Journal of Anxiety Disorders 37 (2016) 71–77
Contents lists available at ScienceDirect
Journal of Anxiety Disorders
Theory of mind in social anxiety disorder, depression, and comorbid
conditions
Dustin Washburn ∗ , Gillian Wilson, Meighen Roes, Katerina Rnic, Kate Leslie Harkness ∗∗
Department of Psychology, Queen’s University, Kingston, ON K7L3N6, Canada
a r t i c l e
i n f o
Article history:
Received 14 January 2015
Received in revised form 4 November 2015
Accepted 7 November 2015
Available online 22 November 2015
Keywords:
Social anxiety disorder
Theory of mind
Major depression
Comorbidity
a b s t r a c t
Social anxiety disorder is characterized by marked interpersonal impairment, particularly when presenting with comorbid major depression. However, the foundational social-cognitive skills that underlie
interpersonal impairment in comorbid and non-comorbid manifestations of SAD has to date received very
little empirical investigation. In a sample of 119 young adults, the current study examined differences
in theory of mind (ToM), defined as the ability to decode and reason about others’ mental states, across
four groups: (a) non-comorbid SAD; (b) non-comorbid Lifetime MDD; (c) comorbid SAD and Lifetime
MDD; and (d) healthy control. The non-comorbid SAD group was significantly less accurate at decoding
mental states than the non-comorbid MDD and control groups. Further, both the comorbid and noncomorbid SAD groups made significantly more ‘excessive’ ToM reasoning errors than the non-comorbid
MDD group, suggesting a pattern of over-mentalizing. Findings are discussed in terms of their implications
for understanding the social cognitive foundations of social anxiety.
© 2015 Elsevier Ltd. All rights reserved.
1. Introduction
Social anxiety disorder (SAD) is characterized by a marked
and persistent fear of social evaluation (APA, 2000). SAD is a
chronic and debilitating psychiatric disorder that is associated with
poor educational and occupational attainment, marked social and
interpersonal impairment, and substantial psychiatric and medical comorbidity (Grant et al., 2005). Individuals with SAD display
a number of negative interpersonal behaviors, including interpersonal dependency, conflict avoidance, and avoidance of emotion,
that result in weak interpersonal ties and eventual social isolation
(see Davila & Beck, 2002). Given the degree and chronicity of social
and interpersonal impairment associated with SAD it is important
to understand the underlying social-cognitive mechanisms.
Critical to successful social and interpersonal functioning is having a ‘theory of mind’ (ToM), or the ability to accurately decode
and reason about the beliefs, intentions, desires, and emotions
of others (Wellman, 1990). ToM is a universal human skill that
involves two separate, but related components (Sabbagh, 2004).
First, theory of mind ‘decoding’ involves the foundational skill of
accurately labeling others’ mental states (e.g., decoding that a conversation partner is ‘interested’ based on facial expression). Second,
theory of mind ‘reasoning’ involves using others’ mental states to
∗ Corresponding author. Fax: +1 613 533 2499.
∗∗ Corresponding author.
E-mail address: [email protected] (D. Washburn).
http://dx.doi.org/10.1016/j.janxdis.2015.11.004
0887-6185/© 2015 Elsevier Ltd. All rights reserved.
make predictions about their future behavior (e.g., reasoning that
one’s conversational partner will continue the conversation based
on one’s judgment that he or she is interested). Deficits in ToM
decoding and reasoning have been reported in a number of clinical
conditions characterized by severe social and interpersonal dysfunction, including autism spectrum disorder (e.g., Baron-Cohen
et al., 1999), schizophrenia (e.g., Frith & Corcoran, 1996), and major
depressive disorder (MDD; e.g., Lee, Harkness, Sabbagh, & Jacobson,
2005).
Despite the fact that SAD presents with marked social and interpersonal dysfunction as a primary impairment, only two studies to
our knowledge have examined ToM skill in individuals with social
anxiety. First, in a community sample of adults, Samson, Lackner,
Weiss, & Papousek (2012) found that higher scores on a measure
of social anxiety were significantly related to lower enjoyment
of humorous cartoons that involved resolving incongruity about
others’ false mental states. The researchers theorized from these
results that humor that involves ToM reasoning may elicit negative affect in individuals with high levels of social anxiety, thus
interfering with its enjoyment.
