Affective and Self-Esteem Instability in the Daily Lives of People With Generalized Social Anxiety Disorder

Abstract

Research on affect and self-esteem in social anxiety disorder (SAD) has focused on trait or average levels, but we know little about the dynamic patterns of these experiences in the daily lives of people with SAD. We asked 40 adults with SAD and 39 matched healthy controls to provide end-of-day reports on their affect and self-esteem over 2 weeks. Compared to healthy adults, participants with SAD exhibited greater instability of negative affect and self-esteem, though the self-esteem effect was driven by mean-level differences. The SAD group also demonstrated a higher probability of acute changes in negative affect and self-esteem (i.e., from one assessment period to the next), as well as difficulty maintaining positive states and improving negative states (i.e., dysfunctional self-regulation). Our findings provide insights on the phenomenology of SAD, with particular attention to the temporal dependency, magnitude of change, and directional patterns of psychological experiences in everyday life.

Full text

Affective and Self-Esteem Instability in the Daily Lives of People
with Generalized Social Anxiety Disorder
Antonina S. Farmer and
Department of Psychology, George Mason University
Todd B. Kashdan
Department of Psychology, George Mason University
Abstract
Research on affect and self-esteem in social anxiety disorder (SAD) has focused on trait or
average levels, but we know little about the dynamic patterns of these experiences in the daily
lives of people with SAD. We asked 40 adults with SAD and 39 matched healthy controls to
provide end-of-day reports on their affect and self-esteem over two weeks. Compared to healthy
adults, participants with SAD exhibited greater instability of negative affect and self-esteem,
though the self-esteem effect was driven by mean level differences. The SAD group also
demonstrated a higher probability of acute changes in negative affect and self-esteem (i.e., from
one assessment period to the next), as well as difficulty maintaining positive states and improving
negative states (i.e., dysfunctional self-regulation). Our findings provide insights on the
phenomenology of SAD, with particular attention to the temporal dependency, magnitude of
change, and directional patterns of psychological experiences in everyday life.
Keywords
social anxiety; emotion; self-esteem; emotional control; individual differences
People with generalized social anxiety disorder (SAD) experience significant impairment in
quality of life and, specifically, in the social domain (Wittchen & Beloch, 1996). This
condition is marked by pervasive fears of being evaluated by others and avoidance of social
situations that may lead to scrutiny or rejection (American Psychiatric Association, 2000).
Ample research has shown that people with SAD experience elevated levels of negative
affect (NA; e.g., Watson, Clark, & Carey, 1988), attenuated positive affect (PA; Kashdan,
2007), and low self-esteem (SE; e.g., Leary, Kowalski, & Campbell, 1988), but we know
little about the quality and patterns of affective and SE fluctuations in their daily lives. In the
current study, we investigated whether affective or SE instability plays a role in the
phenomenology of SAD.
All people experience some variability in their affect and self-esteem, as fluctuations in
emotions (Keltner & Kring, 1998) and self-esteem (Leary & Downs, 1995) are integral to
Correspondence concerning this article should be addressed to Todd B. Kashdan, Department of Psychology, MS 3F5, George Mason
University, Fairfax, VA 22030. tkashdan@gmu.edu.
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effectively navigating social relationships. For example, a decrease in self-esteem alerts us
to the likelihood that we might make a negative impression on others, which could lead to
rejection (Leary, Haupt, Strausser, & Chokel, 1998). However, some people are prone to
affective instability (frequent and/or severe shifts in affect) or self-esteem instability
(frequent and/or severe shifts in self-views). Excessive fluctuation in self-esteem may
represent dysfunction in mechanisms aimed at maintaining a degree of stability in these
psychological states (e.g., Carver & Scheier, 2001; Tesser, 1988). Examining the temporal
patterns of psychological states in SAD may provide crucial information about underlying
regulatory functioning in this condition.
Since frequent, unpredictable emotional changes tend to be distressing (Craske, Brown,
Meadows, & Barlow, 1995), it is not surprising that people with affective instability are at
greater risk for developing disorders (Koenigsberg, 2010). Excessive affective instability has
been found in patients with borderline personality disorder (e.g., Ebner-Priemer et al., 2007),
major depressive disorder (e.g., Thompson et al., 2012), and bulimia nervosa (Anestis et al.,
2010). The deleterious effects of instability are not limited to NA fluctuations. Instability of
PA has been linked to psychological symptoms (e.g., Gruber, Kogan, Quoidbach, & Mauss,
2013). Only two studies have investigated mood instability in anxiety disorders using
experience-sampling methodology (ESM; Larson & Csikszentmihalyi, 1983), each
suggesting that patients with anxiety disorders experience greater NA instability (Bowen,
Baetz, Hawkes, & Bowen, 2006; Bowen, Clark, & Baetz, 2004). However, these studies
made no comparisons between anxiety disorder diagnoses, used one-item affect scales, and
failed to address mean affect ratings as a covariate (see Kashdan, Uswatte, Steger, & Julian,
2006).
For people with generalized SAD, affective instability might be particularly important,
because their source of intense distress (i.e., social interaction) is ubiquitous in daily life.
The affective profile of SAD is distinct from other anxiety disorders, with amplified levels
of NA accompanied by deficient PA (e.g., T. A. Brown, 2007; Hughes et al., 2006) that
cannot be attributed to comorbidity with depressive disorders (Kashdan, 2007). Notably,
ESM studies (e.g., Kashdan, Julian, Merritt, & Uswatte, 2006; Kashdan & Steger, 2006) that
support these global self-report findings have used samples with analogue problems instead
of SAD diagnoses. To date, researchers have ignored instability, which may clarify whether
PA deficits reflect consistently dampened PA experiences (PA generally low, with little
improvement) or greater PA instability (high PA but short lived and infrequent). In the
present study, we investigated the level and stability of PA and NA in healthy adults and
those with SAD diagnoses.
Dominant models of SAD highlight the role of emotional reactivity, in part due to biased
processing of social situations (Clark & Wells, 1995; Rapee & Heimberg, 1997).
Consequently, we expected the SAD group to display greater NA instability in daily life.
Considering prior studies that found no differences in PA instability in anxiety disorders
(e.g., Bowen et al., 2006) and stable, low PA levels over three months in socially anxious
people (Kashdan & Breen, 2008), we expected no group differences in PA instability. In
analyses controlling for average levels of affect, we addressed the parsimonious explanation
that any effects might be a function of stable emotional disturbances.
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Although no studies to date have used ESM to study self-esteem experiences in people with
SAD over time, several dominant models of SAD (Clark & Wells, 1995; Moscovitch, 2009)
describe the role of low and, specifically, unstable self-esteem in the phenomenology of
SAD. In particular, Clark and Wells (1995) suggested that instability of self-esteem might
distinguish SAD from the stable, low self-esteem in people with depression. Related
research provides preliminary evidence that self-esteem instability is worthy of investigation
in people with SAD. First, on global and implicit measures, socially anxious people tend to
have less-certain self-concepts, i.e., they report being less confident in and take longer in
describing their personality traits (Stopa, Brown, Luke, & Hirsch, 2010; Wilson & Rapee,
2006). Second, ESM research has shown that high self-esteem variability predicted greater
focus on threatening aspects of social interactions (Waschull & Kernis, 1996), greater social
anxiety (Kernis, Grannemann, & Barclay, 1992), more social avoidance, and fewer social
interaction (Oosterwegel, Field, Hart, & Anderson, 2001)—all features commonly seen in
patients with SAD (Leary et al., 1988).
In addition to studying instability, researchers can examine the quality of changes in
reported experiences, particularly their amplitude and direction. The likelihood of acute
changes in affect (i.e., large shifts in amplitude from one occasion to the next) and the
patterns of direction of shifts (i.e., shifting toward more positive or more negative valence)
have been of particular interest to researchers studying borderline personality disorder (e.g.,
Ebner-Priemer et al., 2007; Trull et al., 2008). Little consideration has been given to acute
changes and directional shifts in other psychological disorders. Based on theories of hyper-
reactivity and emotion regulation deficits in SAD, we expected to find a higher probability
of acute changes in NA and self-esteem (but not PA), and a dysfunctional pattern of affect
shifts in participants with SAD.
