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Working memory load moderates lateattentional bias in social anxietyMatt R. Judah a , DeMond M. Grant a , William V. Lechner a & Adam C. Millsa

a Department of Psychology, Oklahoma State University, Stillwater, OKVersion of record first published: 11 Sep 2012.

To cite this article: Matt R. Judah , DeMond M. Grant , William V. Lechner & Adam C. Mills (2013): Workingmemory load moderates late attentional bias in social anxiety, Cognition & Emotion, 27:3, 502-511

To link to this article: http://dx.doi.org/10.1080/02699931.2012.719490

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BRIEF REPORT

Working memory load moderates late attentional biasin social anxiety

Matt R. Judah, DeMond M. Grant, William V. Lechner, and Adam C. Mills

Department of Psychology, Oklahoma State University, Stillwater, OK

The vigilance�avoidance hypothesis suggests that socially anxious individuals attempt to detect signsthat they are being evaluated (vigilance) and subsequently direct attention away from such stimuli(avoidance). Although extensive evidence supports vigilance, data concerning subsequent avoidance isequivocal. Drawing from models of attention, the current study hypothesised that working memoryload moderates late attentional bias in social anxiety such that avoidance occurs if working memoryload is low, and difficulty disengaging attention occurs if working memory load is high. Forty-oneundergraduates (19 socially anxious; 22 non-anxious controls) completed a dot-probe task withemotional (happy and disgust) and neutral facial expressions and a concurrent n-back task. Resultssupported the hypothesis such that socially anxious subjects demonstrated avoidance of disgust faceswhen working memory load was absent, but had difficulty disengaging attention during highworking memory load. Theoretical implications and directions for future research are discussed.

Keywords: Social anxiety; Vigilance�avoidance; Attention bias; Working memory.

Cognitive models of social anxiety disorder posit

that fear of negative evaluation biases selective

attention toward cues which suggest that evaluation

is likely (Clark & Wells, 1995; Rapee & Heimberg,

1997). Specifically, Rapee and Heimberg (1997)

suggested that socially anxious individuals (HSAs)

monitor the environment for cues that they are

being negatively evaluated by others, a process

known as vigilance. Attention toward threat is

fundamental to cognitive models and is thought to

prevent the recognition of cues which indicate that

the situation is not threatening (Clark & Wells,

1995). Consistent with their important role in

cognitive models, evidence suggests that attention

Correspondence should be addressed to: DeMond M. Grant, Department of Psychology, Oklahoma State University,

Stillwater, OK 74078, USA. E-mail: demond.grant@okstate.edu

Portions of these data were submitted for presentation at the 45th annual meeting of the Association for Behavioral and

Cognitive Therapies, National Harbor, MD.

The authors would like to thank Courtney Cavett, Lucinda Chee, Mike Dunn, Mike Fitzgerald, Zach Johnson, Morgan

McCulley, and Jessie Riess for their assistance with data management and collection, and the students of Oklahoma State

University who generously gave their time to participate in this project.

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biases increase social anxiety (Heeren, Peschard, &Philippot, in press) and attenuate followingtreatment (Mattia, Heimberg, & Hope, 1993).Due to their role in the aetiology and main-tenance of symptoms, these biases are the targetof emerging treatments, such as attention mod-ification. Despite the importance of attentionbiases in social anxiety disorder, research on thistopic is currently limited by discrepancies in theliterature and hypotheses that do not adequatelydescribe empirical observations. The goal of thecurrent study was to advance the understanding ofattention biases in social anxiety by testing thehypothesis that working memory load plays a rolein these biases, and to determine whether thishypothesis may be useful for explaining equivocalresults in the literature.

