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The words and the we’s: When is a new addiction scale not a new addiction scale?

“The words you use should be your own/Don’t plagiarize or take on loans/There’s always someone, somewhere/With a big nose, who knows” (Lyrics written by Morrissey from ‘Cemetry Gates’ (sic) by The Smiths)

Over the last few decades, research into ‘shopping addiction’ and ‘compulsive buying’ has greatly increased. In 2015, I along with my colleagues, developed and subsequently published (in the journal Frontiers in Psychology) a new scale to assess shopping addiction – the 7-item Bergen Shopping Addiction Scale (BSAS) which I wrote about in one of my previous blogs.

We noted in our Frontiers in Psychology paper that two scales had already been developed in the 2000s (i.e., one by Dr. George Christo and colleagues in 2003, and one by Dr. Nancy Ridgway and colleagues in 2008 – see ‘Further reading’ below), but that neither of these two instruments approached problematic shopping behaviour as an addiction in terms of core addiction criteria that are often used in the behavioural addiction field including salience, mood modification, tolerance, withdrawal, conflict, relapse, and problems. We also made the point that new Internet-related technologies have now greatly facilitated the emergence of problematic shopping behaviour because of factors such as accessibility, affordability, anonymity, convenience, and disinhibition, and that there was a need for a psychometrically robust instrument that assessed problematic shopping across all platforms (i.e., both online and offline). We concluded that the BSAS has good psychometrics, structure, content, convergent validity, and discriminative validity, and that researchers should consider using it in epidemiological studies and treatment settings concerning shopping addiction.

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More recently, Srikant Amrut Manchiraju, Sadachar and Jessica Ridgway developed something they called the Compulsive Online Shopping Scale (COSS) in the International Journal of Mental Health and Addiction (IJMHA). Given that we had just developed a new shopping addiction scale that covered shopping across all media, we were interested to read about the new scale. The scale was a 28-item scale and was based on the 28 items included in the first step of BSAS development (i.e., initial 28-item pool). As the authors noted:

“First, to measure compulsive online shopping, we adopted the Bergen Shopping Addiction Scale (BSAS; Andreassen, 2015). The BSAS developed by Andreassen et al. (2015), was adapted for this study because it meets the addiction criteria (e.g., salience, mood modification, etc.) established in the DSM-5. In total, 28 items from the BSAS were modified to reflect compulsive online shopping. For example, the original item – ‘Shopping/buying is the most important thing in my life’ was modified as ‘Online shopping/buying is the most important thing in my life’… It is important to note that we are proposing a new behavioral addiction scale, specifically compulsive online shopping … In conclusion, the scale developed in this study demonstrated strong psychometric, structure, convergent, and discriminant validity, which is consistent with Andreassen et al.’s (2015) findings”.

Apart from the addition of the word ‘online’ to every item, all initial 28 items of the BSAS were used identically in the COSS. Therefore, I sought the opinion of several research colleagues about the ‘new’ scale. Nearly all were very surprised that an almost identical scale had been published. Some even questioned whether such wholescale use might constitute plagiarism (particularly as none of the developers of the COSS sought permission to adapt our scale).

According to the plagiarism.org website, several forms of plagiarism have been described including: “Copying so many words or ideas from a source that it makes up the majority of your work, whether you give credit or not” (p.1). Given the word-for-word reproduction of the 28 item–pool, an argument could be made that the COSS plagiarizes the BSAS, even though the authors acknowledge the source of their scale items. According to Katrina Korb’s 2012 article on adopting or adapting psychometric instruments:

“Adapting an instrument requires more substantial changes than adopting an instrument. In this situation, the researcher follows the general design of another instrument but adds items, removes items, and/or substantially changes the content of each item. Because adapting an instrument is similar to developing a new instrument, it is important that a researcher understands the key principles of developing an instrument…When adapting an instrument, the researcher should report the same information in the Instruments section as when adopting the instrument, but should also include what changes were made to the instrument and why” (p.1).

Dr. Manchiraju and his colleagues didn’t add or remove any of the original seven items, and did not substantially change the content of any of the 28 items on which the BSAS was based. They simply added the word ‘online’ to each existing item. Given that the BSAS was specifically developed to take into account the different ways in which people now shop and to include both online and offline shopping, there doesn’t seem to be a good rationale for developing an online version of the BSAS. Even if there was a good rationale, the scale could have made reference to the Bergen Shopping Addiction Scale in the name of the ‘new’ instrument. In a 2005 book chapter ‘Selected Ethical Issues Relevant to Test Adaptations’ by Dr. Thomas Oakland (2005), he noted the following in relation to plagiarism and psychometric test development:

Psychologists do not present portions of another’s work or data as their own, even if the other work or data source is cited … Plagiarism occurs commonly in test adaptation work (Oakland & Hu, 1991), especially when a test is adapted without the approval of its authors and publisher. Those who adapt a test by utilizing items from other tests without the approval of authors and publishers are likely to be violating ethical standards. This practice should not be condoned. Furthermore, this practice may violate laws in those countries that provide copyright protection to intellectual property. In terms of scale development, a measure that has the same original items with only one word added to each item (which only adds information on the context but does not change the meaning of the item) does not really constitute a new scale. They would find it really hard to demonstrate discriminant validity between the two measures”.

Again, according to Oakland’s description of plagiarism specifically in relation to the development of psychometric tests (rather than plagiarism more generally), the COSS appears to have plagiarized the BSAS particularly as Oakland makes specific reference to the adding of one word to each item (“In terms of scale development, a measure that has the same original items with only one word added to each item … does not really constitute a new scale”).

Still, it is important to point that I have no reason to think that this use of the BSAS was carried out maliciously. Indeed, it may well be that the only wrongdoing was lack of familiarity with the conventions of psychometric scale development. It may be that the authors took one line in our original Frontiers in Psychology paper too literally (the BSAS may be freely used by researchers in their future studies in this field”). However, the purpose of this sentence was to give fellow researchers permission to use the validated scale in their own studies and to avoid the inconvenience of having to request permission to use the BSAS and then waiting for an answer. Another important aspect here is that the BSAS (which may be freely used) consists of seven items only, not 28. The seven BSAS items were extracted from an initial item pool in accordance with our intent to create a brief shopping addiction scale. Consequently, there exists only one version of BSAS, the 7-item version. Here, Dr. Manchiraju and his colleagues seem to have misinterpreted this when referring to a 28-item BSAS.

(Please note: This blog is adapted using material from the following paper: Griffiths, M.D., Andreassen, C.S., Pallesen, S., Bilder, R.M., Torsheim, T. Aboujaoude, E.N. (2016). When is a new scale not a new scale? The case of the Bergen Shopping Addiction Scale and the Compulsive Online Shopping Scale. International Journal of Mental Health and Addiction, 14, 1107-1110).

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Aboujaoude, E. (2014). Compulsive buying disorder: a review and update. Current Pharmaceutical Design, 20, 4021–4025.

Andreassen, C. S., Griffiths, M. D., Pallesen, S., Bilder, R. M., Torsheim, T., & Aboujaoude, E. (2015). The Bergen Shopping Addiction Scale: reliability and validity of a brief screening test. Frontiers in Psychology, 6, 1374. doi: 10.3389/fpsyg.2015.01374

Christo, G., Jones, S., Haylett, S., Stephenson, G., Lefever, R. M., & Lefever, R. (2003). The shorter PROMIS questionnaire: further validation of a tool for simultaneous assessment of multiple addictive behaviors. Addictive Behaviors, 28, 225–248.

Griffiths, M.D.  (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10, 191-197.

Griffiths, M.D., Andreassen, C.S., Pallesen, S., Bilder, R.M., Torsheim, T. Aboujaoude, E.N. (2016). When is a new scale not a new scale? The case of the Bergen Shopping Addiction Scale and the Compulsive Online Shopping Scale. International Journal of Mental Health and Addiction, 14, 1107-1110.

