On the Relation between Social–Emotional and School Functioning During Early Adolescence

Pergamon

Journal of School Psychology, Vol. 39, No. 2, pp. 111–139, 2001 Copyright  2001 Society for the Study of School Psychology Printed in the USA 0022-4405/01 $–see front matter

PII S0022-4405(01)00060-7

On the Relation between Social–Emotional and School Functioning During Early Adolescence Preliminary Findings from Dutch and American Samples Robert W. Roeser Stanford University

Kees van der Wolf Universiteit van Amsterdam

Karen R. Strobel Stanford University In this study, we used data collected from early adolescents (ages 12 to 14 years) in the San Francisco Bay area of the United States and Amsterdam, The Netherlands to examine two questions concerning their social-emotional and school functioning. First, we compared adolescents’ self-reported emotional-behavioral problems, general self-esteem, and their sense that negative moods interfered with their ability to learn in school across the two samples. Consistent with previous research, we found that American youth reported more internalizing and externalizing problems than did their Dutch peers, and said that negative moods interfered more with their ability to learn in school. Second, we examined the relative predictive relations between adolescents’ social-emotional functioning and motivation to learn and their reported investment in or disaffection from school. Both sets of indices predicted investment in both samples, although the pattern of significant relations differed by country. Findings are discussed in relation to a broader model of the social, demographic, and psychological processes that shape patterns of academic investment or disaffection, achievement, and choice during the adolescent years.  2001 Society for the Study of School Psychology. Published by Elsevier Science Ltd Keywords: Adolescence, Motivation, School, Mental health.

Adolescence is an important period in the evolution of young people’s academic and social-emotional functioning in industrialized nations all over the world (Lerner, Ostrom, & Freel, 1997). The manner in which youth Received March 23, 2000; accepted December 20, 2000. Address correspondence and reprint requests to Robert W. Roeser, Stanford University, Cubberley Hall, 485 Lasuen Mall, Stanford, CA 94305-3096. Phone: (650) 723-2109; fax: (650) 725-7412; E-mail: [email protected]

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navigate the concurrent biological, psychological, and social changes they experience during these years can portend long-term patterns of promise or problems in the academic and social-emotional domains of functioning. Although research has shown that not all young people experience significant problems as they address the challenges of this period, there is still cause for concern (Rakoff, 1998; Schulenberg, Maggs, & Hurrelmann, 1997). Studies of adolescents in the United States, for example, have documented increases in internalizing and externalizing problems, and declines in academic engagement during the early years of adolescence in particular (Eccles, Lord, & Roeser, 1996; Elliott, 1994; Petersen, Leffert, Graham, Alwin, & Ding, 1997). Problems during this period can leave adolescents vulnerable to curtailed educational attainments and economic earnings over the longer term (Kessler, Foster, Saunders, & Stang, 1995; Roderick, 1993). In light of these findings, the early adolescent period (ages 10–14) has aptly been called a “turning point” and a “great transition,” and researchers have increasingly focused attention on describing and explaining problematic or promising patterns of functioning during this period (Carnegie Council on Adolescent Development, 1995). CROSS-NATIONAL STUDIES OF ADOLESCENT DEVELOPMENT Concerns about the development of adolescents are not unique to the United States, but are present among elders in many Western democratic nations that are experiencing similar economic and social changes (e.g., Noack & Kracke, 1997; Robins, 1995). Demographic shifts in population, the economic dimensions of globalization, urbanization, and changes in family structures are issues common to most contemporary Western democracies. Such changes can exacerbate adolescent problems because they make the identity formation process more challenging by requiring both youth and their elders to adopt new social roles and to meet new expectations that they may not have encountered in the past. This can increase the uncertainties youth feel as they attempt to find their place in a changing, ongoing cultural concern, and increase the uncertainties their elders feel as they attempt to assist youth in this process (Erikson, 1968). Today, researchers in many industrialized countries are conducting cross-national research on educational and social-emotional outcomes in youth, and on the social actors and systems that shape such outcomes during the adolescent years. This work is aimed at understanding commonalties and differences in developmental pathways, socialization influences, and effective intervention strategies that exist within and across the Western societies under investigation (see Eccles, Wigfield, & Schiefele, 1998; Lefley, 1999; Rutter, 1995; Schulenberg et al., 1997; Stevenson & Stigler, 1992).

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Figure 1. Model of academic functioning.

Consistent with this trend, this article provides a preliminary report on the results of a collaborative effort between the first two authors aimed at understanding patterns of academic engagement, achievement, and choice among early adolescents growing up in The Netherlands and the United States. This particular collaboration was based on the shared interests of the authors in connecting the study of social-emotional functioning with the study of motivation and learning during childhood and adolescence (e.g., Roeser, Eccles, & Strobel, 1998; van der Wolf & Sayer, 1999); on findings that indicate negative changes in functioning among Dutch early adolescents that are similar to those reported among youth in the United States (Beker, Maas-de Waal, Boelhouwer, & Hoff, 1998); and on results of a crossnational study comparing the social-emotional functioning of Dutch and American adolescents. Concerning this latter point, Verhulst, Achenbach, Ferdinand, and Kasius (1993) found, based on adolescents’ self-reports, that American adolescents reported more internalizing and externalizing problems than their Dutch peers, and that females reported more internalizing problems and males more externalizing problems across countries. There was no indication in this study of how such problems might relate to Dutch and American youths’ academic functioning, however, and this was the issue we took up in this study. For instance, we wondered whether American adolescents, because they reported more emotionalbehavioral problems than their Dutch peers, might also feel that negative moods interfered more with their ability to learn in school. The model we used to explore these issues was derived from previous research on motivation and adolescent development and is presented in Figure 1.

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A MODEL OF ACADEMIC ENGAGEMENT AND ACHIEVEMENT Contemporary theorists interested in motivation and development posit that adolescents’ academic engagement and achievement is a conjoint function of aspects of their social worlds, demographic characteristics, and personality- and ability-related factors (Connell, Spencer, & Aber, 1994; Connell & Wellborn, 1991; Deci & Ryan, 1985; Eccles et al., 1998; Snow, 1989). Figure 1 presents a simplified model of these multiple influences. Briefly, the model depicts a causal flow from adolescents’ social spheres of experience (e.g., neighborhood, home, school) and sociodemographic characteristics (e.g., social status) to aspects of their self-system (e.g., academic motivational beliefs, social-emotional well-being, cognitive abilities). Self-related processes are then hypothesized to influence investment in or disaffection from learning activities that, in turn, are hypothesized to affect educational outcomes such as achievement and choice (e.g., course selections, decision to go to college). It is important to note that Figure 1 depicts a “slice in time” and does not reflect the reciprocal processes known to exist between the panels of the model. For instance, there is evidence that just as motivation to learn can influence investment in learning and achievement (Eccles et al., 1998), so too can these academic “outcomes” affect motivation (e.g., Bandura, 1997). Furthermore, just as there is evidence that social-contextual and sociodemographic factors are important predictors of adolescents’ personality and intellectual functioning (see Rutter & Rutter, 1993), so too is there evidence that these characteristics of individuals influence their social environments (e.g., Sameroff, 1983). In this study, we focused on a subset of constructs in this model. Previous research in the United States has shown that early adolescents who feel academically efficacious and who value a subject matter also report greater use of adaptive learning strategies and get higher grades on classroom tests and assignments than early adolescents with lower perceived efficacy and lower valuing of a subject matter. Such proximal beliefs are, in short, linked to engagement and achievement in the middle school classroom (Pintrich & De Groot, 1990). In addition, Roeser, Eccles, and Sameroff (1998) suggested that during the identity struggles of early adolescence, adolescents’ mental health may also affect their engagement and performance in middle school. Testing this empirically, these authors found that early adolescents’ academic efficacy and value beliefs were the strongest predictors of achievement and restraint from negative behaviors at school (e.g., cheating, fighting), but that emotional distress also predicted these outcomes after accounting for the effects of motivation, prior achievement, and sociodemographic characteristics. Specifically, adolescents’ emotional distress was negatively related to their grade point average and positively related to their involvement in problematic behaviors at school. Few other studies, however, have examined the relations of motivation, social-emotional functioning, and patterns of cognitive and behavioral investment in or disaffection from learning.