During the last two decades, research hasbegun to uncover the complexity of attentionalprocesses in social anxiety. Early tests of thevigilance hypothesis described in Rapee andHeimberg’s (1997) cognitive model met withmixed results (see Cisler & Koster, 2010; Schultz& Heimberg, 2008; Staugaard, 2010; Yiend,2010), with some studies supporting vigilancefor threatening stimuli (e.g., Mattia et al., 1993)and others suggesting attentional bias away fromthreat (e.g., Mansell, Clark, Ehlers, & Chen,1999), a process known as avoidance. Thevigilance�avoidance hypothesis emerged as anattempt to integrate these disparate findings(Mogg, Philippot, & Bradley, 2004) and predictsthat HSAs automatically orient attention towardthreat (vigilance) and subsequently direct atten-tion away from it (avoidance). To test thishypothesis, researchers have modified thedot-probe task to use varying stimulus onset times(usually between 500 and 1,500 ms) in order toobtain a snapshot of attentional processes atdifferent post-presentation latencies. Many stu-dies using this and similar approaches supportthe vigilance�avoidance hypothesis (e.g., Garner,Mogg, & Bradley, 2006; Mogg et al., 2004;Wieser, Pauli, Weyers, Alpers, & Muhlberger,2009). For example, Wieser and colleagues (2009)tracked eye movements during passive viewing ofemotional facial expressions and found that

individuals with high fear of negative evaluationshowed orientation toward emotional faces duringthe first second of exposure and avoidance fromone to one-and-a-half seconds after face presenta-tion. However, other evidence presents a problemfor the vigilance�avoidance hypothesis. Numerousstudies suggest that HSAs have difficulty disen-gaging attention from threatening stimuli (e.g.,Buckner, Maner, & Schmidt, 2010; Schofield,Johnson, Inhoff, & Coles, 2012). The quantity ofevidence suggesting late avoidance of threat anddifficulty disengaging from threat has not yet beensynthesised into a validated hypothesis, and fewtheorists have articulated an explanation for thesediscrepant data.

Theories of attention may provide the mostparsimonious explanation of these findings. Gen-erally, theories of attention dichotomise atten-tional processes into two modes of resourceallocation (see Corbetta & Shulman, 2002; Klein& Lawrence, 2012). The first of these is theexogenous, or stimulus-driven, system. Stimulus-driven attention is primarily concerned withdetecting salient stimuli in the environment,including threat. The second system is known asthe endogenous, or goal-directed, system. Thissystem typically comes on line later and isprimarily concerned with executive control overattentional processes (Klein & Lawrence, 2012).These systems differ in that the stimulus-drivensystem is automatic, placing few demands onattentional resources, whereas the goal-directedsystem is top-down, regulates stimulus-drivenresponses, and competes with other cognitiveprocesses for limited executive resources (Corbetta& Shulman, 2002). Other models have describedthe goal-directed system as an ability known asattentional control (e.g., Derryberry & Reed,2002). Researchers have hypothesised that atten-tional control is the primary mechanism ofattentional avoidance in anxiety (e.g., Cisler &Koster, 2010). Indeed, Derryberry and Reed(2002) found that trait anxious individuals highin attentional control were more likely to disen-gage their attention from threatening stimuli at500 ms and that those low in attentional controlhad difficulty disengaging attention from such

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stimuli. Thus, attentional control represents abasic executive function, which may explain thediscrepancies in the vigilance�avoidance socialanxiety literature.

A close association between attentional controland working memory capacity has been noted bymany researchers, some of whom have suggestedthat they are the same entity (e.g., Redick &Engle, 2006). In support of this, Jonides (1981)found that working memory load impaired goal-directed attention (i.e., attentional control). How-ever, working memory load did not affect thestimulus-driven system. Similarly, Redick andEngle (2006) found that performance on theOSPAN task, which measures working memorycapacity, predicted executive control of attention,but was unrelated to stimulus-driven processes.Thus, increased burden on working memoryshould lead to changes in attentional biases asso-ciated with the endogenous, goal-oriented system.

Avoidance has been posited to represent a biasin this goal-oriented system (Cisler & Koster,2010). It follows that avoidance is dependent onthe availability of executive resources. This con-ceptualisation is consistent with attentional con-trol theory (e.g., Eysenck, Derakshan, Santos, &Calvo, 2007), which predicts that anxiety impairsthe executive control sector of working memory,especially the ability to inhibit pre-potent, stimu-lus-driven processes and to shift attentional focusaway from threat. Thus, effortful avoidanceappears to involve the inhibition of stimulus-driven attentional orientation toward threat andthe shifting of attention away from threat. There-fore, preoccupation of executive resources (e.g.,working memory) by a secondary process shouldresult in an impaired ability to initiate avoidance,and difficulty disengaging attention should result.