Second, Hezel and McNally (2014) found that individuals with
a diagnosis of SAD were significantly impaired relative to healthy
controls on tasks of ToM decoding and ToM reasoning. Specifically,
individuals with SAD were significantly less accurate than controls
at decoding the subtle mental states portrayed by photographs
of eyes in the Reading the Mind in the Eyes task (Baron-Cohen,
Wheelwright, Hill, Raste, & Plumb, 2001), particularly if the eyes
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D. Washburn et al. / Journal of Anxiety Disorders 37 (2016) 71–77
depicted mental states of a negative valence. Further, individuals
with SAD were significantly impaired relative to controls at reasoning about the intentions and beliefs of characters presented
in movie clips in the Movie Assessment of Cognition task (MASC;
Dziobek et al., 2006). In particular, they showed a pattern of performance that was consistent with using excessive ToM. That is,
they over-interpreted the mental states of the characters in the
film clips. Hezel and McNally (2014) suggest from this latter finding
that individuals with SAD may show “cognitive empathy” towards
others, which could explain their tendency to “over-mentalize”
others’ perspectives (see also Tibi-Elhanany & Shamay-Tsoory,
2011). However, this interpretation is inconsistent with results
showing that individuals with SAD performed more poorly than
controls on the Eyes task, which also requires respondents to
put themselves into the minds of others (see Harkness, Sabbagh,
Jacobson, Chowdrey, & Chen, 2005). Therefore, further investigation of the differential pattern of performance across tasks of
ToM decoding and ToM reasoning, and across different diagnostic groups is required. Nevertheless, these studies are important in
suggesting that deficits in the foundational social cognitive skills of
ToM decoding and reasoning may underlie the marked social and
interpersonal impairment shown by individuals with SAD.
One critical question that remains unanswered from the studies cited above concerns the extent to which deficits in ToM in
individuals with SAD can be accounted for by comorbid conditions
that are associated with social-cognitive impairment. In particular, 20–37% of individuals with SAD also suffer from Lifetime major
depressive disorder (MDD; Merikangas & Angst, 1995; Ohayon &
Schatzberg, 2010). Similar to SAD, MDD is associated with excessive
negative self-focused attention (Mor & Winquist, 2002), negative
interpersonal behaviors such as avoidance, and marked interpersonal impairment (Alden & Taylor, 2004; Segrin & Abramson, 1994).
Consistent with the hypothesis that deficits in the foundational
social-cognitive skill of ToM underlie interpersonal impairment,
several studies have documented deficits in ToM decoding and ToM
reasoning in patients with MDD relative to healthy controls both
when in episode (Lee et al., 2005; Wang, Wang, Chen, Zhu, & Wang,
2008; Kettle, O’Brien-Simpson, & Allen, 2008) and upon remission
(Inoue, Tonooka, Yamada, Kanba, 2004; Inoue, Yamada, & Kanba,
2006; Harkness, Jacobson, Duong, & Sabbagh, 2010).
Individuals with comorbid SAD and MDD report even higher
levels of avoidance of negative emotional stimuli, higher levels
of social avoidance, and greater impairments in social functioning
than those with SAD or MDD alone (Aderka et al., 2012; Dalrymple &
Zimmerman, 2007; LeMoult & Joormann, 2012; Ottenbreit, Dobson,
& Quigley, 2014). Therefore, there is reason to suspect that individuals with comorbid SAD and MDD may show lower levels of
ToM performance than non-comorbid conditions. Indeed, given the
strong comorbidity between MDD and SAD, and the presence in
both conditions of significant social-cognitive and interpersonal
impairment, it is important to clarify the extent to which deficits
in performance associated with MDD or SAD shown in previous
studies can be better accounted for by their comorbidity.
Individuals with SAD (either alone or comorbid with MDD) also
differ from those with MDD alone on a number of variables that
are of crucial relevance to social cognition. For example, they show
significantly greater avoidance of social situations (Ottenbreit et al.,
2014), and greater avoidance of negative emotional stimuli (e.g.,
angry faces; Kircanski, Joormann, & Gotlib, 2014). This prior literature suggests that individuals with SAD, whether or not comorbid
with MDD, may show greater ToM deficits than those with MDD
alone. Therefore, the goal of the current study was to compare
ToM decoding and ToM reasoning accuracy across four diagnostic
groups: 1. Those with a diagnosis of SAD and no comorbid lifetime
diagnosis of MDD; 2. Those with a lifetime diagnosis of MDD and no
comorbid SAD; 3. Comorbid SAD and lifetime MDD; and 4. Healthy
controls with no history of a psychiatric diagnosis. We employed
the Eyes task to assess ToM decoding and the MASC task to assess
ToM reasoning. We hypothesized that the SAD only and comorbid
groups would evidence significantly lower accuracy on the Eyes
and MASC tasks than the Lifetime MDD only and control groups.
