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SPECIAL SECTION ARTICLE
Are affluent youth truly “at risk”? Vulnerability and resilience
across three diverse samples
SUNIYA S. LUTHAR AND SAMUEL H. BARKIN
Teachers College, Columbia University
Abstract
Building upon prior findings of elevated problems among East Coast suburban youth through the 11th grade, this study establishes disproportionatelyhigh
incidence of maladjustment across three disparate samples: East Coast Suburban youth at the end of their senior year in high school, and 11th and 12th graders
in (a) a Northwest suburb and (b) an East Coast city. Both East Coast samples showed pronounced elevations in substance use, whereas the Northwest
suburban sample showed marked vulnerability in serious internalizing and externalizing symptoms. Across all samples, parents’ low perceived containment
for substance use (lax repercussions on discovering use) was a major vulnerability factor, followed by parents’ knowledge of their teens’ activities. Overall,
adolescents’ symptom levels were more strongly related to their relationships with mothers than with fathers. An exception was boys’ apparent vulnerability
to fathers’, but not mothers’, perceived depressive symptoms. As with affluent eighth graders, we found that “overscheduling” in extracurriculars is not a critical
vulnerability factor among these high school students. Finally, youth reports suggested that most affluent parents do not indiscriminately bail their children out
of all problem situations (although a small subset, apparently, do). Results are discussed along with the implications for practice and for future research.
Affluent youth are a “newly identified at-risk group,” according
to an editorial statement in Journal of the American Academy
of Child & Adolescent Psychiatry (Koplewicz, Gurian, & Wil-
liams, 2009, p. 1053). The authors note that affluenza, a meta-
phorical illness connoting hyperinvestment in material wealth,
is rapidly spreading among upper-middle class, white-collar
families. The children concomitantly show elevations in var-
ious maladjustment domains (substance use, depression, and
anxiety), indicating the urgent need for preventive interven-
tions (Koplewicz et al., 2009). In support of their arguments,
the authors cite review articles as well as empirical research
by our group on suburban youth in the Northeast (Luthar,
2003; Luthar & Becker, 2002; Luthar & Latendresse, 2005a).
At this stage, we know little about the generalizability of
our early findings. As reported in our 2005 review (Luthar
& Latendresse, 2005a), our first affluent cohort comprised
high schoolers from an affluent Northeastern suburb (Luthar
& D’Avanzo, 1999). Cohort II and Cohort III were middle
schoolers from another suburb in the Northeast, with the for-
mer assessed cross-sectionally and the latter followed over
time. Overall, findings with Cohort III, also known as the
New England Study of Suburban Youth (NESSY) cohort,
did show elevations in problems starting at around the seventh
grade (Luthar & Becker, 2002; Luthar & Latendresse, 2005b),
and escalating by the 10th and 11th grades (Luthar & Ansary,
2005; Luthar & Goldstein, 2008).
What remains to be seen is the degree to which (a) NESSY
students experienced elevated problems even when well past
the major stress of college admissions (at the end of high
school), and, more importantly, (b) whether our early find-
ings might generalize across disparate geographical areas,
which is more important. To illustrate, youth in suburbs might
be more prone to boredom, and thus to problem behaviors
including substance use, than those in large cities where there
are multiple opportunities for “safe” leisure activities such as
theater, music, or sports (Luthar & Latendresse, 2005a).
Accordingly, in this paper, we present data on three sam-
ples of youth. For comparison purposes, we present data from
the NESSY cohort as they were completing their senior year
of high school. In addition, we present data for 11th and 12th
graders from (a) a suburban public school in the Northwest
and (b) an independent school in a large East Coast city.
Outcome Domains
In research on resilience and vulnerability, it is logical to focus
primarily on those outcome domains that are most threatened
by the “risk factor” studied (Luthar, 2006; Luthar & Brown,
2007; Luthar, Cicchetti, & Becker, 2000). Accordingly, we
focus here on spheres where youth in wealthy, ultra achieve-
ment-oriented communities are likely to be vulnerable. These
Address correspondence and reprint requests to: Suniya S. Luthar, Teach-
ers College, Columbia University,Box 133, 525 West 120th Street, New York,
NY 10027; E-mail: Luthar@tc.edu
We gratefully acknowledge funding from the National Institutes of Health
(R01DA014385-06, R13 MH082592, and R01 DA010726-12). Sincere
thanks as well to students in our research laboratory for their invaluable con-
tributions to this programmatic work over the years.
Development and Psychopathology 24 (2012), 429–449
#Cambridge University Press 2012
doi:10.1017/S0954579412000089
429
include the frequency of substance use (including alcohol,
marijuana, and cigarettes), as well as rebellious, rule-breaking
behaviors (Ansary & Luthar, 2009; Luthar & Goldstein,
2008). In the internalizing category, our focus is on anxious/
depressed as well as somatic problems, which often derive
from underlying distress.
We consider these domains with two sets of questions in
mind. The first is whether students in any of the three geo-
graphically disparate cohorts might actually show “normal”
patterns of adjustment problems, when compared against
the yardstick of national normative data. The second question
concerns vulnerability and protective factors. What are the
major dimensions distinguishing youth who overindulge in
substance use, for example, compared to those who do not?
Risk Modifiers: Replicating Prior Findings and
Exploring New Constructs
In examining potentially salient risk modifiers, our goal is to
replicate prior findings and also consider new potentially
important constructs. Our first set of our replicative analyses
is aimed at corroborating the claim that “overinvolvement”
in extracurricular activities is, in essence, a scapegoat in ex-
plaining the distress of the most troubled affluent youth.
Among eighth graders (the NESSY cohort), Luthar, Shoum,
and Brown (2006) showed that the number of hours in extra-
curriculars explained minimal variance in children’s malad-
justment scores; far more important were aspects of family
relationships, particularly high levels of parent criticism, and
low expectations for adolescents’ achievement.
This pattern may hold true for older teens as well; yet, it is
plausible that the pressures from extracurriculars do affect stu-
dents in the thick of the college application process. In aca-
demically elite communities, establishing one’s “stardom” at
extracurriculars could, conceivably, be a source of much pres-
sure for high school juniors and seniors.
We also attempt to replicate, across our three disparate sam-
ples, the importance of perceived parent “containment,” par-
ticularly for substance use (Luthar & Goldstein, 2008). This
construct captures youngsters’ beliefs that parents will impose
serious consequences for various misbehaviors. Among 11th
grade suburban youth, we found that even after considering
many other parenting dimensions, parenting containment
for substance use was strongly associated with levels of use
among both girls and boys (Luthar & Goldstein, 2008).
Finally, we seek to replicate findings on stronger links,
with early adolescents’ self-reported distress, of the quality
of relationships with their mothers as opposed to fathers (Lu-
thar & Becker, 2002). It is unclear whether trends previously
documented among middle school students will also hold
true among youth who are in late adolescence.
New Parenting Dimensions Explored
Guided by qualitative research (as we were, in assessing par-
ent containment; see Luthar & Goldstein, 2008), we created a
measure to explore another potential risk modifier: parents’
tendencies to bail their teenagers of out problem situations.
There are ubiquitous suggestions in the popular press that ra-
ther than letting their teens suffer the consequences of rash,
illicit behaviors, affluent parents routinely intervene and inap-
propriately protect their offspring (e.g., Marano, 2008; Mo-
gel, 2001).
A second dimension we explored was adolescent percep-
tions of parents’ depression. Parental depression is a particu-
larly insidious risk factor, as it pervades not only specific as-
pects of parent functioning but also the overall ambience in
the home (Beardslee, 2002; Hammen, Bistricky, & Ingram,
2010; Luthar & Sexton, 2007). Whereas the effects of mater-
nal depression on youth are well documented, we considered,
here, associations for paternal depression as well. In upper
middle-class communities, fathers are more often than not
the primary wage earners. With the vicissitudes of the Amer-
ican economy over the last decade and several high wage
earners losing some or much of their previously guaranteed
earnings, distress among affected fathers may well spread to
others in the family.
Summary
In his early, pioneering works on resilience, Norman Garmezy
presciently showed that family poverty does not necessarily
connote youth maladjustment, as several critical protective
processes can promote positive outcomes (Garmezy, 1971,
1974). In the last decade, our own research has suggested a
parallel postulate at the other end of the socioeconomic status;
that is, that family wealth can connote significant risks to ado-
lescents’ adjustment. Based largely on studies of suburban
students in the Northeast, we have attempted to illuminate
salient factors that differentiate the more poorly functioning
“privileged” youth from others.
Extending our past work, in this report on affluent high
school students, we seek first to determine if elevations in mal-
adjustment previously seen in the East Coast suburbs might
generalize to Northwest suburbs, and to students in a large
East Coast city. Second, we seek to replicate earlier findings
(a) of the importance of parental containment for substance
use, and of relationships with mothers more so than fathers;
and (b) that extracurricular activity involvement is not a potent
vulnerability factor. Finally, we aim to explore the potential
significance of two risk modifiers not previously considered
among affluent youth; that is, parents bailing their teens out
of “problem situations,” and adolescents’ perceptions of de-
pression in both mothers and fathers.