Based on these models and an integration ofempirical findings, the current study hypothesisedthat working memory load moderates late atten-tional biases such that: (1) in conditions of lowworking memory load, HSAs will shift attentionaway from threatening stimuli (i.e., avoidance);and (2) in conditions of high working memoryload, HSAs will have difficulty initiating avoid-ance, and difficulty disengaging attention from

threatening stimuli will result. To test this,individuals high and low in social anxiety com-pleted a dot-probe task that required them toidentify a probe appearing 1,500 ms after a pair offaces, one neutral, one emotional (disgust andhappy) appeared. A secondary modified n-backtask was included during the dot-probe task inorder to manipulate working memory load. Pre-vious research supports the n-back task as a validmanipulation of working memory load (Gray,Chabris, & Braver, 2003; Watter, Geffen, &Geffen, 2001). The n-back task varied across threeblocks, resulting in no (n�0), low (n�1), andhigh (n�2) working memory load conditions. Itwas predicted that HSAs would respond fasterto probes which followed neutral faces when n�0or 1, and that they would respond faster to probeswhich followed emotional faces when n�2.

METHOD

Participants

Participants were recruited from a large mid-western university through an online researchcredit system. These participants were selectedbased on a measure of social anxiety (i.e., SocialInteraction Anxiety Scale; SIAS) filled out duringa pre-screener prior to entering the study. Parti-cipants who scored at least one standard deviationabove the mean (i.e.,]30) and those who scoredequal to or less than the mean (i.e.,519) reportedfor a college sample by Mattick and Clarke (1998)were invited to participate in the study asqualifiers for the HSA and LSA groups, respec-tively. Immediately prior to the administration ofthe dot-probe task, participants completed theSIAS again. Scores at the second administrationwere used to classify participants into high andlow social anxiety groups with cut-offs identical tothe criteria used for recruiting subjects. The meanSIAS score for the entire sample was 26.95, with amean of 12.73 for the low anxiety group and amean of 43.42 for the high anxiety group. Therewere 28 females (68.3%) and 13 males. Both sexeswere equally represented in groups, x2(1) �0.02,p�.90. The mean ages for the HSA and LSA

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groups were 19.79 and 19.14, respectively, andthere was not a significant difference betweengroups, t(39) �1.13, p�.27. Twenty-seven sub-jects identified as Caucasian (65.9%). The samplealso consisted of six African American (14.6%),two Asian (4.9%), one Native American (2.4%),and five biracial individuals (12.1%).

Two participants were dismissed before com-pleting the dot-probe task because of difficultiescommunicating in English. Out of the 56 partici-pants who completed the entire protocol, 11 werenot included in the analyses because they did not fallinto the LSA or HSA group (i.e., SIAS scores werebetween 19 and 30). Additionally, two participantswere excluded from analyses because of equipmentmalfunctions during data collection, and anothertwo participants were excluded for failing to followinstructions during the dot-probe task.

Materials

Each participant filled out the Social InteractionAnxiety Scale (SIAS; Mattick & Clarke, 1998), a20-item self-report questionnaire which measuresthe severity of fears concerning general socialsituations. Responses using a Likert-type scalerange from 0 (Not at all characteristic or true of me)to 4 (Extremely characteristic or true of me) withtotal scores ranging from 0 to 80. The SIAS hasgood internal consistency, convergent validitywith other measures of social anxiety, and candistinguish between individuals with social anxietydisorder and other anxiety disorders (Brown et al.,1997). The SIAS has been shown to have stronginternal consistency (a�.94; Mattick & Clarke,1998). For the current study a�.95.

