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This study examines relationships between emotion beliefs and emotion regulation strategy use among people with social anxiety disorder (SAD) and a psychologically healthy control group. Using experience-sampling methodology, we tested group differences in 2 types of emotion beliefs (emotion control values and emotion malleability beliefs) and whether emotion beliefs predicted trait and daily use of cognitive reappraisal and emotion suppression. People with SAD endorsed higher emotion control values and lower emotion malleability beliefs than did healthy controls. Across groups, emotion control values were positively associated with suppression (but unrelated to reappraisal), and emotion malleability beliefs were negatively associated with suppression and positively associated with reappraisal. We also addressed 2 exploratory questions related to measurement. First, we examined whether trait and state measures of emotion regulation strategies were related to emotion control values in different ways and found similar associations across measures. Second, we examined whether explicit and implicit measures of emotion control values were related to daily emotion regulation strategy use in different ways-and found that an implicit measure was unrelated to strategy use. Results are discussed in the context of growing research on metaemotions and the measurement of complex features of emotion regulation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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Valuing Emotional Control in Social Anxiety Disorder: A Multimethod
Study of Emotion Beliefs and Emotion Regulation
Fallon R. Goodman
University of South Florida
Todd B. Kashdan and Aslıhan I
˙mamog
˘lu
George Mason University
This study examines relationships between emotion beliefs and emotion regulation strategy use among
people with social anxiety disorder (SAD) and a psychologically healthy control group. Using
experience-sampling methodology, we tested group differences in 2 types of emotion beliefs (emotion
control values and emotion malleability beliefs) and whether emotion beliefs predicted trait and daily use
of cognitive reappraisal and emotion suppression. People with SAD endorsed higher emotion control
values and lower emotion malleability beliefs than did healthy controls. Across groups, emotion control
values were positively associated with suppression (but unrelated to reappraisal), and emotion mallea-
bility beliefs were negatively associated with suppression and positively associated with reappraisal. We
also addressed 2 exploratory questions related to measurement. First, we examined whether trait and state
measures of emotion regulation strategies were related to emotion control values in different ways and
found similar associations across measures. Second, we examined whether explicit and implicit measures
of emotion control values were related to daily emotion regulation strategy use in different ways—and
found that an implicit measure was unrelated to strategy use. Results are discussed in the context of
growing research on metaemotions and the measurement of complex features of emotion regulation.
Keywords: emotion beliefs, emotion regulation, expressive suppression, cognitive reappraisal, social
anxiety
Supplemental materials: http://dx.doi.org/10.1037/emo0000750.supp
People are not passive recipients of emotions; they hold atti-
tudes and beliefs that influence how they experience, express, and
respond to emotions. Inherent to an emotional experience is a
person’s belief about his or her emotion(s)—is this emotion help-
ful, harmful, controllable, modifiable? These emotion beliefs in-
fluence how they respond to different emotional experiences. If a
person believes an emotion is harmful, they might try to avoid it or
situations that increase the likelihood of experiencing it. If a person
believes an emotion is helpful, they might engage in behaviors that
increase its intensity or duration.
The notion that people appraise emotions is present in theoret-
ical and clinical applications of emotion regulation (e.g., mindful-
ness in Acceptance and Commitment Therapy (ACT) and Dialec-
tical Behavior Therapy (DBT) as a nonjudgmental awareness of
emotions and psychoeducation on the adaptive functions of emo-
tions in emotion regulation therapy). In early writings on “emo-
tional disorders” Barlow (1991) suggested that more so than the
experience of emotions, beliefs of emotions—and subsequent re-
actions— contribute to the development and maintenance of men-
tal illness. Nearly 30 years later, (negative) emotion beliefs are
now one of three criteria that define emotional disorders (Bullis,
Boettcher, Sauer-Zavala, & Barlow, 2019). Despite a foothold in
theory and treatment, empirical examination of emotional beliefs
lags. As Ford and Gross (2018) pointed out the following:
. . . a theme that pervades the field of emotion regulation on a
theoretical level but has been relatively sparsely empirically exam-
ined: individuals’ fundamental beliefs about emotion. Individuals
differ in how they think about emotions and it is becoming increas-
ingly clear that these varying beliefs are deeply consequential. The-
orizing and initial evidence strongly suggests that emotion regulation
may be a core conduit through which these beliefs influence our lives.
(p. 1)
In the current work, we examine emotion beliefs among people
diagnosed with social anxiety disorder (SAD) and a healthy con-
trol comparison group. People with SAD display difficulties reg-
ulating emotions. They frequently use emotion regulation strate-
gies that are ineffective at meeting regulatory goals (e.g., Werner,
Goldin, Ball, Heimberg, & Gross, 2011), exacerbate unwanted
Fallon R. Goodman, Department of Psychology, University of South
Florida; Todd B. Kashdan and Aslıhan I
˙mamog
˘lu, Department of Psychol-
ogy, George Mason University.
Aslıhan I
˙mamog
˘lu is now at the Department of Psychology, University
of North Carolina at Chapel Hill.
During the preparation of this article, Fallon R. Goodman was supported
by a National Research Service Award (F31) predoctoral fellowship, and
Todd B. Kashdan was supported by the Center for the Advancement of
Well-Being as senior scientist at George Mason University and Grant
R21-MH073937 from the National Institute of Mental Health.
Correspondence concerning this article should be addressed to Fallon R.
Goodman, Department of Psychology, University of South Florida, 4202
East Fowler Avenue, PCD 4121, Tampa, FL 33620. E-mail: fgoodman@
usf.edu
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Emotion
© 2020 American Psychological Association
ISSN: 1528-3542 http://dx.doi.org/10.1037/emo0000750
2021, Vol. 21, No. 4, 842–855
842
This article was published Online First March 19, 2020.
anxiety symptoms (e.g., Kashdan et al., 2014), and detract from the
pleasure of everyday situations (e.g., Kashdan & Steger, 2006).
Despite considerable research on the impact of different emotion
regulation strategies (for a review, see Jazaieri, Morrison, Goldin,
& Gross, 2015), comparatively less is known about individual
differences that influence why people deploy certain strategies. In
this study, we focus on one set of emotion beliefs that is pertinent
to the phenomenology of social anxiety: beliefs of emotional
control. We first examined how people with and without SAD
differed in emotional control beliefs; then with experience-
sampling methodology, we examine how beliefs predicted daily
use of emotion regulation strategies. As a secondary aim, we
explored two measurement issues relevant to explicit versus im-
plicit measures and trait versus state measures of emotion regula-
tion.
Emotion Beliefs
Emotion beliefs refer to people’s evaluations about what emo-
tions they can or should experience, alter, or regulate. Emotion
beliefs have been studied under several names including beliefs
about emotions (e.g., Tamir, John, Srivastava, & Gross, 2007),
attitudes toward emotions (e.g., Harmon-Jones, Harmon-Jones,
Amodio, & Gable, 2011), and metaemotions (e.g., Norman &
Furnes, 2016). Emotion beliefs have been studied within specific
facets, such as fear of emotions (e.g., Williams, Chambless, &
Ahrens, 1997), and within discrete or specific sets of emotions,
such as nonacceptance of negative emotions (e.g., Gratz & Ro-
emer, 2004). In this work, we use the term emotion beliefs to
encompass this broad set of cognitive and affective evaluations.
There are several types of emotion beliefs. Ford and Gross
(2018) offer an early conceptual map that organizes emotion
beliefs into superordinate categories: beliefs about malleability and
beliefs about the value of emotions. Nested within these two
categories are four subordinate categories: beliefs about specific
emotional states (e.g., anger, anxiety), beliefs about specific emo-
tional channels (e.g., emotional expression, subjective feelings),
beliefs about emotions within specific contexts (e.g., at work, with
romantic partners), and beliefs about specific targets (e.g., myself,
other people). In this work, we examine the superordinate category
of beliefs about the value of emotions, and specifically, the beliefs
about the value of emotional control. Beliefs about the value of
emotion can be broadly understood by whether a person believes
emotions are “good” or “bad.” These beliefs reflect judgments
about whether emotions are useful (vs. useless), helpful (vs. harm-
ful), and/or desirable (vs. undesirable).
1
Emotion beliefs are thought to underlie multiple stages of the
emotion regulation process. They influence choices about whether
or not to regulate emotions, which strategies to use, and the
relative success of efforts (Ford & Gross, 2018;Gross, 2015;
Tamir & Mauss, 2011). A small but growing body of research
suggests that beliefs about emotion may also contribute to the
development and maintenance of mental illness (De Castella et al.,
2013;De Castella, Platow, Tamir, & Gross, 2018;Ford, Lwi,
Gentzler, Hankin, & Mauss, 2018;Kneeland & Dovidio, 2019;
Romero, Master, Paunesku, Dweck, & Gross, 2014;Schroder,
Dawood, Yalch, Donnellan, & Moser, 2015) and specifically SAD
(De Castella et al., 2014,2015). In perhaps the strongest evidence
to date for a link to mental illness, a meta-analysis found that
depressive symptoms were better predicted by negative emotion
beliefs (e.g., emotions are harmful, intolerable) than emotion reg-
ulation strategies (via effect sizes comparison with those in Aldao,
Nolen-Hoeksema & Schweizer’s, 2010 meta-analysis; Yoon,
Dang, Mertz, & Rottenberg, 2018); yet, vastly more research effort
has focused on the link between depression and emotion regulation
strategies.
Emotion Control Values
Of particular relevance to social anxiety are beliefs about the
value of controlling emotions (i.e., emotion control values). A
person who believes emotional control is valuable believes that
people should try to mitigate emotional intensity, remain in control
of their emotional experiences, and monitor emotional expression
(Mauss, Butler, Roberts, & Chu, 2010), whereas a person who
believes that emotional control is not valuable believes it is ac-
ceptable for people to experience and express the full spectrum of
human emotions. For someone with SAD, offering another person
access into their internal emotional storehouse is a daunting prop-
osition. People with SAD hold themselves to unreasonably high
social standards and believe with near certainty that they will
underperform in social situations (Moscovitch, 2009). They worry
that upon interacting with other people, they will expose their
(perceived) character flaws to other people, increasing the odds of
scrutiny and rejection. Of note, this fear of evaluation is not limited
to negative evaluation; people with SAD also demonstrate fear of
positive evaluation (Weeks & Howell, 2012). They worry that
performing well might threaten others (especially people higher in
social rank) and/or raise other people’s expectations for their
performance in future social situations. These two evaluative
fears—negative and positive evaluation—might facilitate avoidant
behavior in which someone tries to “fly under the radar” by
behaving as neutrally as possible, a strategy to avoid moving too
far up or down the social hierarchy. As such, people with SAD
might hold relatively strong beliefs about appropriate social be-
havior and social norms (e.g., Heinrichs et al., 2006), including
emotional expression. Indeed, preliminary research among college
undergraduates found that compared with those low in social
anxiety, those high in social anxiety more strongly endorsed the
belief that emotions are a sign of weakness and potential risk for
social rejection and placed higher importance on keeping emotions
in control (Spokas, Luterek, & Heimberg, 2009).
In addition to evaluative fears influencing the desire to control
the public expression of emotions, people with SAD display a
tendency to avoid the internal experience of emotions. A growing
body of research suggests that experiential avoidance, defined as
an unwillingness to be in contact with uncomfortable internal
sensations, thoughts, and feelings (Hayes, Strosahl, & Wilson,
1999), is implicated in the onset and maintenance of several
anxiety disorders (for a review, see Goodman, Larrazabal, West, &
Kashdan, 2019) and SAD in particular (Kashdan et al., 2013,
1
For ease of interpretation, we chose one term (value) to use throughout
this article. Values as used here implies that a person holds beliefs that
emotions are valuable (i.e., helpful, useful, and/or desirable in some way);
this is not (necessarily) synonymous with “values” as a way to describe
personally important life domains, activities, standards, and/or desirable
goals (e.g., Schwartz, 1992).