Further, we hypothesized that the Lifetime MDD only group would
evidence significantly lower accuracy on the Eyes and MASC tasks
than the Healthy control group.
2. Materials and methods
2.1. Subjects
The General Research Ethics Board at Queen’s University
approved this study. All participants provided written informed
consent. Participants included 119 individuals (81 females; ages
17–36, M = 19.38, SD = 2.87; 65% European–Canadian, 31% Asian, 4%
Other ethnicity) recruited from an introductory psychology class.
All students from the introductory psychology class completed the
Beck Depression Inventory-II (BDI-II; Beck, 1996) and the Social
Anxiety and Avoidance Scale for Adolescents (SAASA; Cunha, PintoGouveia, & do Céu Salvador, 2008) during a prescreening session
held at the beginning of the academic year. To increase our chances
of recruiting individuals with a history of depression and social anxiety symptoms, we oversampled from this prescreen pool students
with elevated scores on the BDI-II (over 10) or SAASA (over 70).
Community advertisements also targeted socially anxious individuals. Exclusion criteria were a lifetime history of psychotic disorder,
manic episodes, drug/alcohol dependence, or developmental disability.
All potential participants underwent an initial telephone screen
performed by the first author that queried for exclusion criteria.
This telephone screen also included the depressive disorder and
the SAD modules of the Structured Clinical Interview for DSM-IV
Axis I Disorders (SCID-I/P; First, Spitzer, Gibbon, & Williams, 2002).
Potential participants were invited to participate in the study if
they answered ‘no’ to the questions querying the exclusion criteria and met criteria based on the SCID-I/P modules for one of our
study groups (lifetime MDD, SAD, comorbid lifetime MDD and SAD,
or no history of MDD or SAD). An initial 121 individuals passed
the phone screen and were invited to participate. Two participants
were excluded because they scored more than two standard deviations below the sample mean on the MASC task, leaving a final
sample of 119.
2.2. Measures
2.2.1. Diagnostic interview
The Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I/P; First et al., 2002) was administered at the time
of the study to confirm diagnoses by clinical psychology graduate and senior undergraduate students trained to reliability under
the senior author’s supervision (Ä = .71–1.00). Participants were
assigned to the study groups based on their clinical diagnoses as
determined by the in-person SCID-I/P as follows: (a) SAD only
(n = 12) consisted of those who met current DSM-IV criteria for SAD
and did not have a history of MDD; (b) Lifetime MDD only (n = 40)
included individuals with a current or past episode of MDD and
no current diagnosis of SAD; (c) Comorbid SAD and Lifetime MDD
(n = 24) included individuals diagnosed with both current SAD and
a current or past episode of MDD; or (d) Healthy Control (n = 43)
included those who had never met criteria for SAD or MDD or any
other psychiatric diagnosis.
2.2.2. Depression and social anxiety measures
At the experimental session participants again completed the
BDI-II and SAASA, and means and standard deviations on these
D. Washburn et al. / Journal of Anxiety Disorders 37 (2016) 71–77
73
Table 1
Descriptive statistics of demographic variables, BDI, and SAASA scores stratified by group.
Lifetime MDD
(n = 40)
SAD
(n = 12)
Comorbid
(n = 24)
Control
(n = 43)
Age M (SD)
Sex: Female n (%)
19.73 (3.43)
28 (70)
19.83 (4.11)
7 (58.3)
19.71 (2.81)
18 (75)
18.74 (1.71)
28 (65)
Ethnicity (n/%)
White
Asian
Other
28 (70)
11 (27.5)
1 (2.5)
5 (41.7)
6 (50)
1 (8.3)
15 (62.5)
9 (37.5)
0 (0)
29 (67.4)
11 (25.6)
3 (7)
BDI-II
M (SD)
Range
16.38a (10.12)
1.00–46.00
16.92a (11.41)
2.00–18.00
19.71a (11.19)
0.00–38.00
7.35b (6.88)
0.00–29.00
SAASA
M (SD)
Range
Anxiety M (SD)
Avoidance M (SD)
92.85 (21.70)b
48.50–136.00
100.53 (23.39)b
85.18 (21.56)b
113.13a (20.12)
78.50–136.00
122.00a (20.31)
104.25a (21.12)
111.92a (19.91)
78.00–147.50
120.42a (22.07)
103.42a (19.94)
77.12c (18.49)
45.00–130.50
82.91c (20.00)
71.33c (18.52)
Notes: BDI-II = Beck depression inventory; SAASA = Social anxiety and avoidance scale for adolescents.
a
Group differences were significant at p < .01.
b
Group differences were significant at p < .01.
c
Group differences were significant at p < .01.
measures by group are provided for descriptive purposes in Table 1.