Although affect changes from positive to negative states tend to be distressing (Craske et al.,
1995), the ability to shift from negative states to positive states may be a sign of effective
emotion regulation. A growing body of literature supports emotion regulation difficulties as
a feature and possible maintenance factor of SAD (e.g., Goldin, Manber, Hakimi, Canli, &
Gross, 2009; Kashdan & Steger, 2006). In particular, people with SAD tend to overuse the
emotion regulation strategies of avoidance and suppression, which tend to be ineffective for
altering negative emotions (Campbell-Sills, Barlow, Brown, & Hofmann, 2006) and
contribute to deficits in positive experiences (Farmer & Kashdan, 2012; Kashdan & Steger,
2006). Rigid reliance on pushing emotions away and having difficulty using more adaptive
strategies (e.g., Werner, Goldin, Ball, Heimberg, & Gross, 2011) suggest that people with
SAD may have difficulty reducing negative affect. Consequently, we expected participants
with SAD to experience smaller positive shifts (i.e., toward more positive valence) when in
negatively valenced states.
People with SAD may also have a harder time maintaining high PA states. Prior research
found that socially anxious people tend to suppress positive emotions more frequently in
daily life than less anxious peers (Farmer & Kashdan, 2012). This strategy is in conflict with
more adaptive emotion regulation strategies that intensify and prolong positive experiences
(Tugade & Fredrickson, 2006). Thus, people with SAD may more rapidly shift to relatively
negative affect states after the rare days on which they experience predominantly positive
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valence. Consistent with this idea, we expected SAD participants to experience more
negative shifts (i.e., toward more negative valence) after being in positively valenced states.
Understanding emotional dysregulation patterns in the daily lives of people with SAD may
offer insights into the source of functional impairment in this population.
In the present investigation, we used a two-week daily diary ESM to examine affective and
self-esteem instability in people with generalized SAD compared to healthy adults. To
capture instability, a measure must incorporate the amplitude, frequency, and temporal
dependency of changes in experiences over time (Larsen, 1987). One such measure is the
mean squared successive differences (MSSD; von Neumann, Kent, Bellinson, & Hart,
1941), calculated by aggregating the degree of fluctuation between each time point and the
time point immediately preceding it. Variations of this approach that further improve the
measurement include correcting for missing data and varying durations between assessments
(Jahng, Wood, & Trull, 2008). MSSD and its variations have been applied to the study of
affective instability in a number of clinical populations for which labile affect has been
theoretically or clinically problematic (e.g., Anestis et al., 2010; Bowen et al., 2006).
In the present study, we used a two-week daily diary ESM to investigate the temporal
dynamics of affect and self-esteem in people with generalized SAD compared to healthy
adults. We hypothesized that the SAD group would experience (a) lower mean levels of PA
and self-esteem, and higher mean levels of NA; (b) greater NA and self-esteem instability,
but no differences in PA instability; (c) higher probability of acute changes in NA and self-
esteem, but not PA; and (d) more negative shifts from positively valenced affect and less
positive shifts from more negatively valenced affect. To test specificity, we examined
whether group differences remained after accounting for differences in mean intensity levels
and the presence of comorbid depressive and anxiety conditions. Additionally, we explored
the relationship of instability measures with each other and with global measures of
symptom severity and well-being.
Method
Participants
Our sample included 86 adults (53 females) from the Northern Virginia community, of
whom 43 participants were diagnosed with social anxiety disorder (SAD), generalized
subtype, and 43 (50.0%) were a healthy control (HC) group with no psychiatric disorders.
All participants spoke English fluently and were familiar with computers. Participants with
SAD were excluded from the study if they presented with psychotic symptoms or substance
misuse, but other comorbid disorders were allowed. We excluded seven participants from
analyses because they did not provide at least three daily diary entries after the initial
screening. This led to a final sample of 40 participants with generalized SAD diagnoses (25
women) and 39 HC participants (26 women), with an average age of 28.86 (SD = 8.76). Of
our sample, 54.4% identified themselves as Caucasian/White, 19.0% as African American/
Black, 12.7% as Hispanic/Latino, 5.1% as Asian/Asian-American, and 8.9% as “Other”. As
for relationship status, 62.1% of the sample was single, 16.1% was married, 11.5% was
cohabitating, 4.6% was divorced or separated, and 4.6% listed another relationship status.
As for education level, 6.8% of our sample had completed high school or less, 32.2% had
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finished some college, 6.8% completed an Associate’s degree or professional school, 31%
held a Bachelor’s degree, and 8% had completed at least some graduate study. Groups did
not differ in age, t(77) = 0.52, p = .60, d = 0.12, gender, χ
2
(1) = 0.15, p = .70, d = 0.09,
ethnicity, χ
2
(4) = 2.73, p = .60, relationship status, χ
2
(4) = 5.23, p = .27, or education, χ
2
(4)
= 3.09, p = .54. Notably, one participant in the HC group did not respond to questions on
relationship or education status.
We evaluated participants for the presence of comorbid Axis I psychological conditions
using a clinical interview (described below). In the SAD group, 18 people met criteria for a
comorbid anxiety disorder (ANX, 45%). Specifically, 11 qualified for a specific phobia, six
for post-traumatic stress disorder, three for generalized anxiety disorder, two for obsessive-
compulsive disorder, and one person for a panic disorder diagnosis. In addition, seven
people in the SAD group met criteria for a current major depressive disorder episode or
dysthymic disorder (DEP, 17.5%), and one participant met criteria for bipolar disorder.
Notably, 42.5% of the SAD group had no comorbid diagnoses, and 25% were taking
prescribed psychotropic medications. Treatment (binary coded for presence/absence) was
not significantly related to any of the instability or compliance measures (all ps > .35). The
average age of SAD onset was 12.46 years (SD = 4.22).
Procedure
We recruited potential participants using online advertisements and flyers (e.g., on bulletin
boards) in the community urging interested persons to call our laboratory for information.
Following a brief verbal informed consent procedure, trained research assistants conducted a
structured phone screen with potential participants, assessing for social anxiety, generalized
anxiety, depression symptoms, functional impairment, suicidality, and psychotic symptoms.
If participants endorsed suicidal ideation, we provided referrals to local providers or
emergency services as needed. If potential participants showed evidence of social anxiety
fears that extended beyond public speaking situations (or endorsed no psychological
symptoms for the healthy control group), the research assistant scheduled them for an initial
assessment.
During the initial face-to-face session (conducted with 122 potential participants),
participants provided informed consent and completed self-report questionnaires, including
demographic questions and trait measures. Doctoral-level students in clinical psychology
assessed for anxiety, mood, substance use, eating, and psychotic disorders with the
Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I; First, Spitzer, Gibbon,
& Williams, 2002). In addition, the SCID was supplemented with the SAD module of the
Anxiety Disorders Interview Schedule for DSM–IV: Lifetime Version (Di Nardo, Brown, &
Barlow, 1994). To be eligible for the generalized SAD group, participants had to endorse
more than two feared social situations (beyond performance settings) and this condition had
to be the primary or most severe diagnosis if other comorbid psychiatric conditions were
present. To ensure inter-rater reliability for SAD diagnoses, 45 randomly chosen recorded
interviews were rated by multiple researchers, resulting in excellent agreement (Cohen’s κ
= .87).
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Participants who qualified for the study received a 1.5-hr introductory session on the full
protocol, which included practice with the self-initiated recording of daily social
interactions, random prompts, and end-of-day records. The only data used in the present
study were from the end-of-day records, for which participants were provided a de-identified
code for making online daily diary entries each evening for the following 14 days. We chose
14 days as a time long enough to capture variability in daily life (i.e., by encapsulating every
day of the week twice) without burdening participants. Participants were instructed to
complete each daily entry between 6:00 P.M. on the day in question up to 11:59 A.M. of the
following day to minimize memory bias. We excluded entries provided outside this period
from analyses.
Two days into the experience-sampling data collection, we contacted participants to answer
questions or troubleshoot any problems with logging into the questionnaire server or
completing entries. Following this contact, researchers sent multiple reminder e-mails each
week that emphasized compliance, confidentiality, and data coding details (i.e., time-and-
date stamped entries). We also used an incentive structure to maximize compliance, such
that participants received a minimum payment of $165 and could earn up to $50 in bonus
money (50¢ for each completed end-of-day record and random prompt response, and $10
bonus for each uninterrupted week of reports). Prior research has used similar procedures to
minimize missing data (e.g., Bardone, Krahn, Goodman, & Searles, 2000). Moreover,
experience-sampling measures were kept brief to maintain participant motivation and
maximize responses without sacrificing reliability or validity (Nezlek, 2012). At the end of
the data collection, participants were debriefed, asking about any problems with data entry
or data inaccuracies.