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843
EMOTION BELIEFS IN SOCIAL ANXIETY
2014). Experiential avoidance perpetuates an inflexible pattern of
responding to emotional experiences, whereby uncomfortable
emotions are perceived as invaluable, perhaps even harmful, and
therefore should be eliminated. A strong belief that emotions
should be controlled or concealed might facilitate avoidance of
uncomfortable emotions that could lead to negative social conse-
quences (e.g., anxiety), and frequent avoidance of uncomfortable
emotions might facilitate a reinforcement cycle that maintains and
strengthens the belief that emotions should be suppressed. Taken
together, people with SAD likely hold strong emotion control
values.
Emotion control values, like other emotion beliefs, likely shape
the emotion regulation strategies that people use. Broadly, people
differ in their reasons why they regulate emotions, and these
individual differences predict the strategies they deploy in re-
sponse to different emotional experiences (e.g., Eldesouky & Eng-
lish, 2019a,2019b). If a person believes a certain type of emotional
experience is valuable, they will likely use emotion regulation
strategies to facilitate this experience. It is, therefore, unsurprising
that negative emotion beliefs are associated with greater attempts
to avoid or attenuate the intensity of emotional experiences (e.g.,
Campbell-Sills, Barlow, Brown, & Hofmann, 2006a,2006b). In
particular, people who believe emotion control is valuable are
more likely to use strategies to intentionally constrain emotional
experiences (Burton & Bonanno, 2016;Mauss et al., 2010). Some-
one high in emotion control values, for example, might believe that
expressing their emotions conveys vulnerability and offers an inlet
to establishing intimacy with someone. As a result, they freely
express emotions with little self-monitoring. In contrast, a person
high in emotional control values might view emotional expression
as taboo or even dangerous. They might worry that expressing
emotions, especially intense or negative emotions, will offend
someone or run contrary to perceived social expectations. If they
display fewer emotions, others have fewer observable data to form
unfavorable evaluations. As a result, they will work hard to con-
strain and suppress emotional experiences.
Measurement Consideration 1: Implicit Versus
Explicit Measures of Beliefs
In affective clinical science and elsewhere, there is an ongoing
debate about whether people are aware of their beliefs and atti-
tudes and willing to report on them. Some researchers refer to
emotion beliefs as “implicit theories” because they are thought to
be implied and outside of one’s awareness rather than explicitly
held (e.g., Tamir et al., 2007). This raises an interesting method-
ological question—if beliefs are implicit, can they be measured
with explicit measures? This question has contributed to the use of
implicit measures, which are purported to minimize bias by reduc-
ing participants’ conscious efforts to be perceived in a particular
and/or socially desirable manner (e.g., trying to convey greater
independence in a culture where independence is celebrated).
Unlike self-reports, implicit measures do not rely exclusively on
information retrieved via introspection. Thus, implicit measures
are thought to access a person’s appraisals, beliefs, and biases with
limited awareness of the construct(s) being assessed (LeBel &
Paunonen, 2011).
The most widely used implicit measure is the Implicit Associ-
ation Test (IAT; Greenwald, McGhee, & Schwartz, 1998). The
assumption behind the IAT is that participants will more quickly
classify two concepts together if they already associate them
together (e.g., “anxiety” and “bad”) compared with two less asso-
ciated concepts (e.g., “anxiety” and “good”). IAT measures
typically demonstrate adequate internal consistency (Hofmann,
Gawronski, Gschwendner, Le, & Schmitt, 2005). Following the
publication of an improved scoring algorithm (Greenwald, Nosek,
& Banaji, 2003), internal consistencies for IAT studies varied
between .60 to .90 (LeBel & Paunonen, 2011). Implicit and ex-
plicit measures of the same construct are often weakly to moder-
ately correlated (Gawronski, LeBel, & Peters, 2007;Lane, Banaji,
Nosek, & Greenwald, 2007;Uhlmann, Pizarro, & Bloom, 2008). A
meta-analysis of 126 studies found an average correlation of .24
between IAT and corresponding explicit measures (Hofmann et
al., 2005).
Despite modest correlations between explicit and implicit mea-
sures, IAT measures often demonstrate adequate predictive valid-
ity. Variations of the IAT predict behavioral outcomes across
domains, such as shyness-IAT predicting spontaneous shy behav-
ior (Asendorpf, Banse, & Mücke, 2002), anxiety-IAT predicting
behavioral expressions of anxiety (Egloff & Schmukle, 2002), and
race-IAT predicting certain prejudiced behaviors (McConnell &
Leibold, 2001). These findings raise an important question: Are
implicit and explicit measures capturing the same construct at
different levels of analysis, or are they measuring related but
distinct constructs (Blanton, Jaccard, Gonzales, & Christie, 2006)?
Considering recent debates around, skepticism toward, and out-
right rejection of implicit measures (e.g., Blanton et al., 2009),
participants in the present study completed an implicit measure of
beliefs about the value of emotion control (via the IAT). Results
were compared against results from an explicit measure.
Measurement Consideration 2: Trait Versus State
Measures of Emotion Regulation Strategies
Research on emotion regulation strategies predominantly uses
trait questionnaires within cross-sectional designs. Although trait
measures are useful in describing a person’s general tendencies
across time and context, they neglect a critical aspect of person-
ality: how processes unfold over time within a single person.
Experience-sampling methodology (ESM) can address this gap by
capturing data in real-time, over repeated occasions, in a person’s
natural setting (see Conner, Tennen, Fleeson, & Barrett, 2009).
ESM minimizes information-processing biases by limiting the
time between occurrence and recall of the event (Reis & Gable,
2000). Individual differences might be best captured by distribu-
tions of states (aggregate of several ratings of a state measure)
rather than a single rating, as captured on trait measures. State
measures are useful for capturing momentary states, such as emo-
tions and rapidly deployed strategies to regulate these emotions.
Interestingly, trait and state measures of emotion regulation strat-
egies—particularly cognitive reappraisal and emotion suppres-
sion—tend to be weakly to moderately correlated and differ in
predictive validity (e.g., Blalock, Kashdan, & Farmer, 2016;
Brockman, Ciarrochi, Parker, & Kashdan, 2017;Schwartz, Neale,
Marco, Shiffman, & Stone, 1999;Todd, Tennen, Carney, Armeli,
& Affleck, 2004). It is possible that participants rely on different
information when making judgments to answer state versus trait
questionnaires. With respect to social anxiety, people with SAD
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844 GOODMAN, KASHDAN, AND I
˙MAMOG
˘LU
tend to hold distorted views of themselves and their actual behav-
ior (Hofmann, 2007;Rapee & Heimberg, 1997) and therefore
might hold biased perceptions of their general patterns of emotion
regulation use, which are biases that are potentially minimized
when reporting on strategy use closer to real-time. Thus, in the
present study, we included both state and trait measures of emotion
regulation strategy use.
We measured two emotion regulation strategies: expressive
suppression and cognitive reappraisal. They are the two most
robustly studied and widely understood emotion regulation strat-
egies, are commonly used in everyday life, and are influenced by
individual differences (Gross & John, 2003). They are implicated in
emotion dysregulation models of anxiety disorders (Hofmann, Saw-
yer, Fang, & Asnaani, 2012) and specifically SAD (Morrison &
Heimberg, 2013). In much of this work, reappraisal is described as an
adaptive regulatory strategy and suppression is described as a mal-
adaptive strategy (see Aldao, Nolen-Hoeksema, & Schweizer, 2010’s
meta-analysis). Nonetheless, there is emerging research that chal-
lenges the assumption that these strategies are putatively adaptive or
maladaptive, suggesting that the relative effect of each strategy is
contingent on the context (e.g., situational characteristics, timing,
duration, emotion valence) in which it is deployed (e.g., Brans, Koval,
Verduyn, Lim, & Kuppens, 2013;Kalokerinos, Greenaway, & Den-
son, 2015). Accordingly, there are likely a number of individual
differences that influence how, when, and under what conditions
people deploy reappraisal and suppression. In this study, we examine
one set of individual differences— emotion beliefs—that may influ-
ence strategy use.
Emotion Beliefs Are a Diverse Set
The primary purpose of our article was to examine beliefs about
the value of emotional control and address related measurement
considerations. Nonetheless, emotion beliefs encompass a diverse
set of beliefs, each of which may impact the regulatory process in
different and/or important ways. One type of emotion belief has
received considerable attention in research on psychopathology
(e.g., Kneeland, Nolen-Hoeksema, Dovidio, & Gruber, 2016) and
elsewhere, that is emotion malleability beliefs. Emotion malleabil-
ity beliefs refer to how much a person believes emotions can be
modified or controlled (Tamir et al., 2007). A person with high
emotion malleability beliefs perceives emotions as changeable; a
person with low emotion malleability beliefs perceives emotions
as fixed and immovable. Emotion malleability beliefs are generally
linked with healthy outcomes, including more adaptive responses
to stressors, less emotional distress, and more frequent reappraisal
use (Gutentag, Halperin, Porat, Bigman, & Tamir, 2017;Karnaze
& Levine, 2018;Kneeland, Goodman, & Dovidio, in press;Sch-
roder, Callahan, Gornik, & Moser, 2019;Tamir et al., 2007).
Moreover, there is some evidence to suggest that social anxiety is
associated with less malleable emotion beliefs (De Castella et al.,
2014;Kivity & Huppert, 2016;Kneeland et al., 2016;Schroder et
al., 2015). Thus, emotion malleability beliefs are relevant to both
emotion regulation and social anxiety. In the context of research on
beliefs about emotions’ value, beliefs about emotions’ malleability
represent one set of beliefs from the other “type” of emotion belief
posited in prevailing theoretical frameworks (Ford & Gross, 2018,
2019). Accordingly, we conducted a set of supplemental analyses
testing all primary hypotheses about emotion regulation strategy
use with emotion malleability beliefs, and to examine the speci-
ficity of emotion control values, we tested all primary hypotheses
controlling for emotion malleability beliefs.
2
The Present Study
Data were collected from community adults diagnosed with
SAD and healthy control comparisons matched on demographic
variables. Participants completed a diagnostic assessment and
baseline questionnaires, then completed daily reports for 14 con-
secutive days. We tested three primary study aims. First, we
examined group differences in emotion control values; we hypoth-
esized that people with SAD would report higher emotion control
values compared with healthy adults (i.e., Hypothesis 1). Second,
we examined how emotion control values predicted the use of
emotion regulation strategies; we hypothesized that higher emo-
tion control values would be associated with more suppression
(i.e., Hypothesis 2a) and less reappraisal (i.e., Hypothesis 2b).
Third, we examined if relationships differed between people with
and without SAD; we hypothesized that SAD diagnosis would
moderate the relationship between emotion control values and
strategy use, such that emotion control values would be more
strongly linked with strategy use for people with SAD compared
with healthy adults (i.e., Hypothesis 3). We also explored second-
ary aims related to measurement. First, we tested if an implicit
measure of emotion control values predicted emotion regulation
strategy use in the same way (i.e., meaningful effects in the
hypothesized direction) as an explicit measure. We hypothesized
that, considering growing concerns about the IAT’s predictive
validity (Blanton et al., 2009), implicit measures would be unre-
lated to emotion regulation strategy use (i.e., Hypothesis 4). Sec-
ond, we tested if emotion beliefs predicted trait versus state mea-
sures of emotion regulation strategy in different ways, and we
hypothesized similar relationships (i.e., meaningful effects in the
hypothesized direction; i.e., Hypothesis 5). We conducted a set of
supplemental analyses to (1) examine hypotheses about emotion
beliefs and strategy use with a measure of emotion malleability
beliefs and (2) to examine the specificity of emotion control values
(i.e., controlling for emotion malleability beliefs) in all primary
analyses.
