Social anxiety and the interpretation of morphed facial expressions following exclusion and inclusion

Journal Pre-proof Social anxiety and the interpretation of morphed facial expressions following exclusion and inclusion Roy Azoulay, Uri Berger, Hadar Keshet, Paula M. Niedenthal, Eva GilboaSchechtman PII:

S0005-7916(18)30247-7

DOI:

https://doi.org/10.1016/j.jbtep.2019.101511

Reference:

BTEP 101511

To appear in:

Journal of Behavior Therapy and Experimental Psychiatry

Received Date: 7 October 2018 Revised Date:

27 June 2019

Accepted Date: 31 August 2019

Please cite this article as: Azoulay, R., Berger, U., Keshet, H., Niedenthal, P.M., Gilboa-Schechtman, E., Social anxiety and the interpretation of morphed facial expressions following exclusion and inclusion, Journal of Behavior Therapy and Experimental Psychiatry (2019), doi: https://doi.org/10.1016/ j.jbtep.2019.101511. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Social Anxiety and the Interpretation of Morphed Facial Expressions Following Exclusion and Inclusion

Roy Azoulaya, Uri Bergerb, Hadar Kesheta, Paula M. Niedenthalc, and Eva Gilboa-Schechtmana

a

Department of Psychology and the Gonda Brain Science Center, Bar-Ilan University, Israel

b

Department of Psychiatry, Yale University, USA

c

Department of Psychology, University of Wisconsin-Madison, USA *Corresponding author: Roy Azoulay, [email protected]

Social Anxiety and the Interpretation of Morphed Facial Expressions Following Exclusion and Inclusion Abstract Background and Objectives: Negative interpretation biases are postulated to play etiological and maintaining roles in social anxiety (SA). However, empirical support for interpretation biases of facial expression in SA is inconsistent. Given the importance of signals of (dis)approval in SA, our objective was to examine whether SA is associated with enhanced sensitivity to such signals especially following exclusion. Methods: In Study 1, participants (N = 139) underwent an exclusion/inclusion manipulation and were then presented with video clips of smiles gradually changing into disgust expressions (smile-to-disgust). In Study 2 (N = 203), participants saw smile-to-disgust as well as disgust-to-smile clips following an exclusion/inclusion manipulation. Participants' task in both studies was to detect the offset of the initial expression. Results: Results of Study 1 show that detection latency of smiles’ disappearance is negatively associated with SA severity. The results of Study 2 suggest that this association is stronger following exclusion, and specific to the smile-to-disgust as opposed to the disgust-to-smile, transitions. Limitations: Our studies did not examine whether the observed interpretation bias was specific to SA. Conclusions: Our findings support and refine cognitive theories of SA, suggesting that interpretation biases for facial information in SA may be especially pronounced following exclusion. Keywords: Exclusion, Social anxiety, Cognitive biases, Approval, Smiles, Cyberball, Facial expressions.

Social Anxiety and the Interpretation of Facial Expressions Social Anxiety and the Interpretation of Morphed Facial Expressions Following Exclusion and Inclusion Social anxiety disorder (SAD) is a condition involving marked fear or anxiety about common social situations in which there is a potential for a negative evaluation by others (DSM-V, APA, 2013). Lifetime prevalence of SAD is estimated to be around 12%, and it is associated with severe psychological, interpersonal, and professional consequences (e.g., Ruscio et al., 2008). Cognitive models of SAD suggest that enhanced processing of negative social cues is at the core of this condition (Clark &Wells, 1995; Rapee & Heimberg, 1997). Negative interpretation biases are postulated to play etiological and maintaining roles in social anxiety (SA; Mobini, Reynolds, & Mackintosh, 2013). Such biases are evidenced by a tendency to interpret ambiguous social cues as signs of disapproval. A wealth of studies indicates that individuals high in SA, as compared to individuals low in SA, exhibit a propensity to perceive ambiguous social information in a negative manner (Clark & McManus, 2002; Hirsch & Clark, 2004). Indeed, high-SA individuals apprehend descriptions of ambiguous social scenarios as indicating disapproval (Amir, Foa, & Coles, 1998; Constans, Penn, Ihen, & Hope, 1999; Stopa & Clark, 2000; Voncken, Bögels, & de Vries, 2003). However, this robust and theory-consistent pattern of finding is limited mostly to studies examining verbal information (Heinrichs & Hofmann, 2001). Results are equivocal when non-verbal information such as emotional facial expressions, a crucial channel for conveying attitudes (Ekman & Oster, 1979), are used as stimuli (Staugaard, 2010). Several different laboratories investigated interpretation patterns of ambiguous facial expressions in SA using morphed faces – the visual combination of two distinct expressions – as stimuli

