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A Family Study of Major Depressive Disorder in a Community Sample of Adolescents
Daniel N. Klein, PhD;
Peter M. Lewinsohn, PhD;
John R. Seeley, MS;
Paul Rohde, PhD
Arch Gen Psychiatry. 2001;58:13-20.
ABSTRACT
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Background Family studies provide a useful approach to exploring the continuities
and discontinuities between major depressive disorder (MDD) in children and
adolescents and MDD in adults. We report a family study of MDD in a large
community sample of adolescents.
Methods Probands included 268 adolescents with a history of MDD, 110 adolescents
with a history of nonmood disorders but no history of MDD through age 18 years,
and 291 adolescents with no history of psychopathology through age 18 years.
Psychopathology in their 2202 first-degree relatives was assessed with semistructured
direct and family history interviews, and best-estimate diagnoses were derived
with the use of all available data.
Results The relatives of adolescents with MDD exhibited significantly elevated
rates of MDD (hazard ratio [HR], 1.77; 95% confidence interval [CI], 1.46-2.31),
dysthymia (HR, 1.79; 95% CI, 1.11-2.87), and alcohol abuse or dependence (HR,
1.29; 95% CI, 1.05-1.53), but not anxiety disorders, drug abuse or dependence,
or antisocial and borderline personality disorder. In contrast, anxiety, substance
use, and disruptive behavior disorders in adolescents were not associated
with elevated rates of MDD in relatives. However, the relatives of probands
with anxiety and substance use disorders exhibited elevated rates of anxiety
and substance use disorders, respectively.
Conclusions The results provide evidence of the familial aggregation of adolescent
MDD, and also indicate that there is a considerable specificity in the pattern
of familial transmission. In addition, we found preliminary evidence of the
familial aggregation of adolescent anxiety and substance use disorders.
INTRODUCTION
DURING THE past 2 decades, there has been increasing recognition of
mood disorders in children and adolescents.1, 2, 3, 4
Much of the research in this area has focused on the continuities and discontinuities
between depression in juveniles and adults.
The clinical manifestation of major depressive disorder (MDD) in children
and adolescents tends to be similar to that of MDD in adults.5, 6, 7
Few studies have followed up youths with MDD into adulthood, but the existing
data indicate that many depressed adolescents experience episodes of MDD as
adults.8, 9, 10, 11, 12
In contrast, recent studies suggest that children with MDD may not be at increased
risk for MDD as adults.9, 13 Data
on the continuity between juvenile and adult MDD with respect to neurobiological
correlates and medication response is still inconclusive.1, 2, 14, 15
Family studies provide another means of exploring this issue. The familial
transmission of MDD can be examined by means of a top-down approach, which
focuses on the offspring of parents with MDD, or a bottom-up approach, which
focuses on the relatives of children and adolescents with MDD.16, 17
Most top-down studies have reported an increased rate of MDD in the offspring
of parents with MDD.18, 19, 20
However, these offspring also have elevated rates of a variety of nonmood
disorders.
The generalizability of top-down studies is limited, as most youths
with MDD do not have parents with MDD. Unfortunately, there have been fewer
bottom-up studies of juvenile MDD. These studies indicate that there is a
higher rate of MDD in the relatives of children and adolescents with MDD than
the relatives of normal control subjects.21, 22, 23, 24, 25
Several studies have also reported a higher rate of MDD in the relatives of
children and adolescents with MDD than in the relatives of juveniles with
nonmood disorders,25, 26, 27
but others have found no differences.22, 28, 29
These studies have also differed on whether the relatives of youths with MDD
have elevated rates of nonmood disorders. All of these studies used clinical
samples, and most relied on family history data rather than interviewing relatives
directly.
This article presents the major findings from the Oregon Adolescent
Depression Project family study, which used direct interviews to assess psychopathology
in the first-degree relatives of a large community sample of adolescents with
a history of MDD, a history of nonmood disorders, and no lifetime history
of psychopathology. This study has 2 important methodologic features. First,
the use of a community sample increases the generalizability of the findings,
as clinical samples of children and adolescents are not representative of
cases in the community,30 and studies of adult
MDD indicate that patient samples can bias the results of family studies.31, 32 Second, we used a longitudinal approach
to diagnosis, examining the probands twice in adolescence and a third time
in young adulthood.
