anxiety goes under the skin: behavioral inhibition, anxiety, and autonomic arousal in speech-anxious...

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Personality and Individual Differences 40 (2006) 1441–1451

Anxiety goes under the skin: Behavioral inhibition,anxiety, and autonomic arousal in speech-anxious males

Stefan G. Hofmann *, Hyo-Jin Kim

Department of Psychology, Boston University, 648 Beacon Street, 6th Floor,

Boston, MA 02215-2002, United States

Received 15 August 2005; received in revised form 1 November 2005; accepted 2 December 2005Available online 31 January 2006

Abstract

This study examined the physiological correlates of behavioral inhibition and trait anxiety in speech-anx-ious male college students. We hypothesized that behavioral inhibition and trait anxiety would be associ-ated with an increase in skin conductance level (SCL), but not heart rate, in response to an impromptuspeech task. Hierarchical multiple regressions revealed that trait anxiety, but not behavioral inhibition, pre-dicted SCL. Neither behavioral inhibition nor trait anxiety predicted heart rate reactivity. These findingssupport the notion that SCL is a better autonomic indicator of trait anxiety than heart rate.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Behavioral inhibition; Anxiety; BIS/BAS; Autonomic arousal; Skin conductance level; Speech anxiety;Public speaking

1. Introduction

The role of temperament in the development of psychopathology has been of great interest inrecent years. Temperament has been conceptualized as relatively stable individual differences inbehavioral and affective response styles that emerge early in life and are in part influenced by

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* Corresponding author. Tel.: +1 617 353 9610; fax: +1 617 353 9609.E-mail address: [email protected] (S.G. Hofmann).

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1442 S.G. Hofmann, H.-J. Kim / Personality and Individual Differences 40 (2006) 1441–1451

genetic constitution (Kagan, Snidman, Arcus, & Reznick, 1994). Gray (e.g., Gray, 1982) proposeda neurobiological model that links individual differences in temperament to the interactionsbetween two functionally distinct motivational systems, which determine the intensity of affectiveand behavioral responses to incentives and threats. Gray (e.g., Gray & McNaughton, 1996)named these the Behavioral Inhibition System (BIS) and the Behavioral Approach System(BAS). The BIS, which underlies aversive motivational functions, is sensitive to conditioned aver-sive and extreme novel stimuli and is activated in response to punishment and cues of frustrativenon-reward. Its underlying neural circuits (e.g., septo-hippocampal system) are believed to play animportant role in anticipating and assessing threats. For example, it responds to threat stimuli byproducing anxiety and by inhibiting appetitive behaviors when negative or painful consequencesare anticipated (Fowles, 1980). In contrast, the Behavioral Activation System, or BAS (Fowles,1980) underlies appetitive motivational functions and governs behaviors that are intended to max-imize rewards and minimize punishment.

Some authors (e.g., Fowles, 1994; Quay, 1993) have suggested that quantitative differences inthe strength of these two systems may contribute to a vulnerability to pathology. Gray (1982),for example, proposed that the BIS is the neurophysiological substrate for anxiety. This hypoth-esis is based on animal studies, which demonstrated that anxiolytic drugs had disinhibitory effectson an animal’s behavioral response to punishment; the animal continued to respond despite re-peated punishment (e.g., Gray, 1982). Similarly, the effects of the drugs interfered with the extinc-tion of behaviors following continuous non-reward. These findings led Gray to believe that theBIS represents an anxiety system, and that trait anxiety is a temperamental marker for the BIS(Gray & McNaughton, 1996). Thus, one might assume that trait anxiety reflects individual differ-ences in the reactivity of the BIS.