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In the current study, we address three issues. First, we examine mean level differences in the levels of emotional-behavioral problems, self-esteem, and perceptions that negative moods interfere with learning among Dutch and American early adolescents. Second, we examine the relation between adolescents’ motivation to learn and social-emotional functioning in both samples. Third, we examine the relative predictive contributions of motivational and social-emotional indicators to patterns of investment in or disaffection from learning among these two groups. Consistent with previous research, we predict that (a) American youth will report more socialemotional problems than their Dutch counterparts (e.g., Verhulst et al., 1993) and, concomitantly, more of a sense that such problems negatively affect their ability to learn in school; (b) that motivation to learn will be negatively related to indices of social-emotional distress in both samples (Roeser, Eccles, & Sameroff, 1998); and (c) that both motivation to learn and social-emotional problems will predict the quality of adolescents’ engagement in learning, but adolescents’ motivation to learn will be the stronger predictor in both samples (Roeser, Eccles, & Sameroff, 1998). METHOD Sample Descriptions American sample. In 1997, we recruited a sample of early adolescents from two middle schools in the San Francisco Bay area of California to participate in this study. Both schools serve primarily white, middle- to upperclass families. School principals and teachers were contacted and active parental consent was sought for a subset of students. The participation rate for the solicited sample was 79%, resulting in 97 early adolescents in the study. The sample was drawn from a total of five classrooms: two social studies classes and three science classes. Sixth- (n ⫽ 21), seventh- (n ⫽ 16), and eighthgrade (n ⫽ 60) students participated in the study. There were 57 girls (58.8%) and 40 boys (41.2%). Participants’ race/ethnicity was assessed via youth self-reports: 85% self-identified as white, 12% as Asian American, 2% as African American, and 1% Latino. The mean education level of the participants’ fathers was a master’s degree and that of their mothers was a 4-year college degree. Census data from 1990 documented that the median household income for the areas served by these schools was approximately $100,000. Dutch sample. In 1998, students in a research course at the pre-master’s level at the Pedagogical Department of the University of Amsterdam assisted in the recruitment of a sample of Dutch adolescents. Four upperlevel graduate students trained 60 students from a research course on adolescent problem behaviors in methods of surveying adolescents.1 As part of 1 We wish to thank Karen Heinsman, Saskia Hombroek, Rhodee van Herk, and Miranda van den Akker for their assistance with this project in the Netherlands, and also Rosemary Gonzalez, Derek Lopez, Gisell Quihuis, and Jennifer Henderlong for their assistance in the United States.

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the coursework, students in the course recruited 2 to 4 adolescents to participate in a survey study on motivation to learn and mental health. Letters of parental permission were obtained from adolescents who were recruited. This “snowball procedure” resulted in a sample of 238 adolescents ages 11–17 years who filled out the survey. These youth were very much like the students who were in the university course—primarily non-Surinamese, non-Turkish, non-Morroccan (e.g., European, white) Dutch citizens of middle-class backgrounds who were in the upper-level streams of courses (i.e., tracks) in the country’s educational system. Educationally, these adolescents were enrolled primarily in what is called the general secondary education stream for adolescents between the ages of 12 and 17 years or the pre-university educational stream for adolescents between the ages of 12 and 18 years. In The Netherlands, as in the United States, children and adolescents of middle- and upper-class families are more likely to be in the “higher” streams of the educational system (Dronkers & Ultee, 1995; Oakes, Gamoran, & Page, 1992). Based on educational levels and youth reports of their neighborhoods, we ascertained that the sample consisted of adolescents from primarily middle-class backgrounds who were college bound. The Dutch and American samples then were similar with respect to their majority status and educational level, although the American sample of youth came from wealthier families than their Dutch counterparts. Survey Administration American sample. Survey data were collected from American adolescents in their classrooms in two sessions at the end of the 1997 school year. Trained research assistants administered two questionnaires during school hours. Surveys of the academic constructs were read aloud to students in one session during either their science or social studies class. A survey of the mental health constructs was administered at a later date in the same class but these items were not read aloud to insure student privacy. Students completed these items at their own pace with assistance from the research assistants. T-tests were conducted on all measures to examine between-school and between-subject matter differences. None were found, so measures were standardized within each school and merged together for purposes of analysis. Dutch sample. Survey data were collected from Dutch adolescents in individualized sessions with the university students during the middle of the 1998 school year. Trained university students administered a shortened version of the American survey instrument (translated into Dutch) in a single session with the adolescent during a convenient time outside of school. The adolescents read through the surveys themselves but the university student was available to assist them as they completed the survey.

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Table 1 Constructs, Number of Items, and Scale Reliability Coefficients by Country

Construct

Dutch Sample (N ⫽ 238)

American Sample (N ⫽ 97)

No. Items

␣

␣

4 36 20 16 10

.77 .82 .78 .82 .76

.84 .92 .86 .88 .89

5 4

.63 .64

.84 .85

7 29 4 3 4

.79 .70 — — —

.88 .84 .88 .83 .75

48

.81

.89

Social-Emotional Functioning Positive self-esteem Total problem behavior items Subset internalizing problems Subset externalizing problems Depressive symptoms (CDI-S) Motivation to learn Academic efficacy Academic value Investment in/disaffection from learning Mood interference with learning Use of learning strategies Classroom disruptive behavior Classroom withdrawal behavior Classroom work refusal Social desirability Children’s social desirability scale CDI-S ⫽ short form of the Child Depression Infentory.

