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Graduate Student Journal of Psychology
2023, Vol. 20

Copyright 2023 by the Department of Counseling and Clinical Psychology
Teachers College, Columbia University

The Effects of Face Masks on Emotion Interpretation in 
Socially Anxious Individuals

Lexie M. Mathis
Towson University, Department of Psychology 

 The COVID-19 pandemic (henceforth referred 
to as the pandemic), prompted widespread use of face 
masks in public settings. With this necessary protec-
tive measure, there were unintended social and mental 
health consequences. Masks impair emotion recogni-
tion (Carbon, 2020; Gori et al., 2021; Grundmann et 
al., 2021), and negatively impact perceptions of oth-
ers, including perceived closeness (Grundmann et al., 
2021), empathy (Wong et al., 2013), and friendliness 
(Wiesmann et al., 2021). Importantly, social anxiety 
(SA) affects the interpretation of emotions, including 
hypervigilance for threat faces (Klumpp & Amir, 2009; 
Mogg et al., 2004) and biases in emotion interpreta-
tion (Button et al., 2013; Gutiérrez-García & Calvo, 
2017; Schofield et al., 2007; Yoon & Zinbarg, 2008). 
Considering these impacts, socially anxious individu-
als (SA individuals) may demonstrate unique patterns 
of emotion inference when viewing masked faces.
Social Anxiety and Emotion Interpretation
 More specifically, regarding emotion interpre-
tation biases, Gutiérrez-García and Calvo (2017) 
studied interpretations of ambiguous emotional fac-
es and found that when compared to non-anxious 
controls, SA individuals were more likely to correct-
ly detect low intensity displays of disgust and anger, 
more likely to incorrectly identify neutral faces as an-
gry, and less likely to interpret neutral faces as happy 
or sad. These findings may reflect a greater ability or 
motivation of SA individuals to identify social threat 

emotions, possibly due to their hypervigilance for 
threat faces. Further, using an incidental learning task, 
Yoon and Zinbarg (2008) found that SA individuals 
demonstrate a default bias toward interpreting neu-
tral faces as threatening. This bias may impact the 
mental health of SA individuals, as they also attri-
bute excessive social cost to interacting with others 
displaying negative emotions of various intensities 
(i.e., they report that it would be excessively bad for 
them to interact with individuals displaying nega-
tive emotions, as compared to control participants’ 
reports; Button et al., 2013; Schofield et al., 2007). 
Impacts of Face Masks
 Moreover, researchers have found evidence that 
emotion identification accuracy is impaired when 
masks are worn. Several experimental studies have ex-
amined this topic by having participants view photos 
of individuals and identify the facial expressions dis-
played, with and without the presence of masks in the 
photos (Carbon, 2020; Gori et al., 2021; Grundmann 
et al., 2021). All three of these recent studies found 
evidence that masks presented a challenge to emotion 
identification, as accuracy was lower for masked faces. 
This effect exists regardless of participant age, as it has 
been shown in children as young as age three (Gori et al., 
2021) and in young, middle-aged, and older adults (Car-
bon, 2020; Gori et al., 2021; Grundmann et al., 2021). 
 Aside from impacting emotion identification, 
masks also have effects on social judgments and percep

Previous research has found emotion interpretation biases in individuals with social anxiety (SA) when emo-
tions are ambiguous. Additionally, research has shown that face masks impair emotion recognition. The pres-
ent within-subjects, quasi-experimental study examined the impact of face masks on emotion identification in 
individuals with SA. After pre-screening using a brief SA scale (the SIAS-6, a shortened version of the Social In-
teraction Anxiety Scale), 92 undergraduate students with qualifying SA scores completed an emotion identifica-
tion task. The task included images of masked and unmasked individuals expressing four emotions. Results indi-
cated impaired accuracy for all types of masked trials. When examining incorrect choice selections, it was found 
that neutral masked faces were misinterpreted as sad or fearful significantly more than their unmasked counter-
parts, suggesting a mask-specific interpretation bias. In relation to previous research on SA and hypervigilance 
for threat faces, when considering all masked trials, accuracy was highest for masked angry trials. While this study 
was limited in that it did not include a non-anxious group, the results have interesting implications. Important-
ly, the present findings suggest that some previously identified SA-related emotion interpretation characteris-
tics persist when viewing masked faces (e.g., hypervigilance for threats), while others do not (e.g., default bias 
for interpreting neutral as hostile). Future research should focus on elucidating the causes of the present results, 
which are important to this population and clinicians, as socially anxious individuals attribute greater social cost 
to negative emotions; thus, misinterpretation of emotions as negative may be detrimental to their mental health. 
 Keywords: social anxiety, face masks, emotion recognition, face perception, emotions