Fowles (1980) expanded upon Gray’s theory and proposed that electrodermal activity (EDA)and heart rate (HR) may be good physiological indices of the BIS and the BAS, respectively. Fow-les’ postulation of the relationship between HR and BAS was derived from studies showing thatanimals and humans exhibited increased HR when given incentives (Fowles, 1980; Fowles, Fisher,& Tranel, 1982). In a series of studies on a college sample, Fowles and colleagues observed thatHR increased in response to monetary incentives (for a detailed review see Fowles, 1983). Agraded increase in the monetary incentive was associated with a graded increase in HR (Fowleset al., 1982; Tranel, Fisher, & Fowles, 1982). However, a frustrative non-reward condition didnot reveal HR effects upon failure feedback (Fisher, 1982 as cited in Fowles, 1988). Likewise,experimental paradigms, which activated conditioned stimuli for punishment, were associatedwith increases in EDA but were not associated with changes in HR (Fowles, 1980, 1983). Hence,Fowles (1980) suggested that tonic increases in EDA are associated with the activation of the BISin punishment or frustrative non-reward situations, while tonic increases in HR are more closelyassociated with the activation of the BAS in incentive-related situations (Fowles, 1980).

Although the writings by Gray, Fowles, and others have been highly influential, the empiricaltests of these theories have been equivocal (for a review see Matthews & Gilliland, 1999). Somestudies show that EDA responds to a wide range of stimuli (Keltikangas-Jarvinen, Kettunen,Ravaja, & Naatanen, 1999). Other studies suggest that EDA may be a specific index of BIS. Fow-les (1980) reviewed the literature on EDA, which suggests that skin conductance level (SCL) tendsto increase in response to threat of punishment (Fowles, 2000; Hoehn, Braune, Scheibe, & Albus,1997; Scarpa, Raine, Venables, & Mednick, 1997). Furthermore, robust EDA findings have been

S.G. Hofmann, H.-J. Kim / Personality and Individual Differences 40 (2006) 1441–1451 1443

observed in clinical disorders characterized by impulsiveness, such as psychopathy (Arnett, 1997;Fowles, 2000). These findings are in line with Fowles’ theory that EDA may reflect individual dif-ferences in the strength of the BIS (Fowles, 2000).

The current study examined Fowles’ hypothesis about the psychophysiological correlates of theBIS using an analogue sample of speech-anxious college students. The hypothesis was tested in thecontext of an experimental paradigm involving an aversive social task (e.g., impromptu speech)that was intended to activate the BIS. If Fowles’ hypothesis was correct, individuals with highlevels of behavioral inhibition would be expected to exhibit high tonic electrodermal activity inresponse to this aversive social task. Given Gray’s hypothesis that a strong BIS promotes strongtrait anxiety and the conceptual similarity between these two constructs, we expected that traitanxiety would similarly predict changes in SCL but not HR.

2. Method

2.1. Participants

A total of 55 male participants took part in the study. All participants were right-handed asmeasured with the Edinburgh Inventory (Oldfield, 1971). The mean age for the entire samplewas 19.13 (SD = 1.20), ranging from 18 to 23. Seventy-three percent of the participants were Cau-casian, 23% were Asian, 4% were South East Asian, and 2% were Hispanic.

Participants were recruited from an undergraduate introductory psychology course at BostonUniversity, Massachusetts. They received course credit for their participation. Standard experi-mental procedure required all participants to undergo an initial screening. During the screening,participants were asked to rate their level of public-speaking fear on a 0–100 Likert scale with 100indicating the highest level. Only male participants who reported moderate to high levels of pub-lic-speaking anxiety (operationally defined as greater than 65) were recruited. Participants takingpsychotropic medications (e.g., anti-anxiety medications) were not eligible for the study.

2.2. Measures

The following self-report measures were administered subsequent to the experiment to assessfor social anxiety, behavioral inhibition, and trait anxiety.

The Personal Report of Confidence as a Speaker (PRCS; Paul, 1966) is a 30-item measure in atrue/false format, assessing public-speaking fear. The PRCS has shown to have high internal con-sistency (Daly, 1978).

The Social Avoidance and Distress Scale (SADS; Watson & Friend, 1969) is a widely usedinstrument assessing the degree to which one expects to be negatively evaluated by others. It con-sists of 28 items that are rated as either ‘‘true’’ or ‘‘false’’.

