“I fear, therefore, I shop!” exploring anxiety sensitivity in relation to compulsive buying

Personality and Individual Differences 104 (2017) 37–42

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“I fear, therefore, I shop!” exploring anxiety sensitivity in relation to compulsive buying Catherine E. Gallagher a, Margo C. Watt b,c,⁎, Angela D. Weaver b, Keely A. Murphy d a

Department of Psychology, University of New Brunswick, Fredericton, New Brunswick E3B 5A3, Canada Department of Psychology, St. Francis Xavier University, Antigonish, Nova Scotia, B2G 2W5, Canada c Department of Psychology & Neuroscience, Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada d Department of Psychology, University of Calgary, Calgary, Alberta T2N 1N4, Canada b

a r t i c l e

i n f o

Article history: Received 25 March 2016 Received in revised form 19 July 2016 Accepted 20 July 2016 Available online 29 July 2016 Keywords: Compulsive buying Negative affect Anxiety sensitivity

a b s t r a c t Compulsive buying involves a preoccupation with, or urges to, buy, that are experienced as intrusive and uncontrollable. Compulsive buying is associated with impaired functioning and serves to alleviate negative emotional arousal. Anxiety sensitivity (AS: fear of arousal-related somatic sensations) is a known risk factor for negative emotional arousal. The present study investigated whether AS was linked to compulsive buying, over and above negative affect (depression, anxiety, stress), in a sample of Canadian undergraduates. Results showed that females (vs. males) were more likely to report spending in the moment and experiencing guilt after shopping. Males were more apt to report experiencing negative feelings about shopping. Anxiety predicted the tendency to spend in the moment and to buy compulsively, while stress and depression predicted post-purchase guilt. AS-Physical and AS-Cognitive concerns predicted compulsive buying over and above negative affect. No role was found for AS-Social concerns. The findings are discussed in terms of clinical implications and directions for future research. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction Shopping is a necessary part of modern life, and an activity that many consider harmless. In 2015, however, the average Canadian was carrying nearly $21,000 in consumer debt (Luciw, 2015). This level of debt carries serious implications for individuals (e.g., risk for bankruptcy) and may involve some measure of compulsive buying (Black, 2010). Compulsive buying involves a preoccupation with buying, or urges to buy, that are experienced as intrusive and uncontrollable (McElroy, Keck, Pope, & Smith, 1994). 1.1. Conceptualization of compulsive buying Although not an officially recognized psychological disorder, compulsive buying can lead to marked distress and impaired personal, financial, and social functioning (Black, Shaw, McCormick, Bayless, & Allen, 2012). Researchers have variously argued that compulsive buying is most closely related to obsessive-compulsive spectrum disorders (Frost, Steketee, & Williams, 2002), impulse control disorders (Black et al., 2012), and behavioural addiction (Lejoyeux & Weinstein, 2010). ⁎ Corresponding author at: Department of Psychology, St. Francis Xavier University, Antigonish, Nova Scotia B2G 2W5, Canada. E-mail address: [email protected] (M.C. Watt).

http://dx.doi.org/10.1016/j.paid.2016.07.023 0191-8869/© 2016 Elsevier Ltd. All rights reserved.

Given this conceptual heterogeneity, numerous instruments have been developed to measure compulsive buying. The Compulsive Buying Scale was developed to measure thoughts, feelings, and behaviours associated with compulsive buying (Faber & O'Guinn, 1992). Subsequently, the Edwards Compulsive Buying Scale (ECBS; Edwards, 1993) identified five factors associated with compulsive buying: (1) tendency to spend, (2) impulsivity while shopping, (3) dysfunctions pertaining to shopping, (4) feelings while shopping, and (5) post-purchase guilt. Validation studies, however, have only found support for three factors for the 13-item measure (Tommasi & Busonera, 2012) and four factors when utilizing the initial 29-item pool (Maraz et al., 2015). These factor differences may reflect methodological and/or cultural differences. To date, no research has examined the factor structure of the 13-item ECBS with a Canadian sample. The estimated prevalence of compulsive buying is 6% (Müeller, Mitchell, & de Swaan, 2015) with some finding a higher prevalence among females than males (Harvanko et al., 2013), and others finding no sex differences (Müeller et al., 2010). Sex differences have been found within undergraduate, but not community-based, samples. Among undergraduate students, compulsive buying has been linked to lower academic performance, increased stress levels, somatic complaints, and suicidal behaviours (Harvanko et al., 2013). Compulsive buying has been linked to psychopathology, including mood and anxiety disorders (Black et al., 2012), with compulsive buying behaviours