89

tions of others. In their experiment examining masks 
and emotion identification, Grundmann et al. (2021) 
also examined participants’ social judgments of the 
image models. They found that participants’ ratings 
of perceived closeness to the individual pictured were 
lower when the individual was wearing a mask. Further, 
Wiesmann et al. (2021) investigated an intervention to 
mitigate the negative effects of masks on the doctor-pa-
tient relationship. Their intervention, which consisted 
of smiling portrait photos placed on the chests of hos-
pital staff members, was associated with significantly 
higher ratings of staff friendliness compared to when 
the staff wore masks alone. This suggests that patients 
perceive staff members as less friendly when masks are 
worn. Similar effects were found prior to the pandem-
ic; in a randomized-controlled trial, Wong et al. (2013) 
examined the effect of medical face masks worn by 
physicians on the doctor-patient relationship. They 
found that patients perceived their doctors as signifi-
cantly less empathetic when the doctors were masked 
versus not. Taken together, the results of these three 
studies indicate that masks negatively impact percep-
tions of others, including perceived closeness (Grund-
mann et al., 2021), empathy (Wong et al., 2013), and 
friendliness (Wiesmann et al., 2021). Considering 
the effects of SA on emotion interpretation, these 
impacts on perceptions of others may be exacerbat-
ed by the interpretation biases already present in SA.
Implications for the Present Study
 While it is known that masks impair emotion rec-
ognition (Carbon, 2020; Gori et al., 2021; Grundmann 
et al., 2021) and induce more negative perceptions of 
others (Grundmann et al., 2021; Wiesmann et al., 2021; 
Wong et al., 2013), researchers have not yet identified 
specific populations which may be affected to a higher 
degree. As such, SA individuals may be at a higher risk 
of misinterpreting facial expressions when masks must 
be worn. Specifically, SA individuals interpret ambig-
uous faces as hostile (Gutiérrez-García & Calvo, 2017; 
Yoon & Zinbarg, 2008) - this may also be true when 
masks are worn, as they make expressions more uncer-
tain. Those with SA attribute excessive social cost to 
interacting with individuals displaying negative emo-
tions (Button et al., 2013; Schofield et al., 2007), and 
thus, misinterpretation of emotions may be detrimen-
tal to their mental health. This would be important 
for mental health professionals to be aware of when 
treating individuals with SA during the pandemic. 

 Based on evidence from prior research, the pur-
pose of the present study was to examine emotion 
interpretation in individuals with SA when viewing 
masked and unmasked faces. A 2 (masking) X 4 (ex-
pression) within-subjects, quasi-experimental design 
was used to assess the following hypotheses: 

H1: SA individuals will demonstrate lower accu-
racy for masked faces, with the lowest accuracy for 
neutral masked faces. 
H2: Neutral faces will be most commonly con-
fused with anger, with this being more likely to 
occur when faces are masked. 
H3: SA scores will be negatively correlated with 
overall accuracy, and with accuracy for masked tri-
als, while being positively correlated with the per-
centage of neutral faces confused as angry.