Korb, K. (2012). Adopting or adapting an instrument. Retrieved September 12, 2016, from: http://korbedpsych.com/R09aAdopt.html

Manchiraju, S., Sadachar, A., & Ridgway, J. L. (2016). The Compulsive Online Shopping Scale (COSS): Development and Validation Using Panel Data. International Journal of Mental Health and Addiction, 1-15. doi: 10.1007/s11469-016-9662-6.

Maraz, A., Eisinger, A., Hende, Urbán, R., Paksi, B., Kun, B., Kökönyei, G., Griffiths, M.D. & Demetrovics, Z. (2015). Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population and in shopping centres. Psychiatry Research, 225, 326–334.

Maraz, A., Griffiths, M. D., & Demetrovics, Z. (2016). The prevalence of compulsive buying in non-clinical populations: A systematic review and meta-analysis. Addiction, 111, 408-419.

Oakland, T. (2005). Selected ethical issues relevant to test adaptations. In Hambleton, R., Spielberger, C. & Meranda, P. (Eds.). Adapting educational and psychological tests for cross-cultural assessment (pp. 65-92). Mahwah, NY: Erlbaum Press.

Oakland, T., & Hu, S. (1991). Professionals who administer tests with children and youth: An international survey. Journal of Psychoeducational Assessment, 9(2), 108-120.

Plagiarism.org (2016). What is plagiarism? Retrieved September 12, 2016, from: http://www.plagiarism.org/plagiarism-101/what-is-plagiarism

Ridgway, N., Kukar-Kinney, M., & Monroe, K. (2008). An expanded conceptualization and a new measure of compulsive buying. Journal of Consumer Research, 35, 622–639.

Weinstein, A., Maraz, A., Griffiths, M.D., Lejoyeux, M. & Demetrovics, Z. (2016). Shopping addiction and compulsive buying: Features and characteristics of addiction. In V. Preedy (Ed.), The Neuropathology Of Drug Addictions And Substance Misuse (Vol. 3). (pp. 993-1008). London: Academic Press.

Running up debt: A brief overview of our recent papers on exercise and shopping addictions

Following my recent blogs where I outlined some of the papers that my colleagues and I have published on mindfulness, Internet addiction, gaming addiction, youth gambling and other addictive behaviours, here is a round-up of recent papers that my colleagues and I have published on exercise addiction and shopping addictions (i.e., compulsive buying).

Griffiths, M.D., Urbán, R., Demetrovics, Z., Lichtenstein, M.B., de la Vega, R., Kun, B., Ruiz-Barquín, R., Youngman, J. & Szabo, A. (2015). A cross-cultural re-evaluation of the Exercise Addiction Inventory (EAI) in five countries. Sports Medicine Open, 1:5.

  • Research into the detrimental effects of excessive exercise has been conceptualized in a number of similar ways, including ‘exercise addiction’, ‘exercise dependence’, ‘obligatory exercising’, ‘exercise abuse’, and ‘compulsive exercise’. Among the most currently used (and psychometrically valid and reliable) instruments is the Exercise Addiction Inventory (EAI). The present study aimed to further explore the psychometric properties of the EAI by combining the datasets of a number of surveys carried out in five different countries (Denmark, Hungary, Spain, UK, and US) that have used the EAI with a total sample size of 6,031 participants. A series of multigroup confirmatory factor analyses (CFAs) were carried out examining configural invariance, metric invariance, and scalar invariance. The CFAs using the combined dataset supported the configural invariance and metric invariance but not scalar invariance. Therefore, EAI factor scores from five countries are not comparable because the use or interpretation of the scale was different in the five nations. However, the covariates of exercise addiction can be studied from a cross-cultural perspective because of the metric invariance of the scale. Gender differences among exercisers in the interpretation of the scale also emerged. The implications of the results are discussed, and it is concluded that the study’s findings will facilitate a more robust and reliable use of the EAI in future research.

Mónok, K., Berczik, K., Urbán, R., Szabó, A., Griffiths, M.D., Farkas, J., Magi, A., Eisinger, A., Kurimay, T., Kökönyei, G., Kun, B., Paksi, B. & Demetrovics, Z. (2012). Psychometric properties and concurrent validity of two exercise addiction measures: A population wide study in Hungary. Psychology of Sport and Exercise, 13, 739-746.

  • Objectives: The existence of exercise addiction has been examined in numerous studies. However, none of the measures developed for exercise addiction assessment have been validated on representative samples. Furthermore, estimates of exercise addiction prevalence in the general population are not available. The objective of the present study was to validate the Exercise Addiction Inventory (EAI; Terry, Szabo, & Griffiths, 2004), and the Exercise Dependence Scale (EDS; Hausenblas & Downs, 2002b), and to estimate the prevalence of exercise addiction in general population. Design: Exercise addiction was assessed within the framework of the National Survey on Addiction Problems in Hungary (NSAPH), a national representative study for the population aged 18–64 years (N = 2710). Method: 474 people in the sample (57% males; mean age 33.2 years) who reported to exercise at least once a week were asked to complete the two questionnaires (EAI, EDS). Results: Confirmatory Factor Analysis (CFA) indicated good fit both in the case of EAI (CFI = 0.971; TLI = 0.952; RMSEA = 0.052) and EDS (CFI = 0.938; TLI = 0.922; RMSEA = 0.049); and confirmed the factor structure of the two scales. The correlation between the two measures was high (r = 0.79). Results showed that 6.2% (EDS) and 10.1% (EAI) of the population were characterized as nondependent-symptomatic exercisers, while the proportion of the at-risk exercisers were 0.3% and 0.5%, respectively. Conclusions: Both EAI and EDS proved to be a reliable assessment tool for exercise addiction, a phenomenon that is present in the 0.3–0.5% of the adult general population.

Szabo, A., Griffiths, M.D., de La Vega Marcos, R., Mervo, B. & Demetrovics, Z. (2015). Methodological and conceptual limitations in exercise addiction research. Yale Journal of Biology and Medicine, 86, 303-308.

  • The aim of this brief analytical review is to highlight and disentangle research dilemmas in the field of exercise addiction. Research examining exercise addiction is primarily based on self-reports, obtained by questionnaires (incorporating psychometrically validated instruments), and interviews, which provide a range of risk scores rather than diagnosis. Survey methodology indicates that the prevalence of risk for exercise addiction is approximately 3 percent among the exercising population. Several studies have reported a substantially greater prevalence of risk for exercise addiction in elite athletes compared to those who exercise for leisure. However, elite athletes may assign a different interpretation to the assessment tools than leisure exercisers. The present paper examines the: 1) discrepancies in the classification of exercise addiction; 2) inconsistent reporting of exercise addiction prevalence; and 3) varied interpretation of exercise addiction diagnostic tools. It is concluded that there is the need for consistent terminology, to follow-up results derived from exercise addiction instruments with interviews, and to follow a theory-driven rationale in this area of research.

Andreassen, C.S., Griffiths, M.D., Pallesen, S., Bilder, R.M., Torsheim, T. Aboujaoude, E.N. (2015). The Bergen Shopping Addiction Scale: Reliability and validity of a brief screening test. Frontiers in Psychology, 6:1374. doi: 10.3389/fpsyg.2015.01374.

  • Although excessive and compulsive shopping has been increasingly placed within the behavioral addiction paradigm in recent years, items in existing screens arguably do not assess the core criteria and components of addiction. To date, assessment screens for shopping disorders have primarily been rooted within the impulse-control or obsessive-compulsive disorder paradigms. Furthermore, existing screens use the terms ‘shopping,’ ‘buying,’ and ‘spending’ interchangeably, and do not necessarily reflect contemporary shopping habits. Consequently, a new screening tool for assessing shopping addiction was developed. Initially, 28 items, four for each of seven addiction criteria (salience, mood modification, conflict, tolerance, withdrawal, relapse, and problems), were constructed. These items and validated scales (i.e., Compulsive Buying Measurement Scale, Mini-International Personality Item Pool, Hospital Anxiety and Depression Scale, Rosenberg Self-Esteem Scale) were then administered to 23,537 participants (Mage = 35.8 years, SDage = 13.3). The highest loading item from each set of four pooled items reflecting the seven addiction criteria were retained in the final scale, The Bergen Shopping Addiction Scale (BSAS). The factor structure of the BSAS was good (RMSEA=0.064, CFI=0.983, TLI=0.973) and coefficient alpha was 0.87. The scores on the BSAS converged with scores on the Compulsive Buying Measurement Scale (CBMS; 0.80), and were positively correlated with extroversion and neuroticism, and negatively with conscientiousness, agreeableness, and intellect/imagination. The scores of the BSAS were positively associated with anxiety, depression, and low self-esteem and inversely related to age. Females scored higher than males on the BSAS. The BSAS is the first scale to fully embed shopping addiction within an addiction paradigm. A recommended cutoff score for the new scale and future research directions are discussed.