Research Instruments Survey instruments for this study drew upon scales from several well-established measures of self-esteem (Rosenberg, 1979), emotional and behavioral problems (Achenbach, 1991), depressive symptoms (Kovacs, 1992), and indicators of motivation to learn (Midgley et al., 1998; Pintrich & De Groot, 1990). Under the direction of the second author at the University of Amsterdam, a subset of these measures were translated into Dutch by three upper-level graduate students who were all at least bilingual (English/ Dutch). Group members individually translated the questionnaire and cross-checked their respective translations with each other and the second author as a means of insuring the comparability of the English and Dutch versions. Cronbach reliability analyses suggested that statistical reliabilities were generally similar across the samples (see Table 1). Additionally, previous research with national probability samples in the Netherlands showed that the various forms of the Child Behavior Checklist (CBCL), of which some items were employed in this study, were reliable and valid in samples of Dutch parents, teachers, and youth (Verhulst & van der Ende, 1997). Assessment of social-emotional functioning. Measures of positive selfesteem, internalizing and externalizing emotional-behavioral problems, and a new measure of mood interference with learning were used as indicators

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of social-emotional functioning. Self-esteem was measured by four positive items of Rosenberg’s (1979) measure.2 Sample items include “On the whole, I am satisfied with myself” and “I feel I have a number of good qualities.” To assess internalizing and externalizing forms of emotional and behavioral problems, we drew a subset of 36 items from Achenbach’s (1991) youth self-report (YSR) form of the CBCL. Each item of the YSR asks adolescents to mark on a 3-point Likert-type scale (0 ⫽ never, 1 ⫽ sometimes, 2 ⫽ often) how often (“now or in the past 6 months”) they have experienced a particular problem or symptom. Adolescents did not complete the full checklist of problems on the YSR due to time constraints and concerns of U.S. school officials about some of the items. Sixteen items were drawn from the withdrawn and anxiety/depression subscales to measure internalizing problems,3 and 20 items were drawn from the delinquent and aggressive subscales to assess externalizing problems.4 We also administered the short form of Kovacs’ (1992) Child Depression Inventory (CDI-S), a measure of depressive symptoms experienced during the prior 2 weeks. For each item, students checked the box next to one of three descriptions that they felt best portrayed their feelings during that period (e.g., “I am sad once in a while,” “I am sad many times,” “I am sad all the time”). Students’ responses were then coded on a 3-point scale (0 ⫽ absence of symptom, 1 ⫽ mild symptom, 2 ⫽ presence symptom).5 A series of new questions were developed for this study by the first author in which youth were specifically asked whether bad moods ever interfered with their ability to concentrate and learn in school. Sample items included “I find it hard to concentrate in my classes because I am in a bad mood” and “I often feel too upset in school to do my work.” Youth responded on a 5-point Likert scale ranging from 1 (not at all true of me) to 5 (very true of 2 There are five positively and five negatively worded items on Rosenberg’s (1979) original self-esteem scale. Owens (1994) has shown that Rosenberg’s full scale actually factors into two distinct constructs when used with adolescents: a measure of self-deprecation (five negatively worded items) and a measure of positive self-esteem (five positively worded items). In this study, we were only interested in positive self-esteem because we had other measures of emotional distress. Furthermore, we used only four of the positively worded items, discarding “I am able to do things as well as most other people” because of the relevance of this item to achievement-related concerns such as school. To minimize the conceptual overlap of the esteem and more achievement-related motivational measures, this item was dropped. 3 The specific items of the YSR used to assess internalizing problems included items 42, 65, 69, 75, 102, 103, 111, 12, 14, 32, 33, 35, 45, 50, 112, 71. 4 It is important to note that the items assessing adolescents’ externalizing problems in particular assessed more minor acts of delinquency and aggression than the full set of measures on the YSR. The specific items of the YSR used to assess externalizing problems included items 26, 39, 43, 63, 90, 101, 3, 7, 16, 19, 20, 21, 23, 27, 37, 86, 87, 94, 95, 104. For the analyses predicting aggressive behavior and refusal behavior in the classroom, we extracted two items, item 101 “school truancy” and item 23 “disobeys at school” from the externalizing problem scale because of the obvious overlap between such item content and the classroom-specific behavior scales we were predicting with the YSR-CBCL scales. 5 It is important to note for purposes of this study that the short form of the CDI does not contain any of the items pertaining to school-related symptoms that are part of the complete CDI scale (Kovacs, 1992).

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me). The final “mood interference scale” included seven items. This scale has been found to be statistically reliable in three different samples of adolescents we have been studying in California and Colorado (␣ ⬎ .85) and shows a 1-month test–retest reliability of r(60) ⫽ .89, p ⬍ .001. As displayed in Table 1, the scale was also reliable among the Dutch sample of adolescents (␣ ⫽ .79). Assessment of motivation to learn. Because of differences in survey administration, U.S. adolescents responded about their motivation in relation to a specific subject matter (social studies or science) while in these particular classrooms; whereas the Dutch adolescents who were surveyed outside of school were asked to report on their motivation to learn in general. Two measures of academic motivation were assessed: students’ self-reported efficacy to learn the material in their science or social studies class (U.S. sample) or in school generally (Dutch sample), and their valuing of the subject (U.S. sample) or school generally (Dutch sample). Items were measured on a 5-point Likert scale (1 ⫽ not at all true of me to 5 ⫽ very true of me). The self-efficacy scale was drawn from the work of Midgley et al. (1998) and consisted of seven items regarding students’ perceived ability to master academic material [e.g., “I’m certain I can master the skills taught in social studies/science class (school) this year”]. The academic value scale was based on the work of Eccles (see Eccles et al., 1998) and included four items that assessed adolescents’ perceptions of the importance and utility of the subject matter (or school generally), as well as their intrinsic interest in the subject matter (or school generally). These measures of motivation were reliable in both samples (see Table 1). Assessment of cognitive investment. Two scales were used to assess students’ self-reported use of cognitive and metacognitive strategies during learning. The cognitive learning-strategy scale was adapted from the work of Pintrich and De Groot (1990) and consisted of 10 items pertaining to the use of cognitive learning strategies such as rehearsal, summarizing and paraphrasing ideas, and organizing study materials (e.g., outlining book chapters). The metacognitive learning-strategy scale was also adapted from Pintrich and De Groot (1990) and included 19 items that assessed strategies such as planning, skimming, comprehension monitoring, and effort management during studying. Students responded to the items on a 7-point Likert scale (1⫽ not at all true of me to 7⫽ very true of me), in terms of their behavior in social studies or science class (U.S. sample) or when they did schoolwork generally (Dutch sample). Because these measures were strongly positively correlated in each sample, Dutch sample: r(70) ⫽ .50, p ⬍ .001; U.S. sample: r(70) ⫽ .76, p ⬍ .001, they were combined together into a single “use of learning strategies scale.” This higher order scale was reliable in each country (see Table 1) and assessed general cognitive investment in learning (Pintrich & Schrauben, 1992).