Stimuli used in the dot-probe task includedpictures of neutral, happy, and disgust facesobtained from 24 (12 male, 12 female) Caucasianmodels selected from the Radboud Faces Data-base (Langner et al., 2010). Faces conveyingdisgust were used because they are rated byHSAs as being more negative than angry faces(Amir, Najmi, Bomyea, & Burns, 2010) and havebeen commonly used in similar studies (e.g.,Buckner et al., 2010). Happy faces were includedbecause several recent studies suggest that socially

anxious individuals may perceive them to bethreatening and display biased attention to happyexpressions (Horley, Williams, Gonsalvez, &Gordon, 2004; Schofield et al., 2012; Wieseret al., 2009). These faces were presented on a43.2 cm Crystal Scan SVGA colour monitorattached to a Dell 3100 Pentium computer.

Procedure

All procedures were IRB approved. After provid-ing informed consent, participants filled out on-line versions of the SIAS and other measureswhich were not included in the current study.Participants were seated approximately 80 cmfrom a computer monitor. Participants thencompleted three counter-balanced blocks consist-ing of 96 trials each, which were scripted andadministered using DirectRT (Jarvis, 2008). Thethree blocks consisted of a standard dot-probetask (see Figure 1), a dot-probe task with asecondary 1-back task, and a dot-probe taskwith a secondary 2-back task. Each trial beganwith a light grey fixation cross, which waspresented in the centre of the monitor for 500ms. After this, face pairs consisting of a neutraland an emotional (happy or disgust) facial expres-sion made by the same model appeared for 1,500ms. This presentation time was selected as it haspreviously been shown that conclusions regardingdifficulty disengaging attention and avoidance canbe made at this latency (Schofield et al., 2012;Wieser et al., 2009). Each facial picture was 8.8cm wide by 11.5 cm high and appeared at a visualangle of approximately 6.38 by 8.28. Face pairswere separated by 22.5 cm. After the facesdisappeared, a probe appeared in the centre ofthe position previously occupied by one of thefaces. The letters ‘‘E’’ and ‘‘F’’ were used as probesin order to prevent participants from using theirperipheral vision to identify probes. Each probemeasured 1 by 1.5 cm and appeared in the centreof the position of the preceding face. The distancebetween the probe positions was 31.3 cm; thus,the horizontal visual angle in which the probesappeared was approximately 22.18. Responseinstructions were counterbalanced such that

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participants were instructed to press a button on a

game controller with the right thumb for one letter

and a different button with the left thumb for the

other letter. The next trial began immediately after

this response or 3,000 ms after the appearance of

the probe if no response was made. Each block

utilised the same faces. Trials, face positions (left

or right), and probe position were randomised.

Before completing each block, subjects completed

10 practice trials with feedback in order to ensure

that the instructions for the block were under-

stood. In line with similar research (see Klumpp &

Amir, 2009), reaction times which did not fall

between 100 and 3,000 ms were removed from the

analyses as anticipatory or excessively delayed

responses, and this resulted in the removal of

1.2% of trials. Dot-probe trials were removed from

the analyses if the participant identified the probe

incorrectly, resulting in the removal of 2.9% of

trials overall. A 2 (Group: HSA, LSA)�3 (Work-

ing Memory Load: no load, 1-back, 2-back)

analysis of variance (ANOVA) revealed that the

number of incorrect trials did not differ between

blocks, FB1, ns, but did differ by Group, F(1,

39) �10.65, p�.002, g2p ¼ :22, such that the

HSA group (M�3.88, SD�2.88) made more

errors than the LSA group (M�1.88, SD�2.67).

The interaction was not significant, FB1, ns.The blocks loading working memory included

fixation crosses with either one or two circles

around them for the 1-back and 2-back tasks,

respectively. For the 1-back block, participants

were instructed to verbalise the letter which

appeared on the previous trial whenever a cross

with a circle appeared. For the 2-back block,

subjects were required to verbalise the letter which

appeared two trials back whenever two circles

appeared around the fixation cross. The circles

(either one or two) appeared randomly in 25% of

the trials for each block. Verbal responses to n-

back trials were transmitted to an adjacent room

by a wireless intercom. An experimenter recorded

the first verbalisation following each n-back cue,

and these responses were later matched to the

corresponding trials in the DirectRT log file to

assess accuracy. Average n-back task accuracy was

Figure 1. Dot-probe procedure. Face images are taken from the Radboud Faces Database (Langner et al., 2010) and are used with

permission from the copyright holder and publisher.