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C.E. Gallagher et al. / Personality and Individual Differences 104 (2017) 37–42

most likely to occur in response to negative mood states (e.g., stress, anxiety; Billieux, Rochat, Rebetez, & Van der Linden, 2008). The relief of negative affect experienced as a result of a buying episode is brief and often followed by feelings of guilt, shame, and anxiety (Williams & Grisham, 2012). 1.2. Role of anxiety sensitivity High anxiety sensitivity (AS: fear of arousal-related somatic sensations; Reiss, 1991) is a known risk factor for psychopathology characterized by negative affect (e.g., anxiety, depression, substance use; Conrod, Pihl, Stewart, & Dongier, 2000). AS is conceptualized as a hierarchical, multidimensional construct comprised of three lower order factors: (1) Cognitive concerns (e.g., fear of losing control); (2) Physical concerns (e.g., fear of having a heart attack); and (3) Social concerns (e.g., fear of public ridicule; Taylor et al., 2007). It has a subordinate relationship with negative affect, accounting for incremental variance over and above negative affect when predicting psychopathology (Sexton, Norton, Walker, & Norton, 2003). People with high AS tend to avoid situations that elicit the feared physiological sensations, such as physical and sexual activity (Sabourin, Hilchey, Lefaivre, Watt, & Stewart, 2011; Gerrior, Watt, Weaver, & Gallagher, 2015) and/or escape the sensations (e.g., substance use; Conrod et al., 2000). Compulsive buying may be another way to escape the aversive sensations associated with negative affect. Recent research has linked AS-Physical concerns to compulsive hoarding behaviour after controlling for depressive symptoms (Medley, Capron, Korte, & Schmidt, 2013). AS dimensions have been found to differentially predict specific obsessive-compulsive symptoms, even when controlling for comorbid depression and anxiety (Raines, Oglesby, Capron, & Schmidt, 2014), with AS-Cognitive concerns predicting neutralizing and obsessing symptoms, and AS-Social concerns predicting ordering symptoms. 1.3. Current study The primary objective of the present study was to examine the potential role of the AS dimensions among the relationship between negative affect and compulsive buying. Given that negative affect has been found to be associated with compulsive buying and is superordinate to AS, it was hypothesized that negative affect (depression, anxiety, stress), AS, and compulsive buying would be positively correlated. Moreover, given that compulsive buying is associated with obsessivecompulsive symptoms and AS has been found to predict other obsessive-compulsive symptoms over and above negative affect (Raines et al., 2014), it was hypothesized that AS would predict compulsive buying behaviour over and above negative affect. Finally, it was predicted that females would report higher levels of compulsive buying than males. Prior to testing the primary objective, we submitted the ECBS to factor analysis given the conflicting results of validation studies and the noted redundancy across items (Tommasi & Busonera, 2012). As with other studies conducted in developed countries (i.e., US, Italy), it was hypothesized that a three-factor structure would emerge in a Canadian sample. 2. Method 2.1. Participants Participants in the current study were 437 undergraduate students (78% females) enrolled in introductory psychology at a Canadian university. Participants received course credit for their participation. Participants ranged in age from 17 to 41 years (M = 18.39, SD = 1.52), and identified primarily as Euro-Canadian (86.2%).

2.2. Measures 2.2.1. Compulsive Buying Scale (CBS; Faber & O'Guinn, 1992) The CBS is a 7-item self-report measure designed as a screener for compulsive buying behaviour. Items describe thoughts, feelings, and behaviours associated with compulsive buying (e.g., “I have bought something in order to make myself feel better”). Respondents indicate how often each statement describes their behaviour using a 5-point Likert scale ranging from 1 (never) to 5 (very often). The CBS has demonstrated good reliability and validity (Tommasi & Busonera, 2012; α = 0.95 in the current study). 2.2.2. Edwards Compulsive Buying Scale (ECBS; Edwards, 1993) The ECBS is a 13-item questionnaire assessing various aspects of compulsive buying. Each item is rated on a 5-point scale ranging from 1 (never) to 5 (very often), and include items such as “I feel anxious after I go on a buying binge.” The ECBS has demonstrated good construct validity and reliability (Edwards, 1993; α = 0.89 in the current study). 2.2.3. Depression Anxiety Stress Scale-21 (DASS-21; Lovibond & Lovibond, 1995) The DASS-21 is a self-report measure comprised of three 7-item subscales that measure symptoms of depression (e.g., “I felt that I had nothing to look forward to”), anxiety (e.g., “I felt I was close to panic”), and stress (e.g., “I found it difficult to relax”). Respondents rate their experience over the past week using a scale ranging from 0 (did not apply) to 3 (applied to me much). The internal reliabilities for the DASS-21 subscales in the present study were found to be good (Depression: α = 0.89; Anxiety: α = 0.79; Stress: α = 0.81). 2.2.4. Anxiety Sensitivity Index-3 (ASI-3, Taylor et al., 2007) The ASI-3 is an 18-item self-report questionnaire assessing individual's fear of arousal-related sensations. The scale measures global AS levels, comprised of the three AS dimensions: (1) Cognitive concerns (e.g., “When my thoughts seem to speed up, I worry that I may be going crazy); (2) Physical concerns (e.g., “It scares me when my heart beats rapidly”); and (3) Social concerns (e.g., “I worry that other people will notice my anxiety”). Respondents rate their own experience using a Likert scale ranging from 0 (very little) to 4 (very much). Internal consistency for the ASI-3 in the present study was excellent (α = 0.90), and was good for Cognitive (α = 0.87), Physical (α = 0.84), and Social (α = 0.75) subscales. 2.3. Procedure Following institutional ethics approval, all study measures were embedded in an online questionnaire package administered to students in Introductory Psychology. Students were able to access the questionnaires using a secure web-based participant pool management system. Participants were asked to read an invitation to participate and acknowledge consent prior to completing the questionnaires in a counterbalanced order. 3. Results There were no cases with excessive missing data (i.e., ≥10% missing); cases with missing data points were imputed via mean substitution. Three univariate outliers were identified, as determined by z-scores, and their scores were winsorized. No multivariate outliers were identified (Mahalanobis distance, p b 0.001). No assumptions of normality were violated when assessing skewness and kurtosis. Results of the data screening process resulted in a final sample of 437 participants (95 males, 339 females). Three participants did not indicate sex and were only excluded from analyses examining sex differences.