Person-Level Measures
Social anxiety—The 20-item Social Interaction Anxiety Scale (SIAS; Mattick & Clarke,
1998) measured tendencies to fear and avoid social interactions due to concerns about being
scrutinized by other people. Participants responded to statements using a 5-point Likert scale
ranging from 0 (not at all characteristic of me) to 4 (extremely characteristic of me), with
higher scores on this scale representing greater social anxiety. This scale has demonstrated
good reliability and validity across clinical, community, and student samples (E. J. Brown et
al., 1997; Heimberg, Mueller, Holt, Hope, & Liebowitz, 1993; Mattick & Clarke, 1998).
Notably, removing the three reverse scored items has been shown to slightly improve
reliability and validity in prior work (Rodebaugh et al., 2011; Rodebaugh, Woods, &
Heimberg, 2007). Thus, we used the 17-item SIAS-Straightforward (SIAS-S) scores for
subsequent analyses for a more reliable and valid measure. Notably, in our study, the 17-
and 20-item versions had identical internal consistency (α = .97) and correlated at .99, p < .
001.
Depression—We assessed for the severity of depressive symptoms using the 21-item
Beck Depression Inventory–Second Edition (BDI-II; Beck, Steer, & Brown, 1996).
Participants responded to items on a scale from 0 to 3 to describe their experiences over the
prior 2-week period, such that higher scores represented greater depressive symptoms. In
prior research, this measure has demonstrated excellent reliability and validity, including the
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ability to differentiate people with and without mood disorder diagnoses (Beck et al., 1996;
Sprinkle et al., 2002). Our sample had acceptable internal reliability (α = .93).
Daily Measures
Daily affect—Each evening, participants described their affective experience on that
particular day with 12 items. Using a 5-point Likert scale from 1 (very slightly/not at all) to
5 (extremely), participants rated how much the following adjectives described them “today”.
Negative affect items were anxious, angry, sluggish, sad, irritable, and distressed. Positive
affect items were content, relaxed, enthusiastic, joyful, proud, and interested. These
adjectives reflect items from the Positive and Negative Affect Schedule—Expanded Form
(PANAS-X; Watson & Clark, 1994) that sample both high and low energy emotions in the
circumplex model of emotions (Barrett, 1998); similar items have been used in prior
experience sampling research (e.g., Nezlek & Kuppens, 2008). We calculated reliability of
the scales by creating a series of three-level unconditional models with items nested within
days, and days nested within people (Nezlek, 2007). In these analyses, the reliability of the
Level 1 intercept is functionally equivalent to a Cronbach’s alpha, adjusted for differences
between days and people. Given that reliability was acceptable for positive (α = .89) and
negative (α = .81) affect items, these were averaged for each day to create positive affect
(PA) and negative affect (NA) daily scores.
Daily Self-Esteem—We assessed participants’ self-esteem on the day in question with a
2-item measure. On a 7-point scale from 1 (very uncharacteristic of me today) to 7 (very
characteristic of me today), participants responded to two items: “I felt I had good qualities”
and “I felt satisfied with myself”. This scale has been used in prior experience-sampling
research (e.g., Kashdan, Weeks, & Savostyanova, 2011), and our sample demonstrated
acceptable reliability (α = .90), calculated as described above. We averaged items to create a
daily self-esteem score for each end-of-day entry.
Data Analysis
Given that our daily diary data involved multiple assessments over many days, not all
participants provided an equal number of entries across the assessment period. To account
for the unbalanced data contributions of each participant, we used multilevel modeling to
estimate mean levels of affect and self-esteem, as well as to investigate group differences in
variability, instability, and affect changes. We set the statistical significance level of the p-
value to .05, adjusted with Bonferroni correction for multiple comparisons to minimize Type
I error (
Ludbrook, 1998).
Mean levels—First, we examined group differences in PA, NA, and self-esteem using
two-level models with each measurement for each participant (at Level 1) as the outcome,
predicted by SAD diagnostic status (at Level 2).
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Instability
1
—We investigated instability by calculating the fluctuations of affect and self-
esteem over time using squared successive differences (SSDs). Similar to the mean squared
successive differences (MSSD) statistic suggested by Jahng and colleagues (2008), we
computed the difference from each measurement to the next (squared, so that larger changes
are weighted more). Given the possible influence of missing data inflating changes, we
divided SSDs by the number of days elapsed since the prior measurement. Notably, our
results were similar with and without this time adjustment. Given that participants
contributed different numbers of entries to the calculation of the instability, and given that
SSD scores follow a gamma distribution, we estimated MSSDs using generalized multilevel
modeling with log link. In these two-level models, adjusted SSDs were modeled as
outcomes predicted by SAD diagnostic group at Level 2. Covariates (e.g., mean levels,
gender, comorbid diagnoses) were added to the models to test for specificity of results.
Although there are currently no accepted guidelines for reporting effect sizes in multilevel
models, we reported Cohen’s d values derived from t-ratios and degrees of freedom for an
estimate of the magnitude of our effects (Rosenthal, Rosnow, & Rubin, 2000). Cohen (1988)
defined medium effect sizes at d = .5 and large effect sizes at d = .8.
Acute changes—We sought to investigate whether people with SAD experience more
frequent extreme affect or self-esteem shifts. Following Trull et al. (2008), we characterized
acute changes as those that equaled or exceeded the value for the 90
th
percentile of SSDs
(defined as above) across all participants in the study
2
. We then used logistic (binomial)
multilevel models to compare the probability of acute changes between diagnostic groups.
Acute changes at each measurement occasion (1 = occurred, 0 = not occurred) were modeled
as the outcome at Level 1, with SAD diagnostic group as a Level 2 predictor. Similarly,
covariates were added to the models to test for specificity.
Affect shift patterns—To understand the direction of affective shifts, we computed a
single index of affect valence to capture the continuum of affective experiences from
negative to positive by subtracting the NA score from the PA score for each data point
(resulting in a range of −4 to 4). Researchers have used this aggregating method to account
for the inverse correlation between PA and NA over the course of brief time intervals
(Green, Salovey, & Truax, 1999). PA and NA correlated at -.829 (p < .001) in our sample.
Given the high collinearity between valence and PA (r = .942, p < .001, d = 5.61), and
between valence and NA (r = -.854, p < .001, d = 3.28), we used this index only to test
hypotheses regarding affect shifts on the positive to negative affect continuum.
We calculated successive differences of valence (adjusted for time as above but not squared
to preserve direction) and categorized each change based on the affect valence of its initial
time point. Specifically, if the initial measurement in the shift was positive (i.e., PA – NA >
0 on that occasion), the shift was grouped with other shifts from positive valence, and if the
initial measurement was negatively valenced (i.e., PA – NA ≤ 0), it was grouped with other
1
We also tested for group differences in within-person variability by comparing models that assume homogenous variance vs.
heterogeneous variance. All three constructs were more variable for SAD participants. Deviance tests favored heterogeneous models
for daily PA (χ
2
= 12.66, p = .001), daily NA (χ
2
= 91.05, p < .001) and daily SE (χ
2
= 71.82, p < .001).
2
The critical value for acute change (90
th
percentile) was 1.36 for PA, 1.0 for NA, and 4.0 for SE.
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shifts from negative valence. Effectively, we separately characterized the magnitude and
direction of changes participants experienced from days they had primarily positive (or
negative) affect. Notably, participants had unequal numbers of days contributing to these
categories (38 HC vs. 39 SAD for positive, but 11 HC vs. 36 SAD for negative). Thus, we
compared groups using multilevel modeling, which is robust for unbalanced observations
across participants, since it allows relative contribution of each participant to vary. In these
models, changes for each category were modeled as outcomes, with SAD diagnostic group
included as a Level 2 predictor. As previously, covariates were added to the models in tests
of specificity.
Associations of instability with well-being—To address the phenomenology of
unstable affect and self-esteem, we analyzed relationships of the estimated MSSD variables
(estimated intercepts from multilevel analyses) with each other and with person-level
measures. To explore whether instability measures predict global levels of social anxiety or
depression, we used hierarchical linear regressions, where we controlled for mean levels in
the first step, then added instability in the second step, and then a Mean Level × Instability
effect. Predictors were standardized prior to creating interaction terms.