The Behavioral Inhibition System/Behavioral Activation System Scale (BIS/BAS; Carver &White, 1994) is a 20-item scale assessing dispositional BIS/BAS sensitivities. The BIS/BAS scaleconsists of four subscales: Behavioral Inhibition, BAS Reward Responsiveness, BAS Drive, andBAS Fun Seeking. The BIS subscale measures the degree to which respondents expect to feel anx-iety when confronted with cues for punishment. Each item is rated on a four-point Likert scale


(1 = ‘‘very true for me’’ to 4 = ‘‘very false for me’’), with higher scores indicating higher sensitiv-ities. The BIS/BAS scales have shown to have good internal consistencies (Carver & White, 1994).For the purpose of the current study, only the 7-item BIS subscale was used.

The State Trait Anxiety Inventory (STAI-T; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs,1983) is a 20-item questionnaire with a 4-point Likert response format, ranging from 1 (‘‘almostnever’’) to 4 (‘‘almost always’’). It is commonly viewed as a global measure of anxiety and anxietyproneness, with higher scores indicating higher trait anxiety. It has shown adequate psychometricproperties and good internal consistency (Spielberger et al., 1983). The STAI-T has also been usedas a dispositional measure of the behavioral inhibition system. Zinbarg and Mohlman (1998)found STAI-T scores to be positively associated with the acquisition of punishment expectancyduring performance on a standard approach-avoidance discrimination task.

Distress ratings. Following the baseline phase and the speech condition, participants were askedto rate their maximum level of distress they experienced during the experimental condition on ascale from 0 (no distress) to 100 (extreme distress).

Physiological measures. Heart rate and skin conductance level were recorded continuously dur-ing the experiment with equipment by James Long Company (Caroga Lake, New York) and withthe data-acquisition program Snap-MasterTM for Windows. The biosignals were digitized at 512samples per second with a 31-channel A/D converter operating at a resolution of 12 bits andhaving an input range of �2.5 V to +2.5 V. Autonomic indicators included heart rate and skinconductance level. The psychophysiological channels were amplified by individual SA Instrumen-tation Bioamplifiers. The amplification rates and high-pass filter (HPF) and low-pass filter (LPF)settings were consistent with our other studies (e.g., Hofmann, Moscovitch, & Kim, in press) forboth the electrocardiogram (gain = 500, HPF = 0.1 Hz, LPF = 1000 Hz) and skin conductancelevel (gain = 0.1 V per micro-Siemens, HPF = none/DC, LPF = 10 Hz).

Heart rate data were analyzed using a computer program by James Long Company. R-waveswere automatically detected by the computer program and, subsequently, raw ECG and R-waveidentification marks were viewed graphically by the experimenter. The R-wave file was manuallycorrected to remove R-wave identification marks that were incorrectly specified (e.g., a movementartifact that the computer coded as an R-wave) or to score R-waves that were missed by the auto-mated detection. Heart rate was computed as number of R-waves per minute. Skin conductancelevel was derived by applying 0.5 vrms/30 Hz excitation voltage to a pair of electrodes that wereattached to the palmar surface of the middle phalanges of the third and fourth fingers of the non-dominant (left) hand. The recording signal was averaged over one second intervals and measuredin micro-Siemens. The amplifier output to measure SCL was a constant 0.5 vrms excitation signal.

2.3. Procedure

Eligible participants were individually scheduled for an appointment. They were asked to re-frain from consuming caffeine, alcohol, or any other substances, which could alter physiologicalresponses on the day of the experiment. Prior to the experiment, informed consent was obtainedand each participant was familiarized with the experimental premises.

After signing the informed consent form, participants were taken to a soundproof room wherea research assistant attached the electrodes. The plus and minus channel of the grounded electro-cardiogram was recorded through electrodes that were attached to either side of the participant’s


lowest ribs. Target skin areas were cleaned with alcohol wipes and allowed to dry. Skin conduc-tance level was measured using two Ag–AgCl electrodes filled with electroconductive gel that isisotonic to sweat. Participants washed their hands with water before the electrodes were attached.