Methods
Sample
As noted earlier, we present data from the NESSY cohort, in-
volving a group of suburban students first studied when they
were in the sixth grade (Luthar & Latendresse, 2005b) and fol-
S. S. Luthar and S. H. Barkin430
lowed annually ever since. Our analyses here are based on (a)
the NESSY cohort on completing high school, and on 11th and
12th graders from (b) a suburban public school in the North-
west and (c) an independent school in a large East Coast city.
Characteristics of samples are shown in Table 1. As seen
there, most students at all three schools came from Caucasian
families, with highly educated parents. Median family incomes
were almost three times the national level of about $50,000 in
2000 (United States Bureau of the Census, 2000). Overall,
therefore, all three samples were clearly from upper middle
class backgrounds.
As in our prior studies, students’ participation was based on
passive consent procedures, as data collections were done as
part of school-based initiatives on positive youth develop-
ment. To ensure that parents were well informed, administra-
tors sent letters to all homes via US mail before each wave of
data collection. Students were informed that their participation
was voluntary and on completion of data collection, question-
naires were stored with subject numbers as identifiers (for fur-
ther details on methods and procedures, please see Luthar &
Goldstein, 2008; Yates, Tracy, & Luthar, 2008).
Procedure
All three samples were assessed during May of their senior
year (2005, 2006, and 2006 for the East-Suburb, West-Suburb,
and East-Urban samples, respectively). All measures were ad-
ministered in groups. NESSY students, who were completing
their sixth annual assessment for this study, received a $30
gift certificate. Administrators at the other two schools did
not wish to provide students with incentives; despite this, par-
ticipation rates were over 80% (see Table 1).
Measures. Unless otherwise indicated, all measures have been
used in our past research (Luthar & Goldstein, 2008; Luthar
et al., 2006) with good reliability and validity. In this study,
alpha coefficientsof the various subscales were generally sim-
ilar across schools; in the interest of brevity, we provide aver-
age values for girls and boys across the three samples.
Substance use. We used the Monitoring the Future Study Sur-
vey (Johnston, O’Malley, & Bachman, 1984), which has well-
documented reliability and validity. As in our previous studies
(Luthar & Becker, 2002; Luthar & Goldstein, 2008), we cre-
ated a composite substance use variable by adding scores for
cigarettes, alcohol, and marijuana. Alpha coefficients in this
sample were 0.79 and 0.77 for girls and boys, respectively.
Rule breaking. The Youth Self-Report (YSR; Achenbach &
Rescorla, 2001) contains 112 items encompassing internaliz-
ing and externalizing domains (Achenbach & Rescorla,
2001). The externalizing subscale central to our analyses,
rule breaking, had avalues of 0.76 and 0.77 for females
and males, respectively, in this study. (Coefficients for ag-
gressive behavior were 0.81 and 0.84, respectively.)
Anxious–depressed and somatic complaints. These two YSR
internalizing subscales (Achenbach & Rescorla, 2001), cen-
tral to our analyses, had respective avalues of 0.85 and
0.77 among girls and 0.84 and 0.82 among boys. (Coeffi-
cients for withdrawn–depressed were 0.75 and 0.77 among
girls and boys, respectively.)
Perceived parent containment. Based on a 14-item, 5-point
scale, Luthar and Goldstein (2008) assessed the seriousness
of students’ anticipated parental repercussions on discovering
different errant teen behaviors across four areas of nonconfor-
mity: substance use,delinquency, rudeness, and academic
disengagement. In this study, reliability coefficients among
females and males respectively were as follows for the respec-
tive four subscales: 0.88 and 0.91, 0.84 and 0.84, 0.74 and
0.80, and 0.73 and 0.71.
Table 1. Description of participating samples
E-SuburbaW-Suburb E-Urban
Grade 12 11 & 12 11 & 12
Number of
Females 120 262 70
Males 132 275 68
Participation 79.5% 82.9% 86%
White 88.0% 67.2% 75.4%
Black 1.6% 1.1% 3.6%
Hispanic 4.4% 2.6% 4.3%
Asian 2.8% 18.0% 7.2%
Parents’ education
College degree (mother/father) 48%/32% 41%/34% 30%/27%
Graduate degree (mother/father) 37%/52% 43%/52% 63%/64%
Median family incomeb$153,131 (1999) $110,830 (1999) $149,367 (2000)
Note: E-Suburb, East Coast suburban sample; W-Suburb, Northwest Coast suburban sample; E-Urban, East Coast urban sample.
aParticipants in the longitudinal New England Study of Suburban Youth (Luthar & Goldstein, 2008).
bFrom Census data.
Affluent adolescents 431
Closeness to parents. The Inventory of Parent and Peer At-
tachment (IPPA; Armsden & Greenberg, 1987), contains 50
items (25 pertaining to each parent) rated on a 5-point scale.
Scores are obtained for an overall attachment score as well
as three subscale scores, for which we obtained the following
acoefficients for mother/father in this sample: trust: girls,
0.94/0.94, boys, 0.91/0.92; communication: girls, 0.93/0.91,
boys, 0.86/0.87; alienation: girls, 0.85/0.83, boys, 0.76/0.79.
Parent criticism. We used the four-item subscale of the Multi-
dimensional Perfectionism Scale (Frost, Marten, Lahart, & Ro-
senblate, 1990), including items such as, “I am punished for
doing things less than perfectly.” Alpha coefficients were 0.82
and 0.78 among girls and boys, respectively, in this sample.
Parent expectations. The five-item parental expectations sub-
scale of the Multidimensional Perfectionism Scale (Frost et al.,
1990), with items such as, “My parents set very high standards
for me,” yielded acoefficients of 0.81 and 0.80 for girls and
boys, respectively.
Parent knowledge. Participants were asked about how much
their parents know about their activities (Luthar & Goldstein,
2008), via a five-item, 5-point scale. Illustrative items include
“My parents know where I am after school,” and “My parents
know who my friends are.” Alpha coefficients were 0.84 and
0.79 for girls and boys, respectively.
Extracurricular involvement. Following Luthar et al. (2006),
we asked students about the number of hours (range ¼0–8 or
more) spent in four categories of activities outside of school
hours and in the presence of an adult. These categories in-
cluded sports, art or theater, academic activities, and civic ac-
tivities.
New parenting dimensions assessed: Parent bailing out. As
in our previous research on complex aspects of parent–child
relations (Luthar, Doyle, Suchman, & Mayes, 2001), we cre-
ated a measure, consisting of six vignettes, of situations to as-
sess the degree to which teens expected their parents would
bail them out of problem situations. An example: “For a ma-
jor academic course, you copied part of an essay from an in-
ternet source. The teacher discovered this and plans to fail you
for cheating. Would your parents protest?” Responses were
rated on a 5-point scale (definitely not to definitely,yes;see
Appendix A). Internal consistency coefficients for the Parent
Bailing Out (PBO) score were 0.73 and 0.72 for girls and
boys, respectively.
To explore the validity of this measure, we correlated it
with the four-parent containment scores, with which it should,
conceptually, show strong links. Results showed only modest
associations. Furthermore, simple correlations between PBO
and outcome variables were generally small and nonsignifi-
cant, clearly indicating low predictive value.
Based on these initial findings, we did not consider PBO
scores in multivariate analyses of our central hypotheses.
We do, however, provide descriptive responses to the six
vignettes (see the Results Section), both to inform current
stereotypes about affluent parents and, potentially, to help
guide future quantitative research on these issues.
Parent depression. The depression section of the Family His-
tory Screen (Weissman et al., 2000) was used to measure teen’s
perceptions of depressive symptoms in each parent (dichoto-
mous responses: yes/no). Illustrative items are, “Did anyone
in your familyever seem to experience greatly reduced interest
or pleasure in everyday activities?” and “Did anyone ever seem
more irritable than usual?” Alpha coefficients for mothers/
fathers, respectively, were 0.67/0.64 among girls and 0.58/
0.61 among boys.
Despite the modest reliability, both mother and father per-
ceived depression showed multiple correlations with several
parenting dimensions as well as outcomes. Thus, we elected
to include this dimension in multivariate tests of central hy-
potheses.
Results
Descriptive data
Table 2 presents means and standard deviations on all vari-
ables, separately by school and gender. A two-way (School
Gender) multivariate analysis of variance1showed significant
main effects for school (Wilks l¼0.20, p,.001), and gen-
der (Wilks l¼0.81, p,.001). The interaction effect was not
significant.
School differences were seen across most adjustment mea-
sures. As shown in Table 2, the East Coast suburban (E-Sub-
urb) and East Coast urban (E-Urban) samples reported rela-
tively high substance use, whereas the Northwest suburban
(W-Suburb) and E-Suburb samples had relatively high inter-
nalizing and externalizing symptoms.
