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Journal of Abnormal Psychology
Distinguishing Healthy Adults From People With Social
Anxiety Disorder: Evidence for the Value of Experiential
Avoidance and Positive Emotions in Everyday Social
Interactions
Todd B. Kashdan, Antonina S. Farmer, Leah M. Adams, Patty Ferssizidis, Patrick E. McKnight,
and John B. Nezlek
Online First Publication, July 1, 2013. doi: 10.1037/a0032733
CITATION
Kashdan, T. B., Farmer, A. S., Adams, L. M., Ferssizidis, P., McKnight, P. E., & Nezlek, J. B.
(2013, July 1). Distinguishing Healthy Adults From People With Social Anxiety Disorder:
Evidence for the Value of Experiential Avoidance and Positive Emotions in Everyday Social
Interactions. Journal of Abnormal Psychology. Advance online publication. doi:
10.1037/a0032733
Distinguishing Healthy Adults From People With Social Anxiety Disorder:
Evidence for the Value of Experiential Avoidance and Positive Emotions
in Everyday Social Interactions
Todd B. Kashdan, Antonina S. Farmer,
Leah M. Adams, Patty Ferssizidis,
and Patrick E. McKnight
George Mason University
John B. Nezlek
College of William and Mary, University of Social Sciences and
Humanities, Faculty in Pozna
´
n, Poland
Despite the increased attention that researchers have paid to social anxiety disorder (SAD), compared
with other anxiety and mood disorders, relatively little is known about the emotional and social factors
that distinguish individuals who meet diagnostic criteria from those who do not. In this study, participants
with and without a diagnosis of SAD (generalized subtype) described their daily face-to-face social
interactions for 2 weeks using handheld computers. We hypothesized that, compared with healthy
controls, individuals diagnosed with SAD would experience fewer positive emotions, rely more on
experiential avoidance (of anxiety), and have greater self-control depletion (feeling mentally and
physically exhausted after socializing), after accounting for social anxiety, negative emotions, and
feelings of belonging during social interactions. We found that compared with healthy controls, indi-
viduals with SAD experienced weaker positive emotions and greater experiential avoidance, but there
were no differences in self-control depletion between groups. Moreover, the differences we found could
not be attributed to comorbid anxiety or depressive disorders. Our results suggest that negative emotions
alone do not fully distinguish normal from pathological social anxiety, and that assessing social anxiety
disorder should include impairments in positive emotional experiences and dysfunctional emotion
regulation (in the form of experiential avoidance) in social situations.
Keywords: social anxiety disorder, experiential avoidance, positive emotions, experience sampling
Social anxiety disorder (SAD) is characterized by a persistent
fear of scrutiny by others due to the belief that such scrutiny will
lead to negative evaluation and rejection (Clark & Wells, 1995;
Heimberg, Brozovich, & Rapee, 2010). Researchers have com-
pared people with SAD and those without a diagnosis based on
self-reported negative emotions (e.g., Watson, Clark, & Carey,
1988), physiological correlates of fear (e.g., Beidel, Turner, &
Dancu, 1985; Hofmann, Newman, Ehlers, & Roth, 1995), and
avoidant behavior during laboratory social interactions (e.g., Chen,
Ehlers, Clark, & Mansell, 2002; Heuer, Rinck, & Becker, 2007).
This research, along with expert judgment and clinical observa-
tion, led to the existing diagnostic criteria for SAD (e.g., American
Psychiatric Association, 2000).
Most researchers distinguish the socially relevant anxious states
of those with SAD from those without a diagnosis based upon the
intensity, frequency, and duration of anxiety symptoms (Heim-
berg, Mueller, Holt, Hope, & Liebowitz, 1992; Mennin et al.,
2002). Compared with those without SAD, people with SAD are
anxious more often, and these feelings are stronger and last longer
when they occur. Nevertheless, these criteria do not take into
account recent research about SAD, and clinicians who rely on the
existing criteria may not identify some individuals with the disor-
der. Accurate diagnostic criteria are essential to identifying, clas-
sifying, and treating individuals with SAD. In this article we
present evidence that suggests that the current criteria need to be
expanded.
Positive Emotions
Although anxiety disorders have been linked with high negative
affect, SAD is the only anxiety disorder associated with low levels
of positive affect (Brown, 2007; Watson et al., 1988). Compared
with their nonanxious peers, people with SAD expect positive
events to be less likely to occur (Gilboa-Schechtman, Franklin, &
Foa, 2000), and, in fact, studies with nonclinical samples in ev-
eryday life have shown that excessive social anxiety is associated
with a lower frequency of positive life events (Farmer & Kashdan,
2012; Kashdan et al., 2011; Kashdan & Steger, 2006). A recent
meta-analysis found that the inverse relationship between SAD
and positive emotions could not be explained by the comorbidity
Todd B. Kashdan, Antonina S. Farmer, Leah M. Adams, Patty Ferssiz-
idis, and Patrick E. McKnight, Department of Psychology, George Mason
University; John B. Nezlek, Department of Psychology, College of Wil-
liam and Mary, University of Social Sciences and Humanities, Faculty in
Pozna
´
n, Poland.
This research was supported by the NIMH R21-MH073937 and the
Center for Consciousness and Transformation at George Mason University.
Correspondence concerning this article should be addressed to Todd B.
Kashdan, Department of Psychology, MS 3F5, George Mason University,
Fairfax, VA 22030. E-mail: tkashdan@gmu.edu
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Journal of Abnormal Psychology © 2013 American Psychological Association
2013, Vol. 122, No. 3, 000 0021-843X/13/$12.00 DOI: 10.1037/a0032733
1
between depression and SAD (Kashdan, 2007). Despite evidence
that low levels of positive emotions characterize the experiences of
people with SAD, researchers have yet to examine whether posi-
tive emotions during the course of everyday life offer incremental
validity in distinguishing individuals with and without diagnoses
of SAD above and beyond more traditional constructs.
Experiential Avoidance
Distinct from the experience of social anxiety is the regulation
of this emotional experience (Gross, Sheppes, & Urry, 2011).