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Assessment of behavioral disaffection. In the U.S. sample, because the study was conducted in a particular classroom setting, we also examined several self-reported indicators of classroom behavior. These scales were new and were designed to assess what could be considered types of behavioral disaffection in this classroom—those we hypothesized would be linked to particular forms of emotional-behavioral distress (see Roeser, Eccles, & Strobel, 1998). The constituent items, principal components factor analysis with oblimon rotation, alpha reliabilities, and intercorrelations among these subscales are presented in Table 2. Three subscales of behavioral disaffection emerged: withdrawal behaviors in which an adolescent reported attempts to “lay low” and not participate in class; refusal behaviors in which the adolescent reported attempts to refuse to do classwork, study for tests, or come to class; and disruptive aggressive behaviors in which an adolescent reported yelling at the teacher in the classroom regardless of the consequences. Items were measured on a 5-point Likert scale (1 ⫽ not at all true of me to 5 ⫽ very true of me). Covariates. Gender was included in each analysis to account for mean level differences in outcomes (coded ⫺1 for female, 1 for male). A measure of social desirability was also included in each analysis because prior research has shown that self-report measures of mental health often elicit socially desirable response patterns (Shedler, Mayman, & Manis, 1993). We employed a measure of social desirability developed by Crandall, Crandall, and Katkovsky (1965) called the “Children’s Social Desirability” (CSD) scale. The CSD scale is an established measure that can be used with adolescents. It consists of 48 true and false questions such as “I always finish all of my homework on time,” and “I always help people who need help.” A sum score is created such that higher scores, reflective of “true” on the “always” items and “false” on the “sometimes” items, indicate an adolescent who engages in a more socially desirable pattern of survey responding. Finally, because of our interest in the relative predictive relations of socialemotional functioning and motivation to learn with adolescents’ cognitive and behavioral investment in or disaffection from learning, we used a measure of prior achievement as a covariate to account for adolescents’ performance histories in estimating these relations. Prior grade in social studies or science class, measured on a 4-point scale (4 ⫽ A, 0 ⫽ F), was used as a covariate in the U.S. sample, whereas in the Dutch sample, previous overall grade point average (GPA), measured on the same 4-point scale, was used as a covariate. Use of the full GPA for the Dutch sample was conceptually necessary due to the domain general nature of the academic motivation measures assessed in that sample. Final Sample Selection and Matching To equate sample sizes and match them on age and gender across the two countries for purposes of this article, we focused here on white adolescents

* p ⱕ .05, ** p ⱕ .01.

Mean (SD)

Cronbach’s Alpha

1.72 (0.92)

.88

.73

.78

.92

.96

Disruption

2.14 (0.95)

.83

⫺.89 ⫺.78

.91

Withdrawal

Rotated Factor Loadings

1.56 (0.71)

.75

.78 .77 .76 .59

Refusal

Disruption Withdrawal Refusals

Disruption 1.00 .06 .51**

1.00 .32**

Withdrawal

1.00

Refusal

choose not to study for tests in my science class. choose not to do my science homework. refuse to do assignments the teacher gives us in science class. skip my science class on purpose.

Pearson r Correlation Matrix

I I I I

I make it a point to get involved in discussions in my science class (reversed). I try not to be called on by the teacher in science class. I try to stay out of whole-class discussions in my science class.

I talk back to my science teacher even if I know I’ll get in trouble for it. I yell at my science teacher if I don’t like something even if I know I’ll get in trouble for it. I say what I want to in science class even if it is disrespectful to the teacher. I let my science teacher know that s/he doesn’t control me.

Survey Items

Table 2 Factor Loadings and Summary Statistics for Classroom Disaffection Measures

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in the United States and The Netherlands who were between the ages of 12 and 14 years. In the U.S. sample, which was considerably smaller than the full Dutch sample, this included 72 adolescents. A random sample of white Dutch adolescents that was equivalent in size, age, and gender composition was drawn from the overall Dutch sample. This resulted in two samples of 72 adolescents. Because of the small sample sizes, estimates of central tendencies for the problem behavior scales were sensitive to outliers. Prior to running analyses, we examined the distributions of the emotional/behavioral problems and removed 2 American adolescents whose scores on the total set of internalizing and externalizing items were in excess of 3 standard deviations from the sample mean (a 12-year-old male and a 14-year-old female). We then randomly removed two Dutch cases matched on age and gender to create final matched samples of 70 adolescents (38 females and 32 males) in each country. Thus, the final samples were 54% female with a mean age of 13.16 years (SD ⫽ 0.81). Analytic Approaches Analysis of the data proceeded in two main ways. First, we employed analysis of covariance (ANCOVA) procedures to examine mean level differences in social-emotional functioning by country and gender. Second, using correlational and multiple regression techniques, we examined the bivariate and multivariate relations among the indicators of social-emotional functioning, motivation to learn, and cognitive and behavioral investment in or disaffection from learning. Interaction effects between gender and internalizing and externalizing problems on outcomes were also tested, one at a time, due to the small sample size and our desire to maintain an adequate cases-to-predictor variable ratio. Cross-products were used to test these interactions within each sample using procedures outlined by Jaccard, Turrisi, & Wan (1990), where gender was contrasted coded, the social-emotional variables were centered at the group mean, and an interaction term was calculated by taking a cross-product of gender and each functioning measure. RESULTS Cross-National and Gender Differences in Social–Emotional Functioning ANCOVAs were used examine country and gender differences in selfesteem, internalizing and externalizing problems, and mood interference in learning. Due to small sample sizes, the between-subjects effects tested included country (The Netherlands and United States), gender, and their interaction; covariates included age (12, 13, and 14 years) and social desirability. The unadjusted means and standard deviations by country and gender for this set of indicators are presented in Table 3. Summary statistics for the ANCOVAs are found in Table 4.

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Table 3 Unadjusted Means and Standard Deviations for Social-emotional Functioning and Mood Interference by Country and Gender

Measure Positive self-esteem Males Females Total problem behavior items Males Females Subset internalizing problems Males Females Subset externalizing problems Males Females Depressive Symptoms (CDI-S) Males Females Mood interferes with learning Males Females

Dutch Sample (n ⫽ 70)

American Sample (n ⫽ 70)

M (SD)

M (SD)

3.72 3.99 3.49 13.76 12.84 14.53 5.66 5.16 6.08 8.22 7.69 8.68 2.21 1.47 2.84 2.09 1.94 2.22

(0.69) (0.65) (0.65) (7.12) (7.29) (6.97) (4.26) (4.04) (4.44) (4.46) (5.02) (3.92) (2.03) (1.57) (2.18) (0.66) (0.63) (0.66)

4.26 4.41 4.13 17.14 16.97 17.29 7.10 6.69 7.45 14.37 14.19 14.53 2.46 1.74 3.05 2.50 2.65 2.36

(0.76) (0.53) (0.90) (9.80) (9.59) (10.10) (5.29) (5.22) (5.39) (8.86) (8.63) (9.17) (2.76) (2.14) (3.09) (0.78) (0.71) (0.83)

Note. N ⫽ 140; 70 adolescents: 38 females and 32 males from each country; CDI-S ⫽ short form of the Child Depression Inventory.

