Content uploaded by Richard E Zinbarg
Author content
All content in this area was uploaded by Richard E Zinbarg
Content may be subject to copyright.
A Longitudinal Examination of Stress Generation in Depressive and
Anxiety Disorders
Amanda A. Uliaszek
Northwestern University Richard E. Zinbarg
Northwestern University and the Family Institute at
Northwestern University
Susan Mineka
Northwestern University Michelle G. Craske
University of California, Los Angeles
James W. Griffith and Jonathan M. Sutton
Northwestern University Alyssa Epstein and Constance Hammen
University of California, Los Angeles
The current study compared two competing theories of the stress generation model of depression (stress
causation vs. stress continuation) using interview-based measures of episodic life stress, as well as
interpersonal and noninterpersonal chronic life stress. We also expanded on past research by examining
anxiety disorders as well as depressive disorders. In addition, we examined the role of neuroticism and
extraversion in these relationships. Participants were 627 adolescents enrolled in a two-site, longitudinal
study of risk factors for depressive and anxiety disorders. Baseline and follow-up assessments were
approximately one year apart. Results supported the stress causation theory for episodic stress generation
for anxiety disorders, with neuroticism partially accounting for this relationship. The stress causation
theory was also supported for depression, but only for more moderate to severe stressors; neuroticism
partially accounted for this relationship as well. Finally, we found evidence for interpersonal and
noninterpersonal chronic life stress continuation in both depressive and anxiety disorders. The present
findings have implications regarding the specificity of the stress generation model to depressive
disorders, as well as variables involved in the stress generation process.
Keywords: stress generation, depression, anxiety, personality
Research has consistently shown that major stressful life events
often precede the onset of an initial depressive episode (e.g.,
Hammen, 2005; Monroe, Slavich, & Georgiades, 2009). The stress
generation model of depression (Hammen, 1991), which states that
depression also predicts future stress, has less often been the focus
of study. The body of research on stress generation has grown in
recent years, with results suggesting that depressed individuals
tend to generate primarily dependent interpersonal stress (for a
recent review, see Liu & Alloy, 2010). Hypothesized mechanisms
of stress generation also have been examined, with a focus on
specific cognitive and interpersonal styles, as well as family vari-
ables (e.g., Liu & Alloy, 2010). However, there are still many
unanswered questions concerning these relationships. For exam-
ple, recent reviews suggest a closer examination of chronic life stress
because most research has focused solely on episodic life stress (e.g.,
Liu & Alloy, 2010). In addition, little is known about whether stress
generation is found in other closely related conditions (such as anxiety
disorders) or whether stress generation is specific to depressive dis-
orders. Moreover, we present two theoretically distinct interpretations
of the stress generation model: the stress continuation theory versus
the stress causation theory. This is the first study to explicitly articu-
late and compare two interpretations of stress generation. Finally,
additional third variables in the stress generation relationships, such as
personality traits, may help inform our understanding of stress gen-
eration. The present study addresses each of these issues in a large
sample of adolescents.
This article was published Online First October 17, 2011.
Amanda A. Uliaszek, Susan Mineka, James W. Griffith, and Jonathan
M. Sutton, Department of Psychology, Northwestern University; Richard
E. Zinbarg, Department of Psychology, Northwestern University, Patricia
M. Nielson Research chair and Director of Anxiety and Panic Treatment
Program, The Family Institute at Northwestern University; Michelle G.
Craske, Alyssa Epstein, and Constance Hammen, Department of Psychol-
ogy, University of California, Los Angeles.
James W. Griffith is now at the Department of Medical Social Sciences,
Northwestern University; Jonathan M. Sutton is now at Edward Hines, Jr. VA
Hospital, Hines, IL; and Amanda A. Uliaszek is now at the University of
Toronto, Scarborough.
This research was supported by National Institute of Mental Health Grants
R01 MH65651 to Richard Zinbarg and Susan Mineka (Northwestern Univer-
sity) and R01 MH65652 to Michelle Craske (University of California, Los
Angeles). Richard Zinbarg was also supported by the Patricia M Nielsen
Research Chair of the Family Institute at Northwestern University.
Correspondence concerning this article should be addressed to Amanda A.
Uliaszek, Department of Psychology, University of Toronto, Scarborough, 1265
Military Trail, Toronto, Ontario, M1C 1A4. E-mail: auliaszek@utsc.utoronto.ca
Journal of Abnormal Psychology © 2011 American Psychological Association
2012, Vol. 121, No. 1, 4–15 0021-843X/11/$12.00 DOI: 10.1037/a0025835
4
Dimensions of Life Stress
The majority of stress research has focused on episodic life
stress, which refers to events that take place within discrete,
limited time periods. In contrast, chronic life stress is defined as
ongoing life difficulties (e.g., Wheaton, 1994). Chronic life stress
has been shown to be cross-sectionally related to depressive symp-
toms in adults (e.g., McGonagle & Kessler, 1990), depressive
disorders in children and adolescents (e.g., Rudolph et al., 2000;
Uliaszek et al., 2010), and anxiety disorders in adolescents (e.g.,
Uliaszek et al., 2010). A few prospective studies have also found
that chronic life stress predicted the severity of depression and the
first onset of depression (e.g., Daley, Hammen, & Rao, 2000;
Hammen, Davila, Brown, Ellicott, & Gitlin, 1992).
Life stress can be characterized by two additional dimensions:
independent/dependent and interpersonal/noninterpersonal. Inde-
pendent stress refers to events that are beyond one’s control;
examples include natural disasters, being in a plane crash, or the
death of a loved one. Dependent stress occurs, at least in part, as
a result of the individual’s own actions (Daley et al., 1997).
Examples include financial, marital, or academic difficulties (al-
though these examples could be independent stressors under cer-
tain circumstances). Interpersonal stress is defined as difficulties
with family, peers, or significant others, whereas noninterpersonal
stress refers to occupational, educational, and health problems
(Hammen, 1991).
Stress Generation
Research has shown that those with a history of depression tend
to experience higher levels of interpersonal life stress, even when
euthymic, than do those without a history of depression (e.g.,
Chun, Cronkite, & Moos, 2004; Harkness & Stewart, 2009; Ru-
dolph, 2008; Rudolph, Flynn, Abaied, Groot, & Thompson, 2009).
Such effects of baseline depression on later stress have been found
in clinical, collegiate, and community samples (Chun et al., 2004;
Daley et al., 1997; Hammen, 1991; Shih, 2006), child and adoles-
cent samples (Cole, Girgus, Paul, & Nolen-Hoeksema, 2004; Ru-
dolph, 2008; Rudolph et al., 2000, 2009), and a late middle-aged
sample (Holahan, Moos, Holahan, Brennan, & Schutte, 2005).
Rudolph and colleagues (2009) found that stress generated by
depression partially accounted for the continuity of depression
over time in female youth. These results are consistent with stress
generation being a potential mechanism explaining the high rate of
relapse in major depression (e.g., Daley et al., 1997). We empha-
size that stress generation does not imply that the mean level of
stress continues to increase over time. Instead, stress generation
implies that a heightened level of stress continues to be maintained
for a time period after a depressive episode relative to what would
be expected with nondepressed individuals with high levels of
stress over the same time period.
Two Contrasting Interpretations of Stress Generation
There is an abundance of evidence supporting stress generation
in depression when this phenomenon is construed broadly. How-
ever, there are at least two plausible theoretical interpretations of
stress generation that differ in terms of whether intraindividual
characteristics (e.g., depression or neuroticism) exert a causal
influence on subsequent life stress and there is a paucity of data
that would allow us to choose among the two interpretations. The
first, which we refer to as the stress causation theory is similar to
the way stress generation is typically described (e.g., Hammen,
1991). In stress causation, the characteristics of the depressed
person (symptoms of depression or other predictors of depression)
are thought to play a causal role in generating stress over time. In
contrast, the second interpretation, which is referred to as stress
continuation theory, posits that the prospective relationship be-
tween depression and stress is actually accounted for by the
continuity of stress over time. According to this view, there is no
causal influence of depression on subsequent life stress. Instead,
there is a cross-sectional relationship between depression and life
stress at baseline (e.g., Rudolph et al., 2000; Uliaszek et al., 2010)
and that stress demonstrates a large degree of temporal stability.
Thus, the partial correlation between depression and subsequent
life stress should not be significant when accounting for baseline
stress.
