Implicit associations between anxiety-related symptoms ... - CiteSeerX

Download PDF
47 downloads 0 Views 129KB Size Report
Comment
sensitive individuals' risk for panic disorder and hypochondriasis. The present study employed the Extrinsic Affective Simon Task (EAST) recently developed by ...
COGNITION AND EMOTION 2006, 20 (2), 295±308

Implicit associations between anxiety-related symptoms and catastrophic consequences in high anxiety sensitive individuals Marie-joseÂe Lefaivre Dalhousie University, Halifax, Nova Scotia, Canada

Margo C. Watt Dalhousie University, Halifax and St. Francis Xavier University, Antigonish, Nova Scotia, Canada

Sherry H. Stewart and Kristi D. Wright Dalhousie University, Nova Scotia, Canada Anxiety sensitivity refers to the fear of anxiety-related physical sensations arising from beliefs that these sensations have harmful consequences (Reiss & McNally, 1985). The present study examined whether individuals with high (vs. low) anxiety sensitivity show stronger implicit associations in memory between anxiety-related symptoms, as opposed to neutral body parts, and harmful, as compared to harmless, consequences. A total of 22 undergraduate students (14 F, 8 M) completed the Extrinsic Affective Simon Task (EAST; De Houwer, 2003). Results indicated that high anxiety sensitive individuals (n = 10) tended to implicitly associate harmful consequences with anxiety-related symptoms. Their performance was significantly faster on trials where target words related to anxiety symptoms were mapped on to the same response key as harmful consequences. No significant difference in performance was found for low anxiety sensitive individuals (n = 12) or when target words were body parts unlikely related to diseases. Between-group differences persisted after controlling for trait anxiety and history of panic attacks, but not when illness-related beliefs were introduced as a covariate. Identifying this implicit association bias provides additional empirical support for the concept of anxiety sensitivity.

Correspondence should be addressed to Dr Margo C. Watt, Department of Psychology, St. Francis Xavier University, P.O. Box 5000, Antigonish, Nova Scotia B2G 2W5, Canada; e-mail: [email protected] The authors would like to thank members of Dr Ray Klein's laboratory at Dalhousie University (particularly Patti Devlin) for their assistance with the computer programming and Tara MacDonald at St. Francis Xavier University for her assistance with data collection. # 2006 Psychology Press Ltd http://www.psypress.com/cogemotion DOI:10.1080/02699930500336466

296

LEFAIVRE ET AL.

Anxiety sensitivity is an individual difference factor that refers to the fear of anxiety-related physical sensations. This fear arises from beliefs that anxietyrelated sensations have harmful somatic, psychological, or social consequences (Reiss & McNally, 1985). Whereas individuals with low anxiety sensitivity recognise that bodily sensations associated with anxiety are unpleasant but transient and harmless, individuals with high anxiety sensitivity fear these symptoms may have dire consequences (McNally, 1999a). Anxiety sensitivity, as measured by the Anxiety Sensitivity Index (ASI; Peterson & Reiss, 1992), has demonstrated incremental validity above and beyond measures of trait anxiety in discriminating between panic disorder and generalised anxiety disorder (e.g., Taylor, Koch, & McNally, 1992), as well as in predicting fear and panic (Peterson & Reiss, 1992). Anxiety sensitivity has been shown to be an important risk factor for the development and maintenance of panic disorder (see review by Cox, Borger, & Enns, 1999), and hypochondriasis (Otto, Demopulos, McLean, Pollack, & Fava, 1998; Stewart & Watt, 2000). Information-processing models consider anxiety disorders to result from maladaptive schemas in memory misguiding information processing (Teachman & Woody, 2003; for a review, see Coles & Heimberg, 2002). These models predict that anxiety-congruent information will be subject to attentional, processing, and retrieval biases, which contribute to the development and maintenance of anxiety disorders (Foa & Kozak, 1986; for a review, see Coles & Heimberg, 2002). For example, Beck and Clark (1997) propose a three-stage model to explain the relative roles of explicit (conscious) and implicit (automatic) information-processing in the etiology of pathological anxiety. Whereas most research has focused on the third stage of Beck and Clark's model (i.e., self-reported cognitions), more recently, researchers have started to explore the earlier stages; stages not accessible to conscious processing (see McNally, 1995). In order to examine the more automatic and implicit stages of informationprocessing, researchers generally must employ tasks that measure, in milliseconds, automatic actions, or judgements that do not, by definition, require conscious awareness on the participant's part (see Egloff & Schmukle, 2002; McNally, 2001). These types of tasks provide complementary information to explicit research designs (e.g., self-report, free-recall test) interested in the more reflective and conscious processing stage of Beck and Clark's (1997) model by providing insight on earlier information-processing stages. Studies employing implicit cognition tasks have demonstrated that, as opposed to controls, clinically diagnosed anxiety disorder patients have a tendency to show selective processing biases favouring information relevant to their anxiety-related concerns (see reviews in Coles & Heimberg, 2002; McNally, 1999b; Williams, Mathews, & MacLeod, 1996). Other studies have examined the relationship between anxiety sensitivity and informationprocessing biases before the onset of anxiety problems to determine if anxiety