Davenport, K., Houston, J. & Griffiths, M.D. (2012). Excessive eating and compulsive buying behaviours in women: An empirical pilot study examining reward sensitivity, anxiety, impulsivity, self-esteem and social desirability. International Journal of Mental Health and Addiction, 10, 474-489.

  • ‘Mall disorders’ such as excessive eating and compulsive buying appear to be increasing, particularly among women. A battery of questionnaires was used in an attempt to determine this association between specific personality traits (i.e., reward sensitivity, impulsivity, cognitive and somatic anxiety, self-esteem, and social desirability) and excessive eating and compulsive buying in 134 women. Reward sensitivity and cognitive anxiety were positively related to excessive eating and compulsive buying, as was impulsivity to compulsive buying. Somatic anxiety and social desirability were negatively related to compulsive buying. These preliminary findings indicate that excessive behaviours are not necessarily interrelated. The behaviours examined in this study appear to act as an outlet for anxiety via the behaviours’ reinforcing properties (e.g., pleasure, attention, praise, etc.). As a consequence, this may boost self-esteem. The findings also appear to indicate a number of risk factors that could be used as ‘warning signs’ that the behaviour may develop into an addiction.

Maraz, A., Eisinger, A., Hende, Urbán, R., Paksi, B., Kun, B., Kökönyei, G., Griffiths, M.D. & Demetrovics, Z. (2015). Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population and in shopping centres. Psychiatry Research, 225, 326–334.

  • Due to the problems of measurement and the lack of nationally representative data, the extent of compulsive buying behaviour (CBB) is relatively unknown. The validity of three different instruments was tested: Edwards Compulsive Buying Scale, Questionnaire About Buying Behavior and Richmond Compulsive Buying Scale using two independent samples. One was nationally representative of the Hungarian population (N=2710) while the other comprised shopping mall customers (N=1447). As a result, a new, four-factor solution for the ECBS was developed (Edwards Compulsive Buying Scale Revised (ECBS-R)), and confirmed the other two measures. Additionally, cut-off scores were defined for all measures. Results showed that the prevalence of CBB is 1.85% (with QABB) in the general population but significantly higher in shopping mall customers (8.7% with ECBS-R, 13.3% with QABB and 2.5% with RCBS-R). Conclusively, due to the diversity of content, each measure identifies a somewhat different CBB group.

Maraz, A., Griffiths, M.D., & Demetrovics, Z. (2016). The prevalence of compulsive buying in non-clinical populations: A systematic review and meta-analysis. Addiction, 111, 408-419.

  • Aims: To estimate the pooled prevalence of compulsive buying behaviour (CBB) in different populations and to determine the effect of age, gender, location and screening instrument on the reported heterogeneity in estimates of CBB and whether publication bias could be identified. Methods: Three databases were searched (Medline, PsychInfo, Web of Science) using the terms ‘compulsive buying’, ‘pathological buying’ and ‘compulsive shopping’ to estimate the pooled prevalence of CBB in different populations. Forty studies reporting 49 prevalence estimates from 16 countries were located (n = 32 000). To conduct the meta-analysis, data from non-clinical studies regarding mean age and gender proportion, geographical study location and screening instrument used to assess CBB were extracted by multiple independent observers and evaluated using a random-effects model. Four a priori subgroups were analysed using pooled estimation (Cohen’s Q) and covariate testing (moderator and meta-regression analysis). Results: The CBB pooled prevalence of adult representative studies was 4.9% (3.4–6.9%, eight estimates, 10 102 participants), although estimates were higher among university students: 8.3% (5.9–11.5%, 19 estimates, 14 947 participants) in adult non-representative samples: 12.3% (7.6–19.1%, 11 estimates, 3929 participants) and in shopping-specific samples: 16.2% (8.8–27.8%, 11 estimates, 4686 participants). Being young and female were associated with increased tendency, but not location (United States versus non-United States). Meta-regression revealed large heterogeneity within subgroups, due mainly to diverse measures and time-frames (current versus life-time) used to assess CBB. Conclusions: A pooled estimate of compulsive buying behaviour in the populations studied is approximately 5%, but there is large variation between samples accounted for largely by use of different time-frames and measures.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Allegre, B., Souville, M., Therme, P. & Griffiths, M.D. (2006). Definitions and measures of exercise dependence, Addiction Research and Theory, 14, 631-646.

Allegre, B., Therme, P. & Griffiths, M.D. (2007). Individual factors and the context of physical activity in exercise dependence: A prospective study of ‘ultra-marathoners’. International Journal of Mental Health and Addiction, 5, 233-243.

Berczik, K., Szabó, A., Griffiths, M.D., Kurimay, T., Kun, B. & Demetrovics, Z. (2012). Exercise addiction: symptoms, diagnosis, epidemiology, and etiology. Substance Use and Misuse, 47, 403-417.

Berczik, K., Griffiths, M.D., Szabó, A., Kurimay, T., Kökönyei, G., Urbán, R. and Demetrovics, Z. (2014). Exercise addiction – the emergence of a new disorder. Australasian Epidemiologist, 21(2), 36-40.

Berczik, K., Griffiths, M.D., Szabó, A., Kurimay, T., Urban, R. & Demetrovics, Z. (2014). Exercise addiction. In K. Rosenberg & L. Feder (Eds.), Behavioral Addictions: Criteria, Evidence and Treatment (pp.317-342). New York: Elsevier.

Griffiths, M.D. (1997). Exercise addiction: A case study. Addiction Research, 5, 161-168.

Griffiths, M.D., Szabo, A. & Terry, A. (2005). The Exercise Addiction Inventory: A quick and easy screening tool for health practitioners. British Journal of Sports Medicine, 39, 30-31.

Kurimay, T., Griffiths, M.D., Berczik, K., & Demetrovics, Z. (2013). Exercise addiction: The dark side of sports and exercise. In Baron, D., Reardon, C. & Baron, S.H., Contemporary Issues in Sports Psychiatry: A Global Perspective (pp.33-43). Chichester: Wiley.

Szabo, A. & Griffiths, M.D. (2007). Exercise addiction in British sport science students. International Journal of Mental Health and Addiction, 5, 25-28.

Terry, A., Szabo, A. & Griffiths, M.D. (2004). The Exercise Addiction Inventory: A new brief screening tool, Addiction Research and Theory, 12, 489-499.

Warner, R. & Griffiths, M.D. (2006). A qualitative thematic analysis of exercise addiction: An exploratory study. International Journal of Mental Health and Addiction, 4, 13-26.

Bought in the act: How prevalent is compulsive buying?

Although shopping is a necessity in modern life, it is also a leisure activity and a form of entertainment with a rewarding value for some people. However, as I have noted in a number of my previous blogs, when taken to the extreme, shopping (or buying) can be a harmful and destructive activity for a minority of individuals. The consequences of compulsive buying behaviour (CBB) are often underestimated.

For instance, CBB can result in (i) large debts, (ii) inability to meet payments, (iii) criticism from partners, friends and acquaintances, (iv) legal and financial consequences, (v) criminal legal problems, and (vi) guilt. Furthermore, individuals with CBB often describe an increasing level of urge or anxiety that can only be alleviated and lead to a sense of completion when a purchase is made. Research has demonstrated that compulsive buying is a frequent disorder in a small minority of shopping mall visitors and is associated with important and robust indicators of psychopathology such as psychiatric distress, borderline personality disorder, and substance abuse. Compared to non-compulsive buyers, compulsive buyers are over twice as likely to abuse substances, have any mood or anxiety disorder, and three times more likely to develop eating disorder than non-compulsive buyers. However, most of these findings are based on a small number of studies, all of which have sampling limitations.