A comparison of these two interpretations of stress generation is
important from both a theoretical and an applied standpoint. If the
stress continuation theory is supported, then we might see evidence
of stress continuation in other disorders associated with life stress,
as well as in people without a diagnosed disorder who are expe-
riencing heightened life stress. However, if the stress causation
theory is supported, future studies should focus on depression-
specific characteristics as variables of interest in understanding
stress generation. These characteristics may be specific to the
symptoms of depression (e.g., anhedonia, irritable mood) or to
specific correlates of depression. However, it is important to note
that if specific correlates of depression (e.g., social withdrawal,
high neuroticism) are salient third variables, then other disorders
related to these correlates (e.g., anxiety disorders) may be associ-
ated with stress causation as well. Regardless of which theory is
supported, the applied consequences are the same: those with a
history of depression are prone to later stress and this stress might
well cause further depression (Rudolph et al., 2009).
Given that the distinction between the stress causation and stress
continuation theories has not previously been articulated, it is not
surprising that previous studies have adopted analytic strategies
that are insufficient for testing both interpretations. That is, many
previous studies have only reported the direct relationship between
depression and future stress without accounting for baseline stress
(e.g., Daley et al., 1997; Hammen, 1991; Shih, 2006), while a
small number of studies have only reported results where baseline
stress has been taken into account. Thus, the present study reports
results relevant to both theories in a single sample.
Neuroticism and Extraversion
Researchers have noted that depressive symptoms alone do not
seem to explain the continued elevated stress following the onset
of a depressive episode (Chun et al., 2004; Daley et al., 1997;
Hammen, 1991). For example, some past studies have found that
people who were depressed at a baseline assessment often contin-
ued to have elevated levels of stress long after the depressive
episode ends (e.g., Chun et al., 2004). Evidence supports negative
cognitive styles, family factors, and interpersonal styles as impor-
tant explanatory factors in stress generation (for a review, see Lui
& Alloy, 2010). There is also some evidence pointing to neuroti-
5
STRESS, PERSONALITY, EMOTIONAL DISORDERS
cism and extraversion as potential explanatory factors in stress
generation.
Neuroticism is conceptualized as a core general risk factor for
depression (e.g., Clark, Watson, & Mineka, 1994; Klein, Durbin,
& Shankman, 2009), with neuroticism prospectively predicting
increased risk for depression (e.g., Kendler, Kuhn, & Prescott,
2004; Krueger, 1999). In cross-sectional analyses, neuroticism is
associated with both episodic life stress (Kendler, Gardner, &
Prescott, 2003; Saudino, Pederson, Lichtenstein, McClearn, &
Plomin, 1997) and chronic life stress (Ormel, Oldehinkel, & Bril-
man, 2001; Uliaszek et al., 2010). Moreover, one study found that
neuroticism prospectively predicted dependent episodic life stress
(Magnus, Diener, Fujita, & Pavot, 1993). Research has also ex-
amined the interrelationships among neuroticism, life stress, and
depression, with cross-sectional findings demonstrating that neu-
roticism partially accounts for the relationship between interper-
sonal chronic life stress and depression (Uliaszek et al., 2010).
Concerning extraversion, some studies have shown that de-
pressed individuals report lower levels of extraversion than con-
trols (Reich, Noyes, Hirschfeld, Coryell, & O’Gorman, 1987; Trull
& Sher, 1994) and that extraversion is inversely related to risk for
a first onset of depression (e.g., Hirschfeld, Klerman, Lavori &
Keller, 1989), although the results are mixed (e.g., Kendler, Neale,
Kessler, Heath, & Eaves, 1993). At least one study has demon-
strated low extraversion to be concurrently associated with chronic
life stress in an adolescent sample (Uliaszek et al., 2010).
Based on the above literature, it is possible that these personality
variables partially account for the relationship between stress and
depression. Specifically, heightened neuroticism and/or low extra-
version could be third variables in the relationship between ele-
vated stress and depression. Concerning neuroticism, this might be
caused by an increase in emotion sensitivity and negative mood
states that make interpersonal interactions conflictual. In the case
of low extraversion, this might result from withdrawal from
friends, family, or work life.
Anxiety Disorders
Depression is the disorder most frequently examined in stress
generation research (Hammen, 2005). However, because anxiety
disorders are conceptually and empirically related to depression,
they are promising candidates for further exploration. First, de-
pressive and anxiety disorders are highly comorbid and have many
overlapping features (e.g., Kessler, Chiu, Demler, & Walters,
2005; Mineka, Watson, & Clark, 1998). Thus, certain character-
istics of depression that have been shown to be important in stress
generation may also be present in some anxiety disorders. For
example, negative interpersonal characteristics such as an avoidant
coping style act as third variables in stress generation in depression
(for review, see Liu & Alloy, 2010). There is also evidence that
similar negative interpersonal characteristics are present in anxiety
disorders (e.g., Heering & Kring, 2007). Second, as with depres-
sion, neuroticism is a risk factor for many anxiety disorders (e.g.,
Clark et al., 1994; Hayward, Killen, Kraemer, & Taylor, 2000).
Some research also supports a relationship between low extraver-
sion and several anxiety disorders (see Trull & Sher, 1994),
although other research points to a specific relationship between
extraversion and social phobia (Uliaszek et al., 2010; Watson et
al., 2005). Thus, if neuroticism and/or extraversion are important
third variables in stress generation, then we might see stress
generation in anxiety disorders because of their relationship to
those personality variables. Third, if the temporal stability of stress
is an important factor in stress generation, as posited by the stress
continuation theory, and anxiety disorders have a cross-sectional
relationship with stress, this would constitute a further reason why
we would hypothesize stress continuation in anxiety disorders.
Some studies have indeed reported an association between anx-
iety and life stress. For example, social phobia was cross-
sectionally associated with interpersonal chronic life stress in our
sample of adolescents (Uliaszek et al., 2010). This relationship was
partially accounted for by neuroticism and extraversion. In a series
of prospective studies examining college students, negative events
were shown to be risk factors for anxiety symptoms (Hankin,
Abramson, Miller, & Haeffel, 2004). However, at least one study
has examined stress generation in self-reported anxiety symptoms
utilizing a checklist measure of life stress; this study failed to find
evidence of stress generation (Joiner, Wingate, Gencoz & Gencoz,
2005). Liu and Alloy (2010) concluded that more research is
needed to further explore these relationships.
Present Study
The present study utilized data from the Youth Emotion Proj-
ect—a large multiyear, two-site prospective study examining risk
factors for psychopathology in late adolescence (see Zinbarg et al.,
2010, for more details). The present analyses used data from two
time points, collected approximately one year apart. A goal of this
study was to expand on previous stress generation research by
examining both interpersonal and noninterpersonal chronic life
stress, as well as dependent episodic life stress. Only dependent
events were examined because, based on the definition of
independent life stress, we believe that a person’s direct actions
cannot cause these events. These relationships were examined
for both depressive and anxiety disorders. This study also
examined the competing hypotheses of the stress continuation
and stress causation theories for both depression and anxiety
disorders. We also sought to test the role of personality traits in
stress generation. Given the abundance of research demonstrat-
ing the relationships among personality with depressive and
anxiety disorders and the relationships between personality and
life stress, we hypothesized that neuroticism and extraversion
would at least partially account for stress generation in depres-
sive and anxiety disorders.
Method
Participants
Participants were from the Youth Emotion Project, a multiyear,
two-site prospective study designed to identify risk factors for
emotional disorders in a large sample of late adolescents (see
Zinbarg et al., 2010 for more details). The present study included
two assessment points, collected approximately 1 year apart. A
total of 627 participants were recruited for the Time 1 assessment
(T1). These participants, all in their junior year of high school,
were recruited over three years based on scores from the neurot-
icism scale of the revised Eysenck Personality Questionnaire
(EPQ-R-N; Eysenck & Eysenck, 1975), which was administered
6ULIASZEK ET AL.
during mass screening sessions (see Zinbarg et al., 2010). Because
neuroticism has been shown to be a risk factor for depressive and
anxiety disorders (e.g., Clark et al., 1994; Klein et al., 2009),
participants scoring in the top third on the EPQ-R-N were over-
sampled. This behavioral high-risk design was intended to over-
come statistical problems associated with the low base rates of
particular disorders in community samples (Hauner, Revelle &
Zinbarg, 2011).
1
Of the participants who were invited and who
participated in the T1 assessment (n⫽627), 368 had high, 145 had
medium, and 114 had low scores on the EPQ-R-N (58.7, 23.1, and
18.2%, respectively).
Participants were recruited from two large metropolitan areas
(suburban Chicago and suburban Los Angeles). There were 305
participants drawn from the Northwestern University site and 322
participants from the University of California, Los Angeles site.