C.E. Gallagher et al. / Personality and Individual Differences 104 (2017) 37–42

3.1. Factor analysis of the Edwards Compulsive Buying Scale A confirmatory factor analysis indicated that the five-factor structure of the ECBS was not a good fit for the data, RMSEA = 0.09, CFI = 0.91, TLI = 0.91, χ2 (55) = 222.35, p b 0.001. Results of the CFA demonstrated high cross-loadings among items for three subscales (i.e., tendency to spend, impulsivity while shopping, and dysfunctions pertaining to shopping). To determine the factor structure of the ECBS in the study sample, EFA via maximum-likelihood and oblique (direct oblimin, δ = 0) rotation were employed. Results of the KMO (0.89) and Bartlett's test of sphericity, χ2 (78) = 2706.34, p b 0.001, indicated that there were different factors among the 13 ECBS items. Parallel analysis and goodness-of-fit statistics indicated that the data were best represented by a three-factor solution, RMSEA = 0.07, CFI = 0.95, TLI = 0.93, χ2 (42) = 161.80, p b 0.001, accounting for 66% of the variance. Eigenvalues for the three-factors were 5.77, 1.69, and 1.11, with the remaining eigenvalues well below 1.00. As per the pattern matrix, all items loaded above |0.50| on their respective factors and demonstrated minimal to near-zero cross-loadings (see Table 1). The rotated factors demonstrated low to moderate correlations, suggesting three distinct, yet related, factors. Consistent with previous research (Tommasi & Busonera, 2012), results indicated that Factor 1 was comprised of 9 items (tendency or compulsion to spend in the moment); Factor 2 was comprised of 2 items (feelings about shopping); and Factor 3 was comprised of 2 items (post-purchase guilt). 3.2. Sample characteristics A summary of descriptive statistics for all study variables is presented in Table 2. DASS-21 scores were significantly higher than those reported by community adults (Sinclair et al., 2012) and undergraduates (Alexander & Harrison, 2013), all ps b 0.02. Total ASI-3 scores were comparable to scores reported by other undergraduate samples but lower than scores reported by clinical samples (Osman et al., Table 1 Exploratory factor analysis via maximum likelihood factor extraction of the Edwards Compulsive Buying Scale (ECBS). Factor Item Item no.

1 (α = 0.89)

2 (α = 0.83)

3 (α = 0.80)

6

0.78

−0.04

0.10

0.74 0.71 0.68

0.19 −0.02 −0.11

0.02 −0.00 −0.00

0.67

−0.17

−0.03

0.63

−0.02

−0.25

0.60

0.11

−0.10

0.53

−0.20

−0.14

0.50 0.02 0.03 0.01

−0.31 −0.83 −0.83 −0.06

0.01 −0.01 −0.01 −0.83

0.01

0.05

−0.79

12 4 7 13 8 10 1

5 3 2 9 11

I buy things even when I don't need anything. I buy things I don't need or won't use. I go on buying binges. I go on a buying binge when I'm upset, disappointed, depressed, or angry. I sometimes feel compelled to go shopping. I worry about my spending habits but still go out and shop and spend money. I buy things even though I cannot afford them. I feel driven to shop and spend, even when I don't have the time or the money. I feel “high” when I go on a buying spree. I hate to go shopping.a I get little or no pleasure from shopping.a I feel anxious after I go on a buying binge. I feel guilty or ashamed after I go on a buying binge.

