Arash Emamzadeh

Compulsive Behaviors

Compulsive shopping: a guide to causes and treatment, reviewing the latest research on the treatment of compulsive shopping..

Posted June 27, 2022 | Reviewed by Gary Drevitch

  • What Is a Compulsive Behavior?
  • Find an Obsessive-Compulsive (OCD) Therapist
  • Compulsive shopping refers to a preoccupation with buying goods and services and spending money.
  • Compulsive shopping is associated with distress, financial difficulties, reduced quality of life, and family and marital problems.
  • The most promising treatment for compulsive shopping is group psychotherapy, primarily cognitive-behavioral therapy.

StockSnap/Pixabay

Published in the August issue of Current Opinion in Psychology , an article by D. W. Black reviews the latest research on the classification, assessment, and treatment of compulsive shopping.

What is Compulsive Shopping?

Compulsive shopping (sometimes called compulsive buying or shopping addiction) refers to a preoccupation with purchasing products and spending money.

Compulsive shopping shares several characteristics with other psychological disorders, including anxiety and mood disorders, substance abuse , impulse-control disorders, and obsessive-compulsive disorder (OCD). Therefore, many questions remain about how it should be classified.

More recently, compulsive shopping has been classified as a behavioral addiction . Though behavioral addictions such as gambling disorder do not involve the ingestion of addictive substances, they share some characteristics (e.g., repetitive behaviors).

How Is Compulsive Shopping Diagnosed?

According to a 2021 paper in the Journal of Behavioral Addictions , the proposed criteria for compulsive shopping include recurrent or persistent dysfunctional shopping-related thoughts and behaviors , as indicated by the following (examples in parentheses):

  • Preoccupation with shopping (an irresistible urge to buy a product).
  • Reduced control over buying behaviors (spending more time/money shopping than intended).
  • Buying products but not using them for the purposes they were intended to serve.
  • Using shopping to regulate mood (to experience a “high” or to reduce tension and boredom ).
  • As a result of compulsive buying, experiencing negative consequences or impairment ( guilt , shame , debt, relationship problems).
  • Negative mood and cognitive symptoms if attempting to stop (e.g., anxiety, agitation, anger , worry, rumination).
  • Despite the negative consequences, continuing to engage in dysfunctional shopping behavior.

The prevalence of compulsive shopping in American adults is estimated to be between 2 and 8 percent. About 80 to 94 percent of people with this condition are female. The onset is usually in late teens or early adulthood and, according to the author, “may correspond with emancipation from the nuclear family as well as with the age at which people first establish credit.”

Compulsive shopping can be episodic or chronic. Particularly when chronic, compulsive buying is associated with financial difficulties (debt, bankruptcy, and even shoplifting and other crimes), reduced quality of life, family and marital problems, and subjective distress (e.g., due to inability to control behavior).

Compulsive Shopping: Risk Factors, Comorbidity, and Differential Diagnoses

One major risk factor for compulsive shopping is childhood adversity . This includes having a “physically abusive or neglectful parent,” an “emotionally neglectful parent who demands the child earn their love through ‘good’ behavior,” or an “absent parent who has little time or energy for the child,” but also “families that have experienced financial reversals and fixate on lost luxury.”

In these dysfunctional family environments, possessions often “achieve importance as a means of easing suffering, boosting self-esteem , or restoring lost social status.”

Compared to healthy controls, first-degree relatives of people who shop compulsively are more likely to have the same condition or other mental health issues, such as anxiety disorders, mood disorders, and substance use disorders.

As for differential diagnosis, it is important to differentiate compulsive buying from bipolar disorder , in which case the buying behavior (during mania or hypomania ) is driven by euphoria and grandiosity—and to differentiate it from schizophrenia, in which the shopping behavior is more likely to be bizarre and related to delusions.

In terms of comorbidity , research shows that anxiety, mood, substance use, and personality disorders (especially avoidant, dependent, and obsessive-compulsive personality disorder) are prevalent in this group. Also prevalent are compulsive gambling, exercising, and internet use.

On “dimensional ratings,” the author notes, people with this condition “tend to have elevated scores for depression, trait impulsivity, and ratings of attention deficit hyperactivity disorder , but have low self-esteem.”

compulsive buying disorder essay

And on the five-factor model of personality (the Big Five), they have lower scores on agreeableness and conscientiousness but higher scores on neuroticism and novelty-seeking.

How Is Compulsive Shopping Treated?

A variety of group therapies have been used in the treatment of compulsive buying behavior, most of which use cognitive-behavioral therapy techniques.

The goal of treatment is to “help persons interrupt and control their problematic buying behavior, establish healthy purchasing patterns, and develop healthy coping, stress management , and problem-solving skills.” Pharmacotherapy is also useful, especially to manage certain symptoms. Pharmacotherapy includes medications such as naltrexone (an opioid antagonist), memantine (an NMDA antagonist), and antidepressants , particularly serotonin-specific reuptake inhibitors (SSRIs).

A systematic review of treatments for compulsive buying (17 psychotherapies and 12 pharmacotherapies) found that based on the available evidence, group psychotherapy was the “most promising treatment option.”

Concluding Thoughts

According to Black, compulsive shopping is “characterized by excessive or poorly controlled [shopping] preoccupations or urges that lead to subjective distress and can impair functioning.”

Though it is not clear whether it is better classified as an anxiety/ mood disorder or a behavioral addiction, compulsive shopping is often comorbid with anxiety disorders, mood disorders, substance abuse, and personality disorders (particularly Cluster C or anxious-fearful disorders).

The most promising treatment is group psychotherapy, which often uses elements of cognitive-behavioral therapy (CBT)—e.g., identifying the cues that trigger compulsive shopping, learning the consequences of engaging in the problem behaviors, stress management, and exposure and response prevention.

Let me end with a note of caution: Frequent shopping or spending a lot of money do not necessarily indicate a compulsion. Indeed, normal buying may appear compulsive on certain occasions (e.g., during holidays, birthdays, after winning the lottery). Therefore, it is important to see a therapist, instead of self-diagnosing, if you are concerned about your shopping behavior.

To find a therapist near you, visit the Psychology Today Therapy Directory .

Arash Emamzadeh

Arash Emamzadeh attended the University of British Columbia in Canada, where he studied genetics and psychology. He has also done graduate work in clinical psychology and neuropsychology in U.S.

  • Find a Therapist
  • Find a Treatment Center
  • Find a Psychiatrist
  • Find a Support Group
  • Find Teletherapy
  • United States
  • Brooklyn, NY
  • Chicago, IL
  • Houston, TX
  • Los Angeles, CA
  • New York, NY
  • Portland, OR
  • San Diego, CA
  • San Francisco, CA
  • Seattle, WA
  • Washington, DC
  • Asperger's
  • Bipolar Disorder
  • Chronic Pain
  • Eating Disorders
  • Passive Aggression
  • Personality
  • Goal Setting
  • Positive Psychology
  • Stopping Smoking
  • Low Sexual Desire
  • Relationships
  • Child Development
  • Therapy Center NEW
  • Diagnosis Dictionary
  • Types of Therapy

January 2024 magazine cover

Overcome burnout, your burdens, and that endless to-do list.

  • Coronavirus Disease 2019
  • Affective Forecasting
  • Neuroscience

Volume 7 Supplement 1

International Society on Brain and Behaviour: 3rd International Congress on Brain and Behaviour

  • Poster presentation
  • Open access
  • Published: 17 April 2008

Compulsive buying: a review

  • Pandelis Pazarlis 1 ,
  • Konstantinos Katsigiannopoulos 1 ,
  • Georgios Papazisis 1 ,
  • Stavroula Bolimou 1 &
  • Georgios Garyfallos 2  

Annals of General Psychiatry volume  7 , Article number:  S273 ( 2008 ) Cite this article

4947 Accesses

4 Citations

Metrics details

Compulsive or pathological buying (or oniomania) is defined as frequent preoccupation with buying or impulses to buy that are experienced as irresistible, intrusive, and/or senseless. The buying behavior causes marked distress, interferes with social functioning, and often results in financial problems. It should be diagnosed as impulse control disorder not otherwise specified (ICD-10 F63.9). Compulsive buying has received increased research attention in the last decade.

Materials and methods

This review summarizes the literature on compulsive buying published during the past 15 years. Two medical libraries (MEDLINE, COCHRANE) were searched in order to investigate the related articles.

Prevalence studies of compulsive buying found a rate between 1 and 6% in the general population. About 90% of those affected are female. Onset occurs in the late teens or early twenties, and the disorder is generally chronic. Psychiatric comorbidity is frequent, particularly mood, anxiety, substance use, eating, impulse control and obsessive-compulsive disorders. In other cases, bipolar disorders express themselves as impulsive behaviours i.e. pathological buying. Treatment has not been well delineated, but individual and group psychodynamic psychotherapy or cognitive-behavioural therapy may be helpful. Serotonin re-uptake inhibitors (SSRI's) may help some patients regulate their buying impulses. Other pharmacological agents have also been used -opioid antagonists, mood stabilizers, and atypical antipsychotics.

Conclusions

Compulsive buying is characterized by repetitive compulsive and excessive misappropriated buying. Labels for this pathological behaviour vary and its classification is uncertain. To date, there is no consistent concept for diagnosis and treatment.

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

PubMed   Google Scholar  

Hollander E, Allen A: Is Compulsive Buying a Real Disorder, and Is It Really Compulsive?. Am J Psychiatry. 2006, 163 (10): 1670-1671. 10.1176/appi.ajp.163.10.1670.

Article   PubMed   Google Scholar  

Marcinko D, Karlovic D: Oniomania-successful treatment with fluvoxamine and cognitive-behavioral psychotherapy. Psychiatr Danub. 2005, 17 (1-2): 97-100.

Mitchell JE, Redlin J, Wonderlich S, Crosby R, Faber R, Miltenberger R, Smyth J, Stickney M, Gosnell B, Burgard M, Lancaster K: The relationship between compulsive buying and eating disorders. Int J Eat Disord. 2002, 32 (1): 107-11. 10.1002/eat.10053.

Download references

Author information

Authors and affiliations.

Panhellenic Association for Continual Medical Research (PACMeR), Greece

Pandelis Pazarlis, Konstantinos Katsigiannopoulos, Georgios Papazisis & Stavroula Bolimou

2nd Department of Psychiatry, Aristotle University of Thessaloniki, Greece

Georgios Garyfallos

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article.

Pazarlis, P., Katsigiannopoulos, K., Papazisis, G. et al. Compulsive buying: a review. Ann Gen Psychiatry 7 (Suppl 1), S273 (2008). https://doi.org/10.1186/1744-859X-7-S1-S273

Download citation

Published : 17 April 2008

DOI : https://doi.org/10.1186/1744-859X-7-S1-S273

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Bipolar Disorder
  • Atypical Antipsychotic
  • Impulse Control
  • Psychiatric Comorbidity
  • Mood Stabilizer

Annals of General Psychiatry

ISSN: 1744-859X

compulsive buying disorder essay

Change Password

Your password must have 6 characters or more:.

  • a lower case character, 
  • an upper case character, 
  • a special character 

Password Changed Successfully

Your password has been changed

Create your account

Forget yout password.

Enter your email address below and we will send you the reset instructions

If the address matches an existing account you will receive an email with instructions to reset your password

Forgot your Username?

Enter your email address below and we will send you your username

If the address matches an existing account you will receive an email with instructions to retrieve your username

Psychiatry Online

  • February 01, 2024 | VOL. 181, NO. 2 CURRENT ISSUE pp.83-170
  • January 01, 2024 | VOL. 181, NO. 1 pp.1-82

The American Psychiatric Association (APA) has updated its Privacy Policy and Terms of Use , including with new information specifically addressed to individuals in the European Economic Area. As described in the Privacy Policy and Terms of Use, this website utilizes cookies, including for the purpose of offering an optimal online experience and services tailored to your preferences.

Please read the entire Privacy Policy and Terms of Use. By closing this message, browsing this website, continuing the navigation, or otherwise continuing to use the APA's websites, you confirm that you understand and accept the terms of the Privacy Policy and Terms of Use, including the utilization of cookies.

Is Compulsive Buying a Real Disorder, and Is It Really Compulsive?

  • Eric Hollander M.D.
  • Andrea Allen Ph.D.

Search for more papers by this author

The article in this issue by Koran et al. raises several intriguing questions regarding a novel proposed psychiatric disorder: compulsive buying. DSM provides a working model of categories and diagnostic criteria for psychiatric disorders. DSM is constantly evolving and research planning is underway for DSM-V. Changes to DSM-V being considered include the creation of two broad new categories that may influence the conceptualization of compulsive buying.

A category related to obsessive-compulsive-related disorders might include disorders such as obsessive compulsive disorder, obsessive compulsive personality disorder, hoarding, body dysmorphic disorder, eating disorders, hypochondriasis, Tourette’s syndrome, Sydenham’s chorea or pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections, and pathological grooming disorders, such as trichotillomania, skin picking, and nail biting. Compulsive buying was not determined to be a good fit for this category. On the other hand, a parallel category under consideration is behavioral and substance addictions, which might include substance-related disorders and several impulse-control disorders (pathological gambling, pyromania, and kleptomania), as well as others currently in the category of impulse control disorders not otherwise specified (Internet addiction, impulsive-compulsive sexual behavior, and compulsive buying). The National Institute on Drug Abuse has considered behavioral addictions (such as compulsive buying) to be “cleaner” and more homogeneous models of substance addictions because these conditions may share clinical features and perhaps underlying brain circuitry, and these features and circuitry are not altered by the ingestion of exogenous substances. Similar phases seem to occur for behavioral and substance addictions: initially, episodes are characterized by increasing physiological and emotional arousal before the act; pleasure, high, or gratification associated with the act; and a decrease in arousal and feelings of guilt and remorse afterward. Tolerance and physiological withdrawal can also develop. Because an impulsive component (pleasure, arousal, or gratification) is involved in initiating the cycle, and a compulsive component is involved in the persistence of the behavior, these conditions may also be thought of as impulsive-compulsive disorders.

The creation of a condition such as compulsive buying might be associated with controversy and criticized by some as creating a trivial disorder; “medicalizing” a “moral” problem or creating a new disorder in order to sell more pharmaceuticals. Similar criticisms of attention deficit hyperactivity disorder (ADHD) and social anxiety disorder have been raised: that children with minor and natural levels of excess activity should not be “medicalized” or medicated or that because so many people are socially anxious, this is a natural trait not worthy of diagnosis or treatment. However, the issues involved in creating new diagnoses is complex.

In this issue, Koran et al. reported on a study of compulsive buying. They surveyed a large random sample of U.S. adults to estimate a prevalence rate and to characterize compulsive buyers. They and others have proposed names and diagnostic criteria for this problem and, as required for most DSM disorders, the criteria include significant distress or functional impairment, as well as criteria specific to the disorder. As is typical at this stage, the specific name and criteria differ from researcher to researcher and study to study, complicating the development of knowledge about the condition. Until a certain amount of evidence of a new disorder is accumulated, not enough is known to define criteria, but at a certain point, there is enough information to propose criteria. Including a disorder in DSM is very helpful for the advance of knowledge because researchers can then use the defined criteria in their new research, and the criteria can be refined over time as more research is completed.

Clearly, the behavioral addictions or impulse control disorders can be viewed from different perspectives, including: a medical perspective; a moral, ethical, or religious perspective; and a legal perspective. These behaviors exist on a continuum, perhaps in a normal distribution in the general population, with many individuals having some of the behaviors, a few showing none, and a few showing a great deal. However, in a subgroup of individuals, a biological vulnerability may result in impairment of control that leads to behavioral excess or disinhibition and is associated with significant levels of distress and functional impairment. Consideration that shopping is universal and making an unwise purchase from time to time is common, although research has shown that there are individuals whose compulsive buying is extreme and leads to significant distress and impairment. Using scores on the Compulsive Buying Scale (1) of 2 standard deviations below the mean, Koran et al. estimated the prevalence of compulsive buying to be 5.8%; even with a very strict criterion of 3 standard deviations below the mean, the prevalence would be 1.4%. Previous estimates based on smaller, less representative samples have ranged from 1.8% to 16%. Thus, whatever estimate is used, the prevalence is higher than or similar to disorders that receive considerable research and clinical attention, and it represents a sizable group suffering distress and or functional impairment. The impairment criteria are important because it is how compulsive buying as a disorder is differentiated from more normal, if excessive, buying. Koran et al. found that when using the criterion of 2 standard deviations on the Compulsive Buying Scale, the individuals had significantly more maladaptive shopping and buying attitudes and behaviors and more financial problems than the other respondents. The data for the group with 3 standard deviations shows consequences that were even more extreme. This sort of distribution applies to many disorders. As mentioned above, ADHD and social anxiety disorder are two examples. One might also look at a long-accepted disorder: major depressive disorder. Many people suffer from occasional sadness and days on which they are “blue,” but that does not diminish the importance of recognizing, researching, and treating major depressive disorder.

One can ask if people are morally responsible for their behavior if they commit unethical acts because of what has been classified as a mental disorder? Similarly, if an individual diagnosed with an impulse control disorder does something illegal, is he or she responsible? Having a diagnosable disorder does not eliminate the moral or legal consequences of bad behavior, although courts can require that the individuals receive treatment in order to prevent a recurrence of the problem. This can be seen with alcoholism, which has long been considered a disorder. If an alcoholic has an accident while driving under the influence, that is not considered a mitigating circumstance but the courts can require that the individual undergo treatment for their alcohol problem, along with any other sentencing requirements. Viewing compulsive buying from a medical perspective and as a diagnosable mental disorder has several advantages. It might facilitate routine screening for the condition by mental health professionals, and perhaps, even inclusion of the disorder in national prevalence surveys, which would help define the true prevalence of the disorder. It might also lead to the study of vulnerability factors for the development of the disorder, better characterization of brain-based circuits, and the development of effective psychosocial and medication treatments. Although prevention of overdiagnosis or possible misuse of diagnostic labels is important, these concerns should be balanced against the advancement of knowledge that could potentially lead to new treatments or prevention strategies for serious human problems.

Address correspondence and reprint requests to Dr. Hollander, Department of Psychiatry, Mt. Sinai School of Medicine, One Gustave L Levy Place, New York, NY 10029; [email protected] (e-mail.) Dr. Hollander has been a consultant to Ortho-McNeil, Abbott, and Forest; and has received research grants from NIMH, NIDA, NINDS, and OPD-FDA. Dr. Freedman has reviewed this editorial and found no evidence of influence from these relationships. Dr. Allen reports no competing interests.