Method
Participants
 Participants were 92 undergraduate psychology 
students at a large mid-Atlantic university with quali-
fying self-reported SA scores. All received course credit 
for participating. SA is especially prevalent in young 
adults and has increased during the pandemic (Hawes 
et al., 2021), making this a relevant population. Five 
participants were excluded, three for being outliers 
and two for other reasons (incomplete data and pri-
or knowledge of the study), leaving 87 participants 
in analyses. A priori power analysis was used initial-
ly to inform the number of participants needed for a 
2 x 4 within-subjects ANOVA, and post hoc power 
analysis indicated an achieved power of 88.08% with 
87 participants for an effect size of η2p = 0.05 (More-
Power version 6.0.4; Campbell & Thompson, 2012).
 A brief SA scale (SIAS-6; Peters et al., 2012) was 
used to pre-screen participants for social anxiety. Inclu-
sion criteria consisted of a SIAS-6 score of at least 7 and 
a minimum age of 18 years old. The sample was diverse 
in race (42.5% White, 29.9% Black, 10.3% Hispanic/
Latinx, 8.0% multiracial, 6.9% Asian, 2.3% other) and 
similar in age (M = 19.49, SD = 1.79). The majority of 
the sample identified as female (72.4%). This reflects 
the higher prevalence of SAD in females compared to 
males in the United States (National Institute of Men-
tal Health, 2017), although other factors, such as ma-
jor, likely contributed to this gender ratio as well. 4.5% 
identified as nonbinary or another gender identity.

EFFECTS OF FACE MASKS IN SOCIALLY ANXIOUS INDIVIDUALS



9090

Measures & Materials
Social Interaction Anxiety Scale
 Mattick and Clarke’s (1998) Social Interaction 
Anxiety Scale (SIAS) is a 19-item self-report measure 
of an individual’s social interaction fear. A 6-item ver-
sion (SIAS-6) was developed by Peters et al. (2012). 
The items are statements intended to measure anxi-
ety levels when initiating and maintaining social in-
teractions; for example, “I have difficulty making eye 
contact with others.” Participants rate the degree to 
which each statement is characteristic of themselves 
on a 5-point Likert scale ranging from 0 (not at all) to 
4 (extremely). The SIAS includes two reverse scored 
items. Total scores are calculated, with optimum cut-
off scores being 39.5 for identifying SAD using the 
SIAS (Carleton et al., 2009) and 7 when using the 
SIAS-6 (Peters et al., 2012). The SIAS is both reliable 
and valid (Mattick & Clarke, 1998), and the SIAS-6 
is comparable to the original scale (Peters et al., 2012).
Emotion Identification Task
 For the emotion identification task, all partic-
ipants viewed the same set of 96 images, which sys-
tematically differed in expressed emotion (happy, 
angry, fearful, neutral), mask-wearing (mask, no 
mask), and sex (male, female). Stimuli appeared in-
dividually in a Qualtrics survey (Qualtrics, Provo, 
UT), with the masked image block first (Gori et al., 
2021) to avoid participant demand characteristics. 
Stimuli order was randomized within blocks. Because 
race can impact emotion identification (Kang & Lau, 
2013; Tuminello & Davidson, 2011) through ste-
reotyping and social categorization, only Caucasian 
faces were shown, as in previous work (e.g., Schofield 
et al., 2017). To mitigate these potential confound-
ing effects, race was kept consistent throughout.
 The images were randomly selected from the 
Chicago Face Database (CFD; version 3.0; Ma et al., 
2015), with each model appearing only once to avoid 
habituation. The CFD provides two types of happy 
images, however, only open-mouth happy images 
were used. CFD images are standardized in many ways, 
including characteristics of the models, environment, 
and photography (Ma et al., 2015). Models had mul-
tiple photos taken for each expression and indepen-
dent raters identified the best photo of each. Neutral 
images were highly reliable based on norming data col-
lected from a large and racially diverse sample; howev-
er, such data was not obtained for emotional images. 