Method
Participants
This research was approved by the institutional review board at
the university at which these data were collected. Eighty-four
adults from northern Virginia and the greater Washington, DC
metropolitan area were recruited to participate in the study. These
data are drawn from a larger study on daily processes in social
anxiety disorder (Blalock et al., 2016;Blalock, Kashdan, & Mc-
Knight, 2018;Farmer & Kashdan, 2014,2015;Goodman, Kashdan,
Stiksma, & Blalock, 2019;Kashdan & Farmer, 2014;Kashdan et al.,
2013,2014;Kashdan & McKnight, 2013). Power analyses were
conducted to determine target sample size. For between groups anal-
2
We are grateful to an anonymous reviewer for suggesting these anal-
yses.
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845
EMOTION BELIEFS IN SOCIAL ANXIETY
yses, drawing from meta-analytic research on social anxiety (Kash-
dan, 2007), an effect size of r.35 was specified. A total sample size
of 80 (40 per cell) will provide power .88 (Dupont & Plummer,
1990). This estimate is based on group differences in single time-point
dependent variables; for multilevel models with multiple records per
participant for a given dependent variable, this can be considered an
underestimation of available power. For within-person analyses,
drawing from research on social/contextual factors in social anxiety
(Kashdan & Wenzel, 2005), an effect size of r.20 was specified.
Simulation studies of multilevel power suggest that designs with 80
Level 2 units (i.e., participants) with 14 Level 1 units (i.e., days)
provide sufficient power (i.e., .80) available to detect effect
sizes .20 (Nezlek, 2011,2012;Raudenbush & Liu, 2000).
The initial sample included 41 participants who met the criteria
for a principal diagnosis of social anxiety disorder (SAD; see the
Diagnostic and Statistical Manual of Mental Disorders (4th ed.)
[DSM–IV]; American Psychiatric Association, 1994), generalized
subtype, and 43 healthy controls with no history of current
DSM–IV psychiatric disorders. The exclusionary criteria for the
SAD group included current psychotic and/or substance use dis-
orders, and participants who only met criteria for the nongeneral-
ized subtype were excluded. Participants were excluded if they did
not provide end-of-day reports (n6) or did not complete the IAT
(n4). As described subsequently, one participant was excluded
for an invalid IAT score, thus leaving a final sample of 73
participants for analyses (36 with SAD, 37 healthy controls) with
ages ranging from 19 to 58 years (M29.26, SD 8.92).
Forty-eight participants were female (65.8%), and self-reported
race/ethnicity was diverse, with 52.1% identifying as Caucasian/
White, 21.9% as African American/Black, 11.0% as Hispanic/
Latino, 4.1% as Asian/Asian American, 1.4% as Middle Eastern,
and 9.6% as other. As for educational level, 31.5% of participants
reported having some college experience, 31.5% held a bachelor’s
degree, 15.1% held a master’s degree, 5.5% held a high school
diploma, 6.8% held an associate’s degree, 5.5% held a doctoral
degree, 1.4% reported some graduate school experience, and 1.4%
reported other. In terms of self-reported family income (in U.S.
dollars), 12.5% of participants earned less than $15,000, 4.2%
earned between %15,000 and $24,999, 18.1% earned between
$25,000 and 34,999, 15.3% earned between $35,000 and $44,999,
16.7% earned between $50,000 and $64,999, 4.2% earned between
$65,000 and $79,999, and 29.2% earned more than $80,000. There
were no significant age, sex, or ethnicity differences among par-
ticipants in diagnostic groups (ps.30).
Procedure
Multiple methods of recruitment (e.g., online advertisements,
flyers) were used to recruit adult participants from the community.
Participants completed preliminary phone screens. After providing
informed consent, participants completed semistructured phone
screens with trained research assistants that assessed for symptoms
of social anxiety, generalized anxiety, depression, suicidality, and
psychosis. Individuals who endorsed symptoms suggestive of so-
cial anxiety or did not endorse any psychopathological symptoms
were scheduled for a follow-up session at a campus research
center. During this in-person assessment, participants first pro-
vided an informed consent, then completed a survey on Qualtrics
containing demographic questions (e.g., age, race) and self-report
questionnaires. After they completed baseline measures, clinical
psychology doctoral students administered the Structured Clinical
Interview for DSM–IV Axis I Disorders to assess for mood, anx-
iety, eating, substance use, and psychotic disorders to ensure
participants met the eligibility criteria for one of two diagnostic
groups (SAD and healthy control). The SAD module of the Anx-
iety Disorders Interview Schedule for DSM–IV: Lifetime Version
was administered to collect additional information about social
anxiety symptoms. To meet eligibility for the SAD group, partic-
ipants had to meet DSM–IV criteria for SAD and endorse fear and
avoidance of at least three social situations. Participants in the
SAD group were included if they had comorbid diagnoses, so long
as SAD was the primary diagnosis.
Diagnostic interviews were audio recorded, and recordings of 45
participants were randomly chosen and rated by multiple research-
ers. Interrater reliability was acceptable (Cohen’s k.87), and
discrepancies were resolved through discussion with advanced
graduate students and the principal investigator. Participants who
qualified for the experience-sampling portion of the study com-
pleted a 90-min training with instructions about the completion of
daily surveys. Each participant received a hand-help computer
(Palm Pilot 22) preprogrammed with the Purdue Momentary
Assessment Tool (PMAT; Weiss, Beal, Lucy, & MacDermid,
2004). Participants were informed that they would receive daily
surveys about emotions, emotion regulation strategies, and social
situations for 14 consecutive days. They were instructed to com-
plete each daily survey between 6:00 p.m. on the day in question
and 11:59 a.m. of the following day. This time limitation was
established to minimize recall bias. Entries outside this time period
were excluded from analyses. All participants were instructed to
initiate the daily diary portion of the study the day after their
baseline laboratory assessment. Throughout the study period, re-
search assistants regularly contacted participants to troubleshoot
any technical issues. Participants received reminder emails that
informed them of their current level of compliance and updated
earnings. Participants received financial compensation for every
survey they completed ($US.50 each), with an additional $10
bonus given for each uninterrupted week of completed reports.
Based on the compliance structure, participants earned a minimum
of $US165.00 and a maximum of $US215.00.
Measures
Implicit emotion control values task. The Emotion Regula-
tion IAT (ER-IAT; adapted by Mauss, Evers, Wilhelm, & Gross,
2006); Greenwald et al., 1998) was used to measure individual
differences in implicit emotion control values. The IAT is a reac-
tion time (RT) task that examines the strength of associations
between two target categories and two attribute categories that are
evaluative of the target categories. In the ER-IAT, the two target
categories are emotion regulation (e.g., “controlled” and “con-
tain”) and emotion expression (e.g., “expressive” and “disclose”),
and the two attribute categories are positive (e.g., “pleasant”) and
negative (e.g., “bad”).
The task was administered via the Inquisit 2.0 program (Draine,
2004) on a computer. During the task, the category labels appeared
on the left and right sides of the computer screen. Items from target
and attribute categories were presented in the center of the screen,
and participants were instructed to sort items into their respective
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846 GOODMAN, KASHDAN, AND I
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categories by pressing one of two response keys. Depending on the
test block, pairs of categories (e.g., emotion regulation and posi-
tive) appeared on the same side of the screen, corresponding to the
same response key. Participants’ RT (latency) and accuracy in
each trial was recorded to examine associations between target and
attribute categories. The rationale behind IAT is that individuals
perform the task faster (indicated by lower response time) during
blocks where the association between target and attribute catego-
ries is more congruent with their preexisting associations. For
example, a person with high implicit emotion control values would
categorize faster when items from “emotion regulation” and “pos-
itive” categories share the same response key.
The ER-IAT consisted of 180 total trials spread across five
blocks. The first two blocks were practice blocks (20 trials per
block), in which items from target and attribute categories were
presented separately and sorted into their respective keys. In Block
3, target and attribute categories were presented simultaneously
over the course of 20 practice and 40 test trials. Participants were
instructed to sort items into two combined categories (“emotion
regulation and positive” vs. “emotion expression and negative”),
involving mapping to the same hand. Block 4 was a practice block
(20 trials) for the subsequent block, in which the placement of
target categories was reversed. In Block 5, participants were asked
to categorize items from both target and attribute categories in
reversed pairings (“emotion regulation and negative” vs. “emotion
expression and positive”). Participants were instructed to respond
(i.e., categorize each stimulus word) as quickly as possible while
making as few mistakes as possible. The software program in-
cluded a built-in error penalty such that when participants an-
swered incorrectly, they were required to provide the correct
answer before proceeding. This error penalty discourages partici-
pants from randomly providing answers.
Participants’ IAT scores were calculated based on an algorithm
and updated recommendations developed by Greenwald et al.
(2003), which included using all practice and test trials in calcu-
lation. In comparison to the conventional algorithm, the inclusion
of practice trials yields higher correlations between implicit and
explicit measures of the same construct (Greenwald et al., 2003).
Trials with latency greater than 10,000 ms were eliminated with
the assumption that they represented momentary lapses in atten-
tion. Likewise, participants (n1) with latency less than 300 ms
more than 10% of the time were excluded due to their responses
being mostly anticipatory. Practice and test trials were used to
calculate standard deviations for each participant individually.
Latencies for each participant were averaged, and this average was
divided by standard deviations calculated in the previous step.
Averages from Block 3 were subtracted from averages from Block
5, which provided the final IAT scores. Higher ER-IAT scores
indicate that participants were faster in associating emotion regu-
lation with positive words, in comparison to negative words.
We used the ER-IAT as our measure of implicit emotion control
values given prior research demonstrating strong predictive valid-
ity via associations between individuals’ ER-IAT scores and both
physiological and behavioral responses; specifically, greater ER-
IAT scores were associated with less anger, more adaptive cardio-
vascular response patterns, self-reported suppression, and fewer
negative thoughts (Mauss et al., 2006). ER-IAT scores were also
found to be related to greater well-being, social adjustment, and
less depressive symptoms for individuals high in reappraisal
(Hopp, Troy, & Mauss, 2011). ER-IAT has demonstrated accept-
able internal consistency (␣⫽.86), test–retest reliability (r.68,
p.001, N36), and convergent and discriminant validity (see
Mauss et al., 2006).
Emotion control values: Self-report. How much a person
believes that emotional control is valuable was measured with
Mauss et al.’s (2010) Emotion Control Values–Self-report mea-
sure. Six items measured beliefs of control of emotional expression
(e.g., “People should not express their emotions openly” and
“People in general should control their emotions more”). Items
were rated on a Likert scale, ranging from 0 (strongly disagree)to
10 (strongly agree). Positive associations with emotion suppres-
sion demonstrate construct validity (Burton & Bonanno, 2016;
Mauss et al., 2010). Reliability was acceptable (␣⫽.78).
Emotion malleability beliefs. How much a person believes
emotions are malleable was assessed with four items (Tamir et al.,
2007). Two items measured a malleable emotion mindset (“Ev-
eryone can learn to control their emotions” and “If they want to,
people can change the emotions that they have”), and two items
measured a fixed emotion mindset (“No matter how hard they try,
people can’t really change the emotions they have” and “The truth
is, people have very little control over their emotions”). Items were
rated on a Likert scale, ranging from 0 (strongly disagree)to10
(strongly agree). The two fixed emotion mindset items were re-
versed scored, and then all four items were averaged to calculate
a total score; higher scores indicate more malleable beliefs. Posi-
tive associations with appraisal of negative affect and negative
associations with self-esteem and depression demonstrate con-
struct validity (Kappes & Schikowski, 2013;Tamir et al., 2007).