We addressed 4 questions: (1) Is there a higher rate of MDD in the relatives
of adolescents with a history of MDD than in the relatives of adolescents
with no history of psychopathology? (2) Do the relatives of adolescents with
a history of nonmood disorders also have elevated rates of MDD? (3) Are the
rates of nonmood disorders higher in the relatives of adolescents with MDD
than in the relatives of never-depressed adolescents? (4) Does the familial
aggregation of MDD vary according to the sex of probands and relatives?
SUBJECTS AND METHODS
SUBJECTS
Probands
Probands were selected in 3 cohorts from 9 high schools in western Oregon.
Sampling fractions of 10%, 18.5%, and 20% were used for each cohort; sampling
within each school was proportional to the size of the school, the size of
the grade within the school, and the proportion of male and female students
within grade. A total of 1709 adolescents (aged 14-18 years; mean age, 16.6
years; SD, 1.2 years) completed the initial (T1) assessment between 1987 and
1989. Approximately 1 year later, 1507 of the adolescents (88%) had a second
evaluation (T2). Differences between the sample and the larger population
from which it was selected, and between participants and those who declined
to participate or dropped out before T2, were small.33
At age 24 years, all probands with a history of MDD (n = 360) or nonmood
disorders (n = 284) through T2, and an approximately equal number of adolescents
with no history of psychopathology through T2 (n = 457), were invited to participate
in a T3 evaluation. Of the 1101 T2 participants selected for a T3 interview,
940 (85%) completed the evaluation. The T2 diagnostic groups did not differ
on the rate of participation at T3.
Relatives
We assessed lifetime psychopathology in the first-degree relatives (older
than 13 years) of the T3 participants. To supplement the direct interviews
and ensure that at least some data were available for relatives who could
not be interviewed, informant data on relatives were collected from probands
and/or other relatives. We sought to collect at least 2 sources of diagnostic
data for each family member. Of the 1101 probands selected for a T3 interview,
family diagnostic information was available for 840 (76%). Of the 940 probands
with T3 data, family data were available for 802 (85%). Family data were also
available for 38 probands who were selected for, but did not complete, the
T3 evaluation. Of the 2750 relatives with diagnostic data, direct interviews
were obtained from 1744 (63%). At least 2 sources of data were available for
all but 440 relatives (16%).
For this report, we excluded probands with a history of psychotic disorder
(n = 2), bipolar disorder (n = 19), and dysthymic disorder or adjustment disorder
with depressed mood but no history of MDD (n = 9 and 87, respectively) through
T3. In addition, to maintain pure comparison groups, we excluded 46 subjects
with nonmood disorders and 8 subjects with no history of psychopathology who
developed a mood disorder for the first time between T2 and age 18 years.
This report focuses on the remaining groups of 268 adolescents with a history
of MDD, 110 adolescents with a history of nonmood disorders but no history
of mood disorders, 291 adolescents with no history of psychopathology through
age 18 years, and their 2202 first-degree relatives. The mean number of relatives
per proband was 3.29 (SD, 1.17; median, 3.00).
DIAGNOSTIC INTERVIEWS
Probands
At T1, probands were interviewed with a modified version of the Schedule
for Affective Disorders and Schizophrenia for School-Age Children,34 which included additional items to derive DSM-III-R35 diagnoses. Modified 14-item
Hamilton Rating Scale for Depression36 scores
for current or past depressive episodes were extracted from the Schedule for
Affective Disorders and Schizophrenia for School-Age Children.37
At T2 and T3, probands were interviewed by means of the Longitudinal
Interval Follow-up Evaluation,38 which elicited
information about the course of psychopathology since the previous evaluation.