Among the predictor variables, the W-Suburb sample
reported the highest parent containment for drugs (Cont-
Drugs). At the same time, this group also had the most diffi-
culties in parent–child relationships with the highest levels of
criticism, expectations, and alienation from mothers, and the
lowest trust and communication with mothers.
Regarding gender differences, girls reported higher levels
of all internalizing symptoms than did boys. They also had
higher scores on containment for rudeness and delinquency,
and alienation from both fathers and mothers, while simultane-
ously reporting higher levels of communication with mothers.
Comparisons with national norms: Maladjustment
As in our past reports, we compared maladjustment levels
among our samples with national normative data. Figure 1
displays results on substance use. For both genders, substance
1. Only subscale scores were included in the multiple analysis of variance,
not overall scores (e.g., internalizing, externalizing, or attachment).
S. S. Luthar and S. H. Barkin432
Table 2. Means (standard deviations) on outcome variables and predictor variables
All Schools E-Suburb W-Suburb E-Urban
Girls Boys Girls Boys Girls Boys Girls Boys School Gender
Mean Mean Mean Mean Mean Mean Mean Mean FF
Variable (SD)(SD)(SD)(SD)(SD)(SD)(SD)(SD)(h2)(h2)
Outcome Variables
Substance use 5.16 5.48 7.18 6.57 3.60 4.73 7.57 6.32 32.20*** 0.38
(5.11) (5.37) (5.57) (5.48) (4.31) (5.41) (4.95) (4.41) (0.07) (0.01)
Rule breaking 5.79 6.15 5.70 5.67 5.98 6.63 5.21 5.17 4.74** 0.01
(3.98) (4.20) (3.57) (3.90) (4.28) (4.56) (3.44) (2.70) (0.01) (0.00)
Tscorea59 60 59 58 59 60 59 58
Aggressive 6.06 5.48 5.21 4.58 6.35 5.92 6.48 5.45 6.34** 3.85
(4.45) (4.71) (4.08) (4.39) (4.59) (4.95) (4.42) (4.08) (0.01) (0.00)
Tscore 53 52 52 51 53 52 53 52
Anxious–depressed 6.40 3.53 4.32 2.19 7.07 4.04 7.47 4.17 76.24*** 28.99***
(4.75) (3.81) (3.80) (3.30) (4.87) (3.95) (4.76) (3.59) (0.06) (0.08)
Tscore 56 54 52 52 59 57 59 57
Withdrawn–depressed 3.45 2.64 2.83 2.22 3.67 2.86 3.73 2.64 6.62** 16.28***
(2.72) (2.64) (2.46) (4.42) (2.82) (2.76) (2.64) (2.59) (0.02) (0.02)
Tscore 55 54 52 54 55 54 55 54
Somatic 3.91 2.17 3.29 2.00 4.03 2.29 4.55 2.06 2.78 55.86***
(3.37) (2.88) (2.89) (2.92) (3.50) (3.00) (3.56) (2.27) (0.01) (0.06)
Tscore 54 52 54 51 57 52 57 51
Internalizing 13.72 8.28 8.74 6.29 14.73 9.15 15.49 8.74 15.68*** 68.36***
(9.24) (7.94) (7.64) (7.30) (7.64) (7.30) (9.48) (7.19) (0.04) (0.07)
Externalizing 11.82 11.62 10.91 10.26 12.29 12.55 11.66 10.51 5.09** 0.70
(7.56) (8.21) (6.73) (7.66) (8.08) (8.80) (6.80) (5.96) (0.01) (0.01)
Predictor Variables: Perceptions of Parents
Criticism 9.28 8.75 8.33 8.23 10.03 9.31 8.19 7.63 19.14*** 2.66
(3.95) (3.51) (3.84) (3.34) (3.93) (3.52) (3.60) (3.45) (0.04) (0.00)
Expectations 15.51 15.18 13.98 13.60 16.39 16.08 14.99 14.81 23.51*** 0.65
(4.90) (4.64) (4.89) (4.63) (4.72) (4.37) (4.91) (4.90) (0.05) (0.00)
Knowledge 22.66 22.51 21.49 22.44 23.87 22.83 22.63 22.25 9.15*** 0.22
(4.80) (4.02) (5.42) (3.39) (4.50) (4.41) (3.95) (3.57) (0.02) (0.00)
Containmentb
Drugs 13.17 12.87 11.44 11.20 14.36 13.85 11.70 12.27 33.08*** 0.03
(5.11) (4.69) (4.72) (4.22) (5.05) (4.74) (4.80) (4.37) (0.07) (0.00)
Delinquency 13.07 12.68 13.34 12.52 12.91 12.51 12.93 13.20 1.45 2.73†
(2.33) (2.53) (1.93) (2.57) (2.54) (2.60) (2.49) (2.10) (0.00) (0.00)
Rudeness 13.37 12.72 13.98 12.66 13.04 12.56 13.31 13.20 2.36 5.71*
(3.55) (3.31) (3.56) (3.11) (3.69) (3.46) (3.15) (3.05) (0.01) (0.01)
Academics 10.62 10.81 10.40 10.61 10.60 10.82 11.10 11.20 2.40 0.69
(2.72) (2.75) (2.46) (2.67) (2.92) (2.92) (2.33) (2.13) (0.01) (0.00)
433
Table 2 (cont.)
All Schools E-Suburb W-Suburb E-Urban
Girls Boys Girls Boys Girls Boys Girls Boys School Gender
Mean Mean Mean Mean Mean Mean Mean Mean FF
Variable (SD)(SD)(SD)(SD)(SD)(SD)(SD)(SD)(h2)(h2)
Trust
Mother 40.07 39.96 40.18 39.35 39.52 39.53 41.95 42.83 6.54** 0.00
(8.98) (7.74) (8.50) (6.36) (9.35) (8.37) (8.20) (6.98) (0.01) (0.00)
Father 39.61 39.37 39.37 38.86 38.82 39.25 42.90 40.81 7.08*** 1.39
(8.20) (7.89) (7.92) (6.92) (8.31) (8.20) (7.54) (8.27) (0.02) (0.00)
Alienation
Mother 14.77 13.65 13.87 13.54 15.18 14.01 14.79 12.49 3.74* 11.10***
(5.26) (4.32) (4.69) (3.86) (5.74) (4.59) (5.93) (3.90) (0.01) (0.01)
Father 15.53 13.87 14.95 13.89 15.81 13.91 15.44 13.67 0.73 17.31***
(5.19) (4.55) (4.13) (4.38) (5.26) (4.69) (6.35) (4.38) (0.00) (0.02)
Communication
Mother 33.03 30.88 33.60 31.04 32.42 30.21 34.32 33.16 5.39** 10.57**
(8.75) (7.08) (7.60) (5.66) (9.12) (7.56) (9.14) (7.25) (0.01) (0.01)
Father 30.01 29.40 29.92 29.62 29.23 28.93 33.03 30.85 6.88** 2.33
(8.59) (7.54) (7.54) (6.48) (8.72) (7.79) (9.14) (8.29) (0.02) (0.00)
Depression
Mother 4.55 3.65 4.12 3.47 4.16 3.56 5.46 4.32 6.50** 10.67**
(3.14) (2.82) (3.00) (2.64) (3.41) (2.93) (3.85) (2.67) (0.02) (0.01)
Father 4.43 4.28 4.44 4.18 4.40 4.13 4.54 5.06 1.59 0.00
(3.17) (3.06) (3.04) (3.03) (3.24) (3.04) (3.16) (3.14) (0.00) (0.00)
Note: E-Suburb, East Coast suburban sample; W-Suburb, Northwest Coast suburban sample; E-Urban, East Coast urban sample.
aSymptom means shown for Youth Self-Report subscales were first computed from raw data and then converted to Tscores using normative sample charts.
bPerceived parent containment.
†p,.10. *p,.05. **p,.01. ***p,.001.
434
use levels were elevated, with the exception of W-Suburb
girls’ cigarette and marijuana use. Use of alcohol, and fre-
quency of being drunk, showed the most pronounced eleva-
tions, particularly in the two East Coast samples.
Figure 2 displays the proportion of youth falling above
clinically significant symptom levels on the YSR. As we
had expected for these affluent cohorts, we found no eleva-
tions on either withdrawn–depressed or aggressive behaviors.
At the same time, we did see several elevations on the dimen-
sions hypothesized to reflect vulnerability. The most striking
result was that the E-Suburb youth (who were high on sub-
stance use; Figure 1) also had high rates of serious rule-break-
ing behaviors. The E-Urban youth, who were also high on
substance use, reflected elevated proportions of anxious–de-
pressed symptoms, as well as somatic problems among girls.
Third, the W-Suburb sample, which was relatively low on
substance use, showed the most pronounced vulnerability to
serious rule-breaking behaviors and to anxious–depressed
symptoms.
Overall, therefore, the findings show that none of these
three affluent samples were at “low risk” (at, or below, na-
tional norms). Rather, each showed elevations in problems
across multiple hypothesized areas of maladjustment.