The BDI-II is a 21-item self-report questionnaire measuring depression symptom severity (Cronbach’s alpha = .94). The SAASA is a
self-report questionnaire assessing the degree of (a) avoidance
and (b) anxiety from 34 social situations (e.g., “eating in public”,
“being alone with a classmate of the opposite sex”). Avoidance
and anxiety are rated separately on a 5-point scale from 1 – not
anxious/never avoid to 5 – very anxious/almost always avoid (Cronbach’s alpha = .97). Separate avoidance and anxiety subscale scores
are derived by summing the scores for each item. A total SAASA
score is calculated as the mean of the anxiety and avoidance subscales. Thus, the maximum total score is 170. We chose the SAASA
as a measure of social anxiety given the closeness in age of undergraduates to the adolescents on which the SAASA was validated,
and our reasoning that the content of the items was a good match
to the social environment of our young undergraduate sample (e.g.,
“Going to a party given by a classmate”; “performing, for the first
time, a new task or role in front of classmates”).
2.2.3. Reading the mind in the eyes task (Eyes task; Baron-Cohen
et al., 2001)
The Eyes task is a ToM decoding task consisting of 36 black-andwhite photographs of the eye region of faces. Each pair of eyes was
standardized to 15 × 6 cm and presented centered between four
mental state adjectives located in each corner, equally spaced from
the center of a computer screen (e.g., annoyed, horrified, hostile,
preoccupied). Participants chose their response by pressing one
of four keys (S, X, K, M), identified by stickers that were spatially
analogous to the location of the adjectives. Participants’ responses
and response latencies in milliseconds (ms) were digitally recorded.
The Eyes stimuli include three emotional valence categories: positive (e.g. “Friendly”), neutral (e.g. “Reflective”) and negative (e.g.
“Upset”) (see Harkness et al., 2005).
2.2.4. Animals task (Harkness et al., 2005)
The Animals task has been used in a number of previous studies
(Harkness et al., 2005, 2010; Harkness, Washburn, Theriault, Lee, &
Sabbagh, 2011; Lee et al., 2005) as a control to ensure that group
differences on the Eyes task can be ascribed to differences in mental
state decoding rather than to task demands or low-level perceptual
processing. The task includes 12 black-and-white photographs of
animals presented in a format similar to the Eyes task. Participants
were required to choose the correct adjective from an array of four
describing a trait of the animal (e.g., aloof, ferocious, timid, obedient). Responses and response latencies in milliseconds (ms) were
digitally recorded.
2.2.5. Movie for the assessment of cognition (MASC; Dziobek
et al., 2006)
The MASC is a ToM reasoning task in which participants watched
a 15-min video of four actors interacting at a dinner party. The
video was paused at 45 time points and participants were required
to answer questions probing their understanding of the characters’ feelings, thoughts, and intentions at the point at which the
film was stopped (e.g., “What is Betty feeling?”). For each question,
participants chose from one of four possible answers in multiplechoice format. For each question, each of the four possible answers
reflected either: (1) ‘correct’ ToM reasoning (i.e., an appropriate
level of ToM reasoning), (2) excessive ToM, representing overinterpretative mental state reasoning, (3) insufficient, or reduced,
mental state reasoning, and (4) no ToM ability, or non-mental state
reasoning (i.e., physical causation). Percent correct responses, indicating appropriate ToM reasoning ability, were calculated as the
total number of correct responses divided by 45 questions and multiplied by 100. Percent of each type of error was calculated as the
number of items on which participants endorsed each error divided
by the 45 questions and multiplied by 100. In addition to the 45
ToM questions, six questions were control items requiring nonsocial inferencing (e.g., “How did Cliff likely shave when he was
in Sweden?”). Performance on the control items was calculated as
the number of correct responses out of the total number of control
items (n = 6).