In addition, antisocial and borderline personality disorder were assessed
at T3 by means of the Personality Disorder Examination.39
Because of low prevalence rates, we used dimensional scores (the sum of the
scores for each criterion, rated on a 0-2 scale) in analyses of the personality
disorders.40 Interrater reliability of our
T1, T2, and T3 diagnoses was generally excellent, as reported in detail elsewhere.10, 33, 40
Relatives
Parents and siblings older than 18 years were interviewed with the Structured
Clinical Interview for DSM-IV, nonpatient version,41 and the antisocial and borderline personality disorder
sections of the Structured Clinical Interview for DSM-IV for Axis II Personality Disorders.42
Siblings between the ages of 14 and 18 years were interviewed with the Schedule
for Affective Disorders and Schizophrenia for School-Age Children, modified
for DSM-IV.43 All
interviews were conducted blind to proband diagnoses. To guard against interviewers
being biased by patterns of psychopathology within a family, no interviewer
examined more than 2 members of the same family. Interrater reliability was
assessed by having a second rater independently rate audiotapes of a randomly
selected sample (n = 157) of interviews. Interrater reliability was excellent
for lifetime diagnoses of MDD ( = 0.94), anxiety disorders (
= 0.90), alcohol abuse or dependence ( = 0.86), and drug abuse or dependence
( = 0.89). There were too few cases to calculate interrater reliability
for antisocial and borderline personality disorder.
Family history data were collected by means of the revised Family Informant
Schedule and Criteria,44 modified to derive DSM-IV diagnoses. In addition, we assessed borderline personality
disorder by means of the relevant section from the Family History Interview
for Personality Disorders.45 On the basis of
a random sample of informant interviews (n = 242), interrater reliability
ranged from fair to excellent for lifetime diagnoses of MDD ( = 0.90),
anxiety disorders ( = 0.77), alcohol abuse or dependence ( =
0.90), drug abuse or dependence ( = 0.82), antisocial personality disorder
( = 0.56), and borderline personality disorder ( = 1.00).
PROCEDURE
After a thorough description of the study, written informed consent
was obtained from the probands and relatives.
Proband interviews at T3 and interviews with relatives and informants
were conducted by telephone, which generally yields results comparable with
those of face-to-face interviews.46, 47, 48
Most of the interviewers had advanced degrees in clinical or counseling psychology
or social work, and several years of clinical experience. All interviewers
were trained in the use of the Structured Clinical Interview for DSM-IV and the Family Informant Schedule and Criteria and completed
at least 2 supervised training interviews, achieving >0.80 for concordance
between their symptom ratings and those of the supervisor.
Best-estimate diagnoses49 were derived
for all relatives by means of DSM-IV criteria by
4 senior diagnosticians. Two diagnosticians, blind to proband diagnoses, independently
derived diagnoses for each relative with the use of all available data. Disagreements
were resolved by consensus. Interrater reliability for best-estimate diagnoses
was good to excellent: MDD ( = 0.91), anxiety disorders ( =
0.94), alcohol abuse or dependence ( = 0.97), drug abuse or dependence
( = 0.96), antisocial personality disorder ( = 0.80), and borderline
personality disorder ( = 0.72).
DATA ANALYSIS
Descriptive characteristics were compared between groups by means of  2 tests for categorical variables and analysis of variance for continuous
variables. Rates of lifetime best-estimate Axis I disorders in relatives were
analyzed by means of Cox proportional hazards (PH) models. The dependent variable
was time to onset of disorder; relatives without the disorder were considered
censored. Best-estimate Axis II disorders in relatives were analyzed by means
of multiple logistic regression (LR) models. As relatives were clustered within
families rather than comprising independent observations, the use of standard
PH and LR models would underestimate the SEs, increasing the chance of type
I errors. Therefore, we estimated the PH and LR models by means of Taylor
series linearization (or generalized estimating equations), which takes the
clustered structure of the data into account.50
The major independent variables were lifetime diagnoses of MDD, anxiety disorders,
disruptive behavior disorders, and substance use disorders in the probands.
All proband diagnoses were entered into the models simultaneously to control
for proband comorbidity. Therefore, the effect for any particular proband
diagnosis was over and above the effects of the other proband diagnoses. The
models were adjusted for sex of the proband, sex of the relative, generation
of the relative (parent or sibling of the proband), education of the relative
(college graduate vs not), whether the relative had received a direct interview,
and number of family history interviews on the relative. In addition, in analyses
of antisocial and borderline personality disorders in relatives, the corresponding
proband Personality Disorder Examination dimensional scores at T3 were included
as covariates. In all analyses,  was set at .05 and tests were 2 tailed.