 For the present study, Adobe Photoshop was 
used to digitally edit a randomly selected subset of 
images, adding a mask (906 x 644 pixels) that was tai-
lored to the face of each individual, and adding faint 
shadows for realism. Masks were centered horizon-
tally and placed vertically to cover the nasolabial-alar 
crease. An example of a CFD image before and after 
editing can be seen in Figure 1, and the CFD codes 
for all images used are available online at the link pro-
vided in the data availability statement. In the task, 
six multiple-choice options (happy, content, neutral, 
angry, fearful, and sad) were provided in a consistent 
order. Content and sad served as positive and neg-
ative distractor options to avoid ceiling effects and 
were intended to be somewhat distinguishable from 
the emotions shown. Two measures were obtained: 
accuracy and neutral trial incorrect choice selections 
(the percentage of responses for each incorrect option 
when the correct answer was neutral; this was used to 
determine if any interpretation biases were present).
Demographic Information
 Within the Qualtrics survey were several demo-
graphic questions regarding age, gender, and race. 
All were open-ended questions, allowing partici-
pants to respond freely. Responses to the gender 
and race questions were later categorized. Categories 
were created based on the most common responses 
given. Gender categories were female, male, non-bi-
nary, and other, while race categories were White, 
Black, Hispanic/Latinx, multiracial, Asian, and other.
Procedure
 After receiving IRB approval, SIAS-6 pre-screen-
ing occurred online. The researcher was blind to 
pre-screening scores during data collection. Each 
participant came to a university laboratory, provid-
ed written informed consent, and completed the 
Qualtrics survey on a university desktop comput-
er. This included several open-ended demograph-
ic questions, the emotion identification task, and 
the SIAS. The researcher debriefed them, answered 
any questions, and provided mental health resourc-
es. Pre-screening and study data were combined, 
downloaded to Microsoft Excel, and analyzed us-
ing IBM SPSS Statistics 27. University COVID-19 
precautions were complied with in the laboratory.

Results
 In the present study, masking and expression of 

MATHIS 



91

EFFECTS OF FACE MASKS IN SOCIALLY ANXIOUS INDIVIDUALS

the image models were manipulated, and subsequent-
ly, SIAS total scores, emotion identification accuracy, 
and neutral trial incorrect choice selections were mea-
sured. Accuracy outcomes were checked for skewness 
and outliers before analysis. Three outliers were iden-
tified, having unusually low scores attributed to lack of 
attention. Unusually high scores were considered true 
data. While participants answered correctly in about 
three-quarters of all trials, accuracy for masked (M = 
64.39%, SD = 8.30%) and unmasked (M = 86.71%, SD 
= 6.00%) trials notably differed. As for SA scores, the av-
erage SIAS score (M = 38.94, SD = 12.83) approached 
the cut-off score of 39.5, while the average SIAS-6 score 
(M = 11.31, SD = 3.95) exceeded the cut-off score of 7.
 Prior to conducting the planned repeated mea-
sures ANOVAs, test assumptions were checked. Ap-
proximate normality was violated, as the dependent 
variables for each test were extremely skewed in some 
conditions. Transformations were attempted; howev-
er, some conditions became overcorrected. Thus, the 
aligned rank transform procedure (Salter & Fawcett, 
1993), a nonparametric option which aligns and ranks 
data for each effect before conducting factorial ANO-
VAs, was utilized through the program ARTool (Elkin 
et al., 2021; Wobbrock et al., 2011). For each main 
effect and interaction effect, a separate ANOVA was 
conducted using the data aligned and ranked for that 
effect; only the effect for which the data was aligned 
was considered from each (Wobbrock et al., 2011). For 
instance, to examine the main effect of masking, the 
data was aligned and ranked for said effect using AR-
Tool. Then, the appropriate ANOVA was conducted 
using this data, however, only the main effect of mask-
ing could be considered from these results. This pro-
cess was repeated for each main effect and interaction. 
Mauchly’s test was used to check the assumption of 
sphericity and Greenhouse-Geisser corrected values 
were reported if violated. For each simple effects anal-
ysis, an additional ANOVA was conducted using the 
data aligned and ranked for contrasts (Elkin et al., 2021).
Accuracy
 To test H1, a 2 (masking: mask, no mask) x 4 (ex-
pression: happy, neutral, angry, fearful) repeated mea-
sures ANOVA was performed on accuracy (Figure 2). 
Significant main effects of masking, F(1, 86) = 644.70, 
p < .001, η2p = .88, and expression, F(2.52, 216.57) = 
35.59, p < .001, η2p = .29, ε = .84, were found. These 
effects were qualified by a significant interaction, F(3, 

