groups. Future research should definitely use more refined measures of ethnicity/race to examine the model minority versus inferior minority stereotypes.

8 Conclusion The current study supports neither the model minority nor the inferior minority assumptions about ethnic/racial differences in adolescent achievement. The study suggests that high academic performance is protective against the risk of suicide, substance

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abuse, and violent behavior for the two ethnic/racial groups represented in this sample, and low achievement puts them both at risk. These findings add to a growing literature that both assumptions stem from ethnic/racial stereotypes, rather than the realities of Asian American and African American students, with corresponding consequences for both groups (e.g., Museus 2008; Whaley and Noel 2011; Wing 2007). These consequences include an underestimation of the mental health needs of Asian American students, and the neglect of the academic potential of African American students. The fact that there was more with-in group variability than between group variability in the association between academic performance and behavioral health challenges the sociocultural theories about adolescent achievement in culturally diverse communities. “The stereotype of Asian ‘success’ much like black ‘failure’ cannot be explained solely on their cultural orientation. Although race and cultures play an important role in student’ outlook and negotiations of their opportunity structure, this process changes and adapts to given social and school contexts” (Lew 2006, p. 350). Moreover, research paradigms that simultaneously examine the assumptions underlying the achievement behavior of Asian American and African American youth not only allow scholars to “kill” the proverbial “two birds with one stone”, but they also highlight the common issues facing these groups with regard to public educational and behavioral health services. According to Wing (2007), “Asian Americans are commonly used by white mainstream society as a ‘wedge’ against other people of color, with their ‘success story’ pitted against African American and Latino demands for equality, including within our public schools. The model minority stereotype fosters discord among people of color rather than unity in struggle against racism and for greater equity for all people.” (p, 481), The current research paradigm may also make a small contribution toward this unified effort toward educational equity and adequate mental health services. References Ainsworth-Darnell, J.W., & Downey, D.B. (1998). Assessing the oppositional culture explanation for racial/ethnic differences in school performance. American Sociological Review, 63, 536–553. Alvarez, A.N., Juang, L., & Liang, C.H. (2006). Asian Americans and racism: When bad things happen to ’model minorities. Cultural Diversity and Ethnic Minority Psychology, 12(3), 477–492. doi:10. 1037/1099-9809.12.3.477. Arroyo, C.G., & Zigler, E. (2005). Racial identity, academic achievement, and the psychological well-being of economically disadvantaged adolescents. Journal of Personality and Social Psychology, 69, 903–914. Awad, G.H. (2007). The role of racial identity, academic self-concept, and self-esteem in the prediction of academic outcomes for African American students. Juornal of Black Psychology, 33, 188–207. Brener, N.D., Kann, L., McManus, T., Kinchen, S.A., Sundberg, E.C., & Ross, J.G. (2002). Reliability of the 1999 youth risk behavior survey questionnaire. Journal of Adolescent Health, 31, 336–342. Bowman, P.J., & Howard, C. (1985). Race-related socialization, motivation, and academic achievement: A study of Black youth in three-generation families. Journal of the American Academy of Child Psychiatry, 24, 134–141. Bry, B.H., McKeon, P., & Pandina, R.J. (1982). Extent of drug use as a function of number of risk factors. Journal of Abnormal Psychology, 91, 273–279. Centers for Disease Control and Prevention. (2004). Methodology of the youth risk behavior surveillance system. Morbidity and Mortality Weekly, 53(No. RR-12), 1–13. Chang, D.F., & Sue, S. (2003). The effects of race and problem type on teachers’ assessments of student behavior. Journal of Consulting and Clinical Psychology, 71(2), 235–242. doi:10.1037/ 0022-006X.71.2.235.

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Author Biographies Arthur L. Whaley is Professor and Chair, Department of Psychology, Texas Southern University. His research involves the study of the role of cultural and cognitive factors in the etiology, diagnosis, and treatment of mental disorders in ethnic/racial populations, with a particular focus on African Americans. La Tonya Noel is Assistant Professor in the College of Social Work, Florida State University. Her research interests include culturally relevant services, health and mental health disparities, integrated/holistic models of health care and evaluation, school social work with populations of color.

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