1. Faber RJ, O’Guinn TC: A clinical screener for compulsive buying. J Consumer Res 1992; 19:459–469 Google Scholar

  • Introduction to consumer neuroscience
  • Self-control and compulsive buying behavior: The mediating role of ill-being perception 28 November 2023 | Cogent Business & Management, Vol. 10, No. 3
  • A comparison of buying disorder to addictive and obsessive–compulsive disorders on impulsivity, compulsivity, and reward processing: A narrative review 15 August 2023 | Current Psychology, Vol. 34
  • Üniversite Öğrencilerinin Sosyal Medya ve Kompulsif Çevrimiçi Alışveriş Bağımlılığı Arasındaki İlişkinin İncelenmesi 31 March 2023 | İnsan ve Toplum Bilimleri Araştırmaları Dergisi, Vol. 12, No. 1
  • TÜKETİCİ DAVRANIŞLARI AÇISINDAN KOMPULSİF SATIN ALMA DAVRANIŞINA YÖNELİK KAVRAMSAL BİR ÇALIŞMA 28 May 2022 | Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Vol. 12, No. 23
  • Consumers’ de-ownership as a predictor of dark-side digital acquisition behavior: Moderating role of moral intensity and collectivism Journal of Business Research, Vol. 138
  • Compulsive shopping behaviour and executive dysfunction in young adults 13 December 2021 | Applied Neuropsychology: Adult, Vol. 55
  • The Relationship Between Compulsive Buying and Hoarding in China: A Multicenter Study 15 October 2021 | Frontiers in Psychology, Vol. 12
  • Proposed diagnostic criteria for compulsive buying-shopping disorder: A Delphi expert consensus study Journal of Behavioral Addictions, Vol. 10, No. 2
  • Sneaking the dark side of brand engagement into Instagram: The dual theory of passion Journal of Business Research, Vol. 130
  • Predicting the severity of excessive buying using the Excessive Buying Rating Scale and Compulsive Buying Scale Journal of Obsessive-Compulsive and Related Disorders, Vol. 25
  • Buying-shopping disorder—is there enough evidence to support its inclusion in ICD-11? 3 January 2019 | CNS Spectrums, Vol. 24, No. 4
  • Materialism and compulsive buying behaviour Asia Pacific Journal of Marketing and Logistics, Vol. 30, No. 5
  • Cue-Reactivity, Craving, and Decision Making in Buying Disorder: a Review of the Current Knowledge and Future Directions 1 September 2017 | Current Addiction Reports, Vol. 4, No. 3
  • Compulsive buying behavior: Re‐evaluating its dimensions and screening 24 April 2017 | Journal of Consumer Behaviour, Vol. 16, No. 5
  • Dissociating Pathological Buying From Obsessive-Compulsive Symptoms Using Delay Discounting Zeitschrift für Psychologie, Vol. 225, No. 3
  • Gender Differences in Pathways to Compulsive Buying in Chinese College Students in Hong Kong and Macau Journal of Behavioral Addictions, Vol. 5, No. 2
  • A review of adverse events linked to dopamine agonists in the treatment of Parkinson’s disease 20 January 2016 | Expert Opinion on Drug Safety, Vol. 15, No. 2
  • Psychiatry Research, Vol. 237
  • Psychiatry Research, Vol. 240
  • Psychiatry Research, Vol. 244
  • Journal of Addictive Diseases, Vol. 35, No. 4
  • Impaired decision making under ambiguity but not under risk in individuals with pathological buying–behavioral and psychophysiological evidence Psychiatry Research, Vol. 229, No. 1-2
  • Impulsivity and compulsive buying are associated in a non-clinical sample: an evidence for the compulsivity-impulsivity continuum? 1 September 2015 | Brazilian Journal of Psychiatry, Vol. 37, No. 3
  • Life stressors and compulsive buying behaviour among adolescents in India South Asian Journal of Global Business Research, Vol. 4, No. 2
  • Balancing the balance: Self-control mechanisms and compulsive buying Journal of Economic Psychology, Vol. 49
  • Prevalence and construct validity of compulsive buying disorder in shopping mall visitors Psychiatry Research, Vol. 228, No. 3
  • Compulsive buying: Earlier illicit drug use, impulse buying, depression, and adult ADHD symptoms Psychiatry Research, Vol. 228, No. 3
  • Journal of Gambling Studies, Vol. 31, No. 4
  • Comprehensive Psychiatry, Vol. 57
  • Psychiatry Research, Vol. 225, No. 3
  • Journal of Asia-Pacific Business, Vol. 16, No. 1
  • PLOS ONE, Vol. 10, No. 10
  • The Korean Journal of Consumer and Advertising Psychology, Vol. 16, No. 2
  • Sexting, Cybersex, and Internet Use: The Relationship Between Adolescent Sexual Behavior and Electronic Technologies 4 December 2012
  • Journal of Korean Academy of Nursing, Vol. 43, No. 6
  • Journal of Affective Disorders, Vol. 136, No. 3
  • Psychiatry Research, Vol. 200, No. 2-3
  • Advances in Psychiatric Treatment, Vol. 18, No. 4
  • Asian Journal of Education, Vol. 12, No. 2
  • Comparison of Childhood Sexual Histories in Subjects with Pedophilia or Opiate Addiction and Healthy Controls Journal of Psychiatric Practice, Vol. 16, No. 6
  • Nonmotor symptoms in Parkinson’s disease: the dark side of the moon Future Neurology, Vol. 5, No. 6
  • Pathological gambling and compulsive buying: do they fall within an obsessive-compulsive spectrum? 1 April 2022 | Dialogues in Clinical Neuroscience, Vol. 12, No. 2
  • Addictive Behaviors in Comorbid Addiction and Mental Illness: Preliminary Results from a Self-Report Questionnaire Journal of Addiction Medicine, Vol. 4, No. 1
  • Compulsive Buying: Clinical Aspects
  • Journal of Neurology, Vol. 257, No. S2
  • Psychiatry Research, Vol. 178, No. 2
  • Journal of Counseling and Gospel, Vol. 15, No. null
  • Compulsive buying: A cognitive–behavioural model 19 February 2009 | Clinical Psychology & Psychotherapy, Vol. 16, No. 2
  • Journal of Contemporary Psychotherapy, Vol. 39, No. 4
  • Volitional disorders: A proposal for DSM-V 8 December 2009 | The World Journal of Biological Psychiatry, Vol. 10, No. 4-3
  • Korean Journal of Clinical Psychology, Vol. 28, No. 2
  • Comparison of Personality Traits in Pedophiles, Abstinent Opiate Addicts, and Healthy Controls Journal of Nervous & Mental Disease, Vol. 196, No. 11
  • Impulse Control and Related Disorders in Parkinson's Disease Annals of the New York Academy of Sciences, Vol. 1142, No. 1
  • Impulsive–Compulsive Buying Disorder: Clinical Overview 1 January 2008 | Australian & New Zealand Journal of Psychiatry, Vol. 42, No. 4
  • A Critique and Comparison of Two Scales from Fifteen Years of Studying Compulsive Buying 1 February 2008 | Psychological Reports, Vol. 102, No. 1
  • The Cognitive Behaviour Therapist, Vol. 1, No. 1
  • Perspectives Psy, Vol. 47, No. 1
  • Addiction Research & Theory, Vol. 16, No. 6
  • Annals of General Psychiatry, Vol. 7, No. S1
  • Revista de Psiquiatria do Rio Grande do Sul, Vol. 30, No. 1 suppl
  • CNS Drugs, Vol. 22, No. 5
  • Samuel R. Chamberlain, M.A.
  • Lara Menzies, B.A.
  • Barbara J. Sahakian, M.A., Ph.D.
  • Naomi A. Fineberg, M.A., M.R.C.Psych.
  • CNS Spectrums, Vol. 12, No. 6
  • CNS Spectrums, Vol. 12, No. 2
  • Anxiety and OC spectrum disorders over life cycle 12 July 2009 | International Journal of Psychiatry in Clinical Practice, Vol. 11, No. sup2
  • Korean Journal of Health Psychology, Vol. 12, No. 4
  • CNS Spectrums, Vol. 11, No. 12

compulsive buying disorder essay

  • Bipolar Disorder
  • Therapy Center
  • When To See a Therapist
  • Types of Therapy
  • Best Online Therapy
  • Best Couples Therapy
  • Best Family Therapy
  • Managing Stress
  • Sleep and Dreaming
  • Understanding Emotions
  • Self-Improvement
  • Healthy Relationships
  • Student Resources
  • Personality Types
  • Verywell Mind Insights
  • 2023 Verywell Mind 25
  • Mental Health in the Classroom
  • Editorial Process
  • Meet Our Review Board
  • Crisis Support

The Difference Between Impulsive and Compulsive Shopping

compulsive buying disorder essay

Steven Gans, MD is board-certified in psychiatry and is an active supervisor, teacher, and mentor at Massachusetts General Hospital.

compulsive buying disorder essay

Dan Dalton / Getty Images

What Is Impulsive Shopping?

What is compulsive shopping.

  • Important Differences
  • How to Cope

Who doesn't love a great sale? Hitting the shops, looking for a bargain, and buying aesthetically pleasing items may be considered benign "retail therapy" by some. For others, however, shopping can turn into a problem.

Impulsive buying and compulsive shopping are both shopping behaviors that can lead to feelings of regret and financial difficulties. While the two terms are sometimes used interchangeably, they are not the same, and there are important distinctions between them.

This article discusses how impulsive and compulsive shopping are defined and the signs of each behavior. It also covers what causes these problems and the steps people can take to manage their shopping.

Impulsive shopping involves buying items that a person was not planning to purchase. It often happens unexpectedly and in the heat of the moment, inspired by a "can't miss" sale or suddenly coming across covetable items that are too tempting to pass up.

Sometimes these impulsive purchases can be pretty harmless, if they are within a person's budget. But unfortunately, impulsive buying can also result in costly spending sprees that can wreak havoc on their finances.

Signs of Impulsive Shopping

Impulsive shopping is something that happens to most people on occasion. Some signs of impulse shopping:

  • Spending more money than intended
  • Going into stores that often trigger impulsive buys
  • Feelings of instant gratification after unplanned purchases
  • Frequently returning impulse purchases due to regret

Research suggests that impulsive shopping increased during the COVID-19 pandemic. Feelings of stress and anxiety combined with more time at home may have contributed. This demonstrates how people often use shopping to cope with emotions, relieve distress, and improve mood.

Unlike impulsive buying, compulsive shopping is more than just spending more than intended. It involves a compulsive need to buy items, many of which are not necessary. People who engage in compulsive shopping do so to improve their mood, improve their self-image, get social support, and cope with stress.

Compulsive shopping often leads to powerful feelings of shame, guilt, and remorse. People who shop compulsively are also prone to having financial, legal, and relationship problems because of their overspending.

While not recognized as a distinct condition in the " Diagnostic and Statistical Manual of Mental Disorders, 5th Edition " (DSM-5), the tool healthcare providers utilize to diagnose mental health conditions, many experts believe that compulsive shopping is a form of behavioral addiction .

While estimates vary, some research indicates that anywhere between 1% and 30% of the U.S. population may engage in compulsive buying behavior.

Signs of Compulsive Shopping

Because shopping is an activity that everyone must do to some extent, it can be difficult to tell when shopping has crossed the line into compulsive buying. Many people love to shop and even spend more than they should, but this does not necessarily mean that they engage in compulsive behavior.

Some of the critical signs of compulsive shopping include: 

  • Declining financial health or high amounts of credit card debt
  • Distressed relationships due to spending or shopping too much
  • Hiding shopping or the amount spent
  • Losing control during shopping sprees
  • Shopping to avoid feeling guilty about a previous shopping spree
  • Shopping to relieve feelings of emotional distress
  • Spending more than a person can afford

Causes of Impulsive and Compulsive Shopping

Impulsive buying and compulsive shopping often stem from the pleasurable feelings that people get when they make purchases—planned or unplanned. The act of shopping releases endorphins and dopamine in the brain, creating pleasurable sensations. This can cause people to feel compelled to engage in the same behaviors in order to re-experience those feelings.

Some reasons people make impulsive or compulsive purchases:

  • They feel a need to purchase items that are on sale and the deal is just "too good to pass up."
  • They make purchases, regret them, and return the items that they bought.
  • They collect certain items and feel that they must complete each collection in order to feel satisfied.
  • They shop to help relieve feelings of emotional distress.
  • They shop in order to maintain a self-image as a sophisticated person with impeccable taste.
  • They are always on the hunt for certain "trophy" items that they feel they must own in order to feel happy.

Impulsive shopping often stems from a momentary temptation, while compulsive shopping is caused by a need to seek pleasure and relieve feelings of distress.

Impulsive vs. Compulsive Shopping

The important distinction between compulsive shopping and impulse buying lies with the internal motivation , or reason, for making purchases. While impulse buying is largely unplanned and happens in reaction to an external trigger—such as seeing a desired item in a shop—compulsive shopping is more inwardly motivated .

A person who engages in compulsive shopping will plan the shopping experience as a way to avoid or relieve uncomfortable internal feelings, such as anxiety.

Compulsive shopping is also more likely to lead to negative consequences than impulse shopping. Such effects may include running into financial difficulties, having arguments with family members, and experiencing problems with work.

People who engage in compulsive buying behavior are also more likely to fall into a pattern of addictive behavior. They shop more and more in an attempt to stave off stress and anxiety. This is how a shopping addiction develops.

How to Reduce Impulsive and Compulsive Shopping

Impulsive buying is something that happens to everyone from time to time. Compulsive shopping can be more serious and may require the help of a therapist to manage the underlying emotions that contribute to the behavior.

If you feel like your shopping behavior is causing problems in your life, you can use some self-help strategies to help get your shopping behavior under control.

  • Pay attention to your spending habits : Track your budget so you can see where your money goes each month. If you notice that you are overspending on specific items or engaging in too much impulsive shopping, you can take steps to change your spending habits.
  • Set a budget : Create a budget and plan how much you want to spend on different expenses. Sometimes, it is easier to control impulsive buying if you give yourself leeway to spend a small amount of "fun money" on more frivolous or impulsive purchases.
  • Pay with cash : Using credit cards makes it easier to overspend. Instead, use cash or a debit card so that you can see precisely how your purchases are affecting your bank account.
  • Minimize temptation : Avoid going to certain stores if you know that you are more likely to overspend in those shops. If you need to shop there, have a plan, set a strict budget, and bring a friend who can help keep you accountable.
  • Make yourself wait : If you have an urge to make an unplanned purchase, tell yourself that you have to wait a certain amount of time before you can go through with buying the item. Find ways to distract yourself in the meantime. You may find that the urge to buy the item starts to fade when you give yourself time to think about whether you need the item or not.

Dealing with compulsive shopping often requires a multidisciplinary approach, involving professional therapy , medication when indicated, and peer support. Talking to a financial advisor may also be beneficial.

While there is no cure for compulsive shopping, many people who engage in this behavior can regain a sense of control and improve their finances and relationships. Maintaining progress is essential since shopping is part of everyday life and cannot be avoided. Because the temptation is always present, people need to develop coping skills that help them manage their urge to shop excessively. 

Actions such as setting a budget, paying with cash, and instituting a waiting period are tactics that can help reduce impulsive spending. People experiencing compulsive spending would also benefit from talking to a healthcare provider and financial advisor.

A Word From Verywell

Being able to recognize the differences between impulsive and compulsive shopping is essential. While most people make impulsive buys sometimes, regular compulsive shopping is a sign of a more serious issue. 

While dealing with shopping issues can be challenging, there are steps that you can take. If you need help, talking to a healthcare provider and consulting with a financial expert can help get your life and finances back on track.

Wang S, Liu Y, Du Y, Wang X. Effect of the COVID-19 pandemic on consumers' impulse buying: The moderating role of moderate thinking . Int J Environ Res Public Health . 2021;18(21):11116. doi:10.3390/ijerph182111116

Granero R, Fernández-Aranda F, Mestre-Bach G, et al. Compulsive buying behavior: clinical comparison with other behavioral addictions .  Front Psychol . 2016;7:914. doi:10.3389/fpsyg.2016.00914

Basu B, Basu S, Basu J. Compulsive buying: an overlooked entity . J Indian Med Assoc . 2011;109(8):582-5.

Faber R. Impulsive and compulsive buying . In: Wiley International Encyclopedia of Marketing . doi:10.1002/9781444316568.wiem03007

Müller A, Brand M, Claes L, et al. Buying-shopping disorder-is there enough evidence to support its inclusion in ICD-11 ? CNS Spectr . 2019;24(4):374-379. doi:10.1017/S1092852918001323

By Elizabeth Hartney, BSc, MSc, MA, PhD Elizabeth Hartney, BSc, MSc, MA, PhD is a psychologist, professor, and Director of the Centre for Health Leadership and Research at Royal Roads University, Canada.  

Compulsive Buying Behavior as a Lifestyle Dissertation

Introduction, literature review, methodology, results and findings.

On April 1900, Paris held a world trade fair, which brought together people from different consumer markets to celebrate past technological achievements and gain an insight into potential futuristic developments.

The trade fair portrayed the potential of the then and future civilizations to deploy technology, creativity, and innovation to create more consumables to better the life of the future generations.

The trade fair set the foundation for availing more products and services in the marketplace. Primarily, products are availed in the markets for consumers to buy and the buying behaviors are subject to various factors.

The organizations’ ability to generate sales revenue is greatly influenced by their capacity to influence the consumers’ buying behavior. However, Grant, Clarke, and Kyriazis (2013) affirm that the consumer buying behavior is complex because it is influenced by internal and external factors.

The academic trend in studying buying behaviors views them as personality disorders. This approach holds that consumers purchase products compulsively due to anxiety or depression associated with not buying the same products.

This research takes a different approach of studying the consumers’ buying behaviors from what is in the current academic trend. Rather than studying buying behaviors as compulsive disorders, it studies them as lifestyles driven by societal pressures.

Without these behaviors, people are rejected from a given societal class. Compulsive behavior varies according to various demographic differences. For example, women are highly compulsive buyers as opposed to men. However, this conclusion is based on what the society considers as abnormal or normal.

For a considerable duration, some societies have conceptualized normality in terms of men’s behaviors. This perspective suggests that if compulsive buying behavior is more prevalent amongst women as compared to men, it is considered abnormal. This paper refutes such as a conclusion.

This paper’s aims and objectives are three-fold. It conducts a systematic review of the current literature on personality and personality disorders literature coupled with how they contribute to the compulsive buying behaviors. The second objective entails an investigation of whether compulsive behavior is a personality disorder.

Thirdly, it studies the possibility of compulsive behavior being a lifestyle as opposed to a personality disorder. The study has significant contributions to the academic research on consumer buying behaviors.

The dissertation overlooks different factors increasing the prevalence of compulsive buying behavior (CBB) or aggravating it. Stressing on some of these factors is necessary since it has not been projected in previous studies of compulsive buying behavior. Therefore, it sets forth a different paradigm of understanding CBB.

This aspect offers a different way for formulating policies and programs for industries for promoting their products by designing and marketing products and services to meet the lifestyles leading to purchases. Shopping is an essential component of daily life (Li, Unger & Bi, 2014).

However, purchasing without considering its consequences is impulsive, which may lead to anxiety and unhappiness. The main challenge arises when it becomes frequent and uncontrollable.

The paper is organized into four sections. Section 1 reviews the available literature on compulsive buying behaviors and their association with personality and personality disorders. Section 2 discusses the research methodology. Section 3 presents the results and findings of the research study.

Compulsive buying behavior

Shopping entails an important aspect of all people coupled with the economy. While this aspect is a normal behavior, challenges emerge when people overindulge in it without paying attention to its consequences. More focus in buying behaviors has been on compulsive purchasing as it has negative consequences for individuals.

Neuner, Raab, and Reisch (2005) support this assertion adding that more focus on research on compulsive purchasing behavior is due to the view that it is more prevalent among consumers of all demographic differences.

Marketing research focuses on understanding the people’s shopping culture and sought after products and services so that its research and design can focus on these attributes to attract high sales. Indeed, much of the work on this topic has been conducted from marketing research perspective.

Dittmar, Long, and Bond (2007) suggest that people having compulsive purchasing behavior have high probabilities of experiencing strong buying desire, which overcomes the harms of the compulsion on financial coupled with social aspects of life.

Faber and O’Guinn (1992) add that such people do not possess the mechanism for differentiating between abnormal and normal buying behaviors. The question then remains as the origin of such behaviors. Some studies cite compulsive buying as a psychological problem.

Traditionally, psychologists have viewed personality as a distinction criterion for people’s behaviors.

Behaviorism encompasses one of the important schools of thought explaining why people engage in some behaviors and not others. The big five traits theory also explains the differences among people indecision-making.

Experimental analysis of people’s behaviors suggests that interactions with the environment influence one’s personality. However, Goodstein and Lanyon (2009) argue that internal thinking processes coupled with feelings are critical in influencing and structuring of people’s personalities.

Studying compulsive behavior from the perspective of behavioral psychology introduces some challenges depending on the psychological theoretical arguments used. For example, traditional psychologists tested how behaviors influence personality through animal experimentation.

They believed that animals and people shared similarities in terms of the learning process. However, as Goodstein and Lanyon (2009) argue, human learning processes are progressive.

The psychological behavioral theory explains the dynamic process of obtaining the new learning, which shapes one’s personality. After learning behaviors, Goodstein and Lanyon (2009) suggest that before inflexibility of the personality, people can experience emotional responses towards a given situation, thus causing a personality change.

However, as learning continues, it slows down the personality, thus causing stabilization. This assertion implies that people experience stable responses towards a give environmental stimulus (Stricker, Widiger & Weiner, 2003).

Influenced by this pedagogy, marketers deploy classical conditioning to enhance the consumption of their products. This aspect explains the divergent views on how conditioning influences behaviors. Neuner et al (2005) argue that emotions do not affect operant conditioning (behaviors).

Behaviors should be studied from paradigms of environmental influences. Psychological behaviorism holds that classical coupled with operant conditions play significant roles in influencing people’s behaviors (Pachauri, 2001).

Several factors may contribute to people’s emotional responses. These constitute the thoughts, beliefs, and perceptions affecting people’s emotional responses to the specific stimulus. Physiological behaviorism links emotions demonstrated by individuals with responses to the biological and environmental stimuli.

These emotions can be affirmative or negative toward different stimuli. For example, a positive pulse to a food stimulus or a negative emotion in response to the stimuli causes dislike and unwanted feeling. This aspect suggests that microtonal responses can help in increasing a purchasing behavior of a given products.

Li et al. (2014) define compulsive buying behavior as chronic tendency for purchasing products and services in response to negative conditions and feelings. The behaviors encompass an unconditioned response towards desires for goods or services and feelings of depression due to anxiety.

This aspect implies that the desire to purchase specific types of services or goods leads tithe development of compulsive behavior. The absence of these products or services induces stress or anxiety, which induces the compulsive buying behavior.

The five-personality dimension theory may also influence people’s behaviors, viz. the compulsive purchasing behavior. Indeed, Mueller, Mitchell, Claes, Faber, Fischer, and De Zwaan (2011) believe that personality plays important roles in influencing compulsive buying behavior.

Personality refers to “the sum total of ways in which an individual reacts and interacts with others” (Goodstein & Lanyon, 2009, p.291). It is measured by the traits that people exhibit. Research on personality in an organizational context has focused on labeling various traits, which describe employees and customer behaviors.

Some of the personality traits that have been established by various researches as having the ability to influence the behavior of people include ambition, loyalty, aggressiveness, agreeableness, submissiveness, laziness, assertiveness, and being extroverted among others.

Kihlstrom, Beer, and Klein (2002) posit, “Neuroticism, extraversion, openness, agreeableness, and conscientiousness comprise the big five personality traits” (p. 84). These traits can define factors characterizing consumer behavior as a personality type.