RESULTS
CHARACTERISTICS OF PROBANDS AND RELATIVES
For descriptive purposes, the probands were divided into 3 groups: probands
with a history of MDD; probands with a history of nonmood disorders but no
lifetime MDD (NMD); and probands with no history of mental illness through
age 18 years (NMI). The groups were similar with respect to age and race (Table 1). Probands with MDD were significantly
more likely to be female and had significantly higher scores on the Hamilton
Rating Scale for Depression than did the NMD and NMI probands, while probands
with NMD had significantly higher Hamilton Rating Scale for Depression scores
than did NMI probands.
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Table 1. Descriptive Characteristics of the Proband Diagnostic Groups*
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The MDD probands had a mean age at onset of 14.9 years; 26% had a history
of recurrent major depressive episodes; and the mean duration of their longest
episode was 6 months. More than 40% of the NMD probands had substance use
and disruptive behavior disorders, and 30% had anxiety disorders. Although
the rates of nonmood diagnoses were significantly lower among the MDD probands,
many of them also had a history of nonmood disorders.
The relatives of the MDD, NMD, and NMI probands were similar with respect
to age, sex, generation (parent or sibling), and number of informant interviews
(Table 2). However, compared with
the relatives of NMI probands, the relatives of probands with MDD were significantly
less likely to have completed college. In addition, a significantly greater
proportion of relatives of probands with NMD and NMI than relatives of probands
with MDD received direct interviews.
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Table 2. Descriptive Characteristics of First-Degree Relatives by Proband
Diagnostic Group*
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RATES OF MOOD AND NONMOOD DISORDERS IN RELATIVES
The rates of mood disorders, particularly MDD and dysthymic disorder,
were moderately and significantly elevated in the relatives of adolescent
probands with a history of MDD (Table 3). In contrast, the relatives of adolescents with MDD generally
did not exhibit elevated rates of nonmood disorders, with the exception of
a small, but significant, increase in the rate of alcohol abuse or dependence.
To explore this finding further, we examined whether the increased rate of
alcohol abuse or dependence in the relatives of adolescents with MDD could
be attributed to comorbid MDD in the same relatives. Indeed, when comorbid
MDD in the relative was included as an additional covariate in the PH model,
it was significantly associated with alcohol abuse or dependence in the same
relative (hazard ratio [HR], 1.45; 95% confidence interval [CI], 1.21-1.74).
However, the association between MDD in probands and alcohol abuse or dependence
in relatives was no longer significant (HR, 1.19; 95% CI, 0.99-1.43), suggesting
that the increased rate of alcoholism in the relatives of adolescents with
MDD may be due to MDD–alcohol abuse or dependence comorbidity in those
relatives.
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Table 3. Lifetime Best-Estimate Rates of Psychiatric Disorders Among
First-Degree Relatives by Proband Diagnostic Group*
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The specificity of familial aggregation of MDD was further supported
by the data on rates of mood disorders in the relatives of adolescents with
nonmood diagnoses. The relatives of probands with anxiety, disruptive behavior,
and substance use disorders did not have significantly elevated rates of mood
disorders.
Both the anxiety and substance use disorders exhibited significant familial
aggregation. There was a moderately elevated rate of anxiety disorders in
the relatives of adolescents with a history of anxiety disorders, and small
to moderate, but significant, increases in the rates of alcohol abuse or dependence
and drug abuse or dependence in the relatives of adolescents with a history
of substance use disorders. The relatives of adolescents with a history of
disruptive behavior disorders also had a significantly elevated rate of drug
abuse or dependence; however, they did not exhibit increased rates of alcohol
abuse or dependence or antisocial personality disorder.
There was a high degree of specificity in the familial aggregation of
substance use disorders, as the relatives of adolescents with substance use
conditions did not exhibit increased rates of any nonsubstance disorder. There
was somewhat less specificity in the familial aggregation of anxiety and disruptive
behavior disorders. The rate of alcohol abuse or dependence was elevated in
the relatives of adolescents with anxiety disorders, and the rate of anxiety
disorders was elevated in the relatives of probands with disruptive behavior
disorders.