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Social Anxiety and the Interpretation of Facial Expressions (Niedenthal, Halberstadt, Margolis, & Innes-Kerr, 2000). In those studies, participants were exposed to combinations of two expressions and were asked to define the displayed expression. A summary of the findings of these studies is presented in Table 1. As can be seen from this Table, the pattern of findings is anything but consistent – out of the eighteen studies, eleven reported no negative interpretation biases among high-SA individuals, six described an enhanced negative response bias (general propensity to label any expression as negative) and only five studies reported an enhanced negative sensitivity (a tendency to label more ambiguous expressions as negative) among high-SA individuals. Inconsistent findings among these studies may be attributable to variations in experimental methods and stimuli. As can be seen in Table 1, about half of the studies investigated disgust expressions and all but one examined smiles and anger as target expressions. The vast majority of studies using morphs displayed static faces, with only four displaying dynamic video clips. Importantly, in all but one study participants were requested to verbally label the morphed facial expressions. In contrast, Bui and colleagues (2017) simply asked the participants to indicate when one expression changed into a different expression. Finally, only one study used activation of social threat before the interpretation task (Richards et al., 2002, Study 2). Given such methodological discrepancies and the potentially small signal-to-noise ratio of the examined effect (e.g., Maoz et al., 2016; Jusyte & Schönenberg, 2014), a potent manipulation, a sensitive task, and ecologically valid stimuli appear to be needed to identify interpretation differences of facial cues in SA. Interpretation of Emotional Facial Expressions Following Exclusion and Social Anxiety Exclusion has been found to enhance sensitivity to interpersonal cues. Following exclusion, participants were better at remembering and identifying emotional facial expressions (Gardner, Pickett, & Brewer, 2000; Pickett, Gardner, & Knowles, 2004). Moreover, excluded participants 2

Social Anxiety and the Interpretation of Facial Expressions were better at detecting the genuineness of smiles as compared to included participants (Bernstein, Young, Brown, Sacco, & Claypool, 2008 & 2010). Furthermore, among non-clinical populations, exclusion promoted attentional bias to smiling, as compared to angry and disgust faces (DeWall, Maner, & Rouby, 2009; Xu et al., 2015). Although exclusion promotes interest in positive social interaction among low-SA individuals, high-SA individuals were not found to exhibit a similar tendency to reconnect (Maner, DeWall, Baumeister, & Schaller, 2007; Mallott, Maner, DeWall, & Schmidt, 2009). Taken together, these findings suggest that whereas low-SA individuals tend to exhibit enhanced attunement to signs of approval following exclusion, highSA individuals may lack such a compensatory mechanism. The present studies

Two studies were conducted to examine interpretation of emotional facial expressions in SA. In both studies, following a social exclusion (or inclusion) manipulation, participants were shown video clips of smiles gradually changing into disgust expressions (smile-to-disgust morphs). In Study 2, participants were also shown video clips of disgust expressions gradually changing into smiles (disgust-to-smile morphs). Hence, those clips presented a continuous ambiguous facial expression displaying both the emergence and disappearance of two distinctive facial expressions. Using these dynamic stimuli, we sought to explore the perceived boundaries between the two expressions. Participants' task in both studies was to detect the offset of the initial expression by indicating when the first expression is transformed into a different (second) expression.