2.3. Procedure
After providing written informed consent, participants were
seated at a computer and completed the Eyes and MASC tasks in
counter-balanced order. For the Eyes task, participants completed
a practice trial followed by the Eyes and Animals task trials randomly combined in a single block of 48 trials (36 trials for the Eyes
and 12 Animals tasks). For the MASC, participants were told to follow the instructions that appeared on the screen. Participants were
instructed to respond as quickly and accurately as possible. Participants then completed the SAASA, BDI-II, and SCID-I/P interview.
Participants were compensated with course research credit or $20.
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D. Washburn et al. / Journal of Anxiety Disorders 37 (2016) 71–77
Table 2
Correlations between task accuracy and symptom measures.
SAASA
Eyes Task
Positive
Neutral
Negative
Animals Task
MASC Total
Excessive ToM
Low ToM
No ToM
*
BDI-II
SAASA
.54*
−.071
−.077
−.069
−.003
−.028
−.044
.059
−.001
.020
–
−.065
−.15
−.050
.055
−.087
−.034
.11
−.065
−.051
p < .001
3. Results
3.1. Preliminary analyses
Descriptive characteristics of the sample stratified by diagnostic
group are presented in Table 1. Groups did not differ significantly
on age, sex, ethnicity, or education (all ps > .35).1 As expected given
that state depression symptoms are generally elevated in individuals with SAD (Coles, Gibb, & Heimberg, 2001) and in those
with a history of MDD (Paykel et al., 1995), in the current sample
the Lifetime MDD, SAD, and Comorbid groups scored significantly
higher on the BDI-II than controls, F(3, 115) = 11.20, p < .001, partial
Á2 = .23. Further, as expected, the SAD and Comorbid groups had
significantly higher SAASA scores than the Lifetime MDD group,
which scored significantly higher than controls, F(3, 115) = 20.12,
p < .001, partial Á2 = .34. Neither Eyes task accuracy nor any of the
subscales of the MASC were significantly associated with any of the
demographic characteristics (all ps > .31).
As expected, accuracy on the Eyes task was significantly positively correlated with accuracy on the Animals task, r(117) = .38,
p < .001. Further, accuracy on the Eyes task was significantly positively correlated with total accuracy on the MASC task, r(117) = .21,
p = .02. However, as shown in Table 2, correlations between BDI-II
and SAASA scores and accuracy on the Eyes and MASC tasks, partialling variance accounted for by Animals task accuracy and MASC
control item accuracy, respectively, were not significant.
3.2. Group differences in ToM decoding
Descriptive statistics for the primary study variables by group
are presented in Table 3. Group differences in Eyes task accuracy
were evaluated with a one-way Analysis of Covariance (ANCOVA)
including Animals task accuracy and Eyes response latencies as
covariates. Three a priori contrasts were specified as per the study
hypotheses to compare the Lifetime MDD to the SAD only and
Comorbid groups, and the Lifetime MDD group to the Control group.
The omnibus effect of group was significant, F(3, 113) = 3.26,
p = .02, partial Á2 = .08. Consistent with hypotheses, the SAD only
group performed significantly more poorly on the Eyes task than
the Lifetime MDD only group, t(113) = 3.86, p < .001. Contrary to
hypotheses, the Comorbid group did not perform significantly more
poorly on the Eyes task than the Lifetime MDD group, t(113) = 0.02,
p = .89, and the Lifetime MDD group did not perform significantly
more poorly than the Control group, t(113) = .27, p = .47.
1
In preliminary model building we ran the primary models below including sex,
ethnicity, and education, separately, as covariates. Inclusion of these variables did
not change the pattern of results. Therefore, for the sake of parsimony and ease of
interpretation, we present the models without sex, age, and ethnicity below. Results
of the models with covariates are available upon request.
To determine whether a relation of group and Eyes task accuracy was specific to stimulus valence, we conducted a 3 (valence:
positive, negative, neutral) × 4 (group) mixed model ANOVA with
valence as the within-group factor and group as the between-group
factor. There was no evidence of a significant main effect of valence,
F(2, 113) = .45, p = .64, partial Á2 = .008, nor was there a significant
valence by group interaction, F(2, 113) = 2.33, p = .10, partial Á2 = .04.
Instead, replicating the overall accuracy results above, orthogonal contrast results indicated that the SAD only group performed
more poorly than the Lifetime MDD group across the positive,
t(115) = 2.22, p = .03, negative (as a trend), t(115) = 1.72, p = .09, and
neutral eyes, t(115) = 2.15, p = .03. Further, the SAD only group
performed significantly more poorly than the Control group on
the positive, t(115) = 2.66, p = .009 and neutral eyes, t(115) = 2.00,
p = .048. As in the overall accuracy analyses, no other group comparisons were significant.