Factor 2 Factor 3

39

2010), all ps b 0.001. Compulsive buying scores (CBS and ECBS) were comparable to those reported by US undergraduate samples (Manolis & Roberts, 2008). To date, there is no known Canadian data to compare. Independent samples t-tests (n = 434) revealed no sex differences in DASS-21 scores with the exception of stress, which was significantly higher in females than males. No significant sex differences were found in AS dimension scores or compulsive buying (as measured by the CBS). On the ECBS, females reported greater tendencies to shop and post-purchase guilt, whereas males reported more negative attitudes towards shopping (see Table 2). As hypothesized, symptoms of depression, anxiety, and stress were positively correlated with compulsive buying, with the exception of the ECBS-Feelings about Shopping subscale (see Table 2). The AS dimensions correlated positively with both measures of compulsive buying, with the exception of Feelings about Shopping. 3.3. Regression analyses Regression diagnostic analyses indicated that there were no violations of normality, linearity, or homoscedasticity. The following data analytic strategy was employed for each of the four dependent variables: sex was entered in the first step; depression, anxiety, and stress scores were entered in the second step; and the three AS dimensions were entered in the third step. 3.3.1.1. CBS Total The overall model was significant, F(7, 424) = 7.92, p b 0.001, accounting for 10% of the variance (see Table 3). Sex was not a significant predictor of compulsive buying, F(1, 430) = 3.19, p b 0.08. Negative affect (specifically anxiety) accounted for a significant proportion of unique variance, ΔF(3, 427) = 12.87, p b 0.001. AS-Physical and ASCognitive concerns were found to be significant predictors, ΔF(3, 424) = 12.87, p b 0.007. 3.3.1.2. ECBS-tendency or compulsion to spend in the moment The overall model was significant, F(7, 424) = 13.66, p b 0.001, accounting for 17% of the variance (see Table 4). Sex was a significant predictor, F(1, 430) = 30.92, p b 0.001. Negative affect (specifically anxiety) accounted for a significant proportion of unique variance, ΔF(3, 427) = 15.11, p b 0.001. The addition of the AS dimensions was significant, ΔF(3, 424) = 4.75, p b 0.004, however, at the coefficient level, ASPhysical concerns emerged only as a marginal predictor only. 3.3.1.3. ECBS-feelings about shopping The overall model was significant, F(7, 424) = 7.17, p b 0.001, accounting for 9% of the variance (see Table 4). Sex was a significant predictor, F(1, 430) = 45.96, p b 0.001. Negative affect, ΔF(3, 427) = 0.76, p = 0.52, and AS dimensions, ΔF(3, 424) = 0.11, p = 0.95, were not significant predictors. 3.3.1.4. ECBS-post-purchase guilt The overall model was significant, F(7, 424) = 8.18, p b 0.001, accounting for 10% of the variance (see Table 4). Sex was a significant predictor, F(1, 430) = 14.16, p b 0.001. Negative affect (stress and depression) accounted for a significant proportion of unique variance, ΔF(3, 427) = 10.05, p b 0.001. The AS dimensions did not contribute to the prediction of Post-Purchase Guilt. 4. Discussion

Factor correlation matrix −0.38 – −0.52 0.11 –

Factor loadings above .50 appear in bold; factor loadings from pattern matrix are reported; direct oblimin (δ = 0) rotation was employed. a Items are reverse coded.

The present study examined relations among compulsive buying, negative affect, and AS in a sample of university students. Results showed that females reported more spending in the moment and more guilt after shopping than males, while males reported more negative feelings about shopping. Anxiety predicted compulsive buying

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C.E. Gallagher et al. / Personality and Individual Differences 104 (2017) 37–42

Table 2 Means, standard deviations, and bivariate correlations for study variables of interest (N = 437).

1. CBS total 2. ECBS tendency 3. ECBS feelings 4. ECBS guilt 5. Depression 6. Anxiety 7. Stress 8. AS-cognitive 9. AS-physical 10. AS-social

Total M (SD) (N = 437)

Males (n = 95)

Females (n = 339)

2.

3.

4.

5.

6.

7.

8.

9.

10.

1.83 (0.56) 2.22 (0.82) 3.68 (1.07) 2.18 (1.11) 10.41 (9.39) 9.71 (7.95) 13.94 (8.50) 4.49 (4.82) 4.98 (4.76) 9.52 (5.07)

1.74 (0.54) 1.79 (0.64) 3.05 (1.02) 1.80 (0.94) 10.82 (10.27) 9.39 (6.96) 11.72 (7.52) 4.47 (4.72) 4.42 (4.45) 9.13 (4.82)

1.85 (0.56) 2.29 (0.81)a 3.86 (1.01)a 2.28 (1.13)a 10.30 (9.14) 9.80 (8.21) 14.56 (8.66)b 4.49 (4.86) 5.13 (4.83) 9.63 (5.14)

0.74⁎ –

0.28⁎ 0.43⁎ –

0.37⁎ 0.47⁎ 0.11 –

0.24⁎ 0.22⁎ −0.06 0.22⁎ –

0.27⁎ 0.29⁎ −0.05 0.17⁎ 0.61⁎ –

0.25⁎ 0.30⁎ −0.01 0.26⁎ 0.64⁎ 0.71⁎

0.27⁎ 0.28⁎ −0.04 0.22⁎ 0.47⁎ 0.51⁎ 0.49⁎

0.24⁎ 0.27⁎ 0.01 0.21⁎ 0.28⁎ 0.47⁎ 0.38⁎ 0.58⁎

0.18⁎ 0.25⁎ −0.02 0.23⁎ 0.42⁎ 0.46⁎ 0.44⁎ 0.55⁎ 0.57⁎

–

–

–

–

CBS = Compulsive Buying Scale; ECBS = Edwards Compulsive Buying Scale; AS = anxiety sensitivity. t-value corresponding with equal variances not assumed. a p b 0.001. b p b 0.005. ⁎ p b 0.001 following Bonferroni correction.