Facial expressions of disgust and smile were chosen to represent disapproval and acceptance, respectively. Facial expressions of disgust are known to be consistently associated with 3

Social Anxiety and the Interpretation of Facial Expressions disapproval (Widen & Russell, 2013; Seidel, Habel, Kirschner, Gur, & Derntl, 2010), whereas smiles are typically considered as expressions of friendliness and acceptance (Heurer et al., 2010). We used video clips because in real life facial emotions emerge dynamically (Ambadar, Schooler, & Cohn, 2005; Rubenstein, 2005). As documented in Table 1, the vast majority of studies examining the association between SA and interpretation of emotional facial expressions used verbal labeling task. Such tasks demand defining the emotion displayed at each morph. The demand for a specific verbal labeling may direct the participants (especially those high in SA) to search for an objectively accurate criterion. In our task we simply asked participants to indicate a transition point at which the initial expression is transformed into a different expression. Thus, participants were not asked to explicitly interpret the facial expression and label it but rather to interpret the transition point of the two predefined expressions. The use of a task that does not require explicit verbal labeling is likely to emphasize more intuitive and less deliberate criteria (Bui et al., 2017). Study 1 Two main a-priori hypotheses were examined. First, we hypothesized that SA-severity is associated with faster detection of the offset of smiles in a smile-to-disgust morph (the SAinterpretation hypothesis). Second, we expected that the positive association between SAseverity and detection latencies of smile offsets is stronger in the exclusion versus the inclusion condition (the reduced affiliative attunement following exclusion among SA hypothesis). Method Participants

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Social Anxiety and the Interpretation of Facial Expressions Participants were recruited via Amazon's Mechanical Turk (MTurk), an online labor market. MTurk was found to be useful for studying clinical and subclinical populations and to provide data of high quality (Shapiro, Chandler & Mueller,2013). Demographically, MTurk samples tend to be more diverse and representative of the U.S. population than other internet and undergraduate samples (Buhrmester et al., 2011; Casler et al., 2013). Participants (N = 239) received $2 for their participation. In order to enhance data quality, we excluded participants who filled the survey from the same I.P. address more than once (n = 62) as well as participants who appeared to fill all the questionnaires non-conscientiously (i.e., had zero standard deviation in all four questionnaires of our study, n = 27). This cleaning procedure was found to be effective in coping with data contamination in MTurk (Bai, 2018a; Bai, 2018b). Furthermore, a static clip served as an additional "litmus test" of non-conscientious responding. In this clip, a single, nonchanging expression was displayed while participants were asked to identify a change between expressions. Participants who detected a change in this clip were excluded (n = 10). Thus, the final sample consisted of 139 participants (73 women, mean age = 35.01, SD = 10.23). This sample size provides sufficient power for identifying an anticipated small-medium effect-size as found in previous studies (Maoz et al., 2016; Jusyte & Schönenberg 2014). Procedure Participants were invited to take part in a study investigating visual mentalization. They were told that they will play an online ball-tossing game named “Cyberball IV” (Williams, Cheung, & Choi, 2000) with two other players from the same online labor market. Before the game began, participants were asked to write the name they would like to be referred by in the game. During the game, when receiving the ball from one of the other two players, participants were required to indicate to whom they would like to pass the ball by clicking on the appropriate player's 5