Self-esteem. ANCOVA results for the positive self-esteem scale showed that after covarying out the significant effects of social desirability (␤ ⫽ .32, p ⱕ .01, Eta-squared ⫽ .11), there was a significant main effect by country, F(1, 136) ⫽ 33.54, p ⱕ .01, Eta squared ⫽ .20, and gender, F(1, 136) ⫽ 10.22, p ⱕ .01, Eta squared ⫽ .07. American males and females reported more positive self-esteem than their Dutch peers, and males in both countries reported higher self-esteem compared with females. No effects for age or the interaction of country and gender were found. YSR emotional/behavioral problems. ANCOVA results for the CBCL items, conceptualized as both a total problem scale and an internalizing and externalizing subscale, revealed only one significant effect: After covarying out the effect of social desirability (␤ ⫽ ⫺.54, p ⱕ .01, Eta squared ⫽ .31), American adolescents reported significantly more externalizing problems than their Dutch peers, F(1, 136) ⫽ 9.80, p ⱕ .01, Eta squared ⫽ .07. No country, gender, or higher order effects were found for internalizing or total problems. CDI-S depressive symptoms. The ANCOVA for the CDI-S (Kovacs, 1992) revealed several significant effects: After accounting for the effect of social

8.73*** 21.77*** 3.85** 31.15*** 5.88*** 13.94***

Positive self-esteem Total problem behavior items Subset internalizing problems Subset externalizing problems Depressive symptoms (CDI-S) Mood interferes with learning

Eta Squared .00 .01 .01 .00 .00 .02

␤ ⫺.03 .09 .11 .04 .03 .13*

Age

.32*** ⫺.49*** ⫺.20** ⫺.54*** ⫺.27*** ⫺.38***

␤ .11 .23 .04 .31 .08 .14

Eta Squared

Social Desirability

33.54*** 0.19 0.92 9.80*** 6.10** 3.94**

F Value .20 .00 .01 .07 .04 .03

Eta Squared

Country

10.22*** 0.12 0.85 0.03 4.03** 0.10

F Value

.07 .00 .01 .00 .03 .00

Eta Squared

Gender

0.47 0.00 0.00 0.04 4.33** 4.94**

.00 .00 .00 .00 .03 .04

Eta Squared

Interaction F Value

Main Effects and Interaction

Note. N ⫽ 140; 70 adolescents from each country; 38 females and 32 males; degrees of freedom (4, 139); ␤ ⫽ Standardized regression coefficient; CDI-S ⫽ short form of the Child Depression Inventory. * p ⱕ .10, ** p ⱕ .05, *** p ⱕ .01.

F Value

Outcome Measure

Total Covariates

Covariate Effects

Table 4 Analysis of Covariance Results for Social-Emotional Problems and Mood Interference with Learning: Comparisons by Country and Gender Controlling for Age and Social Desirability

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desirability (␤ ⫽ ⫺.27, p ⱕ .01, Eta squared ⫽ .08), significant effects for country, F(1, 136) ⫽ 6.10, p ⱕ .05, Eta squared ⫽ .04, gender, F(1, 136) ⫽ 4.03, p ⱕ .05, Eta squared ⫽ .03, and their interaction, F(1, 136) ⫽ 4.33, p ⱕ .05, Eta squared ⫽ .03, were found. American youth reported more frequent symptoms on the CDI-S than did their Dutch peers, and females in both the United States and The Netherlands reported more frequent symptoms than males. The interaction revealed that it was American females who scored higher than any of the other three groups on this depressivesymptoms measure. Mood interference. The final ANCOVA assessed group differences on the mood interference scale. After accounting for effects for age (␤ ⫽ .13, p ⫽ .08, Eta squared ⫽ .02) and social desirability (␤ ⫽ ⫺.38, p ⱕ .01, Eta squared ⫽ .14), we found a significant main effect for country, F(1, 136) ⫽ 3.94, p ⱕ .05, Eta squared ⫽ .03, and a significant interaction between country and gender, F(1, 136) ⫽ 4.94, p ⱕ .05, Eta squared ⫽ .04. American youth reported more mood interference than Dutch youth. A series of post hoc analyses revealed the main source of the Country ⫻ Gender interaction: American male adolescents reported significantly more interference of negative moods on their learning than their Dutch male counterparts, t(62) ⫽ 4.24, p ⱕ .001. Summary. American adolescents reported higher self-esteem, more externalizing problems, more internalizing problems as measured by the CDI-S, and more extensive mood interference in their ability to learn compared with a matched sample of Dutch adolescents. It was American females in particular who reported the highest scores on the CDI-S, and American males in particular who reported the most mood interference with learning. Social desirability was strongly associated with reports of social-emotional functioning in each analysis. Correlations Among Social-Emotional, Motivation, and Engagement Indicators Next, correlations among indicators of social-emotional functioning, motivation to learn, and cognitive engagement in learning were examined. Results are presented in Table 5. Correlations for the Dutch sample are presented above the diagonal and those for the United States are presented below the diagonal. Dutch sample. Among Dutch adolescents, perceived academic efficacy was positively correlated with self-esteem, but was not significantly correlated with emotional-behavioral problems as assessed by the YSR-CBCL subscales or the CDI-S. Academic value was unrelated to any of these socialemotional indicators. In terms of mood interference, Dutch adolescents

Positive self-esteem Internalizing problems Externalizing problems Depressive symptoms (CDI-S) Academic efficacy Academic value Mood interference Learning-strategy use

— ⫺.49** ⫺.60** ⫺.75** .38** .34** ⫺.50** .33**

1

3 ⫺.25* .33** — .65** ⫺.38** ⫺.21 .59** ⫺.36**

2 ⫺.52** — .58** .68** ⫺.27* .05 .38** ⫺.01

⫺.60** .69** .39** — ⫺.35** ⫺.22 .43** ⫺.19

4 .28* ⫺.14 ⫺.13 ⫺.23 — .40** ⫺.38** .33**

5

a Resutls for Dutch sample (n ⫽ 70) are above the diagonal; results for American sample (n ⫽ 70) are below the diagonal. CDI-S ⫽ short form of the Child Depression Inventory; * p ⱕ .05, ** p ⱕ .01.

1. 2. 3. 4. 5. 6. 7. 8.

Measures

.03 .04 ⫺.14 ⫺.02 .22 — ⫺.15 .62**

6

Table 5 Bivariate Correlations Among Indicators of Academic and Social-Emotional Functioning by Countrya

⫺.44** .49** .41** .49** ⫺.43** ⫺.13 — ⫺.26*

7

⫺.03 ⫺.01 ⫺.09 .00 .33** .38** ⫺.24* —

8

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with poorer self-esteem, more emotional problems, and poorer academic efficacy were more likely to report that bad moods undermined their ability to learn in school. In terms of reported learning-strategy use, only the motivational indicators (efficacy, value) and not the social-emotional indicators were significantly (positively) correlated with learning-strategy use. American sample. The same basic pattern of correlations was found in the U.S. sample. American adolescents’ perceived academic efficacy was positively correlated with their self-esteem, and negatively correlated with their reports of internalizing and externalizing problems. These latter correlations were stronger and, hence, statistically significant among the American compared with the Dutch youth. Academic value was positively associated with self-esteem but, as with the Dutch and other U.S. samples of adolescents, was unrelated to emotional distress (Roeser, Eccles, & Sameroff, 1998). In terms of mood interference, American adolescents with poorer self-esteem, more emotional problems, and poorer academic efficacy beliefs were more likely to report that bad moods interfered with their efforts to learn in school. In terms of reported learning-strategy use, both motivational and mental health variables showed significant bivariate relations among the U.S. adolescents: Academic efficacy, value, and self-esteem were positively correlated and externalizing problems were negatively correlated with learning-strategy use. Multivariate Predictions of Engagement in Learning The next series of analyses used ordinary least squares regression techniques to examine the relative predictive effects of the social-emotional and motivation-to-learn indicators on mood interference and learning-strategy use. Internalizing and externalizing problems, academic efficacy, and value beliefs were used as predictors. Self-esteem and the CDI-S measures were not included in these equations because of their strong correlations with the YSR-CBCL indicators and concerns about multicollinearity. We assumed the two YSR-CBCL subscales were sufficient proxies for adolescents’ overall social-emotional functioning. Gender, prior achievement, and social desirability were also included in these equations as statistical controls. Interactions between gender and internalizing and externalizing problems were tested one at a time and are described in the text. Mood interference. Table 6 presents the regression results for mood interference. For the Dutch, internalizing problems were the strongest positive predictor, and academic efficacy was the strongest negative predictor of mood interference in learning after controlling for social desirability and the other variables in the model. Overall, the model accounted for