3.3. Group differences in ToM reasoning
We evaluated group differences in accuracy on the MASC task
with a one-way ANCOVA controlling for accuracy on the Control
items. The omnibus ANCOVA failed to reach statistical significance,
F(3, 114) = 1.58, p = .20, partial Á2 = .04, although the orthogonal
contrasts confirmed hypotheses that the SAD and Comorbid groups
performed significantly more poorly than the Lifetime MDD group,
t(115) = 1.79, p = .038.
An analysis of group differences on MASC error types revealed
that the SAD only group, t(115) = 2.66, p = .009, and the Comorbid
group, t(115) = 2.51, p = .052, at a trend, made more excessive ToM
errors than the Lifetime MDD group, and the Lifetime MDD group
did not differ significantly from controls, t(115) = 1.16, p = .25. No
significant group differences were found for errors involving insufficient ToM, ts(115) < .54, ps > .60, or no ToM, ts(115) < .83, ps > .40.
4. Discussion
Consistent with hypotheses, individuals with SAD were significantly less accurate at decoding the subtle social features of eye
expressions than were those with MDD. However, this effect was
specific to non-comorbid conditions. Those with comorbid SAD
and lifetime MDD did not differ significantly from MDD alone or
from healthy controls. Very few studies have compared those with
SAD alone to those with comorbid SAD and MDD, but those that
have consistently find greater functional impairment in comorbid presentations (e.g., Aderka et al., 2012). Therefore, we were
surprised to find worse ToM decoding performance only in the noncomorbid SAD group. SAD generally precedes the onset of MDD,
and longitudinal studies have shown that those with SAD who go
on to develop MDD are characterized by higher levels of interpersonal over-sensitivity and social impairment than those who
do not (e.g., Katz, Conway, Hammen, Brennan, & Najman, 2011;
Starr, Hammen, Connolly, & Brennan, 2014). By definition, individuals who endorse high levels of interpersonal sensitivity think
and care more about what others are thinking and feeling. This
construct has, thus, been proposed as one explanation for the paradoxical findings linking some clinical conditions (e.g., subthreshold
depression, borderline personality disorder) with enhanced theory
of mind decoding abilities (see Dinsdale & Crespi, 2013; Franzen
et al., 2011; Harkness et al., 2005, 2010, 2011; Harkness, Jacobson,
Sinclair, Chan, & Sabbagh, 2012). That is, these groups may be significantly more accurate than others at decoding mental states
because they are more sensitive to (i.e., care more about) what
others may be thinking and feeling. Therefore, perhaps individuals
with non-comorbid SAD who never develop MDD suffer from the
central social avoidance that characterizes SAD generally, and that
D. Washburn et al. / Journal of Anxiety Disorders 37 (2016) 71–77
75
Table 3
Group means and standard deviations for the eyes and MASC tasks.
M (SD)
Lifetime MDD (n = 40)
SAD (n = 12)
Comorbid (n = 24)
Control (n = 43)
Eyes Accuracy
Positive Eyes
Negative Eyes
Neutral Eyes
Eyes Response Latency
Animals Accuracy
MASC Accuracy
72.57 (8.21)
72.50 (18.32)
74.55 (13.99)
71.25 (10.94)
4105.34 (1134.55)
72.71 (13.87)
77.94 (8.29)
62.04 (15.99)
59.26 (19.73)
65.15 (19.70)
61.46 (15.95)
6005.46 (3833.54)
68.06 (22.14)
74.07 (8.17)
71.53 (9.91)
71.30 (18.51)
75.00 (15.92)
69.27 (14.50)
4512.29 (1607.96)
70.00 (15.61)
74.17 (8.74)
70.87 (12.08)
74.94 (17.16)
68.08 (18.11)
70.49 (15.27)
4187.38 (1760.42)
72.48 (17.21)
77.00 (7.61)
MASC Errors
Excessive ToM
Low ToM
No ToM
MASC Control
11.94 (6.89)
6.61 (3.81)
2.67 (2.48)
75.00 (14.12)
17.22 (6.22)
5.93 (3.83)
2.22 (2.32)
70.83 (22.61)
15.00 (4.83)
6.94 (4.11)
3.24 (2.78)
79.86 (16.28)
13.49 (5.73)
6.51 (4.15)
2.53 (2.81)
74.42 (17.19)
Notes: MASC = Movie for the Assessment of Social Cognition; ToM = Theory of mind.
would prevent an entraining of accuracy at decoding social stimuli, and they also lack the interpersonal orientation of depression
vulnerability that could provide the motivation to override this central social-cognitive deficit. This explanation is very speculative at
present, particularly given the small size of the non-comorbid SAD
group. However, the current results highlight the need for more
research specifically comparing comorbid and non-comorbid SAD
on measures of social cognition and interpersonal outcomes.