The racial makeup of the total sample was as follows: Caucasian,
n⫽302 (48.2%); Hispanic/Latin American, n⫽96 (15.3%);
African American, n⫽82 (13.1%); more than one ethnicity, n⫽
82 (13.1%); other, n⫽34 (5.4%); Asian American, n⫽27
(4.3%); Pacific Islander, n⫽4 (0.6%).
At T1, the participants ranged in age from 15 to 18 years, with
a mean (M) age of 16.91 (standard deviation [SD]⫽.39). The
participants included 195 males (31.1%) and 432 females. This
gender difference in participation was unintentional and occurred
for several reasons, such as females being more likely to agree to
complete the screening questionnaire and to participate in the
study if invited. Because females tend to score higher on neurot-
icism (see Costa et al., 2001) and due to our behavioral high risk
design, more females were invited to participate.
Measures
Structured Clinical Interview for the Diagnostic and Statis-
tical Manual for Mental Disorders–IV (DSM)–IV. (SCID; First,
Spitzer, Gibbons, & Williams, 2002). Diagnoses of current
Axis I disorders were made using the SCID. SCID interviewers
were graduate students, postdoctoral fellows, and bachelor’s level
research assistants. Training included approximately 60 hours of
didactics, matching gold standard ratings, role-playing, and live
observations. Each diagnosis was presented at a supervision and
consensus meeting led by doctoral-level supervisors. To maintain
consistency across sites, difficult cases were presented at weekly
teleconferences that were periodically attended by supervisors
from the other site.
Interrater reliability for categorical DSM–IV (American Psychi-
atric Association, 2004) diagnoses was assessed by having trained
interviewers observe live SCIDs on a subset of 69 cases. Cohen’s
(1960) kappa was acceptable to good when aggregated across all
disorders (⫽.82) and for the individual disorders, including
major depressive disorder (⫽.83), social phobia (⫽.65),
generalized anxiety disorder (⫽.85), and obsessive–compulsive
disorder (⫽.85). Kappa estimates are only available for these
disorders because they were the only ones rated frequently enough
(at least five cases) in this subset of cases.
The depressive and anxiety disorder variables included in the
present study required the participant to meet criteria for the
disorder and demonstrate clinically significant distress and/or im-
pairment. Participants with a not-otherwise-specified depressive or
anxiety diagnosis were labeled as not having the specific disorder
(n⫽44). Each diagnostic variable was labeled as present or absent
for every participant. Participants with no present diagnoses were
not excluded from analyses. The depressive disorders variable in
the current study consisted of current cases of major depressive
disorder (n⫽23) and dysthymia (n⫽7). The anxiety disorders
variable consisted of current cases of the following disorders:
social phobia (n⫽52); posttraumatic stress disorder (n⫽4);
obsessive–compulsive disorder (n⫽9); generalized anxiety dis-
order (n⫽17); specific phobia (n⫽37); and panic disorder (n⫽
3). Sixteen participants met criteria for both a current depressive
and anxiety disorder.
Life Stress Interview (LSI; Hammen et al., 1987). Life
stress was evaluated using the LSI, a semistructured interview that
assesses chronic life stress and episodic life stress. The chronic life
stress portion assessed the level of ongoing objective stress expe-
rienced by the participant in 10 domains over the past year. This
version of the LSI contains chronic life stress domains relevant to
an adolescent population, including four interpersonal domains
(close friendship, social life, romantic relationships, and family)
and six noninterpersonal domains (neighborhood, school, work,
finances, personal health, and health of close family members).
Unlike the episodic stressors, the chronic life stress domains can-
not be separated by dependence. To determine chronic life stress
scores, the interviewer used suggested general probes to elicit
relevant objective information. Subjective impressions offered by
the participant were not probed for and were disregarded if offered.
Ratings ranged in half-point intervals from 1 (ideal circumstances)
to5(most stressful circumstances), with specific behavioral an-
chors for each point on the scale. Training of interviewers involved
approximately 30 hours of didactics, matching gold standard rat-
ings, role-plays, and live observations. T1 reliability was assessed
by rating 76 intersite and intrasite audio recorded interviews.
Intraclass correlation coefficients (ICCs) ranged from .58 for
health-other to .92 for neighborhood. Averaged across all domains,
the ICC was .70.
Episodic events were probed for within each chronic life stress
domain. Interviewers obtained details concerning the description
and date of the event, the degree, duration, and impact of its
consequences, the participant’s prior experience with the event,
and availability of social support. This information was later
presented by the interviewer to an independent team of two raters
who evaluated the event on its level of contextual threat. Any
subjective impressions the participants offered about the stressful-
ness of an event, as well as any diagnostic information about the
participant, were not presented to the raters. Contextual threat was
assessed by objectively rating how much impact a particular epi-
sodic event would have for the average person in those exact
circumstances.
Ratings for episodic events were made on a 1–5 scale: 1 (min-
imal or no threat), 2 (mild threat), 3 (moderate threat), 4 (marked
1
To ensure that our results were not biased due to the behavioral
high-risk design, all analyses were also completed including sampling
weights to adjust for the differing distributions of neuroticism, sex, and
ethnicity in our sample compared to the population. There were no differ-
ences in statistical significance between results with or without the inclu-
sion of sampling weights. Thus, we followed the recommendation of
Winship and Radbill (1994) and presented the unweighted results.
7
STRESS, PERSONALITY, EMOTIONAL DISORDERS
impact with many consequences), and 5 (severe and catastrophic
negative impact). T1 reliability was assessed by rating 208 audio
recordings of life events across sites. The ICC was .82. In addition
to a contextual threat rating for episodic events, raters assessed the
dependence of the event, with 1 denoting complete independence
and 5 signifying that the event was completely caused by
the respondent. Most interpersonal events were given a rating of
three with the assumption that the event was at least in part the
result of both parties. If raters could not reach consensus, the
episode was then presented to a third rater who helped the raters
reach consensus. The ICC was .90 for the dependence ratings for
the same 208 events used to assess the reliability of the contextual
threat ratings. The episodic life stress variable in the present study
consisted of the average contextual threat ratings for all dependent
events. Dependence ratings greater than 2 were included in the
present analyses based on the assumption that independent epi-
sodic life stress as defined here could not logically be “generated”
by any type of individual difference variable. However, we do
acknowledge that there may be some examples where a person
might select themselves into an environment where independent
events are more likely to happen (i.e., not planning a proper route,
ending up in a high crime neighborhood, and getting robbed) or
where a stable negative environment might contribute to both a
person’s mood state and the likelihood of independent events
(Harkness & Stewart, 2009).
Eysenck Personality Questionnaire—Revised, Neuroticism
Scale (EPQ-R; Eysenck & Eysenck, 1975). The neuroticism
scale of the EPQ-R was the initial screening questionnaire for the
present study. It consists of 22
2
items in a yes–no format, with
higher scores indicative of higher levels of neuroticism. Coeffi-
cient alpha was .79 and coefficient omega
hierarchical
(
h
; Zinbarg,
Revelle, Yovel, & Li, 2005) was .66 (Mor et al., 2006). The
extensive construct validity for this instrument is reported in the
EPQ-R manual (Eysenck & Eysenck, 1975).
International Personality Item Pool-NEO-PI-R (IPIP-N,
2000). The neuroticism scale from the IPIP-N consists of 60
items rated on a 1–5 Likert Scale. This scale was developed to
closely correspond with the neuroticism scale from the NEO-PI-R
(Costa & McCrae, 1985). Goldberg (1999) reported that the total
scores for the two scales correlate .93. A confirmatory factor
analysis completed on one half of the T1 data confirmed six
facets and one general factor underlying the IPIP-N (Uliaszek et
al., 2009). Because of fit indices below conventional levels of
acceptable fit, the model was modified. First, the sample was
randomly split and modifications were tested in the second
subsample suggesting correlated residuals. This resulted in 21
items being cut from the original measure. This altered model
was confirmed in the second half of the data, revealing a
satisfactory fit for this revised version and an
h
estimate of .86
on the full sample (for details, see Uliaszek et al., 2009).
Therefore, the 39 item IPIP-N measure was used in the current
analyses.
The Behavioral Inhibition Scale (BIS; Carver & White,
1994). The BIS, which measures concern over and sensitivity to
negative outcomes, consists of seven items rated on a 4-point
Likert scale. Carver and White (1994) have demonstrated the
convergent and divergent validity of the BIS. The coefficient alpha
at T1 in this study was .75.