258) = 90.56, p < .001, η2p = .51. A simple effects anal-
ysis revealed that masks significantly impaired accuracy 
for happy, F(1, 86) = 741.70, p < .001, angry, F(1, 86) 
= 138.74, p < .001, and fearful trials, F(1, 86) = 495.51, 
p < .001, but not neutral trials. Frequent confusion 
with one distractor option may have caused the lack of 
an effect on accuracy for neutral trials. Here, the first 
part of H1, which stated that accuracy would be lower 
for masked faces, was supported, however, the second 
part of H1, which predicted that accuracy would be 
lowest for neutral masked trials, was not supported. 
Interestingly, when comparing accuracy among all 
masked trials, accuracy was highest for masked angry 
trials (M = 79.50, SD = 13.13), suggesting that hy-
pervigilance was present for ambiguous threat faces.
Neutral Trial Incorrect Choice Selections
 To test H2, a 2 (masking: mask, no mask) X 5 (ex-
pression choice: happy, content, angry, fearful, sad) re-
peated measures ANOVA was performed on the per-
centages of incorrect responses for each option (Figure 
3). Notably, seven participants were accurate for all 
neutral masked trials, unmasked trials, or both, mean-
ing that n = 80, as participants with missing data were 
excluded here. Significant main effects of masking, F(1, 
79) = 69.75, p < .001, η2p = .47, and expression choice, 
F(2.43, 192.24) = 145.94, p < .001, η2p = .65, ε = .61 
were found. These effects were qualified by a significant 
interaction effect, F(1.91, 151.07) = 27.06, p < .001, 
η2p = .26, ε = .48. A simple effects analysis revealed a 
significant effect of masking on selecting content, F(1, 
79) = 15.96, p < .001, fearful, F(1, 79) = 17.42, p < .001, 
or sad, F(1, 79) = 18.86, p < .001, rather than neutral. 
Specifically, when incorrect, participants tended to 
choose content instead of neutral for unmasked trials, 
while they tended to choose fearful and/or sad instead 
of neutral for masked trials. There was no effect of 
masking on selecting happy or angry rather than neu-
tral. Contrary to H2, there was a nonsignificant trend 
toward selecting angry for neutral unmasked faces.
Relationships Among Variables
 Lastly, to test H3, Spearman’s correlations among 
SA scores, accuracy outcomes, and neutral trial in-
correct choice selections were calculated. “SA scores” 
refers to both SIAS and SIAS-6 scores. “Accuracy 
outcomes” refers to accuracy for each masking con-
dition. No correlations were significant among SA 
scores and accuracy outcomes or among SA scores 
and neutral trial incorrect choice selections. As such, 



92

H3 was not supported. SIAS and SIAS-6 scores had 
a moderate positive correlation, r = .47, p < .001.

Discussion
 This study aimed to determine whether SA in-
dividuals demonstrate emotion interpretation biases 
when viewing masked faces, as previous research had 
not examined the effects of masks in populations that 
may be differentially affected by the associated emotion 
recognition challenges. The present study’s SA partic-
ipants demonstrated impaired accuracy for identifying 
the emotions of masked individuals, while having high 
accuracy for masked angry trials and misinterpreting 
neutral faces as sad and/or fearful significantly more 
when masked than not. Response tendencies were iden-
tified by examining confusions of neutral faces, but it is 
unknown if tendencies when viewing masked faces are 
specific to SA or if they are more generally applicable.
Accuracy
 Consistent with previous research regarding the 
impact of masks on emotion recognition (Carbon, 
2020; Gori et al., 2021; Grundmann et al., 2021), accu-
racy was impaired for masked trials. Accuracy was not 
significantly different for neutral trials based on mask-
ing, however, accuracy for neutral unmasked trials was 
lower than accuracy for other unmasked trials. This 
may have been due to one of the distractor emotions 
used, namely “content,” being similar to “neutral.” As 
seen in Figure 3, more than half of incorrect responses 
for neutral unmasked trials were content (M = 54.78%). 
 In addition, among all types of masked trials, the 
present study’s SA participants displayed the highest 
accuracy for masked angry trials. This is consistent 
with previous research which found that SA partic-
ipants correctly identified low intensity displays of 
disgust and anger more often than non-anxious con-
trols (Gutiérrez-García & Calvo, 2017), as participants 
in both studies identified ambiguous expressions of 
anger correctly. If this is specific to SA individuals, 
it may imply greater motivation or ability to iden-
tify ambiguous expressions of anger. Further, this 
relates to prior findings of hypervigilance for threat 
faces by SA individuals (Klumpp & Amir, 2009; 
Mogg et al., 2004), as anger is a social threat emotion.
Incorrect Response Tendencies for Neutral 
Trials
 As aforementioned, neutral faces were confused 
as fearful and/or sad more frequently when faces were 