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95.4% for the 1-back block and 82.3% for the 2-back block. A 2 (Group: HSA, LSA)�2 (Work-ing Memory Load: 1-back, 2-back) ANOVArevealed a main effect for Working MemoryLoad, F(1, 39) �17.95, p�.001, g2

p ¼ :32, suchthat subjects made more errors on the 2-back task(M�4.25, SD�3.91) compared to the 1-backtask (M�1.08, SD�2.52). This suggested thatthe task was a successful manipulation of cognitiveload. Neither the interaction, FB1, ns, nor themain effect of Group, F(1, 39) �1.24, p�.27,were significant, suggesting that the reaction timeresults are not accounted for by differentialperformance on the task between groups.

Analytical approach

A 2 (Group: HSA, LSA)�3 (Working MemoryLoad: no, low, and high)�3 (Facial Expression:neutral, disgust, and happy) mixed ANOVA wasused as an Omnibus test of differences in reactiontime as measured in milliseconds. In order toprobe the nature of the effect, bias scores forhappy and disgust faces were calculated using theformula Rn � Re, where Rn is the mean reactiontime to probes appearing in the position of theneutral stimulus and Re is the mean reaction timeto probes following emotional stimuli. Thus, apositive bias score indicates a faster response toemotional faces, which suggests an attentionalbias toward such stimuli. A negative bias scoreindicates that the participant responded morequickly to neutral faces, which suggests avoidanceof emotional faces. Finally, a bias score near zeroindicates no differences in response times betweenemotional and neutral faces. A 2 (Group: HSA,LSA)�3 (Working Memory Load: no, low, andhigh) mixed ANOVA was used to examine thepresence of attentional biases. Greenhouse�Geissercorrections were used as needed.

RESULTS

Omnibus test

For the reaction-time ANOVA, there was asignificant interaction between Group, Working

Memory Load, and Facial Expression, F(2.77,108.05) �6.46, p�.001, g2

p ¼ :14. The maineffect for Working Memory Load was significant,F(1.66, 68.86) �24.90, pB.001, g2

p ¼ :39. Posthoc dependent t-tests suggested that reactiontimes were slower, t(40) �4.88, pB.001, for the2-back block (M�733.10, SD�126.55) than the1-back block (M�673.09, SD�91.47) and wereslower, t(40) �6.02, pB.001, than the block onwhich working memory was not loaded(M�657.61, SD�89.88). Reaction times forthe 1-back block were not significantly differentfrom those for the condition on which workingmemory was not loaded. No significant effectswere noted for Group, FB1, ns, or FacialExpression, F(1.77, 68.86) �1.08, p�.34.

Disgust biases

For the disgust bias score ANOVA, there was asignificant interaction between Working MemoryLoad and Group, F(2, 78) �3.55, p�.03,g2

p ¼ :08. As hypothesised, a simple effects ana-lysis suggested differences between WorkingMemory Load conditions for the HSA group,F(2, 36) �4.19, p�.023, but not for the LSAgroup, F(2, 42) �2.32, p�.11. Follow-up pair-wise comparisons revealed that HSA participantsdisplayed significantly higher mean bias scores inthe 2-back condition (M�19.56, SD�54.07)than they did in the no working memory loadcondition (M��19.13, SD�33.88; p�.004).Scores for the 1-back task (M��7.51, SD�46.03) were not significantly different from scoreson the 2-back (p�.08) or the condition on whichworking memory was not loaded (p�.41; seeFigure 2). This suggests that HSA participantsdisplayed relative avoidance of disgust faces whenworking memory load was absent (as indicated bynegative bias scores) compared to a relativedifficulty in disengaging attention from these faces(as indicated by a positive bias score) when underhigh working memory load. One-sample t-testswere used to determine whether HSA disgust biasscores differed from zero. HSAs showed difficultydisengaging attention for disgust faces withoutworking memory load, t(18)��2.46, p�.02,