Big Five Mini-Markers Scale (Saucier, 1994). This 40-item
measure consists of eight items assessing each of the Big 5
personality traits: neuroticism, extraversion, agreeableness, con-
scientiousness, and openness/intellect. The extraversion and neu-
roticism scales were used in the present analyses. Each item is
rated on a 9-point Likert scale ranging from extremely inaccurate
to extremely accurate. Saucier (1994) reported a coefficient alpha
of .76 for the neuroticism scale and .85 for the extraversion scale.
In this study, the coefficient alphas at T1 were .80 for both
neuroticism and extraversion.
Procedures
A mass screening of potential participants was completed during
school hours. For both T1 and Time 2 (T2) assessments, SCID and
LSI interviews occurred after regular school hours throughout the
entirety of the school year. Participants were interviewed in person
for approximately 1.5 to 3 hr at each time point. Questionnaire
measures were completed either immediately after the interviews
or arrangements were made for the participant to return to com-
plete the questionnaires, usually within the next week. All ques-
tionnaires were completed at both T1 and T2 except for the
EPQ-R-N, which was used only as the screening questionnaire at
the beginning of T1.
A total of 497 participants from T1 also participated at T2.
Similar to the full T1 sample, T2 included 30.6% males (n⫽152)
and 69.4% females (n⫽345). T1 noninterpersonal chronic life
stress was the only variable in the present study to predict attrition
at T2 (B⫽.54, standard error [SE]B⫽.25, Wald
2
⫽4.42, p⬍
.05, odds ratio ⫽1.71). When each noninterpersonal chronic life
stress domain was looked at individually, the only domain to
predict attrition was the school domain (B⫽.38, SE B ⫽.13,
Wald
2
⫽8.43, p⬍.01, odds ratio ⫽1.46). Thus, participants
who experienced more school-related stress at T1 were less likely
to complete the assessment at T2.
Data Analysis
The present analyses were completed using Mplus structural
equation modeling software (Muthe´n & Muthe´n, 2007) with full
information maximum likelihood estimation. The use of this
method allowed us to include all 627 participants in analyses and
potentially corrected at least some of the biases that would ensue
from including only participants with complete data (see McArdle,
1994). Only neuroticism was modeled as a latent variable because
it was the only variable to have multiple indicators. Thus, struc-
tural equation modeling was used for all analyses including neu-
roticism. All other analyses were conventional regressions con-
ducted using Mplus in order to handle missing data using full
information maximum likelihood. A description of the models is
shown in Figure 1. First, we examined the zero-order path from T1
disorder (depressive disorders or anxiety disorders) predicting T2
stress (interpersonal chronic life stress, noninterpersonal chronic
2
The original EPQ Neuroticism Scale consists of 24 items. The item
referring to suicidality was omitted based on recommendations from the
Institutional Review Board. The item, “Do you worry about your health”
was also omitted from scoring because it failed to load on any factor in
preliminary analyses (Mor et al., 2008).
8ULIASZEK ET AL.
life stress, or episodic stress; Figure 1, Panel a). Second, we
examined the path from T1 disorder predicting T2 stress with T1
stress as a covariate (Figure 2, Panel b, path a). The covariate was
the same type of stress as the dependent variable. A significant
zero-order association of T1 disorder with T2 stress with a non-
significant path aprovided support for stress continuation, while a
significant path aprovided support for stress causation. If we
found evidence for stress generation, we then completed an addi-
tional analysis with neuroticism and/or extraversion included in
the model to test whether these two personality traits at least
partially accounted for the effect of T1 disorder on T2 stress above
and beyond T1 stress (Panel c). We also examined the unique
relationships of these two T1 personality variables predicting T2
life stress, accounting for T1 life stress, as a means of assessing a
stress causation theory for these two personality variables, as well
as these two personality traits as third variables partially explain-
ing stress continuation (see Figure 2).
Results
Means and standard deviations are displayed in Table 1. Cor-
relations among T1 interpersonal chronic life stress, noninterper-
sonal chronic life stress, the average contextual threat rating for
dependent episodic life stress, neuroticism, and extraversion are
displayed in Table 2. All correlations were significant with the
exception of the correlation between T1 extraversion and T1
episodic life stress. The T2 correlations among interpersonal
chronic life stress, noninterpersonal chronic life stress, and epi-
sodic life stress also are shown in Table 2, above the diagonal. All
T2 correlations were significant.
Neuroticism Measurement Model
A measurement model was estimated using full information
maximum likelihood to evaluate a unidimensional model of the
Figure 1. Panel a. Time 1 (T1) disorder predicting Time 2 (T2) life stress.
Panel b. T1 disorder predicting T2 life stress. T1 life stress, the same type
of stress as the dependent variable, is entered as a covariate. Panel c. T1
disorder and T1 personality predicting T2 life stress with T1 life stress
entered as a covariate. Disorder and stress variables are in square boxes
because they indicate observed variables. Personality is represented by a
circle because, in the case of neuroticism, it is a latent variable with
multiple indicators.
Figure 2. Time 1 (T1) personality predicting Time 2 (T2) life stress. T1
life stress, the same type of stress as the dependent variable, is entered as
a covariate. Stress variables are in square boxes because they indicate
observed variables. Personality is represented by a circle because, in the
case of neuroticism, it is a latent variable with multiple indicators.
Table 1
Means and Standard Deviations for All Interpersonal Chronic
Life Stress Domains, Noninterpersonal Chronic Life Stress
Domains, the Average Contextual Threat Rating of Dependent
Episodic Life Stress, Neuroticism Measures, and Extraversion at
Time 1(T1) and Time 2 (T2)
T1 Mean (SD),
n⫽697
T2 Mean (SD),
n⫽497
Interpersonal chronic life stress 2.39 (.47) 2.31 (.44)
Noninterpersonal chronic life stress 2.20 (.38) 2.14 (.34)
Episodic life stress 1.30 (.80) 1.27 (.86)
Moderate episodic life stress .90 (1.30) .44 (1.02)
Neuroticism
EPQ-R-N 11.89 (4.52)
IPIP-N 2.65 (.65)
BIS 2.90 (.58)
Big Five Mini-Markers Scale-N 4.77 (1.42)
Extraversion 5.70 (1.34)
Note. EPQ-R-N ⫽neuroticism scale of the revised Eysenck Personality
Questionnaire; IPIP-N ⫽neuroticism scale of the International Personality
Item Pool; BIS ⫽the Behavioral Inhibition Scale; SD ⫽standard devia-
tion. The range of scores is as follows: interpersonal chronic life stress
(1–5), noninterpersonal chronic life stress (1–5), episodic life stress (0–5),
moderate episodic life stress (0–5), EPQ-R-N (0–22), IPIP-N (0–5), BIS
(0–4), Big Five Mini-Markers Scale-N (0–9), extraversion (0 –9).
9
STRESS, PERSONALITY, EMOTIONAL DISORDERS
latent structure of T1 neuroticism as measured by the EPQ-R-N,
IPIP-N, BIS, and Big Five Mini-Markers N Scale. Standardized
factor loadings for each of these measures are as follows: EPQ-
R-N ⫽.68, IPIP-N ⫽.90, BIS ⫽.65, and Mini-Markers ⫽.77.
This model had excellent fit indices of
2
(2) ⫽1.34, nonsignifi-
cant, comparative fit index ⫽1.00, root mean square error of
approximation ⫽.00 (90% confidence interval [CI]: .00–.07), and
standardized root mean square residual ⫽.01.
Depression and Anxiety Predicting
Episodic Life Stress
First, we determined that there was a significant direct path
between T1 and T2 episodic life stress (standardized regression
weight ⫽.18, SE ⫽.04, p⬍.001). Next, we examined the
zero-order path between T1 depressive and anxiety disorders pre-
dicting T2 episodic life stress (see Table 3). Both relationships
were significant. We then examined T1 depressive and anxiety
disorders predicting T2 episodic life stress with T1 episodic life
stress as a covariate (see Table 4). Only the relationship between
T1 anxiety disorders and T2 episodic life stress remained signifi-
cant after accounting for T1 episodic life stress. Together these
results supported the stress causation theory for anxiety disorders
and the stress continuation theory for depressive disorders.
However, the above analyses included a high frequency of mild
stressors. Because research has often supported a specific role of
only moderate to severe stress (and not mild stress) in the predic-
tion of major depression (see Hammen, 2005; Monroe & Reid,
2009), we thought it was important to also examine the relation-
ship between depression and moderate to severe levels of stress.