Social Anxiety and the Interpretation of Facial Expressions "icon". In all conditions, the game lasted 30 ball tosses (approximately 5 min). In the exclusion condition, the participant received three tosses (10%) in the beginning of the game. The rest of the time the tosses were interchanged between the two other presumed players while the participant was being ignored. In the inclusion condition, the ball was passed equally frequently to all participants, resulting in the participant receiving 10 tosses (33%). Participants were randomly assigned to either the exclusion or the inclusion condition. Next, participants were informed that they will watch video clips in which smile expressions will be changing to disgust expressions. The participants' task was to stop the video at "the moment you feel that the facial expression changed". The six video clips were presented in a random order. Finally, participants filled the Basic Needs Threat Questionnaire regarding their experience during the Cyberball game (Zadro, Williams, & Richardson, 2004). Next, they completed questionnaires assessing SA severity. Lastly, they were debriefed about the real propose of the game and the fact that they played with virtual players (as in Wolf et al., 2015). Stimuli The six video clips were generated by a Morph software which enables the creation of a continuum clip in which a facial expression morphs into another facial expression. Every morph video lasted 20 seconds and included expressions from a standardized set of faces (NimStim Face Stimulus Set; Tottenham et al., 2009). There were three male and three female actors. In addition to those clips, a video clip in which the facial expression did not change was also presented. This clip served as a test for the conscientiousness of the task completion and was not included in the analyses. 6

Social Anxiety and the Interpretation of Facial Expressions

Self-report measures Participants completed the Basic Needs Threat questionnaire following the Cyberball manipulation (Zardo et al., 2004). The questionnaire includes items assessing the effect of the Cyberball on belongingness, sense of control, self-esteem and meaningful existence. Subsequently, participants completed two measures assessing the severity of SA. First, they filled out the Social Phobia Inventory (SPIN; Connor et al., 2000), which is comprised of 17 questions that are rated on a Likert scale ranging from 0 (not at all) to 4 (extremely). In the current study, the internal reliability of the SPIN was .94 (M = 10.41; SD = 16.62) Next, they completed the Liebowitz Social Anxiety Scale (LSAS; Liebowitz, 1987) which consists of 24 situations. Participants rate on two scales ranging from 0 to 3 to what extent they (a) find each situation anxiety-inducing and (b) seek to avoid such a situation. In our study, the internal reliability of the LSAS was .96 (M = 45.37; SD = 32.35). Results and Discussion To examine the effect of our manipulation, we conducted a General Linear Model (GLM) on our dependent variables. Condition, SA-severity and their interaction served as predictors. SAseverity was computed as the mean standard scores of the LSAS and SPIN questionnaires. We conducted the aforementioned GLM on the Basic Needs Threat questionnaire. The model explained 63.7% of the variance (F(3,135)= 79.03, p<.001). As expected, the analysis revealed a main effect of Condition (Beta = 0.75, t(135)= 13.32, p < .001) which reflects lower needs satisfaction under the exclusion, as compared to the inclusion condition. Those results indicate that the manipulation was effective. A main effect of SA was also found, such that SA was 7

Social Anxiety and the Interpretation of Facial Expressions correlated with lower needs scores (Beta = -0.22, t(135) = -3.85, p <.01). The SA-severity X Condition interaction was not significant (Beta = 0.07, t(135) = 1.35, p = .17). To test our primary hypotheses, we conducted the aforementioned GLM on mean decision latencies to identify emotional transitions. The model explained 3.4% of the variance (F(3,135)= 1.97, p=.12). No main effect of Condition was found (Beta =0.02, t(135) = 0.26, p =.79). Consistent with our SA negative interpretation hypothesis, SA was correlated with faster detection of the offset of smiles and the onset of disgust (Beta = -0.203, t(135) = -2.38, p = .018). However, inconsistent with our reduced affiliative attunement following exclusion among SA hypothesis, no SA X Condition interaction was identified (Beta = 0.04, t(135) = 0.53, p =.59). To graphically depict the results, we divided the participants into two groups based on their SA scores: Low SA group (LSAS < 30 & SPIN < 10) and high SA group (LSAS > 60 & SPIN > 30). These results are depicted in Figure 1. The results support the SA negative interpretation hypothesis such that SA-severity is associated with faster detection of the offset of smiles (and onset of disgust). It is possible that the moderating effect of the exclusion manipulation were obscured by participants' consistent encounters with acceptance to disapproval transformations. These sequences may have evoked exclusion feelings in all individuals regardless of condition and individual differences. In addition, it is possible that SA is associated with faster identification of any facial change. Finally, we sought to enhance our sample size as it did not reach the sufficient statistical power needed for the detection of mixed interaction effects (Leon & Heo, 2009). Hence, in the next study, we presented two types of emotional transition: from smile to disgust and from disgust to smile. We reasoned that using a task including negative (smile-to-disgust) as