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but no other tests were significant. There was amain effect for working memory load, F(2, 78) �3.16, p�.048, g2

p ¼ :08. Pairwise comparisonsshowed that bias scores were larger for the 2-backblock (M�11.71, SD�7.77; p�.03) than the1-back condition (M��11.02, SD�7.56). Thecondition without working memory load did notsignificantly differ from the 2-back (p�.08) or1-back (p�.41) conditions. There was no maineffect for group, FB1, ns.

Happy biases

For the ANOVA analysing biases for happy facialexpressions, there was a significant interactionbetween Working Memory Load and Group,F(2, 78) �5.69, p�.005, g2

p ¼ :13. A simpleeffects analysis revealed that bias scores differedbetween Working Memory Load conditions forthe LSA group, F(2, 42) �3.84, p�.029, but didnot differ for the HSA group, F(2, 36) �2.26,p�.12. Follow-up pairwise comparisons indi-cated that LSA participants displayed significantlyhigher mean bias scores in the 1-back condition(M�23.71, SD�55.70) than they did in thecondition in which working memory load wasabsent (M��11.63, SD�48.21; p�.04), or inthe 2-back condition (M��21.97, SD�59.50;p�.02), although these conditions were notsignificantly different (see Figure 3). There wasno main effect for working memory load or group,Fs B1, ns.

DISCUSSION

The current study tested the hypothesis thatworking memory load moderates late attentionalbias in social anxiety. The results are largelyconsistent with these predictions and suggest thatsocially anxious individuals avert attention awayfrom social threat if sufficient executive resourcesare available. However, they may have difficultydisengaging attention from threat if other pro-cesses are competing for executive resources. Morespecifically, the current study found that workingmemory load moderated late attentional biassuch that HSAs showed avoidance of threateningfaces when working memory load was absentand had difficulty disengaging attention fromthreatening faces when it was high.

The current findings are somewhat inconsis-tent with several recent studies which suggestthat HSAs may display biased attention foremotional facial expressions in general, includinghappy faces, rather than specifically for negativeexpressions (e.g., Garner et al., 2006; Horleyet al., 2004; Schofield et al., 2012; Wieser et al.,2009). Although this seems contradictory totheoretical predictions, these findings have ledseveral researchers to suggest that socially anxiousindividuals may perceive happy faces to bethreatening, perhaps because laughter may conveynegative evaluation (Schofield et al., 2012).In support of this, one recent study found that

HSA LSA

Difficulty disengaging

Avoidance

Figure 2. Disgust bias scores (in ms). HSA �high social anxiety

group; LSA �Low social anxiety group. Bars denote standard

error.

HSA LSA

Difficulty disengaging

Avoidance

Figure 3. Happy bias scores (in ms). HSA �high social anxiety

group; LSA �Low social anxiety group. Bars denote standard

error.

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HSAs showed a stronger startle response toboth positive and negative emotional faces com-pared to non-anxious controls (e.g., Garner,Clarke, Graystone, & Baldwin, 2011), suggestingthat HSAs find both positive and negativeemotional faces to be aversive. Additional researchis needed in order to clarify how HSAs processpositive facial expressions and to clarify whetherthis is affected by cognitive load.

The late attentional bias findings provideinitial support for a hypothesis that may con-tribute toward resolving long-standing empiricaldiscrepancies. Broadly, this hypothesis predictsthat individual and situational differences in theexecutive control of attention may affect endo-genous attentional processes. Theories of atten-tion conceptualise a stimulus-driven system,which is automatic and reactive to threat, as wellas an executive control system capable of theeffortful direction of attention (Corbetta &Shulman, 2002; Derryberry & Reed, 2002; Klein& Lawrence, 2012). The current study supportsCisler and Koster’s (2010) hypothesis that avoid-ance is a function of the latter system. Specifically,HSAs showed late attentional avoidance of emo-tional stimuli if working memory load was low orabsent and difficulty disengaging attention if itwas high. This is consistent with recent studieswhich suggest that trait anxious individuals showimpaired attentional control under cognitive loadcompared to non-anxious controls (Berggren,Koster, & Derakshan, 2012). It is possible thatanxiety and executive control processes competefor the same attentional resources, resulting indeficits if demand for these resources exceeds theiravailability (Berggren & Derakshan, in press).