ANXIETY SENSITIVITY AND IMPLICIT BIAS

297

sensitivity could be considered a cognitive risk factor for anxiety disorders (Keogh, Dillon, Georgiou, & Hunt, 2001; Lees, Mogg, & Bradley, 2005; McCabe, 1999; McNally, Horning, Hoffman, & Han, 1999; Stewart, Conrod, Gignac, & Pihl, 1998). It remains unclear whether cognitive biases precede or follow the development of an anxiety disorder given the limited amount of research on nonclinical samples to date (see McNally et al., 1999). The above studies have varied by sample and methodology. Moreover, none have used association-type tasks thereby preventing the examination of automatic associative processes as a function of anxiety sensitivity levels. By definition, high anxiety sensitive individuals should be differentiated from low anxiety sensitive individuals not simply by their fear of anxiety-related sensations but also by their beliefs about the catastrophic consequences of experiencing these sensations. Consequently, the objective of the present study was to extend previous findings by examining whether high anxiety sensitive individuals tend to catastrophise the consequences of their physical symptoms. More precisely, we were interested in whether there is a stronger implicit association (vs. dissociation) between physical symptoms and harmful outcomes (vs. harmless outcomes) concepts in memory for high anxiety sensitive individuals as compared to low anxiety sensitive individuals. Identifying the presence of an implicit association bias between anxiety-related sensations and negative outcomes among high anxiety sensitive individuals using a novel research task could provide additional empirical support for the concept of anxiety sensitivity, as well as explicating possible cognitive mechanisms involved in high anxiety sensitive individuals' risk for panic disorder and hypochondriasis. The present study employed the Extrinsic Affective Simon Task (EAST) recently developed by De Houwer (2003). The EAST is a modified version of the popular Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) that measures participants' reaction times (RTs) when categorising stimuli by pressing either a left or a right computer key. The underlying assumption that forms the basis of tasks, such as the EAST or IAT, is that a relationship exists between cognitive structures and automaticity (see Teachman & Woody, 2003). The EAST is therefore seen as a measure of cognitive structure or automatic associations in memory based on RTs. The EAST was chosen for the present study because it circumvents some of the problems associated with the IAT (see De Houwer, 2003). In the present study, individuals were asked to categorise body parts (e.g., abdomen, elbow) and anxiety-related sensations (e.g., breathless, dizzy) based on their colour, as well as to categorise positive (e.g., benign, healthy) and negative (e.g., faint, stroke) health outcomes, presented in white, based on their valence (see details in the Method section). As suggested by Palfai and Ostafin (2003), we selected words representing body parts unlikely to be associated with negative physical outcomes (e.g., diseases) as control targets, because similar evaluative responses would be expected across individuals therefore providing, hopefully, a stable contrast.

298

LEFAIVRE ET AL.

It was hypothesised that, if a tendency to catastrophise anxiety-related physical sensations existed among the high anxiety sensitive participants, their performance would be superior on trials where they needed to select an extrinsically negative (vs. positive) response key for coloured target words that were anxiety-related sensations. It was also expected that this performance facilitation for targets by pairing with the extrinsically negative response key would be specific to high anxiety sensitive (as opposed to low anxiety sensitive) individuals, and to trials involving anxiety-related sensations (as opposed to body parts) as target items.

METHOD Participants The participants were 22 (14 F, 8 M; mean age = 18.5, SD = 0.80) undergraduate students from St. Francis Xavier University who received course credit for participating in the study. Participants were randomly selected and assigned to groups according to their scores on the Anxiety Sensitivity Index (ASI; Peterson & Reiss, 1992) administered during a mass in-class screening. The high and low anxiety sensitivity groups were composed of participants scoring at least one standard deviation above (> 17.9 + 8.7) or below (< 17.978.7) the ASI mass screening sample mean, respectively (see Peterson & Reiss, 1992; Watt, Stewart, & Cox, 1998). The results of independent-sample t-tests and chi-square analyses showed that the two groups did not significantly differ in terms of age, gender ratio, level of education in years, or number of participants who had ever experienced a spontaneous panic attack but they did differ significantly in trait anxiety as assessed by the State-Trait Anxiety Inventory-Trait Subscale (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983) and health anxiety as assessed by the Illness Attitudes Scale (Kellner, 1987). The descriptive statistics for both groups are presented in Table 1. Participants had normal or corrected-to-normal vision. Students who were colour-blind and/or students whose language was not English were excluded from the study given that the EAST is a cognitive task that requires the rapid distinction between two similar colours (i.e., green and blue) and the rapid categorisation of English words based on their semantic meaning.