Emotion regulation refers to attempts to alter the onset or experi-
ence of an emotion, or to modify the outward expression an
emotion (Cisler, Olatunji, Feldner, & Forsyth, 2010). When avoid-
ance of an anxiety provoking situation is impossible, people with
SAD may engage in experiential avoidance, as defined by efforts
to escape, avoid, alter, or conceal undesirable emotions and
thoughts (Hayes, Wilson, Gifford, Follette, & Strosahl, 1996).
Despite evidence that experiential avoidance may be an important
change mechanism in the treatment of SAD (Dalrymple & Herbert,
2007), few studies have investigated the role of experiential avoid-
ance in SAD.
Research on constructs related to experiential avoidance sup-
ports the contribution of this emotion regulation strategy to im-
paired well-being. For example, experience-sampling studies have
found people with elevated social anxiety to be more likely to
make attempts to conceal emotions (Farmer & Kashdan, 2012) and
to experience the fewest positive experiences on days when they
engage in this emotion regulation strategy (Kashdan & Steger,
2006). Furthermore, some theorists view the concealment of anx-
iety as a safety behavior that aims to minimize contact with
unpleasant experiences during social interactions (Voncken, Al-
den, & Bögels, 2006). When people with SAD rely on such safety
behaviors, they inadvertently contribute to the maintenance of their
social anxiety symptoms (Wells et al., 1995). Research is mixed as
to whether experiential avoidance decreases (Sloan, 2004) or in-
creases (Feldner, Zvolensky, Eifert, & Spira, 2003) physiological
arousal. Nevertheless, attempts to avoid or conceal anxious
thoughts and feelings in social situations hinder emotional pro-
cessing (particularly of disconfirmatory evidence), and, conse-
quently, prevent habituation to unpleasant situations (Butler et al.,
2003). Theorists have suggested that the transition from normative
to pathological social anxiety in the form of SAD occurs when
people are unwilling to experience naturally occurring anxious
feelings, and their efforts to manage anxiety are ineffective or
counterproductive (Herbert & Cardaciotto, 2005; Kashdan, Weeks,
& Savostyanova, 2011).
Expanding the Conceptualization of SAD: Experiential
Avoidance, Self-Control Depletion, and Positive
Emotions
Experimental studies have shown that experiential avoidance
increases cognitive load during stressful tasks (Hayes et al., 1996).
Rigid attempts to avoid anxious thoughts and feelings reduce
attention to competing reward cues in one’s immediate environ-
ment (Gross & John, 2003). There is reason to expect these
problems to be particularly pronounced in people with SAD,
because they are more likely to view themselves as undesirable
and inferior to interaction partners (Kashdan & Savostyanova,
2011). Indeed, the prospect of having undesirable characteristics
exposed for scrutiny by other people may initiate anxiety and
self-conscious thoughts and feelings (Moscovitch, 2009). In the
hope of protecting themselves from evaluation and reducing any
additional unpleasant thoughts and feelings, people with SAD
attempt to conceal any perceived deficiencies (Moscovitch &
Huyder, 2011) and avoid the expression of intense emotions that
might draw public exposure (Heimberg et al., 2010; Hofmann,
2007).
Engaging in cognitively demanding situations may lead to self-
control depletion, as defined by the exhaustion of a person’s
capacity to regulate attention, energy, and tolerance of distress
(Finkel et al., 2006; Vohs, Baumeister, & Ciarocco, 2005). People
have a limited amount of energy, attention, and self-control at any
given time (Baumeister, 2002), and the effort exerted by people
with SAD to manage the impressions they make on other people
during social interactions (Clark & Wells, 1995; Heimberg et al.,
2010) may drain these resources (Vohs et al., 2005). In turn,
people who have exhausted their self-regulatory resources are
likely to make decisions based on immediate rewards, such as the
temporary relief of escaping from an anxiety-provoking situation
(Baumeister & Vohs, 2007). In such a state, people with SAD may
be less able to respond to potentially rewarding social cues and less
likely to make progress toward desired goals, such as satisfying
their need to belong and achieving a sense of meaning in life
(Mallott, Maner, DeWall, & Schmidt, 2009; Stillman et al., 2009).
In effect, people with SAD not only view social situations as
particularly stressful but may also suffer from the additional stress
and exhaustion that result from relying on the counterproductive
strategy of experiential avoidance.
A growing body of research indicates that experiential avoid-
ance is associated with excessive social anxiety and that this
emotion regulation strategy might account for the deficits in pos-
itive emotions and rewarding social experiences linked to exces-
sive social anxiety (Kashdan, Barrios, Forsyth, & Steger, 2006;
Kashdan & Breen, 2008; Kashdan & Steger, 2006; Rodebaugh &
Heimberg, 2008; Rodebaugh & Shumaker, 2012). Furthermore,
devoting finite effort and energy to alleviate momentary discom-
fort through experiential avoidance might not only interfere with
enjoyment of social interactions but also contribute to self-control
depletion, and consequently steal time and effort from other plea-
surable and meaningful life pursuits. We incorporated this per-
spective on pathological social anxiety, spanning experiential
avoidance, self-control depletion, and positive emotions into a
study of how to identify individuals with SAD using a dynamic,
ecologically valid methodology.
The Present Study
The primary goal of the present study was to determine if
positive emotions, experiential avoidance, and/or self-control de-
pletion aid in classifying individuals as meeting diagnostic criteria
for the generalized subtype of SAD. Nongeneralized SAD (when
feared situations are limited to public speaking or performing in
front of other people) fails to encompass the interpersonal dynam-
ics of interest that generate positive emotions (Hughes et al.,
2006). We collected data from adults diagnosed as having the
generalized subtype of SAD and a healthy comparison group,
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2
KASHDAN ET AL.
matched on several demographic characteristics. With these two
groups, we assessed the types of events expected to be problematic
for people with SAD—social interactions during the course of
daily life. Instead of relying on retrospective reporting in surveys
or interviews, we collected event-contingent data with an
experience-sampling approach. Participants recorded face-to-face
social interactions that lasted at least 10 minutes using hand-held
electronic diaries over the course of 2 weeks. Experience sampling
provided a tool to examine social events and experiences in their
natural, spontaneous context by minimizing the amount of time
between the actual event and the recall of the event to lessen the
influence of information processing biases (Reis & Gable, 2000).