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Social Anxiety and the Interpretation of Facial Expressions well as positive (disgust-to-smile) transformations would help examine the specificity interpretation tendencies in SA, as well as present a more balanced and diverse sequence of facial changes. Study 2 The design of Study 2 was identical to Study 1 with a single exception – we presented participants with clips of facial expressions changing from disgust-to-smile as well as from smile-to-disgust. Thus, a new variable of Direction (positive: disgust-to-smile vs. negative: smile-to-disgust) was added to the analysis. We expected that SA-severity is associated with enhanced preference to detect the offset of smile as compared to the offset of disgust expressions (the SA negative interpretation hypothesis). Finally, we expected SA-severity to be associated with a propensity to detect the offset of smiles faster than the offset of disgust following exclusion, as compared to inclusion condition (the reduced affiliative attunement following exclusion in SA hypothesis). Method Participants Participants (N = 406) were recruited via MTurk and received $2 for their participation. Following the same data monitoring procedure as in Study 1, we first excluded participants who used the same I.P. address more than once (n = 103). Then we excluded participants with nonconscientious response patterns (did not respond appropriately to a test video included in the task, n = 27; filled all items in the questionnaires including the reversed items with zero standard deviation, (n = 72). The final sample consisted of 203 participants (112 women, Mean age = 35.08, SD = 11.85), a sufficient sample size for the predicted effects. In the current study, the 9

Social Anxiety and the Interpretation of Facial Expressions internal reliability of the SPIN questionnaire was.93 (M = 19.43; SD = 56.64) and the internal reliability of LSAS was .95 (M = 45.92; SD = 26.39). Procedure The procedure in this study was identical to that of Study 1, apart from the inclusion of six additional video clips of facial expressions changing from disgust-to-smile (to the existing six video clips changing from smile to disgust used in Study 1). The twelve video clips were based on the same six pairs of faces. As in Study 1, we included a "test" clip. The 13 clips were presented in a random order. Results and Discussion As in Study 1, we conducted a GLM on the Basic Needs Threat questionnaire using Condition, SA-severity and their interaction as predictors. This model explained 62.34% of the variance (F(3,199)= 107.83, p<.001). Again, the analysis revealed the expected main effect of Condition (Beta = 0.75, t(200 ) = 17.72, p<.001) and SA(Beta = -0.22, t(200) = -5.23, p<.001) such as that SA-severity was correlated with lower needs scores. No interaction between SA-severity and Condition was found (Beta = 0.75, t(200)= -0.24, p=.808). In order to test our main hypotheses, a hierarchical repeated GLM was conducted with Condition, SA-severity, Direction and their interactions as predictors and decision latencies as a dependent variable. In the first Step, we used all three variables and their two-way interactions as predictors and in the second Step we added the three-way interaction to the model. No main effect was found for SA-severity (Beta =-0.08, t(200)= -1.27, p=.20 ) or Condition (Beta = 0.05, t(200) = - 0.7, p =.43) . Furthermore, no significant interaction between Direction and SAseverity (Beta = 0.07, t(200) = 0.99, p =.32) or Direction and Condition was found (Beta = 0.006, t(200)= 0.09, p =.91).The lack of interaction between Direction and SA-severity contradict the 10