The results of the current study may haveimplications for understanding the nature ofattentional biases in psychopathology. Contem-porary models of anxiety and mood disorders positthat cognitive processes, such as worry andrumination, are a core feature of these disorders.Such processes may utilise working memory andthereby impair attentional control. For example,Clark and Wells (1995) posited that focuson internal threat cues reduces attention towardnon-threatening stimuli in the environment.

Anticipatory processing, which is characterisedby this internal focus, may preoccupy executiveresources and thereby interfere with controllingattention away from threat. The current studysuggests that research is needed to investigateattentional biases within the context of suchprocesses. Additionally, these findings suggestthat future research should account for individualand situational variability in basic cognitive pro-cesses, such as working memory. This may beparticularly important in the case of sociallyanxious individuals because previous researchsuggests that they may have impaired workingmemory capacity for neutral, but not threatening,information compared to normal controls (Amir& Bomyea, 2011).

The current study’s results are consistent withextant research which suggests that workingmemory plays an important role in cognitivecontrol. For example, studies have shown thatlow working memory capacity is associated withdiminished ability to suppress thoughts (e.g.,Brewin & Beaton, 2002). These data contributetoward a pool of evidence which suggests thatanxiety, attentional processes, and working mem-ory influence one another. Additionally, thesedata provide emerging support for a hypothesiswhich may apply to attention biases in otheranxiety disorders and in depression. Cognitiveprocesses in these disorders (e.g., worry andrumination) may preoccupy executive resourcesand result in difficulties controlling attention.Therefore, research is needed to determine howthe manipulation of working memory affectsattentional biases across disorders.

The novel approach of combining the dot-probe task with the n-back task may be a usefulmanipulation for future research. Increasing n forthe n-back task led to the commission of moren-back errors and delayed reaction times on thedot-probe task, thus suggesting that it was asuccessful manipulation of working memory load.Additional research is needed in order to evaluatethis paradigm more fully, and future research mayimprove upon this methodology.

This study was not without limitations. Aclinical sample was not used, and this limits the

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generalisability of the results. However, studies

using non-clinical samples with high levels of

social anxiety are generally consistent with those

which use social phobics, and current models

conceptualise subclinical social anxiety and social

phobia as being on a continuum of severity (e.g.,

Rapee & Heimberg, 1997). The verbal responses

made on the n-back blocks present a limitation in

comparing them to the block in which working

memory was not manipulated, as there were no

verbalisations in this condition. However, this was

necessary in order to achieve a condition with

minimal working memory load. The performance

of a concurrent verbal task is thought to load

working memory (Baddeley, 2007), which was the

purpose of the manipulation. Nevertheless, future

studies are needed to overcome this limitation.

The use of the dot-probe task also presents

limitations because it captures a single moment

of attentional deployment. This task also mea-

sures attention between two competing stimuli;

therefore, it is of limited ecological validity.

Future research should examine the effects of

manipulating working memory on other cognitive

tasks.Despite these limitations, the current results

add to the extensive literature examining atten-

tional processes among individuals with social

anxiety. In particular, this study provides a frame-

work to explain the equivocal literature testing

attentional biases among these individuals. Addi-

tional research is needed which examines the

hypotheses of the current study using a clinical

sample and other experimental protocols. Such

studies are likely to benefit by using paradigms

which assess covert attention and track eye-

movements simultaneously. This research may

expand upon the current study’s initial evidence

for the important role which working memory

plays in attentional biases in social anxiety.

Manuscript received 27 March 2012

Revised manuscript received 2 August 2012

Manuscript accepted 4 August 2012

First published online 10 September 2012

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