This study aimed to empirically test recent theoretical models of
SAD (Cisler et al., 2010; Heimberg et al., 2010; Kashdan et al.,
2011; Moscovitch, 2009), and to improve our understanding of the
factors responsible for the shift from normative anxiety in social
situations to the experiences of people with a SAD diagnosis. Our
primary hypothesis was that low positive emotions, an overreli-
ance on experiential avoidance, and self-control depletion in the
context of everyday social interactions, would distinguish individ-
uals with SAD from a healthy comparison group above and be-
yond the more widely studied constructs of negative emotions,
social anxiety, and feelings of belonging. To examine the speci-
ficity of these relationships, we controlled for the presence of
depressive disorders or other comorbid anxiety conditions.
Method
Participants
Our initial sample consisted of 84 participants (52 women) from
Northern Virginia. Forty-one participants were diagnosed with
Social Anxiety Disorder (SAD), generalized subtype, and 43
(51%) were a healthy control group with no psychiatric disorders.
We matched groups on gender, race, marital status, and age (see
Procedures). Participants with SAD were not selected if they only
met criteria for the nongeneralized subtype, had a psychotic dis-
order, or qualified for a substance use disorder, but other comor-
bidities were allowed. All participants were native English speak-
ers. Nine participants were excluded from analyses because they
did not provide daily social interaction data. This led to 38 par-
ticipants with generalized SAD diagnoses (25 women) and 38
healthy controls (24 women). Excluded participants did not sig-
nificantly differ from included participants on study variables.
Sample details are reported in Table 1. Notably, 15 of the 38 SAD
participants had no comorbidities, and eight were receiving treat-
ment, but these variables did not predict experience-sampling,
trait, or compliance measures (ps ⬎ .10).
Procedure
We recruited participants via flyers and online community ad-
vertisements. Following this, we conducted a phone screen with
potential participants following an informed consent procedure.
Trained research assistants used a structured questionnaire to as-
sess for social anxiety, generalized anxiety disorder, depression,
suicidality, and psychotic symptoms. We provided referrals as
needed following lethality assessments. Potential participants with
evidence of generalized social anxiety fears were retained for
further assessment.
Participants provided informed consent and completed demo-
graphic and personality questionnaires and then clinical psychol-
ogy doctoral students administered the Structured Clinical Inter-
view for DSM–IV Axis I Disorders (SCID; First, Spitzer, Gibbon,
& Williams, 2002) to assess for anxiety, mood, substance use,
eating, and psychotic disorders. 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, this condition had to
be the principal or most severe diagnosis. Interrater reliability for
SAD diagnoses was calculated, resulting in excellent agreement
(Cohen’s ⫽.87). Upon recruiting a participant with SAD, we
used demographic information (race/ethnicity, gender, and age
within 8 years) to find a comparable healthy control match. We did
this by using targeted advertisements as necessary. This matching
system was successful for 82% of our sample, and the final groups
did not differ significantly on these variables (see Table 1).
To provide experience-sampling data, we gave participants
hand-held computers (Palm Pilot Z22), programmed using the
Purdue Momentary Assessment Tool (PMAT; Weiss, Beal, Lucy,
& MacDermid, 2004). Participants received a 1.5-hr introductory
session, including practice with self-initiated recording of every
face-to-face social interaction lasting at least 10 minutes. We
defined a social interaction as “any situation involving you and one
or more other people in which the behavior of each person is
affected by the behaviors of the others.” We instructed participants
to complete the records as soon as possible after each interaction.
Research assistants described what did (e.g., conversation) and did
not (e.g., quietly watching a movie) qualify as social interactions,
and discussed survey items until participants felt comfortable with
the procedure. Definitions and procedures were based on 35 years
of daily diary research (Nezlek, 2012).
Two days into data collection, we contacted participants to
troubleshoot. Following this, we sent multiple reminder e-mails
each week to emphasize compliance, confidentiality, and data
coding details (i.e., time-and-date stamped entries), and we de-
briefed participants at the end of the 2-week assessment period. To
maximize compliance, participants received a minimum payment
of $165 and could earn up to $50 in bonus money. The entire study
consisted of three parts—social interaction records, end of day
records, and random prompts—with only the first being relevant to
this study. Participants received 50¢ for each completed random
prompt record and end-of-day record, plus $10 for each uninter-
rupted calendar week. Additionally, each end-of-day assessment
included a reminder about social interaction entries. Moreover, we
kept all measures brief to maintain participant motivation and
maximize responses—a strategy that does not sacrifice reliability
or validity (e.g., Nezlek, 2012).
Trait Measures
Social Interaction Anxiety Scale. This 20-item scale (SIAS;
Mattick & Clarke, 1998) measured fear and avoidance of social
interactions due to concerns about being scrutinized by other
people. Participants responded to items using a 5-point Likert scale
ranging from 0 (not at all characteristic of me)to4(extremely
characteristic of me), with higher scores representing greater so-
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3
DISTINGUISHING DISORDER
cial anxiety. This scale demonstrated strong reliability and validity
across clinical and community samples (Brown et al., 1997; Heim-
berg et al., 1992). We removed three reverse scored items, which
have been shown to slightly reduce reliability and validity (Rode-
baugh et al., 2011; Rodebaugh, Woods, & Heimberg, 2007). In our
sample, reliability was identical using the 17- and 20-item versions
(␣⫽.94), with a .997 (p ⬍ .001) correlation between the two
versions. We used the 17-item SIAS-Straightforward (SIAS-S)
scores for subsequent analyses; however, results were virtually
identical when including reverse-score items.
The SAD group had greater social anxiety (M ⫽ 43.44, SD ⫽
8.91) than healthy controls (M ⫽ 8.70, SD ⫽ 6.31), t(74) ⫽ 19.60,
p ⬍ .001, d ⫽ 4.56. The means for our SAD group were com-
mensurate with clients in treatment for SAD (M ⫽ 43.93, SD ⫽
11.84; Rodebaugh et al., 2011). We also compared our SAD
sample with established norms on the 20-item SIAS. Of our SAD
sample, 97.4% of participants scored above the optimal cut-off
score of 34 (in terms of sensitivity and specificity) for distinguish-
ing people with SAD from a healthy community comparison group
(Brown et al., 1997).