masked than not. These response tendencies are par-
ticularly interesting and may reflect participants’ per-
sonal feelings during the pandemic. Notably, the mean 
percentage of neutral masked faces confused as sad (M 
= 57.32%) was larger than the percentage confused as 
fearful (M = 5.62%). Perhaps the tendency to misinter-
pret neutral masked faces as sad could be explained by 
the projection of depressive symptoms. There is rea-
son to speculate such, as depression increased in prev-
alence since the pandemic began. Early in the pandem-
ic, the prevalence of moderate to severe depression in 
U.S. college students was approximately 36.2% (Lee et 
al., 2021), while prior to the pandemic, 25.67% of U.S. 
college students had scores indicative of possible major 
depression (Acharya et al., 2018). Moreover, depres-
sion is the most common comorbid condition for indi-
viduals suffering from SAD, with 35-70% having this 
comorbidity based on several clinical studies (Koyun-
cu et al., 2019). Given these statistics, the prevalence of 
depression in this sample was potentially high. If so, the 
sad response tendency may reflect participants project-
ing their own negative emotions onto the neutral faces 
viewed, particularly when ambiguous due to masking. 
 Importantly, projection of one’s own affective 
state when interpreting the emotions of others is sup-
ported by research. For example, Trilla et al. (2021) 
observed the phenomenon of emotional egocentricity 
when participants’ affective states were manipulated 
before an emotion perception task. Participants were 
more likely to judge faces as sad when they were experi-
encing sadness as opposed to happiness, indicating that 
projection affects the perception of facial expressions. 
Furthermore, in a study comparing the responses of 
depressed, remitted, and healthy control individuals, 
Leppänen et al. (2004) found an impairment in the 
recognition of neutral faces. Specifically, depressed and 
remitted patients tended to mistake neutral faces for 
emotional faces (e.g., sad or happy), although false hap-
py responses occurred more in the group of remitted 
patients. Given this strong evidence for perception of 
neutral faces as sad in those with depressive symptoms, 
along with the phenomenon of emotional egocentric-
ity shown by Trilla et al. (2021) and the prevalence 
rates of depression mentioned previously, projection 
of depressive emotions may have impacted interpre-
tations of neutral masked faces in the present study. 
 In contrast, several prior studies have shown a bias 
for interpreting neutral faces as threatening in SA in