After electrodes were attached, participants were instructed to carefully listen to a standardizedaudiotape that explained the purpose of the research and provided initial instructions for theexperimental procedure. Baseline levels of heart rate and skin conductance level were obtainedduring a 6-min resting period. Anxiety was induced through an impromptu speech task. Partici-pants were asked to give a 10-min speech on three unfamiliar topics (capital punishment, gun con-trol, and seat belt laws) in front of a video camera. They were told that a research team wouldlater evaluate the quality of their speech. Participants had no restrictions in what they couldsay and were given the option to speak on as many or as few topics as they wished. Furthermore,they were informed that they could end the task at any time.

3. Results

Prior to multivariate analyses, the data were inspected for univariate and multivariate outliers.Univariate outliers were conceptualized as scores that were three standard deviations above orbelow the mean. Multivariate outliers were inspected through Mahalanobis D2, using a p < .05criterion. Examination of the data revealed two univariate and two potential multivariate outliers,which were consequently excluded from the analyses, leading to a further reduction of the samplefrom 53 to 49. Assumptions of normality of sampling distributions, linearity, and homogeneity ofvariance–covariance matrices were also examined. Results of these multivariate assumptions weresatisfactory. The sample size for the following analyses ranged from 46 to 51 due to missing orincomplete self-report data on three subjects.

3.1. Self-report data

Descriptive statistics on the five self-report instruments are presented in Table 1. Means andstandard deviations are provided for the entire sample. Scores on the SADS and the PRCS werecomparable to those reported on clinical samples of socially phobic individuals (e.g., Boone et al.,1999; Hofmann, Newman, Ehlers, & Roth, 1995; McNeil, Vrana, Melamed, Cuthbert, & Lang,1993). Scores on the STAI for this sample were within the range of scores reported for individualswith panic disorder and social phobia (e.g., Hofmann et al., 1995; Oie, Evans, & Crook, 1990).The BIS and STAI showed a moderately high correlation, r(47) = .50, p < .0001.

Table 1Means (standard deviations) for self-report measures (Ns = 49–51)

Measure M (SD)

BIS 20.04 (2.90)PRCS 21.14 (5.31)SADS 12.55 (7.67)STAI-trait 43.98 (8.97)


3.2. Speech length

The average length of the speech was 7:54 min (SD: 2:33). The median was 9:53 min, and themode was 10 min; 50% of the sample spoke for the entire 10 min. The shortest duration was2:05 min. Participants who spoke for the entire time did not differ in the change scores (baselineto speech task) of the distress ratings, t(46) = 1.03, p = .31, heart rate, t(46) = .39, p = .69, andskin conductance level, t(46) = .77, p = .31. Furthermore, the length of the speech was not corre-lated with changes from baseline in subjective distress, r(48) = .05, p = .72, heart rate, r(48) = .06,p = .69, and skin conductance level, r(48) = �.13, p = .38.

3.3. Psychophysiological measures

A repeated measure MANOVA with the distress rating, heart rate, and skin conductance levelas dependent variables and the changes from baseline to the speech task as the within-subject fac-tor revealed a significant within-subject task effect, F(3,46) = 159.16, p = .0001, g2 = .91. Table 2presents the means (standard deviations) of participants’ heart rate, skin conductance level, anddistress rating at baseline and the speech condition. The univariate tests showed that the speechtask was successful in inducing subjective level of distress and physiological arousal. The subjec-tive distress ratings during the speech task ranged between 0 and 100 with a median of 55 and amode of 60.

Physiological reactivity was analyzed by employing difference scores contrasting the partici-pants’ initial baselines and their psychophysiological responses to the speech task. Results re-vealed a significant correlation between SCL reactivity and STAI-trait scores, (r(49) = 0.36,p < .02). The scatterplot of this relationship is shown in Fig. 1. None of the other correlationswere significant, including the correlations between SCL reactivity and BIS scores, r(47) = .13,p = .39, SCL reactivity and BAS scores, r(47) = �.12, p = .42, heart rate reactivity and STAIscores, r(49) = �.13, p = .38, heart rate reactivity and BIS scores, r(47) = .01, p = .93, and heartrate reactivity and BAS scores, r(47) = �.02, p = .89.