Beck Depression Inventory-II. Severity of depressive symp-
toms was assessed using this 21-item questionnaire (BDI-II; Beck,
Steer, & Brown, 1996). Participants responded to items on a scale
from 0 to 3 to reflect their experiences over a 2-week period, with
higher scores representing greater depressive symptoms. Our sam-
ple had acceptable internal reliability (␣⫽.94). The SAD group
had significantly greater BDI-II scores than healthy controls, M ⫽
16.71, SD ⫽ 10.59 vs. M ⫽ 2.87, SD ⫽ 3.06; t(74) ⫽ 7.74, p ⬍
.001, d ⫽ 1.80.
Acceptance and Action Questionnaire-II. This 7-item scale
(AAQ-II; Bond et al., 2011) assessed experiential avoidance, or the
inability to accept aversive internal experiences and pursue impor-
tant life goals despite the presence of these experiences. Partici-
pants used a 7-point scale from 1 (never true)to7(always true)
with higher scores reflecting a greater tendency to avoid unpleas-
ant experiences. This scale has strong reliability and validity across
clinical and community samples (Bond et al., 2011). Prior work
has shown that experiential avoidance as measured by the AAQ-II
is related to but distinct from anxiety sensitivity, contributing
unique variance to the prediction of anticipatory anxiety and
Table 1
Demographic and Diagnostic Information by Participant Group
Variable
Group
Difference testControl
a
SAD
a
Diagnosis 0.0%
Social anxiety disorder 0.0% 100%
Major depressive disorder 0.0% 21.1%
Dysthymia 0.0% 13.2%
Panic disorder 2.6% 5.3%
Post traumatic stress disorder 0.0% 13.2%
Generalized anxiety disorder 0.0% 5.3%
Obsessive-compulsive disorder 5.3% 5.3%
Specific phobia 28.9%
Age (M, SD) 29.39 (10.29) 27.29 (6.03) t(74) ⫽ 1.09, p ⫽ .280
Gender (% women) 65.8% 63.2%
2
(1) ⫽ 0.06, p ⫽ .811
Race-Ethnicity
2
(5) ⫽ 2.89, p ⫽ .717
African American 28.9% 18.4%
Asian/Asian American 2.6% 5.3%
Caucasian/White 52.6% 50.0%
Hispanic/Latino 7.9% 13.2%
Middle Eastern 0.0% 2.6%
Other 7.9% 10.5%
Education
2
(4) ⫽ 3.65, p ⫽ .455
High school or less 2.6% 13.2%
Some college 36.8% 28.9%
Associate’s degree 5.3% 7.9%
Bachelor’s degree 36.8% 28.9%
At least some graduate level 18.4% 21.1%
Family income
2
(3) ⫽ 4.38, p ⫽ .223
⬍$15,000 10.5% 15.8%
$15,000–$49,999 26.3% 44.7%
$50,000–$79,999 26.3% 18.4%
⬎$80,000 36.8% 21.1%
Relationship status
2
(4) ⫽ 4.05, p ⫽ .400
Single 65.8% 63.2%
Cohabitating 21.1% 13.2%
Married 10.5% 10.5%
Divorced/Separated 0.0% 7.9%
Other 2.6% 5.3%
On psychoactive medications 2.6% 21.1%
2
(1) ⫽ 6.18, p ⫽ .013
Note. SAD ⫽ Social Anxiety Disorder.
a
n ⫽ 38.
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4
KASHDAN ET AL.
functional impairment in clients with anxiety disorders (Kämpfe et
al., 2012). Our sample had acceptable internal reliability (␣⫽.92).
The SAD group had significantly greater scores on the AAQ-II
than healthy controls (M ⫽ 24.38, SD ⫽ 5.29 vs. M ⫽ 11.76, SD ⫽
3.33; t(73) ⫽ 12.39, p ⬍ .001, d ⫽ 2.90).
1
Experience-Sampling Social Interaction Measures
Social anxiety. To assess social anxiety during interactions,
participants answered three items (from Kashdan & Steger, 2006):
“I worried about what other people thought of me,” “I was afraid
that others did not approve of me,” and “I was worried that I would
say or do the wrong things.” Participants used a 5-point response
scale ranging from 1 (very slightly or not at all) to 5 (extremely).
All social interaction measures used this response scale.
Experiential avoidance. Experiential avoidance during inter-
actions were measured with four items: “How upset and bothered
were you about anxiety-related feelings or thoughts?”, “How much
did you try to hide and/or conceal your anxiety from others?”,
“How much did you try to control your anxiety-related feelings or
thoughts?”, and “To what degree did you give up saying or doing
what you like (or mattered to you) in order to control and manage
anxiety?”
Emotions. Participants rated how much eight emotional ad-
jectives described them “right now” during social interactions.
Negative emotions were anxious/nervous, angry, sad, and slug-
gish. Positive emotions were content, relaxed, enthusiastic, and
joyful.
Feelings of belonging. How much people felt their need to
belong was satisfied during interactions was measured with two
items: “I felt close and connected to others during the interaction”
and “I felt accepted by others during the interaction.”
Self-control depletion. Mental and physical resource deple-
tion during interactions were measured with two items: “I feel
mentally exhausted” and “Right now, it would take a lot of effort
for me to concentrate on something” (from Ciarocco, Twenge,
Muraven, & Tice, 2010).
Participant Compliance
Participants described an average of 9.83 social interactions
(SD ⫽ 4.63), over 11.45 days (SD ⫽ 4.80). There were no
significant differences between the SAD and control groups on
number of social interactions (M ⫽ 10.11, SD ⫽ 5.41 vs. M ⫽
9.55, SD ⫽ 3.79; t(74) ⫽ 0.52, p ⫽ .606, d ⫽ 0.12) and days the
diary was maintained (M ⫽ 11.45, SD ⫽ 4.83 vs. M ⫽ 11.45, SD
⫽ 4.84; t(74) ⫽ 0.00, p ⬎ .99, d ⫽ 0.00). Furthermore, we used
time stamps of social interaction entries to ensure that participants
did not enter multiple social interactions in one sitting. All but two
entries (99.7%) were more than 25 minutes after the prior entry.