Measures Demographic information. Age, gender, and level of education of the participants were collected with a researcher-compiled demographic information questionnaire.

ANXIETY SENSITIVITY AND IMPLICIT BIAS

299

TABLE 1 Means (and standard deviations) comparing the two anxiety sensitivity groups

Age Gender Level of education ASI-Total STAI-T IAS-Total PAQ (% spontaneous panic reporters)

LAS (n = 12)

HAS (n = 10)

18.42 (0.9) 5 M; 7 F 14.5 (1.0) 7.0 (1.8) 36.5 (8.6) 28.9 (12.6) 2 (17%)

18.6 (0.7) 3 M; 7 F 14.2 (0.4) 32.9 (2.8)*** 46.0 (10.7)* 43.3 (15.4)* 2 (20%)

LAS, low anxiety sensitive; HAS, high anxiety sensitive; STAI-T, State Trait Anxiety Inventory-Trait Scale; ASI, Anxiety Sensitivity Index; PAQ, Panic Attack Questionnaire; IAS, Illness Attitudes Scale. * p < .05; ** p < .01; *** p < .001.

Anxiety Sensitivity Index (ASI; Peterson & Reiss, 1992). Using 5-point Likert-type scales, the ASI assesses the respondent's level of agreement/ disagreement with 16 statements relating to the beliefs that anxiety sensations are associated with physical, social, or psychological consequences. Psychometric information concerning the excellent reliability and validity of the measure for clinical and nonclinical populations is available in Peterson and Reiss (1992). Illness Attitudes Scale (IAS; Kellner, 1987). This 29-item self-report scale is divided into nine subscales that assess fears, behaviours, beliefs, and effects associated with hypochondriasis (see Stewart & Watt, 2000), as well as psychopathology associated with abnormal illness behaviours. The IAS has been shown to have good test-retest reliability (see Fava, Kellner, Zielzny, & Grandi, 1988; Kellner, 1987), acceptable internal reliability (see Stewart & Watt, 2000; Wise & Sheridan, 2001), good concurrent validity (Kellner, Abbot, Winslow, & Pathak, 1987), and convergent validity (Speckens, Spinhoven, Sloekers, Bolk, & van Hemert, 1996). Panic Attack Questionnaire±Revised (PAQ-R; Cox, Norton, & Swinson, 1992). The PAQ-R provides a description of a panic attack as defined in the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition-Revised (American Psychiatric Association, 1987) and asks participants to indicate whether they have ever experienced such an attack. The experience of at least one spontaneous (``out of the blue'') panic attack was used to assess panic history.

300

LEFAIVRE ET AL.

State-Trait Anxiety Inventory-Trait Subscale (STAI-T; Spielberger et al., 1983). This self-report subscale assesses participants' general tendency to react anxiously to potentially threatening stimuli. Participants are asked to rate how they generally feel about 20 statements using 4-point Likert-type scales. The STAI manual (Spielberger et al., 1983) provides information about the good psychometric proprieties of this scale. EAST Stimulus Materials. Five anxiety-related symptoms (i.e., breathless, dizzy, numbness, palpitation, shaky) were selected from word lists previously used in anxiety sensitivity studies (McCabe, 1999; McNally et al., 1999). Five negative health outcomes matching these particular symptoms (i.e., suffocate, faint, stroke, heart attack, seizure) were then selected in order to reflect the anticipated negative consequences of experiencing such symptoms. Subsequently, five body parts identified as unlikely related to diseases (i.e., abdomen, ankle, elbow, finger, nose) and five positive health outcomes (e.g., benign, healthy, innocuous, resilient, thriving) were also selected to complete the four stimuli categories for the EAST. The results of two one-way analyses of variance (ANOVA) indicated that the four word groups did not differ in average word length, F(3, 16) = 1.661, ns, and average word frequency, F(3, 16) = 0.828, ns. The average word frequency was calculated using a popular Internet search engine (www.google.com; see Blair, Urland, & Ma, 2003). EAST apparatus. The EAST (De Houwer, 2003) was conducted using the SuperLab software programmed on an iMac computer running in OS 9.1. Participants were seated in front of the computer at a distance of approximately 40 cm from the 14-inch screen. The words' letters were around 7 mm high and 5 mm wide and were presented on a black background. The descriptors were presented in white using the default Adobe Photoshop values. The target words were presented in either blue or green. The red, blue, and green settings used to create the blue (0,117,97) and the green (0,97,117) produced two colours that were quite similar. Participants used either the ``A'' key or ``L'' key of the (QWERTY) keyboard to categorise the stimuli. Participants' response times, defined as the time between the onset of a word and the first key press, were measured using the highly accurate (< 1 ms) Timer-1 included in the SuperLab software.