This is because such results would provide stronger evidence that
stress generation might play in the role of maintenance and/or
recurrence of depression. Thus we completed additional analyses
with the focus on the generation of more moderate to severe events
(average episodic life stress rating of 2.5 or higher on a 5-point
scale). We then repeated the above analyses including only these
stressors. There was a significant direct path between T1 and T2
moderate episodic life stress (standardized regression weight ⫽
.16, SE ⫽.04, p⬍.001). Depressive disorders predicted moderate
episodic life stress after accounting for baseline moderate episodic
life stress, supporting the stress causation theory (see Table 3).
These analyses were repeated for the anxiety disorders, as well as
the personality trait analyses (see below). In these cases, there
were no differences in results between the full range of episodic
stressors and only the moderate episodic stressors. Thus, they are
not discussed further and follow-up analyses focus only on the full
range of episodic stressors for these variables.
Depression and Anxiety Predicting Chronic Life Stress
For chronic life stress, we first determined that there was a
significant zero-order association between T1 and T2 interpersonal
chronic life stress (standardized regression weight ⫽.55, SE ⫽
.03, p⬍.001) and noninterpersonal chronic life stress (standard-
ized regression weight ⫽.68, SE ⫽.02, p⬍.001). Next, we
examined the zero-order association between depressive and anx-
iety disorders and T2 chronic life stress (see Table 3). We found
that T1 depressive disorders predicted both interpersonal and non-
Table 2
Correlations Among Time 1 Interpersonal Chronic Life Stress, Noninterpersonal Chronic Life Stress, the Average Contextual Threat
Rating of Dependent Episodic Life Stress, Neuroticism, and Extraversion
Interpersonal chronic
life stress
Noninterpersonal chronic
life stress
Episodic life
stress Neuroticism
Interpersonal chronic life stress — .45
ⴱⴱⴱ
.15
ⴱⴱⴱ
—
Noninterpersonal chronic life stress .47
ⴱⴱⴱ
— .17
ⴱⴱⴱ
—
Episodic life stress .17
ⴱⴱⴱ
.16
ⴱⴱⴱ
——
Neuroticism .38
ⴱⴱⴱ
.05
ⴱⴱⴱ
.14
ⴱⴱ
—
Extraversion ⫺.22
ⴱⴱⴱ
⫺.13
ⴱⴱ
.08 ⫺.47
ⴱⴱⴱ
Note. The correlations above the diagonal represent the correlations at Time 2, N⫽627. Neuroticism is a latent variable measured by the neuroticism
scale of the revised Eysenck Personality Questionnaire, neuroticism scale of the International Personality Item Pool, Big Five Minimarkers Scale-N, and
the Behavioral Inhibition Scale.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
Table 3
Results Examining the Longitudinal Relationships Between
Time 1 Disorders and Personality Predicting Time 2 Life Stress,
N⫽627
Standardized regression
weight (SE)
Depressive disorders
Episodic life stress (all levels) .10 (.04)
ⴱ
Moderate episodic life stress .12 (.04)
ⴱⴱ
Interpersonal chronic life stress .21 (.04)
ⴱⴱⴱ
Noninterpersonal chronic life stress .20 (.04)
ⴱⴱⴱ
Anxiety disorders
Episodic life stress .16 (.04)
ⴱⴱⴱ
Moderate episodic life stress 16 (.04)
ⴱⴱⴱ
Interpersonal chronic life stress .16 (.04)
ⴱⴱⴱ
Noninterpersonal chronic life stress .16 (.04)
ⴱⴱⴱ
Neuroticism
Episodic life stress .13 (.04)
ⴱⴱ
Moderate episodic life stress .14 (.05)
ⴱⴱ
Interpersonal life stress .35 (.04)
ⴱⴱⴱ
Noninterpersonal life stress .09 (.05)
Extraversion
Episodic life stress ⫺.04 (.03)
Moderate episodic life stress ⫺.03 (.05)
Interpersonal life stress ⫺.20 (.04)
ⴱⴱⴱ
Noninterpersonal life stress ⫺.14 (.05)
ⴱⴱ
Note. SE ⫽standard error.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
10 ULIASZEK ET AL.
interpersonal chronic life stress at T2, but these relationships did
not remain significant after accounting for T1 chronic life stress
(see Table 4). Concerning anxiety disorders, we also found evi-
dence for the stress continuation theory but not the stress causation
theory in chronic life stress. Specifically, T1 anxiety disorders
significantly predicted both interpersonal and noninterpersonal
chronic life stress at T2 (see Table 3), but these relationships did
not remain significant after accounting for T1 stress (see Table 4).
Effects of Personality Variables
We first examined the zero-order association of T1 personality
with T2 life stress. These results are displayed in Table 3. T1
neuroticism significantly predicted both T2 episodic life stress and
T2 interpersonal chronic life stress. T1 extraversion also signifi-
cantly predicted T2 interpersonal and noninterpersonal chronic life
stress. We then examined these relationships while accounting for
T1 life stress. The relationships between T1 neuroticism and T2
episodic life stress, and T2 interpersonal chronic life stress, re-
mained significant after accounting for T1 life stress (see Table 5),
supporting the stress causation theory. T1 extraversion was not a
significant predictor of T2 stress after accounting for T1 stress,
supporting the stress continuation theory.
Our final set of analyses examined whether neuroticism at least
partially accounted for stress causation in the relationships be-
tween T1 depressive disorders and T2 moderate episodic life stress
(accounting for T1 moderate episodic life stress) and T1 anxiety
disorders and T2 episodic life stress (accounting for T1 episodic
life stress). Only neuroticism was examined because we did not
find evidence that extraversion was associated with T1 or T2
episodic life stress. We completed the product of coefficients test
using the program PRODCLIN (distribution of the PRODuct Con-
fidence Limits for Indirect effects; MacKinnon, Fritz, Williams, &
Lockwood, 2007). This program converts the regression weights
and standard errors from the analyses into zscores and finds
critical values based on the product of two random variables. The
result is a nonsymmetrical confidence interval around the product
of coefficients. If it includes zero, the effect is not significant
(MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002; MacK-
innon, Lockwood, & Williams, 2004). Although this test is often
used in meditational analyses, it is also appropriate for tests of
confounding or third variables (MacKinnon, Krull, & Lockwood,
2000). In these analyses, the ␣coefficient is the direct relationship
between the disorder of interest (depression or anxiety) and neu-
roticism. The coefficient is the relationship between neuroticism
and T2 life stress after accounting for the disorder of interest and
T1 life stress. Thus, results (for the product of ␣) indicate the role
of neuroticism in the relationship between disorder and T2 life
stress, after accounting for T1 life stress.
The first analysis examined T1 depressive disorders (standard-
ized regression weight ⫽.08, SE ⫽.05, ns), moderate episodic life
stress (standardized regression weight ⫽.13, SE ⫽.05, p⬍.01),
and neuroticism (standardized regression weight ⫽.11, SE ⫽.05,
p⬍.05) as predictors of T2 moderate episodic life stress. In this
analysis, T1 neuroticism was significantly correlated with T1
depression (r⫽.18, SE ⫽.04). The product of coefficients test
revealed that neuroticism partially accounted for the stress causa-
tion effect in depression (␣⫽.02, confidence interval ⫽.002–
.04). Next, we examined T1 anxiety disorders (standardized re-
gression weight ⫽.11, SE ⫽.05, p⬍.05), episodic life stress
(standardized regression weight ⫽.15, SE ⫽.04, p⬍.05), and
neuroticism (standardized regression weight ⫽.08, SE ⫽.05, ns.)
as predictors of T2 episodic life stress. In this analysis, T1 neu-
roticism was significantly correlated with T1 anxiety disorders
(r⫽.37, SE ⫽.04). The product of coefficients test revealed that
neuroticism partially accounted for stress causation in anxiety
disorders (␣ ⫽ .04, confidence interval ⫽.004–.08).