Social Anxiety and the Interpretation of Facial Expressions SA negative interpretation hypothesis. However, in the second block a significant three-way Direction X Condition X SA-severity interaction effect (Beta =- 0.5, t(199)= 2.15, p=.03) was found. This final model explained 3.4% of the variance (F(3,199)= 2.31, p=.07). Follow-up analyses revealed that a two-way Group X SA-severity interaction was significant only in the Smile-to-Disgust direction (Beta = 0.5, t(199)= 2.28, p =.024) representing a negative correlation between SA-severity and decision latencies following exclusion (Beta = - 0.26, t(100) = -2.27, p =.007) but not following inclusion (Beta = 0.02, t(99) = 0.28, p=0.77). Such a two way interaction was not found for the Disgust-to-smile direction (Beta = 0.06, t(199) = 0.26, p = 0.79). Taken together, the results support the reduced affiliative attunement following exclusion in SA hypothesis. These findings are graphically depicted in Figure 2 based on the aforementioned (Study 1) division to high and low SA groups. In sum, the results of Study 2 reveal that following exclusion (but not inclusion), SA-severity is associated with faster detection of the offset of smile as compared to the offset of disgust expressions. General Discussion Our results were partially supportive of our main hypotheses. First, consistent with the negative facial interpretation in SA hypothesis, in Study 1, SA was found to be associated with faster detection of the offset of smiles in both exclusion and inclusion conditions. These data are consistent with cognitive theories of SAD highlighting fears of losing positive and inducing negative evaluations by others. Those fears may be partly manifested as faster accrual of facial information indicating signals of rejection, or as slower accrual of facial information indicating signals of acceptance.

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Social Anxiety and the Interpretation of Facial Expressions Second, in Study 2 we found that the association between SA and proclivity to detect the offset of smiles faster than the offset of disgust was stronger following exclusion than following inclusion. Those results suggest an enhanced negative interpretation bias following exclusion in SA. Cognitive models of SAD implicate fear of rejection as one of the main components of this disorder (Bruch & Cheek, 1995). A materialization of exclusion – socially anxious individuals' most distressing scenarios – may activate a cascade of processes contributing to the enhancement of such fears, leading, in turn, to avoidance and withdrawal from social interaction. Our studies examine the conditions under which interpretation biases of emotional facial expressions in SA are likely to emerge. First, we examined interpretation biases following the activation of belongingness concerns – social exclusion. Exclusion may serve as a catalyst of negative interpretation biases thus highlighting SA-related interpretation tendencies. Specifically, exclusion may evoke two distinct coping strategies based on the prospects of re-connection. If these prospects are perceived as low, suspicions and withdrawal may follow (DeWall & Richman, 2011). Thus, a recent exclusion may highlight the difficulty of re-connection (and approval), and heighten protective and avoidant motivations. Such mindset enhances the availability of negative information. In contrast, if the occurrence of exclusion is taken as a transient state, and the prospects of re-connection are high, then a strategy of approval-seeking is likely to be undertaken to compensate for the loss of belongingness (DeWall & Richman, 2011. Molden & Maner, 2013). Whereas the former coping mode may be used by individuals high in SA, the latter is more likely to be used by individuals low in SA. Second, we chose to focus on the question "when do you feel that the stimulus change?" rather than "what is the stimulus?", thus placing subjective assessment at the center of the interpretation process. That is, we focused on the point from which the meaning attributed to the expression 12