Procedure After reading and signing the Consent Form, the participants completed the EAST and the questionnaires individually. The EAST included several trials during which participants were presented with words one by one, and were asked to classify these words based on either their meaning or colour. Participants had to categorise white words (i.e., descriptors) according to the word's

ANXIETY SENSITIVITY AND IMPLICIT BIAS

301

valence (i.e., positive or negative). Participants were told to press the GOOD key when words referred to something positive (e.g., healthy, innocuous) or the BAD key if the word was something negative (e.g., stroke, faint). Participants also had to categorise coloured words (i.e., targets) according to their colour (i.e., blue vs. green) regardless of the valence. The target words were either anxiety-related symptoms or body parts unlikely to be related to disease. On the trials of the test blocks, one descriptor and one colour were mapped on to one response key (e.g., A = positive and blue) and the other descriptor and the other colour were mapped on to the other response key (e.g., L = negative and green). Consequently, the targets become extrinsically related to the descriptors' valence because of the task instructions (see De Houwer, 2003; see also Appendix). The key mapping assignments for the descriptors and the targets were manipulated in an orthogonal way to control for possible location-effect between participants. The participants were told to respond as quickly as possible without making any errors. A red cross appearing on the screen informed participants when they had made an incorrect response. The EAST took about 15 minutes to complete and included two practice blocks of 20 trials followed by four test blocks of 30 trials. Participants were presented the same stimuli during the practice and test blocks (see De Houwer, 2003). The first practice block consisted of white words only during which each 10 stimuli were presented twice in a random order. The random presentation of the 10 coloured words, once in each colour, was the second practice block. The four test blocks of 30 trials followed during which each of the 10 target words were presented once in each colour and each of the 10 descriptor words were presented once in white. The words were all presented in random order with the restriction that the same word could not be presented on two or more consecutive trials and that the required response could not be the same on four or more consecutive trials. At each trial, the presentation of the word was preceded by a white fixation symbol of 350 ms. The word remained on the screen until the participants pressed a response key. The intertrial interval was 250 ms. Prior to starting each block, participants were presented with instructions reminding them what key to press for which type of stimuli.

RESULTS Results of the evaluation of assumptions indicated a violation of normality, which required log-transformation of data, but satisfactory homogeneity of variance-covariance matrices. The analyses were performed using the mean logtransformed RTs of the test trials where a correct response was made for coloured words only. The RTs of trials with an incorrect response were excluded from the analyses as were trials with a RT below 300 ms or above 3000 ms (see Brendl, Markman, & Messner, 2001). The mean log-transformed RT was calculated for the four types of trials: (1) body parts extrinsically mapped on to a

302

LEFAIVRE ET AL. TABLE 2 Log-transformed means (and standards deviations) of the trial types for both anxiety sensitivity groups Trial type Body part + Positive Outcome Body part + Negative Outcome Symptom + Positive Outcome Symptom + Negative Outcome

LAS (n = 12) 2.829 2.924 2.827 2.839

(0.112) (0.091) (0.102) (0.080)

HAS (n = 10) 2.847 2.934 2.887 2.857

(0.060) (0.088) (0.108)a (0.129)a

LAS, low anxiety sensitive; HAS, high anxiety sensitive. a Significant difference between these two trial types for the HAS group at p < .05.