Reliability was acceptable (␣⫽.74).
Reappraisal and suppression. The Emotion Regulation
Questionnaire (ERQ; Gross & John, 2003) was used to measure
the tendency to regulate emotions using suppression and cognitive
reappraisal. Four items were averaged to create the suppression
subscale (e.g., “When feeling positive emotions” and “I’m careful
not to express them”) and six items were averaged to create the
reappraisal subscale (e.g., “When I want to feel more positive
emotion, I change the way I’m thinking about the situation”). The
ERQ has been used extensively in research on emotion regulation
and demonstrates acceptable internal consistency and construct
validity (Gross & John, 2003). Items were rated on a Likert scale,
ranging from 1 (strongly disagree)to7(strongly agree). Reliabil-
ity was acceptable for suppression (␣⫽.78) and reappraisal (␣⫽
.86).
Nonacceptance of emotions. The Nonacceptance of Emo-
tions subscale of the Difficulties in Emotion Regulation Scale
(DERS; Gratz & Roemer, 2004) was used to measure negative
self-judgments about feeling “upset” and a secondary emotional
response to a primary negative emotion (e.g., “When I am upset, I
feel ashamed with myself for feeling that way”). Six items were
rated on a Likert scale, ranging from 1 (almost never)to5(almost
always). The DERS-Nonacceptance has demonstrated adequate
internal consistency and construct validity (Gratz & Roemer,
2004). Reliability for the nonacceptance subscale was acceptable
(␣⫽.87).
Anxiety symptoms. A shortened version of the State Trait
Anxiety Inventory (STAI-T; Spielberger, Gorsuch, Lushene,
Vagg, & Jacobs, 1983) was used to measure trait-level anxiety.
The STAI-T consists of 10 items (e.g., “I feel nervous and rest-
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847
EMOTION BELIEFS IN SOCIAL ANXIETY
less”) that assess the propensity to experience anxiety. Items were
rated on a four-point Likert scale, ranging from 1 (almost never)to
4(almost always). Reliability for the STAI-T was acceptable (␣⫽
.93).
Daily reappraisal and suppression. Daily use of emotion
regulation strategies was measured with seven items from the ERQ
(Gross & John, 2003) modified for daily use, consistent with prior
research (Kashdan & Steger, 2006;Nezlek & Kuppens, 2008).
Suppression was measured with four items: “I kept my emotions to
myself”; “When I was feeling positive emotions, I was careful not
to express them”; “I controlled my emotions by not expressing
them”; and “When I was feeling negative emotions, I made sure
not to express them.” Reappraisal was measured with three items:
“When I wanted to feel more positive emotion (such as joy or
amusement), I changed what I was thinking about”; “When I
wanted to feel less negative emotion (such as sadness or guilt), I
changed what I was thinking about”; and “I controlled my emo-
tions by changing the way I thought about the situation I was in.”
Participants rated the extent to which each statement applied to
how they managed their emotions that day on a Likert scale,
ranging from 1 (strongly disagree)to7(strongly agree). Prior
daily diary studies on emotion regulation have validated these
items via associations with measures of daily and trait affect and
trait emotion regulation (Brockman et al., 2017;Kashdan & Ste-
ger, 2006;Nezlek & Kuppens, 2008).
Results
Analytic Plan
Data were conceptualized as hierarchically nested with days
(Level 1) nested within people (Level 2). Analyses were conducted
using a series of multilevel models using R (R Core Team, 2014).
Continuous Level 1 variables were entered group-mean centered,
continuous Level 2 variables were entered grand-mean centered,
and dichotomous variables were entered uncentered.
Descriptive Statistics
Reliability estimates for daily measures were calculated with the
multilevel.reliability function in R, which computes generalizabil-
ity coefficients for multilevel data.
3
The R
CN
is an index of the
reliability of within-person variations averaged across time. R
CN
coefficients were .53 for reappraisal and .36 for suppression.
Because the distribution of behaviors from one moment to the next
does not cohere in the same manner as a trait measure (e.g.,
Fleeson, 2004;Nezlek, 2007), greater intraindividual variability is
expected when data is analyzed correctly at the daily level (Nezlek,
2011). Descriptive statistics for trait measure are presented in
Table 1, and descriptive statistics for daily measures are included
in Table 2.
Internal consistency of implicit emotion control values measure
(ER-IAT) was calculated by subtracting each Block 3 trial latency
from the corresponding Block 5 trial latency. Internal consistency
was acceptable (␣⫽.75). Construct validity was assessed by
examining correlations with explicit emotion control values, non-
acceptance of emotions, and trait anxiety. Implicit emotion control
values were unrelated to explicit emotion control values (r.18,
p.12), nonacceptance of emotional responses (r⫽⫺.05, p
.65), and trait anxiety (r.02, p.90). In terms of compliance,
the two diagnostic groups did not differ in compliance rates
(␤⫽⫺.04, t.37, p.81, 95% CI [1.27, 1.85], Ms12.77
and 12.48).
Primary Analyses
Group differences in emotion control values. Compared
with healthy controls, people with SAD endorsed higher explicit
emotion control values (␤⫽.46, t2.03, p.05, 95% CI [.01,
.92], Ms3.42 and 4.21). There were no group differences in
implicit emotion control values (␤⫽⫺.03, t⫽⫺.14, p.89,
95% CI [.50, .44], Ms.001 and .01).
Emotion control values predict trait use of reappraisal and
suppression. This set of analyses examined whether explicit and
implicit emotion control values predict dispositional use of reap-
praisal and suppression. In four regression equations, explicit and
implicit emotion control values were entered as predictors, and
reappraisal and suppression were entered as outcomes. Explicit
emotion control values were positively associated with trait sup-
pression (␤⫽.32, t2.86, p.01, 95% CI [.10, .54]) and
unrelated to trait reappraisal (␤⫽⫺.08, t⫽⫺.67, p.50, 95%
CI [.32, .16]), whereas implicit emotion control values were
unrelated to trait suppression (␤⫽.13, t1.08, p.28, 95% CI
[11, .36]) and trait reappraisal (␤⫽⫺.02, t⫽⫺.17, p.87,
95% CI [.26, .22]).
To examine if these effects differed between groups, SAD
diagnosis was entered as a Level 2 moderator. SAD diagnosis did
not moderate the relationship between explicit emotion control
values and trait suppression (␤⫽.09, t.42, p.68, 95% CI
[.34, .52]) or trait reappraisal (␤⫽.01, t.06, p.95, 95% CI
3
Reliability was also conducted with hierarchical linear modeling using
unconditional three-level models, in which items were nested within days
nested within people (Nezlek, 2011). Reliability estimates were identical.
Table 1
Means, Standard Deviations, and Intercorrelations of
Trait Measures
Measure 1 2 3 4 5 6 7
1. ER-IAT
2. ECV .18
3. DERS-NA .05 .05
4. STAI-T .02 .13 .50
5. ERQ-R .02 .08 .44
.66
6. ERQ-S .13 .32
.27
.37
.28
7. EMB .16 .08 .10 .37
.35
.31
M.01 3.80 11.62 2.01 30.48 13.78 6.00
SD .39 1.74 5.88 .84 6.84 5.82 1.88
Note. For bivariate correlations between daily reappraisal and suppres-
sion, the coefficients below the diagonal represent the between-person
correlation, and the coefficients above the diagonal represent within-person
correlation. ER-IAT Emotion Regulation Implicit Association Test;
ECV emotion control values measure; DERS-NA Difficulties in
Emotion Regulation Scale–Nonacceptance subscale; STAI-T State–
Trait Anxiety Inventory, Trait version; ERQ-R Emotion Regulation
Questionnaire, Reappraisal subscale; ERQ-S Emotion Regulation Ques-
tionnaire, Suppression subscale; EMB emotion malleability beliefs
measure.
p.05.
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848 GOODMAN, KASHDAN, AND I
˙MAMOG
˘LU
[.38, .41]). SAD diagnosis did not moderate the relationship
between implicit emotion control values and trait suppression (␤⫽
.12, t.57, p.58, 95% CI [.30, .54]) or trait reappraisal
(␤⫽⫺.18, t⫽⫺.95, p.34, 95% CI [.55, .20]).
Emotion control values predict daily use of reappraisal and
suppression. We examined whether implicit and explicit emo-
tion control values predicted daily use of reappraisal and suppres-
sion. In these models, implicit and explicit emotion control values
were entered at Level 2 and daily reappraisal and suppression were
entered as outcomes.
Explicit emotion control values were positively associated with
daily use of suppression (␤⫽.45, t5.41, p.001, 95% CI [.29,
.61]) and unrelated to daily reappraisal (␤⫽⫺.07, t⫽⫺.81, p
.42, 95% CI [.24, .10]). Implicit emotion control values were
unrelated to daily use of suppression (␤⫽.17, t1.78, p.08,
95% CI [.02, .36]) and daily reappraisal (␤⫽⫺.02, t⫽⫺.19,
p.85, 95% CI [.18, .15]).
To examine if these effects differed between groups, SAD
diagnosis was entered as a Level 2 moderator. SAD diagnosis did
not moderate the relationship between explicit emotion control
values and daily suppression (␤⫽⫺.28, t⫽⫺1.76, p.08, 95%
CI [.58, .03]) or daily reappraisal (␤⫽⫺.16, t⫽⫺.92, p.36,
95% CI [.50, .18]). SAD diagnosis did not moderate the rela-
tionship between implicit emotion control values and daily sup-
pression (␤⫽⫺.23, t⫽⫺
1.35, p.18, 95% CI [.56, .10]) or
daily reappraisal (␤⫽⫺.22, t⫽⫺1.31, p.19, 95% CI [.55,
.10]).
Supplemental Analyses
Emotion malleability beliefs were unrelated to emotion control
values (r.08, p.51). People with SAD endorsed less mal-
leable emotion beliefs than healthy controls (␤⫽⫺.62,
t⫽⫺2.79, p.01, 95% CI [1.07, 0.18], Ms5.40 and 6.57).
Emotion malleability beliefs were negatively related to trait sup-
pression (␤⫽⫺.31, t⫽⫺2.70, p.01, 95% CI [.53, 0.08])
and positively related to trait reappraisal (␤⫽.35, t3.11, p
.01, 95% CI [.12, .57]). SAD diagnosis did not moderate either of
these relationships (␤⫽.39, t1.76, p.08, 95% CI [.05,
.82]; ␤⫽.06, t.28, p.78, 95% CI [.34, .45], respectively).
Emotion malleability beliefs were negatively related to daily sup-
pression (␤⫽⫺.20, t⫽⫺6.21, p.001, 95% CI [.26, .14])
and positively related to daily reappraisal (␤⫽.18, t5.59, p
.001, 95% CI [.12, .24]). SAD diagnosis did not moderate either of
these relationships (␤⫽.35, t1.88, p.06, 95% CI [.01,
.71]; ␤⫽.04, t.25, p.80, 95% CI [.30, .39], respectively).
Despite emotion malleability beliefs appearing orthogonal to
emotion control values (theoretically e.g., Ford & Gross, 2019 and
as suggested by the nonsignificant bivariate correlation in this
study), it is possible that the effect of emotion control values on
strategy use differs when accounting for emotion malleability
beliefs. As a conservative test, we reran all primary analyses
controlling for emotion malleability beliefs. The direction (posi-
tive/negative) and significance (yes/no at p.05 threshold) of all
effects remained the same. Significant diagnostic group differ-
ences in explicit emotion control values remained (␤⫽.57, t
2.37, p.05, 95% CI [.09, 1.05]). See Table S1 in the online
supplemental material for full strategy use results.