Results
Preliminary Analyses
Overall, our sample demonstrated good compliance. During the experience-sampling data
collection, participants provided an average of 12.19 end-of-day entries (SD = 3.67), for a
total of 963 days of data. There were no differences between the SAD and control groups in
the number of days reported (t = 0.92, SE = 0.83, p = .92, Cohen’s d = 0.09). Not
surprisingly, SAD and control groups significantly differed on the person-level measures,
with higher scores on the SIAS-S (d = 4.74) and BDI (d = 1.72). Table 1 lists the descriptive
statistics of the measures by group. Notably, the means for our SAD group on the SIAS-S
were commensurate with average scores of clients in treatment for SAD (M = 43.93, SD =
11.84) and substantially higher than scores of community samples of adults (M = 16.30, SD
= 12.48;
Rodebaugh et al., 2011).
Do People with SAD Differ in Mean Level or Variability of Daily Experiences?
Consistent with our first hypothesis (a), the SAD group had lower levels of daily PA and
self-esteem, and higher levels of daily NA on average. Group status explained 30.7%,
40.1%, and 34.1% in between-person variance (R
2
) in PA, NA, and self-esteem, respectively
(ds = 1.62, 1.37, and 1.34, respectively). Additionally, the SAD group had lower average
levels of affect valence, with group status explaining 45.6% of variance in valence (d =
1.78). Table 1 lists the estimated means by group.
Do People with SAD Have More Unstable Daily Experiences?
Since variability does not capture the frequency or extremity of fluctuations, we computed
SSDs of PA, NA, and self-esteem ratings, as described above. Consistent with hypotheses
(b), SAD diagnosis predicted significantly more unstable NA (R
2
= .15, d = 0.66) and self-
esteem (R
2
= .12, d = 0.93), but not PA (R
2
= .02, d = 0.28) without any covariates. We then
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tested whether these differences were significant when controlling for mean levels (age and
gender were entered as covariates initially and removed if not significant). Table 2 describes
multilevel analyses of group differences in SSDs.
We found a significant SAD × Mean PA interaction (d = 0.70) in predicting PA instability;
we probed this effect by computing parameter estimates separately by group and plotting
exponentiated function values for each group (Ai & Norton, 2003). Figure 1 (a)
demonstrates that higher mean PA predicted greater PA instability for people with SAD (b
= .35, p = .009) but slightly less PA instability for controls (b = -.43, p = .055). This result
suggests that, among people with SAD, those who experienced more PA on average
displayed greater PA fluctuation (i.e., intermittent high PA days), while among controls,
those with higher mean PA tended to have more stable PA experiences. Age was also a
significant predictor, such that older participants displayed more stable PA (d = 0.70). SAD
(d = 0.20) and mean PA (d = 0.02) were not significant main effects in this final model,
which altogether explained 21.2% of between-person variance in PA instability.
When we included mean intensity of daily NA as a covariate in predicting NA instability,
we also found a significant interaction effect of SAD × Mean NA (d = 1.07). Figure 1 (b)
demonstrates that people who experienced higher mean levels of NA tended to have more
unstable NA, but controls demonstrated a steeper effect (b = 1.32, p < .001) than the SAD
group (b = .62, p < .001). Mean NA (d = 2.78), but not SAD (d = 0.15), also had a
significant main effect. The full model explained 67.5% of between person variance in NA
instability.
When including average self-esteem levels as a covariate in predicting self-esteem
instability, SAD was no longer significant (d = 0.32). A main effect of mean self-esteem was
significant (d = 0.86), suggesting that people with higher self-esteem had more stable self-
esteem. Additionally, there was a marginal nonsignificant SAD x Mean Self-Esteem
interaction (d = 0.41, p = .083, uncorrected). Tentative decomposition of the effect
suggested that healthy controls had a stronger negative relationship of mean level and
instability (b = −0.72, p = .007) than SAD participants (b = −.25, p = .023). The final model
explained 22% of the between-person variance in self-esteem instability. Overall, these
results suggest that people with SAD have more unstable SE, but this difference is a
function of having lower self-esteem levels.
Are These Differences Due to Comorbid Conditions?
To address the possibility that SAD instability findings
3
may be due to comorbid conditions,
we ran additional analyses including binary variables for comorbid depression disorders
(DEP; 1 = present, 0 = absent) and comorbid anxiety disorders (ANX; 1 = present, 0 =
absent). The SAD x Mean Level interactions remained significant for NA instability (d =
0.90, p < .001) and PA instability (d = 0.60, p = .014). Notably, DEP significantly predicted
more stable NA (β = −.83, SE = .23, p = .001, d = 0.85) but not PA (β = −.42, SE = .26, p = .
11, d = 0.38). ANX did not significantly predict PA instability (β = .34, SE = .22, p = .13, d
3
SE instability was not significantly predicted by either of the comorbid diagnostic predictors (ps > .3).
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= 0.36) or NA instability (β = .33, SE = 0.23, p = .16, d = 0.33). Models with comorbid
diagnoses explained an additional 18.5% and 2.9% of between-person variance in NA and
PA instability, respectively.
Do People with SAD Experience More Acute Shifts in Daily Experiences?
Consistent with our hypothesis (c), SAD participants experienced more extreme shifts
(magnitude > 90
th
percentile) in NA and self-esteem, but not PA. Table 1 lists estimated
mean probabilities and group differences in experiencing acute shifts. Specifically, SAD
predicted a greater likelihood of acute changes in NA (R
2
= .13, d = 0.73) and self-esteem
(R
2
= .12, d = 0.70), but not PA (R
2
= .01, d = 0.22). These differences remained significant
(ps < .01, ds > 0.6) in follow-up tests controlling for comorbid diagnoses. ANX was
marginally predictive of more likely acute changes in PA (β = .65, SE = .34, p = .061, d =
0.43), and no other covariates were significant (ps > .5). Additionally, models with
comorbid diagnoses explained no additional variance (0%).
Do People with SAD Display Different Patterns of Affect Changes?
Consistent with our hypothesis, we found a dysfunctional directional pattern of affect
changes in participants with SAD. SAD predicted less positive shifts in valence following
days on which affect balance was predominantly negative (β = −.41, SE = .11, p = .001, R
2
= .72, d = 1.04) and more negative shifts following days on which affect was predominantly
positive (β = −.27, SE = .06, p < .001, R
2
= .26, d = 1.0). Figure 2 depicts estimated group
means in affect changes for each valence category. Follow-up analyses showed that these
differences remained (ps < .004, ds > 0.7) when controlling for DEP and ANX.
Additionally, MDD predicted less improvement in affect following negatively valenced days
(β = −.63, SE = .15, p < .001, d = 1.25) and marginally more deterioration after positively
valenced days (β = -.24, SE = .14, p < .094, d = 0.40), but no ANX effects were significant
(ps > .2). Comorbid diagnoses explained an additional 29.1% of variance in changes after
negative days, but no additional variance in changes after positive days.
Does Instability Relate to Psychological Functioning?
All three instability measures were significantly positively correlated (rs > .47, ps < .001, ds
> 1.0). Moreover, people who displayed unstable affect or self-esteem were more likely to
display acute changes in NA, PA, and self-esteem (rs > .41, ps < .001, ds > 0.9). Those with
high levels of NA experienced more instability (rs > .31, ps < .005, ds > 0.65) and more
frequent acute changes (rs > .32, ps < .001, ds > 0.68) in all three measures. Those with low
levels of PA and self-esteem experienced greater self-esteem instability and more NA and
self-esteem acute changes (rs < −.33, ps < .003, ds > 0.7), but not other measures (ps > .5).
These results suggest that instability—particularly NA and self-esteem instability—is
associated with poorer daily psychological functioning.
We then used hierarchical regressions to see if instability was associated with global
measures of social anxiety and depression above and beyond mean levels. We found a
significant NA Mean Level × Instability interaction in predicting SIAS-S (β = −.25, t =
−2.59, p = .011; d = 0.60, R
2
= .38, ΔR
2
= .06). Simple slopes (Aiken & West, 1991) showed
that overall high NA levels predict more social anxiety, but for people who have lower mean
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NA (−1 SD), greater instability predicted more social anxiety symptoms (b = 5.15), and for
those who have higher NA (+1 SD), greater instability predicted lower SIAS-S (b = −4.16).
No other instability or interaction effects were significant (ps > .13).
Discussion
The goal of this study was to examine the dynamic nature of affect and self-esteem in people
with SAD to offer a more nuanced understanding of how these psychological experiences
fluctuate in everyday life. Compared to healthy adults, we found participants with SAD to
experience unstable high NA, unstable low self-esteem, but stable low PA in their daily
lives. In addition to greater instability in NA and self-esteem (though not when controlling
for mean levels), participants with SAD had a higher probability of experiencing acute shifts
in NA and self-esteem (but not PA) from day to day. Greater instability of NA and self-
esteem may contribute to the disruptions in social relationships often reported by people
with SAD, since the affect and self-esteem shifts they experience would be less meaningful
and thus less useful to managing those relationships. Furthermore, people with SAD
displayed a dysfunctional pattern of affective shifts in that they perseverated in negative
affect states and displayed deficient maintenance of positive affect states.