Discussion
This is the first prospective study to demonstrate stress gener-
ation in both depressive and anxiety disorders using DSM–IV
Table 5
Results Examining the Longitudinal Relationships Between Time
1 Personality Variable and Time 2 Life Stress, Accounting for
T1 Life Stress, N⫽627
a⬙b⬙
Standardized
regression
weight (SE)
Standardized
regression
weight (SE)
Neuroticism
Episodic life stress .13 (.05)
ⴱ
.16 (.04)
ⴱⴱⴱ
Moderate episodic life stress .12 (.05)
ⴱ
.14 (.05)
ⴱⴱⴱ
Interpersonal chronic life stress .15 (.04)
ⴱⴱⴱ
.49 (.04)
ⴱⴱⴱ
Extraversion
Interpersonal chronic life stress ⫺.06 (.04) .54 (.03)
ⴱⴱⴱ
Noninterpersonal chronic life stress ⫺.01 (.03) .69 (.02)
ⴱⴱⴱ
Note. In the column to the left, a⬘represents the relationship between T1
personality and T2 life stress, while accounting for T1 life stress (see
Figure 2, Path a⬘). b⬘represents the relationship between T1 life stress and
T2 life stress within the specified relationship.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
Table 4
Results Examining the Longitudinal Relationships Between Time
1 Disorder and Time 2 Life Stress, Accounting for T1 Life
Stress, N⫽627
ab
Standardized
regression
weight (SE)
Standardized
regression
weight (SE)
Depressive disorders
Episodic life stress .08 (.04) .16 (.04)
ⴱⴱⴱ
Moderate episodic life stress .10 (.04)
ⴱ
.15 (.04)
ⴱⴱⴱ
Interpersonal chronic life stress .05 (.04) .54 (.03)
ⴱⴱⴱ
Noninterpersonal chronic life stress .05 (.03) .68 (.03)
ⴱⴱⴱ
Anxiety disorders
Episodic life stress .14 (.04)
ⴱⴱⴱ
.16 (.04)
ⴱⴱⴱ
Moderate episodic life stress .15 (.04)
ⴱⴱⴱ
.15 (.04)
ⴱⴱⴱ
Interpersonal chronic life stress ⫺.02 (.04) .54 (.03)
ⴱⴱⴱ
Noninterpersonal chronic life stress ⫺.004 (.03) .69 (.02)
ⴱⴱⴱ
Note. In the column to the left, arepresents the relationship between T1
disorder and T2 life stress, while accounting for T1 life stress (see Figure 1
Panel b, Path a). brepresents the relationship between T1 life stress and T2
life stress within the specified relationship.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
11
STRESS, PERSONALITY, EMOTIONAL DISORDERS
diagnoses and an interview-based assessment of stress. In addition,
we believe this is the first study to directly examine both the stress
continuation and stress causation theories of stress generation in
the same study. These results also examined the role of neuroti-
cism and extraversion in stress generation, with neuroticism par-
tially accounting for episodic stress generation in both depressive
and anxiety disorders.
Our analyses supported the stress causation theory when exam-
ining stress generation in depressive disorders with moderate to
severe episodic life events. Thus, something specific to depression
at baseline, apart from elevated concurrent stress, has a predictive
relationship to later moderate to severe episodic stressors. One
such variable that we found to be important in this relationship is
elevated neuroticism. Neuroticism partially accounted for the stress
generation relationship between depression and moderate episodic
stressors, even after accounting for baseline stress. These results have
both theoretical and clinical implications. First, these results show
that, relative to the nondepressed, people with depression are at an
elevated risk for future dependent episodic stress of moderate to
severe intensity. These types of stressful life events may well lead to
continued depressive symptoms and future recurrence of depressive
episodes (e.g., Rudolph et al., 2009). This provides one possible
explanation for the high recurrence rate of depression (e.g., Boland
& Keller, 2009) and for subclinical depressive symptoms between
episodes of depression (Judd et al., 1998). Second, these findings
suggest that clinical interventions should target stress reduction as
a means of preventing future depressive episodes.
It is important to note that a few other studies have found a
predictive relationship between depression and episodic stress,
even after accounting for baseline stress (e.g., Harkness & Stewart,
2009; Holahan et al., 2005; Rudolph et al., 2009), that is, support-
ing the stress causation theory. In our sample, this was only
replicated with moderate to severe episodic life stress. There are
several possible explanations for why we did not replicate these
findings for analyses including all levels of episodic life stress.
First, our analyses did not separate interpersonal from noninter-
personal episodic life stress (although we did for chronic life
stress). Several studies have found stress generation for depression
to be stronger for interpersonal episodic life stress (e.g., Rudolph
et al., 2000; Shih, 2006). Second, we used more rigorous method-
ology than many other studies, including clinically significant
diagnoses for our disorder variables and an interview-based mea-
sure of life stress. It is possible that more studies would have failed
to support stress generation in depression if using such stringent
criteria.
The findings on episodic stress generation in anxiety disorders
are an exciting addition to the stress generation literature, with this
evidence demonstrating that the phenomenon is not specific to
depression. Because we found evidence of stress generation in
anxiety disorders, we are led to believe that there is something
about the characteristics of anxiety disorders that lead to elevated
levels of episodic stress. We found that high neuroticism is one
such characteristic, partially accounting for the relationship be-
tween T1 anxiety disorders and T2 episodic life stress, after
accounting for T1 episodic life stress. However, neuroticism did
not completely explain stress generation in anxiety. Another im-
portant characteristic to examine might be the interpersonal pro-
cesses similar to what is seen in depression. Much research points
to an interpersonal theory of stress generation in depression, with
a focus on interpersonal style and interpersonal stressors (e.g.,
Eberhart & Hammen, 2009; Flynn, Kecmanovic, & Alloy, 2010),
and how this process may lead to future depressive episodes
(Rudolph et al., 2009). Future studies examining stress generation
in anxiety disorders might examine negative interpersonal charac-
teristics as variables that might, at least in part, account for this
relationship.
A recent review article has noted the importance of examining
chronic life stress in stress generation research (Liu & Alloy,
2010). We found evidence for stress continuation theory, but not
for stress causation, for both interpersonal and noninterpersonal
chronic life stress in both depressive and anxiety disorders. These
results demonstrate that, although characteristics of depressive and
anxiety disorders do not appear to be causal agents in the gener-
ation of chronic life stress, those with these disorders are prone to
future elevated levels of chronic life stress nonetheless. This is
clinically and theoretically important when thinking about the
developmental course and prognosis of those with depressive and
anxiety disorders. Similar to a scar effect, we expect those with a
history of a depressive or anxiety disorder would continue to
experience elevated levels of chronic life stress relative to those
without such a history. It is possible that we did not find support
for the stress causation theory with chronic life stress because it is
by its nature enduring and so it may be more difficult to detect
changes. In fact, results supported the high stability of both inter-
personal and noninterpersonal chronic life stress.
As mentioned above, neuroticism was a significant third vari-
able in stress generation for depressive and anxiety disorders.
Results looking solely at neuroticism also supported the stress
causation theory for both episodic life stress and interpersonal
chronic life stress. In other words, T1 neuroticism predicted both
types of stress at T2, even after accounting for baseline stress.
Taken together, these findings demonstrate that being high in
neuroticism, at least in late adolescence, is a risk factor for later
chronic and episodic stress. We can at least partially attribute this
continued elevation in stress to specific characteristics or corre-
lated behaviors of a person high in neuroticism. For example,
increased emotional sensitivity may lead a person to actions that
interfere with social and romantic relationships or school and work
performance.
Extraversion was not associated with a significant stress causa-
tion effect for any type of stress. However, T1 extraversion did
predict both T2 interpersonal and noninterpersonal chronic life
stress, supporting the stress continuation theory. Support of this
theory does provide evidence that those displaying the withdrawn,
nonassertive behavior characteristic of introversion are likely to
have continued elevated chronic life stress in the future, if only due
to the cross-sectional relationship between chronic life stress and
introversion and the temporal stability of chronic life stress.
There are several limitations of the current study. First, because
our sample consisted entirely of late adolescents and because we
present several new findings, our results need to be replicated in
additional samples before firm conclusions can be drawn. This is
also pertinent to the results concerning stress generation in anxiety
disorders because this area of study is quite new. Second, there
was a large difference in the number of participants meeting
criteria for a depressive disorder (n⫽28) versus an anxiety
disorder (n⫽92). The resulting difference in power was another
possible reason why the stress causation theory was supported for
12 ULIASZEK ET AL.
the full range of episodic stressors in anxiety disorders, but not in
depressive disorders. In this regard, however, we also note that the
effect size estimates for depressive disorders were consistently
smaller than those for the anxiety disorders suggesting that power
alone cannot entirely explain the differences in results between
depressive disorders and anxiety disorders. Third, participants
reported an average of two dependent episodic life events in T1
(M⫽1.90, SD ⫽1.63) and 1.5 in T2 (M⫽1.54, SD ⫽1.48). One
possible reason for the decrease is the socialization of the partic-
ipants to the LSI; they may have learned that reporting fewer
episodic events results in a shorter interview. In addition, attrition
was predicted by chronic life stress in the school domain suggest-
ing that those having higher school stress were also likely to drop
out of the study. A fourth limitation is that we only tested a small
set of possible third variables. It is possible that there are other
third variables with some of them having even larger effects than
the ones we examined. A final limitation is related to the approx-
imate one-year time lag between assessments. This time lag was a
matter of convenience; any shorter period of time would unduly
tax the participants, whereas a longer lag would make it too
difficult to recall the stress since the previous interview. Thus, it is
possible that the results would be different if there were more or
less time between assessments.