Despite many studies highlighting the severe negative consequences that compulsive buying can lead to, the latest (fifth) edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) did not include compulsive buying disorder due to insufficient research in the field. Therefore, individuals with the condition are classified within the residual category of “Unspecified disruptive, impulse-control, and conduct disorders”. Diagnostic criteria elsewhere include (i) maladaptive preoccupation with buying or shopping, or maladaptive buying or shopping impulses; (ii) generation of marked distress by the buying preoccupations, impulses or behaviours, which are time consuming, significantly interfere with social or occupational functioning or result in financial problems; and (iii) lack of restriction of the excessive buying or shopping behaviour to periods of hypomania or mania.

The age of onset for CBB appears to be in the late teens or early twenties, although some studies have reported a later mean age of 30 years. There is also a lack of consensus relating to gender differences. Most clinical studies report that women are much more likely to become compulsive buyers than men, but not all surveys have found significant differences in buying tendencies between men and women. Cultural mechanisms have been proposed to recognize the fact that CBB mainly occurs among individuals living in developed countries. Elements reported as being necessary for the development of CBB include the presence of a market-based economy, the availability of a wide variety of goods, disposable income, and significant leisure time. For these reasons, most working in the area agree that CBB is unlikely to occur in poorly developed countries, except among the wealthy elite.

Given this background, Aniko Maraz, Zsolt Demetrovics and I recently carried out a meta-analytic review that was published in the journal Addiction using all the empirical data concerning the prevalence of compulsive buying in non-clinical populations. We attempted to estimate a pooled prevalence of compulsive buying behaviour (CBB) in different populations across the world where studies have been carried out. We also examined the effect of age, gender, geographical location of the study.

Our initial literature search identified 638 publications. We then excluded case studies (n=23), reviews or theoretical works (n=192), studies involving data from clinical samples (n=244), qualitative studies (n=26), studies that used a compulsive buying scale to determine shopping severity but didn’t report a prevalence rate (n=73), studies written in a foreign language (n=15), dissertations and conference abstracts (n=7), studies written in a foreign language (n=15), small studies with a sample size of below 145 participants (n=16), and studies involving adolescents (n=2). This left 40 studies that met the inclusion criteria for the review. We then extracted sample mean age, proportion of females (in %), the study’s geographical location, and the screening instrument used to assess CBB, and the reported prevalence estimate of CBB.

The 40 relevant studies identified reported 49 different prevalence rate estimates for 32,333 participants. We then divided the data into four sub-samples: adult representative, adult non-representative, university student and shopping-specific. The mean prevalence of compulsive buying was 4.9% in adult representative samples [10,102 participants], 12.3% in adult non-representative samples [3,929 participants], 8.3% in university student samples [14,947 participants] and 16.2% in shopping-specific samples [4,686 participants]. Unsurprisingly, the highest prevalence rates were among shopping-specific samples.

We noted that the heterogeneity in prevalence rates of CBB may be because of the lack of consensus regarding the definition of compulsive buying. Studies used different measures to assess CBB, each having a different conceptual background. Most definitions include cognitive-affective indicators as well as maladaptive behavioural consequences when defining the disorder (e.g., debts). The screening instruments used across studies differed in indicators of financial consequences (e.g., credit card use, debts, loan etc.) and are subject to differences according to countries, sub-cultures and/or age groups.

Another problem we identified was that measures used to assess CBB didn’t explicitly distinguish current and lifetime assessment of CBB. Prevalence rates assessed with an instrument that assessed lifetime prevalence report 1.6 times higher rates on average than those that assessed current prevalence. We also observed that non-representative samples (e.g., adults, university students, shoppers) tended to recruit younger participants who were more likely to be female than representative studies. However, we also noted that the mean age of the sample and the proportion of males and females did not have a reliable effect on the prevalence estimates.

Being of a younger age was predictive of CBB according to individual study results and also according to the regression analysis that we carried out in the representative samples. However, it remains open as to whether compulsive buying tendency decreases with age or this difference reflects generational differences. If the latter was the case, then the prevalence of compulsive buying behaviour is expected to increase in the future. We also found some evidence for increasing rates of CBB in Germany and in Spain, but longitudinal studies are needed to clarify this.

In relation to data collection, estimates from the United States (18 out of 49) were over-represented compared to countries other than the USA, although there was no difference in the reported estimates between the U.S. and non-U.S. countries. However, it is difficult to draw reliable conclusions regarding the cultural variance of CBB given that adult representative estimates are only available from the USA, Spain, Germany and Hungary.

The fact that compulsive buying behaviour is a relatively common disorder with severe consequences for a minority of individuals should not be overlooked. It appears that approximately one in 20 individuals suffer from CBB at some point in their lives and that being young and female are associated with a higher risk of CBB. High heterogeneity is likely to be the result of methodological variability within studies, such as assessment screens with different time frames and conceptual background. We concluded that future studies should therefore think carefully about how to conceptualise the disorder and to clearly separate out current versus lifetime prevalence in the samples used.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Please note : This article was co-written with Aniko Maraz and Zsolt Demetrovics (Institute of Psychology, Eötvös Loránd University, Budapest, Hungary)

Further reading

Alemis, M. C., & Yap, K. (2013). The role of negative urgency impulsivity and financial management practices in compulsive buying. Australian Journal of Psychology, 65(4), 224-231.

Andreassen, C.S., Griffiths, M.D., Pallesen, S., Bilder, R.M., Torsheim, T. Aboujaoude, E.N. (2015). The Bergen Shopping Addiction Scale: Reliability and validity of a brief screening test. Frontiers in Psychology, 6:1374. doi: 10.3389/fpsyg.2015.01374.

Basu, B., Basu, S., & Basu, J. (2011). Compulsive buying: an overlooked entity. Journal of the Indian Medical Association, 109(8), 582-585.

Black, D.W., Shaw, M., McCormick, B., Bayless, J.D., Allena, J. (2012). Neuropsychological performance, impulsivity, ADHD symptoms, and novelty seeking in compulsive buying disorder. Psychiatry Research, 200, 581–587.

Black, D. W. (2007). A review of compulsive buying disorder. World Psychiatry, 6, 14-18.

Davenport, K., Houston, J.E., Griffiths, M.D. (2012). Excessive eating and compulsive buying behaviours in women: An empirical pilot study examining reward sensitivity, anxiety, impulsivity, self-esteem and social desirability. International Journal of Mental Health and Addiction, 10, 474–489.

Dittmar, H., Long, K. & Bond, R. (2007). When a better self is only a button click away: Associations between materialistic values, emotional and identity-related buying motives, and compulsive buying tendency online. Journal of Social and Clinical Psychology, 26, 334-361.

Duroy, D., Gorse, P., & Lejoyeux, M. (2014). Characteristics of online compulsive buying in Parisian students. Addictive Behaviors, 39, 1827-1830.

Frost, R.A., Tolin, D.F., Steketee, G., Fitch, K.E., Selbo-Bruns, A. (2009). Excessive acquisition in hoarding, Journal of Anxiety Disorders, 23, 632-639.

Guo, Z., Cai, Y. (2011). Exploring the antecedents of compulsive buying tendency among adolescents in China and Thailand: A consumer socialization perspective. African Journal of Business Management, 5(24), 10198-10209.

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.

Jung, J., & Yi, S. (2013). Assessment of heterogeneity of compulsive buyers based on affective antecedents of buying lapses. Addiction Research and Theory, 22, 37-48.

Koran, L.M., Faber, R.J., Aboujaoude, M.A., Large, M.D., Serpe, R.T. (2006). Estimated prevalence of compulsive buying behavior in the United States. American Journal of Psychiatry, 163, 1806-1812.