Comparisons with national norms: Dimensions of parent–
child relationships
We conducted exploratory analyses to determine if as a group,
affluent youth are relatively dissatisfied with parent–child rela-
tionships. Although national normative data are not available
on the IPPA to our knowledge, we did obtain mean values
on a socioeconomically diverse sample of 326 high school stu-
dents (14–19 years old; Fosco & Grych, 2010). Figure 3 shows
that, overall, mean parenting scores of affluent girls and boys
were better than those in the other, more diverse sample.
Parents’ “bailing out”: Descriptive data
Figure 4 displays responses for the six vignettes of the PBO,
across all three schools (responses were similar). As shown
there, patterns varied according to seriousness of infrac-
tions; students believed their parents would be more likely
to intervene for “minor” violations such as being unprepared
for a test, than for major ones such as plagiarism. At the same
time, about 1 in 10 students did anticipate parent interven-
tion—probably or definitely—even for serious transgressions
involving active plagiarism, as did over 20% for a repeat in-
cident involving alcohol on the school premises.
Multiple regression analyses: Replicating findings
on containment
In examining the importance of parent containment dimen-
sions, we controlled for other critical indices of parent child
relations (Luthar & Goldstein, 2008): perceived criticism, ex-
pectations, and parent attachment. Rather than considering
mother and father attachment separately, we included a single
dimension (to conserve degrees of freedom, given the small
Figure 1. The percentage of students reporting substance use in the past month, compared to national norms (2006). National normative data are
not available for girls and boys separately.
Affluent adolescents 435
Figure 2. The incidence of clinically significant self-reported symptoms among participants, compared to national norms.
S. S. Luthar and S. H. Barkin436
sample size especially in the E-Urban school). Specifically,
we considered the higher of the two attachment scores for
mothers and fathers “attachment (maximum),” based on evi-
dence of high protective effects of strong relationships with at
least one caregiver (Luthar, 2006).2
The results (see Table 3) provided unequivocal support for
the importance of containment for adolescents’ substance use,
across all schools and genders. Replicating Luthar and Gold-
stein’s (2008) findings, furthermore, Cont-Drugs and parent
knowledge both showed multiple associations with substance
use as well as rule breaking. As expected, containment di-
mensions showed few significant associations with the two
internalizing outcomes considered: anxious–depressed and
somatic symptoms.
Exploratory analyses: Cont-Drugs
The mechanisms underlying our Cont-Drugs findings are not
clear: it could be that very serious parent consequences are as-
sociated with abstinence from substances, or that extreme lax-
ness with very high use, or both. We explored this issue by
plotting, on the Yaxis, distribution of use scores for alcohol
and marijuana (the two most highly used substances), against
seriousness of Cont-Drugs on the Xaxis. Results, shown in
Figure 5, showed that at low Cont-Drugs, students tended
to report high use of both alcohol and marijuana. At the high-
est levels of Cont-Drugs, alcohol use tended to be low, as
might be expected. Drunkenness and marijuana use, how-
ever, showed considerable variations, suggesting that parents’
extreme consequences for substance use failed to serve as a
guaranteed deterrent for at least some affluent teens.
Multiple regression analyses: Replicating findings
on extracurricular involvement
In our second set of regression analyses, we sought to replicate
prior findings that “overscheduling” in extracurricular activ-
ities is not a potent “vulnerability factor,” once parenting di-
mensions are considered (Luthar et al., 2006). The results
(see Table 4) were remarkably consistent with earlier findings
on eighth graders. Overall, there were negligible associations
between hours spent in activities and maladjustment outcomes.
There was just one exception: academic hours was linked with
internalizing symptoms among girls, across all three schools.
Multiple regression analyses: Dimensions of attachment
to mothers versus fathers
Table 5 presents the relative strength of mother versus father
in predicting to teens’ adjustment outcomes. (We include
substance use among the major outcome variables in this ta-
ble merely for the sake of consistency; as we know from our
prior work, it is proactive parental discipline, rather than
closeness to either parent, that is most strongly related to af-
fluent teens’ substance use.) The results provided in Table 5
are again consistent with prior findings on the critical impor-
tance of teens’ relationships with their mothers. For all three
symptom domains (rule breaking, anxious–depressed, and
somatic symptoms), block Rsquared values were higher for
mother versus father variables—among both girls and boys,
and in all three schools. The 18 ratios in question (see Table 5)
ranged from 1.2 to a high of 17.0, with a median value of
about 4.
Results of these regressions also showed that of the three
attachment dimensions, alienation (from mothers and fathers)
was the only one to show multiple unique effects. Closeness
and trust with each parent showed only sporadic links.
Figure 3. Mean scores on the Inventory of Parent and Peer Attachment subscales compared with normative values. Values representing “norms”
are from an economically diverse sample of teens (Fosco & Grych, 2010). M, mother; F, father; Alien., alienation; Comm., communication.
2. Considering the average of mother and father attachment yielded results
similar to those reported in Table 2.
Affluent adolescents 437
Multiple regression analyses: Perceived parental
depression
In exploring teen’s perception of parent’s depression, once
again, we considered the maximum score of attachment to
mother versus father in order to conserve degrees of freedom,
and also considered the average containment score across the
four subscales.3Even after considering the commonly tested
aspects of parent–teen relationships, perceived father depres-
sion consistently emerged as a unique, significant predictor
across multiple maladjustment outcomes among affluent
boys (see Table 6).
Discussion
The results of this study corroborate suggestions that some
“privileged” youth are actually at high risk for serious adjust-
ment problems. Across three geographically diverse samples,
adolescents reported elevations, compared to national norms,
in one or more domains of substance use and/or rates of clini-
cally significant internalizing and externalizing symptoms.
Our findings strongly supported previous suggestions of co-
variance (a) of teens’ substance use, with anticipated parental
Figure 4. Descriptive data on student responses to parent bailing out items.
3. Including the apparently most potent containment score—Cont-Drugs—
instead yielded results similar to those reported in Table 5.
S. S. Luthar and S. H. Barkin438
Table 3. Parent containment versus other parenting dimensions for girls and boys
Substance Use: Girls Rule Breaking: Grils
Parent Predictors E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Containmenta
Drugs 20.55*** 20.35*** 20.52*** 20.25* 20.12 20.19
Delinquency 0.07 0.09 0.11 20.03 20.02 0.05
Rudeness 0.08 20.09 20.24† 20.14 20.12 20.20
Academic 0.21† 20.09 0.16 0.25* 20.02 0.16
Knowledge 20.16† 20.24*** 20.38** 20.05 20.29*** 20.50***
Criticism 0.34* 0.15† 20.24 0.23† 0.19* 0.06
Expectations 20.22† 20.11 0.20 20.11 20.13 0.12
Attachment (max)b0.10 20.01 20.21† 20.26* 20.11 20.09
Total R20.26*** 0.33*** 0.51*** 0.23*** 0.29*** 0.41***
Anxious–Depressed: Girls Somatic: Girls
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Containment
Drugs 0.02 20.02 20.07 20.21† 20.06; 20.32*
Delinquency 20.10 0.04 0.03 20.08 0.08 0.13
Rudeness 0.07 0.11 0.09 0.03 0.11 20.02
Academic 20.07 20.20* 20.11 0.10 20.23* 20.09
Knowledge 0.32** 20.03 0.07 0.27* 20.13† 20.01
Criticism 0.15 0.22* 0.19 0.17 0.29** 0.33
Expectations 0.10 0.07 0.32† 20.16 20.9 0.18
Attachment (max) 20.19 20.13† 20.06 20.23 20.11 20.05
Total R20.19** 0.13*** 0.22† 0.12† 0.16*** 0.24†
Substance Use: Boys Rule Breaking: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Containment
Drugs 20.44*** 20.27*** 20.28* 20.24** 20.17* 20.10
Delinquency 20.05 0.08 0.09 20.04 0.05 0.19
Rudeness 0.01 20.01 20.35† 20.20† 20.09 20.23
Academic 0.08 0.05 0.17 0.22 0.08 0.07
Knowledge 20.24** 20.31*** 20.34* 20.22* 20.36*** 20.13
Criticism 0.09 20.06 0.13 0.48*** 0.05 20.30
Expectations 20.22† 20.01 20.25 20.40** 0.15† 0.25
Attachment (max) 0.05 20.05 0.01 0.03 20.06 20.39*
Total R20.31*** 0.19*** 0.33** 0.30*** 0.22*** 0.24†
Anxious–Depressed: Boys Somatic: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Containment
Drugs 0.01 0.06 0.07 0.02 20.01 0.06
Delinquency 20.19† 20.02 20.12 20.23† 0.02 0.19
Rudeness 20.12 20.02 0.28† 0.04 20.04 0.02
Academic 0.23* 0.02 20.10 0.22† 20.08 20.17
Knowledge 0.02 20.06 0.09 20.13 20.04 0.09
Criticism 0.49** 0.13 0.11 0.31† 0.05 20.47*
Expectations 20.32* 0.16* 0.43* 20.17 0.13 0.56**
Attachment (max) 0.05 20.14† 20.17 0.06 20.14† 20.46**
Total R20.22*** 0.13*** 0.39*** 0.14* 0.07* 0.31*
Note: Values in italics appear to be due to suppressor effects, because the statistically significant beta weights are opposite in valence to those in parallel zero-order
correlations. Hence, they are not interpreted. E-Suburb, East Coast suburban sample; W-Suburb, Northwest Coast suburban sample; E-Urban, East Coast urban sample.
aPerceived parent containment.
bMaximum of mother/father attachment.