3.4. Prediction of physiological reactivity

Two hierarchical multiple regression analyses were conducted to examine whether behavioralinhibition, as measured by the BIS and the STAI, predicted changes in SCL and HR. The inde-pendent variables were centered scores on the BIS and the STAI in the first step, and their prod-uct-term in the second step. The predictor variables were entered in a block in a single step, using

Table 2Means (standard deviations) of psychophysiological data and distress ratings during baseline and speech task

Variables Baseline Speech F-values g2

Distress rating (0–100) 17.78 (18.86) 51.41 (24.93) 78.99*** 0.62Skin conductance level (lS) 14.71 (6.66) 16.34 (6.32) 49.01*** 0.51Heart rate (bpm) 68.37 (7.93) 82.76 (18.86) 262.14*** 0.85

*** p < .0001.

Change from Baseline to Speech Task in SCL

0 1 2 3 4 5

STA

I-tr

ait S

core

s

30

35

40

45

50

55

60

65

r (49) = .36, p < .02

Fig. 1. Scatterplot between STAI-trait scores and change scores in SCL from baseline to the speech task.


the Enter command of the statistical program (SPSS version 7.0 for Windows). The dependentvariables were the change from baseline to speech in (1) SCL and (2) HR.

Results from the first analysis showed that the linear combination of the BIS and the STAI wassignificantly related to SCL, F(3,43) = 2.98, p < .05. The STAI was a significant predictor of SCL,t(45) = 2.70, p < .02, while the BIS was not, t(45) = �.32, p > .7. No interaction effect was foundbetween the independent variables, F(1,43) = .02, p > .9 (Table 3).

Results from the second regression analysis using HR as the DV showed that neither the BISnor the STAI were significantly related to changes in HR from baseline to speech, F(3,45) = .73,p > .5. No interaction effect was found, p > .5 (Table 4).

Table 3Summary of hierarchical regression analysis for variables predicting SCL (N = 47)

Variable B SEB b

Step 1

BIS �.024 .080 �.048STAI-trait .076 .028 .437**

Step 2

BIS �.027 .084 �.054STAI-trait .077 .028 .439**

Interaction term �.001 .008 �.019

Note: R2 = .172 for Step 1; DR2 = .000 for Step 2 (ps < .05). * p < .05; ** p < .01.

Table 4Summary of hierarchical regression analysis for variables predicting heart rate (N = 47)

Variable B SEB b

Step 1

BIS .268 .355 .125STAI-trait �.146 .114 �.212

Step 2

BIS .268 .359 .125STAI-trait �.147 .116 �.214Interaction term .003 .041 .010

Note: R2 = .036 for Step 1; DR2 = .000 for Step 2.


Because the BIS and STAI showed a moderately high correlation, r(47) = .50, we examinedwhether multicollinearity imposed a significant threat for the interpretation of these analyses.The Variance Inflation Factor (VIF) is a commonly used indicator to measure the degree of mul-ticollinearity (Cohen, Cohen, West, & Aiken, 2003). VIF values of 10 or greater provides evidencefor serious multicollinearity (Cohen et al., 2003). The VIF of the regression analysis to predictSCL was 1.21; the VIF of the analysis to predict HR was 1.37. These results suggest that multi-collinearity did not present a significant problem for the analyses.

4. Discussion

The aim of the current study was to examine psychophysiological correlates associated with theactivation of the BIS in a speech-anxious sample. In line with Fowles’ (1980, 2000) hypothesis,SCL was a more sensitive indicator of anxiety than HR. However, only trait anxiety (as measuredwith the STAI), but not behavioral inhibition (as measured with the BIS/BAS), was associatedwith changes in SCL during a social stress task. Neither of the self-report measures predictedchanges in HR reactivity in response to the speech task. These results are in line with the notionthat high trait anxiety is associated with a more labile electrodermal system (Cruz & Larsen,1995). Moreover, the findings favor Fowles’ over Gray’s hypothesized correlates of trait anxiety.