Kukar-Kinney, M., Ridgway, N. M., & Monroe, K. B. (2012). The role of price in the behavior and purchase decisions of compulsive buyers. Journal of Retailing, 88(1), 63-71.

Lejoyeux, M., Weinstein, A. (2010). Compulsive buying. American Journal of Drug and Alcohol Abuse, 36 (5), 248–253.

Maraz, A., Griffiths, M. D., Demetrovics, Z. (2015). The prevalence of compulsive buying in nonclinical populations: a systematic review and meta-analysis. Addiction, doi:10.1111/add.13223.

Mikołajczak-Degrauwe, K., & Brengman, M. (2014). The influence of advertising on compulsive buying – The role of persuasion knowledge. Journal of Behavioral Addictions3(1), 65–73.

Mueller, A., Mitchell, J. E., Peterson, L. A., Faber, R. J., Steffen, K. J., Crosby, R. D., & Claes, L. (2011). Depression, materialism, and excessive Internet use in relation to compulsive buying. Comprehensive Psychiatry, 52(4), 420-424.

Tommasi, M., & Busonera, A. (2012). Validation of three compulsive buying scales on an Italian sample 1. Psychological Reports, 111(3), 831-844.

Weinstein, A., Maraz, A., Griffiths, M.D., Lejoyeaux, M. & Demetrovics, Z. (in press). Shopping addiction and compulsive buying: Features and characteristics of addiction. In V. Preedy (Ed.), The Neuropathology Of Drug Addictions And Substance Misuse. London: Academic Press.

Good buy to love: Introducing the Bergen Shopping Addiction Scale

(Please note that the following article was co-written using material provided by my research colleague Dr. Cecilie Schou Andreassen and our fellow researchers).

In two of my previous blogs I took a brief look at the area of shopping addiction (that you can read here and here). Since writing those blogs I’ve co-written a few papers on compulsive buying and shopping addiction (see ‘Further reading’ below), the latest of which was published in the journal Frontiers in Psychology (FiP) and led by my friend and research colleague Dr. Cecilie Schou Andreassen at the University of Bergen in Norway. In the FiP paper we reported on the development of a newly created instrument to assess this disorder called the Bergen Shopping Addiction Scale (BSAS).

Whether compulsive and excessive shopping represents an impulse-control, obsessive-compulsive or addictive disorder has been debated for several years This fact is reflected in the many names that have been given to this disorder including ‘oniomania’, ‘shopaholism’, ‘compulsive shopping’, ‘compulsive consumption’, ‘impulsive buying’, “compulsive buying’ and ‘compulsive spending’. In a review by Dr. Andreasson in the Journal of Norwegian Psychological Association, she argued that shopping disorder is best understood from an addiction perspective, and defined it as “being overly concerned about shopping, driven by an uncontrollable shopping motivation, and to investing so much time and effort into shopping that it impairs other important life areas”. Several authors (including myself) share this view as a growing body of research shows that those with problematic shopping behaviour report specific addiction symptoms such as craving, withdrawal, loss of control, and tolerance.

Research also suggests that the typical shopping addict is young, female, and of lower educational background. Some personality factors have also been shown to be associated with shopping addiction including extroversion and neuroticism. It has been suggested that neurotic individuals (typically being anxious, depressive, and self-conscious) may use shopping as means of reducing their negative emotional feelings. Other personality factors may actually protect individuals from developing shopping addictions (e.g., conscientiousness). Empirical research (including some research I carried out with Kate Davenport and James Houston published in a 2012 issue of the International Journal of Mental Health and Addiction) has consistently reported significantly lower levels of self-esteem among shopping addicts. Such findings suggest that irrational beliefs such as “buying a product will make life better” and “shopping this item will enhance my self-image” may trigger excessive shopping behaviour in people with low self-esteem. However, this may be related to depression, which has been shown to be highly comorbid with problematic shopping.

Other factors, such as anxiety have also often been associated with shopping, and it has also been suggested that self-critical people shop in order to escape, or cope with, negative feelings. In addition, shopping addiction has also been explained (by such people as Dr. Marc Potenza and Dr. Eric Hollander) as a way of regulating neurochemical (e.g., serotonergic, dopaminergic, opioid) abnormalities and has been successfully treated with pharmacological agents, including selective serotonin reuptake inhibitors (SSRIs) and opioid antagonists.

One of the key problems that we outlined in our new FiP paper is that in prior research there is a lack of a common understanding about how problematic shopping should be defined, conceptualized, and measured. Consequently, there are huge disparities and unreliable prevalence estimates of shopping addiction ranging from 1% to 20% and beyond (depending upon the criteria used to assess the disorder). Although several scales for assessing shopping addiction have been developed (mainly in the late 1980s and early 1990s) many of them have poor theoretical anchoring and/or are primarily rooted within the impulse-control paradigm. We also argued that several items of existing scales are outdated with regards to modern consumer patterns (such as people using cheques or no reference to online shopping). Newer scales that have been developed don’t view problematic shopping behaviour as an addiction in terms of core addiction criteria (i.e., salience, mood modification, tolerance, withdrawal, conflict, relapse and resulting problems).

This is why we decided to develop a new shopping addiction scale (i.e., the BSAS) containing a small number of items that reflect the core elements of addiction (and if you want to take the test yourself, it’s at the end of this article). We examined the psychometric properties of the new scale among a large sample of Norwegian individuals (n=23,537), and the testing phase began with 28 items (four statements for each of the seven components of addiction outlined above). The BSAS was constructed simply by taking the highest scoring item from each of seven 4-item clusters. We found that scores on the BSAS were significantly higher among females, as well as being inversely related to age (and therefore in line with previous research). We also found that scores on the BSAS were positively associated with extroversion and neuroticism.

The association of shopping addiction with extroversion may reflect that, in general, extroverts need more stimulation than non-extroverted individuals, a notion that is in line with studies showing that extroversion is associated with addictions more generally. It may also reflect the notion that extroverts purchase specific types of products excessively as a means to express their individuality, enhance personal attractiveness, or as a way to belong to a certain privileged group a (e.g., the buying of high end luxury goods). The association of shopping addiction with neuroticism may be because neuroticism is a general vulnerability factor for the development of psychopathology and that people scoring high on neuroticism engage excessively in different behaviours in order to escape from dysphoric feelings.

We also found that shopping addiction was inversely related to self-esteem. This is also in line with the findings of previous studies and implies that some individuals shop excessively in order to obtain higher self-esteem (e.g., associated “rub-off” effects from high status items such as popularity, compliments, in-group ‘likes’, omnipotent feelings while buying items, attention during the shopping process from helping retail personnel), to escape from feelings of low self-esteem, or that shopping addiction lowers self-esteem. Obviously our new scale needs to be further evaluated in future studies (as it has only been investigated in this one study) and it also requires validation in other cultures.

Overall, we concluded that the BSAS has good psychometrics – basically the scale is quick to administer, reliable and valid. With the advent of new technology and modern consumer patterns we may be witnessing an increase in problematic shopping behaviour. It is likely that new Internet-related technologies can greatly facilitate the emergence of problematic shopping behaviour because of factors such as accessibility, affordability, anonymity, convenience, and disinhibition. Therefore, we encourage other researchers to consider using the BSAS in epidemiological studies and treatment settings.

Want to take the test?  

Answer each of the following questions with one of the following five responses: ‘completely disagree’, ‘disagree’, ‘neither disagree nor agree’, ‘agree’, and ‘completely agree’.

  • You think about shopping/buying things all the time
  • You shop/buy things in order to change your mood
  • You shop/buy so much that it negatively affects your daily obligations (e.g., school and work)
  • You feel you have to shop/buy more and more to obtain the same satisfaction as before.
  • You have decided to shop/buy less, but have not been able to do so
  • You feel bad if you for some reason are prevented from shopping/buying things
  • You shop/buy so much that it has impaired your well-being

If you answer “agree” or “completely agree” on at least four of the seven items, you may be a shopping addict.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Aboujaoude, E. (2014). Compulsive buying disorder: A review and update. Current Pharmaceutical Design, 20, 4021-4025.