and the tendency to spend in the moment, while stress and depression predicted post-purchase guilt. AS-Physical and AS-Cognitive (but not AS-Social) concerns also predicted compulsive buying as measured by the CBS (but not the ECBS), over and above negative affect. At first blush, this discrepancy in findings between two measures of compulsive buying seems confusing. Research, however, has found considerable differences among compulsive buying measures, with different measures identifying different aspects of compulsive buying behaviour (Maraz et al., 2015). For example, the CBS seems to measure the severity of buying behaviour, whereas the ECBS appears to measure the compulsivity (i.e., tendency) to shop, attitudes towards shopping, and negative affect experienced post-shopping. Thus, the results of the present study imply that ASPhysical and Cognitive concerns play a role in predicting the severity of one's compulsive buying, as opposed to one's tendency or compulsivity to engage in the behaviour. Finding that females (vs. males) were more apt to spend in the moment is consistent with other studies using undergraduate samples (Harvanko et al., 2013) but contrasts with the findings for older, community-based samples (Müeller et al., 2010). Perhaps, the impulse to buy decreases as a function of age, at least for females, which could account for why sex differences appear in young adult samples only (Müeller et al., 2010). Of course, it is not known if females or male's buying patterns change over time and awaits further research. Females in the present study also experienced more guilt post-purchase and more symptoms of stress (but not anxiety or depression) than males. Interestingly, research suggests that young females may not experience more stressful events than young males but they are more apt to perceive events as being stressful (Cicognani, 2011). Perhaps, compulsive buying offers a form of mental disengagement, whereby the individual

Table 3 Hierarchical regression analysis of negative affect and AS dimensions on compulsive buying as measured by the Compulsive Buying Scale (Faber & O'Guinn, 1992). Variable Step 1 Sex Step 2 DASS Depression DASS Anxiety DASS Stress Step 3 ASI-3 Cognitive ASI-3 Physical ASI-3 Social

B (SE)

β

t

p

Sr2

−0.12 (0.07)

−0.09

−1.79

0.08

−0.09

ΔR2 0.01

0.01 (0.01) 0.01 (0.01) 0.00 (0.01)

0.12 0.15 0.06

1.88 2.19 0.80

0.06 0.03 0.43

0.09 0.10 0.04

0.01 (0.01) 0.02 (0.01) −0.01 (0.01)

0.13 0.12 −0.07

1.97 1.98 −1.15

0.05 0.05 0.25

0.09 0.09 −0.05

0.08⁎⁎

0.03⁎

Sex was dummy coded with females as the reference group; DASS = Depression Anxiety Stress Scale-21 Item; ASI-3 = Anxiety Sensitivity Index-3. ⁎ p b 0.01. ⁎⁎ p b 0.001.

attempts to cope with stressful events and escape negative feelings by concentrating on a single self-focused activity. If females engage in more compulsive shopping than males, then they will have more opportunities to experience post-purchase guilt. Chronological relations among these variables merits further investigations, as does the potential influence purchasing frequency and intensity (e.g., amount spent during binges). Consistent with previous research (Hu & Jasper, 2004), males in the present study reported more negative feelings about shopping than females. This finding might be due to items on the Feelings Towards Shopping subscale reflecting an attitude towards shopping, whereas Table 4 Hierarchical regression analysis of negative affect and AS dimensions on compulsive buying as measured by Edwards Compulsive Buying Scale (Edwards, 1993). Variable

β

t

p

Sr2

0.27

5.80

b0.001

0.27

0.05 0.19 0.10

0.75 2.84 1.48

0.45 0.005 0.14

0.03 0.13 0.07

0.10 0.09 0.04

1.69 1.53 0.62

0.09 0.13 0.54

0.07 0.07 0.03

0.31

6.78

b0.001

0.31

−0.05 −0.04 0.01

−0.78 −0.57 0.20

0.44 0.57 0.84

−0.04 −0.03 0.01

−0.03 0.03 0.00

−0.47 0.48 0.01

0.64 0.63 0.99

−0.02 0.02 0.00

0.48 (0.13)

0.18

3.76

b0.001

0.18

0.02 (0.01) −0.01 (0.01) 0.02 (0.01)

0.13 −0.04 0.18

2.13 −0.55 2.47

0.03 0.58 0.01

0.10 −0.03 0.11

0.01 (0.02) 0.02 (0.02) 0.02 (0.01)

0.05 0.09 0.09

0.80 1.38 1.41

0.42 0.17 0.16

0.04 0.06 0.06

B (SE)

Tendency or compulsion to spend Step 1 Sex 0.54 (0.09) Step 2 DASS Depression 0.00 (0.01) DASS Anxiety 0.02 (0.01) DASS Stress 0.01 (0.01) Step 3 ASI-3 Cognitive 0.02 (0.01) ASI-3 Physical 0.02 (0.01) ASI-3 Social 0.01 (0.01) Feelings about shopping Step 1 Sex 0.80 (0.12) Step 2 DASS Depression −0.01 (0.01) DASS Anxiety −0.01 (0.01) DASS Stress 0.00 (0.01) Step 3 ASI-3 Cognitive −0.01 (0.01) ASI-3 Physical 0.01 (0.01) ASI-3 Social 0.00 (0.01) Post-purchase guilt Step 1 Sex Step 2 DASS Depression DASS Anxiety DASS Stress Step 3 ASI-3 Cognitive ASI-3 Physical ASI-3 Social

ΔR2 0.07⁎⁎ 0.09⁎⁎

0.03⁎

0.10⁎⁎ 0.01

0.00

0.03⁎⁎ 0.06⁎⁎

0.02

Sex was dummy coded with females as the reference group. ⁎ p b 0.01. ⁎⁎ p b 0.001.