2
Results
The social interaction diary data comprised a hierarchically
nested data set, with observations (interactions) nested within
persons. Accordingly, the data were analyzed with a series of
multilevel models using HLM 6.08 (Raudenbush, Bryk, Cheong,
& Congdon, 2000). Our analyses followed guidelines and proce-
dures described by Nezlek (2011, pp. 9 –34).
Daily Measures: Descriptive Data, Reliability, and
Validity
We examined the reliability of experience-sampling measures
with three-level unconditional models with items nested within
interactions, and interactions nested within people. In the model
equations below, there were i items nested within j interactions
nested with k participants. In such an analysis, the reliability of the
Level 1 intercept is the functional equivalent of an interaction level
Cronbach’s alpha, adjusted for differences among interactions and
among people.
Item Level 1 : Y
ijk
⫽
0jk
⫹ c
ijk
Interaction Level 2 :
0jk
⫽
00k
⫹ r
0jk
Person Level 3 : 
00k
⫽␥
000
⫹ u
00k
Each of the social interaction measures had acceptable reliabil-
ity (see Table 2). We computed social interaction measures as the
mean response to the items for each scale. All HLM analyses
presented below had interactions nested (n ⫽ 742) within persons
(n ⫽ 76). Table 2 also contains the basic multilevel descriptive
statistics of each measure: mean, standard error, and two variance
estimates: between- and within-person.
To evaluate the validity of our two primary experience-sampling
measures (social anxiety and experiential avoidance), we exam-
ined relationships between the participants’ interaction scores and
scores on corresponding trait measures (Nezlek, 2007). For exam-
ple, we modeled social anxiety during social interactions as a
function of the SIAS-S:

0j
⫽␥
0
⫹␥
1
共
SIAS-S
兲
⫹ u
j
.
We estimated validity by comparing the between-person vari-
ance of social anxiety in the unconditional model (0.65) with the
residual between-person variance from the model above (0.29).
This 55% reduction in variance corresponds to a correlation of .74
(square root of .55), B ⫽ .03, SE ⫽ .004, t(74) ⫽ 8.20, p ⬍ .001.
As evidence of divergent validity, when we included the SIAS-S
and the BDI-II as predictors in the same model, the experience-
sampling measure of social anxiety was positively related to the
SIAS-S, B ⫽ .02, SE ⫽ .01, t(73) ⫽ 4.36, p ⬍ .001, but not the
BDI-II, B ⫽ .02, SE ⫽ .01, t(73) ⫽ 1.51, p ⫽ .135.
For our interaction level measure of experiential avoidance, the
AAQ-II was used as a trait predictor. The between-person variance
of experiential avoidance from the unconditional model was 0.46.
The residual variance after including the AAQ-II was 0.21—a
reduction of 56%, corresponding to a correlation of .75, B ⫽ .07,
SE ⫽ .01, t(73) ⫽ 8.77, p ⬍ .001. When we included the AAQ-II
and SAD diagnostic status as person level predictors in the same
model, the AAQ-II remained significantly related to the
experience-sampling measure of experiential avoidance, B ⫽ .04,
SE ⫽ .01, t(72) ⫽ 2.66, p ⫽ .010, after controlling for the effect
of SAD diagnosis, B ⫽ .25, SE ⫽ .11, t(72) ⫽ 2.17, p ⫽ .033.
1
One participant in the SAD group had missing data for the AAQ-II due
to a technical malfunction.
2
These two social interaction entries were completed within 10 minutes
of the prior entry and represented a change in activity during an elongated
social interaction (i.e., within instruction parameters).
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5
DISTINGUISHING DISORDER
These data provide support for the construct specificity for our
experience-sampling measure of experiential avoidance.
3
Notably,
our measure is specific to experiential avoidance during social
interactions, although the trait measure is not restricted to a par-
ticular context.
Differences Between SAD and Control Group in Social
Interaction Experiences
We examined relationships between SAD diagnostic status and
our social interaction measures with two-level models. Social
interaction measures were the dependent measures at Level 1 (in
separate models), and SAD diagnostic status was a predictor at
Level 2. SAD was contrast-coded (1 ⫽ SAD, ⫺1 ⫽ Control) and
entered uncentered in the following model:
Interaction Level 1 : Y
ij
⫽
0j
⫹ r
ij
.
Person Level 2 : 
0j
⫽␥
00
⫹␥
01
共
SAD
兲
⫹ u
0j
Initially, we included the number of social interactions a person
described as a Level 2 covariate. Including this variable did not
influence the findings, which was not surprising, given that SAD
and number of interactions were unrelated. Thus, this covariate
was removed.
As summarized in Table 3, the SAD group reported more social
anxiety, negative emotion, experiential avoidance, and self-control
depletion in social interactions compared with the control group.
The SAD group also reported less positive emotion and feelings of
belonging.
To address construct specificity, we conducted additional anal-
yses controlling for the presence of comorbid mood and anxiety
disorders. We created contrast-coded variables to reflect whether
participants met diagnostic criteria for any other anxiety disorder
or mood disorder. We then entered these two variables, uncen-
tered, as additional Level 2 predictors.
For all outcomes, the SAD effects controlling for comorbid
conditions were similar to the effects found without these covari-
ates—as before, all SAD effects were significant at p ⬍ .001.
Controlling for mood and anxiety disorder comorbidity, SAD
remained directly related to our experience-sampling measures of
social anxiety (B ⫽ .51, SE ⫽ .10, t(72) ⫽ 5.03, p ⬍ .001),
negative emotions (B ⫽ .21, SE ⫽ .05, t(72) ⫽ 3.76, p ⫽ .001),
experiential avoidance (B ⫽ .49, SE ⫽ .08, t(72) ⫽ 5.94, p ⬍
.001), and self-control depletion (B ⫽ .37, SE ⫽ .10, t(72) ⫽ 3.74,
p ⫽ .001), and inversely related to positive emotions (B ⫽⫺.50,
SE ⫽ .08, t(72) ⫽⫺6.61, p ⬍ .001) and feelings of belonging
(B ⫽⫺.38, SE ⫽ .08, t(72) ⫽⫺4.76, p ⬍ .001). In contrast,
anxiety disorder comorbidity was not significantly related to any
social interaction measure (ps ⬎ .25), and comorbid depressive
disorders were significant only in the prediction of negative emo-
tions (B ⫽ .41, SE ⫽ .13, t(72) ⫽ 3.11, p ⫽ .003), positive
emotions (B ⫽⫺.59, SE ⫽ .17, t(72) ⫽⫺3.51, p ⫽ .001), and
feelings of belonging (B ⫽⫺.58, SE ⫽ .23, t(72) ⫽⫺2.58, p ⫽
.012). These results support the specificity of SAD in relation to
social interaction measures of social anxiety and experiential
avoidance.