†p,.10. *p,.05. **p,.01. ***p,.001.
Affluent adolescents 439
Figure 5. Descriptive data on the frequencyof alcohol use, being drunk, and marijuana use in the past year, by parent containment for drugs. The numbers in the graphs represent random subject
ID numbers. (W) Outlier and (w) extreme outlier. The yaxis values represent the number of times used per year: 0 ¼never,1¼once or twice,2¼3–5 times,3¼6–9 times,4¼10–19 times,5¼
20–39 times, and 6 ¼40þtimes. [A color version of this figure can be viewed online at http://journals.cambridge.org/dpp]
440
repercussions on discovering their use, and (b) of symptom
levels, with attachment to mothers more so than to fathers.
Concomitantly, we corroborated that stress from too many ex-
tracurriculars is not a major “vulnerability factor.” Perceived
parental tendency to bail teenagers out of problem situations
was also apparently unrelated to maladjustment. Finally, we
found that even after considering multiple dimensions of par-
ent–child relationships, adolescent boys’ perceptions of fa-
thers’ depression was related to multiple indices of distress.
Each of these findings is discussed in turn.
Table 4. Hours spent in extracurricular activities in relation to central adjustment outcomes for girls and boys
Substance Use: Girls Rule Breaking: Girls
Predictors E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Parent knowledge 20.13 20.43*** 20.47*** 20.21* 20.46*** 20.56***
Parent criticism 0.16 0.04 20.33 0.34* 0.17* 0.08
Parent expectations 20.15 20.13 0.16 20.16 20.16† 0.05
Sports hours 20.14 0.05 20.10 20.07 20.04 20.22*
Arts hours 20.01 20.10 20.15 0.13 0.03 20.06
Academic hours 0.00 0.05 0.03 0.11 0.07 20.08
Civic hours 0.18† 20.09 20.12 0.03 0.00 20.01
Total R20.08 0.23*** 0.28* 0.16** 0.27*** 0.46***
Anxious–Depressed: Girls Somatic: Girls
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Parent knowledge 0.14 20.10 0.06 0.06 20.16* 20.06
Parent criticism 0.27* 0.20* 0.11 0.20 0.29** 0.25
Parent expectations 0.03 0.03 0.30 20.22 20.21* 0.13
Sports hours 0.00 20.10 20.30* 0.02 20.11 20.03
Arts hours 0.07 0.01 0.06 0.18† 20.05 0.02
Academic hours 0.18† 0.10 0.25* 0.28** 0.19** 0.27†
Civic hours 0.07 0.02 20.14 20.09 0.02 20.19
Total R20.20*** 0.10** 0.38*** 0.15* 0.16*** 0.22†
Substance Use: Boys Rule Breaking: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Parent knowledge 20.34*** 20.39*** 20.41** 20.28** 20.44*** 20.32*
Parent criticism 20.04 20.06 20.05 0.46*** 0.06 20.15
Parent expectations 20.17 20.07 20.09 20.36** 0.05 0.27
Sports hours 0.01 20.01 0.03 0.00 0.03 0.11
Arts hours 20.01 20.01 0.09 0.00 0.06 20.19
Academic hours 0.06 0.06 20.13 20.05 20.02 0.17
Civic hours 0.04 0.07 20.26* 0.02 0.03 20.17
Total R20.16** 0.17*** 0.32** 0.21*** 0.21*** 0.22†
Anxious–Depressed: Boys Somatic: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Parent knowledge 0.01 20.11 0.08 20.08 20.10 20.02
Parent criticism 0.55*** 0.14 0.46* 0.39** 0.08 0.13
Parent expectations 20.28* 0.19* 0.14 20.19 0.08 0.17
Sports hours 20.21* 20.06 20.08 20.17† 20.14† 20.02
Arts hours 0.08 0.08 0.08 20.02 20.01 0.12
Academic hours 20.10 0.11 0.11 0.02 0.02 20.17
Civic hours 0.02 0.12† 0.04 20.02 0.17* 0.14
Total R20.24*** 0.17*** 0.39*** 0.12* 0.09* 0.14
Note: Values in italics appear to be due to suppressor effects, because the statistically significant beta weights are opposite in valence to those in parallel zero-
order correlations. Hence, they are not interpreted. E-Suburb, East Coast suburban sample; W-Suburb, Northwest Coast suburban sample; E-Urban, East Coast
urban sample.
†p,.10. *p,.05. **p,.01. ***p,.001.
Affluent adolescents 441
Table 5. Individual dimensions of parent attachment in relation to central adjustment outcomes for girls and boys
Substance Use: Girls Rule Breaking: Girls
Predictors E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother trust 0.59* 0.00 20.18 0.16 20.12 20.31
Mother communication 20.20 20.10 0.07 0.00 0.02 0.00
Mother alienation 0.51* 20.14 20.19 0.61** 0.07 0.06
Mother variables: R20.05 0.02 0.03 0.21*** 0.12*** 0.23**
Father trust 20.46† 20.10 20.05 20.29 20.14 0.16
Father communication 0.16 20.02 20.26 0.03 0.08 20.35
Father alienation 20.18 0.17 0.08 20.21 0.22 0.13
Father variables: R20.04 0.04* 0.07 0.02 0.05** 0.04
R2block mother: father 1.25 0.50 0.43 10.50 2.40 5.75
Anxious–Depressed: Girls Somatic: Girls
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother trust 20.29 20.13 20.06 20.11 20.09 20.07
Mother communication 0.33 0.41** 0.10 20.16 0.28 0.14
Mother alienation 0.25 0.34* 0.04 20.03 0.44** 0.05
Mother variables: R20.19*** 0.18*** 0.08 0.05 0.17*** 0.06
Father trust 0.06 20.12 20.19 0.03 0.01 20.15
Father communication 0.16 0.07 0.01 0.34† 0.09 20.05
Father alienation 0.32 0.27* 0.29† 0.33 0.19 0.24
Father variables: R20.03 0.06*** 0.06 0.04 0.01 0.05
R2block mother: father 6.33 3.00 1.33 1.25 17.00 1.20
Substance Use: Boys Rule Breaking: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother trust 0.35 20.01 0.11 0.30 0.21 0.12
Mother communication 20.21 20.14 20.05 0.06 20.01 20.15
Mother alienation 0.16 0.02 0.08 0.50* 0.47** 0.21
Mother variables: R20.01 0.03† 0.03 0.07* 0.18*** 0.20**
Father trust 20.41 20.13 0.08 20.49† 20.21 0.25
Father communication 0.19 0.06 20.12 20.06 0.16 20.40
Father alienation 20.20 20.11 0.10 20.40 0.06 0.06
Father variables: R20.02 0.00 0.01 0.04 0.02 0.03
R2block mother: father 0.50 7.50 3.00 1.75 9.00 6.67
Anxious–Depressed: Boys Somatic: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother trust 20.26 20.29* 20.50* 0.03 20.12 20.44†
Mother communication 0.60*** 0.26* 0.32 0.26 0.10 0.29
Mother alienation 0.24 0.12 0.04 0.45* 0.08 0.30
Mother variables: R20.17*** 0.19*** 0.21** 0.06† 0.10*** 0.21**
Father trust 0.09 0.24 0.25 20.21 20.04 0.20
Father communication 20.37† 20.03 20.11 20.10 0.17 20.34
Father alienation 0.11 0.49*** 0.41 20.33 0.34* 20.21
Father variables: R20.04† 0.05*** 0.04 0.02 0.03* 0.03
R2block mother: father 4.25 3.80 5.25 3.00 3.33 7.00
Note: Values in italics appear to be due to suppressor effects, because the statistically significant beta weights are opposite in valence to those in parallel zero-
order correlations. Hence, they are not interpreted. E-Suburb, East Coast suburban sample; W-Suburb, Northwest Coast suburban sample; E-Urban, East Coast
urban sample.
†p,.10. *p,.05. **p,.01. ***p,.001.