Andreassen, C. S. (2014). Shopping addiction: An overview. Journal of Norwegian Psychological Association, 51, 194–209.

Andreassen, C.S., Griffiths, M.D., Pallesen, S., Bilder, R.M., Torsheim, T. Aboujaoude, E.N. (2015). The Bergen Shopping Addiction Scale: Reliability and validity of a brief screening test. Frontiers in Psychology, 6:1374. doi: 10.3389/fpsyg.2015.01374.

Davenport, K., Houston, J. & Griffiths, M.D. (2012). Excessive eating and compulsive buying behaviours in women: An empirical pilot study examining reward sensitivity, anxiety, impulsivity, self-esteem and social desirability. International Journal of Mental Health and Addiction, 10, 474-489.

Maraz, A., Eisinger, A., Hende, Urbán, R., Paksi, B., Kun, B., Kökönyei, G., Griffiths, M.D. & Demetrovics, Z. (2015). Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population and in shopping centres. Psychiatry Research, 225, 326–334.

McQueen, P., Moulding, R., & Kyrios, M. (2014). Experimental evidence for the influence of cognitions on compulsive buying. Journal of Behavior Therapy and Experimental Psychiatry, 45, 496–501.

Workman, L., & Paper, D. (2010). Compulsive buying: A theoretical framework. Journal of Business Inquiry, 9, 89–126.

Deal love: Bargain hunting as an addiction

“Bargain hunting may save money, but for some people, looking for the next ‘great deal’ becomes an addiction. The call of the clearance rack wins out over practical matters – like whether you need or want what you found, or even have a place to put it” (Tesh Media, ‘Are You Addicted To Bargain Hunting?’)

A couple of weeks ago, I did some background research for a newspaper interview on the psychology of bargain hunting (only for the journalist then to interview somebody else about it). Instead of wasting all the material collected, I decided to use it for this article. Most of the material in this article borders on ‘pop psychology’ but I found it interesting nonetheless. For instance, in a recent article on the BBC News website, the (anonymous) author provided some basic rules on how to be a more savvy shopper and bargain hunter (which I am quoting verbatim):

  • “Try to avoid stores that are too busy with loud music. This can confuse and distract you from judging what is a genuine offer.
  • Ask the sales rep to repeat the sales details in a clear and slow manner and if possible ask him/her to write them down.
  • Before you make a decision take a break, count from one to ten and think again about the benefits and perils of the offer.
  • Can you shop alone? Peer pressure has been proven to be a key indicator for individuals buying products that they do not need.
  • Never shop when you are feeling emotionally upset. Purchasing to overcome any mood or behavioural troubles is not beneficial in the long term.
  • Go shopping after a meal or when in a good and clear mood. There is evidence that shopping when you feel peckish can make you spend more than intended”.

As soon as we enter any shop (online or offline) we are being bombarded with psychological tactics in an attempt to get us to buy more products (such as selling products that have a price ending in 99p). The BBC article interviewed consumer psychologist Dr. Dimitri Tsivrikos who said:

“These prices are obviously used to convince you that you are spending less than you actually are. A price reduction makes it even more tempting. The bargain price is appealing to you because it challenges the status quo. The retailer appears not to be in complete control of the final price of the product, and this makes you feel that you are now in control. And because of that you feel you can negotiate the final price that you have to pay – whether that is the sale price or even a buy one get one free deal…Brain studies have shown that when we are excited by a bargain, this interferes with your ability to clearly judge whether it is actually a good offer or not”.

When I started researching online, I came across a number of articles claiming that for a small minority, bargain hunting was addictive (as the opening quote demonstrates). In another article on the Tesh Media website, reference was made to April Lane Benson’s edited book I Shop, Therefore I Am. According to that article (which merges bargain hunting addiction with shopping addiction more generally):

“[Benson] says that when it comes to bargain-hunting addictions, what people buy isn’t as important as how big the price reduction is. In fact, the bigger the price cut, the more tempting a purchase is. After all, if something’s 80% off the original price – you’re saving 80 percent! What you may not consider is that by not buying, you’ll save 100%. Bargain addicts also make illogical purchases, like grabbing up sale-price auto parts for cars they don’t own, or bargain kid’s clothes for children they don’t have…So, why is a bargain-hunting addiction so common? Tim Kasser, a professor of psychology at Knox College in Illinois, says it’s a way for people to ease insecurities, and feel more competent and in control. In fact, shopping addicts often don’t realize they have a problem, even when the bags and bills start stacking up. It usually takes a big event to bring it to their attention, like divorce, a new baby, unemployment, or retirement. Or they simply max out their credit cards, and have no more spending power”

In the same article published on the Tech Media website, it claimed the five signs of being ‘addicted’ to bargain hunter were:

  • “You hit sales and clearance racks when you feel angry or blue. Or you feel guilty after shopping and hide your purchases.
  • You spend more money than you can afford.
  • You see sales as opportunities you can’t pass up.
  • Another clue you’re a bargain addict: You spend so much time tracking down deals that it intrudes on your time with family and friends.
  • You often forget what you bought, and find things in your closets you’ve never used”.

Obviously some of these ‘warning signs’ tap into what I believe are the core components of addiction (such as the fourth bullet point that taps into ‘conflict’), however, most of the criteria have nothing to do with ‘addiction’ whatsoever. Using bargain-hunting as a way of making oneself feel better mirrors what is found in other addictions, but characteristics such as not being able to pass up a bargain, and forgetting what has been bought are not core signs of addiction but are idiosyncratic consequences that specifically relate to bargain hunting. Another online article also noted:

“According to new survey findings from Consumer Reports, 23% of women say they sometimes buy things they don’t need just because they’re on sale. For most of us, getting a discount is enough of a reward: 80% say they would hunt for a bargain even if money weren’t an issue for them. In general, the survey found bargain shopping has increased significantly, from 76% in 2011 to 83% today. That shift may be due in part to the growing use of smartphone coupons, which has increased from 11% in 2011 to 24% today. Human psychology may help explain the irresistible allure of a discount. Research suggests that people tend to enjoy bargains, regardless of whether any financial gain is involved. You might even be able to blame your bargain hunting on Mom and Dad, because some experts say genetic differences make certain people predisposed to finding pleasure in raiding the sale rack”.

This paragraph provided a hyperlink to some genuine academic research carried out by Dr. Peter Darke and his colleagues (published in a 2006 issue of the Journal of Applied Social Psychology). They carried out a couple of experiments examining both the financial and non-financial motivations underlying bargain hunting. They reported that:

“Subjects read scenarios that described the purchase of a television set. Scenarios differed in terms of whether a bargain was received, whether there was personal financial gain, and whether the sale was acquired through skill or luck. The results suggest that subjects generally enjoyed bargains regardless of any financial gain, thereby implying that nonfinancial motives might also be involved. Surprisingly, bargains acquired skillfully were not enjoyed more than lucky bargains. Thus, achievement motives could not explain why subjects enjoyed bargains when there was no associated financial gain. Instead, it seemed that acquiring a bargain was primarily considered a matter of luck”.

I was also interested in the claims that bargain hunting might be underpinned by genetic influences. These claims were made by Mark Ellwood in his 2013 book Bargain fever: How to shop in a discounted world. Ellwood summarized his book in an article for Time magazine and wrote:

“As it turns out, a passion for finding bargains is genetically preprogrammed in all humans, although it’s activated much more in some than others. Spotting special offers triggers a release of dopamine, the feel-good neurotransmitter that I like to think of as ‘buyagra’. Dopamine is such a powerful chemical that our brains have developed a built-in system to clean it up as quickly as possible. One in four Caucasians has an otherwise harmless flaw in what’s known as the COMT gene. While the rest of us can flush our brains free of dopamine with the efficiency of a Dyson, those with an iffy COMT gene can brandish only a hand broom. It takes more time and effort to flush their brains clean of buyagra – and so they are physiologically more prone to splurge, especially on bargains”.