Added Value of Experiential Avoidance, Self-Control
Depletion, and Positive Emotions in Predicting SAD
Diagnosis
Multilevel analyses. Following preliminary analyses, we ex-
amined our primary question about the added value of experiential
avoidance, self-control depletion, and positive emotions during
social interactions to understand SAD diagnoses. Would relation-
ships between these variables and SAD diagnosis remain after
controlling for variance attributable to more commonly used mea-
sures of social anxiety, negative emotions, and feelings of belong-
ing? To answer this question, we first conducted a series of
multilevel analyses with experiential avoidance, self-control de-
pletion, and positive emotions as dependent measures. We in-
cluded SAD diagnosis as a Level 2 predictor and the following as
simultaneous Level 1 predictors: social anxiety, negative emo-
tions, and feelings of belonging. Social anxiety, negative emotions,
and feelings of belonging were grand-mean centered to control for
individual differences (Nezlek, 2011, pp. 13–18).
Controlling for social anxiety, negative emotions, and feelings
of belonging in social interactions, the relationship between SAD
diagnosis and experiential avoidance remained significant (B ⫽
.11, SE ⫽ .04, t(74) ⫽ 3.19, p ⫽ .003), as did the relationship
between SAD and positive emotions (B ⫽⫺.26, SE ⫽ .05, t(74) ⫽
3
Supporting the validity of the experience-sampling measure of expe-
riential avoidance, the AAQ-II was a significant predictor, B ⫽ .04, t ⫽
2.71, p ⫽ .009, even after accounting for the variance attributable to the
SIAS-S, B ⫽ .02, t ⫽ 2.56, p ⫽ .013.
Table 2
Multilevel Descriptive Statistics for Social Interaction Measures
Measure M (SE)
Variance
ICC ReliabilityWithin Between
Social anxiety 1.81 (.10) .63 .65 .50 .84
Negative emotions 1.55 (.05) .25 .17 .41 .85
Positive emotions 2.87 (.09) .62 .55 .31 .87
Belonging 3.56 (.08) .95 .42 .47 .78
Experiential avoidance 1.72 (.08) .55 .46 .45 .87
Self-control depletion 1.70 (.08) .67 .43 .40 .83
Note. Intraclass correlation coefficients (ICC) represent the proportion of
between-person variance to total variance.
Table 3
Differences Between Social Anxiety Disorder (SAD) and Healthy
Control Groups for Social Interaction Measures
Measure bSE t
Estimated means (SE)
Control SAD
Social anxiety .51 .08 6.71 1.30 (.11) 2.32 (.11)
Negative emotions .24 .04 5.76 1.30 (.06) 1.79 (.06)
Positive emotions ⫺.53 .07 ⫺8.09 3.41 (.09) 2.34 (.09)
Belonging ⫺.41 .07 ⫺5.95 3.97 (.10) 3.15 (.10)
Experiential avoidance .48 .06 8.11 1.23 (.09) 2.19 (.09)
Self-control depletion .37 .07 5.32 1.32 (.10) 2.06 (.10)
Note. Differences and estimated means were computed with two-level
HLM models, where SAD predicted each outcome measure separately. All
t-ratios have 74 df and were significantly different from 0 at p ⬍ .001.
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6
KASHDAN ET AL.
⫺4.84, p ⬍ .001), but the relationship between SAD and self-
control depletion was no longer statistically significant (B ⫽ .05,
SE ⫽ .03, t(74) ⫽ 1.41, p ⫽ .16). These results suggest that the
association of SAD with greater experiential avoidance and less
positive emotions in everyday social interactions could not be
explained by variance attributable to social anxiety, negative emo-
tions, and feelings of belonging in social interactions.
Classification analysis. We supplemented the prior multi-
level analyses with a classification analysis. Following previous
work on diagnostic classification (e.g., Nock & Kessler, 2006), we
used hierarchical logistical regression to determine if experiential
avoidance, positive emotions, and self-control depletion improve
the accuracy of predicting SAD diagnoses beyond the contribu-
tions of social anxiety, negative emotions, and feelings of belong-
ing. To conduct these analyses, we aggregated within-person so-
cial interaction measures into between-person variables. At Step
One, we included social anxiety, negative emotions, and feelings
of belonging during social interactions as predictors of SAD di-
agnosis. At Step Two, we added experiential avoidance, positive
emotions, and self-control depletion during social interactions as
predictors.
As reported in Table 4, at Step One, we found evidence that both
social anxiety and feelings of belongingness during daily social
interactions were significant predictors of SAD diagnostic cate-
gory (R
2
⫽ .61). Specifically, greater social anxiety and less
belonging during daily social interactions helped to distinguish
participants with SAD from our healthy comparison group. This
finding provides additional support for the validity of our
experience-sampling measure of social anxiety. At Step One of the
model, with experience-sampling measures of social anxiety, neg-
ative emotions, and belonging as predictors, 81.6% of participants
with SAD were correctly classified (sensitivity) and 84.2% of
participants without SAD were correctly classified (specificity).
At Step Two, experiential avoidance and positive emotions
during social interactions predicted SAD diagnostic status above
and beyond the constructs in the prior step, with a 17% incremental
improvement in variance explained (R
2
⫽ .77). As shown in Table
4, greater experiential avoidance and less positive emotions during
social interactions added to the prediction of SAD diagnoses
beyond the contributions of the more routinely assessed constructs.
Self-control depletion did not significantly add to the prediction of
SAD diagnosis and neither social anxiety nor feeling of belonging
remained significant. Negative emotions emerged as a significant
predictor in the final model, though in the opposite direction.