positive health outcome response key; (2) body parts extrinsically mapped on to a negative health outcome response key; (3) anxiety-related symptoms extrinsically mapped on to a positive health outcome response key; (4) anxiety-related symptoms extrinsically mapped on to a negative health outcome response key. The overall untransformed mean of these fours trial types for both anxiety sensitivity groups combined was 760.4 (SD = 200.2). The log-transformed means of the four trial types for each anxiety sensitivity group are presented in Table 2. An independent-samples t-test was conducted to evaluate the usefulness of the selected control categories (i.e., body parts identified as unlikely to be related to diseases and positive health outcomes). Results indicated no significant difference in RT between anxiety sensitivity groups when target words referring to body parts were mapped on to the same response key as the white words referring to positive health outcome, t(20) = 70.47, ns. The absence of a significant difference suggested that these control categories provided a stable contrast from which a comparison could be made with the trials of main interest (i.e., trials wherein the participants needed to select extrinsically negative responses for coloured words that were anxiety-related symptoms). The error rates and deleted trials represented, on average, 5.8% and 1.3% of all trials, respectively. Two 2 6 2 6 2 (anxiety sensitivity group 6 target words 6 health outcome responses) ANOVA with repeated measures was conducted on the error rate and deleted trials data. No significant effects were revealed. The internal consistency of the EAST was assessed using 40 RT differences for targets paired with negative vs. positive outcomes. Error rates and deleted trials were treated as missing values and were replaced prior to alpha calculation. Cronbach's alpha indicated adequate reliability of .63. A 2 6 2 6 2 ANOVA with repeated measures was conducted to evaluate the effects of the anxiety sensitivity groups (high vs. low), target words (body

ANXIETY SENSITIVITY AND IMPLICIT BIAS

303

parts vs. anxiety symptoms), and extrinsic health outcome responses (positive vs. negative) on RTs. Results of the ANOVA indicated a significant threeway interaction, F(1, 20) = 10.07, p < .005, partial Z2 = .34. Consequently, two 2 6 2 ANOVAs were conducted to evaluate the effects of target words and extrinsic health outcome responses on RT for each anxiety sensitivity group. Results of the ANOVA for the low anxiety sensitivity group found no significant main effects for target words, F(1, 11) = 0.38, ns, or health outcomes, F(1, 11) = 0.03, ns, nor a significant interaction, F(1, 11) = 1.69, ns. These results suggested that participants in the low anxiety sensitivity group did not differ significantly in their RTs whether the target words (i.e., body parts vs. anxiety symptoms) were extrinsically mapped on to the same response key as positive or negative health outcomes. The results of the ANOVA for the high anxiety sensitivity group found no significant main effects for target words, F(1, 9) = 1.55, ns, or health outcomes, F(1, 9) = 1.07, ns. However, the results indicated a significant target words 6 health outcome interaction, F(1, 9) = 20.50, p < .001, partial Z2 = .70. To further examine this significant two-way interaction for the high anxiety sensitivity group, post hoc analyses were performed. Given that the specific comparison of interest was the performance of high anxiety sensitive individuals on trials where they needed to select an extrinsically negative (vs. positive) response for words that were anxiety-related (vs. body parts), paired ttests with Dunnett's correction was used (Tabachnick & Fidell, 2001). This approach revealed that high anxiety sensitive participants responded significantly faster when anxiety-related symptoms were extrinsically mapped onto the same response key as negative health outcomes vs. positive outcomes, t(9) = 2.28, p < .05. There were no significant differences in participants' responding to the pairings of body parts with either negative or positive outcomes. These findings support the contention that there exists a stronger implicit association (vs. dissociation) between anxiety-related physical symptoms and harmful (vs. harmless) concepts among high anxiety sensitive individuals. The three-way interaction, F(1, 19) = 4.89, p < .05, and the contrast of interest, t(9) = 1.86, p < .05 remained significant when trait anxiety as assessed by the STAI-T (Spielberger et al., 1983) was entered as a covariate. When history of panic attacks (no spontaneous panic attack vs. at least one spontaneous panic attack) was entered as a covariate, the three-way interaction, F(1, 19) = 9.53, p < .01 and the contrast of interest, t(9) = 2.22, p < .05, also remained significant. The three-way interaction remains significant when hypochondriacal concerns, as assessed by the IAS (Kellner, 1987), was entered as a covariate, F(1, 19) = 7.09, p < .05, but the contrast of interest becomes only marginally significant, t(9) = 1.78, p < .10. The three-way interaction, however, is only marginally significant when the illness-related beliefs factor is introduced by itself as the covariate, F(1, 19) = 4.248, p = .053.

304

LEFAIVRE ET AL.