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EFFECTS OF FACE MASKS IN SOCIALLY ANXIOUS INDIVIDUALS

dividuals (Gutiérrez-García & Calvo, 2017; Yoon & 
Zinbarg, 2008), which was not replicated here. The 
present results illustrate that SA participants most fre-
quently confused neutral faces as sad when masked, 
while Gutiérrez-García and Calvo (2017) found that 
SA individuals were less likely than non-anxious 
controls to interpret neutral faces as sad. This incon-
sistency suggests a mask-specific effect, however, it 
is unknown whether this is generalized or SA-based. 
Although the neutral threat bias, such as that shown 
by Yoon and Zinbarg (2008), was not present for 
neutral unmasked trials either, the presence of prior 
masked trials may have impacted this, and thus, the 
previous findings are not refuted. Further, the meth-
odology may not have allowed for enough SA vari-
ation to produce similar results. The present study 
recruited participants with a minimum score, where-
as previous studies selected extreme scores from a 
participant pool (Gutiérrez-García & Calvo, 2017), 
used median split grouping (Klumpp & Amir, 2009), 
or clinician diagnosis grouping (Mogg et al., 2004).
Limitations
 The present study had several important limita-
tions. First, it did not include a low- or non-anxious 
group due to the limited scope of this study, being that 
it served as a first-year project leading up to a master’s 
thesis. Inclusion of a control group would aid in elu-
cidating whether the identified mask-related response 
tendencies are specific to SA. Second, the researcher 
lacked access to a clinical sample, relying on a brief 
SA scale for pre-screening, which was not as high-
ly correlated with the full scale as expected (Peters et 
al., 2012), suggesting measurement problems. Third, 
ecological validity should be considered, as static im-
ages are unlike real life, where movement and contex-
tual information facilitate emotion interpretation. 
Implications and Future Research
 Despite the limitations, the present findings con-
tribute information to the research gap on popula-
tions that may be uniquely affected by the challenges 
associated with mask-wearing. As predicted, emotion 
identification accuracy was impaired for masked trials, 
however, neutral masked trials were misinterpreted 
differently than expected (as sad rather than angry). 
These findings can inform clinicians about how those 
with SA interpret the emotions of masked individu-
als, contributing to an improved understanding of 
pandemic-related effects when providing treatment. 

The mental health effects of the incorrect response 
tendencies identified here should be considered, as 
individuals with SA attribute excessive social cost to 
negative emotions, including fear and sadness (But-
ton et al., 2013). Importantly, neutral masked faces 
were most often confused as sad, with this occurring 
significantly more than when unmasked. If SA indi-
viduals often misinterpret neutral masked faces as 
sad, this may cause greater anxiety for these individu-
als when in social situations due to their attribution 
of excessive social cost to interacting with individuals 
displaying sadness. Furthermore, these findings may 
bring increased awareness to possible differential ef-
fects of masks on other neurodivergent populations. 
Future research could examine the effects of masks on 
emotion interpretation in other populations typically 
affected by interpretation biases to determine whether 
the known effects are altered by the presence of masks.
 In addition, the higher accuracy shown for 
masked angry trials may reflect greater motivation or 
ability of SA individuals to identify these social threat 
emotions, which can be explained by their hypervigi-
lance for threat faces (Klumpp & Amir, 2009; Mogg et 
al., 2004). These results reinforce prior findings of hy-
pervigilance for ambiguous threat faces, demonstrat-
ing that this effect is also applicable to situations when 
SA individuals view masked angry faces. However, the 
previously identified neutral threat bias, which is char-
acteristic of SA, was not reproduced here, suggesting 
that this effect may not be present when viewing faces 
during the pandemic. Instead, a different emotion in-
terpretation bias in which neutral masked faces were 
most often misinterpreted as sad, may have taken pre-
cedence. This bias may result from the projection of 
depressive emotions, as depression is the most com-
mon comorbidity of SA and its prevalence increased 
during the pandemic. Future research should examine 
the role of both SA and depression in interpreting 
the emotions of masked faces and should prioritize 
the inclusion of a low- or non-anxious control group.

Acknowledgements
 The author wishes to thank Dr. Kim Shifren 
for her continued mentorship and valuable in-
sight, Dr. Justin Buckingham for consultation on 
study design, Dr. Jeff Kukucka for statistical sug-
gestions, and Ryan Rosenthal for his critical re-
viewal of the manuscript and support throughout. 



94

Declaration of Interest Statement
The author reports no conflict of interest. 

Data Availability Statement
The data that support the present findings are openly 
available in Open Science Framework at http://doi.
org/10.17605/OSF.IO/VM4DC.

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Figure 1

Emotion Identification Task Image Examples

Note. Although the same individual is shown here, this is for illustrative purposes only, as no individuals were 

included more than once in the task. For this individual, the expression shown is neutral and the mask-edited 

image was used in the task. CFD stimulus code: CFD-WF-211-001-N. (Left) original CFD image. (Right) 

mask-edited CFD image.

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Figure 2

Emotion Identification Accuracy Among Masking and Expression Conditions

Note. n = 87.

***p < .001.



98

MATHIS 

Figure 3

Neutral Trial Incorrect Choice Selections

Note. n = 80.

***p < .001.