In conclusion, we believe that this study provides some of the
most comprehensive evidence to date on stress generation. We
examined the effects of both depression and anxiety disorders on
both chronic and episodic life stress. To our knowledge, ours is the
first study to distinguish between and test both the stress contin-
uation and stress causation theories of stress generation. Moreover,
we examined the role of normal personality traits in stress gener-
ation, with results showing that neuroticism partially accounted for
the predictive relationship between depressive disorders and mod-
erate episodic life stress, as well as the relationship between
anxiety disorders and episodic life stress. Finally, this study pro-
vides new evidence demonstrating that stress generation is not
specific to depressive disorders, but also occurs in those with
anxiety disorders and elevated neuroticism.
References
American Psychiatric Association. (2004). Diagnostic and statistical man-
ual of mental disorders (4th ed.) – Text Revision. Washington, DC:
American Psychiatric Association.
Boland, R. J., & Keller, M. B. (2009). Course and outcome of depression.
In I. H. Gotlib & C. L. Hammen (Eds.). Handbook of depression (2nd
ed., pp. 23–43). New York, NY: Guilford Press.
Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral
activation, and affective responses to impending reward and punishment:
The BIS/BAS scales. Journal of Personality and Social Psychology, 67,
319–333. doi:10.1037/0022-3514.67.2.319
Chun, C. A., Cronkite, R. C., & Moos, R. H. (2004). Stress generation in
depressed patients and community controls. Journal of Social and Clin-
ical Psychology, 23, 390–412. doi:10.1521/jscp.23.3.390.35453
Clark, L. A., Watson, D., & Mineka, S. (1994). Temperament, personality,
and the mood and anxiety disorders. Journal of Abnormal Psychology,
103, 103–116. doi:10.1037/0021-843X.103.1.103
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educa-
tional and Psychological Measurement, 20, 37–46. doi:10.1177/
001316446002000104
Cole, D. A., Girgus, J., Paul, G., & Nolen–Hoeksema, S. (2004). Stress
exposure and stress generation in child and adolescent depression: A
latent state-trait-error approach to longitudinal analyses. Journal of
Abnormal Psychology, 115, 40–51. doi:10.1037/0021-843X.115.1.40
Costa, P. T., Jr., & McCrae, R. R. (1985). The NEO Personality Inventory
manual. Odessa, FL: Psychological Assessment Resources.
Costa, P. T., Jr., Terracciano, A., & McCrae, R. R. (2001). Gender
differences in personality traits across cultures: Robust and surprising
findings. Journal of Personality and Social Psychology, 81, 322–331.
doi:10.1037/0022-3514.81.2.322
Daley, S. E., Hammen, C., Burge, D., Davila, J., Paley, B., Lindberg, N.,
& Herzberg, D. S. (1997). Predictors of the generation of episodic stress:
A longitudinal study of late adolescent women. Journal of Abnormal
Psychology, 106, 251–259. doi:10.1037/0021-843X.106.2.251
Daley, S. E., Hammen, C., & Rao, U. (2000). Predictors of first onset and
recurrence of major depression in young women during the 5 years
following high school graduation. Journal of Abnormal Psychology,
109, 525–533. doi:10.1037/0021-843X.109.3.525
Eberhart, N. K., & Hammen, C. L. (2009). Interpersonal predictors of
stress generation. Personality and Social Psychology Bulletin, 35, 544–
556. doi:10.1177/0146167208329857
Eysenck, H. J., & Eysenck, S. B. (1975). Eysenck Personality Question-
naire manual. San Diego, CA: EdITS.
First, M. B., Spitzer, R. L., Gibbon, M., & Williams, J. B. W. (2002).
Structured Clinical Interview for DSM–IV–TR Axis I Disorders, re-
search version, patient edition with psychotic screen. New York, NY:
Biometrics Research, New York State Psychiatric Institute.
Flynn, M., Kecmanovic, J., & Alloy, L. B. (2010). An examination of
integrated cognitive-interpersonal vulnerability to depression: The role
of rumination, perceived social support, and interpersonal stress gener-
ation. Cognitive Therapy and Research, 34, 456–466. doi:10.1007/
s10608-010-9300-8
Goldberg, L. R. (1999). A broad-bandwidth, public domain, personality
inventory measuring the lower-level facets of several five-factor models.
In I. Mervielde, I. Deary, F. De Fruyt, & F. Ostendorf (Eds.), Personality
psychology in Europe (Vol. 7, pp. 7–28). Tilburg, The Netherlands:
Tilburg University Press.
Hammen, C. (1991). Generation of stress in the course of unipolar depres-
sion. Journal of Abnormal Psychology, 100, 555–561. doi:10.1037/
0021-843X.100.4.555
Hammen, C. (2005). Stress and depression. Annual Review of Clinical
Psychology, 1, 293–319. doi:10.1146/annurev.clinpsy.1.102803.143938
Hammen, C., Adrian, C., Gordon, D., Burge, D., Jaenicke, C., & Hiroto, D.
(1987). Children of depressed mothers: Maternal strain and symptom
predictors of dysfunction. Journal of Abnormal Psychology, 96, 190–
198. doi:10.1037/0021-843X.96.3.190
Hammen, C., Davila, J., Brown, G., Ellicott, A., & Gitlin, M. (1992).
Psychiatric history and stress: Predictors of severity of unipolar depres-
sion. Journal of Abnormal Psychology, 101, 45–52. doi:10.1037/0021-
843X.101.1.45
Hankin, B. L., Abramson, L. Y., Miller, N., & Haeffel, G. J. (2004).
Cognitive vulnerability-stress theories of depression: Examining affec-
tive specificity in the prediction of depression versus anxiety in three
prospective studies. Cognitive Therapy and Research, 28, 309–345.
doi:10.1023/B:COTR.0000031805.60529.0d
Harkness, K. L., & Stewart, J. G. (2009). Symptom specificity and the
prospective generation of life events in adolescence. Journal of Abnor-
mal Psychology, 118, 278–287. doi:10.1037/a0015749
Hauner, K., Zinbarg, R., & Revelle, W. (2011). The effects of oversampling
on directly and indirectly oversampled predictors. Manuscript in prep-
aration.
Hayward, C., Killen, J. D., Kraemer, H. C., & Taylor, C. B. (2000).
Predictors of panic attacks in adolescents. Journal of the American
Academy of Child & Adolescent Psychiatry, 39, 207–214. doi:10.1097/
00004583-200002000-00021
Heering, E. A., & Kring, A. M. (2007). Interpersonal consequences of
13
STRESS, PERSONALITY, EMOTIONAL DISORDERS
social anxiety. Journal of Abnormal Psychology, 116, 125–134. doi:
10.1037/0021-843X.116.1.125
Hirschfeld, R. M., Klerman, G. L., Lavori, P., Keller, M. B., Griffith, P., &
Coryell, W. (1989). Premorbid personality assessments of first onset of
major depression. Archives of General Psychiatry, 46, 345–350.
Holahan, C. J., Moos, R. H., Holahan, C. K., Brennan, P. L., & Schutte,
K. K. (2005). Stress generation, avoidance coping, and depressive symp-
toms: A 10-year model. Journal of Consulting and Clinical Psychology,
73, 658–666. doi:10.1037/0022-006X.73.4.658
International Personality Item Pool. (2001). A scientific collaboratory for
the development of advanced measures of personality traits and other
individual differences Retrieved from http://ipip.ori.org/
Joiner, T. E., Jr., Wingate, L. R., Gencoz, T., & Gencoz, F. (2005). Stress
generation in depression: Three studies on its resilience, possible mech-
anism, and symptom specificity. Journal of Social & Clinical Psychol-
ogy, 24, 236–253. doi:10.1521/jscp.24.2.236.62272
Judd, L. L., Akiskal, H. S., Maser, J. D., Zeller, P. J., Endicott, J., Coryell,
W.,...Keller, M. B. (1998). A prospective 12-year study of subsyn-
dromal and syndromal depressive symptoms in unipolar major depres-
sive disorders. Archives of General Psychiatry, 55, 694–700. doi:
10.1001/archpsyc.55.8.694
Kendler, K. S., Gardner, C. O., & Prescott, C. A. (2003). Personality and
the experience of environmental adversity. Psychological Medicine, 33,
1193–1202. doi:10.1017/S0033291703008298
Kendler, K. S., Kuhn, J., & Prescott, C. A. (2004). The interrelationship of
neuroticism, sex, and stressful life events in the prediction of episodes of
major depression. American Journal of Psychiatry, 161, 631–637. doi:
10.1176/appi.ajp.161.4.631
Kendler, K. S., Neale, M. C., Kessler, R. C., Heath, A. C., & Eaves, L. J.