Providing additional support, upon inclusion of comorbid depres-
sive and anxiety conditions as additional predictors, experiential
avoidance (B ⫽ 7.63, SE ⫽ 3.00, Wald ⫽ 6.45, p ⫽ .01, OR ⫽
2057) and positive emotions (B ⫽⫺3.68, SE ⫽ 1.69, Wald ⫽
4.77, p ⫽ .029, OR ⫽ 0.03) continued to predict SAD diagnostic
status.
4
In sum, the odds of having SAD increased more than 163 times
with every one-point increase in the average level of experiential
avoidance reported in social interactions. The odds increased more
than 33 times with every one-point decrease in the average positive
emotions reported. As for the predictive value of our model, we
found evidence of high sensitivity (classifying 92.1% of individ-
uals with SAD) and specificity (classifying 86.8% of individuals
from the healthy control group). We found evidence for a strong
classification model where 89.5% of our cases were correctly
classified (68 out of 76). This represents an 11% improvement in
sensitivity and a 3% increase in specificity over a model with only
social anxiety, negative emotions, and belonging as predictors.
Discussion
The results of this experience-sampling study support theories
suggesting that, in addition to elevated anxiety in social interac-
tions, other characteristics distinguish the social experiences of
individuals with SAD. These characteristics include diminished
positive emotions (Kashdan, 2007; Watson et al., 1988) and ex-
periential avoidance, involving attempts to alter, avoid, or conceal
4
We ran separate logistic regression models for each discrete negative
and positive emotion, respectively. The only negative emotion item that
was statistically significant after including the Step Two predictors was
anger, 〉⫽⫺3.19, SE ⫽ 1.32, Wald ⫽ 5.86, p ⫽ .015, OR ⫽ .041. For
positive emotions, significant predictors included relaxed, 〉⫽⫺1.75,
SE ⫽ .83, Wald ⫽ 4.51, p ⫽ .034, OR ⫽ .174, content, 〉⫽⫺1.78, SE ⫽
.82, Wald ⫽ 4.78, p ⫽ .029, OR ⫽ .168, and enthusiasm, 〉⫽⫺1.88,
SE ⫽ .66, Wald ⫽ 8.07, p ⫽ .005, OR ⫽ .153, with joy showing a trend
effect, 〉⫽⫺1.11, SE ⫽ .61, Wald ⫽ 3.32, p ⫽ .069, OR ⫽ .330.
Table 4
Hierarchical Logistic Regression Analyses Predicting Social Anxiety Disorder (SAD) Diagnostic Status From Social
Interaction Measures
Predictor BSEWald POR 95% CI R
2
Step One .605
Social anxiety 1.61 0.73 4.82 .028 5.00 [1.19, 21.04]
Negative emotions 0.81 1.11 0.53 .466 2.24 [0.26, 19.70]
Belonging ⴚ1.86 0.62 9.03 .003 0.16 [0.05, 0.52]
Step Two .772
Social anxiety 0.41 0.96 0.19 .666 1.51 [0.23, 9.82]
Negative emotions ⴚ4.62 2.24 4.23 .040 0.01 [0.00, 0.80]
Belonging ⫺0.60 0.79 0.57 .451 0.55 [0.12, 2.60]
Self-control depletion ⫺0.63 1.07 0.35 .556 0.53 [0.07, 4.36]
Experiential avoidance 5.10 1.92 7.07 .008 163.85 [3.82, 7036.34]
Positive emotions ⴚ3.51 1.27 7.69 .006 0.03 [0.003, 0.36]
Note. SE ⫽ standard error; OR ⫽ odds ratio; CI ⫽ confidence interval. Bolded terms reflect a significant contribution to the prediction model. For the
full model, 92.1% of participants with SAD were correctly classified (sensitivity) and 86.8% of participants without SAD were correctly classified
(specificity).
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7
DISTINGUISHING DISORDER
anxious thoughts and feelings (Herbert & Cardaciotto, 2005; Kash-
dan et al., 2006). We found that individuals with SAD, compared
with healthy controls, could be differentiated by their attenuated
positive emotions and increased reliance on experiential avoidance
during social interactions in daily life. These relationships re-
mained after controlling for the variance attributable to more
routinely studied constructs of negative emotions, social anxiety,
and feelings of belonging and after accounting for the presence of
depressive disorders and comorbid anxiety conditions.
In prior attempts to distinguish individuals with and without
SAD, researchers relied on a narrow band of predictors. Nearly all
published studies on the classification of SAD have focused on
how well trait measures of social anxiety are able to identify SAD
when present (e.g., Mennin et al., 2002). In this study, we extended
recent research linking social anxiety to emotion regulation diffi-
culties and diminished/impaired positive experiences (for reviews,
see Kashdan et al., 2011; Watson & Naragon-Gainey, 2010). By
using a community sample of healthy adults and adults who met
diagnostic criteria for SAD, we provided evidence that experiential
avoidance and a dearth of positive emotions during social encoun-
ters offer improved predictive validity for SAD diagnosis beyond
anxiety during naturalistic social interactions.
To our knowledge, this was the first study to examine if expe-
riences during naturally occurring social interactions can distin-
guish people with and without SAD. Prior work on social anxiety
and both experiential avoidance and positive emotions has been
primarily limited to cross-sectional (Brown, Chorpita, & Barlow,
1998; Kashdan et al., 2006; Watson et al., 1988) or two-wave
(Kashdan & Breen, 2008) designs in which people aggregated
experiences across time and context using traditional global ques-
tionnaires. A small number of studies supplemented these ap-
proaches by examining how people with SAD respond in a labo-
ratory setting (Mallott et al., 2009; Taylor & Amir, 2012; Wallace
& Alden, 1997). Using event-contingent experience-sampling
methods with a carefully diagnosed sample, we were able to show
that the types of feelings, beliefs, and behaviors people with SAD
report on questionnaires, during interviews, or in laboratory ob-
servations also occur in real-world settings.
By asking participants to rate experiences as soon as possible
following each social interaction lasting over 10 minutes, our
approach circumvents some of the recall bias and distortion asso-
ciated with retrospective reports, allowing for greater ecological
validity over methods that rely on aggregated remembered expe-
riences or artificial contexts (Csikszentmihalyi & Larson, 1987;
Scollon, Kim-Prieto, & Diener, 2003). For a dynamic, contextu-
alized approach, we asked participants to report on their experi-
ences over the course of several weeks with electronic diaries, and
all entries were time-and-date stamped. This procedure ensured
that participants reported on their social interactions and associated
experiences over a range of social encounters, not merely recalling
a number of interactions on a single assessment occasion.