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Table 6 Regression Analyses Predicting Self-Reported Interference of Negative Mood on Learning: Standardized Beta Coefficients, Bivariate Correlations, and Adjusted r-Square Values in Two Samples Dutch Sample (n ⫽ 70) Predictors

␤

r

American Sample (n ⫽ 70) ␤

r

Internalizing problems Externalizing problems Academic efficacy Academic value

.40*** .06 ⫺.35*** .03

.49 .41 ⫺.43 ⫺.13

.08 .41*** ⫺.20* .02

.38 .59 ⫺.38 ⫺.15

Prior achievement Social desirability Gender (⫺1 ⫽ female, 1 ⫽ male)

⫺.02 ⫺.33** ⫺.02

⫺.20 ⫺.39 ⫺.21

⫺.04 ⫺.10 .20**

⫺.09 ⫺.40 .19

Total Adjusted r squared F value

.51 8.98***

.43 6.61***

Note. ␤ ⫽ standardized beta regression coefficient; r ⫽ bivariate correlation; all correlations at the |.23| are significant at p ⱕ .05 for n ⫽ 70. * p ⱕ .10; ** p ⱕ .05; *** p ⱕ .01.

51% of the variance. No significant interactions of gender and type of distress on mood interference were found. For the Americans, a slightly different pattern of multivariate predictors was found. Externalizing rather than internalizing problems were the strongest (positive) predictor of mood interference, and academic efficacy had a marginally significant negative predictive association. In addition, among the U.S. adolescents, boys reported more mood interference than girls, a difference not noted in the Dutch sample. Overall, this set of variables accounted for 43% of the variance. No significant interactions of gender and type of distress on mood interference were found. Learning-strategy use. Table 7 presents the regression results for adolescents’ reported use of learning and metacognitive strategies. A similar pattern of predictors emerged across countries. For the Dutch, academic efficacy, academic value, and prior achievement were all significant positive predictors of strategy use. The emotional problem variables had no significant effects. Among the Americans, academic value was the strongest positive predictor of strategy use and, similar to the findings for the Dutch, emotional problems had no relation to strategy use. However, there were significant interactions between gender and internalizing, change in F(1, 62) ⫽ 3.26, p ⫽ .08, adjusted r 2 ⫽ .03, and externalizing, change in F(1, 62) ⫽ 5.40, p ⱕ .05, adjusted r 2 ⫽ .04, problems on learning-strategy use among the U.S. adolescents. Females with higher levels of either type of distress showed steeper declines in their reported use of learning strategies

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Table 7 Regression Analyses Predicting Self-Reported Use of Learning Strategies: Standardized Beta Coefficients, Bivariate Correlations, and Adjusted r-Squares in Two Samples Dutch Sample (n ⫽ 70) Predictors Internalizing problems Externalizing problems Academic efficacy Academic value

␤

r

.01 ⫺.01 .10 ⫺.09 .24** .33 .26** .38

Prior achievement .21** .29 Social desirability .20 .23 Gender (⫺1 ⫽ female, 1 ⫽ male) ⫺.05 ⫺.01 Total adjusted r squared F value

.27 3.28***

American Sample (n ⫽ 70) ␤

r

.12 ⫺.01 ⫺.14 ⫺.36 .06 .33 .50*** .62 .07 .26** ⫺.10

.17 .43 ⫺.07 .51 9.24***

Note. ␤ ⫽ standardized beta regression coefficient; r ⫽ bivariate correlation; all correlations at the |.23| are significant at p ⱕ .05 for n ⫽ 70. * p ⱕ .10; ** p ⱕ .05; *** p ⱕ .01.

compared with the males. Overall, a larger proportion of variation in strategy use was accounted for by these predictors among the Americans (51%) than among the Dutch (27%). Behavioral disaffection. The final series of regression analyses explored the relative predictive associations of the social-emotional, motivational, and statistical control variables with American adolescents’ self-reports of disruptive, refusal, and withdrawal behaviors in the classroom. Results are presented in Figure 2. In the middle of the diagram, we present the significant standardized multivariate beta coefficients found in three separate equations used to predict each behavioral outcome. These coefficients are net of the effects of the statistical control variables (prior achievement, social desirability, and gender) that were also included in the models. Effects of the controls and interactions are described in the text. In the prediction of disruptive behavior, these variables accounted for 50% of the variance, F(7, 62) ⫽ 8.74, p ⱕ .01. Youth reports of internalizing problems and valuing of the class were significant negative predictors of disruptive behavior, whereas externalizing problems were positively associated with acting out in the classroom. No significant interactions of gender and type of distress on disruptive behaviors were found. In the prediction of refusal behaviors, variables in the model accounted for 41% of the variance F(7, 62) ⫽ 6.16, p ⱕ .01. A similar pattern of findings to those reported for disruption were found: Youth reports of internalized distress had a significant negative effect on refusal behaviors, as did valuing of the class, whereas externalized distress had a significant positive

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Figure 2. Prediction of forms of behavioral disaffection. Standardized regression coefficients and adjusted r-square values. Coefficients are adjusted for effects of sex, prior achievement, and social desirability. * p ⱕ .05, ** p ⱕ .01.

predictive effect. The only other (marginally) significant effect found was for gender (␤ ⫽ .18, p ⱕ .08): Boys reported more refusal behavior than girls. No significant interactions of gender and type of distress on refusal behaviors were found. Finally, in the prediction of withdrawal behavior in the classroom, the model accounted for 28% of the variance, F(7, 62) ⫽ 3.47, p ⱕ .01. These behaviors were linked most closely to internalizing problems. Youth reports of internalizing problems had a significant positive predictive effect on withdrawal behaviors, whereas externalizing problems and valuing of class had significant negative predictive effects. A significant interaction between gender and internalizing distress, change in F(1, 62) ⫽ 5.95, p ⱕ .02, adjusted r 2 ⫽ .06, was also found: Females showed greater withdrawal at higher levels of internalized distress compared with boys. DISCUSSION Country Differences Consistent with our hypotheses and previous research, results based on adolescent self-reports indicated that youth who were growing up in rather wealthy suburbs in California reported slightly more emotional problems than did their Dutch peers growing up in middle-class suburbs outside of