Social Anxiety and the Interpretation of Facial Expressions shifts from smile to disgust. Putting the spotlight on this transition point allows the examination of facial interpretation without the emphasis on a specific verbal label. Our findings using this technique harmonize with the findings from studies measuring neural response to emotional facial expressions in SA. Such studies found that highly socially anxious individuals, as compared to low socially anxious individuals, demonstrate enhanced amygdala activation in response to morphed disapproval faces. This activation may indicate a tendency to interpret those expressions as threatening (Blair et al., 2008; Moser, Huppert, Duval, & Simons, 2008). Third, we sought to include disgust expressions, as it is possible that SA is associated with a particular sensitivity to expressions evocative of fears of exclusion and rejection (Amir et al., 2005). Indeed, highly socially anxious individuals tend to perceive disgust as displaying contempt (Heurer et al., 2010) and rate interactions with targets showing disgust as costlier than do controls (Schofield et al., 2007). Moreover, disgust facial expressions are perceived more negatively by individuals high, but not low, in SA (Amir, Najmi, Bomyea, & Burns, 2010). Finally, high, but not low, SA individuals were found to be more sensitive to facial expressions of disgust as compared to anger (Rossignol, Anselme, Vermeulen, Philippot, & Campanella, 2007). Several clinical implications can be derived from the present investigation. First, taken together with the findings of other studies, the results of Study 2 suggest that SA interacts with exclusion in affecting the interpretation of interpersonal cues. Clinical interventions may highlight the link between feelings of exclusion on the one hand, and negative biases on the other. Awareness of such tendencies is likely to be needed to reduce those biases. Second, the results of our studies suggest that a possible interpretation modification strategy may be a facilitation of a quantitative change in interpretation. This is in contrast to the majority of existing efforts of interpretation 13

Social Anxiety and the Interpretation of Facial Expressions modification in SA which focus on the categorical change in the initial interpretation of social situations (from negative to positive or neutral). In other words, the goal of interpretation training would be to affect the amount of information needed to form an interpretation rather than modifying the initial interpretative tendency. In closing, several limitations of the present research need to be noted. First, it is possible that SA was associated with a faster smile-to-disgust identification because of the reduced willingness to look at disgust faces rather than the faster accrual of negative information (Schofield et al., 2007). Future studies may disentangle change detection from exposure duration by extending the presentation of the clips beyond participants' detection action. Second, the present task does not differentiate between the onset of disgust and the offset of smile (and vice versa). Research currently conducted in our lab differentiates between the emergence of cues of affiliation and the emergence of cues of disapproval. Third, because of the possible link between SA and the tendency to interpret smiling facial expressions as threatening, SA may not associated with the perceptions of smiles as approval. Future studies may emphasize the interpersonal meaning of expressions by explicitly including the evaluative dimension of the decision. That is, asking the participant to note when the expression ceases to indicate approval (or disapproval) may further highlight interpretative tendencies. Fourth, our studies did not examine whether the observed interpretation bias were specific to SA. Future studies may address this question, and extend similar paradigm to clinical samples of SAD and of depression, as well as to other populations exhibiting high rejection sensitivity. Finally, pre-registration of experimental design and hypothesis could greatly strengthen our findings (Van't Veer and GinerSorolla, 2016).

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Social Anxiety and the Interpretation of Facial Expressions In conclusion, the findings of the present study support the notion that SAD is associated with biased processing of ambiguous facial cues (Clark & Wells, 1995; Rapee & Heimberg, 1997). Importantly, this SA-related bias is enhanced following social exclusion. Reducing the amount of evidence needed by highly socially anxious individuals to interpret social cues as signaling approval may enhance their ability to note signals of affection and affiliation and reduce their sense of alienation. A successful intervention may lead highly anxious individuals to question their outlook by asking themselves – Maybe she started smiling at me a while ago, and I noticed it only now?

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Social Anxiety and the Interpretation of Facial Expressions Acknowledgements This work was supported by the U.S. – Israeli Binational Science Foundation [grant number 2013205 to P.M.N. and E.G.S.]; and the Israel Science Foundation [grant number 740/15 to E.G.S.]. The authors thank Omri Rubinstein for his assistance with stimuli creation. Sources of financial support had no influence over the design, analysis, interpretation, or choice of submission outlet for this research. Data are available by contacting the corresponding author.

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27

Social Anxiety and the Interpretation of Facial Expressions Figure 1. Mean Detection Time (in seconds) of the Offset of Smiles following Exclusion and Inclusion in High and Low Socially Anxious Individuals (Study 1).