C.E. Gallagher et al. / Personality and Individual Differences 104 (2017) 37–42

other subscales seem to tap into the function (and consequences) of shopping. Females report more positive attitudes overall towards shopping. Whereas males tend to shop for utilitarian reasons (i.e., with an intended purpose), females report more hedonic reasons and as a way to relieve stress (Hu & Jasper, 2004). Participants in the present study reported significantly higher levels of depression, anxiety, and stress symptoms compared to some other samples of university students and community-based adults (Alexander & Harrison, 2013; Sinclair et al., 2012). It is possible that these elevated levels reflect the timing of data collection. Our data was collected early in students' first year of transitioning to university. This is known to be a highly stressful time with students facing many challenges (e.g., adopting to new roles, new social networks). Levels of AS, however, were consistent with other non-clinical samples (Osman et al., 2010), as were self-reported levels of compulsive buying (Manolis & Roberts, 2008). As expected, high levels of both general anxiety and AS predicted higher self-reported levels of compulsive buying behaviours as measured by the CBS. Whereas the association between negative affect and compulsive buying behaviours has been demonstrated in past research (Billieux et al., 2008), the relationship between AS and compulsive buying is a novel finding. AS-Physical and AS-Cognitive concerns predicted compulsive buying (as measured by the CBS) over and above negative affect. In other words, and consistent with previous research, fears of the physical and cognitive consequences of anxiety are more strongly related to compulsive buying than fears of social consequences (Medley et al., 2013). The current findings suggest that the acquisition of material goods may serve the function of distracting the individual from internal (vs. external or social) perceptions of his or her own affective state (i.e., physical and cognitive concerns). Whereas AS-Physical concerns are associated with hoarding behaviour (Medley et al., 2013), AS-Cognitive and Social concerns are associated with obsessive-compulsive disorder symptoms (Raines et al., 2014). Given that the DSM-5 (APA, 2013) considers hoarding to be separate from obsessive-compulsive disorder, finding a role for both AS-Physical and Cognitive concerns in predicting compulsive buying behaviour suggests that compulsive buying may not fall neatly into one of the existing diagnostic categories. Post-purchase guilt, as measured by the ECBS, was predicted by sex, and both depression and stress symptoms, but none of the AS dimensions. In addition to assessing feelings of post-purchase guilt, items on this subscale assess feelings of shame in relation to shopping. Although guilt and shame are strongly correlated, shame is more predictive of depression symptoms (Tangney, Wagner, & Gramzow, 1992). The variance shared by guilt/shame and depression might explain the lack of finding with regard to AS. Moreover, it is possible that the Post-Purchase Guilt subscale more accurately reflects an individual's tendency to experience negative emotions and cognitions consequent to a shopping episode. 4.1. Implications The study findings of this study have a number of clinical implications. Findings show that compulsive buying is linked to both negative affect and a risk factor for negative affect; namely, AS. High AS is a known risk factor for a wide range of psychopathologies and, as such, is eligible for consideration as a transdiagnostic factor – a factor presumed to underlie and explain comorbidity across disorders (Naragon-Gainey, 2010). Targeting transdiagnostic factors, such as high AS, allows for treatments to yield positive outcomes across a range of disorders rather than targeting disorder-specific symptoms. Although AS is considered a dispositional factor, it has been shown to be amenable to change and brief cognitive behavioural interventions targeting AS have been found to be effective in reducing clinically meaningful levels of AS and negative affect (Olthuis, Watt, Mackinnon, & Stewart, 2015).