Since behavioral inhibition and trait anxiety are thought to be closely related constructs, it wassurprising that scores on the BIS scale did not predict SCL. One possible explanation for thesefindings is that the content of the items that make up the BIS scale may be too restricted in whatthey measure. Carver and White (1994) developed this scale to measure BIS responsivity and vul-nerability to anxiety. The items represented in the scale focus on concerns about the anticipationof negative consequences (e.g., ‘‘I feel worried when I think that I have done poorly at some-thing.’’), but fail to include other aspects of the BIS such as responses to extreme novelty, innatefears, and behavioral responses to potential punishment (Heubeck, Wilkinson, & Cologon, 1998).Furthermore, Carver and White (1994) purposefully did not include items reflecting general affec-tive tone, which seems to be an important component of temperament. The STAI, on the otherhand, measures affective tone and anxiety proneness and, therefore, may tap into the discreteaffective components associated with the activation of the BIS. Thus, the STAI may be more


sensitive to the affective and perhaps also the physiological aspects of the BIS. The 7-item BISscale, in its current version, may not adequately capture all aspects of the BIS. In fact, the possiblerange of scores on the BIS scale is from 0 to 28. Scores for a normative, college-age sample havebeen reported to be between 19 and 21 (Caseras, Avila, & Torrubia, 2003; Gomez & Gomez, 2002;Jorm et al., 1999). As a result of the limited number of items and the content that they measure,the BIS scale seems to have poor sensitivity.

The participants in our study had been selected for their heightened speech anxiety, which wascorroborated by their elevated scores on self-report measures of social anxiety and trait anxiety.Their scores on these instruments were in the range of clinical samples (Boone et al., 1999; Hof-mann et al., 1995; McNeil et al., 1993). However, participants’ subjective distress during thespeech test was only in the moderate range. Similarly, participants scored within the normativerange on the BIS scale. Finally, we found that subjective measures of trait anxiety, but not ofbehavioral inhibition predicted SCL, but not HR reactivity. Consistent with other studies (e.g.,Croft, Gonsalvez, Gander, Lechem, & Barry, 2004), our findings emphasize the need to accountfor EDA and cardiac activity independently in studies that measure autonomic arousal of socialperformance anxiety. Moreover, the study raises important questions about the validity of the BISscale, the operational definition of the construct, and the differentiation between this constructand trait anxiety. Future studies will need to further examine the differences between trait anxietyand behavioral inhibition, and explore the role of BAS in the relationship between BIS, trait anx-iety, and autonomic arousal.

There are several limitations to this study. First, the sample consisted of only male college stu-dents. Therefore, generalizability of these findings is limited. Second, it remains unclear what therole of the behavioral activation system is. The aim of this study was to test some predictions de-rived from the theories by Fowles and Gray, neither of which explicate the role of the BAS in theanxiety response. Therefore, we limited our analyses to the BIS and trait anxiety as predictors ofautonomic correlates of state anxiety. Third, our experimental paradigm did not include incen-tive-related cues to examine Fowles’ assertion about the relationship between HR and theBAS. Thus, we are unable to draw any conclusions about the implications of our findings withrespect to that component of Fowles’ theory. The incorporation of incentive cues would havebeen useful in clarifying this hypothesis. Fourth, a 10-min epoch is relatively long to aggregatephysiological measures. Although this not an unusual method for measuring autonomic arousalduring a public speech test (e.g., Boone et al., 1999; Hofmann et al., 1995), it s possible that habit-uation effects influenced some of our results. Finally, our measure of electrodermal activity didnot include skin conductance response.

Despite these limitations, our findings suggest that SCL is associated with STAI-trait but notBIS scores, and that HR is not associated with either of these variables. These results emphasizethe importance of examining trait anxiety when recording SCL during social stress.

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anxiety goes under the skin: behavioral inhibition, anxiety, and autonomic arousal in speech-anxious...

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