Within-person effects (with experience-sampling approaches)
and between-person effects (with item-correlations among trait
measures) are conceptually distinct (e.g., Affleck, Zautra, Tennen,
& Armeli, 1999). As evidence of this, we found that social anxiety
in the context of everyday social interactions significantly distin-
guished individuals with and without SAD diagnoses, but this
effect did not hold after the inclusion of positive emotions, expe-
riential avoidance, and self-control depletion into analytic models.
One explanation for this result is that the intensity/frequency of
social anxiety is less critical to pathology than the unwillingness to
remain in contact with unwanted anxious thoughts and emotions
(i.e., experiential avoidance). These results are consistent with
laboratory studies showing that shy participants without SAD
experience levels of social anxiety during conversations with
strangers as people with SAD (Heiser, Turner, Beidel, &
Roberson-Nay, 2009). Other researchers have shown that positiv-
ity impairments in daily life only occur when people with high trait
social anxiety both experience high social anxiety and tend to
suppress these anxious reactions on the same day (Kashdan &
Steger, 2006), suggesting that functional impairment hinges on the
co-occurrence of anxiety and experiential avoidance.
Our finding that experiential avoidance outperformed social
anxiety in distinguishing people with SAD demonstrates that so-
cial anxiety is more than just a collection of self-reported distress.
Notably, the very large odds ratio for experiential avoidance
(OR ⫽ 163.85) as a predictor of diagnostic status is a function of
the near absence of experiential avoidance in the healthy control
group. This is likely due to the healthy control group generating
and regulating emotions differently in everyday social interactions
compared with the SAD group. Further research might examine
the use of different emotion regulation strategies during social
interactions to better understand this effect.
Prior research has shown that people with SAD tend to suppress
the expression of both negative emotions (Erwin, Heimberg, Sch-
neier, & Liebowitz, 2003) and positive emotions (Turk, Heimberg,
Luterek, Mennin, & Fresco, 2005). Other studies suggest that
people with SAD are more likely to act in an unassertive, submis-
sive manner (Hopko, McNeil, Zvolensky, & Eifert, 2002). Based
on these findings, we suspect that healthy adults in the community
may differ from people with SAD in their willingness to have
emotionally charged conversations. This would explain our seem-
ingly unusual finding that after accounting for experiential avoid-
ance, people with SAD could be distinguished from healthy con-
trols by the presence of less negative emotions in their everyday
social interactions. Given that people with SAD fear the possibility
of having their perceived deficiencies scrutinized and believe that
visible anxiety is a sign of weakness, then experiential avoidance
(of negative thoughts and feelings) appears to be a useful self-
protection strategy. Concealing the expression of perceived defi-
ciencies becomes a safeguard against the feared consequences
linked to SAD (Alden & Taylor, 2011). The unfortunate by-
product of experiential avoidance is that this biased allocation of
attention limits access to rewards, as shown by the deficient
generation of positive emotions in the present study (extending
prior work on positivity deficits; Kashdan et al., 2011).
Separating the generation of emotions from emotion regulation
is important when contemplating the design of future studies on
moment-to-moment dynamic processes that contribute to the de-
velopment and maintenance of SAD. We chose to use experience
sampling to best capture naturalistic experiences while maintain-
ing some level of measurement control. Despite these efforts, our
experience-sampling procedure might have missed crucial infor-
mation about how people with SAD navigate their social world.
First, although we assessed experiential avoidance, we did not
inquire about specific safety behaviors to minimize contact with
experiences (e.g., fidgeting, averting eye contact). These and other
microlevel processes in everyday contexts may provide additional
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8
KASHDAN ET AL.
insights into the phenomenology of SAD. Second, people with
SAD tend to avoid the very situations that invoke anxiety for them.
We did not gather data about social opportunities that were
avoided or interactions that ended quickly. The broader tendency
to avoid discomfort may explain in part why we found such a large
effect for experiential avoidance within social interactions. Simi-
larly, the intentional avoidance of particularly anxiety-provoking
situations that would be mentally exhausting might explain why
we did not find a significant effect of self-control depletion in
classifying people with SAD.
Refined methodologies can evaluate the extent to which people
with SAD avoid/escape social activities and unwanted distress in
everyday life as it naturally unfolds. Future studies can explicitly
ask about briefer interactions (e.g., where someone escapes within
seconds of contact with another person), use of e-mail and texting
to avoid face-to-face encounters, and other tactics to prevent feared
interactions (e.g., taking different routes to a destination to avoid
people). Nevertheless, people with emotional disorders such as
SAD are often unaware of the extent of their behavioral avoidance
and monitoring may change behavior patterns.
Although our naturalistic data collection process had many
benefits, there are limitations worthy of future correction. First,
social interaction episodes involve at least two people, but we only
collected data from a single person. Future studies should consider
dyadic data collection for behavioral assessment reports (e.g.,
capturing a lack of responsiveness to another person’s self-
disclosure). Second, our participants sometimes recorded social
interactions after they occurred, leading to a degree of retrospec-
tive interpretation. The screening of time and date stamps ad-
dressed some of these concerns, but future research ought to ensure
that participants enter data as close as possible to the triggering
events (e.g., by using participants’ own mobile phones for ease of
data entry). Third, we did not test other relevant theoretical models
(e.g., estimates of the probability and cost of social blunders,
rumination, and fear of positive evaluation) due to response burden
concerns. Future work can expand the current findings with inno-
vative experimental, longitudinal, and intervention designs.
Our findings support an expanding conceptualization of SAD
where both negative and positive emotional reactions to social
events, and an overreliance on attempts to avoid anxious thoughts
and feelings during social events help differentiate individuals
with SAD from healthy adults in the community. Clinicians might
consider expanding the explicit target of interventions for SAD to
include the reduction of experiential avoidance and increase of
positive experiences (Alden & Taylor, 2011; Dalrymple & Her-
bert, 2007).
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Received October 12, 2012
Revision received March 20, 2013
Accepted March 25, 2013 䡲
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