Our finding that participants with SAD exhibited higher levels of NA in their naturalistic
environment compared to healthy adults was consistent with daily diary findings in analogue
samples (e.g., Farmer & Kashdan, 2012). Although people with higher NA levels had more
unstable NA, this effect was less pronounced in people with SAD, suggesting that instability
may be more prominent in this population, even at lower NA levels. Furthermore, mean
level and instability of NA interacted in predicting social anxiety severity (i.e., instability
predicted more severe social anxiety when mean levels were high). Confirming greater
fluctuations in NA, we found that the SAD group was approximately three times more likely
to experience acute shifts in NA. These results indicate that emotion difficulties in people
with SAD extend beyond the experience of frequent or intense NA (e.g., anxiety). For
people with SAD, experiencing unstable affect may lead them to view emotional
experiences as particularly uncontrollable and thus threatening, contributing to attempts to
avoid, conceal, and suppress the expression of these emotions—regulatory strategies
theorized to maintain and exacerbate distress and impairment (Rapee & Heimberg, 1997).
Prior research has established a strong evidence base for positivity deficits in people with
SAD (Kashdan et al., 2011), and our findings shed further light on this phenomenon. First,
we confirmed prior research with analog samples that people with SAD have less intense
daily PA on average. We also found that in healthy adults, experiencing more PA on average
related to more stable PA, while the effect was inversed for the SAD group. This suggests
that people with SAD generally experience low, stable PA, but those who do experience
relatively more PA are likely to do so on intermittent and transient occasions (contributing
to high PA instability). Further supporting our hypothesis that people with SAD have stable,
low PA, the SAD and healthy control groups displayed no differences in rates of acute
changes in PA.
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Emotion regulation skills are necessary not only to down-regulate negative emotions but
also to enhance or prolong positive emotions (Tugade & Fredrickson, 2006). Inability to
savor and extend positive emotion states may not only limit exposure to positive experiences
but also interfere with adaptive responses to stress (Fredrickson, Mancuso, Branigan, &
Tugade, 2000). Theorists suggest that people gravitate toward stable states (Carver &
Scheier, 2001), which tend to be generally positive in terms of mood (Johnson & Nowak,
2002). This was true for the healthy adults in our sample, who generally tended to maintain
positive affect with small affect changes from positively valenced states. Furthermore, they
quickly shifted toward more positive affect after negatively valenced states. The SAD group
did not display this pattern, instead experiencing more severe shifts toward negative affect
from positively valenced states, and less strong positive shifts from negatively valenced
states. These findings support literature on emotion regulation deficits in SAD, specifically
in the greater use of down-regulating positive emotions and difficulty using strategies that
effectively reduce negative emotions (e.g., Werner et al., 2011). Consequently, people with
SAD may more quickly return to (more negative) baseline states after pleasant experiences.
Our finding of people with SAD tending to shift more extremely toward negatively valenced
affect following days with mostly positively valenced affect provides initial evidence for
this possibility.
To our knowledge, this was the first study to examine daily self-esteem in people diagnosed
with SAD, despite a growing body of literature and theory suggesting the role of low,
unstable self-worth in this population. Our experience sampling data confirmed prior global
self-report findings of low self-esteem (Baños & Guillén, 2000; Chartier, Hazen, & Stein,
1998; Izgiç, Akyüz, Doğan, & Kuğu, 2004; Leary, 2001). SAD participants also exhibited
greater self-esteem instability, but this relationship was no longer evident when we took
global self-esteem level into account. There is mixed evidence on whether it is necessary to
control for mean levels in such analyses (Russell, Moskowitz, Zuroff, Sookman, & Paris,
2007). Providing further evidence for increased fluctuation, we found that SAD participants
were three times more likely to experience acute shifts in self-esteem. Overall, these
findings provide initial experience-sampling evidence that people with SAD have unstable,
low self-esteem, consistent with cognitive models of the disorder (Clark & Wells, 1995;
Moscovitch, 2009). Future research may address other aspects of these models by exploring
how the context-dependency of self-esteem and self-esteem shifts relate to SAD and well-
being.
Given the theoretical support and related empirical data, self-esteem instability may be an
important marker for social anxiety symptoms. Overly variable self-esteem may reflect a
miscalibrated gauge of one’s impression on others, such that instead of providing accurate
information about the state of one’s relational value, people with SAD may react to small
perceived depreciations in acceptance or anticipated devaluation rather than true rejection
(Leary et al., 1998). In response, they may take extreme measures to avoid devaluation (e.g.,
with efforts to make positive impressions or by avoiding social interactions), or to avoid
relational devaluation (e.g., by avoiding social interactions). Thus, variable self-esteem may
serve as a possible mechanism for maintaining social anxiety symptoms. Alternatively, self-
esteem instability may represent flexibility and/or destabilization of entrenched beliefs when
it precedes the learning of novel associations, as in cognitive behavior therapy (e.g., Hayes,
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Laurenceau, Feldman, Strauss, & Cardaciotto, 2007). Notably, given that our data collection
was during a random two-week segment of life (not a transition stage), the latter explanation
is less likely.
To date, studies of self-esteem instability have used measures of variability (e.g., standard
deviation) to capture this construct (e.g., Kashdan, Julian, et al., 2006; Kernis, Paradise,
Whitaker, Wheatman, & Goldman, 2000). Self-esteem variability predicted vulnerability to
depression (Kernis et al., 1998; Roberts, Kassel, & Gotlib, 1995), stress reactivity (Greenier
et al., 1999), interpersonal aggression (Kernis, Grannemann, & Barclay, 1989), and impaired
well-being (Kashdan, Uswatte, et al., 2006). By analyzing self-esteem instability with a
measure that incorporated a temporal aspect of self-esteem fluctuations, we provided
additional evidence for unstable self-esteem relating to poorer daily well-being.
It is worth noting that some prior research has suggested that instability may be adaptive
when self-esteem levels are generally low, contributing to people using more adaptive
coping strategies under stress (e.g., Kernis, Cornell, Sun, Berry, & Harlow, 1993). However,
low self-esteem (even when variable) still increased the risk of developing depression over
time, particularly when individuals experience chronic daily stress (Kernis et al., 1998). This
relationship may help explain why in cases where SAD is comorbid with depression, social
anxiety symptoms tend to precede depressive symptoms (Merikangas & Angst, 1995).
This research adds novel understanding to the phenomenology of SAD by taking an
experience-sampling approach to investigate shifts and fluctuations of psychological states
over time. Our findings build on prior SAD research that focused exclusively on global self-
esteem, PA, and NA (e.g., T. A. Brown, 2007; Leary, 1983), or relied on mean daily affect
levels (Kashdan & Steger, 2006). By using experience-sampling methods, we were able to
examine affect and self-esteem as dynamic, contextualized constructs (see Bolger, Davis, &
Rafaeli, 2003; Nezlek, 2012). Additionally, asking participants to describe their experiences
over the course of several weeks with online diaries with time-stamped entries minimized
some of the limitations of retrospective reports (Robinson & Barrett, 2010; Scollon, Kim-
Prieto, & Diener, 2003), allowing us to study affect and self-esteem shifts in their natural,
spontaneous context with greater ecological validity (Csikszentmihalyi & Larson, 1987). In
fact, comparing ESM data with global self-reports has shown only moderate agreement on
instability and variability, and poor agreement on affect changes (Kernis et al., 1992;
Solhan, Trull, Jahng, & Wood, 2009), which suggests that people have little insight into the
degree of fluctuations they experience.
While our methods improved over global assessments and aggregation of assessment across
time, our investigation was limited in that we did not examine the sources of day-to-day
fluctuations or examine more complex sequences over time. Prior time-series research has
demonstrated that self-esteem tends to covary with experienced affect (Nezlek, 2005) and
experienced stressors (Greenier et al., 1999). Future studies might use multilevel growth
curve modeling to examine temporal dependency of these constructs and the relationship of
instability to emotional reactivity and contextual factors.