(1993). A longitudinal twin study of personality and major depression in
women. Archives of General Psychiatry, 50, 853–862.
Kessler, R. C., Chui, W. T., Demler, O., & Walters, E. E. (2005). Preva-
lence, severity, and comorbidity of 12-month DSM–IV disorders in the
National Comorbidity Survey Replication. Archives of General Psychi-
atry, 62, 617–709. doi:10.1001/archpsyc.62.6.617
Klein, D. N., Durbin, C. E., & Shankman, S. A. (2009). Personality and
mood disorders. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of
depression (2nd ed., pp. 93–112). New York, NY: Guilford Press.
Krueger, R. F. (1999). Personality traits in late adolescence predict mental
disorders in early adulthood: A prospective-epidemiological study. Jour-
nal of Personality, 67, 39–65. doi:10.1111/1467-6494.00047
Liu, R. T., & Alloy, L. B. (2010). Stress generation in depression: A
systematic review of the empirical literature and recommendations for
future study. Clinical Psychology Review, 30, 582–593. doi:10.1016/
j.cpr.2010.04.010
MacKinnon, D. P., Fritz, M. S., Williams, J., & Lockwood, C. M. (2007).
Distribution of the product confidence limits for the indirect effect:
Program PRODCLIN. Behavior Research Methods, 39, 384–389. doi:
10.3758/BF03193007
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence
of the mediation, confounding, and suppression effect. Prevention Sci-
ence, 1, 173–181. doi:10.1023/A:1026595011371
MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., &
Sheets, V. (2002). A comparison of methods to test mediation and other
intervening variable effects. Psychological Methods, 7, 83–104. doi:
10.1037/1082-989X.7.1.83
MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence
limits for the indirect effect: Distribution of the product and resampling
methods. Multivariate Behavioral Research, 39, 99–128. doi:10.1207/
s15327906mbr3901_4
Magnus, K., Diener, E., Fujita, F., & Pavot, W. (1993). Extraversion and
neuroticism as predictors of objective life events: A longitudinal anal-
ysis. Journal of Personality and Social Psychology, 65, 1046–1053.
doi:10.1037/0022-3514.65.5.1046
McArdle, J. J. (1994). Structural factor analysis experiments with incom-
plete data. Multivariate Behavioral Research, 29, 409–454. doi:
10.1207/s15327906mbr2904_5
McGonagle, K. A., & Kessler, R. C. (1990). Chronic stress, acute stress,
and depressive symptoms. American Journal of Community Psychology,
18, 681–706. doi:10.1007/BF00931237
Mineka, S., Watson, D. W., & Clark, L. A. (1998). Psychopathology:
Comorbidity of anxiety and unipolar mood disorders. Annual Reviews of
Psychology, 49, 377–412.
Monroe, S. M., & Reid, M. W. (2009). Life stress and major depression.
Current Directions in Psychological Science, 18, 68–72. doi:10.1111/
j.1467-8721.2009.01611.x
Monroe, S. M., Slavich, G. M., & Georgiades, K. (2009). The social
environment and life stress in depression. In I. H. Gotlib, & C. L.
Hammen, (Eds.), Handbook of depression (2nd ed., pp. 340–360). New
York, NY: Guilford Press.
Mor, N., Zinbarg, R. E., Craske, M., Mineka, S., Uliaszek, A. A., Griffith,
J., . . . Waters, A. (2008). Factor structure and factorial invariance of the
EPQ-R Neuroticism Scale in high school juniors. Journal of Personality
Assessment, 90, 66–75. doi:10.1080/00223890701693777
Muthe´n, L. K., & Muthe´n, B. O. (2007). Mplus user’s guide (5th ed.). Los
Angeles, CA: Muthe´n & Muthe´n.
Ormel, J., Oldehinkel, A. J., & Brilman, E. I. (2001). The interplay and
etiological continuity of neuroticism, difficulties, and life events in the
etiology of major and subsyndromal, first and recurrent depressive
episodes in later life. American Journal of Psychiatry, 158, 885–891.
Reich, J., Noyes, R., Hirschfeld, R., Coryell, W., & O’Gorman, T. (1987).
State and personality in depressed and panic patients. American Journal
of Psychiatry, 144, 181–187.
Rudolph, K. D. (2008). Developmental influences on interpersonal stress
generation in depressed youth. Journal of Abnormal Psychology, 117,
673–679. doi:10.1037/0021-843X.117.3.673
Rudolph, K. D., Flynn, M., Abaied, J. L., Groot, A., & Thompson, R.
(2009). Why is past depression the best predictor of future depression?
Stress generation as a mechanism of depression continuity in girls.
Journal of Clinical Child and Adolescent Psychology, 38, 473–485.
doi:10.1080/15374410902976296
Rudolph, K. D., Hammen, C., Burge, D., Lindberg, N., Herzberg, D., &
Daley, S. E. (2000). Toward an interpersonal life-stress model of de-
pression: The developmental context of stress generation. Development
and Psychopathology, 12, 215–234. doi:10.1017/S0954579400002066
Saucier, G. (1994). Mini-markers: A brief version of Goldberg’s unipolar
Big-Five markers. Journal of Personality Assessment, 63, 506–516.
doi:10.1207/s15327752jpa6303_8
Saudino, K. J., Pederson, N. L., Lichtenstein, P., McClearn, G. E., &
Plomin, R. (1997). Can personality explain genetic influences on life
events? Journal of Personality and Social Psychology, 72, 196–206.
doi:10.1037/0022-3514.72.1.196
Shih, J. (2006). Sex differences in stress generation: An examination of
sociotropy/autonomy, stress, and depressive symptoms. Personality and
Social Psychology Bulletin, 32, 434–446. doi:10.1177/0146167205282739
Trull, T. J., & Sher, K. J. (1994). Relationship between the five-factor model of
personality and Axis I disorders in a nonclinical sample. Journal of Abnormal
Psychology, 103, 350–360. doi:10.1037/0021-843X.103.2.350
Uliaszek, A. A., Hauner, K. K. Y., Zinbarg, R. E., Craske, M. G., Mineka,
S., Griffith, J., & Epstein, A. (2009). An examination of content overlap
and disorder-specific predictions in the associations of neuroticism with
anxiety and depression. Journal of Research in Personality, 43, 785–
794. doi:10.1016/j.jrp.2009.05.009
Uliaszek, A. A., Zinbarg, R. E., Mineka, S., Craske, M. E., Sutton, J. M.,
Griffith, . . . Hammen, C. (2010). The role of personality in the stress-
depression and stress-anxiety relationships. Anxiety, Stress, and Coping,
23, 363–381. doi:10.1080/10615800903377264
Watson, D., Gamez, W., & Simms, L. J. (2005). Basic dimensions of
14 ULIASZEK ET AL.
temperament and their relations to anxiety and depression: A symptom-
based perspective. Journal of Research in Personality, 39, 46–66.
Wheaton, B. (1994). Sampling the stress universe. In W. R. Avison, & I. H.
Gotlib (Eds.), Stress and mental health: Contemporary issues and pros-
pects for the future (pp. 43–70). New York, NY: Plenum Press.
Winship, C., & Radbill, L. (1994). Sampling weights and regression
analysis. Sociological Methods and Research, 23, 230–257. doi:
10.1177/0049124194023002004
Zinbarg, R. E., Mineka, S., Craske, M. G., Griffith, J. W., Sutton, J., Rose,
R.D.,...Waters, A. M. (2010). The Northwestern-UCLA Youth Emo-
tion Project: Associations of cognitive vulnerabilities, neuroticism and
gender with past diagnoses of emotional disorders in adolescents. Be-
haviour Research and Therapy, 48, 347–358. doi:10.1016/
j.brat.2009.12.008
Zinbarg, R. E., Revelle, W., Yovel, I., & Li, W. (2005). Cronbach’s ␣,
Revelle’s , and McDonald’s h: Their relations with each other and
two alternative conceptualizations of reliability. Psychometrika, 70,
123–133. doi:10.1007/s11336-003-0974-7
Received March 30, 2010
Revision received August 10, 2011
Accepted August 11, 2011 䡲
15
STRESS, PERSONALITY, EMOTIONAL DISORDERS
A preview of this full-text is provided by American Psychological Association.
Content available from Journal of Abnormal Psychology
This content is subject to copyright. Terms and conditions apply.