Discussion
This study examined how emotion beliefs predict emotion reg-
ulation strategy use among people with SAD and a healthy control
group. We examined emotion beliefs that are theoretically relevant
to social anxiety: emotion control values, defined as a person
valuing a sense of control over felt emotions. Consistent with
hypotheses, people with SAD held stronger beliefs about the value
of emotion control and more fixed emotion beliefs than did healthy
adults. Results from a 14-day diary study found that explicit
emotion control values were positively associated with daily use of
emotional suppression, offering additional support that the beliefs
a person has about emotions contribute to the strategies they use to
manage emotions. Emotion malleability beliefs were positively
associated with (trait and daily) reappraisal and negatively asso-
ciated with (trait and daily) suppression. To explore common
measurement features, we pursued two secondary aims. We found
that (1) explicit emotion control values were associated with both
trait and state measures of emotion suppression, and (2) implicit
measures of emotion beliefs were unrelated to (trait or state)
emotion regulation strategy use.
Emotion Beliefs and Social Anxiety
Theoretical and empirical research suggest people with SAD
make negatively biased beliefs about themselves and others
(Boden et al., 2012;Clark & Wells, 1995;Foa, Franklin, Perry, &
Herbert, 1996;Heimberg, Brozovich, & Rapee, 2010;Hofmann,
2007). Theorists suggest that people with SAD believe they are
inherently deficient or flawed, hold themselves to unreasonably
high expectations, and overestimate the likelihood of social rejec-
tion (Moscovitch, 2009). This constellation of beliefs facilitates an
avoidant style of emotion regulation, in which the motivation to
avoid rejection overrides the motivation to pursue potential social
rewards and valued goals (Kashdan, Weeks, & Savostyanova,
2011). Results of the present study suggest that another set of
beliefs— emotion beliefs—might also be relevant to social anxi-
ety.
Compared with psychologically healthy adults, people with
SAD endorsed stronger beliefs about the value of emotional con-
trol. Our results are consistent with a growing body of literature
that illustrates people with SAD hold (potentially) negative beliefs
about emotions. People with SAD tend to be nonaccepting of
Table 2
Descriptive Statistics of Daily Variables
Statistic Reappraisal Suppression
Grand M12.46 13.03
SD (between) 2.82 4.90
SD (within) 2.56 3.06
ICC .47 .66
r(between) .09
r(within) .09
Note. For bivariate correlations between reappraisal and suppression, the
coefficient above the diagonal represents the between-person correlation
(i.e., r[between]), and the coefficient below the diagonal represents within-
person correlation (r[within]). ICC intraclass correlation coefficient.
p.01.
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849
EMOTION BELIEFS IN SOCIAL ANXIETY
negative emotions; they are critical and unforgiving of themselves,
often feeling angry or ashamed for experiencing negative emotions
(Blalock et al., 2016;Kivity & Huppert, 2016). They also doubt
their ability to regulate negative emotions and tend to be pessi-
mistic about whether efforts to downregulate negative emotions
will be successful (Sung et al., 2012). Of note, the self-report
measure of emotion control values used in this study (Mauss et al.,
2010) includes one item that may be referring to emotional expe-
rience more so than (or in addition to) outward emotional expres-
sion (i.e., “People in general should control their emotions more.”).
Theorists differ on whether the experience and regulation of emo-
tions can be distinguished (Gross & Barrett, 2011). In future
research, it might be helpful to tease apart the two stages, as
research suggests that how people experience emotions has unique
consequences from whether the same emotions are publicly ex-
pressed or inhibited (e.g., Webb, Miles, & Sheeran, 2012).
Our results extend research on emotion malleability beliefs.
People with SAD endorsed a more fixed mindset of emotions than
healthy controls. This result replicates prior findings (De Castella,
et al., 2014) and offers additional support to theoretical frame-
works suggesting that people with SAD hold potentially problem-
atic beliefs (e.g., Clark & Wells, 1995;Heimberg et al., 2010;
Hofmann, 2007). It is worth noting that emotion malleability
beliefs were distinct from emotion control values (r.08, p
.51). Taken together, our group comparison results suggest that
people with SAD hold emotion beliefs that might set up a “no-
win” situation in regulation: compared with healthy controls, they
believe emotions are (relatively) uncontrollable, yet believe there
is (relatively) high value in controlling them. Of course, these are
relative group differences, not absolute thresholds of “high” or
“low,” and more work in diverse samples with different compar-
ison groups will be important to determine if and how emotion
beliefs operate uniquely in people with SAD.
Measurement Considerations in Emotion Regulation
A secondary aim of this study was to address two measurement
concerns in emotion regulation research. We first explored the
assumption that beliefs—which are frequently referred to as “im-
plicit theories”—are best measured implicitly. Results suggest that
implicit emotion control values (measured via an IAT) offered no
predictive validity for emotion regulation strategy use. We caution
against overinterpreting null results, and in the spirit of our dis-
cussion of measurement, offer two considerations for future re-
search in this area.
First, as is often the case in IAT research, analyses included
constructs that were measured at different levels of analysis—
implicit emotion control values were measured via a computerized
performance task dependent on RT, whereas explicit emotion
control values and emotion regulation strategies were measured
with untimed self-report questionnaires. Different tasks rely on
different skills (e.g., RT vs. introspection), and it is possible that
measures of the same type (e.g., behavioral task vs. self-report)
more closely correspond to one another. Second, implicit and
explicit measures of purportedly the same construct might measure
distinct constructs. There are many questions about what con-
structs IAT measures capture and how closely they map onto
constructs with corresponding explicit measures (Nosek, 2007).
More work is needed to understand the precise nature of these
measurements and their relationships with emotion regulation
strategies.
We explored how emotion control values predicted trait and
state measures of emotion regulation strategy use (i.e., suppression
and reappraisal). Results indicated that trait and state measures
were related to emotion beliefs in the same way (i.e., meaningful
effects in the expected direction). Specifically, higher emotion
control values were associated with more frequent trait and daily
use of suppression, and higher emotion malleability beliefs were
associated with less frequent trait and daily use of suppression and
more frequent use of trait and daily reappraisal. Future research
can assess emotion regulation strategies at different levels of
analysis (e.g., state self-report vs. physiological records) to under-
stand how and when different measures converge and to explore
reasons for discrepancies when they do not (e.g., Alfano, Patriquin,
& De Los Reyes, 2015;De Los Reyes, Lerner, Thomas, Daruwala,
& Goepel, 2013). Emotion regulation, for example, might be best
measured in response to a particular episode (e.g., Werner et al.,
2011) or emotion (e.g., Lee, Weathers, Sloan, Davis, & Domino,
2017) rather than a whole day. In this way, using a state measure
of emotion regulation that is tied to a discrete event (e.g., “what
was the most stressful event that occurred today?”) might offer
greater precision than day-level averages. Contrary to hypotheses,
the relationship between emotion control values and (trait or state)
strategy use did not differ between the SAD and healthy control
groups. Given that our analyses are likely underpowered to detect
small effects, future research is needed to examine these relation-
ships with well-powered samples and sufficient replication before
drawing conclusions.
Clinical Considerations
Cognitive-behavioral therapies are rooted in the idea that clients
have distorted maladaptive beliefs that contribute to unwanted
outcomes, and these beliefs can be altered to facilitate wanted
outcomes. Emotion beliefs represent one subset of beliefs that, if
problematic, can be modified with intervention. Clinicians can
challenge patients’ maladaptive “myths” about emotions (Leahy,
Tirch, & Napolitano, 2011), such as believing that emotions can
hijack self-control (Veilleux, Salomaa, Shaver, Zielinski, & Pol-
lert, 2015). There is some evidence to suggest that people can alter
their emotional beliefs and that these changes influence treatment
outcomes. In one cognitive-behavioral therapy intervention, reduc-
tions in emotion malleability beliefs (i.e., whether someone per-
ceives emotions as modifiable) partially explained changes in
symptoms during the course of treatment for social anxiety (De
Castella et al., 2015). Patients can complete exercises that test
faulty assumptions about emotions (e.g., negative emotions are
always harmful; emotions should be avoided) and build evidence
that challenges assumptions and facilitates belief change.
Limitations and Future Directions
Results should be interpreted in the context of study limitations.
This research is correlational, and conclusions about causality and
direction of effects cannot be drawn. Emotion beliefs and regula-
tory strategies likely develop in tandem over time, whereby par-
ticular beliefs facilitate use of particular strategies, which in turn
reinforce beliefs. Additional research is needed to disentangle
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850 GOODMAN, KASHDAN, AND I
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˘LU
these effects and better understand directional relationships. Our
sample size, though within recommendations for experience-
sampling designs (e.g., Nezlek, 2012) might not be sufficiently
powered to detect meaningful small effects. In the present study,
tests of moderation (i.e., diagnostic group differences in beliefs-
strategy use relationships) might not be sufficiently powered to
detect small effects. Specifically for implicit measures, prior re-
search has demonstrated relatively small effect sizes with IAT and
outcomes of interest (e.g., Greenwald, Poehlman, Uhlmann, &
Banaji, 2009;Oswald, Mitchell, Blanton, Jaccard, & Tetlock,
2013). As such, we interpret these results cautiously and encourage
future replication efforts. It will be important to examine these
research questions in large clinical samples to determine if and
how emotion beliefs operate differently for particular psycholog-
ical disorders. It is unclear whether emotion belief systems are
disorder-specific, transdiagnostic, or common to the bulk of the
population.
Our measures of emotion beliefs did not specify particular
emotion categories, and there are additional types of emotion
beliefs that warrant further exploration. For instance, there are
measures of beliefs about specific emotions such as anger and
sadness (Harmon-Jones et al., 2011) or broader groups of emotions
(e.g., “negative” emotions). A person’s beliefs about particular
emotions might also depend on the context in which they are
experiencing the emotion(s). Anger, for example, is perceived as
more valuable in confrontational versus collaborative social inter-
actions (Tamir & Ford, 2012). Future research can extend this
work to people with SAD by examining how beliefs toward
specific emotions in different situations predict strategy use.
In addition to examining other types of emotion beliefs, future
research can explore different dimensions of emotion regulation
strategies, such as perceived regulatory effectiveness or how strat-
egies work in tandem with one another (i.e., polyregulation; Ford,
Gross, & Gruber, 2019). A large majority of research thus far has
examined regulatory strategies in isolation; the reality of our
emotional lives is likely more complex, where we may use a
number of strategies at once or in response to a single episode.
Perhaps certain emotion beliefs are predictive of unique combina-
tions or sequences of strategy use.
Although our participant sample was relatively diverse in terms
of race/ethnicity, we did not include measures of cultural norms or
values. Cultures vary in their beliefs, experiences, and expressions
of emotions (see Ford & Mauss, 2015 for an overview), and there
is some evidence of culture-specific presentations of mental illness
that differ in form and function (e.g., Taijin kyofusho [TKS] form
of SAD in Japan; Hofmann, Anu Asnaani, & Hinton, 2010).
Cultural values can influence a person’s motivation to regulate
emotions, which strategies they use to do so, and consequences of
these attempts (e.g., emotion suppression in Western European vs.
Asian cultures; Butler, Lee, & Gross, 2007). Emotion regulation
processes are determined by a complex system of cultural values
(and beyond a simple ethnic/racial category; English & John,
2013), and future research is needed to explore intersections with
emotion beliefs.