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Given the findings of the present study, compulsive buying might be viewed as a maladaptive strategy for coping with negative affect, a strategy intended to relieve sensitivity to arousal (high AS), especially physical concerns associated with that arousal. Cognitive behavioural intervention targeting high AS-Physical concerns, specifically, might be effective in the prevention and treatment of compulsive buying. Further research in this area is warranted. That said, negative affect and AS only accounted for 20% of the variance in compulsive buying behaviour. There are likely other meaningful factors that contribute to the development and maintenance of compulsive buying, including: impulsivity; compulsivity; and materialism (Müeller et al., 2014). Developing comprehensive conceptual models of compulsive buying may help determine both the unique and shared contributions of predictors thought to be associated with compulsive buying. 4.2. Limitations and future directions Findings should be considered in light of several limitations. First, the correlational design of the study precludes drawing any causal conclusions about the AS-compulsive buying relationship. Second, while the use of a university population was advantageous given the prevalence of compulsive buying among young adults (Müeller et al., 2014), it limits the generalizability of our findings. Given that sex differences in compulsive buying behaviours differ primarily between college and community-based samples (Müeller et al., 2010), an exploration of the relationship between AS and compulsive buying in a community sample (of males and females) seems warranted. Whereas compulsive buying behaviours have been found to decrease with age (e.g., Müeller et al., 2010), AS is considered to be a trait characteristic that remains stable in the absence of intervention (Reiss, 1991). Finally, the present study did not control for the potential influence of purchasing frequency, which could have influenced participants' responses to items pertaining to compulsive buying behaviour. Future directions for research should expand the assessment of compulsive buying and related constructs to include measures other than self-report (e.g., experimental interventions designed to decrease AS), which could offer insight into how each construct uniquely contributes to compulsive buying. Moreover, future research should examine other emotion regulation strategies (e.g., mindfulness) in the relationship between negative affect and compulsive buying. Future research might also involve an investigation of compulsive buying with respect to online shopping. Perhaps the ability to act immediately on the urgency of negative affect from one's home would exacerbate the frequency of compulsive buying episodes. Finally, delineating the extent to which compulsive buying serves an antecedent and/or consequence of psychopathology will also be an important area for future research with considerable treatment implications (Müeller et al., 2014). 5. Conclusion In summary, the present study is the first known study to examine the association between AS and compulsive buying behaviour. The findings suggest that AS is uniquely related with compulsive buying, above and beyond symptoms of depression, anxiety, and stress. These findings may provide insight regarding the identification of individuals who may be at risk of developing compulsive buying behaviours and may serve as a therapeutic target in intervention. This may be timely considering the current magnitude of consumer debt load and important given the multitude of negative consequences associated with compulsive buying. References Alexander, S. J., & Harrison, A. G. (2013). Cognitive responses to stress, depression, and anxiety and their relationship to ADHD symptoms in first year psychology students. Journal of Attention Disorders, 17, 29–37. http://dx.doi.org/10.1177/1087054711413071.

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Billieux, J., Rochat, L., Rebetez, M. M., & Van der Linden, M. (2008). Are all facets of impulsivity related to self-reported compulsive buying behavior? Personality and Individual Differences, 44(6), 1432–1442. Black, D. W. (2010). Compulsive buying: Clinical aspects. In E., & L. M. (Eds.), Impulse control disorders (pp. 5–22). New York, NY: Cambridge University Press. Black, D. W., Shaw, M., McCormick, B., Bayless, J. D., & Allen, J. (2012). Neuropsychological performance, impulsivity, ADHD symptoms, and novelty seeking in compulsive buying disorder. Psychiatry Research, 200, 581–587. http://dx.doi.org/10.1016/j.psychres. 2012.06.003. Cicognani, E. (2011). Coping strategies with minor stressors in adolescence: Relationships with social support, self-efficacy, and psychological well-being. Journal of Applied Social Psychology, 41(3), 559–578. Conrod, P. J., Pihl, R. O., Stewart, S. H., & Dongier, M. (2000). Validation of a system of classifying female substance abusers on the basis of personality and motivational risk factors for substance abuse. Psychology of Addictive Behaviors, 14, 243–256. http://dx.doi.org/10.1037//0893-164X.14.3.243. Edwards, E. A. (1993). Development of a new scale for measuring compulsive buying behavior. Financial Counseling and Planning, 4, 67–85. Faber, R. J., & O'Guinn, T. C. (1992). A clinical screener for compulsive buying. Journal of Consumer Research, 19(3), 459–469. Frost, R. O., Steketee, G., & Williams, L. (2002). Compulsive buying, compulsive hoarding, and obsessive-compulsive disorder. Behavior Therapy, 33, 201–214. http://dx.doi.org/ 10.1016/S0005-7894(02)80025-9. Gerrior, K. G., Watt, M. C., Weaver, A. D., & Gallagher, C. E. (2015). The role of anxiety sensitivity in the sexual functioning of young women. Sexual and Relationship Therapy, 30(3), 351–363. Harvanko, A., Lust, K., Odlaug, B. L., Schreiber, L., Derbyshire, K., Christenson, G., & Grant, J. E. (2013). Prevalence and characteristics of compulsive buying in college students. Psychiatry Research, 210(3), 1079–1085. Hu, H., & Jasper, C. R. (2004). Men and women: A comparison of shopping mall behaviour. Journal of Shopping Center Research, 11(1/2), 113–123. Lejoyeux, M., & Weinstein, A. (2010). Compulsive buying. The American Journal of Drug and Alcohol Abuse, 36, 248–253. http://dx.doi.org/10.3109/00952990.2010.493590. Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the depression anxiety stress scales. Sydney: Psychology Foundation. Luciw, R. (2015, March 3). Canadians take on even more debt, says new report calling for vigilance. The globe and mail. Manolis, C., & Roberts, J. A. (2008). Compulsive buying: Does it matter how it's measured? Journal of Economic Psychology, 29, 555–576. http://dx.doi.org/10.1016/j.joep.2007. 10.005. Maraz, A., Eisinger, A., Hende, B., Urbán, R., Paksi, B., Kun, B., ... Demetrovics, Z. (2015). Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population in shopping centres. Psychiatry Research, 225, 326–334. http://dx.doi.org/10.1016/j.psycres.2014.11.080. McElroy, S. L., Keck, P. E., Pope, H. G., & Smith, J. M. (1994). Compulsive buying: A report of 20 cases. Journal of Clinical Psychiatry, 55(6), 242–248. Medley, A. N., Capron, D. W., Korte, K. J., & Schmidt, N. B. (2013). Anxiety sensitivity: A potential vulnerability factor for compulsive hoarding. Cognitive Behaviour Therapy, 42, 45–55. http://dx.doi.org/10.1080/16506073.2012.738242.