Ellwood claimed that as soon as “bargain addicts sees one ‘Sale’ sign – cue a jolt of dopamine – they’re hooked”. More specifically, he goes on to argue that:

“Of course, a propensity for bargain hunting isn’t purely genetic…Many hardcore coupon cutters I’ve interviewed cite hardscrabble childhoods or food-bank visits as the foundation of their frugality. Certainly, in the past decade, deal hunting has gone from a sign of indigence to one of intelligence; thanks to the roiling economy and an uncertain future, more people have migrated to the markdown section than ever before…Internet-equipped smartphones turned price comparison into a one-step process in your palm — the practice known as showrooming that’s so detested by retailers. But in our search for bargains, we would do well to ask ourselves whether we are really trying to economize or whether we’re being driven by an even stronger impulse: the chemical drive to get a good price”.

Given that I believe shopping can be an addiction in a minority of individuals, it doesn’t take too much of a leap to suggest bargain hunting could be an addiction (or even a sub-type of shopping addiction). However, as far as I am aware, there has never been any empirical research examining ‘bargain hunting addiction’ more specifically. Based on the few online articles that I read, it certainly appears that we are living in a time and an age where such research would be worth carrying out.

Dr. Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

BBC News (2015). The psychology of shopping for bargains. Located at: http://www.bbc.co.uk/consumer/23818336

Benson, A.L. (2000). I Shop Therefore I Am: Compulsive Buying and the Search for Self. Jason Aronson Inc. Publishers.

Consumer Reports (2014). America’s bargain-hunting habits. What shoppers will and won’t do to save a buck. April 30. Located at: http://www.consumerreports.org/cro/news/2014/04/america-s-bargain-hunting-habits/index.htm

Darke, P. R., & Freedman, J. L. (1995). Nonfinancial Motives and Bargain Hunting1. Journal of Applied Social Psychology, 25(18), 1597-1610.

Davenport, K., Houston, J. & Griffiths, M.D. (2012). Excessive eating and compulsive buying behaviours in women: An empirical pilot study examining reward sensitivity, anxiety, impulsivity, self-esteem and social desirability. International Journal of Mental Health and Addiction, 10, 474-489.

Ellwood, M. (2013). The genetics of bargain hunting. Time, October 21. Located at: http://ideas.time.com/2013/10/21/the-genetics-of-bargain-hunting/

Ellwood, M. (2013). Bargain fever: How to shop in a discounted world. London: Portfolio.

Lebowitz, S. (2014). Extreme bargain hunters: How far would you go for a deal. LearnVest, May 2. Located at: http://www.learnvest.com/2014/05/extreme-bargain-hunters-how-far-would-you-go-for-a-deal-123/

Maraz, A., Eisinger, A., Hende, Urbán, R., Paksi, B., Kun, B., Kökönyei, G., Griffiths, M.D. & Demetrovics, Z. (2015). Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population and in shopping centres. Psychiatry Research, 225, 326–334.

Tesh Media Group (2015). Are you addicted to bargain hunting? Located at: http://www.tesh.com/story/money-and-finance-category/are-you-addicted-to-bargain-hunting/cc/12/id/9141

Williams, A. (2013). Bargain fever: The new secrets of shopping in a discounted world. The Week, November 5. Located at: http://theweek.com/articles/457383/bargain-fever-new-secrets-shopping-discounted-world

Hello, good buy: Another look at shopping addiction

With only a few shopping days left until Christmas, I thought I would take another (hopefully topical) look at shopping addiction. Earlier this year, the Journal of Psychoactive Drugs published a paper by Dr. Heidi Hartston on the case for shopping as an addiction. She argued that the main factors that contribute to shopping addictions are (i) a hyper-stimulating experience (or an experience that was hyper-stimulating during initial exposures); (ii) easy accessibility or a high likelihood of frequent engagement; and (iii) vulnerability to addiction, which can be genetically present or can be created by neuroadaptation or reward deficiency syndrome.

In the section of her paper on the creation of hyper-stimulating experiences, Hartston claimed that in 1903 when Coca-Cola removed the cocaine out of their product, their marketing research found increasingly sophisticated ways to act on the brain’s reward circuitry by utilizing (i) advertising, (ii) product experience and (iii) packaging. According to Harston:

“Neuromarketing is the use of scientific brain research to potentiate the effectiveness of product marketing. This research uses fMRI brain imaging, EEG, skin moisture levels, heart rate, breathing patterns, eye movement and pupil dilation among other scientific measures. Marketing firms have spent 6.8 billion dollars in research (leading to 117 billion in advertising) learning to maximize the influence that branding, packaging, product placement and ad content can have on shopper decisions to buy. Many neuromarketing studies bypass the conscious adult rational decision-making brain functions to maximize excitement, emotional attachment, brand attachment, reward pathway activation, medial prefrontal identification and oxytocin stimulation, influencing impulsive buying decisions in ways individuals are not aware of or informed about (Robischon 2010)”

She then went on to claim that huge multi-national companies like Disney, Google, Frito-Layand and CBS (as well as large election campaigns) use these neuromarketing techniques to examine reactions by consumers (and voters) to their brands (or candidates) and then alter their advertising strategies accordingly. To support these claims, Hartston notes:

“A few examples of scientifically informed marketing include incorporating the color red (think of the coke can) resulting in attributions of intelligence and power to owning a product or to sales people (Elliot & Aarts 2011). ‘Sneaker radio’, a muzak-like soundtrack designed for use in athletic shoe stores, is designed to slow a shopper’s pace through the store and increase impulsive purchases. Studies using fMRI scans can identify which ad strategies trigger the consumer to strongly desire a product, saying they are ‘itching to buy’ (Thompson 2003). Bypassing interaction with the cortex and maximizing stimulation of emotional and reward areas can create hyperstimulating and difficult to resist marketing and can sabotage a vulnerable shopper’s intentions and efforts to resist buying”.

Hartston also makes further interesting observations in how commercial companies can hyper-stimulate shopping by exaggerating the sense of importance to the buying of products, or to the process of shopping itself. Shopping is a behaviour that has the capacity to become a highly rewarding experience. Such rewards can include excitement, identity affirmation, accomplishment, and praise. For a minority, shopaholism may become a difficult behaviour to break. Such observations not only have implications for shopping purchases but also behaviours that I study in my own research such as gambling. In relation to shopping addiction and increased accessibility, Hartston noted that:

“Behaviors may not reach the intense level of [dopamine] hyperstimulation that drugs do when each separate exposure is compared. However, because addictive behaviors are more easily accessible and more frequently engaged in than drug use (more exposures per day or week), the net effect of many more frequent exposures can make an addictive behavior hyperstimulating enough to have similar behavioral and physiological consequences as drugs”.

Comparing two different drug addictions – nicotine addiction and heroin addiction – she notes that nicotine clearly has a much weaker reward stimulation (per exposure) but can be equally addictive as heroin. The key difference is obviously the frequency as smokers will continually smoke cigarettes throughout the day whereas the number of times a heroin addict will take heroin during the day will be considerably less. In essence, Hartston argued:

“More exposures means more pairings of use and mild hyperstimulation, more encoding of the positive associations with smoking in memory, more consistent hyperstimulation of DA reward areas and more ease in increasing use. Due to its ease of availability, someone who tries smoking is more likely to become addicted than someone who tries heroin (Hilts 2009)”.

Relating this to shopping, Hartston makes the point that shopping is no longer something that is time limited by closed shops. The internet has brought the potential for 24/7 shopping. As with other activities with the potential for addiction (e.g., gambling, video gaming, sex), the internet has brought easy access, high availability, convenience, anonymity, dishinibition, and escape. As Hartston rightly asserts:

“A shopper can browse or purposefully seek target items during many stolen moments each day, from almost any location, or for extended amounts of time whenever a break may occur. Impulses to buy can be acted on immediately, without the protective time delay there used to be. And the steps to completing a purchase have become shortened, with credit card numbers already saved and one-click purchasing options additionally catering to impulsivity”.