Literature considering roles of big five-personality traits theory in compulsive buying theory depicts incompatibilities in their results. However, consciousness encompasses an important trait, which can explain the differences in compulsive behaviors among different consumers.

Mueller et al. (2011) argue that although consciousness may be important in explaining differences in consumption behavior, which is important in predicting compulsive buying behavior, neuroticism does not relate to the behavior.

Borrowing from the work of Otero-López and Pol (2013), consumers fall into three groups, viz. high, medium, and low propensity in terms of their buying behaviors. According to Kihlstrom et al. (2002), the group “having the highest propensity possesses the highest levels of neuroticism and lowest consciousness” (p. 85).

The group also features the highest level of neuroticism, which includes anxiety, depression, and impulsiveness. Conversely, the group has relative to medium and low compulsive buying behaviors. Propensity groups have the weakest extraversion assertiveness, positive emotions, and self-consciousness.

Compulsive buying behavior: a personality disorder

Compulsive purchasing behavior encompasses an excessive dysfunctional consumption behavior, which aggravates people’s lives emotionally, financially, and mentally (Koran, Faber, Aboujaoude, Large & Serpe, 2006). Compulsive buying behavior manifests itself through psychological problems like depression and anxiety.

This aspect makes theorists like Faber and O’Guinn (1989) to consider it as a personality disorder. Personality disorder describes perennial maladaptive ways of thinking, feeling, and behaving amongst individuals.

However, Dittmar et al. (2007) argue that in defining compulsive buying behavior, it is critical to recognize that all disorders and perceptions of abnormality have cultural norm influences apart from considering disorders, which can be managed clinically.

The 2013 version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) classifies disorders into five annexes. Personality disorders fall under annex 2 in cluster C.

This group comprises disorders like depression and schizophrenia. It also entails less maladaptive disorders characterized by anxiety and dependent personality or obsessive-compulsive disorders. In the manual, compulsive buying behavior does not appear.

Despite the non-inclusion of compulsive buying behavior in the list of Diagnostic and Statistical Manual of Mental Disorders, many psychologists contend that it should fall under the anxiety personality category due to its characteristics of anxiety coupled with negative feelings amongst people suffering from it.

However, this contention attracts controversies. For example, Li et al. (2014) argue that the behavior encompasses an obsessive-compulsive disorder since it has symptoms similar to it. Black (2001) suggests that it becomes compulsive due to lack of impulsive control.

Studies like Faber and O’Guinn (1992) attempt to highlight the relationships between compulsive buying behaviors and personality traits coupled with family lifestyles. This aspect suggests that the literature on compulsive buying behavior mainly focuses on analyzing it as a personality disorder.

An important gap exists in the attempt to relate the behavior with people’s lifestyles.

The current research approaches the problem of compulsive buying behavior as a lifestyle problem rather than a personality disorder. In achieving this concern, it is also important to study it from the pedagogy of obsessive compulsion.

Indeed, studies based on self-reports indicate that compulsive buyers experience similar symptoms to people with obsessive-compulsive disorder. This aspect includes high anxiety and stress that eventually lead to buying unneeded goods with anticipation for the reduction of negative feelings.

The satisfaction of desires influences anxiety and stress levels for a limited period so that compulsive buying becomes a repeated action. This aspect suggests relationship between compulsive buying behaviors with obsessive-compulsive behaviors.

People suffering from compulsive disorders have possibilities of having experienced situations in life, which led to mistrusts of their priorities coupled with their abilities. The obsessive-compulsive disorder is conceptualized from the paradigms of pursuance of eliminating the anxiety and stressful thoughts in executing certain individual acts.

Similarly, experiencing anxiety, depression, and stress are typical symptoms of compulsive buying behavior leading to the development of the urge to engage in compulsive buying. Faber and O’Guinn (1992) argue that this behavior is an abnormal consumption behavior.

It is abnormal to the extent that after purchasing to reduce stress and negative experiences, people often regret due to its repercussions like ensuing financial challenges.

Black (2001) suggests that for persons with the compulsive behavior disorder, their attention and thoughts give rise to anxiety and compulsions to reduce discomforts associated with failure to purchase products and services they desire urgently.

Obsessions entail negative feelings experienced by people before they engage in compulsive behavior in a bid to reduce anxieties, which encompass feeling of guilt for not engaging in a given act. Amid the established relationship between obsessive behavior and compulsive behaviors including compulsive buying behavior, Koran et al. (2006) classify it under impulsive control disorder.

People become susceptible to impulsive control disorder when they cannot control different urges. Koran et al. (2001) assert that people with compulsive buying disorder often think about shopping as opposed to thinking about its consequences or the objective of purchasing products and services.

For example, if a woman purchases cosmetics and clothing in a bid to satisfy her self-esteem, she may do so without thinking about this objective. It is also impossible to recognize that the buying behavior subjects her to vulnerabilities of suffering from compulsive buying.

This aspect suggests the importance of developing an appropriate scale for measuring compulsive purchasing behavior so that individuals can know when developing the problem.

Faber and O’Guinn (1989) made one of the earliest attempts to develop a scale for measuring compulsive buying behavior. The scale aimed at differentiating compulsive buyers from non-compulsive ones.

Attempts have been made to improve on the scale by incorporating mechanisms for identifying the attitudes toward product categories, processes of acquisition, and post-purchase feedbacks like positive or negative emotions as remorse after spending.

The most recent edition of the scale assesses the spending patterns coupled with behaviors, emotions, and feelings of people towards the desired products and process of acquisition.

Indeed, finance management through cash or credit cards constitutes some of the good examples of progressive precision in conceptualizing the compulsive buying disorder.

The Faber and O’Guinn (1989) scale for differentiation of compulsive buyers from non-compulsive buyers has some limitations. It entails a binary approach to measurement, which introduces challenges of measuring the propensity of the behavior.

However, the scale is crucial as it forms the foundation for the development of scales for measuring people’s compulsive buying behavior. For example, Edwards (1993) developed a scale for measuring the behavior based on Faber and O’Guinn’s scale.

Through the incorporation of spending behaviors as the dependent variable, the scale permits researchers to rate compulsive buying behaviors depending on their propensity. It classifies consumption behaviors into non-compulsive, low compulsive, medium compulsive, and high compulsive (Edwards, 1993).

The compulsive spending model identifies five factors related to compulsive purchasing behaviors. These are the “tendency to spend, compulsion to spend, feeling about shopping and spending, dysfunctional spending, and post-purchase guilt” (Koran et al. 2006, p. 1810).

From the 1980s, there has been an incredible scholarly research on compulsive spending behavior among consumers. For instance, Koran et al. (2006) argue that more than 5 percent of Americans are dealing with compulsive purchasing behavior.

Kukar, Ridgway, and Monroe (2009) reckon that the trend has now increased by about 4 percent to stand at more than 8.5 percent. However, there is no scholarly contention on factors leading to the increasing compulsive buying behavior among the Americans and other people across the globe.

Almost all researches on this subject deploy personality disorder to construct their hypothesis. This aspect excludes many other factors like lifestyles, which may account for the increasing behavior.

Irrespective of the improvements in the mechanisms of detecting mental disorders, the conceptualization of the disorder is incomplete (Li, Unger & Bi, 2014). For example, the definition of normal and abnormal behaviors is not straightforward.

Gaps remain on what amounts to a normal consumption behavior (Freshwater, Sherwood & Drury, 2006). Parts of these gaps are due to the view that people’s behaviors are subject to culture and living styles, but not necessarily a mental disorder.

The latest edition of the DSM-IVTR is composed of five axes for diagnosis based on the Western masculine ideals for a ‘healthy” person. It is likely to define the normal typical behavior of people, especially women, from other cultures as the abnormal behavior (Neuner, Raab & Reisch, 2005).

In such cultures, their behaviors are considered as normal in all aspects as they fit within their norms and cultural value systems. This aspect suggests that what amounts to a normal behavior in a multicultural context is a contentious issue.

Compulsive buying behavior varies with respect to different demographic characteristics of people. For example, it varies according to gender with women having high prevalence levels for the behavior (Maraz et al., 2014).

This assertion confirms the validity of an earlier study by Neuner et al. (2005), indicating higher prevalence levels for the behavior among women as compared to men.

However, Koran et al. (2006) hold that compulsive purchasing transcends gender and it can be viewed as a common personality disorder affecting women and men in equal thresholds. These discrepancies may be accounted for by the perceptions of normal and abnormal behaviors.

For example, masculine purchasing behavior may be labeled normal while feminine purchasing behaviors are labeled abnormal. Methods and theories for measuring prevalence may also have prejudices in terms of what amounts to a normal behavior.

Amid the discrepancies of the prevalence of compulsive buying disorder, an important interrogative explains the different prevalence levels. Eren, Eroglu, and Hacioglu (2012) suggest that women are one and a half times more likely to experience anxiety disorders as compared to men.

The comorbidity of the disorder arises due to the women’s position in society, which is characterized by power imbalances. For example, discrimination against women exposes them to threats of chronic anxiety disorders.

Apart from gender, inconsistency in research on compulsive buying behaviors exists based on other demographical dimensions like age and income levels.

For instance, Black (2001) found a negative correlation between income and compulsive buying density. Conversely, Mueller et al. (2011) found “no relationship between income and compulsive buying behavior” (p. 1310).

Compulsive buying behavior varies according to the state of people’s development. For example, Koran et al. (2006) estimated that 6% of the Americans are likely to consume compulsively. In Germany 5 to 7 percent of the population engages in compulsive buying (Mueller.et al., 2011).

Does this suggest that in Eastern countries people do not buy compulsively? Arguably, inadequate research on such nations and cross-cultural differences among consumers may lead to the attribution of higher compulsive buying to Western nations than in Eastern nations like China.

Indeed, the current literature on compulsive buying documents minimal research based on developing countries like those located in Asia.

The few scholarly researches on this topic in developing nations deploy theories and scales used in similar studies in the Western nations like Germany and the US amid differing lifestyles and ways of doing business.

For example, Eastern nations and Western nations have differing methodologies for paying, differing approaches in making shopping decisions, and differing consumer cultures.

Stemming from the arguments developed in this section, it is important to study compulsive buying behaviors depending on cultural characteristics of the population and using a specific methodology applicable to a given nation or region.

Considering that the majority of the researches in this topic base their hypothesis on compulsive buying behavior as a personality disorder, this research seeks for an alternative explanation of the behavior. It studies it as lifestyle challenge facing consumers in China.

Research design

This research seeks to explore the compulsive buying lifestyle amongst consumers. The study’s findings will provide insight into the consumers’ purchasing behavior. Therefore, the research is exploratory in nature.

Saunders, Thornhill, and Lewis (2009) accentuate that exploratory research design enable researchers to undertake preliminary investigations in areas that have not been characterized by intensive research.

Subsequently, exploratory research leads to the generation of new insights on the phenomenon under investigation (Blanche, Durrhem & Painter).

The research study is based on a qualitative research design, which acts as the framework that guides the researcher in answering the research question. The qualitative research design was selected in order to generate adequate data from the field in order to support the research study.

Moreover, the choice of qualitative research design was further informed by the grounded theory. Strang (2015) defines the grounded theory as ‘the discovery from data systematically obtained from social research with the aim of generating or discovering a theory’ (p.449).

Alternatively, the grounded theory design involves a systematic and qualitative procedure that enables researchers to develop a practical theory that elucidates the phenomenon under evaluation at a conceptual level.

By adopting the grounded theory design, the researcher will be able to understand the social and cultural factors associated with the research topic. Subsequently, the research study will be adequately enriched. Additionally, the choice of qualitative research design is further based on the need to generate gather relevant data from the field.

Andrew (2004) content that ‘qualitative research process involves emerging questions and procedures, data typically collected in the participant’s settings, data analysis that builds inductively and interpretations of the meaning of the data’ (p.46).

Therefore, the qualitative research design enabled the researcher to derive data from the natural setting hence improving its credibility and validity of the research findings. The concepts of validity and credibility are some of the critical determinants of the relevance of research findings.

Population and sampling

In order to improve the capacity of the research study to enhance the consumer behavior theory using the grounded theory design, the researcher appreciated the importance of effective identification of study population. The study population was comprised of individual consumers from cultural and social backgrounds.

The study population was comprised of consumers of American, Iranian, Chinese and Italian consumers. The decision to select respondents from diverse cultural backgrounds was informed by the need to understand the variation with reference to consumer behavior across different cultural backgrounds.

Consequently, the study’s capacity to further explain the impact of cultural and social dimensions between Westerners and Easterners consumers on compulsive buying behavior was improved considerably.

The researcher recognizes cost as a major determinant in conducting the research study. In an effort to minimize the cost of conducting the research study, the researcher integrated the concept of sampling, which entails constructing a subset from the identified study population.

The study sample was constructed using the simple random sampling technique in order to minimize the occurrence of bias in constructing the sample study. Using the simple random sampling technique, the researcher provided all the subjects in the identified study population an opportunity of being included in the research study.

Thus, the sample was representative of the target population. Integrating the sampling technique made the study to be manageable by minimizing the amount of time and finances required to undertake the study.

Furthermore, the simple random sampling technique made the study to be representative of the prevailing consumer behavior (Scott, 2011). The research sample was comprised of 14 respondents.

Fourteen [14] of the respondents were Chinese, 6 female and 4 male respondents. Conversely, two of the respondents were American men, while the others included one Iranian woman and one Italian woman.

Data collection and instrumentation

The researcher understands the fact that the data collected directly influences the research findings. Thus, to improve the research findings, the study is based on data collected from primary sources in order to generate research data from the natural setting.

The primary method of data collection mainly involved conducting interviews on the respondents included in the study sample. The researcher selected the interviewing technique as the method of data collection in order to conduct an in-depth review of the compulsive buying behavior amongst consumers.

Adopting the interviewing technique provided the researcher an opportunity to probe further on research topic hence improving the quality of the data collected.

Interviews with the selected respondents were conducted through telephone in an effort to minimize the cost of the research study. The telephone interview was based on a number of questionnaires were designed in order to guide the researcher in the interviewing process.

The questionnaires were open-ended in nature. Adoption of the open-ended questionnaires provided the respondents an opportunity to answer the questions freely by providing their opinion. Moreover, the open-ended questionnaires limited the likelihood of the researcher influencing the response provided by the respondents.

The researcher ensured that the open-ended questionnaires were adequately reviewed in order to improve the respondents’ ability to understand. The questionnaires acted as the data collection guide. During the interviewing process, the researcher reviewed the respondents’ demographic characteristics.

This was achieved by evaluating their age, gender, disposable income, social status, and family and relationship aspects. Moreover, the researcher reviewed the respondents’ buying behavior such as their methods of payment on purchases, amount of their shopping, and the reason for shopping.

In order to improve the relevance of the data collected, the researcher further assessed the respondents’ product usage behavior. This was attained by asking the respondents whether they used the products after purchasing and if not what they do with the product.

By reviewing this aspect, the researcher was able to generate insight into the compulsive buying behavior amongst consumers characterized by diverse cultural and social backgrounds.

For example, the researcher was able to evaluate the consumers’ decision to increase or decrease the purchase of a particular product and the motivation for such behavior. Integrating such aspects in the research process enabled the researcher to undertake an extensive comparison of the compulsive consumer behavior.

A recorder was used in storing the responses obtained from the field.

Data analysis and presentation

The data collected from the field was analyzed qualitatively. However, the researcher integrated different data analysis and presentation tools. The researcher adopted tabular data presentation by organizing the research data into rows and columns. The main data analysis and presentation tools adopted include graphs, charts and tables.

Furthermore, the researcher also adopts the concept of textual presentation, which entails using statements comprised of numerals in order to explain the research findings effectively. By adopting the textual presentation technique, the researcher has been able to present the collected research data in the expository form.

The researcher was of the view that integrating these tools would have contributed towards the effective analysis of the descriptive research data obtained from the field. Moreover, the aforementioned data presentation methods played an essential role in improving the target audience ability to understand and interpret the data collected.

Ethical issues

In the course of collecting data from the field, the researcher took into account diverse ethical issues. The objective of taking into consideration such aspects was informed by the need to improve the rate of the selected respondents participating in the research study (Finlay, 2006).

First, the researcher ensured that that the selected respondents were adequately informed that the research study was aimed at adding new ideas/insight to the consumer behavior theory. Thus, the purpose of the study is academically inclined.

Therefore, the researcher was able to obtain informed consent in addition to eliminating any form of suspicion from the respondents. Moreover, the researcher provided respondents with an opportunity to pullout of the research study without any negative repercussions.

Moreover, the researcher observed the participants’ privacy during the research. Additionally, the researcher desisted from any form of coercion during the study process. Consequently, the respondents contributed freely in the study.

The study showed the existence of significant differences in compulsive buying behavior amongst consumers of different cultural and social characteristics. One of the most notable issues on compulsive buying behavior is that it extends beyond culture.

On the contrary, the study showed that the consumers’ compulsive buying behavior is greatly influenced by diverse demographic characteristics. Amongst the most notable factors that lead to the development of compulsive buying behavior entails the consumers age, gender, mood, and level of disposable income.

The study further shows that these aspects influence the consumers’ compulsive buying behaviors irrespective of their cultural and social backgrounds.

Moreover, the study showed that individuals characterized by compulsive buying behavior mainly indulge in such a behavior due to external pressures, such as the perception by the society and family members.

Forty-five percent [45%] of the respondents of the respondents interviewed were of the opinion that they engage in compulsive buying behavior in an effort to avoid being ignored and isolated by family members and the society.

Conversely, 25% of the respondents were of the opinion that they engage in compulsive buying behavior in order to reduce work-related stress while 20% of the respondents said that their compulsive buying behavior has been motivated by the need to forget their financial loss or trauma.

Moreover, 10% of the respondents were of the opinion that they engage in such behavior in an effort to compensate or cope with the feeling of being humiliated, powerless or having a faded role. The graph below illustrates the variation in the respondents’ opinion on their motivation towards compulsive buying behavior.

Response on compulsive buying behaviour

Several studies confirm multi-dimensional aspects of compulsive purchasing behavior. Compulsive buying behavior is extensively influenced by personal and environmental characteristics. Faber and O’Guinn (1992) note that buyers can be grouped into different scales.

A Canadian measurement scale for compulsive purchasing behaviors identified three main dimensions of the behavior, viz. spending tendency, reactive aspects, and guilt after purchasing. The findings of the study conducted affirm that the compulsive buying behavior is not subject to the consumers’ cultural backgrounds only.

On the contrary, other individual traits are central determinants in the development of compulsive buying behavior. This shows that individuals’ personality is a critical determinant in the development of compulsive buying behavior.

Traditional behavioral theories postulate that individuals’ personality is due to the interaction between an individual’s personal characteristics and the environmental influences.

This finding is further supported by Faber and O’Guinn (1992) who affirm that compulsive buying behaviors mainly arise from five main personality dimensions. These dimensions include agreeableness, extraversion, neuroticism, conscientiousness, and imagination.

The research study showed that all the respondents characterized by compulsive buying behavior have a common factor that motivates them to engage in such behavior. One of the most common factors entails avoidance. Therefore, consumers develop such behavior in an effort to avoid situations that are unpleasant to the customers.

Some consumers engage in such practices in an effort to leave a potentially provoking situation. Williams (2009) emphasizes that ‘avoidance can also be a more subtle and include things like quickly leaving anxiety-provoking situations as soon as any anxiety is noticed’ (p.124). Therefore, some consumers engage in compulsive buying in an effort to avoid certain situations depending on their feeling. From the findings, avoidance can be categorized into three main levels, which include

  • Active avoidance; this form avoidance is aimed at distracting an individual’s compulsive buying behavior. This form of avoidance mainly targets avoiding unwanted emotions, memories, failures, and experiences that stimulate the development of compulsive buying behavior.
  • Compensate for control ; this form of avoidance is aimed at limiting the development of compulsive purchasing behavior due to pressure from different sources such as family and workplace amongst other sources of pressure.
  • Avoidance in an effort to cope with life problems

Understanding the consumer buying behavior comprises a vital element in organization’s marketing activities. First, understanding the buying behavior provides organizational managers insight on the most effective strategy to adopt in order to influence the consumers’ purchase decision-making process.

Organization’s marketing managers should appreciate the existence of differences with reference to consumer buying behavior. The study shows the consumers’ buying behavior is a factor of the consumers’ personality and the influence of the external pressures. This phenomenon is well illustrated by the compulsive buying behavior.

The behavior entails a compelling need to purchase a product or service in an effort to satisfy a particular need.

The compulsive buying behavior may have a negative impact on the consumer’s purchasing power because the consumer engages in excessive purchase of commodities aimed at addressing psychological needs such as anxieties and avoidance of negative emotions such as humiliation and ignorance.

Therefore, one can argue that the compulsive buying behavior is motivated by the need to entrench an individual’s social status or class.

Compulsive buying behavior stimulates consumers to make purchases without considering the consequences of their behavior including post-purchase guilt. Past research conducted in Westerns nations’ settings like Germany, Canada, and the US considers it as a personality disorder.

On the contrary, this research adopted a different paradigm. It studied the issue as a lifestyle problem. This goal has been achieved by comparison of purchasing behavior across consumers from Eastern countries such as China.

The study underscores the existence of similarity with reference to the factors stimulating development of compulsive buying behavior across consumers characterized by varied cultural and social characteristics. One of the reasons for the existence of compulsive buying behavior entails avoidance.