Conclusion
Emotion dysregulation is increasingly considered a transdiag-
nostic mechanism that contributes to, exacerbates, and maintains
mental illness. The last 3 decades have seen a proliferation of
research on emotion regulation that has yielded invaluable infor-
mation about which and to what degree people use different
strategies to manage their emotions. In recent years, the field has
shifted toward a contextualized science that builds off these foun-
dational findings to identify complex intersections of why, when,
and how people use different strategies (Aldao, 2013). In this
study, we examined one understudied individual difference in
emotion regulation: emotion beliefs. Results from experience-
sampling found that beliefs that emotional control is valuable, as
well as beliefs that emotions are more fixed (vs. malleable),
predicts more frequent use of emotion suppression in daily life,
suggesting that emotion beliefs may be an important construct to
examine across the spectrum of mental health. As future research
explores additional types of emotions beliefs, with careful atten-
tion to measurement, a more nuanced and comprehensive picture
of emotion dysregulation can emerge.
References
Aldao, A. (2013). The future of emotion regulation research: Capturing
context. Perspectives on Psychological Science, 8, 155–172. http://dx
.doi.org/10.1177/1745691612459518
Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-
regulation strategies across psychopathology: A meta-analytic review.
Clinical Psychology Review, 30, 217–237. http://dx.doi.org/10.1016/j
.cpr.2009.11.004
Alfano, C. A., Patriquin, M. A., & De Los Reyes, A. (2015). Subjective–
objective sleep comparisons and discrepancies among clinically-anxious
and healthy children. Journal of Abnormal Child Psychology, 43, 1343–
1353. http://dx.doi.org/10.1007/s10802-015-0018-7
American Psychiatric Association. (1994). Diagnostic and statistical man-
ual of mental disorders (4th ed.). Washington, DC: American Psychiat-
ric Publishing, Inc.
Asendorpf, J. B., Banse, R., & Mücke, D. (2002). Double dissociation
between implicit and explicit personality self-concept: The case of shy
behavior. Journal of Personality and Social Psychology, 83, 380 –393.
http://dx.doi.org/10.1037/0022-3514.83.2.380
Barlow, D. H. (1991). Disorders of emotion. Psychological Inquiry, 2,
58 –71.
Blalock, D. V., Kashdan, T. B., & Farmer, A. S. (2016). Trait and daily
emotion regulation in social anxiety disorder. Cognitive Therapy and
Research, 40, 416 – 425. http://dx.doi.org/10.1007/s10608-015-9739-8
Blalock, D. V., Kashdan, T. B., & McKnight, P. E. (2018). High risk, high
reward: Daily perceptions of social challenge and performance in social
anxiety disorder. Journal of Anxiety Disorders, 54, 57– 64. http://dx.doi
.org/10.1016/j.janxdis.2018.01.006
Blanton, H., Jaccard, J., Gonzales, P. M., & Christie, C. (2006). Decoding
the implicit association test: Implications for criterion prediction. Jour-
nal of Experimental Social Psychology, 42, 192–212. http://dx.doi.org/
10.1016/j.jesp.2005.07.003
Blanton, H., Jaccard, J., Klick, J., Mellers, B., Mitchell, G., & Tetlock,
P. E. (2009). Strong claims and weak evidence: Reassessing the predic-
tive validity of the IAT. Journal of Applied Psychology, 94, 567–582.
http://dx.doi.org/10.1037/a0014665
Boden, M. T., John, O. P., Goldin, P. R., Werner, K., Heimberg, R. G., &
Gross, J. J. (2012). The role of maladaptive beliefs in cognitive-
behavioral therapy: Evidence from social anxiety disorder. Behaviour
Research and Therapy, 50, 287–291. http://dx.doi.org/10.1016/j.brat
.2012.02.007
Brans, K., Koval, P., Verduyn, P., Lim, Y. L., & Kuppens, P. (2013). The
regulation of negative and positive affect in daily life. Emotion, 13,
926 –939. http://dx.doi.org/10.1037/a0032400
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.
851
EMOTION BELIEFS IN SOCIAL ANXIETY
Brockman, R., Ciarrochi, J., Parker, P., & Kashdan, T. (2017). Emotion
regulation strategies in daily life: Mindfulness, cognitive reappraisal and
emotion suppression. Cognitive Behaviour Therapy, 46, 91–113. http://
dx.doi.org/10.1080/16506073.2016.1218926
Bullis, J. R., Boettcher, H., Sauer-Zavala, S., & Barlow, D. H. (2019).
What is an emotional disorder?: A transdiagnostic mechanistic defini-
tions with implications for assessment, treatment and prevention. Clin-
ical Psychology: Science and Practice, 26, e12278. http://dx.doi.org/10
.1111/cpsp.12278
Burton, C. L., & Bonanno, G. A. (2016). Measuring ability to enhance and
suppress emotional expression: The Flexible Regulation of Emotional
Expression (FREE) Scale. Psychological Assessment, 28, 929 –941.
http://dx.doi.org/10.1037/pas0000231
Butler, E. A., Lee, T. L., & Gross, J. J. (2007). Emotion regulation and
culture: Are the social consequences of emotion suppression culture-
specific? Emotion, 7, 30 – 48. http://dx.doi.org/10.1037/1528-3542.7
.1.30
Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G.
(2006a). Acceptability and suppression of negative emotion in anxiety
and mood disorders. Emotion, 6, 587–595. http://dx.doi.org/10.1037/
1528-3542.6.4.587
Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G.
(2006b). Effects of suppression and acceptance on emotional responses
of individuals with anxiety and mood disorders. Behaviour Research and
Therapy, 44, 1251–1263. http://dx.doi.org/10.1016/j.brat.2005.10.001
Clark, D. M., & Wells, A. (1995). A cognitive model of social phobia. In
R. G. Heimberg, M. R. Liebowitz, D. A. Hope, & F. R. Schneier (Eds.),
Social phobia: Diagnosis, assessment, and treatment (pp. 69 –93). New
York, NY: Guilford Press. Retrieved from https://psycnet.apa.org/record/
1995-98887-004
Conner, T. S., Tennen, H., Fleeson, W., & Barrett, L. F. (2009). Experience
sampling methods: A modern idiographic approach to personality re-
search. Social and Personality Psychology Compass, 3, 292–313. http://
dx.doi.org/10.1111/j.1751-9004.2009.00170.x
De Castella, K., Goldin, P., Jazaieri, H., Heimberg, R. G., Dweck, C. S., &
Gross, J. J. (2015). Emotion beliefs and cognitive behavioural therapy
for social anxiety disorder. Cognitive Behaviour Therapy, 44, 128 –141.
http://dx.doi.org/10.1080/16506073.2014.974665
De Castella, K., Goldin, P., Jazaieri, H., Ziv, M., Dweck, C. S., & Gross,
J. J. (2013). Beliefs about emotion: Links to emotion regulation, well-
being, and psychological distress. Basic and Applied Social Psychology,
35, 497–505. http://dx.doi.org/10.1080/01973533.2013.840632
De Castella, K., Goldin, P., Jazaieri, H., Ziv, M., Heimberg, R. G., &
Gross, J. J. (2014). Emotion beliefs in social anxiety disorder: Associ-
ations with stress, anxiety, and well-being. Australian Journal of Psy-
chology, 66, 139 –148. http://dx.doi.org/10.1111/ajpy.12053
De Castella, K., Platow, M. J., Tamir, M., & Gross, J. J. (2018). Beliefs
about emotion: Implications for avoidance-based emotion regulation and
psychological health. Cognition and Emotion, 32, 773–795. http://dx.doi
.org/10.1080/02699931.2017.1353485
De Los Reyes, A., Lerner, M. D., Thomas, S. A., Daruwala, S., & Goepel,
K. (2013). Discrepancies between parent and adolescent beliefs about
daily life topics and performance on an emotion recognition task. Jour-
nal of Abnormal Child Psychology, 41, 971–982. http://dx.doi.org/10
.1007/s10802-013-9733-0
Draine, S. C. (2004). Inquisit (Version 2.0) [Computer software]. Seattle,
WA: Millisecond Software.
Dupont, W. D., & Plummer, W. D., Jr. (1990). Power and sample size
calculations. A review and computer program. Controlled Clinical Tri-
als, 11, 116 –128. http://dx.doi.org/10.1016/0197-2456(90)90005-M
Egloff, B., & Schmukle, S. C. (2002). Predictive validity of an Implicit
Association Test for assessing anxiety. Journal of Personality and Social
Psychology, 83, 1441–1455. http://dx.doi.org/10.1037/0022-3514.83.6
.1441
Eldesouky, L., & English, T. (2019a). Individual differences in emotion
regulation goals: Does personality predict the reasons why people reg-
ulate their emotions? Journal of Personality, 87, 750 –766. http://dx.doi
.org/10.1111/jopy.12430
Eldesouky, L., & English, T. (2019b). Regulating for a reason: Emotion
regulation goals are linked to spontaneous strategy use. Journal of
Personality, 87, 948 –961. http://dx.doi.org/10.1111/jopy.12447
English, T., & John, O. P. (2013). Understanding the social effects of
emotion regulation: The mediating role of authenticity for individual
differences in suppression. Emotion, 13, 314 –329. http://dx.doi.org/10
.1037/a0029847
Farmer, A. S., & Kashdan, T. B. (2014). Affective and self-esteem insta-
bility in the daily lives of people with generalized social anxiety disor-
der. Clinical Psychological Science, 2, 187–201. http://dx.doi.org/10
.1177/2167702613495200
Farmer, A. S., & Kashdan, T. B. (2015). Stress sensitivity and stress
generation in social anxiety disorder: A temporal process approach.
Journal of Abnormal Psychology, 124, 102–114. http://dx.doi.org/10
.1037/abn0000036
Fleeson, W. (2004). Moving personality beyond the person-situation de-
bate: The challenge and the opportunity of within-person variability.
Current Directions in Psychological Science, 13, 83– 87. http://dx.doi
.org/10.1111/j.0963-7214.2004.00280.x
Foa, E. B., Franklin, M. E., Perry, K. J., & Herbert, J. D. (1996). Cognitive
biases in generalized social phobia. Journal of Abnormal Psychology,
105, 433– 439. http://dx.doi.org/10.1037/0021-843X.105.3.433
Ford, B. Q., & Gross, J. J. (2018). Emotion regulation: Why beliefs matter.
Canadian Psychology, 59, 1–14. http://dx.doi.org/10.1037/cap0000142
Ford, B. Q., & Gross, J. J. (2019). Why beliefs about emotion matter: An
emotion-regulation perspective. Current Directions in Psychological
Science, 28, 74 – 81. http://dx.doi.org/10.1177/0963721418806697
Ford, B. Q., Gross, J. J., & Gruber, J. (2019). Broadening our field of view:
The role of emotion polyregulation. Emotion Review, 11, 197–208.
http://dx.doi.org/10.1177/1754073919850314
Ford, B. Q., Lwi, S. J., Gentzler, A. L., Hankin, B., & Mauss, I. B. (2018).
The cost of believing emotions are uncontrollable: Youths’ beliefs about
emotion predict emotion regulation and depressive symptoms. Journal
of Experimental Psychology: General, 147, 1170 –1190. http://dx.doi
.org/10.1037/xge0000396
Ford, B. Q., & Mauss, I. B. (2015). Culture and emotion regulation.
Current Opinion in Psychology, 3, 1–5. http://dx.doi.org/10.1016/j
.copsyc.2014.12.004
Gawronski, B., LeBel, E. P., & Peters, K. R. (2007). What do implicit
measures tell us? Scrutinizing the validity of three common assumptions.
Perspectives on Psychological Science, 2, 181–193. http://dx.doi.org/10
.1111/j.1745-6916.2007.00036.x
Goodman, F. R., Kashdan, T. B., Stiksma, M. C., & Blalock, D. V. (2019).