DISCUSSION The present experiment was designed to investigate whether high anxiety sensitive individuals tend to catastrophise the consequences of anxiety-related symptoms based on cognitive implicit associations. This was examined with the EAST (De Houwer, 2003), an implicit measure of cognitive structure or automatic associations in memory based on RTs. Participants in the present study were asked to categorise white descriptor words (i.e., harmless and harmful health outcomes) based on their valence (i.e., positive vs. negative), as well as to categorise coloured target words (i.e., body parts unlikely related to diseases and anxiety-related symptoms) based on their colour (i.e., blue or green) while ignoring their valence. Consistent with information-processing models of anxiety (e.g., Beck & Clark, 1997), results indicated that high (vs. low) anxiety sensitive individuals tend to implicitly associate anxiety-related symptoms with negative consequences. High anxiety sensitive individuals responded significantly faster on trials where anxiety-related target words were mapped on to the same response key as harmful (vs. harmless) health outcomes. High anxiety sensitive individuals did not show the same tendency for associating body parts with negative outcomes on the EAST and none of the RTs for the different pairings of the target words and the health outcomes were significantly faster for the low anxiety sensitivity group. The between-group differences persisted after controlling for trait anxiety and history of panic attacks; however, results suggested that illness-related beliefs may be contributing to this implicit bias of associating anxiety-related symptoms with negative outcomes in high anxiety sensitive individuals. This could be due to the fact that illness-related beliefs factor of the IAS (Kellner, 1987) is the more closely linked to the DSM-IV's (American Psychiatric Association, 2001) concept of hypochondriasis (see Stewart & Watt, 2000). This factor is also better at discriminating between parents with hypochondriasis diagnosis vs. controls than other IAS factors (see Kellner et al., 1987). Based on the underlying assumption of the EAST, these results suggest that the performance of high AS individuals on trials where they needed to make an negative extrinsic response choice for anxiety-related symptoms (i.e., anxietyrelated target words were mapped on to the same response key as harmful outcomes) was superior as compared to other trials because this response choice corresponded more closely to their associations in memory. Thus, anxiety sensitivity could be a cognitive risk factor for anxiety disorders (see Keogh et al., 2001; McCabe, 1999; McNally et al., 1999; Stewart et al., 1998). Identifying this implicit association bias provides additional empirical support for the concept of anxiety sensitivity. Indeed, the use of the EAST in the present study extends the work of previous studies investigating cognitive biases of threat in nonclinical populations (e.g., Keogh et al., 2001; McCabe, 1999; McNally et al., 1999; Stewart et al., 1998) by distinguishing between the

ANXIETY SENSITIVITY AND IMPLICIT BIAS

305

anxiety-related symptoms (e.g., breathless) and their possible consequences (e.g., suffocate). This distinction is important because the results of the present study suggest that, consistent with the anxiety sensitivity definition, high anxiety sensitive individuals can be differentiated from low anxiety sensitive persons not simply by their fear of anxiety-related symptoms but also their beliefs about the consequences of experiencing such symptoms. This study, however, only investigated the relationship between anxiety-related symptoms and their possible physical consequences. It did not examine whether this tendency to catastrophise the consequences of anxiety-related sensations would be observed if participants had also been presented with possible psychological and/or social consequences of experiencing those symptoms. Consequently, the results might only be specific to physical concerns associated with high anxiety sensitivity and should not be generalised to psychological and social concerns associated with anxiety-related symptoms. It is also possible that the significant results are simply an artefact of the small sample, although this seems unlikely given that a predicted three-way interaction emerging by chance is highly unlikely. In any event, these results require replication with an independent sample to ensure that they are reliable. The present study is considered a necessary first step in addressing a related research question as to whether it is possible to differentiate between high anxiety sensitivity individuals and individuals with strong hyponchondriacal tendencies on the basis of their implicit associations between arousal-reactive (vs. arousal-nonreactive) symptoms and immediate (vs. delayed) consequences (e.g., Stewart & Watt, 2000). In this case, it could be hypothesised that stronger implicit associations between arousal-reactive symptoms (e.g., heart palpitations) and immediate consequences (e.g., heart attack) would be found in high anxiety sensitive individuals, whereas individuals with more hyponchondriacal tendencies would also show stronger implicit associations between arousalnonreactive symptoms (e.g., lump) and delayed consequences (e.g., cancer). The sample size of the present study did not allow for the direct comparison of gender differences in anxiety-related implicit associations. However, previous studies suggest that females, compared to males, tend to score higher on the physical concerns factor of the ASI (e.g., Stewart, Taylor, & Baker, 1997). Another study by Stewart et al. (1998) found that, when completing a modifiedStroop colour-naming task, high anxiety sensitive women demonstrated more interference with physical threat cues as compared to their low anxiety sensitive counterparts, whereas high anxiety sensitive men displayed more interference for psychological/social threat as compared to low anxiety sensitive men. Moreover, samples employed in previous studies (e.g., Keogh et al., 2001; McNally et al., 1999) have been predominantly female. Consequently, future research should consider investigating whether high anxiety sensitive women would show a stronger implicit association between arousal-reactive symptoms and negative health outcomes than high anxiety sensitive men. Future research