Consumers characterized by such practices are motivated by the need to avoid an unfavorable occurrence in their consumption patterns.

In summary, understanding the compulsive buying behavior is a fundamental element in improving an organization’s capacity to generate sales by exploiting the compulsive buying behavior.

For example, organizations should consider integrating effective marketing strategies that influence the development of compulsive buying behavior amongst consumers. One of the fundamental aspects that marketers should take into consideration entails the consumers’ personality.

Black, D. (2001). Compulsive Buying Disorder: Definition, Assessment, Epidemiology and Clinical Management. CNS Drugs, 15 (1), 17–27.835

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 (3), 334-361.

Edwards, A. (1993). Development of a New Scale for Measuring Compulsive Buying Behavior. Financial Counseling and Planning, 4 (2), 67-85.

Eren, S., Eroglu, F., & Hacioglu, G. (2012). Compulsive Buying Tendencies through Materialistic and Hedonic Values among College Students in Turkey . Social and Behavioral Sciences, 58 (1), 1370 –1377.

Faber, J., & O’Guinn, C. (1992). A Clinical Screener for Compulsive Buying. Journal of Consumer Research, 19 (3), 459–469.

Faber, R., & O’Guinn, C. (1989). Compulsive Buying: A Phenomenon logical Exploration. Journal of Consumer Research, 16 (2), 147–157.

Finlay, L. (2006). Rigor, Ethical Integrity or Artistry” Reflexively Reviewing Criteria For Evaluating Qualitative Research. British Journal of occupational Therapy, 69 (7), 319-326.

Freshwater, D., Sherwood, G., & Drury, V. (2006). International research collaboration: Issues, benefits and challenges of the global network. Journal of Research in marketing, 11 (4), 295-303.

Goodstein, L., & Lanyon, R. (2009). Application of Personality Assessment to the Work Place. Journal of Business and Psychology, 13 (3), 291-313.

Grant, R., Clarke, R., & Kyriazis, E. (2013). Modeling Real-Time Online Information: A New Research Approach for Complex Consumer Behavior. J ournal of Marketing Management, 29 (8), 950-972.

Kihlstrom, J., Beer, S., & Klein, B. (2002). Self and Identity as Memory . New York, NY: Guilford Press.

Koran, L., Faber, R., Aboujaoude, E., Large, M., & Serpe, R. (2006). Estimated Prevalence of Compulsive Buying Behavior in the United States. American Journal of Psychiatry, 16 (3), 1806-1812.

Kukar, M., Ridgway, N., & Monroe, K. (2009). The Relationships Between Consumers’ Tendencies To Buy Compulsively and their Motivations to Shop and Buy on the Internet. Journal of Retailing, 85 (3), 298-307.

Li, S., Unger, A., Bi, C. (2014). Different Facets of Compulsive Buying Among Chinese Students. Journal of Behavioral Addiction, 3 (4), 238-245.

Maraz, A., Eisinger, A., Hende, B., Urbán, R., Paksi, B., Kun, B., Demetrovics, Z. (2014). Measuring compulsive buying behavior: Psychometric validity of three different scales and prevalence in the general population and in shopping centers. Psychiatry Research, 225 (2), 326-34.

Mueller, A., Mitchell, J., Claes, L., Faber, R., Fischer, J., & De Zwaan, M. (2011). Does Compulsive Buying Differ Between Male and Female Students? Personality and Individual Differences, 50 (3), 1309-1312.

Neuner, M., Raab, G., & Reisch L. (2005). Compulsive Buying in Maturing Consumer Societies: An Empirical Re-Inquiry. Journal of Economic Psychology, 26 (4), 509–522.

Otero-López, J., & Pol, E. (2013). Compulsive Buying and the Five-Factor Model of Personality: A Facet Analysis. Personality and Individual Differences, 55 (1), 585-590.

Pachauri, M. (2001). Consumer Behavior: A Literature Review. The Marketing Review, 2 (1), 319-355.

Saunders, M., Thornhill, A., & Lewis, P. (2009). Research Methods for Business Students . New York, NY: Prentice Hall.

Scott, S. (2011). Research Methodology: Sampling Techniques. Journal of Scientific Research, 2 (1), 87-92.

Strang, K. (2015). The Palgrave handbook of research design in business and management. New York, NY: Palgrave Macmillan.

Stricker, G., Widiger, T., & Weiner, I. (2003). Handbook of Psychology: Clinical Psychology. Hoboken, NJ: John Wiley and Sons.

Williams, C. (2009). Overcoming anxiety, stress, and panic; a five areas approach . New York, NY: CRC Press.

  • Chicago (A-D)
  • Chicago (N-B)

IvyPanda. (2023, December 15). Compulsive Buying Behavior as a Lifestyle. https://ivypanda.com/essays/compulsive-buying-behavior-as-a-lifestyle/

"Compulsive Buying Behavior as a Lifestyle." IvyPanda , 15 Dec. 2023, ivypanda.com/essays/compulsive-buying-behavior-as-a-lifestyle/.

IvyPanda . (2023) 'Compulsive Buying Behavior as a Lifestyle'. 15 December.

IvyPanda . 2023. "Compulsive Buying Behavior as a Lifestyle." December 15, 2023. https://ivypanda.com/essays/compulsive-buying-behavior-as-a-lifestyle/.

1. IvyPanda . "Compulsive Buying Behavior as a Lifestyle." December 15, 2023. https://ivypanda.com/essays/compulsive-buying-behavior-as-a-lifestyle/.

Bibliography

IvyPanda . "Compulsive Buying Behavior as a Lifestyle." December 15, 2023. https://ivypanda.com/essays/compulsive-buying-behavior-as-a-lifestyle/.

  • Compulsive vs. Non-Compulsive Buyers' Behavior
  • The Compulsive Hoarding Concept
  • Psychological Issues: Obsessive Compulsive Disorder
  • Compulsive Buying Behaviour for Self-Actualization
  • Obsessive Compulsive Disorder: Symptoms, Diagnosis and Treatment
  • Obsessive Compulsive Disorder: Definition, Types and Causes
  • Obsessive-Compulsive Behavior: Its Etiology
  • Compulsive and Addictive Behaviors
  • Obsessive-Compulsive Disorder - Psychology
  • Obsessive-Compulsive Disorder (OCD) - Psychology
  • Observational Systems Discussion
  • Social Validity in Behavioural Research
  • Negative Effects of Counselling Without a Self-Care Plan
  • Low-Income African-American Caregivers
  • Social Comparison Theory

Compulsive Buying Disorder

People living in the contemporary world have to cope with various issues, and they often choose different ways that can sometimes be rather destructive. Compulsive buying disorder is often an issue of women trying to cope with depression, but this psychological state is not the only reason for the development of the disorder (Müller et al., 2014). The purpose of this study is to explore the perspectives of women in their late 30s who suffer from compulsive buying disorders.

Women will be encouraged to share their views on possible causes and effects of the disorder as well as the peculiarities of their psychological state and personality. The research question of this study is as follows: How do women in their late 30s view their compulsive buying disorder, its causes and effects on their family life, career, personality, and so on?

To address the research question, it is possible to utilize descriptive qualitative design. The case study design is chosen for this research. This research design enables the researcher to explore an issue and employ a variety of tools to gain an in-depth understanding of the issue (Creswell, 2012). Convenience sampling is the sample type chosen to address the goals of this study. Women will be recruited through social networks to participate in the research.

Coding is the most appropriate data analysis strategy, and, hence, the most recurrent themes will be identified to explore the way women see their compulsive buying disorder, its effects, and causes. The major threats to internal validity are associated with data interpretation bias. Coding checks, triangulation, and detailed descriptions can be used to decrease the validity threats.

It has been acknowledged that women are more likely to be affected by compulsive buying disorder (Granero et al., 2016). Müller et al. (2014) note that the disorder often becomes a result of depressive symptoms. At that, there are other reasons for the development of the disorder, including personality traits (Shahjehan, Qureshi, Zeb & Saifullah, 2012). Women in their late 30s are of particular interest as they often have a career and/or family, enough funds to spend, and various issues to address. This population can provide helpful insights into the nature of the disorder.

The participants will be recruited through social networks. Online semi-structured interviews will be held with those who will volunteer to participate. The data will be stored on the researcher’s computer, and the confidential data will not be provided to any third parties. The participants will receive code names, and the transcripts sent to peers for code check will have the code names. The participants will sign the written consent forms.

A pilot interview with two participants will be held to refine the guided questions as well as other questions of the interview. Online semi-structured interviews will be carried out. To increase the validity of the study, the participants’ posts (textual and visual) available from their social networks accounts (posted up to 6 months ago) will also be analyzed and encoded. QDA Miner Lite will be used to check the relevance of the themes identified.

The research question of this study can be formulated as follows: How do women in their late 30s view their compulsive buying disorder, its causes and effects?

The data will be analyzed manually. The most recurrent themes in the participants’ accounts will be identified. The data analysis software will be used to check the validity of chosen themes. Code checking will be implemented by peers to increase the validity of the study. The themes will also be identified when analyzing posts of the participants. The themes tracked in interviews and posts will be compared.

It is expected that personality affects the development of the disorder in women and that single women are more prone to the disorder and see it as a way to fill in their inner voids. To address the researcher biases, the researcher will try to avoid limiting the participants’ answers in any way and will provide complete freedom to discuss any topics.

Creswell, J. (2012). Qualitative inquiry & research design: Choosing among five approaches . Thousand Oaks, CA: Sage Publications.

Granero, R., Fernández-Aranda, F., Mestre-Bach, G., Steward, T., Baño, M., & Del Pino-Gutiérrez, A…Jiménez-Murcia, S. (2016). Compulsive buying behavior: Clinical comparison with other behavioral addictions . Frontiers in Psychology , 7. Web.

Müller, A., Claes, L., Georgiadou, E., Möllenkamp, M., Voth, E.M., & Faber, R.J… De Zwaan, M. (2014). Is compulsive buying related to materialism, depression or temperament? Findings from a sample of treatment-seeking patients with CB. Psychiatry Research , 216 (1), 103-107.

Shahjehan, A., Qureshi, J.A., Zeb, F., & Saifullah, K. (2012). The effect of personality on impulsive and compulsive buying behaviors. African Journal of Business Management , 6 (6), 2187-2194.

Cite this paper

  • Chicago (N-B)
  • Chicago (A-D)

StudyCorgi. (2020, December 30). Compulsive Buying Disorder. https://studycorgi.com/compulsive-buying-disorder/

"Compulsive Buying Disorder." StudyCorgi , 30 Dec. 2020, studycorgi.com/compulsive-buying-disorder/.

StudyCorgi . (2020) 'Compulsive Buying Disorder'. 30 December.

1. StudyCorgi . "Compulsive Buying Disorder." December 30, 2020. https://studycorgi.com/compulsive-buying-disorder/.

Bibliography

StudyCorgi . "Compulsive Buying Disorder." December 30, 2020. https://studycorgi.com/compulsive-buying-disorder/.

StudyCorgi . 2020. "Compulsive Buying Disorder." December 30, 2020. https://studycorgi.com/compulsive-buying-disorder/.

This paper, “Compulsive Buying Disorder”, was written and voluntary submitted to our free essay database by a straight-A student. Please ensure you properly reference the paper if you're using it to write your assignment.

Before publication, the StudyCorgi editorial team proofread and checked the paper to make sure it meets the highest standards in terms of grammar, punctuation, style, fact accuracy, copyright issues, and inclusive language. Last updated: December 30, 2020 .

If you are the author of this paper and no longer wish to have it published on StudyCorgi, request the removal . Please use the “ Donate your paper ” form to submit an essay.

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • J Behav Addict
  • v.12(3); 2023 Oct
  • PMC10562810

Update on treatment studies for compulsive buying-shopping disorder: A systematic review

Astrid müller.

1 Department of Psychosomatic Medicine and Psychotherapy, Hannover Medical School, Hannover, Germany

Nora M. Laskowski

2 Ruhr-University Bochum, University Clinic for Psychosomatic Medicine and Psychotherapy, Medical Faculty, Campus East-Westphalia, Germany

Tobias A. Thomas

Stephanie antons.

3 General Psychology: Cognition and Center for Behavioral Addiction Research (CeBAR), University of Duisburg-Essen, Germany

Nadja Tahmassebi

4 Salus Klinik Friedrichsdorf, Germany

Sabine Steins-Loeber

5 Department of Clinical Psychology and Psychotherapy, University of Bamberg, Germany

Matthias Brand

6 Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany

Ekaterini Georgiadou

7 Department of Psychiatry and Psychotherapy, Paracelsus Medical University Nuremberg, Germany

Background and aims

Compulsive buying-shopping disorder (CBSD) is mentioned as an example of other specified impulse control disorders in the ICD-11 coding tool, highlighting its clinical relevance and need for treatment. The aim of the present work was to provide a systematic update on treatment studies for CBSD, with a particular focus on online CBSD.

The preregistered systematic review (PROSPERO, CRD42021257379) was performed in accordance with the PRISMA 2020 statement. A literature search was conducted using the PubMed, Scopus, Web of Science and PsycInfo databases. Original research published between January 2000 and December 2022 was included. Risk of reporting bias was evaluated with the CONSORT guideline for randomized controlled trials. Effect sizes for primary CBSD outcomes were calculated.

Thirteen studies were included (psychotherapy: 2 open, 4 waitlist control design; medication: 2 open, 3 placebo-controlled, 2 open-label phase followed by a double-blind discontinuation phase; participants treatment/control 349/149). None of the studies addressed online CBSD. Psychotherapy studies suggest that group cognitive-behavioral therapy is effective in reducing CBSD symptoms. Pharmacological studies with selective serotonin re-uptake inhibitors or topiramate did not indicate superiority over placebo. Predictors of treatment outcome were rarely examined, mechanisms of change were not studied at all. Risk of reporting bias was high in most studies.

Poor methodological and low quality of reporting of included studies reduce the reliability of conclusions. There is a lack of studies targeting online CBSD. More high-quality treatment research is needed with more emphasis on the CBSD subtype and mechanisms of change.

Introduction

For the first time, compulsive buying-shopping disorder (CBSD) is now listed as an example of other specified impulse control disorders in the coding tool of the 11th edition of the International Classification of Diseases (ICD-11 code 6C7Y) ( WHO, 2022 ). Phenomenological features of CBSD are time-consuming shopping activities and excessive spending of consumer items that are not needed or not utilized for the intended purposes, which may be offline (i.e. in-store) or online (i.e. on the internet) ( McElroy, Keck, Pope, Smith, & Strakowski, 1994 ; Müller, Laskowski, Trotzke, et al., 2021 ). Diagnostic characteristics of CBSD include diminished control over buying/shopping (with regard to e.g., frequency, intensity, duration, and context), increasing priority given to buying/shopping to the extent that the consumer activities interfere with other interests, leisure activities, professional duties, and daily responsibilities ( Black, 2022 ; Laskowski, Trotzke, de Zwaan, Brand, & Müller, 2021 ; McElroy et al., 1994 ; Müller, Laskowski, Trotzke, et al., 2021 ), harmful consequences of inappropriate buying/shopping (e.g., clinically significant distress, indebtedness, deceitful behavior, familial discord, shame, regret, embarrassment, or even legal problems) and impairment in personal, family, social, educational, occupational, or other important areas of functioning ( Achtziger, Hubert, Kenning, Raab, & Reisch, 2015 ; Benson, 2013 ; McElroy et al., 1994 ; Müller, Laskowski, Trotzke, et al., 2021 ; Park, Cho, & Seo, 2006 ). Notwithstanding the numerous adverse consequences, the maladaptive consumer behavior is continued or even escalated. Treatment-seeking individuals with CBSD often suffer from other mental disorders, e.g., anxiety and depressive disorders, hoarding disorder (i.e., accumulation of purchased items), eating disorders marked by binge eating, and other addictive behaviors ( Black, 2022 ; Christenson et al., 1994 ; Fernandez-Aranda et al., 2008 ; Granero et al., 2016 ; Müller et al., 2010 ).

With the growth of e-commerce, more and more people are buying/shopping on the internet, resulting in the shift from traditional offline CBSD to online CBSD ( Adamczyk, 2021 ; Augsburger et al., 2020 ; Baggio et al., 2022 ; Duroy, Gorse, & Lejoyeux, 2014 ; Fineberg, Menchon, et al., 2022 ; Müller, Steins-Loeber, et al., 2019 ). Specific internet features (e.g., ubiquity, availability, anonymity, infinite scrolls) and e-marketing (e.g., e-branding, livestream shopping, specific payment options, personalized recommendations) may amplify the addictive potential of online buying/shopping ( Clark & Zack, 2023 ). While the symptomatic pattern described above applies to both offline and online CBSD, it is not yet clear whether online CBSD should be seen as the virtual equivalent of traditional offline CBSD or, at least in a subgroup of individuals with online CBSD, as a standalone specific internet-use disorder that would not have developed in brick-and-mortar retail ( Fineberg, Menchon, et al., 2022 ; Müller, Laskowski, Wegmann, Steins-Loeber, & Brand, 2021 ). It appears that online CBSD as compared to offline CBSD is associated with a higher severity of CBSD and interferes more with daily life, health, school, occupational, and social commitments due to time-consuming browsing for goods on the internet during night, school hours, working time, meetings or while one should be pursuing other daily obligations ( Müller, Steins-Loeber, et al., 2019 ). In addition to specific internet and e-commerce features, individual expectancies and using motives may contribute to the development and maintenance of online CBSD, e.g., buying unobserved, avoiding analogue communication, getting access to huge product variety and anticipating the opportunity to satisfy an urge to buy promptly ( Kukar-Kinney, Ridgway, & Monroe, 2009 ; Trotzke, Starcke, Müller, & Brand, 2015 ). Furthermore, reward and relief mechanisms known form substance use disorders and other behavioral addictions (e.g., gambling disorder) may play an important role in online CBSD as well ( Brand, 2022 ; Brand, Young, Laier, Wölfling, & Potenza, 2016 ; Trotzke, Starcke, Müller, & Brand, 2019 ).

The mention of CBSD in ICD-11 highlights its clinical relevance. Undoubtedly, treatment is necessary for CBSD, as the problem is associated with massive negative consequences for affected persons and their relatives, impairments in important areas of functioning, and chronicity ( Achtziger et al., 2015 ; Benson, 2013 ; McElroy et al., 1994 ; Müller, Laskowski, Trotzke, et al., 2021 ; Park et al., 2006 ). In view of the growth of e-commerce and the presumed increase in problematic or even addictive usage of shopping applications ( Augsburger et al., 2020 ; Müller, Steins-Loeber, et al., 2019 ), more attention should be paid to the specifics of online CBSD that may influence therapy. It is conceivable that successful treatment of online CBSD requires an adaptation of existing therapeutic approaches for CBSD. Past systematic reviews of treatments for CBSD concluded that cognitive-behavioral psychotherapy (CBT) in the group format represents a helpful approach ( Goslar, Leibetseder, Muench, Hofmann, & Laireiter, 2020 ; Hague, Hall, & Kellett, 2016 ; Leite, Pereira, Nardi, & Silva, 2014 ; Vasiliu, 2022 ), while no convincing effect was found for medication ( Soares, Fernandes, & Morgado, 2016 ).

Previous systematic reviews have not paid attention to whether the CBSD occurred offline or online. In this work, we searched for treatment studies for CBSD that reported whether the buying/shopping environment (offline, online, mixed) was assessed and considered in the analyses. The aim was to provide a systematic update on treatment studies for online and/or offline CBSD with a focus on primary outcomes and the quality of reporting by using the Consolidated Standards of Reporting Trials (CONSORT) criteria for treatment studies of the Cochrane Collaboration ( Cumpston & Chandler, 2022 ; Moher et al., 2012 ). This review scope is of relevance for clinicians and researchers because additional information on the treatment of online CBSD will inform about the availability (or lack thereof) of new or adopted treatment approaches which may optimize clinical practice and initiate future proof-of-concept and treatment studies. When we started this project, the last systematic reviews were published three ( Goslar et al., 2020 ) to eight years ago ( Leite, Pereira, et al., 2014 ). Our goal was in line with the recommendations for regular updates of systematic reviews of the Cochrane Collaboration ( Cumpston & Chandler, 2022 ; Moher et al., 2008 ). Recently, another systematic review was published by Vasiliu (2022) that, however, differs from the current work with respect to methodological aspects such as search strategy, included articles, analysis of primary outcomes and discussion. Therefore, the current work is justified and expands on previous reviews. Taking into account past systematic reviews ( Goslar et al., 2020 ; Hague et al., 2016 ; Leite, Pereira, et al., 2014 ; Soares et al., 2016 ; Vasiliu, 2022 ) that found no controlled or open treatment studies for CBSD before 2000 and considering the strong increase of the e-commerce marketplace and the development of Web 2.0 technologies especially during the last two decades ( VanHoose, 2011 ), the present systematic review focuses on treatment studies published since 2000. Due to the expected low number of publications that specifically refer to online CBSD, all available literature on treatments for CBSD was evaluated (not only literature considering particularly online CBSD) that has been published since then. Hereafter, the abbreviation CBSD is used to encompass all possible forms of CBSD: predominantly offline, predominantly online, or mixed forms.