Personal strivings to understand anxiety disorders: Social anxiety as an
exemplar. Clinical Psychological Science, 7, 283–301. http://dx.doi.org/
10.1177/2167702618804778
Goodman, F. R., Larrazabal, M., West, J., & Kashdan, T. B. (2019).
Experiential avoidance across anxiety disorders. In B. O. Olatunji (Ed.),
Cambridge handbook of anxiety and related disorders (pp. 255–281).
Cambridge, UK: Cambridge University Press. Retrieved from https://
books.google.com/books?idk6-BDwAAQBAJ&dqB.O.Olatunji
(Ed.),Cambridgehandbookofanxietyandrelateddisorders
.&lr&sourcegbs_navlinks_s
Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emo-
tion regulation and dysregulation: Development, factor structure, and
initial validation of the difficulties in emotion regulation scale. Journal
of Psychopathology and Behavioral Assessment, 26, 41–54. http://dx.doi
.org/10.1023/B:JOBA.0000007455.08539.94
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring
individual differences in implicit cognition: The implicit association test.
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.
852 GOODMAN, KASHDAN, AND I
˙MAMOG
˘LU
Journal of Personality and Social Psychology, 74, 1464 –1480. http://
dx.doi.org/10.1037/0022-3514.74.6.1464
Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding
and using the implicit association test: I. An improved scoring algorithm.
Journal of Personality and Social Psychology, 85, 197–216. http://dx
.doi.org/10.1037/0022-3514.85.2.197
Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R.
(2009). Understanding and using the Implicit Association Test: III.
Meta-analysis of predictive validity. Journal of Personality and Social
Psychology, 97, 17– 41. http://dx.doi.org/10.1037/a0015575
Gross, J. J. (2015). Emotion regulation: Current status and future prospects.
Psychological Inquiry, 26, 1–26. http://dx.doi.org/10.1080/1047840X
.2014.940781
Gross, J. J., & Barrett, L. F. (2011). Emotion generation and emotion
regulation: One or two depends on your point of view. Emotion Review,
3, 8 –16. http://dx.doi.org/10.1177/1754073910380974
Gross, J. J., & John, O. P. (2003). Individual differences in two emotion
regulation processes: Implications for affect, relationships, and well-
being. Journal of Personality and Social Psychology, 85, 348 –362.
http://dx.doi.org/10.1037/0022-3514.85.2.348
Gutentag, T., Halperin, E., Porat, R., Bigman, Y. E., & Tamir, M. (2017).
Successful emotion regulation requires both conviction and skill: Beliefs
about the controllability of emotions, reappraisal, and regulation success.
Cognition and Emotion, 31, 1225–1233. http://dx.doi.org/10.1080/
02699931.2016.1213704
Harmon-Jones, E., Harmon-Jones, C., Amodio, D. M., & Gable, P. A.
(2011). Attitudes toward emotions. Journal of Personality and Social
Psychology, 101, 1332–1350. http://dx.doi.org/10.1037/a0024951
Hayes, S. C., Strosahl, K., & Wilson, K. G. (1999). Acceptance and
commitment therapy: Understanding and treating human suffering. New
York, NY: Guilford Press. Retrieved from https://www.guilford.com/
books/Acceptance-and-Commitment-Therapy/Hayes-Strosahl-Wilson/
9781462528943
Heimberg, R. G., Brozovich, F. A., & Rapee, R. M. (2010). A cognitive
behavioral model of social anxiety disorder: Update and extension. In
S. G. Hofmann & P. M. DiBartolo (Eds.), Social anxiety: Clinical,
developmental, and social perspective (2nd ed., pp. 395– 422). New
York, NY: Elsevier. http://dx.doi.org/10.1016/B978-0-12-375096-9
.00015-8
Heinrichs, N., Rapee, R. M., Alden, L. A., Bögels, S., Hofmann, S. G., Oh,
K. J., & Sakano, Y. (2006). Cultural differences in perceived social
norms and social anxiety. Behaviour Research and Therapy, 44, 1187–
1197. http://dx.doi.org/10.1016/j.brat.2005.09.006
Hofmann, S. G. (2007). Cognitive factors that maintain social anxiety
disorder: A comprehensive model and its treatment implications. Cog-
nitive Behaviour Therapy, 36, 193–209. http://dx.doi.org/10.1080/
16506070701421313
Hofmann, S. G., Anu Asnaani, M. A., & Hinton, D. E. (2010). Cultural
aspects in social anxiety and social anxiety disorder. Depression and
Anxiety, 27, 1117–1127. http://dx.doi.org/10.1002/da.20759
Hofmann, S. G., Sawyer, A. T., Fang, A., & Asnaani, A. (2012). Emotion
dysregulation model of mood and anxiety disorders. Depression and
Anxiety, 29, 409 – 416. http://dx.doi.org/10.1002/da.21888
Hofmann, W., Gawronski, B., Gschwendner, T., Le, H., & Schmitt, M.
(2005). A meta-analysis on the correlation between the implicit associ-
ation test and explicit self-report measures. Personality and Social
Psychology Bulletin, 31, 1369 –1385. http://dx.doi.org/10.1177/
0146167205275613
Hopp, H., Troy, A. S., & Mauss, I. B. (2011). The unconscious pursuit of
emotion regulation: Implications for psychological health. Cognition
and Emotion, 25, 532–545.
Jazaieri, H., Morrison, A. S., Goldin, P. R., & Gross, J. J. (2015). The role
of emotion and emotion regulation in social anxiety disorder. Current
Psychiatry Reports, 17, 531. http://dx.doi.org/10.1007/s11920-014-
0531-3
Kalokerinos, E. K., Greenaway, K. H., & Denson, T. F. (2015). Reap-
praisal but not suppression downregulates the experience of positive and
negative emotion. Emotion, 15, 271–275. http://dx.doi.org/10.1037/
emo0000025
Kappes, A., & Schikowski, A. (2013). Implicit theories of emotion shape
regulation of negative affect. Cognition and Emotion, 27, 952–960.
http://dx.doi.org/10.1080/02699931.2012.753415
Karnaze, M. M., & Levine, L. J. (2018). Data versus Spock: Lay theories
about whether emotion helps or hinders. Cognition and Emotion, 32,
549 –565. http://dx.doi.org/10.1080/02699931.2017.1326374
Kashdan, T. B. (2007). Social anxiety spectrum and diminished positive
experiences: Theoretical synthesis and meta-analysis. Clinical Psychol-
ogy Review, 27, 348 –365. http://dx.doi.org/10.1016/j.cpr.2006.12.003
Kashdan, T. B., & Farmer, A. S. (2014). Differentiating emotions across
contexts: Comparing adults with and without social anxiety disorder
using random, social interaction, and daily experience sampling. Emo-
tion, 14, 629 – 638. http://dx.doi.org/10.1037/a0035796
Kashdan, T. B., Farmer, A. S., Adams, L. M., Ferssizidis, P., McKnight,
P. E., & Nezlek, J. B. (2013). 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, 122, 645– 655. http://dx.doi.org/10.1037/
a0032733
Kashdan, T. B., Goodman, F. R., Machell, K. A., Kleiman, E. M., Monfort,
S. S., Ciarrochi, J., & Nezlek, J. B. (2014). A contextual approach to
experiential avoidance and social anxiety: Evidence from an experimen-
tal interaction and daily interactions of people with social anxiety
disorder. Emotion, 14, 769 –781. http://dx.doi.org/10.1037/a0035935
Kashdan, T. B., & McKnight, P. E. (2013). Commitment to a purpose in
life: An antidote to the suffering by individuals with social anxiety
disorder. Emotion, 13, 1150 –1159. http://dx.doi.org/10.1037/a0033278
Kashdan, T. B., & Steger, M. F. (2006). Expanding the topography of
social anxiety. An experience-sampling assessment of positive emotions,
positive events, and emotion suppression. Psychological Science, 17,
120 –128. http://dx.doi.org/10.1111/j.1467-9280.2006.01674.x
Kashdan, T. B., Weeks, J. W., & Savostyanova, A. A. (2011). Whether,
how, and when social anxiety shapes positive experiences and events: A
self-regulatory framework and treatment implications. Clinical Psychol-
ogy Review, 31, 786 –799. http://dx.doi.org/10.1016/j.cpr.2011.03.012
Kashdan, T. B., & Wenzel, A. (2005). A transactional approach to social
anxiety and the genesis of interpersonal closeness: Self, partner, and
social context. Behavior Therapy, 36, 335–346. http://dx.doi.org/10
.1016/S0005-7894(05)80115-7
Kivity, Y., & Huppert, J. D. (2016). Does cognitive reappraisal reduce
anxiety? A daily diary study of a micro-intervention with individuals
with high social anxiety. Journal of Consulting and Clinical Psychology,
84, 269 –283. http://dx.doi.org/10.1037/ccp0000075
Kneeland, E. T., Nolen-Hoeksema, S., Dovidio, J. F., & Gruber, J. (2016).
Emotion malleability beliefs influence the spontaneous regulation of
social anxiety. Cognitive Therapy and Research, 40, 496 –509.
Kneeland, E. T., & Dovidio, J. F. (2019). Emotion malleability beliefs and
coping with the college transition. Emotion. Advance online publication.
http://dx.doi.org/10.1037/emo0000559
Kneeland, E. T., Goodman, F., & Dovidio, J. F. (in press). Emotion beliefs,
emotion regulation, and emotional experiences in daily life. Behavior
Therapy.http://dx.doi.org/10.1016/j.beth.2019.10.007
Lane, K. A., Banaji, M. R., Nosek, B. A., & Greenwald, A. G. (2007).
Understanding and using the Implicit Association Test: IV: Procedures
and validity. What we know so far about the method. In B. Wittenbrink
& N. S. Schwarz (Eds.), Implicit measures of attitudes: Procedures and
controversies (pp. 59 –102). New York, NY: Guilford Press. Retrieved
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.
853
EMOTION BELIEFS IN SOCIAL ANXIETY
from https://books.google.com/books/about/Implicit_Measures_
of_Attitudes.html?id7YZ4-2f1bNoC
Leahy, R. L., Tirch, D., & Napolitano, L. A. (2011). Emotion regulation in
psychotherapy: A practitioner’s guide. New York, NY: Guilford Press.
Retrieved from https://www.guilford.com/books/Emotion-Regulation-
in-Psychotherapy/Leahy-Tirch-Napolitano/9781609184834
Lebel, E. P., & Paunonen, S. V. (2011). Sexy but often unreliable: The
impact of unreliability on the replicability of experimental findings with
implicit measures. Personality and Social Psychology Bulletin, 37, 570 –
583. http://dx.doi.org/10.1177/0146167211400619
Lee, D. J., Weathers, F. W., Sloan, D. M., Davis, M. T., & Domino, J. L.
(2017). Development and initial psychometric evaluation of the semi-
structured emotion regulation interview. Journal of Personality Assess-
ment, 99, 56 – 66. http://dx.doi.org/10.1080/00223891.2016.1215992
Mauss, I. B., Butler, E. A., Roberts, N. A., & Chu, A. (2010). Emotion
control values and responding to an anger provocation in Asian-
American and European-American individuals. Cognition and Emotion,
24, 1026 –1043. http://dx.doi.org/10.1080/02699930903122273
Mauss, I. B., Evers, C., Wilhelm, F. H., & Gross, J. J. (2006). How to bite
your tongue without blowing your top: Implicit evaluation of emotion
regulation predicts affective responding to anger provocation. Person-
ality and Social Psychology Bulletin, 32, 589 – 602. http://dx.doi.org/10
.1177/0146167205283841
McConnell, A. R., & Leibold, J. M. (2001). Relations among the Implicit
Association Test, discriminatory behavior, and explicit measures of
racial attitudes. Journal of Experimental Social Psychology, 37, 435–
442. http://dx.doi.org/10.1006/jesp.2000.1470
Morrison, A. S., & Heimberg, R. G. (2013). Social anxiety and social
anxiety disorder. Annual Review of Clinical Psychology, 9, 249 –274.
http://dx.doi.org/10.1146/annurev-clinpsy-050212-185631
Moscovitch, D. A. (2009). What is the core fear in social phobia? A new
model to facilitate individualized case conceptualization and treatment.