Contrary to the results of Hezel and McNally (2014), the poor
ToM decoding performance shown by those with non-comorbid
SAD was not specific to eyes of a negative valence, but held across
the positive, negative, and neutral valence categories. Indeed, in
our sample, group differences were weakest for the negative eyes.
In our previous work using the Eyes task in samples of individuals
with depression we have also generally failed to find valence effects
(e.g., Harkness et al., 2005, 2012; Lee et al., 2005). These results
would appear to be inconsistent with the wealth of literature in
the area of cognition more generally showing that individuals with
SAD and MDD show biased attention to negative facial stimuli
and valence-specific deficits in facial emotion recognition. However, the negative mental states included in the Eyes task are more
complex and subtle than the basic emotions portrayed in studies of biased attention and facial recognition (sad, angry, fearful).
Further, the negative category in the Eyes task includes a wide
range of mental states that represent sadness (“upset,” “regretful”), anger (“hostile,” “defiant”), and fear (“worried,” “nervous”).
In studies of biased attention, individuals with SAD show a preferential bias to angry and threatening facial stimuli (Kircanski et al.,
2014; LeMoult & Joormann, 2012; Mogg & Bradley, 2002), whereas
individuals with MDD show attentional biases preferentially to sad
facial expressions (see Bourke, Douglas, & Porter, 2010). Therefore,
it is possible that group by valence effects would emerge more
consistently in studies of mental state decoding if a more finegrained approach to categorizing negative mental states were taken
in future research.
Consistent with hypotheses, both the comorbid and noncomorbid SAD groups showed a pattern of excessive ToM reasoning
on the MASC task relative to healthy controls. Further, the current
results extend those of Hezel and McNally (2014) by showing that
individuals with SAD also significantly differed in their ToM reasoning abilities to those with MDD alone. Specifically, those with
SAD over-interpreted the thoughts, emotions, and intentions of
others. As suggested by Hezel and McNally (2014), in contrast to
individuals with autism spectrum disorder who fail to use ToM
when reasoning about the scenes in the MASC, individuals with SAD
are “over-mentalizing”, and incorrectly attributing mental states
to others when not appropriate to the context. This is certainly
a ToM reasoning error, and one that would, in real-life contexts,
potentially predict negative interpersonal outcomes (e.g., misun-
derstandings, conflicts, tensions, etc.), although perhaps different
outcomes than those suffered by individuals with autism.
However, to over-mentalize, this suggests that individuals with
SAD care about, and potentially have a motivation to, read into
the minds of others. As such, it fails to account for the differential patterns of performance of the comorbid and non-comorbid
SAD groups across the ToM decoding and ToM reasoning tasks.
ToM decoding and reasoning are related, but also dissociable skills
(Sabbagh, 2004), and, indeed, accuracy on the Eyes and MASC
tasks was only modestly correlated in the current sample. There
is also evidence that they are subserved by distinct neural mechanisms, and specifically that ToM reasoning involves higher-order
prefrontal cortical areas and operates over a longer time course
of neural activation relative to ToM decoding (e.g., Liu, Sabbagh,
Gehring, & Wellman, 2009; Sabbagh, Moulson, & Harkness, 2004).
Therefore, it is possible that higher-level cognitive biases, attributions, and other schematic processing that are applied to the
more cognitively complex task of reasoning about others’ mental states operate similarly in SAD whether or not comorbid with
MDD. Regardless of the exact mechanisms underlying the results
reported here, they highlight the point made recently by Schaafsma,
Pfaff, Spunt, and Adolphs (2015) that ToM is not a monolithic process, and instead is made up of multiple components operating at
different levels of cognition. Further, they highlight the need for
more research comparing comorbid and non-comorbid anxiety and
depressive disorders across strong tasks of both ToM decoding and
reasoning.