The present work was performed in accordance with the PRISMA 2020 statement, an updated guideline for reporting systematic reviews ( Page et al., 2021 ) (see PRISMA checklists in supplementary material, S1 and S2 ). The review was preregistered on Prospero International Prospective Register of Systematic Reviews (PROSPERO CRD42021257379) and the protocol is available under https://www.crd.york.ac.uk/prospero/ . The main methodological adjustments of the preregistered protocol are mentioned below.

Identification of studies

Study selection criteria.

The review included original research (no reviews, no meta-analyses, no case reports) published in scholarly peer reviewed journals between 2000 and December 2022 in the English language. In contrast to the preregistered protocol, the timeframe for the literature search was extended until mid-December 2022. The treatment studies had to include patients with diagnosed CBSD. Participants in the case groups should have received some type of treatment to reduce symptoms of CBSD (e.g., individual psychotherapy, group psychotherapy, medication), while those in the control conditions should not have completed any specific treatment for CBSD or should have undergone only unspecific treatment. Included were case-control (between-group comparisons) and open (within pre-post comparisons) studies.

Studies were excluded if excessive buying/shopping occurred only as a specifier of hoarding disorder, symptom of other disorders (e.g., bipolar disorder, hypomania, mania), result of dopaminergic medication for other disorders (e.g., Parkinson's disease, restless legs syndrome), or symptom of panic buying (not CBSD) during the Covid-19 pandemic. Further reasons for exclusion were: no original or empirical research, case study, lack of quantitative data on treatment evaluation (i.e., symptoms of CBSD as primary endpoint not assessed), and no English language reports.

Information sources and search strategies

The following databases were searched (last search December 15th, 2022): PubMed, Scopus, Web of Science and PsycInfo. Complex search strings for titles/abstracts were used to cover the broad range of possible terms for CBSD. As an example, Table 1 shows the search string for PubMed (see supplementary material S3 for full search strategy of all databases).

Table 1.

Full search strings for Pubmed

Note. CBSD = compulsive buying-shopping disorder

In addition to the preregistered protocol of this study, the following trial registers were searched (last search June 08 th , 2023) for ongoing preregistered treatment studies for CBSD: Open Science Framework (OSF), International Standard Randomised Controlled Trial Number (ISRCTN), ClinicalTrials.gov , EU Clinical Trials Registry, BMC Trials, CenterWatch, American Economic Association RCT Registry, German Clinical Trials Register (DRKS). The search terms used were “buying” OR “shopping” AND “treatment” OR “therapy” OR “psychotherapy” OR “medication”.

Study selection procedure

Studies were selected by using a two-stage procedure. In a first step, two of the authors (NML, TAT) independently screened titles and abstracts. Potential doubts or inconsistencies between both authors about the eligibility of identified studies were discussed and resolved with supervision by the first author (AM) who also performed an additional screening of existing systematic reviews on CBSD treatment ( Bullock & Koran, 2003 ; Goslar et al., 2020 ; Hague et al., 2016 ; Leite, Pereira, et al., 2014 ; Soares et al., 2016 ; Vasiliu, 2022 ) to ensure that no studies were overlooked. In a second step, the first (AM) and the last (EG) author independently examined the full texts of selected articles. In case of disagreements consensus was made regarding the in- or exclusion of studies with the assistance of the whole study team (i.e. all authors).

Data extraction and analysis

Narrative and quantitative analyses of primary outcomes were performed by the first (AM) and last (EG) author. Results are provided for controlled psychotherapy and pharmacological studies. Effect sizes Cohen's d and 95% confidence intervals (CIs) for primary CBSD outcomes for the contrasts baseline vs. post treatment and baseline vs. follow-up are provided (or calculated if not reported in the original publication) in tabular form to enable comparisons. As recommended by Dunlap, Cortina, Vaslow, and Burke (1996) the effect sizes were calculated for independent variables instead of dependent variables as effect sizes for dependent variables often overestimate the actual size of effect. Based on benchmarks suggested by Cohen (1988) , d = 0.2 was considered a small, d = 0.5 a medium and d  = 0.8 a large effect.

Risk of bias assessment

The risk of bias (RoB) assessment followed the approach of previous systematic reviews on treatment for behavioral addictions ( Antons et al., 2022 ; King et al., 2017 ). Quality of reporting was evaluated with the CONSORT guideline for randomized controlled trials. It consists of 37 criteria (assigned to 25 sections) rated as ‘0’ (not present at all), ‘1’ (partially present) or ‘2’ (present) ( Moher et al., 2012 ). If no evaluation of the item was possible or if the item was not applicable (e.g., open studies or if no randomization was done in controlled trials), no rating was given. The sum score for each study could vary from 0 to 74, with higher scores indicating a higher quality of reporting (i.e. lower RoB). The CONSORT criteria for each study were independently assessed by the first (AM) and last (EG) author. Inconsistencies were discussed between the two authors and resolved if possible. In case of disagreement, the respective items were reassessed jointly by two other authors (SSL, MB) and consensus was found.

Extracted studies and diagnosis

Figure 1 presents the flow diagram showing the in- and exclusion process during the systematic literature search. Characteristics and main outcomes of the included 13 studies are detailed in Table 2 (open studies) and Table 3 (controlled studies). We identified six psychotherapy studies, two of those were open trials ( Filomensky & Tavares, 2009 ; Granero et al., 2017 ) and four were randomized controlled studies ( Benson, Eisenach, Abrams, & van Stolk-Cooke, 2014 ; Mitchell, Burgard, Faber, Crosby, & de Zwaan, 2006 ; Müller, Arikian, de Zwaan, & Mitchell, 2013 ; Müller, Mueller, et al., 2008 ). In terms of the seven included pharmacological studies, two were open studies ( Grant, Odlaug, Mooney, O'Brien, & Kim, 2012 ; Koran, Bullock, Hartston, Elliott, & D'Andrea, 2002 ), another two started with an open-label phase that was followed by a double-blind discontinuation phase ( Koran, Aboujaoude, Solvason, Gamel, & Smith, 2007 ; Koran, Chuong, Bullock, & Smith, 2003 ), and three studies had a clear placebo-controlled design ( Black, Gabel, Hansen, & Schlosser, 2000 ; Nicoli de Mattos et al., 2020 ; Ninan et al., 2000 ).

An external file that holds a picture, illustration, etc.
Object name is jba-12-631-g001.jpg

Flow diagram

Table 2.

Characteristics and main findings of included open studies for compulsive buying-shopping disorder (CBSD)

Note : CBT = Cognitive-behavioral therapy; CBS = Compulsive Buying Scale; FU = Follow-up; SCID-I = Structured Clinical Interview for DSM IV Axis I covering impulsive control disorders; Y-BOCS-SV = Yale–Brown Obsessive Compulsive Scale-Shopping Version.

Table 3.

Characteristics and main findings of included controlled studies for compulsive buying-shopping disorder (CBSD)

Note. ACT = Acceptance and Commitment Therapy; CBFS = Compulsive Buying Follow-up Scale; CBS = Compulsive Buying Scale; CBT = Cognitive Behavioral Treatment; DBT = Dialectical Behavior Therapy; FU = Follow-Up Assessment; G-CBS = German Compulsive Buying Scale; GSH = Guided Self-help; ICD-SCID = Structured Clinical Interview for impulse control disorders; Richmond-CBS = Richmond Compulsive Buying Scale; SCID = semi-structured interview modeled after the Schedules for clinical assessment in neuropsychiatry; Valence-CBS = Valence Compulsive Buying Scale; WL = Waiting List; Y-BOCS-SV = Yale–Brown Obsessive Compulsive Scale-Shopping Version.

All identified studies included treatment-seeking patients with the primary diagnosis being CBSD. Most studies ( Benson et al., 2014 ; Black et al., 2000 ; Filomensky & Tavares, 2009 ; Grant et al., 2012 ; Koran et al., 2002 ; Müller et al., 2013 ; Müller, Mueller, et al., 2008 ) applied the criteria for compulsive buying proposed by McElroy et al. (1994) or a combination of those criteria and questionnaire and/or interview thresholds ( Granero et al., 2017 ; Koran et al., 2003 , 2007 ) to define patients with CBSD. Other studies reported that they used a questionnaire only ( Mitchell et al., 2006 ) or a structured clinical interview ( Ninan et al., 2000 ). The additional search for preregistered ongoing treatment trials did not yield any hits.

Sample characteristics and interventions

None of the included studies specifically addressed online CBSD. The preferred mode of buying/shopping ( N = 39; 89% in-store, 6% internet, 2% TV, 3% catalogue shopping) was reported in only one study ( Mitchell et al., 2006 ). Most of the 13 identified studies were conducted in the United States ( Benson et al., 2014 ; Black et al., 2000 ; Grant et al., 2012 ; Koran et al., 2002 , 2003 , 2007 ; Mitchell et al., 2006 ; Müller et al., 2013 ; Ninan et al., 2000 ). Two studies were performed in Brazil ( Filomensky & Tavares, 2009 ; Nicoli de Mattos et al., 2020 ) and one study each in Germany ( Müller, Mueller, et al., 2008 ) and Spain ( Granero et al., 2017 ). Within all studies, mean ages of participants ranged between 24.0 and 46.55 years, and the vast majority of participants were women (range 72–100%). Three studies included only women ( Black et al., 2000 ; Koran et al., 2007 ; Mitchell et al., 2006 ). In terms of treatment, 193 (87 in controlled studies and 106 in open studies) persons received psychotherapy, 156 (84 in open studies, 72 in controlled studies) received pharmacological treatment, and 149 participants were assigned to a waitlist or placebo-control group. Detailed information on sample characteristics and interventions is provided in Table 2 (open studies) and Table 3 (controlled studies).

With respect to psychotherapy, all but one of the studies used group treatment. In the open psychotherapy study by Granero et al. (2017) , 12 sessions of individual CBT were applied ( Granero et al., 2017 ; Jiménez-Murcia, Aymamí-Sanromà, Gómez-Peña, Álvarez-Moya, & Vallejo, 2006 ). Another open study used 20 sessions group CBT with particular focus on identifying and changing cognitive patterns that influence buying/shopping behavior ( Filomensky & Tavares, 2009 ). Four psychotherapy studies compared group psychotherapy with waitlist ( Benson et al., 2014 ; Mitchell et al., 2006 ; Müller et al., 2013 ; Müller, Mueller, et al., 2008 ) and one of them also compared telephone-guided self-help (GSH) with the waitlist condition ( Müller et al., 2013 ). Three of the four controlled studies were based on the same 12-session CBT manual ( Müller & Mitchell, 2011 ; Müller, Mitchell, & de Zwaan, 2008 ). The fourth controlled 12-session group psychotherapy study applied a combination of CBT, dialectical behavior therapy (DBT), psychodynamic psychotherapy (PD), acceptance and commitment therapy (ACT) and mindfulness-based interventions ( Benson et al., 2014 ). In the pharmacological studies different medications were tested: selective serotonin re-uptake inhibitors (SSRIs) ( Black et al., 2000 ; Koran et al., 2002 , 2003 , 2007 ; Ninan et al., 2000 ), the N-methyl-D-aspartate receptor antagonist memantine ( Grant et al., 2012 ) and the anticonvulsant topiramate ( Nicoli de Mattos et al., 2020 ). The rationale for the use of SSRIs was based on analogies between CBSD and obsessive-compulsive disorders (i.e., repetitive problematic behavior, preoccupation). It was assumed that enhancement of serotonergic neurotransmission would decrease the extreme preoccupations with buying/shopping and the repetitive consumption activities ( Black et al., 2000 ; Koran et al., 2002 , 2003 ). With regard to memantine it was presumed that the medication would improve patients' cognitive flexibility and response inhibition by modulating glutamatergic neurotransmission in the cortex, resulting in an improvement of CBSD ( Grant et al., 2012 ). The anticonvulsant topiramate was used to facilitate neurotransmission of γ-aminobutyric acid (GABA) and to inhibit glutamatergic activity, leading to reduced neural excitability and modulation of dopamine activity in the brain reward circuity ( Nicoli de Mattos et al., 2020 ). Topiramate has a complex effect on both the GABAergic and glutamatergic system and may regulate the functioning of the nucleus accumbens in addictive processes ( Nourredine et al., 2021 ).

In the open medication studies the SSRI citalopram ( Koran et al., 2002 ) or the N-methyl-D-aspartate receptor antagonist memantine ( Grant et al., 2012 ) was administered over 10 or 12 weeks respectively. Two controlled medication studies investigated the SSRI fluvoxamine ( Black et al., 2000 ; Ninan et al., 2000 ). Another two studies started with an open-label phase with the SSRIs citalopram ( Koran et al., 2003 ) or escitalopram ( Koran et al., 2007 ) over seven weeks followed by a nine-week double-blind discontinuation phase. The most recent study tested the anticonvulsant topiramate over nine to 12 weeks against placebo pills ( Nicoli de Mattos et al., 2020 ).

Primary outcome measures

Table 4 provides an overview of measures that were applied to assess changes in CBSD symptomatology or other treatment outcomes. Most studies made use of the shopping adaptation ( Monahan, Black, & Gabel, 1996 ) of the Yale-Brown Obsessive-Compulsive Scale (YBOCS) ( Goodman, Price, Rasmussen, Mazure, Delgado, et al., 1989 ; Goodman, Price, Rasmussen, Mazure, Fleischmann, et al., 1989 ) and/or the Compulsive Buying Scale (CBS) ( Faber & O'Guinn, 1992 ) as primary outcome(s). While the YBOCS-shopping version (YBOCS-SV) is a widely used instrument to measure severity and change in shopping obsessions and compulsions ( Monahan et al., 1996 ), the CBS was developed as a screening tool for CBSD ( Faber & O'Guinn, 1992 ).

Table 4.

Measures that were applied to assess changes in CBSD symptomatology and other treatment outcomes across included studies

Other questionnaires that were utilized to assess changes in CBSD symptomatology were the Compulsive Buying Measurement Scale developed by Valence, d'Astous, and Fortier (1988) , the Richmond Compulsive Buying Scale ( Ridgway, Kukar-Kinney, & Monroe, 2008 ), German Compulsive Buying Scale ( Raab, Neuner, Reisch, & Scherhorn, 2005 ), Compulsive Buying Follow-up Scale ( Nicoli de Mattos, Zambrano Filomensky, & Tavares, 2019 ), and Impulse Buying Tendency Scale ( Weun, Jones, & Beatty, 1998 ). Furthermore, purchasing recalls ( Benson et al., 2014 ; Mitchell et al., 2006 ) and compliance to the treatment guidelines, relapse and drop-out rates ( Granero et al., 2017 ) were used as primary outcome measures.

Detailed information on risk of bias assessment is given in Table 5 . The quality of reporting scores ranged between 11 and 47. Three studies ( Müller et al., 2013 ; Müller, Mueller, et al., 2008 ; Nicoli de Mattos et al., 2020 ) reached a RoB assessment score higher than 50% of possible points. Only three studies were registered ( Grant et al., 2012 ; Müller, Mueller, et al., 2008 ; Nicoli de Mattos et al., 2020 ).

Table 5.

Risk of bias (RoB) assessment with CONSORT items

Note . References are sorted from lowest to highest risk of bias with higher sum scores indicating lower risk of bias. A detailed description of the CONSORT items can be retrieved from Moher et al. (2012) . If no evaluation of the item was possible (e.g., open studies, no randomization), no rating was given.

1a = Identify as an “N-of-1 trial” in the title. For series: Identify as “a series of N-of-1 trials” in the title, 1b = Structured summary of trial design, 2a = Scientific background and explanation of rationale, 2b = Specific objectives or hypotheses, 3a = Describe trial design, planned number of periods, and duration of each period (including run-in and wash out, if applicable) and in addition for series: Whether and how the design was individualized to each participant, and explain the series design, 3b = Important changes to methods after trial start, 4a = Diagnosis or disorder, diagnostic criteria, comorbid conditions, and concurrent therapies. For series: Eligibility criteria for participants, 4b = Settings and locations where the data were collected, 4c = Whether the trial(s) represents a research study and if so, whether institutional ethics approval was obtained, 5 = The interventions for each period with sufficient details to allow replication, including how and when they were actually administered, 6a = Completely defined pre-specified primary and secondary outcome measures, including how and when they were assessed, 6b = Any changes to trial outcomes after the trial commenced, with reasons, 7a = How sample size was determined, 7b = When applicable, explanation of any interim analyses and stopping guidelines, 8a = Whether the order of treatment periods was randomized, with rationale, and method used to generate allocation sequence, 8b = When applicable, type of randomization; details of any restrictions, 9 = Mechanism used to implement the random allocation sequence, describing any steps taken to conceal the sequence until interventions were assigned, 10 = Who generated the random allocation sequence, who enrolled participants, and who assigned participants to interventions, 11a = If done, who was blinded after assignment to interventions and how, 11b = If relevant, description of the similarity of interventions, 12a = Methods used to summarize data and compare interventions for primary and secondary outcomes, 12b = For series: If done, methods of quantitative synthesis of individual trial data, including subgroup analyses, adjusted analyses, and how heterogeneity between participants was assessed, 13a = For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analyzed for the primary outcome, 13b = For each group, losses and exclusions after randomization, together with reasons, 14a = Dates defining the periods of recruitment and follow-up, 14b = Whether any periods were stopped early and/or whether trial was stopped early, with reason(s), 15 = A table showing baseline demographic and clinical characteristics for each group, 16 = For each intervention, number of periods analyzed. In addition, for series: if quantitative synthesis was performed, number of trials for which data were synthesized, 17a = For each primary and secondary outcome, results for each group, and the estimated effect size and its precision, 17b = For binary outcomes, presentation of both absolute and relative effect sizes is recommended, 18 = Results of any other analyses performed, including assessment of carryover effects, period effects, intra-subject correlation. In addition for series: If done, results of subgroup or sensitivity analyses, 19 = All harms or unintended effects for each intervention, 20 = Trial limitations, addressing sources of potential bias, imprecision, and, if relevant, multiplicity of analyses, 21 = Generalizability of the trial findings, 22 = Interpretation consistent with results, balancing benefits and harms, and considering other relevant evidence, 23 = Registration number and name of trial registry, 24 = Where the full trial protocol can be accessed, if available, 25 = Sources of funding and other support, role of funders.

The sample size of most studies was small. This is also true for the three studies with the highest RoB scores, which had 31 ( Müller, Mueller, et al., 2008 ) or 22 patients ( Müller et al., 2013 ) in their CBT groups or 25 patients in the verum group ( Nicoli de Mattos et al., 2020 ). An a priori sample size determination was reported in the placebo-controlled medication study by Nicoli de Mattos et al. (2020) but in none of the other studies. The open psychotherapy study by Granero et al. (2017) examined the largest sample with 97 patients. In some studies, there were even fewer than 10 patients in the psychotherapy ( Benson et al., 2014 ; Filomensky & Tavares, 2009 ) or verum ( Grant et al., 2012 ; Koran et al., 2003 , 2007 ) groups.

Main treatment outcomes

Psychotherapy.

Almost all psychotherapy studies reported significant changes in symptoms of CBSD measured with the CBS and/or YBOCS-SV from baseline to end of treatment ( Benson et al., 2014 ; Filomensky & Tavares, 2009 ; Mitchell et al., 2006 ; Müller et al., 2013 ; Müller, Mueller, et al., 2008 ). Granero et al. (2017) used different outcomes and reported about good compliance with therapy guidelines in only 23% of participants (50% moderate, 28% bad compliance), relapses during the CBT program in 47% and risk of dropout in 46% of the sample.

To ensure good comparability between studies, quantitative analyses refer to the CBS ( Faber & O'Guinn, 1992 ) and YBOCS-SV ( Monahan et al., 1996 ) as primary endpoints. Two studies did not report CBS or YBOCS-SV means by group ( Benson et al., 2014 ; Filomensky & Tavares, 2009 ) and, as mentioned above, one study used other outcome variables ( Granero et al., 2017 ). Therefore, quantitative synthesis was performed for the three remaining trials ( Mitchell et al., 2006 ; Müller et al., 2013 ; Müller, Mueller, et al., 2008 ), presented in Table 6 . The results indicate advantage of group CBT over waitlist across the studies and maintenance of treatment effects or even further improvement of CBSD at six-months-follow-ups ( Mitchell et al., 2006 ; Müller et al., 2013 ; Müller, Mueller, et al., 2008 ). In the only three-arm study, group CBT and GSH were compared with a waitlist condition ( Müller et al., 2013 ). At first glance, the within group effect sizes for the CBS and YBOCS-SV in Table 6 suggest comparable superiority of CBT and GSH to wait list. Between group effect sizes, defined as the difference between the end-of-treatment means of the CBT or GSH group and the waitlist group divided by the pooled standard deviation, were reported for CBT vs. waitlist (CBS d = 1.00; YBOCS-SV d = 0.68) and GSH vs. waitlist (CBS d = 0.37; YBOCS-SV d = 0.36) but not for CBT vs. GSH ( Müller et al., 2013 ). The authors also provided information on clinically significant intra-individual changes in YBOCS-SV and CBS scores by using the reliable change index (RCI) ( Jacobson & Truax, 1991 ). Participants in the CBT ( n = 22) and GSH ( n = 20) groups reported comparable clinical change from baseline to end of treatment in YBOCS-SV scores (CBT 50%, GSH 45%) that exceeded that in the waitlist condition ( n = 14; 36% clinical change), whereas clinical relevant changes in CBS scores were found in 50% of the CBT, 10% of the GSH and 14% of the waitlist group ( Müller et al., 2013 ).