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We compared a sample of participants carefully diagnosed with SAD using a well-validated
clinical interview with a carefully screened healthy control group. However, 57.5% of the
SAD group had at least one secondary comorbid diagnosis, consistent with epidemiological
comorbidity research (Merikangas & Angst, 1995). Thus, a possible alternative explanation
for our findings is that instability and dysfunctional patterns in shifts of psychological
experiences are features of psychological difficulties more broadly. This point is particularly
relevant in light of transdiagnostic research demonstrating shared features among commonly
occurring disorders (e.g., emotion regulation; Aldao & Nolen-Hoeksema, 2010). Notably, all
hypothesized effects in our study remained significant after controlling for comorbid
depression and anxiety disorders, providing preliminary evidence that SAD uniquely
contributes to instability. Future research with clinical comparison groups (e.g., major
depressive disorder) may help clarify this question.
Although our findings need replication, this research has important clinical and research
implications. Specifically, we found people with SAD to experience more instability of NA
and self-esteem, and tend to perseverate in NA states but have difficulty maintaining PA
states. These findings suggest that clinicians should consider incorporating strategies that
enhance emotion regulation skills that help to accept or more effectively manage negative
emotions as well as to prolong and intensify positive emotions. Prior work on therapies
employing relaxation, guided meditation, and mindfulness indicates that these techniques
can prolong positive experiences and enhance quality of life (Chesney et al., 2005).
Although cognitive-behavioral interventions have been particularly effective for increasing
self-esteem (Emler, 2001; Goldin et al., in press), studies have yet to examine self-esteem
stability as a treatment outcome. Future studies examining affective and self-esteem stability
longitudinally will help to understand the development of these constructs and to clarify
whether instability is a vulnerability factor, a symptom that occurs during the course of
SAD, or a consequence of the disorder that persists after recovery. Moreover, assessing
instability over critical transition periods (e.g., psychotherapy) may help elucidate patterns
important to therapeutic change (Hayes et al., 2007).
Acknowledgments
This research was supported by grants from the National Institute of Mental Health (R21-MH073937) and the
Center of Consciousness and Transformation at George Mason University to TBK and the National Institute of
Drug Abuse (1F31DA029390) to ASF.
References
Ai C, Norton EC. Interaction terms in logit and probit models. Economics letters. 2003; 80:123–129.
Aiken, LS.; West, SG. Multiple regression: Testing and interpreting interactions. Newbury Park, CA:
Sage; 1991.
Aldao A, Nolen-Hoeksema S. Specificity of cognitive emotion regulation strategies: A transdiagnostic
examination. Behaviour Research and Therapy. 2010; 48(10):974–983. [PubMed: 20591413]
American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-IV-TR.
Washington, DC: American Psychiatric Publishing, Inc; 2000.
Anestis MD, Selby EA, Crosby RD, Wonderlich SA, Engel SG, Joiner TE. A comparison of
retrospective self-report versus ecological momentary assessment measures of affective lability in
the examination of its relationship with bulimic symptomatology. Behaviour Research and Therapy.
2010; 48(7):607–613. [PubMed: 20392437]
Farmer and Kashdan
Page 15
Clin Psychol Sci. Author manuscript; available in PMC 2015 March 25.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript

Baños RM, Guillén V. Psychometric characteristics in normal and social phobic samples for a Spanish
version of the Rosenberg Self-Esteem Scale. Psychological reports. 2000; 87:269–274. [PubMed:
11026424]
Bardone AM, Krahn DD, Goodman BM, Searles JS. Using interactive voice response technology and
timeline follow-back methodology in studying binge eating and drinking behavior: Different
answers to different forms of the same question? Addictive Behaviors. 2000; 25:1–11. [PubMed:
10708315]
Barrett LF. Discrete emotions or dimensions? The role of valence focus and arousal focus. Cognition
& Emotion. 1998; 12(4):579–599.
Beck, AT.; Steer, RA.; Brown, GK. Manual for the Beck Depression Inventory-II. San Antonio, TX:
Psychological Corporation; 1996.
Bolger N, Davis A, Rafaeli E. Diary methods: Capturing life as it is lived. Annual Review of
Psychology. 2003; 54:579–616.
Bowen R, Baetz M, Hawkes J, Bowen A. Mood variability in anxiety disorders. Journal of Affective
Disorders. 2006; 91:165–170. [PubMed: 16458367]
Bowen R, Clark M, Baetz M. Mood swings in patients with anxiety disorders compared with normal
controls. Journal of Affective Disorders. 2004; 78:185–192. [PubMed: 15013242]
Brown EJ, Turovsky J, Heimberg RG, Juster HR, Brown TA, Barlow DH. Validation of the Social
Interaction Anxiety Scale and the Social Phobia Scale across the anxiety disorders. Psychological
Assessment. 1997; 9:21–27.
Brown TA. Temporal course and structural relationships among dimensions of temperament and
DSM-IV anxiety and mood disorder constructs. Journal of Abnormal Psychology. 2007; 116:313–
328. [PubMed: 17516764]
Campbell-Sills L, Barlow D, Brown T, Hofmann SG. Effects of suppression and acceptance on
emotional responses of individuals with anxiety and mood disorders. Behaviour Research and
Therapy. 2006; 44:1251–1263. [PubMed: 16300723]
Carver, CS.; Scheier, MF. On the self-regulation of behavior. New York, NY: Cambridge University
Press; 2001.
Chartier MJ, Hazen AL, Stein MB. Lifetime patterns of social phobia: A retrospective study of the
course of social phobia in a nonclinical population. Depression and Anxiety. 1998; 7:113–121.
[PubMed: 9656091]
Chesney MA, Darbes LA, Hoerster K, Taylor JM, Chambers DB, Anderson DE. Positive emotions:
Exploring the other hemisphere in behavioral medicine. International Journal of Behavioral
Medicine. 2005; 12:50–58. [PubMed: 15901213]
Clark, DM.; Wells, A. A cognitive model of social phobia. In: Heimberg, Richard G.; Liebowitz, MR.;
Hope, DA.; Schneier, FR., editors. Social phobia: Diagnosis, assessment, and treatment. New
York: Guilford Press; 1995. p. 69-93.
Cohen, J. Statistical power analysis for the behavioral sciences. 2nd ed.. Psychology Press; 1988.
Craske MG, Brown TA, Meadows EA, Barlow DH. Uncued and cued emotions and associated distress
in a college sample. Journal of Anxiety Disorders. 1995; 9:125–137.
Csikszentmihalyi M, Larson R. Validity and reliability of the experience-sampling method. Journal of
Nervous and Mental Disease. 1987; 175:526–536. [PubMed: 3655778]
Di Nardo, PA.; Brown, TA.; Barlow, DH. Anxiety Disorders Interview Schedule for DSM–IV:
Lifetime Version (ADIS-IV-L). San Antonio, TX: Psychological Corporation; 1994.
Ebner-Priemer UW, Kuo J, Kleindienst N, Welch SS, Reisch T, Reinhard I, … Bohus M. State
affective instability in borderline personality disorder assessed by ambulatory monitoring.
Psychological Medicine. 2007; 37:961–970. [PubMed: 17202005]
Emler, N. Self-esteem: The costs and causes of low self-worth. London: Joseph Rowntree Foundation;
2001.
Farmer AS, Kashdan TB. Social anxiety and emotion regulation in daily life: Spillover effects on
positive and negative social events. Cognitive Behaviour Therapy. 2012; 41:152–162. [PubMed:
22428662]
Farmer and Kashdan
Page 16
Clin Psychol Sci. Author manuscript; available in PMC 2015 March 25.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript

First, MB.; Spitzer, RL.; Gibbon, M.; Williams, JBW. Structured clinical interview for DSM-IV-TR
axis I disorders, research version, non-patient Edition (SCID-I/NP). New York: Biometrics
Research, New York State Psychiatric Institute; 2002.
Fredrickson BL, Mancuso RA, Branigan C, Tugade MM. The undoing effect of positive emotions.
Motivation and Emotion. 2000; 24:237–258. [PubMed: 21731120]
Goldin PR, Manber T, Hakimi S, Canli T, Gross JJ. Neural bases of social anxiety disorder: Emotional
reactivity and cognitive regulation during social and physical threat. Archives of General
Psychiatry. 2009; 66:170–180. [PubMed: 19188539]
Goldin, Philippe R.; Jazaieri, H.; Ziv, M.; Kraemer, H.; Heimberg, RG.; Gross, JJ. Changes in positive
self-views mediate the effect of cognitive-behavioral therapy for social anxiety disorder. Clinical
Psychological Science. 2013
Green DP, Salovey P, Truax KM. Static, dynamic, and causative bipolarity of affect. Journal of
Personality and Social Psychology. 1999; 76:856–867. [PubMed: 10353205]
Greenier KD, Kernis MH, McNamara CW, Waschull SB, Berry AJ, Herlocker CE, Abend TA.
