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.

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.

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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.

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

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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.