Detection Time of the expressions' offset

12 11 10 9 8 HSA

LSA Inclusion

Exclusion

28

Social Anxiety and the Interpretation of Facial Expressions Figure 2. Mean Detection Time (in seconds) of the offset of smiles and disgust following Exclusion and Inclusion in High and Low Socially Anxious Individuals (Study 2).

Detection Time of the expressions' offset

Inclusion 12 11 10 9 8 HSA

LSA

Smile-To-Disgust

Disgust-To-Smile

Detection Time of the expressions' offset

Exclusion 12 11 10 9 8 HSA Smile-To-Disgust

LSA Disgust-To-Smile

29

Social Anxiety and the Interpretation of Facial Expressions Table 1- Studies Investigating Interpretation of Emotional Facial Expressions in Social Anxiety. Study

Target

Target

Target

Stimuli:

Task:

expression:

expression:

expression:

Type

Labelling

Anger

Disgust

Smile

Manipulation: Threat on belongingness

Results:

Results:

Response

Sensitivity to

Bias

negative expressions

Bell, Bourke, Colhoun,

Yes

Yes

Yes

Stills

Yes

No

Yes

No

Bui et al., 2017

Yes

No

Yes

Clips

No

No

No

No

Button, Lewis, Penton-

Yes

Yes

Yes

Stills

Yes

No

Yes

No

Yes

No

Yes

Stills

Yes

No

No

No

Yes

No

Yes

Stills

Yes

No

Yes

Reduced

Carter, Frampton, & Porter ,2011

Voak, , & Munafò, 2013 Garner, Baldwin, Bradley, & Mogg, 2009 Gilboa-Schechtman, Foa,

30

Social Anxiety and the Interpretation of Facial Expressions Vaknin, Marom, & Hermesh, 2008 Gutiérrez-García & Calvo, Yes

Yes

Yes

Clips

Yes

No

Yes

Enhanced

Yes

Yes

Yes

Clips

Yes

No

No

No

Joorman & Gotlib, 2006

Yes

No

Yes

Clips

Yes

No

No

Enhanced

Justye & Schonenberg,

Yes

No

Yes

Stills

Yes

No

No

No

Kolassa et al., 2009

Yes

No

Yes

Stills*

Yes

No

No

No

Maoz et al., 2016

Yes

No

Yes

Stills

Yes

No

Yes

No

Montage et al., 2006

Yes

Yes

Yes

Clips

Yes

No

No

Reduced

Philippot & Douilliez,

Yes

Yes

Yes

Stills

Yes

No

No

No

2017 Heuer, Lange, Isaac, Rinck, & Becker, 2010

2014

31

Social Anxiety and the Interpretation of Facial Expressions 2005 Qiu, Han, Zhai, & Jia,

Yes

No

Yes

Clips

Yes

No

No

No

Richards et al., 2002

Yes

Yes

Yes

Stills

Yes

Yes

No

No

Stevens, Gerlach, & Rist,

No

Yes

Yes

Stills

Yes

No

No

No

Yes

No

Yes

Stills

Yes

No

Yes

Enhanced

2018

2008 Yoon, Yang, Chong, & Oh, 2014

32

Highlights

• HSAs detect faster the offset of smiles compared to LSAs. • Following exclusion, the described group difference enhances. • No group differences in detection time of the offset of disgust faces were found.

October 07th, 2018 Adam S. Radomsky, PhD Concordia University, Montréal, Quebec Canada Dear Dr. Radomsky, We are declaring that we do not have any conflict of interests regarding the manuscript- It's the End of the Smile as We Know it: Social Anxiety and the Interpretation of Morphed Facial Expressions Following Exclusion and Inclusion. Furthermore, we do not have interests that might be interpreted as influencing the research, and APA ethical standards were followed in the conduct of the study. Sincerely, Roy Azoulay Department of Psychology Bar Ilan University Ramat-Gan, 5290002 Israel Tel: 972-53-2734137 Fax: 972-3-535-0267 E-mail: [email protected]