Müeller, A., Mitchell, J. E., Black, D. W., Crosby, R. D., Berg, K., & de Zwaan, M. (2010). Latent profile analysis and comorbidity in a sample of individuals with compulsive buying disorder. Psychiatry Research, 178, 348–353. http://dx.doi.org/10.1016/j. psychres.2010.04.021. Müeller, A., Claes, L., Georgiadou, E., Möllenkamp, M., Voth, E. M., Faber, R. J., ... de Zwaan, M. (2014). Is compulsive buying related to materialism, depression or temperament? Findings from a sample of treatment-seeking patients with CB. Psychiatry Research, 216, 103–107. http://dx.doi.org/10.1016/j.psychres.2014.01.012. Müeller, A., Mitchell, J. E., & de Swaan, M. (2015). Compulsive buying. American Journal on Addictions, 24, 132–137. http://dx.doi.org/10.1111/ajad.12111. Naragon-Gainey, K. (2010). Meta-analysis of the relations of anxiety sensitivity to the depressive and anxiety disorders. Psychological Bulletin, 136, 128–150. http://dx.doi.org/ 10.1037/a0018055. Olthuis, J. V., Watt, M. C., Mackinnon, S. P., & Stewart, S. H. (2015). CBT for high anxiety sensitivity: Alcohol outcomes. Addictive Behaviors, 46, 19–24. http://dx.doi.org/10. 1016/j.addbeh.2015.02.018. Osman, A., Gutierrez, P. M., Smith, K., Fang, Q., Lozano, G., & Devine, A. (2010). The Anxiety Sensitivity Index-3: Analyses of dimensions, reliability estimates, and correlates in nonclinical samples. Journal of Personality Assessment, 92, 45–52. http://dx.doi.org/ 10.1080/00223890903379332. Raines, A. M., Oglesby, M. E., Capron, D. W., & Schmidt, N. B. (2014). Obsessive compulsive disorder and anxiety sensitivity: Identification of specific relations among symptom dimensions. Journal of Obsessive-Compulsive and Related Disorders, 3, 71–76. http:// dx.doi.org/10.1016/j.jocrd.2014.01.001. Reiss, S. (1991). Expectancy model of fear, anxiety, and panic. Clinical Psychology Review, 11, 141–153. Sabourin, B. C., Hilchey, C. A., Lefaivre, M. J., Watt, M. C., & Stewart, S. H. (2011). Why do they exercise less? Barriers to exercise in high-anxiety-sensitive women. Cognitive Behaviour Therapy, 40(3), 206–215. Sexton, K. A., Norton, P. J., Walker, J. R., & Norton, G. R. (2003). Hierarchical model of generalized and specific vulnerabilities in anxiety. Cognitive Behaviour Therapy, 32(2), 82–94. Sinclair, S. J., Siefert, C. J., Slavin-Mulford, J. M., Stein, M. B., Renna, M., & Blais, M. A. (2012). Psychometric evaluation and normative data for the Depression, Anxiety, and Stress Scales-21 (DASS-21) in a nonclinical sample of U.S. adults. Evaluation & the Health Professions, 35, 259–279. http://dx.doi.org/10.1177/0163278711424282. Tangney, J. P., Wagner, P., & Gramzow, R. (1992). Proneness to shame, proneness to guilt, and psychopathology. Journal of Abnormal Psychology, 101, 469–478. Taylor, S., Zvolensky, M. J., Cox, B. J., Deacon, B., Heimberg, R. G., Ledley, D. R., ... Cardenas, S. J. (2007). Robust dimension of anxiety sensitivity: Development and initial validation of the Anxiety Sensitivity Index-3. Psychological Assessment, 19, 176–188. http:// dx.doi.org/10.1037/1040-3590.19.2.176. Tommasi, M., & Busonera, A. (2012). Validation of three compulsive buying scales on an Italian sample. Psychological Reports, 111, 831–844. http://dx.doi.org/10.2466/03.15. 20.PR0.111.6.831-844. Williams, A. D., & Grisham, J. R. (2012). Impulsivity, emotion regulation, and mindful attentional focus in compulsive buying. Cognitive Therapy and Research, 36, 451–457. http://dx.doi.org/10.1007/s10608-011-9384-9.