Table 6.

Quantitative synthesis of controlled psychotherapy studies sorted by risk of bias assessment

Note . RoB = risk of bias based on CONSORT criteria (higher scores indicate lower risk of bias), CBS = Compulsive Buying Scale, YBOCS-SV = Yale-Brown Obsessive-Compulsive Scale, FU = follow-up, CBT = cognitive behavioral therapy, GSH = guided self-help, WLC = waiting list control.

Cohen's d and 95% confidence intervals (CI) are reported. Positive d CBS and negative d YBOCS-SV indicate improvement. a based on published intention-to-treat analysis, b based on published completer analysis. The findings of the controlled psychotherapy study by Benson et al. (2014) are not included in the quantitative synthesis because YBOCS-SV means and SDs were not provided by group.

Pharmacological treatment

Table 7 lists the results of the quantitative analysis of controlled pharmacological studies. Because the YBOCS-SV ( Monahan et al., 1996 ) was a primary endpoint reported across all medication studies, the analysis refers to the YBOCS-SV results to ensure comparability. The findings of the three placebo-controlled studies ( Black et al., 2000 ; Nicoli de Mattos et al., 2019 ; Ninan et al., 2000 ) did not suggest superiority of medication over placebo regardless of the drug used. Participants receiving the SSRI and those taking placebo pills improved similarly, indicating a high placebo response rate. In the study by Black et al. (2000) , for example, over 60% of placebo-treated participants showed at least moderate improvement in CBSD symptomatology.

Table 7.

Quantitative synthesis of controlled pharmacological studies sorted by risk of bias assessment

Note. RoB = risk of bias based on CONSORT criteria (higher scores indicate lower risk of bias), YBOCS-SV = Yale-Brown Obsessive-Compulsive Scale.

Cohen's d and 95% confidence intervals (CI) are reported. All based on published intention-to-treat analyses. Negative d YBOCS-SV indicate the effect size of improvement in compulsive buying-shopping disorder symptoms. a double-blind discontinuation phase of an open-label study.

The findings of the double-blind discontinuation phase reported by Koran et al. (2007) are not included in the quantitative synthesis because YBOCS-SV means and SDs were not provided by group.

The findings of the two open-label studies followed by a double-blind discontinuation phase revealed mixed results. Koran et al. (2003) reported maintained improvement in the citalopram and deterioration of CBSD symptoms in the placebo group in the discontinuation phase. They evaluated the YBOCS-SV results not only continuously (means and SD s) but also categorically (i.e. Y-BOCS-SV scores ≥17 at end of treatment were defined as relapse) and found no relapses in the medication group compared to a relapse rate of 63.5% in the placebo group ( Koran et al., 2003 ). The findings of the double-blind discontinuation phase reported by Koran et al. (2007) in a later study are not included in Table 7 because YBOCS-SV means and SD s were not provided by group. However, the relapse rates were reported and indicated no difference between the escitalopram and the placebo group (62.5% vs. 66.7%, respectively) ( Koran et al., 2007 ).

Predictors of outcome

Being male, high levels of depressive and obsessive-compulsive symptoms, low levels of anxiety symptoms and the personality traits high persistence, high harm avoidance and low self-transcendence (measured with the Temperament and Character Inventory-Revised ( Cloninger, 1999 ) predicted poor therapy adherence in the open CBT study by Granero et al. (2017) . In one of the controlled group CBT trials, more symptoms of hoarding disorder at baseline and a lower number of visited group sessions were associated with poorer treatment outcome ( Müller, Mueller, et al., 2008 ).

Discussion and conclusions

The aim of the present work was to perform a systematic update on treatment studies for CBSD published since 2000, with a particular focus on online CBSD. Our findings indicate that there is still a paucity of treatment studies for CBSD. Since the systematic reviews published through November 2022 ( Goslar et al., 2020 ; Hague et al., 2016 ; Leite, Pereira, et al., 2014 ; Soares et al., 2016 ), no new controlled psychotherapy studies and only one new medication study ( Nicoli de Mattos et al., 2020 ) were conducted. A search on established public trial registers revealed no evidence of currently ongoing preregistered treatment trials.

It is necessary to address overlaps and differences between the present systematic review and the recently published work by Vasiliu (2022) . Both systematic reviews meet high quality standards, were performed in accordance with the PRISMA 2020 statement ( Page et al., 2021 ), searched on established databases and assessed the quality of included reports using standardized checklists. Differences between the two systematic reviews refer to e.g., search strategies, qualitative and quantitative analyses of outcomes, and preregistration. Vasiliu (2022) included primary and secondary reports (i.e. clinical reports, clinical and epidemiological studies, reviews) on therapeutic management of CBSD published between 1990 and July 2022 and provided treatment recommendations by using GRADE criteria ( Lewin et al., 2018 ). In contrast to Vasiliu's work, the present systematic review was preregistered, has a clear focus on original research (i.e. case reports, reviews and meta-analyses were excluded) published between 2000 and December 2022, uses more comprehensive search terms, provides quantitative analyses of primary outcomes (effect sizes) and evaluates the quality of reporting of included studies based on CONSORT guideline ( Moher et al., 2012 ). Therefore, the current work is not only an update of the systematic reviews published before 2022, but adds to the literature on treatment for CBSD beyond the work of Vasiliu (2022) . In the following, we will discuss the advantages and disadvantages of included studies in detail and provide recommendations for further treatment research.

None of the studies addressed online CBSD specifically. The preferred shopping environment was reported only in the very first CBT study, which was performed more than 17 years ago ( Mitchell et al., 2006 ). The information was not considered in further analyses, likely because the vast majority of patients had indicated offline shopping (89%) ( Mitchell et al., 2006 ). The lack of new treatment studies for CBSD and the gap in treatment studies specifically targeting problematic usage of online shopping applications is concerning given the high prevalence of CBSD ( Maraz, Griffiths, & Demetrovics, 2016 ) and the increase in risky online buying/shopping ( Adamczyk, 2021 ; Augsburger et al., 2020 ; Baggio et al., 2022 ; Fineberg, Menchon, et al., 2022 ; Maraz, Katzinger, & Yi, 2021 ; Müller, Steins-Loeber, et al., 2019 ). Below, we first discuss the results of psychotherapy studies and then turn to pharmacological treatment studies for CBSD.

Increasing certainty of pre-existing reviews and conclusions ( Goslar et al., 2020 ; Hague et al., 2016 ; Leite, Pereira, et al., 2014 ; Vasiliu, 2022 ), the present update indicates that CBT, especially group CBT, is useful in the treatment of CBSD. CBT treatments were related to large pre-post and pre-follow-up effect sizes ( Table 6 ). Unfortunately, no conclusions can be drawn about other forms of psychotherapy (e.g., insight-oriented psychotherapy), third wave CBT (e.g., mindfulness-based, schema or acceptance and commitment therapy or behavioral activation) or internet-delivered approaches for CBSD due to the lack of studies. Although the findings consistently emphasize the advantage of CBT, poor methodological quality and the high risk of publication bias reduce the reliability of this conclusion. In terms of reporting bias, only two psychotherapy studies ( Müller et al., 2013 ; Müller, Mueller, et al., 2008 ) reached a RoB assessment score higher than 50% of possible points. Substantial deficits across all psychotherapy studies were found in the report of the sample size determination, randomization procedure, unintended side effects and trial limitations. In all controlled CBT trials, sample sizes were small and ranged from six ( Benson et al., 2014 ) to 31 ( Müller, Mueller, et al., 2008 ) patients in the CBT group. The study by Granero et al. (2017) included a high number of patients ( N = 97), but it did not have a control condition. Only one psychotherapy study was registered ( Müller, Mueller, et al., 2008 ).

Predictors of treatment outcome were examined in two studies ( Granero et al., 2017 ; Müller, Mueller, et al., 2008 ) which reported a negative impact of comorbid mental health problems, e.g., depressive or hoarding symptoms, and specific personality profiles, e.g., high compulsivity, on treatment outcome ( Granero et al., 2017 ; Müller, Mueller, et al., 2008 ). Therapists' treatment adherence and therapeutic elements that may have contributed to the treatment outcome were not explored. Therefore, no insight can be derived regarding which specific psychotherapy techniques made the treatment effective for CBSD. The potential role of unspecified therapeutic factors such as patient engagement, affective experiencing, therapeutic alliance, readiness to change or resource activation ( Tschacher, Junghan, & Pfammatter, 2014 ) must be considered as effective in light of the very high placebo rates in drug trials (which will be discussed below; e.g. ( Black et al., 2000 ; Ninan et al., 2000 )). Moreover, all controlled psychotherapy studies used a group format. It cannot be ruled out that common nonspecific factors of structured group psychotherapy such as e.g., emotional cohesion, sense of belonging, sense of universality, shared action orientation or coping modeling ( Kealy & Kongerslev, 2022 ) were at least as associated with treatment outcome as the specific CBT interventions. It should also be noted that three out of the four controlled CBT studies used the same CBT manual and had a high degree of overlap of study teams ( Mitchell et al., 2006 ; Müller et al., 2013 ; Müller, Mueller, et al., 2008 ) which reduces the generalisability of findings. An even more important critical point regards to the fact that – with a single exception ( Müller et al., 2013 ) – the controlled psychotherapy trials relied exclusively upon waitlist controls. In psychotherapy research it is well known that the interpretation of effect sizes depend upon the choice of the control condition and that testing a treatment against waitlist is not a very strict approach ( Steinert, Stadter, Stark, & Leichsenring, 2017 ). It is questionable whether waiting lists are the appropriate control condition for psychotherapy because common nonspecific therapeutic effects of CBT are not accounted for with waitlist design. Furthermore, potential nocebo effects in the waitlist group may falsely increase the effect size and result in overestimating the efficacy of CBT ( Fineberg, Pellegrini, et al., 2022 ; Leichsenring & Steinert, 2017 ).

Only one psychotherapy study compared both group CBT and low-intensity telephone-guided self-help (GSH) with a waitlist condition ( Müller et al., 2013 ). The within group effect sizes with broad confidence intervals listed in Table 6 might indicate a comparable benefit from group CBT and GSH and that both approaches were equally superior to waitlist. However, the between group effect sizes for CBT or GSH vs. waitlist reported in the original publication ( Müller et al., 2013 ) rather lead to the assumption that this would be an erroneous non-inferiority guess. Unfortunately, the authors failed to report the between-group effect sizes for CBT vs. GSH. Furthermore, no non-inferiority margins that are necessary for comparing two active treatments ( Rief & Hofmann, 2018 ) were defined for the comparison of CBT with GSH ( Müller et al., 2013 ). Therefore, no valid interpretation on the comparability of group CBT and GSH is possible.

For all the criticism of the included CBT studies it should be taken into account that at least some of these studies (e.g., Mitchell et al., 2006 ) had a pilot character and can be viewed as pioneering work in the treatment of behavioral addictions. They were conducted at a time when very little attention was paid to CBSD. Nevertheless, larger sufficiently powered psychotherapy trials with appropriate control conditions and a focus on mechanisms of change, potential moderators (e.g., gender), mediators (e.g., craving responses, inhibitory control, depressive symptoms), and the preferred shopping mode (i.e., offline or online) should be conducted by different study teams. Of-course, this requires a better understanding of mechanisms underlying the development and maintenance of CBSD, which would help to develop more tailored psychotherapy interventions.

Unfortunately, no conclusion at all can be drawn regarding the psychotherapy of online CBSD. One could argue that the promising results of CBT studies could simply be transferred to online CBSD. In our assumption, this is questionable given the specific features of the internet and e-commerce (e.g., availability, anonymity, speed, technology and social-commerce features, specific payment options, convergence of internet application) that may contribute to problematic buying/shopping on the internet or even cause consumers to slip from risky to addictive online buying/shopping. There is already preliminary evidence for the role of individual expectancies and using motives in online CBSD (e.g., buying unobserved, avoiding analogue communication, browsing a huge product variety, satisfying an urge to buy promptly) ( Kukar-Kinney et al., 2009 ; Trotzke et al., 2015 ). However, little is known about the impact of internet-related technology and social commerce features on compulsive online seeking for and purchasing of consumer products ( Clark & Zack, 2023 ; Fineberg, Menchon, et al., 2022 ; Flayelle et al., 2023 ). Research on the interaction between environmental factors and individual affective and cognitive mechanisms in online CBSD is still at the beginning ( Brand, 2022 ; Brand et al., 2021 ; Fineberg, Menchon, et al., 2022 ; Vogel et al., 2018 ). More effort is needed to better understand the role of online access to consumer goods with respect to CBSD. This would stimulate proof-of-concept studies in order to develop new psychotherapy approaches for online CBSD or to augment existing CBT approaches for CBSD by modules that specifically target problematic online buying/shopping.

In terms of pharmacotherapy, our findings are in line with those of previous reviews that indicated a lack of evidence for drug treatment of CBSD ( Goslar et al., 2020 ; Hague et al., 2016 ; Soares et al., 2016 ; Vasiliu, 2022 ). The open-label studies with SSRIs ( Koran et al., 2003 , 2007 ) or glutamatergic medication (memantine) ( Grant et al., 2012 ) suggested an improvement in CBSD symptom severity between baseline and end of treatment but were limited by the lack of a control groups and follow-ups ( Hague et al., 2016 ). Subsequent, controlled trials indicated similar effects of SSRIs and placebo pills ( Black et al., 2000 ; Koran et al., 2007 ; Ninan et al., 2000 ). Only in the study by Koran et al. (2003) the relapse rate was higher in patients who continued taking the SSRI during the nine-week double-blind discontinuation phase after a seven-week open-label phase ( n = 7) as compared to those in the placebo group ( n = 8). Given the small number of patients participating in the discontinuation phase, the interpretation of the results is limited. Nevertheless, the results may encourage further research on the effectiveness of SSRIs in the treatment of CBSD.

The most recent controlled medication study tested the anticonvulsant topiramate against placebo ( Nicoli de Mattos et al. ,2020 ). Topiramate had already shown promise in two earlier CBSD case studies ( Guzman, Filomensky, & Tavares, 2007 ; Ye, Kadia, & Lippmann, 2014 ) and has been used off-label for the treatment of many types of mental disorders with impaired impulse control such as substance use and eating disorders (especially binge eating disorder) (for review see Chapron et al., 2022 ). The study by Nicoli de Mattos et al. (2020) had the lowest publication bias of all studies (psychotherapy and pharmacological) and the largest sample size within the drug trials included in the present review (i.e. n = 25 in each group). Similar to the controlled SSRI trials for CBSD ( Black et al., 2000 ; Koran et al., 2007 ; Ninan et al., 2000 ), topiramate was not shown to be superior to placebo ( Nicoli de Mattos et al., 2020 ). This is in accordance with recent systematic reviews which did not find clear evidence supporting the efficacy of topiramate in the treatment of individuals with high impulsivity ( Chapron et al., 2022 ) or in the spectrum of addictive behaviors ( Nourredine et al., 2021 ). In individuals with gambling disorder, for example, no treatment effect of topiramate on gambling symptom severity was found in a 14-week, double-blind, placebo-controlled trial ( n = 20 topiramate, n = 22 placebo) ( Berlin et al., 2013 ).

The high placebo rates in the pharmacological studies are striking. They were attributed to the positive effects of maintaining a daily diary to monitor CBSD symptoms ( Ninan et al., 2000 ), reviewing buying/shopping episodes and money spent ( Black et al., 2000 ), and other nonspecific factors with beneficial effects, as discussed above with regard to psychotherapy trials. This raises the question to what extent the high numbers of patients meeting responder status by the end of open-label treatments ( Grant et al., 2012 ; Koran et al., 2002 , 2003 , 2007 ) were caused by a placebo effect.

Interestingly, no studies have been conducted with opioid antagonists (e.g., naltrexone, nalmefene) that inhibit dopamine release in the nucleus accumbens and were beneficial in reducing urges to engage in addictive behaviors such as pathological gambling ( Aboujaoude & Salame, 2016 ; Dowling et al., 2022 ; Piquet-Pessoa & Fontenelle, 2016 ). Considering case reports, Grant (2003) had already reported about partial or complete remission of urges to shop in two women and one men with CBSD treated with naltrexone. It must be noted that the findings referred to high-dose naltrexone of 100–200 mg/d which exceeds the recommended naltrexone dosage of 50 mg/d ( Aboujaoude & Salame, 2016 ) that has been shown to be effective in e.g., gambling disorder ( Grant, Kim, & Hartman, 2008 ). High-dose use of naltrexone may pose a risk of liver damage and requires frequent liver function tests ( Grant, 2003 ). This might be one reason why no controlled naltrexone studies have been performed for CBSD to date.

Taken together, the pharmacological studies included in this review are all preliminary with small samples and a heterogeneity in pharmacological treatment approaches. Insufficient understanding of the neurobiological mechanisms involved in CBSD and the lack of consistency surrounding its recognition as formal diagnosis are obstacles to conducting high quality pharmacological studies. In our opinion, it is also doubtful whether a purely drug-based treatment of CBSD, particularly online CBSD, can be successful in the long term given the assumed complex interactions between environmental, social and individual processes ( Brand et al., 2019 ; Kellett & Bolton, 2009 ; Müller, Laskowski, Wegmann, et al., 2021 ; Trotzke, Brand, & Starcke, 2017 ).

It is important to take a critical look at the measures used to define CBSD and treatment outcomes. In almost all studies, the YBOCS-SV ( Monahan et al., 1996 ) and/or CBS ( Faber & O'Guinn, 1992 ) were used. The overlap of instruments across studies is a strength because it facilitates comparability of results, but the suitability of both instruments as diagnostic tools or outcome measures is limited. The YBOCS was modified 30 years ago for CBSD because of phenomenological similarities between obsessive-compulsive disorders and CBSD (i.e., repetitive problematic behavior, intrusive thoughts, resistance to such thoughts) ( Monahan et al., 1996 ). Reliability and validity of the modified for shopping YBOCS version was initially tested in nine patients with CBSD ( Monahan et al., 1996 ). In a Brazilian sample comprising 588 general population participants and 22 individuals with CBSD, the YBOCS-SV showed satisfactory psychometric properties ( Leite, Filomensky, Black, & Silva, 2014 ). Unlike for example the pathological gambling adaptation of the YBOCS ( Pallanti, DeCaria, Grant, Urpe, & Hollander, 2005 ), the YBOCS-SV has not been validated in a larger sample with CBSD. Also, sensitivity to change of the YBOCS-SV has not been systematically investigated. In light of current common theoretical considerations that CBSD is more likely be understood as a disorder due to addictive behaviors ( Brand et al., 2020 ; Müller, Brand, et al., 2019 ) or according to the ICD-11 as an impulse control disorder ( WHO, 2022 ), the fit of an instrument developed for obsessive-compulsive disorders can be questioned. With regard to the use of the CBS it has to be noted that this questionnaire was developed as a screening tool for CBSD and not to diagnose CBSD or to measure change in symptom severity ( Faber & O'Guinn, 1992 ). Some CBS items are outdated (”I wrote a check ….”) or restricted to offline shopping (“When I enter a shopping center …”) ( Faber & O'Guinn, 1992 ). At the same time, it remains to be remembered that only few assessments for CBSD were available at the time when most drug trials were conducted. In the meantime, other questionnaires have been published that reliably and validly measure CBSD symptoms ( Müller, Mitchell, Vogel, & de Zwaan, 2017 ), e.g., the Bergen Shopping Addiction Scale (BSAS) ( Andreassen et al., 2015 ) and its adopted version for online shopping ( Manchiraju, Sadachar, & Ridgway, 2017 ), and the Pathological Buying Screener (PBS) ( Müller, Trotzke, Mitchell, de Zwaan, & Brand, 2015 ). The BSAS is based on the understanding that CBSD represents an addictive behavior ( Andreassen et al., 2015 ). The PBS considers both addictive and impulse-control disorder facets of CBSD ( Müller et al., 2015 ). Cut-off scores for risk of CBSD are available for both the BSAS ( Andreassen et al., 2015 ; Zarate, Fullwood, Prokofieva, Griffiths, & Stavropoulos, 2022 ) and the PBS ( Müller et al., 2015 ; Müller, Trotzke, et al., 2021 ), whereas only the PBS threshold for CBSD was validated in clinical samples ( Fernandez-Aranda et al., 2019 ; Müller, Trotzke, et al., 2021 ). However, none of the currently available questionnaires for CBSD adequately represent the ICD-11 criteria for disorders due to addictive behaviors or impulse control disorders ( WHO, 2022 ) and only the modified BSAS version for online shopping ( Manchiraju et al., 2017 ) refers to online CBSD. There is a need for quantitative measures to assess symptom severity of CBSD. The requisite for valid assessment tools is the conceptualization of CBSD as formal diagnosis with accepted diagnostic criteria. As with other mental disorders, the clarification of diagnostic criteria of CBSD and the recognition of online CBSD as a form of problematic usage of the internet will encourage the establishment of standard diagnostic assessment tools and help researchers to compare the findings across treatment studies ( Fineberg, Menchon, et al., 2022 ; Müller, Laskowski, Trotzke, et al., 2021 ).