S. S. Luthar and S. H. Barkin442
Table 6. Perceived parent depression in relation to central adjustment outcomes for girls and boys
Substance Use: Girls Rule Breaking: Girls
Predictors E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother depression 20.23 0.11 20.02 20.02 0.12 0.01
Father depression 0.36* 20.11 0.07 0.32† 0.00 20.17
Attachment (max)a0.04 20.04 20.14 20.22† 20.12† 20.12
Containment averageb20.32** 20.35*** 20.38** 20.21* 20.23*** 20.19
Parental criticism 0.29† 0.15† 20.22 0.20 0.19* 0.06
Parent expectations 20.08 20.12 0.14 20.02 20.13 0.13
Parent knowledge 20.17† 20.28*** 20.36** 20.10 20.27*** 20.42**
Total R20.19** 0.30*** 0.40*** 0.27*** 0.31*** 0.40***
Anxious–Depressed: Girls Somatic: Girls
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother depression 20.06 0.22* 0.16 0.03 0.15 0.23
Father depression 0.19 0.04 0.13 20.18 0.13 0.20
Attachment (max) 20.21† 20.11 20.02 20.24† 20.05 0.09
Containment average 20.05 20.03 20.01 20.13 20.06 20.16
Parental criticism 0.08 0.14 0.11 0.07 0.22* 0.28
Parent expectations 0.17 0.07 0.28 20.07 20.10 0.09
Parent knowledge 0.31** 20.03 0.06 0.26* 20.11 20.03
Total R20.20** 0.17*** 0.25* 0.13† 0.20*** 0.31**
Substance Use: Boys Rule Breaking: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother depression 0.21 20.19 20.07 0.14 0.01 0.16
Father depression 0.12 0.25* 0.27* 0.30* 0.34** 0.30*
Attachment (max) 0.08 0.00 0.05 0.07 20.02 20.43**
Containment average 20.27*** 20.12† 2.034* 20.14† 20.05 20.19
Parental criticism 20.06 20.07 20.08 0.38** 0.01 20.40*
Parent expectations 20.10 20.03 20.11 20.31** 0.10 0.27
Parent knowledge 20.29** 20.34*** 20.29* 20.27** 20.36*** 20.01
Total R20.32*** 0.18*** 0.37*** 0.40*** 0.32*** 0.36***
Anxious–Depressed: Boys Somatic: Boys
E-Suburb W-Suburb E-Urban E-Suburb W-Suburb E-Urban
Mother depression 20.13 0.12 0.37** 20.05 0.44*** 0.10
Father depression 0.60*** 0.26* 20.10 0.60*** 0.06 0.12
Attachment (max) 0.11 20.12† 20.08 0.09 20.12† 20.45**
Containment average 0.04 0.11 0.08 0.16† 20.01 0.00
Parental criticism 0.48*** 0.10 0.34† 0.24† 20.04 20.41†
Parent expectations 20.34** 0.13† 0.29† 20.21 0.11 0.44*
Parent knowledge 20.05 20.04 0.14 20.21* 20.02 0.19
Total R20.39*** 0.26*** 0.48*** 0.37*** 0.30*** 0.28*
Note: Values in italics appear to be due to suppressor effects, because the statistically significant beta weights are opposite in valence to those in parallel zero-
order correlations. Hence, they are not interpreted. E-Suburb, East Coast suburban sample; W-Suburb, Northwest Coast suburban sample; E-Urban, East Coast
urban sample.
aPerceived parent containment.
bMaximum of mother/father attachment.
†p,.10. *p,.05. **p,.01. ***p,.001.
Affluent adolescents 443
Maladjustment among affluent youth
Among substance use indicators, the most striking finding
was elevations in rates of drinking relative to norms, and
in particular, of being drunk in the past month. Rates were
pronounced among both the East Coast samples—suburban
and urban—with over half of the girls and almost two-thirds
of the boys reporting being drunk at least once in the past year
(compared to about one-third of youth in norms).
Across the years, our focus groups with affluent teens have
revealed several troubling trends regarding drinking. First,
binge drinking is distressingly commonplace. Students have
remarkably easy access to alcohol, with efficient systems in
place to secure large amounts at a moment’s notice. Second,
youngsters frequently drink with the deliberate intention of
getting drunk; and for every reported incident of serious in-
toxication, involving stomach-pumping, indiscreet sexuality,
and/or violence, there are many others that go undetected by
adults. Third, plans to “party hard” are often made as an anti-
dote to the unrelenting stresses of “working hard” in order to
achieve excellence across multiple domains of achievement
(Luthar & Sexton, 2004).
The trends we are seen in high school are also particularly
worrying given the high rates of serious alcohol use on col-
lege campuses (Del Boca, Darkes, Greenbaum, & Goldman,
2004; Weitzman, Nelson, & Wechsler, 2003), with as many
as 44.4% of college students reporting binge drinking
(Wechsler et al., 2002). Furthermore, extreme drinking in col-
lege is particularly pronounced among students at highly
competitive colleges (Wechsler et al., 2002) and those from
affluent and better-educated families (Dantzer, Wardle,
Fuller, Pampalone, & Steptoe, 2006). Parallel findings have
been reported with marijuana and illicit drug use (Gledhill-
Hoyt, Lee, Strote, Wechsler, 2000).
Admittedly, some adolescents eventually “mature out” of
heavy drinking; at the same time, substance use during high
school is among the strongest predictors of use during college
(Reifman & Watson, 2003). Thus, at least a subgroup of our
affluent samples is likely to show serious substance use in col-
lege. Similarly, there could be a decrease in use once these af-
fluent samples complete college (given new social and career
roles and responsibilities; see Schulenberg & Zarrett, 2006).
Again, this possibility must be weighed against evidence that
40 and 70% of people remain stable in their drinking patterns
(Jackson, Sher, Gotham, & Wood, 2001), with alcohol abuse
becoming serious for some (Schulenberg & Maggs, 2002).
Aside from substance use, our three samples all showed ele-
vations in one or more hypothesized serious internalizing and
externalizing symptoms. It is interesting that the Northwest
suburban youth (who were the lowest of the three samples
on substance use) showed the highest vulnerability on anx-
ious–depressed symptoms, as well as rule breaking. In pre-
vious research, this same group had also shown significant ele-
vations on nonsuicidal self-injurious behavior (Yates et al.,
2008). It should be noted too that the Northwest suburban
group had the poorest levels of attachment to parents, in five
of the six dimensions we considered: trust, communication,
and alienation in relation to mothers and fathers each; they
were also the highest on parent criticism.
Across all three samples, the specific domains of students’
vulnerability, mirror, to some degree, the community concerns
that had sparked research with the groups, respectively. All our
studies of affluent samples had begun with requests from com-
munity/school leaders to help tackle specific areas of concern:
substance use in the East Coast suburb; depression, suicidality,
and feelings of isolation in the Northwest suburb; and general-
ized high stress levels in the East Coast independent school.
Overall, therefore, the heterotypy in the specific types of mal-
adjustment (Price & Ingram, 2010) seen among affluent youth
may, to some degree, be related to local community awareness
and prevention efforts specific to each.4
Vulnerability and protective factors: Predictors
of adjustment problems
Among the “risk modifiers” we examined, findings were the
most compelling on parents’ containment for substance use.
Across all samples, youth reported high levels of use when
they felt their parents were lax in consequences for substance
use. At the same time, high Cont-Drugs in itself was not nec-
essarily a fail-safe protective factor; youth with the strictest of
parentswere not necessarily abstinent. These findings probably
reflect, in part, the power of peer influences, incredibly potent
in sustaining high substance use in the subculture of affluent
adolescence (Luthar & Becker, 2002). In addition, individual
vulnerability factors could be implicated, including the tenden-
cies to use substances in efforts to self-medicate (Brown, 2008;
Luthar & Becker, 2002; Luthar & D’Avanzo, 1999).
In addition to, and independent of, Cont-Drugs, parents’
knowledge of their children’s whereabouts after school was
linked to substance use and with rule-breaking behaviors
across subgroups. As we noted earlier (Luthar & Sexton,
2004), affluent parents may be less than vigilant of their
children’s activities, lulled into a sense of security given the
physical safety of their neighborhoods. In addition, some
teenagers routinely lie to their parents. Thus, the parents’
“lack of knowledge” may be as much a result of teenagers’
deliberately withholding information, as it is about parents’
lack of vigilance.
Of the affective indicators of parent–child relationships,
parent criticism was the only dimension that showed rela-
tively strong associations across subgroup analyses (although
beta weights were sometimes nonsignificant, limited by sam-
ple sizes). The potency of this negative indicator, relative to
others of a positive valence such as attachment, is supported
by prior research on resilience: acrimony from parents to chil-
4. The Northwestern suburban community sampled in this study was par-
ticularly invested in preventing underage drinking. At the time of this writ-
ing, we learned that the City Council had just unanimously passed an Un-
derage Drinking Ordinance, holding homeowners liable (and fined) if
youth were discovered drinking on their property, even if the adults
claimed to be unaware of it.
S. S. Luthar and S. H. Barkin444
dren is highly destructive, especially if it is a consistent pat-
tern (Luthar, 2006).