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Amsterdam. These findings replicate those from a previous study with representative samples of American and Dutch adolescents that showed American youth reported more internalizing and externalizing emotional-behavioral problems than their Dutch counterparts (Verhulst et al., 1993). In this study, we also showed that American youth felt such problems interfered more with their learning at school than their Dutch peers. Other studies have established the association of different forms of emotional-behavioral problems with lower actual achievement (see Roeser, Eccles, & Strobel, 1998 for discussion). In the future, we plan to deepen our understanding of the specific pathways by which emotional problems can affect achievement among different subpopulations of American and Dutch youth by including multiple indicators of academic performance (grades, test scores), teacher ratings of classroom behavior, and interview data with students who do and do not seem to suffer academically as a result of experiencing depressive symptoms, anger, or other potentially debilitating emotions (e.g., Roeser, Lau, & Midgley, 1999; Roeser, Galloway, Watson, Casey-Cannon, & Keller, 2000). In addition to finding more problems reported by the American adolescents, we also found, perhaps paradoxically, that American adolescents reported higher levels of self-esteem compared with their Dutch peers. How can we reconcile these two sets of findings? First, previous research has found that Americans generally tend to rate themselves higher on self-reported measures of self-esteem, and this trend has, in recent years, been explicated in terms of a powerful self-serving cultural bias, especially among White and male Americans, toward seeing oneself in a favorable light (Kitayama & Markus, 1995). What is interesting is this seems to be part of European-American culture, so it seems plausible to posit that this bias exists among majority groups in both the United States and The Netherlands, perhaps with U.S. adolescents showing more of this bias and, therefore, higher self-esteem, as found in this study. In support of this notion, Achenbach, Verhulst, Baron, & Akkerhuis (1987) reported that both American and Dutch parents tended to, on average, see their children as above average in terms of certain social competencies, but American parents showed this “Lake Woebegone” effect more than the Dutch parents. Second, it could be that those adolescents with externalizing problems in particular, which were more prevalent in the U.S. sample, overestimated their self-esteem due to a positive illusory bias in which they view themselves as unrealistically happy and well-adjusted (see Coie & Jacobs, 1993).6 Finally, it may be that these results reflect cultural and generational norms among majority-group adolescents in each country concerning how willing one should be to express feelings (whatever their valence) about the self with others, with youth in the United States perhaps being more assertive, and Dutch 6

Our thanks to an anonymous reviewer for suggesting this.

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youth being more modest in this regard (e.g., Verhulst et al., 1993). This interpretation is supported by the fact that studies based on Dutch and American parent reports of youth problems found no such cross-national differences (Achenbach et al., 1987). However, this study is dated. Our data show American youth reported more emotional distress than Dutch youth. Are they doing worse? We are not sure. We do believe that understanding the consequences of an adolescents’ self-perceived social-emotional well-being is valuable in and of itself for understanding their development, although the importance of gathering data on their functioning from multiple informants (e.g., parents, teachers) is also clear in terms of understanding the conditions of youth in different industrialized countries in the West. Gender Differences The higher levels of depressive symptoms among the U.S. adolescents were explained largely by the higher scale scores among white American females. In fact, we found that both American and Dutch females reported lower levels of self-esteem and higher levels of depressive symptoms in comparison with males in their respective countries, but the U.S. females reported the most symptoms of any of the groups. These results replicate the considerable body of research in the United States that has documented early adolescent white females as being particularly at-risk for internalizing problems (Petersen et al., 1997; Simmons & Blyth, 1987). The consistency of the gender differences across cultures here and in other studies of Dutch and American youth (Verhulst et al., 1993) suggest the possibility that similar biopsychosocial processes associated with the onset of depressive symptoms among some majority (White) females during puberty are occurring in both countries. These processes may include the stress that arises from the management of multiple concurrent life transitions (Eccles et al., 1996; Simmons & Blyth, 1987), heightened concerns about body image and the link of this to female sex-role socialization pressures and the onset of puberty (Harter, 1990), or other biological and social factors (Petersen et al., 1997). What is interesting for purposes of this study is the fact that such problems tend to be associated with reported disengagement from learning among both male and female Dutch adolescents and, in particular, among white U.S. females. Investigating more closely gender-linked symptom profiles and their associations with academic motivation, engagement, and achievement among youth in both countries is another direction we hope to undertake in our future work. Associations of Motivation, Mental Health, and Engagement Our hypotheses concerning the associations among the motivational, social-emotional, and academic engagement indicators were generally supported across the two samples. For instance, we found that adolescents’ efficacy beliefs were negatively associated with emotional problems and mood

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interference, and that these relations were stronger among the American youth. On the other hand, we found that adolescents’ valuing of school was generally not related to their emotional-behavioral problems, a finding noted previously that we reflect upon more below (Roeser, Eccles, & Sameroff, 1998). Also consistent with our hypotheses, we found that efficacy and value beliefs were the strongest predictors of adolescents’ reported use of learning strategies. However, contrary to our hypotheses, we found that internalized and externalized distress were as strongly associated with American adolescents’ behavioral disaffection in the classroom as was their valuing of school. During early adolescence, both motivational and mental health-related processes are associated with how youth report acting in their classrooms. Finally, it is important to note that we found social desirability to be strongly associated with each self-report indicator of adolescents’ social– emotional functioning. These results highlight the importance of including measures of social desirability when employing self-report measures of mental health (Shedler et al., 1993). In totality, these associations are suggestive of several pathways by which negative moods might affect adolescents’ learning and achievement in school: through disruption of self-regulatory processes essential to learning, through an activation of debilitating motivational beliefs (e.g., lack of efficacy), and through an activation of avoidance-behavioral scripts aimed at self-protective rather than educational ends in the classroom. The results of this study also suggest the possibility that adolescents’ sense of academic efficacy and value may protect them against cognitive and behavioral disengagement from learning during the identity struggles characteristic of this developmental period (see Roeser, Eccles, & Sameroff, 1998). Roeser, Eccles, and Strobel (1998) speculated that such valuing provides adolescents with an intrapsychic resource that affords esteem and gives direction to their life, and perhaps provides a “protected space of psychological functioning” in some emotionally distressed youth against the potentially disruptive effects that anger, sadness, or anxiety can otherwise engender on the learning process. We believe that motivational processes such as feeling academically efficacious or valuing school are among those that protect some adolescents growing up in difficult life circumstances or with difficult emotional problems from otherwise failing in or withdrawing from school. Implications In both the United States and The Netherlands, educators and mental health professionals are addressing the challenge of how to make the link with one another in their work in the schools (Dryfoos, 1994). For schoolbased mental health professionals in particular, the ability to “make the