Limitations

The present systematic review has some shortcomings. There is a potential risk of search biases given that studies published before 2000, non-English language manuscripts, grey literature and manuscripts that are not registered with PubMed, Scopus, Web of Science or PsycInfo were not considered. However, wide screening strings were used that were likely be over-inclusive. Additionally, manual search of related articles and reference lists was performed to reduce search biases. While case reports were excluded, open-label trials were included even if only a few patients were treated. The quality of reporting was assessed using the CONSORT criteria for randomized controlled trials, which is not entirely appropriate for the RoB rating of open-label studies. This limited approach was used given the small number of controlled studies. It is also important to note that the RoB assessment refers to the study reports. Hence, missing reports in the publications do not necessary mean that these methods were not used in the respective study.

Implications for future research

Research on CBSD treatment would profit from more systematic, high-quality methodology. Regarding psychotherapy, it is time to compare CBT with an active treatment based on a priori sample size determination using predefined non-inferiority margins. Much more attention should be paid to the mechanisms of change, treatment adherence, the role of specific and nonspecific therapeutic factors and negative side effects of treatment. Complementary computerized interventions to improve cognitive and affective processes relevant in addictive behaviors (e.g., cognitive bias modification training) should be investigated in relation to CBSD. Drug studies would benefit from further insight into the neurobiology of CBSD. Last but not least, future studies should systematically assess and consider the preferred shopping environment (offline, online), specifics of online compared to offline buying/shopping activities, comorbid mental disorders (e.g., hoarding disorder, depression, other potential internet-use disorders) and personality profiles (e.g., high impulsivity or compulsivity) when designing, conducting, and interpreting treatment studies.

Given the increasing importance of online shopping, research should address the question of whether the treatment of online CBSD differs from the treatment of traditional CBSD and, if so, in what aspects exactly. Specific online CBSD-related interventions could focus on dealing with constant availability of shopping websites, online shopping cues (e.g, personalized advertisements, social media influencer posts), technology design features, convergence of shopping platforms with other internet applications (e.g., social network sites) and relapse prevention ( Flayelle et al., 2023 ; Müller, Joshi, & Thomas, 2022 ). Considering the findings indicating that younger consumers tend to engage in problematic online shopping more often than older individuals ( Augsbuger et al., 2020 ; Duroy et al., 2014 ; Müller, Steins-Loeber, et al., 2019 ), more research on prevention or interventions targeting youth populations vulnerable to CBSD (e.g., because of high materialistic values endorsement), with a special emphasis on online CBSD, is necessary. Interventions to reduce a materialistic goal orientation related to compulsive buying in young adults have already been examined ( Lekavičienė et al., 2022 ; Parker, Kasser, Bardi, Gatersleben, & Druckman, 2020 ) and should be further elaborated.

Conclusions

To date, no treatment studies have been published specifically for online CBSD. The studies included in this systematic review did not differentiate between a predominant offline and a predominant online CBSD subtype. While group CBT was effective in reducing the symptom severity of CBSD, the results should be interpreted with caution given the absence of appropriate control conditions and the lack of investigation of nonspecific compared to specific treatment effects and mechanisms of change. Different pharmacological approaches have been investigated with serotonergic, glutamatergic and/or GABAergic medication, mainly not indicating superiority over placebo. Both, the psychotherapy and medication studies, were limited due to small samples, poor quality of reporting, and other methodological shortcomings. The present review extends past reviews by addressing online CBSD and considering potential publication bias in accordance with the CONSORT criteria. More high-quality treatment research is needed in the field of CBSD with more emphasis on the CBSD subtype and mechanisms of change.

Funding sources

The work of AM, TAT, SA, SSL and MB on this article was carried out in the context of the Research Unit ACSID, FOR2974, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 411232260.

Authors' contribution

Study concept and design: AM, NML, MB, EG. Initial literature search and screening of titles and abstracts: NML, TAT. Supervision of literature search: SA, AM. Final selection of studies: AM, NML, EG. Examination of full texts of selected articles: AM, EG. Risk of bias evaluation: AM, EG, SSL, MB. Quantitative analysis and interpretation of data: AM, EG. Writing – original draft: AM, EG, NML. Writing – review & editing: AM, EG, TAT, NML, SA, SSL, MB, NT. All authors had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Conflict of interest

The authors declare no conflict of interest. Matthias Brand and Stephanie Antons are associate editors, and Astrid Müller is editorial board member of the Journal of Behavioral Addictions.

Supplementary material

  • Aboujaoude, E., & Salame, W. O. (2016). Naltrexone: A pan-addiction treatment? CNS Drugs , 30 ( 8 ), 719–733. 10.1007/s40263-016-0373-0. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Achtziger, A., Hubert, M., Kenning, P., Raab, G., & Reisch, L. A. (2015). Debt out of control: The links between self-control, compulsive buying, and real debts . Journal of Economic Psychology , 49 , 141–149. 10.1016/j.joep.2015.04.003. [ CrossRef ] [ Google Scholar ]
  • Adamczyk, G. (2021). Compulsive and compensative buying among online shoppers: An empirical study . Plos One , 16 ( 6 ), e0252563. 10.1371/journal.pone.0252563. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • 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. 10.3389/fpsyg.2015.01374. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Antons, S., Engel, J., Briken, P., Krüger, T. H. C., Brand, M., & Stark, R. (2022). Treatments and interventions for compulsive sexual behavior disorder with a focus on problematic pornography use: A preregistered systematic review . Journal of Behavioral Addictions . 10.1556/2006.2022.00061. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Augsburger, M., Wenger, A., Haug, S., Achab, S., Khazaal, Y., Billieux, J., & Schaub, M. P. (2020). The concept of buying-shopping disorder: Comparing latent classes with a diagnostic approach for in-store and online shopping in a representative sample in Switzerland . Journal of Behavioral Addictions , 9 ( 3 ), 808–817. 10.1556/2006.2020.00051. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Baggio, S., Starcevic, V., Billieux, J., King, D. L., Gainsbury, S. M., Eslick, G. D., & Berle, D. (2022). Testing the spectrum hypothesis of problematic online behaviors: A network analysis approach . Addictive Behaviors , 135 , 107451. 10.1016/j.addbeh.2022.107451. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Benson, A. L. (2013). Amanda: An overshopper's recovery story . Journal of Groups in Addiction & Recovery , 8 ( 1 ), 25–35. 10.1080/1556035X.2013.727729. [ CrossRef ] [ Google Scholar ]
  • Benson, A. L., Eisenach, D., Abrams, L., & van Stolk-Cooke, K. (2014). Stopping overshopping: A preliminary randomized controlled trial of group therapy for compulsive buying disorder . Journal of Groups in Addiction & Recovery , 9 ( 2 ), 97–125. 10.1080/1556035X.2014.868725. [ CrossRef ] [ Google Scholar ]
  • Berlin, H. A., Braun, A., Simeon, D., Koran, L. M., Potenza, M. N., McElroy, S. L., … Hollander, E. (2013). A double-blind, placebo-controlled trial of topiramate for pathological gambling . The World Journal of Biological Psychiatry , 14 ( 2 ), 121–128. 10.3109/15622975.2011.560964. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Black, D. W. (2022). Compulsive shopping: A review and update . Current Opinion in Psychology , 46 , 101321. 10.1016/j.copsyc.2022.101321. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Black, D. W., Gabel, J., Hansen, J., & Schlosser, S. (2000). A double-blind comparison of fluvoxamine versus placebo in the treatment of compulsive buying disorder . Annals of Clinical Psychiatry , 12 ( 4 ), 205–211. 10.1023/a:1009030425631. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brand, M. (2022). Can internet use become addictive? Science , 376 ( 6595 ), 798–799. [ PubMed ] [ Google Scholar ]
  • Brand, M., Müller, A., Stark, R., Steins-Loeber, S., Klucken, T., Montag, C., … Wegmann, E. (2021). Addiction research unit: Affective and cognitive mechanisms of specific internet-use disorders . Addiction Biology , 26 ( 6 ), e13087. 10.1111/adb.13087. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brand, M., Rumpf, H. J., Demetrovics, Z., Müller, A., Stark, R., King, D. L., … Fineberg, N. A. (2020). Which conditions should be considered as disorders in the International Classification of Diseases (ICD-11) designation of “other specified disorders due to addictive behaviors”? Journal of Behavioral Addictions . 10.1556/2006.2020.00035. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brand, M., Wegmann, E., Stark, R., Müller, A., Wölfling, K., Robbins, T. W., & Potenza, M. N. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors . Neuroscience and Biobehavioral Reviews , 104 , 1–10. 10.1016/j.neubiorev.2019.06.032. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brand, M., Young, K. S., Laier, C., Wölfling, K., & Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model . Neuroscience and Biobehavioral Reviews , 71 , 252–266. 10.1016/j.neubiorev.2016.08.033. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Bullock, K., & Koran, L. (2003). Psychopharmacology of compulsive buying . Drugs Today (Barc) , 39 ( 9 ), 695–700. 10.1358/dot.2003.39.9.799477. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Chapron, S. A., Nourredine, M., Donde, C., Haesebaert, F., Micoulaud-Franchi, J. A., Geoffroy, P. A., & Rolland, B. (2022). Efficacy and safety of topiramate for reducing impulsivity: A transdiagnostic systematic review and meta-analysis of a common clinical use . Fundamental & Clinical Pharmacology , 36 ( 1 ), 4–15. 10.1111/fcp.12710. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Christenson, G. A., Faber, R. J., de Zwaan, M., Raymond, N. C., Specker, S. M., Ekern, M. D., … Eckert, E. D. (1994). Compulsive buying: Descriptive characteristics and psychiatric comorbidity . The Journal of Clinical Psychiatry , 55 ( 1 ), 5–11. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/8294395 [ PubMed ] [ Google Scholar ]
  • Clark, L., & Zack, M. (2023). Engineered highs: Reward variability and frequency as potential prerequisites of behavioural addiction . Addictive Behaviors , 107626. 10.1016/j.addbeh.2023.107626. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Cloninger, C. R. (1999). The temperament and character inventory-revised . St Louis, MO: Center for Psychobiology of Personality, Washington University. [ Google Scholar ]
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2 nd ed.). Hillsdale, NJ: Erlbaum. [ Google Scholar ]
  • Cumpston, M., & Chandler, J. (2022). Chapter IV: Updating a review . In Higgins J. P. T., Chandler J., Cumpston M., Li T., Page M. J., & Welch V. A. (Eds.), Cochrane handbook for systematic reviews of interventions, version 6.3 . Cochrane. [ Google Scholar ]
  • Dowling, N., Merkouris, S., Lubman, D., Thomas, S., Bowden-Jones, H., & Cowlishaw, S. (2022). Pharmacological interventions for the treatment of disordered and problem gambling . Cochrane Library: Cochrane Reviews , 9 ( 9 ), CD008936. 10.1002/14651858.CD008936.pub2. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Dunlap, W. P., Cortina, J. M., Vaslow, J. B., & Burke, M. J. (1996). Meta-analysis of experiments with matched groups or repeated measures designs . Psychological Methods , 1 ( 2 ), 170. 10.1037/1082-989X.1.2.170. [ CrossRef ] [ Google Scholar ]
  • Duroy, D., Gorse, P., & Lejoyeux, M. (2014). Characteristics of online compulsive buying in Parisian students . Addictive Behaviors , 39 ( 12 ), 1827–1830. 10.1016/j.addbeh.2014.07.028. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Faber, R. J., & O'Guinn, T. C. (1992). A clinical screener for compulsive buying . Journal of Consumer Research , 19 ( 3 ), 459–469. [ Google Scholar ]
  • Fernandez-Aranda, F., Granero, R., Mestre-Bach, G., Steward, T., Müller, A., Brand, M., … Jimenez-Murcia, S. (2019). Spanish validation of the pathological buying screener in patients with eating disorder and gambling disorder . Journal of Behavioral Addictions , 8 ( 1 ), 123–134. 10.1556/2006.8.2019.08. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Fernandez-Aranda, F., Pinheiro, A. P., Thornton, L. M., Berrettini, W. H., Crow, S., Fichter, M. M., … Bulik, C. M. (2008). Impulse control disorders in women with eating disorders . Psychiatry Research , 157 ( 1–3 ), 147–157. 10.1016/j.psychres.2007.02.011. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Filomensky, T. Z., & Tavares, H. (2009). Cognitive restructuring for compulsive buying . Brazilian Journal of Psychiatry , 31 ( 1 ), 77–78. 10.1590/s1516-44462009000100018. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Fineberg, N. A., Menchon, J. M., Hall, N., Dell'Osso, B., Brand, M., Potenza, M. N., … Zohar, J. (2022). Advances in problematic usage of the internet research - a narrative review by experts from the European network for problematic usage of the internet . Comprehensive Psychiatry , 118 , 152346. 10.1016/j.comppsych.2022.152346. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Fineberg, N. A., Pellegrini, L., Clarke, A., Perera, U., Drummond, L. M., Albert, U., & Laws, K. R. (2022). Meta-analysis of cognitive behaviour therapy and selective serotonin reuptake inhibitors for the treatment of hypochondriasis: Implications for trial design . Comprehensive Psychiatry , 118 , 152334. 10.1016/j.comppsych.2022.152334. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Flayelle, M., Brevers, D., King, D., Maurage, P., Perales, J. C., & Billieux, J. (2023). A classification of technology design features promoting addictive online behaviors . Nature Reviews Psychology , 2 , 136–150. 10.1038/s44159-023-00153-4. [ CrossRef ] [ Google Scholar ]
  • Goodman, W. K., Price, L. H., Rasmussen, S. A., Mazure, C., Delgado, P., Heninger, G. R., & Charney, D. S. (1989). The Yale-Brown obsessive compulsive scale. II. Validity . Archives of General Psychiatry , 46 ( 11 ), 1012–1016. 10.1001/archpsyc.1989.01810110054008. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Goodman, W. K., Price, L. H., Rasmussen, S. A., Mazure, C., Fleischmann, R. L., Hill, C. L., … Charney, D. S. (1989). The Yale-Brown obsessive compulsive scale. I. Development, use, and reliability . Archives of General Psychiatry , 46 ( 11 ), 1006–1011. 10.1001/archpsyc.1989.01810110048007. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Goslar, M., Leibetseder, M., Muench, H. M., Hofmann, S. G., & Laireiter, A. R. (2020). Treatments for internet addiction, sex addiction and compulsive buying: A meta-analysis . Journal of Behavioral Addictions , 9 ( 1 ), 14–43. 10.1556/2006.2020.00005. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Granero, R., Fernandez-Aranda, F., Mestre-Bach, G., Steward, T., Bano, M., Aguera, Z., … Jimenez-Murcia, S. (2017). Cognitive behavioral therapy for compulsive buying behavior: Predictors of treatment outcome . European Psychiatry , 39 , 57–65. 10.1016/j.eurpsy.2016.06.004. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Granero, R., Fernandez-Aranda, F., Mestre-Bach, G., Steward, T., Bano, M., Del Pino-Gutierrez, A., … Jimenez-Murcia, S. (2016). Compulsive buying behavior: Clinical comparison with other behavioral addictions . Frontiers in Psychology , 7 , 914. 10.3389/fpsyg.2016.00914. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Grant, J. E. (2003). Three cases of compulsive buying treated with naltrexone . International Journal of Psychiatry in Clinical Practice , 7 ( 3 ), 223–225. [ Google Scholar ]
  • Grant, J. E., Kim, S. W., & Hartman, B. K. (2008). A double-blind, placebo-controlled study of the opiate antagonist naltrexone in the treatment of pathological gambling urges . The Journal of Clinical Psychiatry , 69 ( 5 ), 783–789. 10.4088/jcp.v69n0511. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Grant, J. E., Odlaug, B. L., Mooney, M., O'Brien, R., & Kim, S. W. (2012). Open-label pilot study of memantine in the treatment of compulsive buying . Annals of Clinical Psychiatry , 24 ( 2 ), 119–126. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/22563566 . [ PubMed ] [ Google Scholar ]
  • Guzman, C. S., Filomensky, T., & Tavares, H. (2007). Compulsive buying treatment with topiramate, a case report . Brazilian Journal of Psychiatry , 29 ( 4 ), 383–384. 10.1590/s1516-44462007000400020. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Hague, B., Hall, J., & Kellett, S. (2016). Treatments for compulsive buying: A systematic review of the quality, effectiveness and progression of the outcome evidence . Journal of Behavioral Addictions , 5 ( 3 ), 379–394. 10.1556/2006.5.2016.064. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Jacobson, N. S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research . Journal of Consulting and Clinical Psychology , 59 ( 1 ), 12–19. 10.1037//0022-006x.59.1.12. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Jiménez-Murcia, S., Aymamí-Sanromà, M., Gómez-Peña, M., Álvarez-Moya, E., & Vallejo, J. (2006). Protocols de tractament cognitivoconductual pel joc patològic i d’altres addiccions no tòxiques . Barcelon, Spain: Hospital Universitari de Bellvitge, Departament de Salut, Generalitat de Catalunya. [ Google Scholar ]
  • Kealy, D., & Kongerslev, M. T. (2022). Structured group psychotherapies: Advantages, challenges, and possibilities . Journal of Clinical Psychology , 78 ( 8 ), 1559–1566. 10.1002/jclp.23377. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Kellett, S., & Bolton, J. V. (2009). Compulsive buying: A cognitive-behavioural model . Clinical Psychology & Psychotherapy , 16 ( 2 ), 83–99. 10.1002/cpp.585. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • King, D. L., Delfabbro, P. H., Wu, A. M. S., Doh, Y. Y., Kuss, D. J., Pallesen, S., … Sakuma, H. (2017). Treatment of Internet gaming disorder: An international systematic review and CONSORT evaluation . Clinical Psychology Review , 54 , 123–133. 10.1016/j.cpr.2017.04.002. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Koran, L. M., Aboujaoude, E. N., Solvason, B., Gamel, N. N., & Smith, E. H. (2007). Escitalopram for compulsive buying disorder: A double-blind discontinuation study . Journal of Clinical Psychopharmacology , 27 ( 2 ), 225–227. 10.1097/01.jcp.0000264975.79367.f4. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Koran, L. M., Bullock, K. D., Hartston, H. J., Elliott, M. A., & D'Andrea, V. (2002). Citalopram treatment of compulsive shopping: An open-label study . The Journal of Clinical Psychiatry , 63 ( 8 ), 704–708. 10.4088/jcp.v63n0808. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Koran, L. M., Chuong, H. W., Bullock, K. D., & Smith, S. C. (2003). Citalopram for compulsive shopping disorder: An open-label study followed by double-blind discontinuation . The Journal of Clinical Psychiatry , 64 ( 7 ), 793–798. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12934980 . [ PubMed ] [ Google Scholar ]
  • 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 ( 3 ), 298–307. 10.1016/j.jretai.2009.05.002. [ CrossRef ] [ Google Scholar ]
  • Laskowski, N. M., Trotzke, P., de Zwaan, M., Brand, M., & Müller, A. (2021). Deutsche Übersetzung der Diagnosekriterien für die Kauf-Shopping-Störung [German Translation of the Diagnostic Criteria for Compulsive Buying-Shopping Disorder Consented by International Experts Using the Delphi Method] . SUCHT , 67 ( 6 ), 323–330. 10.1024/0939-5911/a000737. [ CrossRef ] [ Google Scholar ]
  • Leichsenring, F., & Steinert, C. (2017). Is cognitive behavioral therapy the gold standard for psychotherapy?: The need for plurality in treatment and research . JAMA , 318 ( 14 ), 1323–1324. 10.1001/jama.2017.13737. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Leite, P. L., Filomensky, T. Z., Black, D. W., & Silva, A. C. (2014). Validity and reliability of the Brazilian version of Yale-Brown obsessive compulsive scale-shopping version (YBOCS-SV) . Comprehensive Psychiatry , 55 ( 6 ), 1462–1466. 10.1016/j.comppsych.2014.04.012. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Leite, P. L., Pereira, V. M., Nardi, A. E., & Silva, A. C. (2014). Psychotherapy for compulsive buying disorder: A systematic review . Psychiatry Research , 219 ( 3 ), 411–419. 10.1016/j.psychres.2014.05.037. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Lekavičienė, R., Antinienė, D., Nikou, S., Rūtelionė, A., Šeinauskienė, B., & Vaičiukynaitė, E. (2022). Reducing consumer materialism and compulsive buying through emotional intelligence training amongst Lithuanian students . Frontiers in Psychology , 13 , 1–13. 10.3389/fpsyg.2022.932395. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Lewin, S., Bohren, M., Rashidian, A., Munthe-Kaas, H., Glenton, C., Colvin, C. J., … Carlsen, B. (2018). Applying GRADE-CERQual to qualitative evidence synthesis findings—paper 2: How to make an overall CERQual assessment of confidence and create a summary of qualitative findings table . Implementation Science , 13 ( 1 ), 11–23. 10.1186/s13012-017-0689-2. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Manchiraju, S., Sadachar, A., & Ridgway, J. L. (2017). The compulsive online shopping scale (COSS): Development and validation using panel data . International Journal of Mental Health and Addiction , 15 ( 1 ), 209–223. 10.1007/s11469-016-9662-6. [ CrossRef ] [ Google Scholar ]
  • Maraz, A., Griffiths, M. D., & Demetrovics, Z. (2016). The prevalence of compulsive buying: A meta-analysis . Addiction , 111 ( 3 ), 408–419. 10.1111/add.13223. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Maraz, A., Katzinger, E., & Yi, S. (2021). Potentially addictive behaviours increase during the first six months of the Covid-19 pandemic . Journal of Behavioral Addictions , 10 ( 4 ), 912–919. 10.1556/2006.2021.00079. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • McElroy, S. L., Keck, P. E., Jr., Pope, H. G., Jr., Smith, J. M., & Strakowski, S. M. (1994). Compulsive buying: A report of 20 cases . The Journal of Clinical Psychiatry , 55 ( 6 ), 242–248. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/8071278 . [ PubMed ] [ Google Scholar ]
  • Mitchell, J. E., Burgard, M., Faber, R., Crosby, R. D., & de Zwaan, M. (2006). Cognitive behavioral therapy for compulsive buying disorder . Behaviour Research and Therapy , 44 ( 12 ), 1859–1865. 10.1016/j.brat.2005.12.009. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Moher, D., Hopewell, S., Schulz, K. F., Montori, V., Gotzsche, P. C., Devereaux, P. J., … Consort. (2012). CONSORT 2010 explanation and elaboration: Updated guidelines for reporting parallel group randomised trials . International Journal of Surgery , 10 ( 1 ), 28–55. 10.1016/j.ijsu.2011.10.001. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Moher, D., Tsertsvadze, A., Tricco, A., Eccles, M., Grimshaw, J., Sampson, M., & Barrowman, N. (2008). When and how to update systematic reviews . Cochrane Database of Systematic Reviews , 1 . 10.1002/14651858.MR000023.pub3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Monahan, P., Black, D. W., & Gabel, J. (1996). Reliability and validity of a scale to measure change in persons with compulsive buying . Psychiatry Research , 64 ( 1 ), 59–67. 10.1016/0165-1781(96)02908-3. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Arikian, A., de Zwaan, M., & Mitchell, J. E. (2013). Cognitive-behavioural group therapy versus guided self-help for compulsive buying disorder: A preliminary study . Clinical Psychology & Psychotherapy , 20 ( 1 ), 28–35. 10.1002/cpp.773. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Brand, M., Claes, L., Demetrovics, Z., de Zwaan, M., Fernandez-Aranda, F., … Kyrios, M. (2019). Buying-shopping disorder-is there enough evidence to support its inclusion in ICD-11? CNS Spectrums , 24 ( 4 ), 374–379. 10.1017/S1092852918001323. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Joshi, M., & Thomas, T. A. (2022). Excessive shopping on the internet: Recent trends in compulsive buying-shopping disorder . Current Opinion in Behavioral Sciences , 44 , 101116. 10.1016/j.cobeha.2022.101116. [ CrossRef ] [ Google Scholar ]
  • Müller, A., Laskowski, N. M., Trotzke, P., Ali, K., Fassnacht, D., de Zwaan, M., … Kyrios, M. (2021). Proposed diagnostic criteria for compulsive buying-shopping disorder: A Delphi expert consensus study . Journal of Behavioral Addictions , 10 ( 2 ), 208–222. 10.1556/2006.2021.00013. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Laskowski, N. M., Wegmann, E., Steins-Loeber, S., & Brand, M. (2021). Problematic online buying-shopping: Is it time to considering the concept of an online subtype of compulsive buying-shopping disorder or a specific internet-use disorder? Current Addiction Reports , 8 , 494–499. 10.1007/s40429-021-00395-3. [ CrossRef ] [ Google Scholar ]
  • Müller, A., & Mitchell, J. E. (2011). Compulsive buying: Clinical foundations and treatment . New York: Routledge. [ Google Scholar ]
  • Müller, A., Mitchell, J. E., Black, D. W., Crosby, R. D., Berg, K., & de Zwaan, M. (2010). Latent profile analysis and comorbidity in a sample of individuals with compulsive buying disorder . Psychiatry Research , 178 ( 2 ), 348–353. 10.1016/j.psychres.2010.04.021. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Mitchell, J. E., & de Zwaan, M. (2008). Pathologisches Kaufen: Kognitiv-verhaltenstherapeutisches Therapiemanual . Köln: Deutscher Ärzteverlag. [ Google Scholar ]
  • Müller, A., Mitchell, J. E., Vogel, B., & de Zwaan, M. (2017). New assessment tools for buying disorder . Current Addiction Reports , 4 ( 3 ), 221–227. 10.1007/s40429-017-0161-z. [ CrossRef ] [ Google Scholar ]
  • Müller, A., Mueller, U., Silbermann, A., Reinecker, H., Bleich, S., Mitchell, J. E., & de Zwaan, M. (2008). A randomized, controlled trial of group cognitive-behavioral therapy for compulsive buying disorder: Posttreatment and 6-month follow-up results . The Journal of Clinical Psychiatry , 69 ( 7 ), 1131–1138. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/18557665 . [ PubMed ] [ Google Scholar ]
  • Müller, A., Steins-Loeber, S., Trotzke, P., Vogel, B., Georgiadou, E., & de Zwaan, M. (2019). Online shopping in treatment-seeking patients with buying-shopping disorder . Comprehensive Psychiatry , 94 , 152120. 10.1016/j.comppsych.2019.152120. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Trotzke, P., Laskowski, N. M., Brederecke, J., Georgiadou, E., Tahmassebi, N., … Brand, M. (2021). Der Pathological Buying Screener: Validierung in einer klinischen Stichprobe. [The Pathological Buying Screener: Validation in a clinical sample] . Psychotherapie, Psychosomatik, Medizinische Psychologie , 71 ( 07 ): 294–300. 10.1055/a-1303-4743. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Müller, A., Trotzke, P., Mitchell, J. E., de Zwaan, M., & Brand, M. (2015). The Pathological Buying Screener: Development and psychometric properties of a new screening instrument for the assessment of pathological buying symptoms . Plos One , 10 ( 10 ), e0141094. 10.1371/journal.pone.0141094. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Nicoli de Mattos, C., Kim, H. S., Marasaldi, R. F., Requião, M. G., de Oliveira, E. C., Filomensky, T. Z., & Tavares, H. (2020). A 12-week randomized, double-blind, placebo-controlled clinical trial of topiramate for the treatment of compulsive buying disorder . Journal of Clinical Psychopharmacology , 40 ( 2 ), 186–190. 10.1097/JCP.0000000000001183. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Nicoli de Mattos, C., Zambrano Filomensky, T., & Tavares, H. (2019). Development and validation of the compulsive-buying follow-up scale: A measure to assess treatment improvements in compulsive buying disorder . Psychiatry Research , 282 , 112009. 10.1016/j.psychres.2018.12.078. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Ninan, P. T., McElroy, S. L., Kane, C. P., Knight, B. T., Casuto, L. S., Rose, S. E., … Nemeroff, C. B. (2000). Placebo-controlled study of fluvoxamine in the treatment of patients with compulsive buying . Journal of Clinical Psychopharmacology , 20 ( 3 ), 362–366. 10.1097/00004714-200006000-00012. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Nourredine, M., Jurek, L., Angerville, B., Longuet, Y., de Ternay, J., Derveaux, A., & Rolland, B. (2021). Use of topiramate in the spectrum of addictive and eating disorders: A systematic review comparing treatment schemes, efficacy, and safety features . CNS Drugs , 35 ( 2 ), 177–213. 10.1007/s40263-020-00780-y. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews . Journal of Clinical Epidemiology , 134 , 178–189. 10.1016/j.jclinepi.2021.03.001. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Pallanti, S., DeCaria, C. M., Grant, J. E., Urpe, M., & Hollander, E. (2005). Reliability and validity of the pathological gambling adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS) . Journal of Gambling Studies , 21 ( 4 ), 431–443. 10.1007/s10899-005-5557-3. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Park, T. Y., Cho, S. H., & Seo, J. H. (2006). A compulsive buying case: A qualitative analysis by the grounded theory method . Contemporary Family Therapy , 28 ( 2 ), 239–249. 10.1007/s10591-006-9002-2. [ CrossRef ] [ Google Scholar ]
  • Parker, N., Kasser, T., Bardi, A., Gatersleben, B., & Druckman, A. (2020). Goals for good: Testing an intervention to reduce materialism in three European countries . European Journal of Applied Positive Psychology , 4 , 13. [ Google Scholar ]
  • Piquet-Pessoa, M., & Fontenelle, L. F. (2016). Opioid antagonists in broadly defined behavioral addictions: A narrative review . Expert Opinion on Pharmacotherapy , 17 ( 6 ), 835–844. 10.1517/14656566.2016.1145660. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Raab, G., Neuner, M., Reisch, L. A., & Scherhorn, G. (2005). Screeningverfahren zur Erhebung von kompensatorsichem und süchtigem Kaufverhalten (SKSK) . Göttingen: Hogrefe. [ Google Scholar ]
  • Ridgway, N. M., Kukar-Kinney, M., & Monroe, K. B. (2008). An expanded conceptualization and a new measure of compulsive buying . Journal of Consumer Research , 35 ( 4 ), 622–639. 10.1086/591108. [ CrossRef ] [ Google Scholar ]
  • Rief, W., & Hofmann, S. G. (2018). Some problems with non-inferiority tests in psychotherapy research: psychodynamic therapies as an example . Psychological Medicine , 48 ( 8 ), 1392–1394. 10.1017/S0033291718000247. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Soares, C., Fernandes, N., & Morgado, P. (2016). A review of pharmacologic treatment for compulsive buying disorder . CNS Drugs , 30 ( 4 ), 281–291. 10.1007/s40263-016-0324-9. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Steinert, C., Stadter, K., Stark, R., & Leichsenring, F. (2017). The effects of waiting for treatment: A meta-analysis of waitlist control groups in randomized controlled trials for social anxiety disorder . Clinical Psychology & Psychotherapy , 24 ( 3 ), 649–660. 10.1002/cpp.2032. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Trotzke, P., Brand, M., & Starcke, K. (2017). Cue-reactivity, craving, and decision making in buying disorder: A review of the current knowledge and future directions . Current Addiction Reports , 4 ( 3 ), 246–253. 10.1007/s40429-017-0155-x. [ CrossRef ] [ Google Scholar ]
  • Trotzke, P., Starcke, K., Müller, A., & Brand, M. (2015). Pathological buying online as a specific form of internet addiction: A model-based experimental investigation . Plos One , 10 ( 10 ), e0140296. 10.1371/journal.pone.0140296. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Trotzke, P., Starcke, K., Müller, A., & Brand, M. (2019). Cue-induced craving and symptoms of online-buying-shopping disorder interfere with performance on the Iowa Gambling Task modified with online-shopping cues . Addictive Behaviors , 96 , 82–88. 10.1016/j.addbeh.2019.04.008. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Tschacher, W., Junghan, U. M., & Pfammatter, M. (2014). Towards a taxonomy of common factors in psychotherapy-results of an expert survey . Clinical Psychology & Psychotherapy , 21 ( 1 ), 82–96. 10.1002/cpp.1822. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Valence, G., d'Astous, A., & Fortier, L. (1988). Compulsive buying: Concept and measurement . Journal of Consumer Policy , 11 ( 4 ), 419–433. 10.1007/BF00411854. [ CrossRef ] [ Google Scholar ]
  • VanHoose, D. (2011). Ecommerce economics . Taylor & Francis. [ Google Scholar ]
  • Vasiliu, O. (2022). Therapeutic management of buying/shopping disorder: A systematic literature review and evidence-based recommendations . Front Psychiatry , 13 , 1047280. 10.3389/fpsyt.2022.1047280. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Vogel, V., Kollei, I., Duka, T., Snagowski, J., Brand, M., Müller, A., & Loeber, S. (2018). Pavlovian-to-instrumental transfer: A new paradigm to assess pathological mechanisms with regard to the use of internet applications . Behavioural Brain Research , 347 , 8–16. 10.1016/j.bbr.2018.03.009. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Weun, S., Jones, M. A., & Beatty, S. E. (1998). Development and validation of the impulse buying tendency scale . Psychological Reports , 82 ( 3_suppl ), 1123–1133. 10.2466/pr0.1998.82.3c.1. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • WHO . (2022). ICD-11 for mortality and morbidity statistics (Versio: 02/2022 ). Retrieved from https://icd.who.int/en/ . [ Google Scholar ]
  • Ye, L., Kadia, S., & Lippmann, S. (2014). Topiramate and compulsive buying disorder . Journal of Clinical Psychopharmacology , 34 ( 1 ), 174–175. 10.1097/JCP.0b013e3182aa0139. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Zarate, D., Fullwood, L., Prokofieva, M., Griffiths, M. D., & Stavropoulos, V. (2022). Problematic shopping behavior: An item response theory examination of the seven-item Bergen Shopping Addiction Scale . International Journal of Mental Health and Addiction , 1–19. 10.1007/s11469-022-00844-8. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