IMPACT OF SEX ON FAMILIAL TRANSMISSION OF MDD
The rate of MDD in relatives did not differ as a function of proband
sex (Table 4). However, female
relatives had a significantly higher rate of MDD than male relatives (HR,
1.41; 95% CI, 1.12-1.78). Although parents and siblings had similar uncorrected
rates of MDD, there was a significant effect for generation of relatives in
the Cox PH model because of the earlier age at onset of MDD in the siblings
(mean, 17.2 years; SD, 6.0 years) than the parents (mean, 30.8 years; SD,
11.3 years) (HR, 2.27; 95% CI, 1.72-3.03). Finally, there was a significant
interaction between proband sex and relative sex (21 = 6.21; P = .01). In the relatives of female
probands, the rate of MDD was significantly higher in females than males (HR,
1.79; 95% CI, 1.37-2.34). In contrast, among the relatives of male probands,
the rates of MDD were similar for males and females (HR, 0.69; 95% CI, 0.41-1.15).
No other interactions were significant.
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Table 4. Lifetime Best-Estimate Rates of MDD by Family Member as a
Function of Proband Sex*
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INFORMANT REPORT AS A POTENTIAL SOURCE OF BIAS
Psychopathology in informants can bias reports of psychopathology in
their relatives,51, 52 producing
spurious evidence of familial aggregation. We addressed this possibility in
2 ways. First, we included interactions between each of the proband diagnoses
and whether relatives were directly interviewed in the PH and LR models. None
of the interaction terms was significantly associated with any of the diagnoses
in relatives. Second, we reanalyzed the data by using only Structured Clinical
Interview for DSM-IV, rather than best-estimate,
diagnoses of relatives. The findings were generally similar to the results
with best-estimate diagnoses. The adjusted HRs (95% CIs) for MDD in relatives
were 1.64 (1.30-2.07) for proband MDD, 1.11 (0.81-1.53) for proband anxiety
disorders, 1.38 (1.01-1.88) for proband disruptive disorders, and 0.80 (0.60-1.08)
for proband substance use disorders.
COMMENT
These results are consistent with previous evidence of the familial
aggregation of adolescent MDD from both bottom-up and top-down studies16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29
and extend these earlier findings to a community sample.
The magnitude of the familial aggregation of MDD was somewhat smaller
than in previous family studies of adult MDD.53, 54
This may be due to the use of a community sample, as clinical samples appear
to overestimate the degree of familial aggregation.31, 32
Alternatively, Wickramaratne and Weissman55
suggested that familial transmission plays a smaller role in adolescent-onset
MDD than childhood- or adult-onset MDD. Although 13% of our MDD probands had
a childhood (before age 12 years) onset, most had an onset in adolescence.
We also found that dysthymia aggregated in the families of adolescents
with MDD. This is consistent with family studies of adult probands that have
reported a familial relationship between dysthymia and MDD.56, 57
Previous studies, from both the bottom-up and top-down perspectives,
have reported conflicting findings regarding the specificity of familial aggregation
of juvenile MDD.18, 19, 20, 22, 25, 26, 29
The present study examined this issue from 2 directions and in both cases
found evidence of specificity. First, after controlling for proband comorbidity,
the only nonmood disorder that was significantly elevated in the relatives
of adolescents with MDD was alcohol abuse or dependence. The relatives of
adolescents with MDD did not exhibit increased rates of anxiety disorders,
drug abuse or dependence, or antisocial and borderline personality disorders.
Second, the relatives of adolescents with anxiety, disruptive behavior, and
substance abuse disorders did not exhibit significantly elevated rates of
any mood disorders.
Claims of specificity must be qualified in several respects, however.
First, although we tested the significance of the associations between probands'
and relatives' diagnoses, we did not formally test the significance of the
differences in the magnitude of these associations between different diagnoses.
This can be assessed informally by inspecting the 95% CIs for the hazard and
odds ratios in Table 3. There
is some overlap between the CI for the association between MDD in probands
and MDD in relatives and the CIs for the associations between MDD in probands
and alcohol abuse or dependence, anxiety disorders, and antisocial personality
disorders in relatives. In addition, the CI for the association between proband
MDD and relative MDD overlaps with the CI for the association between disruptive
behavior disorders in probands and MDD in relatives. Finally, when the analyses
were restricted to relatives with direct interviews, there was a small but
significant association between proband disruptive behavior disorders and
MDD in relatives. Nonetheless, the overall pattern of results suggests that
the familial transmission of mood disorders is largely independent of the
transmission of anxiety, disruptive behavior, and substance use disorders.