Cognitive and Behavioral Practice, 16, 123–134. http://dx.doi.org/10
.1016/j.cbpra.2008.04.002
Nezlek, J. B. (2007). A multilevel framework for understanding relation-
ships among traits, states, situations and behaviours. European Journal
of Personality, 21, 789 – 810. http://dx.doi.org/10.1002/per.640
Nezlek, J. B. (2011). Multilevel modeling for social and personality psy-
chology. London, UK: SAGE. http://dx.doi.org/10.4135/978144
6287996
Nezlek, J. B. (2012). Diary methods for social and personality psychology.
London, UK: SAGE.
Nezlek, J. B., & Kuppens, P. (2008). Regulating positive and negative
emotions in daily life. Journal of Personality, 76, 561–580. http://dx.doi
.org/10.1111/j.1467-6494.2008.00496.x
Norman, E., & Furnes, B. (2016). The concept of “metaemotion”: What is
there to learn from research on metacognition? Emotion Review, 8,
187–193. http://dx.doi.org/10.1177/1754073914552913
Nosek, B. A. (2007). Implicit– explicit relations. Current Directions in
Psychological Science, 16, 65– 69. http://dx.doi.org/10.1111/j.1467-
8721.2007.00477.x
Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., & Tetlock, P. E.
(2013). Predicting ethnic and racial discrimination: A meta-analysis of
IAT criterion studies. Journal of Personality and Social Psychology,
105, 171–192. http://dx.doi.org/10.1037/a0032734
Rapee, R. M., & Heimberg, R. G. (1997). A cognitive-behavioral model of
anxiety in social phobia. Behaviour Research and Therapy, 35, 741–756.
http://dx.doi.org/10.1016/S0005-7967(97)00022-3
Raudenbush, S. W., & Liu, X. (2000). Statistical power and optimal design
for multisite randomized trials. Psychological Methods, 5, 199 –213.
http://dx.doi.org/10.1037/1082-989X.5.2.199
R Core Team. (2014). R: A language and environment for statistical
computing. Retrieved from http://www.R-project.org/
Reis, H. T., & Gable, S. L. (2000). Event-sampling and other methods for studying
everyday experience. In H. T . Reis & C. M. Judd (Eds.), Handbook of
research methods in social and personality psychology (pp. 190 –222).
New York, NY: Cambridge University Press. Retrieved from https://
assets.cambridge.org/97811070/11779/frontmatter/9781107011779_
frontmatter.pdf
Romero, C., Master, A., Paunesku, D., Dweck, C. S., & Gross, J. J. (2014).
Academic and emotional functioning in middle school: The role of
implicit theories. Emotion, 14, 227–234. http://dx.doi.org/10.1037/
a0035490
Schroder, H. S., Callahan, C. P., Gornik, A. E., & Moser, J. S. (2019). The
fixed mindset of anxiety predicts future distress: A longitudinal study.
Behavior Therapy, 50, 710 –717. http://dx.doi.org/10.1016/j.beth.2018
.11.001
Schroder, H. S., Dawood, S., Yalch, M. M., Donnellan, M. B., & Moser,
J. S. (2015). The role of implicit theories in mental health symptoms,
emotion regulation, and hypothetical treatment choices in college stu-
dents. Cognitive Therapy and Research, 39, 120 –139. http://dx.doi.org/
10.1007/s10608-014-9652-6
Schwartz, J. E., Neale, J., Marco, C., Shiffman, S. S., & Stone, A. A.
(1999). Does trait coping exist? A momentary assessment approach to
the evaluation of traits. Journal of Personality and Social Psychology,
77, 360 –369. http://dx.doi.org/10.1037/0022-3514.77.2.360
Schwartz, S. H. (1992). Universals in the content and structure of values:
Theoretical advances and empirical tests in 20 countries. In M. P. Zanna
(Ed.), Advances in experimental social psychology (Vol. 25, pp. 1– 65).
New York, NY: Academic Press. http://dx.doi.org/10.1016/S0065-
2601(08)60281-6
Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs,
G. A. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto,
CA: Consulting Psychologists Press.
Spokas, M., Luterek, J. A., & Heimberg, R. G. (2009). Social anxiety and
emotional suppression: The mediating role of beliefs. Journal of Behav-
ior Therapy and Experimental Psychiatry, 40, 283–291. http://dx.doi
.org/10.1016/j.jbtep.2008.12.004
Sung, S. C., Porter, E., Robinaugh, D. J., Marks, E. H., Marques, L. M.,
Otto, M. W.,...Simon, N. M. (2012). Mood regulation and quality of
life in social anxiety disorder: An examination of generalized expectan-
cies for negative mood regulation. Journal of Anxiety Disorders, 26,
435– 441. http://dx.doi.org/10.1016/j.janxdis.2012.01.004
Tamir, M., & Ford, B. Q. (2012). When feeling bad is expected to be good:
Emotion regulation and outcome expectancies in social conflicts. Emo-
tion, 12, 807– 816. http://dx.doi.org/10.1037/a0024443
Tamir, M., John, O. P., Srivastava, S., & Gross, J. J. (2007). Implicit
theories of emotion: Affective and social outcomes across a major life
transition. Journal of Personality and Social Psychology, 92, 731–744.
http://dx.doi.org/10.1037/0022-3514.92.4.731
Tamir, M., & Mauss, I. B. (2011). Social cognitive factors in emotion
regulation: Implications for well-being. In I. Nyklíek, A. D. Vinger-
hoets, & M. Zeelenberg (Eds.), Emotion regulation and well-being (pp.
31– 47). New York, NY: Springer. http://dx.doi.org/10.1007/978-1-
4419-6953-8_3
Todd, M., Tennen, H., Carney, M. A., Armeli, S., & Affleck, G. (2004). Do
we know how we cope? Relating daily coping reports to global and
time-limited retrospective assessments. Journal of Personality and So-
cial Psychology, 86, 310 –319. http://dx.doi.org/10.1037/0022-3514.86
.2.310
Uhlmann, E. L., Pizarro, D. A., & Bloom, P. (2008). Varieties of social
cognition. Journal for the Theory of Social Behaviour, 38, 293–322.
http://dx.doi.org/10.1111/j.1468-5914.2008.00372.x
Veilleux, J. C., Salomaa, A. C., Shaver, J. A., Zielinski, M. J., & Pollert,
G. A. (2015). Multidimensional assessment of beliefs about emotion:
Development and validation of the emotion and regulation beliefs scale.
Assessment, 22, 86 –100. http://dx.doi.org/10.1177/1073191114534883
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.
854 GOODMAN, KASHDAN, AND I
˙MAMOG
˘LU
Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A
meta-analysis of the effectiveness of strategies derived from the process
model of emotion regulation. Psychological Bulletin, 138, 775– 808.
http://dx.doi.org/10.1037/a0027600
Weeks, J. W., & Howell, A. N. (2012). The bivalent fear of evaluation
model of social anxiety: Further integrating findings on fears of positive
and negative evaluation. Cognitive Behaviour Therapy, 41, 83–95.
http://dx.doi.org/10.1080/16506073.2012.661452
Weiss, H., Beal, D. J., Lucy, S. L., & MacDermid, S. M. (2004). Con-
structing EMA studies with PMAT: The Purdue Momentary Assessment
Tool user’s manual. West Lafayette, IN: Purdue University Military
Family Research Institute.
Werner, K. H., Goldin, P. R., Ball, T. M., Heimberg, R. G., & Gross, J. J.
(2011). Assessing emotion regulation in social anxiety disorder: The
emotion regulation interview. Journal of Psychopathology and Behav-
ioral Assessment, 33, 346 –354. http://dx.doi.org/10.1007/s10862-011-
9225-x
Williams, K. E., Chambless, D. L., & Ahrens, A. (1997). Are emotions
frightening? An extension of the fear of fear construct. Behaviour
Research and Therapy, 35, 239 –248. http://dx.doi.org/10.1016/S0005-
7967(96)00098-8
Yoon, S., Dang, V., Mertz, J., & Rottenberg, J. (2018). Are attitudes
towards emotions associated with depression? A conceptual and meta-
analytic review. Journal of Affective Disorders, 232, 329 –340. http://dx
.doi.org/10.1016/j.jad.2018.02.009
Received May 11, 2019
Revision received January 22, 2020
Accepted February 2, 2020
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EMOTION BELIEFS IN SOCIAL ANXIETY
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Objective: We investigated how individual differences in emotion regulation goals predict emotion regulation strategy use in daily life. Method: Across three studies, we assessed two common types of emotion regulation goals (hedonic, social) and strategies spanning the entire process model of emotion regulation (Gross, 1998b). We conducted two studies using global measures with undergraduates (N = 394; 18-25 years; 69% female; 56% European-American) and community members (N = 302; 19-74 years; 50% female; 75% European-American), and a 9-day daily diary study with another community sample (N = 272; 23-85 years; 50% female; 84% European-American). Results: Globally and in daily life, pro-hedonic goals were positively associated with all antecedent-focused strategies (situation selection, situation modification, distraction, reappraisal), pro-social goals were positively linked to reappraisal, and impression management goals positively predicted suppression. Contra-hedonic goals were negatively associated with reappraisal and positively associated with suppression in some studies. Conclusions: The reasons why people regulate their emotions are predictive of the strategies they use in daily life. These links may be functional, such that people typically use strategies that are suitable for their goals. These findings demonstrate the value of an individual difference approach and highlight the motivational component of emotion regulation.
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The world is complicated, and we hold a large number of beliefs about how it works. These beliefs are important because they shape how we interact with the world. One particularly impactful set of beliefs centers on emotion, and a small but growing literature has begun to document the links between emotion beliefs and a wide range of emotional, interpersonal, and clinical outcomes. Here we review the literature that has begun to examine beliefs about emotion, focusing on two fundamental beliefs, namely whether emotions are good versus bad and whether emotions are controllable versus uncontrollable. We then consider one underlying mechanism that we think may link these emotion beliefs with downstream outcomes, namely emotion regulation. Finally, we highlight the role of beliefs about emotion across various psychological disciplines and outline several promising directions for future research.
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Objective: We investigated how the Big Five traits predict individual differences in five theoretically important emotion regulation goals that are commonly pursued – pro-hedonic, contra-hedonic, performance, pro-social, and impression management. Method: We conducted two studies: (1) a large survey study consisting of undergraduates (N = 394; 18-25 years; 69% female; 56% European-American) and community adults (N = 302; 19-74 years; 50% female; 75% European-American) who completed a newly developed global measure of individual differences in emotion regulation goals and (2) a 9-day daily diary study with community adults (N = 272; 50% female; 84% European-American) who completed daily reports of emotion regulation goals. In both studies, participants completed a measure of the Big Five. Results: Across global and daily measures, pro-hedonic goals and pro-social goals were positively associated with agreeableness, performance goals were positively associated with openness, and impression management goals were positively associated with neuroticism. Globally, contra-hedonic goals were also negatively associated with agreeableness and conscientiousness. Conclusions: The Big Five systematically predict the emotion regulation goals people typically pursue. These findings have important implications for understanding why people engage in certain forms of regulatory behavior and why personality has consequences for well-being.