IMAGES

  1. Final Essay on Obsessive Compulsive Disorder PSYC1023

    compulsive buying disorder essay

  2. Compulsive Buying Disorder: Analysis

    compulsive buying disorder essay

  3. Buying Behavior: A Need or a Disorder Essay Example

    compulsive buying disorder essay

  4. PPT

    compulsive buying disorder essay

  5. Compulsive Buying Disorder: Analysis

    compulsive buying disorder essay

  6. What is Shopping Addiction (Oniomania)? Signs, Causes and Treatment of

    compulsive buying disorder essay

VIDEO

  1. Day 17/30: Financial Intelligence

  2. Obsessive-Compulsive Disorder is not a joke #ocd #mentalhealth #mentalhealthawareness

  3. CAUSES OF PERSONALITY DISORDER AND TREATMENT

COMMENTS

  1. A review of compulsive buying disorder

    Compulsive buying disorder (CBD) is characterized by excessive shopping cognitions and buying behavior that leads to distress or impairment. Found worldwide, the disorder has a lifetime prevalence of 5.8% in the US general population. Most subjects studied clinically are women (~80%), though this gender difference may be artifactual.

  2. Understanding Compulsive Shopping Disorder

    Characteristics of compulsive shopping disorder include: Difficulty resisting the purchase of unneeded items. Financial difficulties because of uncontrolled shopping. Preoccupation with shopping for unneeded items. Problems at work, school, or home because of uncontrolled shopping. Spending a great deal of time researching coveted items and/or ...

  3. Compulsive Buying Behavior: Clinical Comparison with Other Behavioral

    Compulsive buying behavior (CBB), otherwise known as shopping addiction, pathological buying or compulsive buying disorder, is a mental health condition characterized by the persistent, excessive, impulsive, and uncontrollable purchase of products in spite of severe psychological, social, occupational, financial consequences (Müller et al., 2015...

  4. Shopping Addiction: Signs, Causes, and Coping

    Shopping addiction is a behavioral addiction that involves compulsive buying as a way to feel good and avoid negative feelings, such as anxiety and depression. Like other behavioral addictions, shopping addiction can take over as a preoccupation that leads to problems in other areas of your life.

  5. Compulsive Shopping: A Guide to Causes and Treatment

    According to a 2021 paper in the Journal of Behavioral Addictions, the proposed criteria for compulsive shopping include recurrent or persistent dysfunctional shopping-related thoughts and...

  6. Compulsive buying: a review

    Compulsive or pathological buying (or oniomania) is defined as frequent preoccupation with buying or impulses to buy that are experienced as irresistible, intrusive, and/or senseless. The buying behavior causes marked distress, interferes with social functioning, and often results in financial problems.

  7. Compulsive buying disorder

    Compulsive buying disorder Conspicuous consumption Consumer capitalism Consumerism Conviviality Criticism of advertising Culture jamming Degrowth Do it yourself Downshifting Durable good Earth Overshoot Day Ecological economics Ecovillage Ethical consumerism Environmental justice Feminist political ecology Food loss and waste Freeganism

  8. Treatments for compulsive buying: A systematic review of the quality

    Background and Aims. Compulsive buying disorder (CBD) is characterized by excessive or poorly controlled preoccupations, urges, or behaviors regarding shopping and spending, which leads to adverse consequences (Black, 2007).CBD is distinguished by a motivation to feel better, rather than from excessive spending and materialism alone (O'Guinn & Faber, 1989), often creating serious associated ...

  9. Compulsive Buying Disorder: A Review of the Evidence

    Compulsive buying disorder is characterized by excessive or poorly controlled preoccupations, urges, or behaviors regarding shopping and spending that lead to subjective distress or impaired functioning. Compulsive buying disorder is estimated to have a lifetime prevalence of 5.8% in the United States general adult population.

  10. Is Compulsive Buying a Real Disorder, and Is It Really Compulsive?

    The impairment criteria are important because it is how compulsive buying as a disorder is differentiated from more normal, if excessive, buying. Koran et al. found that when using the criterion of 2 standard deviations on the Compulsive Buying Scale, the individuals had significantly more maladaptive shopping and buying attitudes and behaviors ...

  11. Impulsive Buying vs. Compulsive Shopping: What Are the Differences?

    The important distinction between compulsive shopping and impulse buying lies with the internal motivation, or reason, for making purchases. While impulse buying is largely unplanned and happens in reaction to an external trigger—such as seeing a desired item in a shop—compulsive shopping is more inwardly motivated .

  12. Compulsive Buying Disorder: Analysis

    Compulsive buying disorder (CBD) or oniomania is a condition that is currently attracting growing attention among medical practitioners, psychiatrists, psychologists, and physicians. Most of the past studies focusing on this illness have indicated that it affects the experiences and economic outcomes of many individuals.

  13. The Problem And Reason Of Compulsive Buying Disorder

    242) As per scholars (O'Guinn and Faber 1989 p.155), compulsive buying is defined as an act of chronic, repetitive purchasing that became a response to primary negative event or feelings. It is said to provide a short-term gratification, however, that cause harm to individuals /others.

  14. Compulsive Buying Disorder (CBD or CB): How Marketing Plays ...

    Introduction Compulsive buying (known as CBD or CB in this review) is an addictive behavior in which individuals experience pleasure in uncontrollable purchases of material items. Unfortunately, most victims of compulsive buying cannot afford the purchased items nor are the items needed.

  15. Proposed diagnostic criteria for compulsive buying-shopping disorder: A

    Considering that 73.8% of the total expert panel (and 66.7% of master experts) stated that CBSD should be categorized as a disorder due to addictive behaviors, in our opinion, the broader term "buying-shopping disorder" should be viewed as an alternative expression to "compulsive buying disorder" or "compulsive buying-shopping ...

  16. Compulsive buying disorder

    Compulsive buying disorder (CBD) is portrayed by extreme shopping cognitions and purchasing conduct that distress pain or impairment. Discovered around the world, the issue has a lifetime pervasiveness of 5.8% in the US all-inclusive community.

  17. Compulsive Buying Behavior as a Lifestyle Dissertation

    Compulsive buying behavior manifests itself through psychological problems like depression and anxiety. This aspect makes theorists like Faber and O'Guinn (1989) to consider it as a personality disorder. Personality disorder describes perennial maladaptive ways of thinking, feeling, and behaving amongst individuals.

  18. Compulsive Buying Disorder

    Compulsive buying disorder is often an issue of women trying to cope with depression, but this psychological state is not the only reason for the development of the disorder (Müller et al., 2014). The purpose of this study is to explore the perspectives of women in their late 30s who suffer from compulsive buying disorders.

  19. Effects Of Compulsive Buying Disorder

    Compulsive buying disorder or Omniomania commonly known as shopping addiction was recognized in the early nineteenth century, and considered as a psychiatric disorder in the early twentieth century. It is characterized by excessive behavior regarding shopping and spending which may lead to dangerous consequences.

  20. Update on treatment studies for compulsive buying-shopping disorder: A

    Compulsive buying-shopping disorder (CBSD) is mentioned as an example of other specified impulse control disorders in the ICD-11 coding tool, highlighting its clinical relevance and need for treatment. The aim of the present work was to provide a systematic update on treatment studies for CBSD, with a particular focus on online CBSD. Method

  21. Compulsive buying disorder Essays

    Impulse Control Disorders describes compulsive buying as when peoples, "lives are organized around a variety of shopping experiences and whose behavior has prompted concerns that it can lead to a clinical disorder" (book). Rebecca Bloomwood provides an example of someone who displays characteristics of having this compulsive disorder.

  22. Compulsive Buying Disorder (CBD)

    Decent Essays. 438 Words. 2 Pages. Open Document. Compulsive buying disorder (CBD) is portrayed by extreme shopping cognitions and purchasing conduct that distress pain or impairment. Discovered around the world, the issue has a lifetime pervasiveness of 5.8% in the US all-inclusive community. Most subjects contemplated clinically are females ...

  23. Addiction and Compulsive Buying Disorder (CBD) Essay

    There are four distinct phases of CBD they are: anticipation, preparation, shopping, and spending (Black, 2007). The amount of time a person shops is the smallest portion of their addiction. Anticipation occurs when thoughts or urges occur, they may be about a specific item or the act of shopping (Black, 2007).