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link” with educators by designing interventions that “fit” with teachers’ everyday needs and goals seems especially critical for insuring the uptake of such reforms into the ongoing life of the school (see Hunter, Elias, & Norris, 2001). Given that the widespread needs among adolescents for intervention services will continue to be unmet (Adelman & Taylor, 1998), it may prove fruitful for school psychologists and social workers to focus on school-level reforms aimed at promoting students’ motivation to learn, skill development, and participation in the life of the school. Such an approach is health- and systems-oriented rather than pathology- and individual-oriented and may prove more cost effective and efficient (Braden, DiMarinoLinnen, & Good, 2001; Cowen, 1980; Felner et al., 2001; Hawkins, 1997; Kuperminc, Leadbeater, & Blatt, 2001). This is not to say that direct provision of mental health services to the highest need adolescents and their families are not necessary, just that by themselves, such approaches will continue to remain woefully inadequate to meet the scope of needs that adolescent school populations present today, especially in the United States (Dryfoos, 1994). For instance, results of this study revealed a negative association between adolescents’ academic self-efficacy and their sense that bad moods interfered with their learning. Intervention work has shown that raising academic skills and confidence can ameliorate social-emotional-behavioral problems in some children (Coie & Krehbiel, 1984). At the classroom level, this type of intervention might involve implementing strategies such as the use of formative feedback and low-stakes assessments, designing of curricula with clear proximal subgoals, normalization of mistakes as part of the learning process, use of tutors who can role model learning strategies, implementation of cooperative learning techniques, and so on (Bandura, 1997; Hawkins, 1997). Helping teachers to design classroom environments that build the academic skills and sense of efficacy among their most alienated students is one way mental health professionals in the schools can “make the link” with teachers. Results of this study were also consistent with other research that documents the importance of adolescents’ intrinsic and instrumental valuing of school for their short- and long-term engagement in learning (Eccles, 1983; Pintrich, Roeser, & De Groot, 1994; Roeser, Eccles, & Sameroff, 1998). Building adolescents’ valuing of learning in the different subject matters and in school more generally is another set of important psychological “targets” for systems-based interventions. Indeed, reforms that aim to enhance adolescents’ “bonding” to (e.g., valuing of) school have already been empirically established as effective (see Hawkins, 1997). Such reforms often include (a) the use of adult or peer-led tutoring programs to increase valuing through academic success; (b) the creation of smaller communities of learning where teacher-to-student and student-to-student relationships can be developed and, in turn, foster a sense of value and commitment to school

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among students (Felner et al., 2001); (c) affordances for student choice and voice in the classroom and in the broader school (Rutter, 1983); and (d) the use of curricula that speak to the diversity of student interests and socioeconomic, ethnic, and cultural backgrounds (Roeser, Eccles, & Sameroff, 1998). Enhancing students’ valuing of school through reforms such as these that are centered on care, community, and responsive curricula may be crucial in diverting the most troubled or alienated adolescents away from decisions that lead to early school withdrawal (Fine, 1991; Finn, 1989). Limitations and Conclusion Several limitations with the current study are important to mention. First, we focused here on samples of white majority-group adolescents in the Amsterdam and San Francisco Bay areas. Understanding how to improve the educational prospects and mental health status of members of immigrant groups from places like Turkey, Morocco, and Surinam in The Netherlands, and from Mexico and other Latin American and Southeast Asian countries in the United States is a pressing, important, and ongoing scientific and social challenge in each country today. We are currently conducting studies with other subpopulations in our respective countries to address these issues. Second, we relied only on adolescent self-report data in this preliminary report. Obtaining multiple indicators of achievement (e.g., teacher grades, achievement tests) and multiple informants on youths’ academic and social-emotional functioning (e.g., parents, peers, teachers) is the next step in our work to improve the validity of our conclusions. We note, however, that the results reported here are consistent with those obtained in other U.S. samples in which combinations of parent, teacher, and adolescent selfreport measures were used (e.g., Pintrich et al., 1994; Roeser, Eccles, & Sameroff, 1998; Roeser et al., 1999). Finally, although there is evidence to suggest cross-cultural validity in the kinds of measures employed in this study (Verhulst & van der Ende, 1997), there are many reasons for why it is often difficult to interpret results across cultures in studies such as these—only one of which we highlight here. To fully understand patterns of academic and social-emotional functioning, it is necessary to understand the specific educational, familial, and community practices, values, and norms out of which such patterns emerge (Eccles et al., 1996; Lerner et al., 1997). By focusing only on outcomes and not the ecological correlates of such outcomes in this study, we do not know the social sources and consequences of the kinds of differences we found. Increasingly, researchers of adolescent development are attending to the overall organization of adolescents’ behavior that includes the situating of psychological and behavioral outcomes in the unique life-spaces that comprise their development (see Figure 1). Our work continues in this direction.

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In sum, we found that American compared with Dutch adolescents reported more emotional-behavioral problems and were more likely to feel such problems interfered with their ability to learn in school. We also documented that indicators of motivation to learn (conceptualized as adolescents’ perceived academic efficacy and value beliefs) were strong predictors of the quality of their reported cognitive and behavioral engagement in school. These findings suggest that enhancing students’ motivation to learn may be one important goal of programs that school-based mental health professionals design and implement in the schools. Making motivation a central concern in such work is one way that school-based mental health professionals can “make the link” with educators as they continue their efforts to redress problems and promote strengths in and among children and adolescents. REFERENCES Achenbach, T. M. (1991). Integrative guide for the 1991 CBCL/4–18 YSR and TRF profiles. Burlington: University of Vermont Department of Psychiatry. Achenbach, T. M., Verhulst, F. C., Baron, G. D., & Akkerhuis, G. W. (1987). Epidemiological comparisons of American and Dutch children: I. Behavioral/emotional problems and competencies reported by parents for ages 4 to 16. Journal of the American Academy of Child and Adolescent Psychiatry, 26, 317–325. Adelman, H. S., & Taylor, L. (1998). Reframing mental health in schools and expanding school reform. Educational Psychologist, 33, 135–152. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Beker, M., Maas-de Waal, C. J., Boelhouwer, J., & Hoff, S. J. M. (1998). Youth report 1997. Amsterdam: Elsevier. Braden, J. S., DiMarino-Linnen, E., & Good, T. L. (2001). Schools, society, and school psychologists: History and future directions. Journal of School Psychology, 39, 203–219. Carnegie Council on Adolescent Development. (1995). Great transitions: Preparing adolescents for a new century. New York: Carnegie. Coie, J. D., & Jacobs, M. R. (1993). The role of social context in the prevention of conduct disorder. Development and Psychopathology, 5, 263–275. Coie, J. D., & Krehbiel, G. (1984). Effects of academic tutoring on the social status of low-achieving, socially rejected children. Child Development, 55, 1465–1478. Connell, J. P., Spencer, M. B., & Aber, J. L. (1994). Education risk and resilience in African-American youth: Context, self, action, and outcomes in school. Child Development, 65, 493–506. Connell, J. P., & Wellborn, J. G. (1991). Competence, autonomy and relatedeness: A motivational analysis of self-system processes. In M. Gunnar & A. Sroufe (Eds.), Minnesota symposium on child psychology (Vol. 23, pp. 43–77). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Cowen, E. L. (1980). The Primary Mental Health Project: Yesterday, today, and tomorrow. Journal of Special Education, 14, 133–154. Crandall, V., Crandall, V. J., & Katkovsky, W. A. (1965). A children’s social desirability scale. Journal of Consulting Psychology, 29, 27–36. Deci, E., & Ryan, R. (1985). Intrinsic motivation and self-determination in human behavior. New York: Academic Press.

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