306

LEFAIVRE ET AL.

also should consider including a measure of depression given the relationship between anxiety sensitivity and depression (see Taylor, Koch, & Woody, 1996) and the evidence that depressed individuals tend to show a memory bias for negative material (Ruiz-Caballero & GonzaÂlez, 1997). In conclusion, the findings of the present study might eventually lead to important clinical implications. Because the cognitive biases in high anxiety sensitive individuals appear to be operating at an automatic level (i.e., not under intentional control), treatment approaches could benefit from consulting studies in the field of social cognition (e.g., Dasgupta & Greenwald, 2001) and the clinical realm (e.g., Teachman & Woody, 2003) that have demonstrated that automatic associations are sensitive to intervention. Similarly, it has been suggested that measures of automatic associations could be useful intervention tools (Teachman & Woody, 2004). Finally measures, such as the EAST, might also be useful as outcome assessment tools to assess the efficacy of treatment in altering implicit associations in memory (e.g., Teachman & Woody, 2003). Manuscript received 1 December 2004 Revised manuscript received 17 August 2005

REFERENCES American Psychiatric Association. (1987). Diagnostic and Statistical manual of mental disorders: DSM-III-R (3rd rev. ed.). Washington, DC: Author. Beck, A. T., & Clark, D. A. (1997). An information processing model of anxiety: Automatic and strategic processes. Behaviour Research and Therapy, 35, 49±58. Blair, I. V., Urland, G. R., & Ma, J. E. (2003). Using internet search engines to estimate word frequency. Behavior Research Methods, Instruments, and Computers, 34, 286±290. Brendl, C. M., Markman, A. B., & Messner, C. (2001). How do indirect measures of evaluation work? Evaluating the influence of prejudice in the Implicit Association Test. Journal of Personality and Social Psychology, 81, 760±773. Coles, M. E., & Heimberg, R. G. (2002). Memory biases in the anxiety disorders: Current status. Clinical Psychology Review, 22, 587±627. Cox, B. J., Borger, S. C., & Enns, M. W. (1999). Anxiety sensitivity and emotional disorders: Psychometric studies and their theoretical implications. In S. Taylor (Ed.), Anxiety sensitivity: Theory, research and treatment of the fear of anxiety (pp.115±148). Mahwah, NJ: Erlbaum. Cox, B. J., Norton, G. R, & Swinton, R.P. (1992). The panic attack questionnaireÐRevised. Unpublished scale, Centre for Addiction and Mental Health, Toronto, Canada. Dasgupta, N., & Greenwald, A. G. (2001). On the malleability of automatic attitudes: Combating automatic prejudice with images of admired and disliked individuals. Journal of Personality and Social Psychology, 81, 800±814. De Houwer, J. (2003). The extrinsic affective simon task. Experimental Psychology, 50, 77±85. Egloff, B., & Schmukle, S. C. (2002). Predictive validity of an implicit association test for assessing anxiety. Journal of Personality and Social Psychology, 83, 1441±1455. Fava, G. A., Kellner, R., Zielezny, M., & Grandi, S. (1988). Hypochondriacal fears and beliefs in agoraphobia. Journal of Affective Disorders, 14, 239±244. Foa, E. B., & Kozak, M. J. (1986). Emotional processing of fear: Exposure to corrective information. Psychology Bulletin, 99, 20±35.