Contrary to hypotheses, we did not find evidence for significantly lower ToM decoding or reasoning accuracy in those with a
non-comorbid lifetime MDD relative to healthy controls. As noted
above, the current results may suggest that over-sensitive reasoning
about the mental states of others in those with a lifetime diagnosis
of MDD may be specific to those with a comorbid anxiety disorder
characterized specifically by marked social fears and avoidance.
However, neither the comorbid or non-comorbid lifetime MDD
groups differed significantly from healthy controls in their mental state decoding. Previous studies have most consistently found
deficits in ToM decoding among individuals in a current episode
of MDD relative to controls. In contrast, while some studies have
found lingering ToM deficits in severely depressed outpatients very
recently remitted from their index episode (e.g., Inoue et al., 2004,
2006), other studies including undergraduate samples with a lifetime history of MDD similar to that assessed here have found that
those with a history of MDD performed significantly more accurately on the Eyes task than never-depressed controls. Similarly,
studies with undergraduate samples have found that those with
current subthreshold symptoms, such as many in the current sample, also display an enhanced pattern of ToM decoding accuracy
relative to controls (e.g., Harkness et al., 2005). In the current sam-
76
D. Washburn et al. / Journal of Anxiety Disorders 37 (2016) 71–77
ple, we did not have sufficient power to further stratify our Lifetime
MDD group into those in a current MDD episode and those with past
MDD. A direct comparison of these groups, taking into consideration the role of comorbid SAD, remains an important question for
future research.
A further interesting and important area for future research
regards the relation of dimensions of symptoms or affect to theory of mind skill. In the current study, continuous measures of
depression and social anxiety symptoms failed to show significant
associations to Eyes task and MASC task accuracy. On the one hand,
this may suggest that a categorical syndrome approach is the best
way to capture individual differences in theory of mind skill. On
the other hand, this may suggest that a dimensional relation would
be better captured by (a) using instruments that more clearly separate depressed versus anxious affect and/or symptoms; and (b)
acknowledging that the relation of symptoms to theory of mind
skill may be non-linear (e.g., Harkness et al., 2005).
Our results should be interpreted in the context of the following limitations. The size of the non-comorbid SAD group was small.
Perhaps not surprisingly, this group was very difficult to find and
recruit into the study. Therefore, replication with a larger sample
is required. Given the small size of the sample, we were unable to
examine other potential moderators of our effects. For example,
although not statistically significant, the non-comorbid SAD group
had the highest proportion of men and individuals of non-White
ethnicity (see Table 1), two variables which affect ToM performance as well as face perception (e.g., Krach et al., 2009; Rehnman
& Herlitz, 2006). While the hypothesized effects remained significant over and above the influence of sex and ethnicity, this does
not rule out moderating effects. There was insufficient statistical
power to examine sex and ethnicity as moderators of the relation of ToM ability and diagnostic status and, thus, this remains
an important question for future investigation. Further, the sample consisted of undergraduate volunteers, and, thus the results
reported here may not generalize to patient or general community samples. Nevertheless, all participants met DSM-IV criteria
for psychiatric diagnosis according to a structured clinical interview. Finally, this study measured social anxiety symptoms using
the SAASA. While this measure has strong psychometric properties and includes content of direct relevance to the college student
experience (e.g., “performing, for the first time, a new task or role in
front of classmates”), it has been validated using a younger sample
than the current study’s sample. Therefore, it is important to replicate the current findings using a social anxiety measure normed for
college-aged participants.
The current results and those of previous studies documenting significant alterations in ToM performance in individuals with
SAD relative to those with MDD and healthy controls highlight the
need for future research characterizing the limits of these effects
both in terms of comorbid psychopathology and ToM modality.
ToM deficits are associated with real-world impairments in social
functioning (e.g., Couture, Penn, & Roberts, 2006), which can have
significant negative effects on the prognosis of psychopathology
and quality of life (Trompenaars, Masthoff, Van Heck, De Vries, &
Hodiamont, 2007). Therefore, our results also suggest the need for
treatment strategies for SAD that consider individual differences in
social cognition. Fostering an optimal level of social sensitivity may
lead to improvements in functioning that ultimately alleviate the
interpersonal impairments that strongly characterize this chronic
disorder.
Acknowledgements
This study was funded by a New Opportunities Grant from the
Canada Foundation for Innovation (CFI) awarded to KH. We wish to
thank Sarah Saperia, Arielle Zahavi, and Stephanie Yu for their help
with data coding and management.
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