As with prior results on eight graders (Luthar et al., 2006),
we found with parenting dimensions considered, hours in ex-
tracurricular activities was unrelated to maladjustment, even
among these teens in the thick of “resume building” for col-
lege applications. There was just one dimension showing
negative links: hours in academics was related to some
form of internalizing symptoms among girls across geo-
graphic locations. Luthar et al. (2006) had also found this di-
mension to be related to multiple symptoms among girls.
These findings probably reflect high pressures for girls to
succeed across multiple areas: to be attractive, popular,
well-behaved, and empathic, as well as every bit as academ-
ically proficient as boys (Hinshaw & Kranz, 2009). Thus, it is
plausible that girls who are struggling academically (and thus
receiving extra help as in tutoring after school) are feeling the
strains of the inordinately high expectations across multiple
domains.
Supporting this argument, girls in all three schools re-
ported higher anticipated consequences from parents for mis-
behavior across domains. Gender differences were significant
for parental containment for rudeness and delinquency, as
was shown by Luthar and Goldstein (2008) with eighth grad-
ers. It is clear, therefore, that affluent young women face
competing and sometimes impossible demands: (a) to be
on par with boys in the male dominated worlds of academics
and career and (b) and to surpass boys in the traditional, other-
centered, feminine roles (Zahn-Waxler, Klimes-Dougan, &
Slattery, 2000) of being well-behaved, polite, considerate,
and physically attractive to boot (see Becker & Luthar, 2007).
Discrete aspects of relationships with mothers
and with fathers
Our findings replicate earlier findings on the critical impor-
tance of relationships with mothers. As with younger affluent
youth (Luthar & Becker, 2002), even the late adolescents
in this sample showed much greater variations, in their self-
reported symptoms, as a function of quality of relationships
with mothers as opposed to fathers. Across the six analyses,
the ratios of variance explained by the blocks of mother versus
father attachment variables ranged from 1.2 to a high of 17.0,
with a median value of almost 4. Similarly, alienation from
mothers was the only parent attachment dimension to be
linked with at least one maladjustment dimension across the
multiple subsamples (with the exception of E-Urban youth).
That the magnitudes of adolescents’ mother-attachment as-
sociations were at least three times as as high (conservatively
averaged) than those of father attachment, probably reflects,
in part, differences in times spent with each parent. Mothers
are generally primary caregivers of their children, across di-
verse cultural contexts. In affluent communities, children are
even more likely to spend more time with their mothers than
with fathers, as the latter are usually the primary wage earners
with careers demanding long hours (Luthar & Sexton, 2004).
Parent attachment relative to norms
Negative stereotypes about affluent parents are rampant, and
they are sometimes fueled by trends in the popular media ( per-
haps inadvertently). Discussing her book called The Price
of Privilege, author Madeline Levine (2008) was quoted
in the New York Times as saying that, “wealthy parents
today ...aremorelikelytobeemotionally distant from their
children, and at the same time to insist on high levels of
achievement, a potentially toxic blend of influences that
can create ‘intense feelings of shame and hopelessness’ in af-
fluent children” (Tough, 2011).
This inference, which was cited as deriving from our
research, is not entirely correct. Our programmatic studies
do indicate, as contended, that, children of affluent parents
exhibit “unexpectedly high rates of emotional problems be-
ginning in junior high school” (Tough, 2011). On the other
hand, this by no means implies that all, or even most, wealthy
youth are troubled, or that most of their parents are deficient in
any way. To the contrary, we have explicitly asserted that our
data counter presumptions of generally “poor” parenting in
wealthy communities, which is a statement strongly supported
by comparisons, in this study, of mean levels of parent attach-
ment with values from economically diverse samples. We
have repeatedly cautioned that, “. . . the range ofperceived par-
enting adequacy is no more constrained among the very weal-
thy than the very poor” (Luthar & Latendresse, 2005b, p. 223).
In all settings there are inevitably some parents who are disen-
gaged, lax, or critical; and in all settings, the quality of parent–
child relationships is inevitably related to children’s adjust-
ment outcomes.
Bailing out
Our exploratory analyses counter yet another widespread ste-
reotype: that affluent parents inappropriately bail their chil-
dren out of all offenses, minor and major. Based on his re-
search in independent schools, Weissbourd (2009, p. 118)
describes views, among teachers, of parents as being “out
of control,” tenaciously demanding them to overlook teen
misbehaviors ranging from rudeness to plagiarism.
Data in this study show that from the children’s perspec-
tive, parents’ anticipated intervention varies with the serious-
ness of offense, more likely with relatively minor infractions
(being unprepared for a test) but not necessarily with egre-
gious ones. At the same time, even in the latter category—in-
cidents of outright plagiarism, and a repeat offense involving
vodka at school—a distinct subgroup of youth believed their
parents would, probably or definitely, protest on their behalf:
about 10% for the former offense, and 23% for the latter.
These data support Weissbourd’s (2009) assertion that in pri-
vileged settings, there is actually a subgroup of parents (albeit
perhaps small) who aggressively, even litigiously, protest dis-
ciplinary actions imposed by schools.
Our failure to find links between parent bailing out scores
and adjustment may partly be because this dimension, like
“overinvolvement” in extracurriculars, does not really con-
Affluent adolescents 445
tribute to maladjustment. A second possibility is that there are
curvilinear effects, with negative repercussions for parents ei-
ther too willing, or inexorably unwilling to intervene, regard-
less of the infraction. A third possibility is that linear findings
actually do exist and might be captured with refinements of
our measure. Although the PBO had good reliability levels,
it combines variations in both (a) type of offense (e.g., aca-
demic, substance use) and (b) seriousness of disciplinary ac-
tions. In future research, it might be useful to separately query
problem behaviors in discrete areas, all engendering serious
disciplinary actions from schools.
Parental depression
We were somewhat surprised to find multiple links between
adolescent boys’ perceptions of fathers’ depression and both ex-
ternalizing and internalizing symptoms. Several factors render
these associations noteworthy. First, they emerged in stringent
analyses, even after considering multiple aspects of parent–
teen relationships. Second, as noted earlier, symptom levels
of affluent boys and girls have consistently varied more relative
to relationships with mothers than with fathers. Yet, there were
no associations here for perceived depression among mothers.
It is possible that patterns we found among these olderado-
lescent boys are a by-product of the young men’s identifica-
tion with their fathers. On the brink of leaving home to enter
the “real world,” these young men may be particularly sensi-
tive to fathers’visible emotional vulnerability. Alternatively, it
is plausible that depressive symptoms may be mostmanifest in
the relationships between men in highly successful, demand-
ing careers and their expectations for, and thus their interac-
tions with, their almost-adult sons.
It is interesting that overall levels of perceived parental de-
pression were generally commensurate among mothers and
fathers, if not slightly higher among the latter; this is in stark
contrast to the fact that adult women are twice as likely to ex-
perience depression than men (Hammen et al., 2010). Our find-
ings may well reflect gender differences in affluent parents’
willingness to seek help when depressed (men are typically
more reluctant; see Hinshaw, 2007), and also, in how parents
manifest their experienced distress. As Shelley Taylor (2002,
2006) has extensively documented, males typically respond
to threats and distress with tendencies to “fight or flight,” that
is, behaviors that connote aggressiveness (irritability) or dis-
tancing. Women’s instinctive defense mechanisms, by contrast,
are to “tend and befriend,” and in particular, to focus on inten-
sively nurturing their offspring. Thus, even though mothers in
our research may have actually experienced as many or more
symptoms of depression as fathers, their distress simply may
not have been as evident in interactions with their children.
Limitations, caveats, and future directions for research
and practice
Prominent among the limitations of this work is its cross-sec-
tional nature; this precludes any firm conclusions about the
direction of links documented here. It is just as likely, for ex-
ample, that misbehavior among children leads to parental crit-
icism and emotional withdrawal, as are links in the opposite
direction. In the future, the use of longitudinal analyses could
enhance understanding of the bidirectional links between dif-
ferent parent dimensions and adolescent outcomes.
The sole use of self-report indices to measure parent–adoles-
cent relationships might be criticized, but this has reflected a de-
liberate choice in our ongoing programmatic research (Luthar &
Becker, 2002; Luthar & Goldstein, 2008; Luthar & Latendresse,
2005b). Our interest is not so much in others’ opinions of par-
ents’ effectiveness, but rather, in adolescents’ own perceptions
of their relationships with parents, and how these perceptions
might play out in different aspects of their adjustment.
There is a possibility of Type II errors in our findings,
so that we did not identify some links that actually did exist.
This is particularly true for the E-Urban sample, which was
small in size, rendering significant none but the most substan-
tial regression coefficients. Similarly, the reliability of mea-
surement was low for perceived parental depression. In this
regard, it should be noted that low reliability limits the likeli-
hood of finding significant links rather than inflating them, so
there is little question about the authenticity of significant as-
sociations that were found for this construct.
A final limitation is that family “affluence” is confounded
with ethnicity in these samples as in others, with the wealthy
families generally being of Caucasian backgrounds. Disen-
tangling ethnicity and income in such research is difficult,
however, given contemporary demographic patterns; multi-
ple school districts will have to be sampled simultaneously
to recruit sufficiently large cohorts of ethnic minority youth
from very wealthy families (Luthar & Latendresse, 2005a).