ANXIETY SENSITIVITY AND IMPLICIT BIAS

307

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74, 1464±1480. Kellner, R. (1987). Abridged manual of the illness attitudes scale. Department of Psychiatry, School of Medicine, University of New Mexico, USA. Kellner, R., Abbott, P., Winslow, W. W., & Pathak, D. (1987). Fears, beliefs, and attitudes in DSMIII hypochondriasis. Journal of Nervous and Mental Disease, 175, 20±25. Keogh, E., Dillon, C., Georgiou, G., & Hunt, C. (2001). Selective attentional biases for physical threat in physical anxiety sensitivity. Anxiety Disorders, 15, 299±315. Lees, A., Mogg, K., & Bradley, B.P. (2005). Health anxiety, anxiety sensitivity and attentional biases for pictorial and linguistic health-threat cues. Cognition and Emotion, 19, 453±462. McCabe, R. E. (1999). Implicit and explicit memory for threat words in high- and low-anxietysensitive participants. Cognitive Therapy and Research, 23, 21±38. McNally, R. J. (1995). Automaticity and the anxiety disorders. Behaviour Research and Therapy, 33, 747±754. McNally, R. J. (1999a). Theoretical approaches to the fear of anxiety. In S. Taylor (Ed.), Anxiety sensitivity: Theory, research and treatment of the fear of anxiety (pp. 3±16). Mahwah, NJ: Erlbaum. McNally, R. J. (1999b). Anxiety sensitivity and information-processing biases for threat. In S. Taylor (Ed.), Anxiety sensitivity: Theory, research and treatment of the fear of anxiety (pp. 183±197). Mahwah, NJ: Erlbaum. McNally, R. J. (2001). On the scientific status of cognitive appraisal models of anxiety disorder. Behaviour Research and Therapy, 39, 513±512. McNally, R. J., Horning, C. D., Hoffman, E. C., & Han, E. M. (1999). Anxiety sensitivity and cognitive biases of threat. Behavior Therapy, 30, 51±61. Otto, M. W., Demopulos, C. M., McLean, N. E., Pollack, M. H., & Fava, M. (1998). Additional findings on the association between anxiety sensitivity and hypochondriacal concerns: Examination of patients with major depression. Journal of Anxiety Disorders, 12, 225±232. Palfai, T. P., & Ostafin, B. D. (2003). Alcohol-related motivational tendencies in hazardous drinkers: Assessing implicit response tendencies using the modified-IAT. Behaviour Research and Therapy, 41, 1149±1162. Peterson, R. A., & Reiss, S. (1992). Anxiety sensitivity index manual (2nd ed.). Worthington, OH: International Diagnostic Systems. Reiss, S., & McNally, R. J. (1985). The expectancy model of fear. In S. Reiss & R. R. Bootzin (Eds.), Theoretical issues in behavior therapy (pp. 107±122). New York: Academic Press. Ruiz-Caballero, J. A., & GonzaÂlez, P. (1997). Effects of level of processing on implicit and explicit memory in depressed mood. Motivation and Emotion, 21, 195±209. Speckens, A. E., Spinhoven, P., Sloekers, P. P. A., Bolk, J. H., & van Hemert, A. M. (1996). A validation study of the Whitley index, the Illness Attitude Scales, and the Somatosensory Amplification Scale in general medical and general practice patients. Journal of Psychosomatic Research, 40, 95±104. Spielberger, C., Gorsuch, R., Lushene, R., Vagg, P., & Jacobs, G. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press. Stewart, S. H., Conrod, P. J., Gignac, M. L., & Pihl, R. O. (1998). Selective processing biases in anxiety-sensitive men and women. Cognition and Emotion, 12, 105±133. Stewart, S. H., Taylor, S., & Baker, J. M. (1997). Gender differences in dimensions of anxiety sensitivity. Journal of Anxiety Disorders, 11, 179±200. Stewart, S. H., & Watt, M. C. (2000). Illness attitudes scale dimensions and their associations with anxiety-related constructs in a nonclinical sample. Behaviour Research and Therapy, 38, 83±99. Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Needham Heights, MA: Allyn & Bacon.

308

LEFAIVRE ET AL.

Taylor, S., Koch, W. J., & McNally, R. J. (1992). How does anxiety sensitivity vary across the anxiety disorders? Journal of Anxiety Disorders, 6, 249±259. Taylor, S., Koch, W. J., & Woody, S. (1996). Anxiety sensitivity and depression: How are they related? Journal of Abnormal Psychology, 105, 474±479. Teachman, B. A., & Woody, S. R. (2003). Automatic processing in spider phobia: Implicit fear associations over the course of treatment. Journal of Abnormal Psychology, 112, 100±109. Teachman, B. A., & Woody, S. R. (2004). Staying tuned to research in implicit cognition: Relevance for clinical practice with anxiety disorders. Cognitive and Behavioral Practice, 11, 149±159. Watt, M. C., Stewart, S. H., & Cox, B. J. (1998). A retrospective study of the learning history origins of anxiety sensitivity. Behaviour Research and Therapy, 36, 505±525. Williams, J. M. G., Mathews, A., & MacLeod, C. (1996). The emotional Stroop task and psychopathology. Psychological Bulletin, 120, 3±24. Wise, T. & Sheridan, M. J. (2001). Psychometric properties of the Illness Attitudes Scale in psychiatric patients. Psychological Reports, 89, 73±76.

APPENDIX Example of instructions for a test-trial block: This is a test phase with white and coloured words. For For For For

white words with a positive meaning: Press the GOOD key (A) white words with a negative meaning: Press the BAD key (L) words in a blue-ish colour: Press the GOOD key (A) words in a green-ish colour: Press the BAD key (L)