Individual differences in reactivity to daily events: Examining the roles of stability and level of
self-esteem. Journal of Personality. 1999; 67:187–208.
Gruber J, Kogan A, Quoidbach J, Mauss IB. Happiness is best kept stable: Positive emotion variability
is associated with poorer psychological health. Emotion. 2013; 13(1):1–6. [PubMed: 23163709]
Hayes AM, Laurenceau J-P, Feldman G, Strauss JL, Cardaciotto L. Change is not always linear: The
study of nonlinear and discontinuous patterns of change in psychotherapy. Clinical Psychology
Review. 2007; 27:715–723. [PubMed: 17316941]
Heimberg RG, Mueller GP, Holt CS, Hope DA, Liebowitz MR. Assessment of anxiety in social
interaction and being observed by others: The Social Interaction Anxiety Scale and the Social
Phobia Scale. Behavior Therapy. 1993; 23:53–73.
Hughes AA, Heimberg RG, Coles ME, Gibb BE, Liebowitz MR, Schneier FR. Relations of the factors
of the tripartite model of anxiety and depression to types of social anxiety. Behaviour Research
and Therapy. 2006; 44:1629–1641. [PubMed: 16457777]
Izgiç F, Akyüz G, Doğan O, Kuğu N. Social phobia among university students and its relation to self-
esteem and body image. Canadian Journal of Psychiatry. 2004; 49:630–634.
Jahng S, Wood PK, Trull TJ. Analysis of affective instability in ecological momentary assessment:
Indices using successive difference and group comparison via multilevel modeling. Psychological
Methods. 2008; 13:354–375. [PubMed: 19071999]
Johnson SL, Nowak A. Dynamical patterns in bipolar depression. Personality and Social Psychology
Review. 2002; 6(4):380–387.
Kashdan TB. Social anxiety spectrum and diminished positive experiences: Theoretical synthesis and
meta-analysis. Clinical Psychology Review. 2007; 27:348–365. [PubMed: 17222490]
Kashdan TB, Breen WE. Social anxiety and positive emotions: A prospective examination of a self-
regulatory model with tendencies to suppress or express emotions as a moderating variable.
Behavior Therapy. 2008; 39:1–12. [PubMed: 18328865]
Kashdan TB, Julian T, Merritt K, Uswatte G. Social anxiety and posttraumatic stress in combat
veterans: Relations to well-being and character strengths. Behaviour Research and Therapy. 2006;
44:561–583. [PubMed: 15972206]
Kashdan TB, Steger MF. Expanding the topography of social anxiety: An experience-sampling
assessment of positive emotions, positive events, and emotion suppression. Psychological Science.
2006; 17:120–128. [PubMed: 16466419]
Kashdan TB, Uswatte G, Steger MF, Julian T. Fragile self-esteem and affective instability in
posttraumatic stress disorder. Behaviour Research and Therapy. 2006; 44:1609–1619. [PubMed:
16445887]
Kashdan TB, Weeks JW, Savostyanova AA. Whether, how, and when social anxiety shapes positive
experiences and events: a self-regulatory framework and treatment implications. Clinical
Psychology Review. 2011; 31:786–799. [PubMed: 21529701]
Keltner D, Kring AM. Emotion, social function, and psychopathology. Review of General Psychology.
1998; 2(3):320–342.
Farmer and Kashdan
Page 17
Clin Psychol Sci. Author manuscript; available in PMC 2015 March 25.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript

Kernis MH, Cornell DP, Sun C-R, Berry A, Harlow T. There’s more to self-esteem than whether it is
high or low: The importance of stability of self-esteem. Journal of Personality and Social
Psychology. 1993; 65:1190–1204. [PubMed: 8295118]
Kernis MH, Grannemann BD, Barclay LC. Stability and level of self-esteem as predictors of anger
arousal and hostility. Journal of Personality and Social Psychology. 1989; 56:1013–1022.
[PubMed: 2746456]
Kernis MH, Grannemann BD, Barclay LC. Stability of self-esteem: Assessment, correlates, and excuse
making. Journal of Personality. 1992; 60:621–644. [PubMed: 1403597]
Kernis MH, Paradise AW, Whitaker DJ, Wheatman SR, Goldman BN. Master of one’s psychological
domain? not likely if one’s self-esteem is unstable. Personality and Social Psychology Bulletin.
2000; 26:1297–1305.
Kernis MH, Whisenhunt CR, Waschull SB, Greenier KD, Berry AJ, Herlocker CE, Anderson CA.
Multiple facets of self-esteem and their relations to depressive symptoms. Personality and Social
Psychology Bulletin. 1998; 24:657–668.
Koenigsberg HW. Affective instability: Toward an integration of neuroscience and psychological
perspectives. Journal of Personality Disorders. 2010; 24:60–82. [PubMed: 20205499]
Larsen RJ. The stability of mood variability: A spectral analytic approach to daily mood assessments.
Journal of Personality and Social Psychology. 1987; 52:1195–1204.
Larson R, Csikszentmihalyi M. The experience sampling method. New Directions for Methodology of
Social & Behavioral Science. 1983; 15:41–56.
Leary MR. Social anxiousness: The construct and its measurement. Journal of Personality Assessment.
1983; 47:66–75. [PubMed: 6834234]
Leary, MR. Social anxiety as an early warning system: A refinement and extension of the self-
presentation theory of social anxiety. In: Hofmann, SG.; DiBartolo, PM., editors. From social
anxiety to social phobia: Multiple perspectives. Needham Heights, MA: Allyn & Bacon; 2001. p.
321-334.
Leary, MR.; Downs, DL. Efficacy, agency, and self-esteem. New York, NY: Plenum Press; 1995.
Interpersonal functions of the self-esteem motive: The self-esteem system as a sociometer; p.
123-144.
Leary MR, Haupt AL, Strausser KS, Chokel JT. Calibrating the sociometer: The relationship between
interpersonal appraisals and the state self-esteem. Journal of Personality and Social Psychology.
1998; 74(5):1290–1299. [PubMed: 9599444]
Leary MR, Kowalski RM, Campbell CD. Self-presentational concerns and social anxiety: The role of
generalized impression expectancies. Journal of Research in Personality. 1988; 22:308–321.
Ludbrook J. Multiple comparison procedures updated. Clinical and Experimental Pharmacology and
Physiology. 1998; 25(12):1032–1037. [PubMed: 9888002]
Mattick RP, Clarke JC. Development and validation of measures of social phobia scrutiny fear and
social interaction anxiety. Behaviour Research and Therapy. 1998; 36:455–470. [PubMed:
9670605]
Merikangas KR, Angst J. Comorbidity and social phobia: Evidence from clinical, epidemiologic, and
genetic studies. European Archives of Psychiatry and Clinical Neuroscience. 1995; 244:297–303.
[PubMed: 7772612]
Moscovitch DA. What is the core fear in social phobia? A new model to facilitate individualized case
conceptualization and treatment. Cognitive and Behavioral Practice. 2009; 16:123–134.
Nezlek JB. Distinguishing affective and non-affective reactions to daily events. Journal of Personality.
2005; 73:1539–1568. [PubMed: 16274445]
Nezlek JB. A multilevel framework for understanding relationships among traits, states, situations and
behaviours. European Journal of Personality. 2007; 21:789–810.
Nezlek, JB. The SAGE Library in Social and Personality Psychology Methods. London: Sage
Publications; 2012. Diary methods for social and personality psychology.
Nezlek JB, Kuppens P. Regulating positive and negative emotions in daily life. Journal of Personality.
2008; 76(3):561–579. [PubMed: 18399953]
Farmer and Kashdan
Page 18
Clin Psychol Sci. Author manuscript; available in PMC 2015 March 25.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript

Oosterwegel A, Field N, Hart D, Anderson K. The relation of self-esteem variability to emotion
variability, mood, personality traits, and depressive tendencies. Journal of Personality. 2001;
69(5):689–708. [PubMed: 11575510]
Rapee RM, Heimberg RG. A cognitive-behavioral model of anxiety in social phobia. Behaviour
Research and Therapy. 1997; 35:741–756. [PubMed: 9256517]
Roberts JE, Kassel JD, Gotlib IH. Level and stability of self-esteem as predictors of depressive
symptoms. Personality and Individual Differences. 1995; 19:217–224.
Robinson MD, Barrett LF. Belief and feeling in self-reports of emotion: Evidence for semantic
infusion based on self-esteem. Self and Identity. 2010; 9:87–111.