In terms of future research directions, it will be useful to
examine vulnerability and resilience among affluent young-
sters via individual-based analyses rather than only vari-
able-based ones (Luthar et al., 2000; Masten, 2007). Much
could be learned from focusing on the subgroup of youth
and families who stand out from others in being particularly
troubled, and then identifying factors distinguishing them
from groups who function well (e.g., Latendresse, 2005;
McMahon & Luthar, 2006).
Concerted attention to both aspects of communities and of
the students’ personal attributes is also critical. In empirically
considering major risk modifiers, our attempts thus far have
generally been to disentangle the relative significance of var-
ious perceived parenting dimensions, which are clearly critical
for youth across contexts (Luthar, 2006). In future efforts to
understand the major sources of pressure faced by affluent
youth, it is important to examine also aspects of school climate
(particularly rigorous expectations and standards around aca-
demics; see Anderson, 2011), peer relationships and romantic
attachments, as well as individual attributes such as personal
values and life goals.
Even as we continue to explore these various dimensions,
one directive is already clear for practice and policy, based
on our own findings and recently, those of others (see Chassin,
S. S. Luthar and S. H. Barkin446
Beltran, Lee, Haller, & Villalta, 2010; Hanson & Chen, 2007;
Trim & Chassin, 2008). This is that parents must be particu-
larly attentive to substance use among affluent youth. We ad-
mit that this is easier said than done, especially given that
some experimentation with substances is normative—and
even perhaps “healthy” (Shedler & Block, 1990)—during
adolescence. Thus, if parents were to categorically disallow
18-year-olds a single drink, even with appropriate adult super-
vision and discussions about the associated hazards, this could
result in a backlash among youth as we have clearly seen in our
focus groups. Draconian punitive measures often backfire,
with teenagers simply disclosing less and less to their parents,
resorting to frequent marijuana use (not as easily detected), and
ultimately, engaging in binge drinking once away from home,
at college. This said, parents would be wise to guard against
extreme laxness around their adolescents’ use of substances.
Particularly essential are clear, consistent messages about the
unequivocal unacceptability of parties entailing unlimited con-
sumption of alcohol. As common as such social events might
be among today’s affluent teens, the dangers are simply far too
grave for adults to allow their occurrence, tacitly or otherwise.
With regard to parents’ relentless, and even unethical or il-
legal pursuit of theirchildren’s high achievement, ourfindings
show that there is a subgroup of wealthy parents who do fit this
profile, but this is by no means true for all or even most of
them. Affluent adults are typically judged as complicit in their
children’s breaking the rules to “get ahead,” as exemplified in
recent discoveries that several students paid another highly
skilled youth to impersonate them while taking the SAT exam-
inations (Anderson & Applebome, 2011). In one investigative
story, a parent was quoted as saying that “he could not ‘ima-
gine that my child would be able to do that and come up
with $1000 or $2000 and me not know about it’” (Anderson
& Applebome, 2011). Caution regarding such inferences is
critical; our own work has shown that raising such sums of
money can be trivial for many youth in affluent communities.
Aside from misappropriating money from family or friends
(see Luthar & Ansary, 2005), income can easily be derived
by writing academic papers for struggling students, for exam-
ple, and from sales of alcohol and even marijuana to others.
Considering these issues in tandem, our central message re-
garding “privileged” parents is, first, that communities and
schools adopt a strict zero-tolerance policy regarding students’
law breaking. Countering the few powerful, litigious parents
who hotly protest punitive actions, the much larger group of
civic-minded parents must equally vocally support adminis-
trators who, like the principal of the school involved in the
SAT cheating described earlier, retain a “moral and legal ob-
ligation” to report criminal activities to the police (Anderson
& Appelbome, 2011). In the words of the district attorney in-
vestigating these incidents, “We have to put accountability
into the system, and there is none right now....Ifwecan’t
teach 16-, 17- and 18-year-olds that cheating is wrong,” she
added, “shame on us” (Anderson & Appelbome, 2011).
Second, another message for parents is that they remain
vigilant about their almost grown children’s activities outside
school. Even the brightest, most academically successful stu-
dents (and sometimes, especially these) will be drawn to
break the rules to get ahead, and as our data show, there
can be strong protective effects if parents stay attuned to their
children’s friends and leisure activities, beginning even with
relatively simple measures like being aware if cases of alcohol
are stored in cars or in homes (for pending sales to other minors).
Third, we need more proactive prevention efforts for fam-
ilies in distress. Talks and workshops in affluent communities
(Luthar & Sexton, 2004), can be used to help parents see the
potential harm, to their children (a) of their belittling, critical
communication patterns, and (b) of high depressive problems
in the parents themselves, for which they are reluctant to seek
help. Particularly useful would be regular support groups held
for mothers, who disproportionately shoulder the task of
shepherding teens through the diverse challenges of life in
privileged settings.
Of the most importance for practice and policy, we in sci-
ence must proactively disseminate central research findings
on this still little-studied “at-risk group,” including results of
stringent multivariate analyses, as well as descriptive data that
can direct future quantitative hypothesis testing (see Luthar,
1999). Above all, it is critical, always, to underscore that the
“pressure-cooker” lives of affluent teens stem from a complex
web of multiple influences. Problems in families certainly con-
tribute, as they do in all contexts. The peer group actively rein-
forces substance use (Balsa, Homer, French, & Norton, 2010;
Luthar& Latendresse, 2005a). Intimacy in close friendships,
which is critical during adolescence, is inevitably thwarted
by competition with one’s closest friends (see Anderson,
2011). Schools relentlessly pursue attendance in college level
courses, and the highest possible SAT scores. And ultimately,
all these pressures stem from, and are reinforced by, these ubi-
quitous, core tenets in the macrocosm of American society:
more is better; material wealth makes for ultimate happiness;
and this, in turn, is best acquired through attendance at elite col-
leges.
Scientists must regularly describe these pressures to the lay
public, via books, commentaries in newspapers, and work-
shops, with appropriate directions for change. Increasingly,
we have seen effective models of such efforts, such as
Schwartz’s (2007) writings on ways to reduce academic pres-
sures (e.g., with college admission decisions decided by lot-
teries of qualified applicants), Weissbourd’s (2011) descrip-
tions about ways in which parents and teachers unwittingly
contribute to students’ stress, and by Zimbardo’s (as cited
in Tugend, 2011) efforts to foster ethical decision-making
patterns among high school students.
Conclusions
In his early writings on resilience among at-risk youth, Norm
Garmezy (1971, 1974, 1983) presciently established two prin-
ciples that have remained cardinal within the field (Luthar,
2006). First, regardless of the risks in a particular socioeco-
nomic setting, some children will thrive even as others falter.
Affluent adolescents 447
Second, that as we in science study resilience, we must retain a
concerted focus on “modifiable modifiers.” We have at-
tempted to live up to Garmezy’s legacy in our decade-long re-
search on ostensibly privileged youth, identifying aspects of
family functioning that are strongly linked with youth malad-
justment, and at the same time, are amenable to change via
preventive interventions. Prominent among these salient risk
modifiers are parents’ attitudes toward teen substance use;
high levels of parent criticism and low expectations of their
children; the quality of relationships with mothers, in particu-
lar; and teens’ perceptions of depressive problems in their par-
ents. In our future work, we hope to further illuminate the most
potent, tractable sets of factors at the community, individual,
and family levels that can help youth thrive despite the relent-
less pressures of upward mobility in the culture of affluence—
or what Kasser (2002) has called “The American Nightmare.”
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Appendix A: Measure of Parents Bailing Out
Directions: When teenagers get into trouble, parents differ in how
quickly they come to defend their children. Please indicate how
your parents would probably react in the following situations (ac-
cording to a 5-point scale: 1 ¼definitely not,2¼unlikely,3¼neu-
tral,4¼likely, and 5 ¼definitely,yes).
1. You and a group of friends were seen laughing at a classmate in
the hallway, making fun of the student and loudly using names
such as “loser.” As punishment, the principal said you could
not attend a fun overnight school trip for your grade. Would
your parents protest?
2. You put off completing a very important school assignment, and
it was due the next day. You could not finish it without help. Your
parents knew that you had left it for the last minute. Would your
parents help you with the assignment?
3. For the third time, you and your friends were caught with vodka
on the school premises; the principal planned to report it to the
police. Would your parents try and stop the report?
4. For a major academic course, you copied part of an essay from an
internet source. The teacher discovered this and plans to fail you
for cheating. Would your parents protest?
5. You are a star athlete but during a game, you lost your temperand
yelled at the head coach. You were thrown off the team. Would
your parents try and get you back on the team?
6. You have a test the next day and you feel stressed out and feel un-
prepared to take it. Would your parents call you in sick the next
day to give you more time to study?
Affluent adolescents 449