Finally, Hartston argues that brain changes associated with Reward Deficiency Syndrome make it harder to stop the behaviors like excessive shopping. There is growing evidence that both chemical and behavioural addictions not only trigger changes in dopamine reward physiology “but also to its cortical connections, thereby impairing self-regulation”. Any person is responsible for their own behaviour but Harston argues that changes to the brain’s physiology makes it harder for vulnerable and susceptible people to control such behaviours. As Harston points out:

“Actions ‘preferred’ (valued at higher importance) by hyperstimulated striatal neurons are more likely to occur despite the addict’s conscious insight (Lau & Glimcher 2008; Hikosaka et al. 2008; Hikosaka, Nakamura & Nakahara 2006). This means that when desires become addictions they can have an overriding command over behavior and decision making, which is difficult to interrupt even in the presence of insight or higher goals. Addicted brains also show less age-related expansion of white matter, reflecting a loss of learning capacity and difficulty making new choices, further inhibiting an addict’s control over impulsive reward seeking behaviors (Goldstein & Volkow 2002). People who find themselves in the trap of addiction, whether to a drug or a behavior like shopping, need to be able to access effective interventions and support in order to stop the problematic behavior and prevent relapses”

Shopping appears to be the latest normal everyday behaviour (along with behaviours like exercise, eating and sex) to have been pathologized. However, (as I noted in my previous blog on shopaholism), there does seem to be some empirical evidence that a small minority of people appear to display addictive-like symptoms as a result of their shopping behaviour. Dr. Harston has done a good job in pointing out of the biological and situational reasons for how and why such addictions may develop.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, U 

Further reading

Elliot, A. & Aarts, H. (2011). Perception of the color red enhances the force and velocity of motor output. Emotion, 11, 445–49.

Goldstein, R. & Volkow, N. (2002). Drug addiction and its underlying neurobiological basis: Neuroimaging evidence for the involvement of the frontal cortex. American Journal of Psychiatry, 159, 1642–52.

Griffiths, M.D. (2010). Internet abuse and internet addiction in the workplace. Journal of Worplace Learning, 7, 463-472.

Hartston, H. (2012). The case for compulsive shopping as an addiction. Journal of Psychoactive Drugs, 44, 64–67.

Hikosaka, O., Nakamura, K., & Nakahara, H. (2006). Basal ganglia orient eyes to reward. Journal of Neurophysiology, 95, 567–84.

Hikosaka, O., Bromberg-Martin, E., Hong, S. & Matsumoto, M. (2008). New insights on the subcortical representation of reward. Current Opinion in Neurobiology, April 18, 203–08.

Hilts, P. (1994). Is nicotine addictive? It depends on whose criteria you use. New York Times. August 2.

Lau, B. & Glimcher, P. (2008). Value representations in the primate striatum during matching behavior. Neuron, 58, 451–63.

Robischon, N. (2010.) Neuromarketing the 2010 elections: Scoring campaign ads. Fast Company. Nov 5. Available at http://www.fastcompany.com/1700207/campaign-ads-and-neuromarketing

Thompson, C. 2003. There’s a sucker born in every medial prefrontal cortex. New York Times Magazine. October 26, 54–65.

Widyanto, L. & Griffiths, M.D. (2006). Internet addiction: A critical review. International Journal of Mental Health and Addiction, 4, 31-51.

Shop until you drop! Can shopping really be addictive?

So far in my articles in this blog, I have tried to argue that behaviours such as gambling, sex, and video game playing can all be viewed as potentially addictive. Empirical research also suggests that the form of addictive behaviour someone develops may depend upon their gender. For instance, men are more likely to be addicted to drugs, gambling and sex whereas women are more likely to suffer from the so-called “mall disorders” such as eating and shopping. For instance, the vast majority of compulsive shoppers (up to 80%) are female.

Compulsive buying has been reported as a way to alter a verity of negative feelings, by achieving short-term gratification through shopping. As with other addictive behaviours, this reward gives shopping its addictive potential, reinforcing the behaviour through pleasure, attention and praise, thereby driving the repetitive and compulsive processes. Compulsive buyers do not buy so much to acquire or gain use from their purchases. Instead they do so to achieve this reward, through the buying process itself. Such repetitive behaviour can – in extreme cases – be problematic. However, those affected may not initially see the behaviour as a problem. In fact, at an early stage it may be seen as providing a quick, perhaps impulsive, relief from anxiety or emotional distress. Consequently, individuals may be unaware of the negative consequences to follow

Compulsive buying disorder was first described clinically in 1915 by the German psychiatrist Emil Kraepelin in terms of what he called “buying maniacs”. More recently compulsive buying has been described as an example of ‘reactive impulse’. For most people, buying behaviour is a normal routine part of everyday life. However, for compulsive buyers, it is an inability to control an overpowering impulse to buy. This impulse can take over lives, resulting in negative consequences – similar to pathological gambling – such as debt, despite repeated attempts to stop. This can create further economic and emotional problems, such as stress and anxiety, for themselves and their families, which can drive the behaviour to continue by using shopping as a form of relief.

Compulsive buyers have been found to frequently have reactions of anxiety to both external and internal stimuli. Empirical research has highlighted that shopping binges are used as a reaction to such feelings. These binges have been found to be a quick relief from anxiety and stress. However, a compulsive buyer may eventually come to view their behaviour as a “loss of control,” creating additional anxiety and frustration. This can increase the ‘need’ to shop as to relive such feelings.

Prevalence rates of shopping have been highly variable and few studies have been carried out on nationally representative samples. A number of reports place it between 12% to 22% among younger people (including college and university students) though most estimates place it as ranging from 1% to 6% among adults with higher figures being reported in places such as the United States. Perhaps somewhat predictably, low levels of self-esteem have also been reported in compulsive buying populations. It is suggested that compulsive behaviours, particularly compulsive buying, are an attempt to temporarily relieve these feelings of low self-esteem by using the reward gained from buying as validation. Alternatively, low self-esteem may be a negative outcome of engaging in these behaviours, which creates the need for validation.

The direction of the relationship is still debated, causing increasing interest in research. Many compulsive buyers display a clear desire to please through their spending habits, portraying a sense of social desirability. This is often done through buying gifts for others, often with the belief that such gifts will make their recipients happy. Pleasing others is seen as a way of getting positive attention or being liked, possibly to boost low self-esteem and receive further rewarding properties. Therefore, the product being bought has no direct effect on the individual. It is the process of buying that creates reward, resulting in a boosting of self-esteem and relief from anxiety that may have increased if the impulse to buy had not been met.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Black, D. W. (2007) A review of compulsive buying disorder. World Psychiatry, 6, 14-18.

Davenport, K., Houston, J. & Griffiths, M.D. (2012). Excessive eating and compulsive buying behaviours in women: An empirical pilot study examining reward sensitivity, anxiety, impulsivity, self-esteem and social desirability. International Journal of Mental Health and Addiction, DOI 10.1007/s11469-011-9332-7.

Dittmar, H. (2005). Compulsive buying-a growing concern? An examination of gender, age, and endorsement of materialistic values as predictors. British Journal of Psychology, 96, 467-491.

Hodgson R.J., Budd R. & Griffiths M. (2001). Compulsive behaviours (Chapter 15). In H. Helmchen, F.A. Henn, H. Lauter & N. Sartorious (Eds) Contemporary Psychiatry. Vol. 3 (Specific Psychiatric Disorders). pp.240-250. London: Springer.

Koran, L.M., Faber, R.J., Aboujaoude, E., Large, M.D., & Serpe, R.T. (2006). Estimated prevalence of compulsive buying behavior in the United States. American Journal of Psychiatry, 163, 1806-1812.

Kukar-Kinney, M., Ridgway. N.M & Monroe, K.B (2009) The relationship between consumers’ tendencies to buy compulsively and their motivations to shop and buy on the internet, Journal of Retailing, 85, 298–307.

MacLaren, V.V., & Best, L.A. (2010). Multiple addictive behaviors in young adults: Student norms for the Shorter PROMIS Questionnaire. Addictive Behaviors, 35, 252-255.

Sussman, S., Lisha, N. & Griffiths, M.D. (2011). Prevalence of the addictions: A problem of the majority or the minority? Evaluation and the Health Professions, 34, 3-56.