Rodebaugh TL, Heimberg RG, Brown PJ, Fernandez KC, Blanco C, Schneier FR, Liebowitz MR.
More reasons to be straightforward: Findings and norms for two scales relevant to social anxiety.
Journal of Anxiety Disorders. 2011; 25:623–630. [PubMed: 21388781]
Rodebaugh TL, Woods CM, Heimberg RG. The reverse of social anxiety is not always the opposite:
The reverse-scored items of the Social Interaction Anxiety Scale do not belong. Behavior Therapy.
2007; 38:192–206. [PubMed: 17499085]
Rosenthal, R.; Rosnow, RL.; Rubin, DB. Contrasts and effect sizes in behavioral research: A
correlational approach. Vol. x. New York, NY, US: Cambridge University Press; 2000.
Russell JJ, Moskowitz DS, Zuroff DC, Sookman D, Paris J. Stability and variability of affective
experience and interpersonal behavior in borderline personality disorder. Journal of Abnormal
Psychology. 2007; 116(3):578–588. [PubMed: 17696713]
Scollon CN, Kim-Prieto C, Diener E. Experience sampling: Promises and pitfalls, strengths and
weaknesses. Journal of Happiness Studies. 2003; 4:5–34.
Solhan MB, Trull TJ, Jahng S, Wood PK. Clinical assessment of affective instability: Comparing
EMA indices, questionnaire reports, and retrospective recall. Psychological Assessment. 2009;
21:425–436. [PubMed: 19719353]
Sprinkle SD, Lurie D, Insko SL, Atkinson G, Jones GL, Logan AR, Bissada NN. Criterion validity,
severity cut scores, and test-retest reliability of the Beck Depression Inventory-II in a university
counseling center sample. Journal of Counseling Psychology. 2002; 49:381–385.
Stopa L, Brown MA, Luke MA, Hirsch CR. Constructing a self: The role of self-structure and self-
certainty in social anxiety. Behaviour Research and Therapy. 2010; 48:955–965. [PubMed:
20800751]
Tesser, A. Toward a self-evaluation maintenance model of social behavior. In: Berkowitz, L., editor.
Advances in experimental social psychology. Vol. 21. San Diego, CA: Academic Press; 1988. p.
181-227.
Thompson RJ, Mata J, Jaeggi SM, Buschkuehl M, Jonides J, Gotlib IH. The everyday emotional
experience of adults with major depressive disorder: Examining emotional instability, inertia, and
reactivity. Journal of Abnormal Psychology. 2012; 121:819–829. [PubMed: 22708886]
Trull TJ, Solhan MB, Tragesser SL, Jahng S, Wood PK, Piasecki TM, Watson D. Affective instability:
Measuring a core feature of borderline personality disorder with ecological momentary
assessment. Journal of Abnormal Psychology. 2008; 117:647–661. [PubMed: 18729616]
Tugade MM, Fredrickson BL. Regulation of positive emotions: Emotion regulation strategies that
promote resilience. Journal of Happiness Studies. 2006; 8:311–333.
Von Neumann J, Kent RH, Bellinson HR, Hart BI. The Mean Square Successive Difference. The
Annals of Mathematical Statistics. 1941; 12:153–162.
Waschull SB, Kernis MH. Level and stability of self-esteem as predictors of children’s intrinsic
motivation and reasons for anger. Personality and Social Psychology Bulletin. 1996; 22:4–13.
Watson, D.; Clark, LA. The PANAS-X: Manual for the Positive and Negative Affect Schedule -
Expanded Form. University of Iowa; 1994.
Watson D, Clark LA, Carey G. Positive and negative affectivity and their relation to anxiety and
depressive disorders. Journal of Abnormal Psychology. 1988; 97:346–353. [PubMed: 3192830]
Werner K, Goldin P, Ball T, Heimberg R, Gross J. Assessing emotion regulation in social anxiety
disorder: The emotion regulation interview. Journal of Psychopathology and Behavioral
Assessment. 2011; 33:346–354.
Farmer and Kashdan
Page 19
Clin Psychol Sci. Author manuscript; available in PMC 2015 March 25.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript

Wilson JK, Rapee RM. Self-concept certainty in social phobia. Behaviour Research and Therapy.
2006; 44:113–136. [PubMed: 16301018]
Wittchen HU, Beloch E. The impact of social phobia on quality of life. International Clinical
Psychopharmacology. 1996; 11:15–23. [PubMed: 8923105]
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Figure 1. Effect of Diagnostic Group × Mean Daily Affect on Affective Instability
Notes. These graphs demonstrate the differential effect of mean affect level on affect
instability (squared successive deviations) for people with and without social anxiety
disorder based on the fitted values from multilevel models. The x-axes represent the
standardized mean levels (shown from −1 SD to +1 SD) for negative affect (a) and positive
affect (b). All individual effects are significantly different from zero (p < .05).
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Figure 2. Average Affect Change from Positive and Negative Valence by Diagnostic Group
Notes. This graph shows the mean direction and intensity of affect shifts (error bars
represent standard error of the mean) from days with predominantly negatively valenced
affect (Positive – Negative < 0) and positively valenced affect (Positive – Negative > 0).
Differences were significant at p < .01.
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Table 1
Descriptive Statistics and Between Group Differences for Daily Affect and Self-Esteem
Group differences
Variable
SAD group
a
HC group
b
β t-ratio p-value
SIAS-S 43.57 (8.86) 8.09 (5.99) 0.91 20.80 < .001
BDI-II 17.00 (10.88) 3.15 (3.60) 0.65 7.55 < .001
Mean Valence 0.36 (0.15) 1.87 (0.13) −0.76 −7.80 < .001
Mean PA 2.33 (0.10) 3.29 (0.09) −0.48 −7.11 < .001
Mean NA 1.97 (0.07) 1.42 (0.06) 0.28 6.01 < .001
Mean SE
c
4.00 (0.21) 5.43 (0.13) −0.72 −5.83 < .001
PA acute changes 0.16 (0.06) 0.12 (0.06) 0.13 0.95 .347
NA acute changes 0.17 (0.07) 0.06 (0.03) 0.55 3.21 .002
SE acute changes
c
0.17 (0.06) 0.06 (0.04) 0.48 3.06 .004
Notes. Tabulated data depict means (with standard deviations) for self-report measures, and estimated group means (with standard errors) for experience sampling data derived from multilevel models.
Acute changes reflect probabilities of shifts ≥ 90
th
percentile in magnitude. SAD = social anxiety disorder; HC = healthy control; SIAS-S = Social Interaction Anxiety Scale-Straightforward; BDI-II = Beck
Depression Inventory-II; PA = positive affect; NA = negative affect; SE = self-esteem.
a
n = 40.
b
n = 39.
c
Statistics based on 78 participants due to missing data.
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Table 2
Multilevel Models Predicting the Instability of Daily Affect and Self-Esteem
Outcome
df
β
SE
t-ratio p-value
Daily PA SSD
Intercept 1, 77 −0.67 0.10 −6.86 < .001
SAD 0.12 0.10 1.24 .221
Intercept 4,74 −0.73 0.08 −8.67 < .001
Age −0.03 0.01 −3.72 .001
SAD 0.11 0.13 0.86 .391
Mean PA −0.01 0.12 −0.07 .949
SAD × Mean PA 0.35 0.12 3.00 .004
Daily NA SSD
Intercept 1, 77 −0.85 0.14 −6.27 < .001
SAD 0.40 0.14 2.91 .005
Intercept 3, 75 −1.20 0.08 −15.44 < .001
SAD 0.06 0.09 0.65 .516
Mean NA 1.00 0.08 12.03 < .001
SAD × Mean NA −0.38 0.08 −4.63 < .001
Daily Self-Esteem SSD
Intercept 1, 76 0.48 0.09 5.40 < .001
SAD 0.36 0.09 4.03 < .001
Intercept 3, 74 0.43 0.09 4.90 < .001
SAD 0.13 0.10 1.37 .174
Mean Self-Esteem −0.49 0.13 −3.71 .001
SAD × Mean Self-Esteem 0.23 0.13 1.76 .083
Notes.Group differences were tested by generalized linear models with log link. Only diagnostic group contrast was entered in first models for each construct. Gender, age, group contrast, mean levels, and
interaction of group and mean level were initially entered in the second models; gender and/or age were removed if non-significant. NA = negative affect; PA = positive affect; SAD = Social Anxiety
Disorder Diagnosis (contrast coded); SSD = squared successive differences.
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