Although this article focused on the familial aggregation of adolescent
MDD, we also presented data on the familial transmission of several groups
of nonmood disorders. Although conclusions must remain tentative until these
groups are broken down into more specific conditions, the data suggest that
there are significant, and fairly specific, patterns of familial aggregation
for adolescent anxiety and substance use disorders. Previous family and offspring
studies of juvenile anxiety58, 59, 60
and substance use disorders60, 61
have also reported significant familial aggregation, although the findings
on specificity of transmission have been mixed.
Consistent with previous studies, adolescents with disruptive behavior
disorders had a significantly elevated rate of drug abuse or dependence in
their relatives.62 The finding of an increased
rate of anxiety disorders in the relatives of adolescents with disruptive
behavior disorders was unexpected, although it is consistent with at least
1 previous study.63 The lack of associations
between proband disruptive behavior disorder and alcohol abuse or dependence
and antisocial personality disorder in relatives was also surprising.64 However, it is consistent with a previous study that
also failed to find an increased rate of alcoholism in the relatives of youths
with attention deficit disorder.65
We also explored the role of sex in the familial transmission of adolescent
MDD. Previous studies of adult MDD have differed on whether female probands
have a similar66, 67 or greater68, 69 familial liability to MDD. In our
sample of adolescents, there was a significant interaction between sex of
the proband and sex of the relative. The expected female preponderance of
MDD was observed in the relatives of female probands. Among the relatives
of male probands, however, males exhibited a nonsignificantly higher rate
of MDD than females. To our knowledge, this effect has not been reported before.
However, in a review and reanalysis of earlier family studies of adult mood
disorders, Faraone et al70 found a pattern
of greater proband-relative concordance in same-sex than opposite-sex sibling
pairs. These data suggest that the factors involved in the etiology of MDD
may differ, at least in part, between males and females.66
Alternatively, these results may be due to cultural transmission, with same-sex
relatives having a greater impact than opposite-sex relatives through identification
or modeling.
The lifetime prevalence of most disorders in the relatives of NMI probands
were comparable with findings of the National Comorbidity Survey.71 The sole exception was the lower rate of anxiety
disorders in the present study, possibly caused by differences in diagnostic
instruments and procedures.
This study had several limitations. The diagnoses of the probands and
relatives were based on retrospective data (although the probands had 3 diagnostic
evaluations), and the long-term test-retest reliability of lifetime diagnoses
in community samples is only moderate.72, 73
Although we were able to conduct direct interviews with 63% of the relatives,
we were forced to rely on informant data for the remaining 37%. Our assessment
of Axis II disorders in relatives was limited to antisocial and borderline
personality, and, when using Axis II psychopathology in probands as a covariate,
we used assessments conducted in young adulthood rather than adolescence.
Finally, diagnoses in probands were based on DSM-III-R,
while diagnoses in relatives were based on DSM-IV,
possibly attenuating estimates of the degree of familial aggregation.
In conclusion, this study indicates that adolescent MDD exhibits both
significant familial aggregation and a high degree of specificity of transmission.
These data support the validity of the diagnosis of MDD in adolescents, and
the continuity between adolescent and adult MDD. In addition, we observed
a significant and relatively specific pattern of familial aggregation for
most broad categories of nonmood disorders, supporting the validity and distinctiveness
of these other forms of psychopathology in adolescents.
AUTHOR INFORMATION
Accepted for publication July 20, 2000.
This work was supported in part by grants MH40501, MH50522, and MH52858
from the National Institute of Mental Health, Bethesda, Md (Dr Lewinsohn).
From the Department of Psychology, State University of New York at
Stony Brook (Dr Klein); and Oregon Research Institute, Eugene (Drs Lewinsohn
and Rohde and Mr Seeley).
Corresponding author: Peter M. Lewinsohn, PhD, Oregon Research Institute,
1715 Franklin Blvd, Eugene, OR 97403-1983.
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