The prevalence of compulsive buying: a meta‐analysis
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Aims: To estimate the pooled prevalence of compulsive buying behaviour (CBB) in different populations and to determine the effect of age, gender, location and screening instrument on the reported heterogeneity in estimates of CBB and whether publication bias could be identified. Methods: Three databases were searched (Medline, PsychInfo, Web of Science) using the terms ‘compulsive buying’, ‘pathological buying’ and ‘compulsive shopping’ to estimate the pooled prevalence of CBB in different populations. Forty studies reporting 49 prevalence estimates from 16 countries were located ( n = 32 000). To conduct the meta‐analysis, data from non‐clinical studies regarding mean age and gender proportion, geographical study location and screening instrument used to assess CBB were extracted by multiple independent observers and evaluated using a random‐effects model. Four a priori subgroups were analysed using pooled estimation (Cohen's Q ) and covariate testing (moderator and meta‐regression analysis). Results: The CBB pooled prevalence of adult representative studies was 4.9% (3.4–6.9%, eight estimates, 10 102 participants), although estimates were higher among university students: 8.3% (5.9–11.5%, 19 estimates, 14 947 participants) in adult non‐representative samples: 12.3% (7.6–19.1%, 11 estimates, 3929 participants) and in shopping‐specific samples: 16.2% (8.8–27.8%, 11 estimates, 4686 participants). Being young and female were associated with increased tendency, but not location ( United States versus non‐ United States ). Meta‐regression revealed large heterogeneity within subgroups, due mainly to diverse measures and time‐frames (current versus life‐time) used to assess CBB. Conclusions: A pooled estimate of compulsive buying behaviour in the populations studied is approximately 5%, but there is large variation between samples accounted for largely by use of different time‐frames and measures.
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There are very few largescale nationally representative epidemiological studies in any of the three proposed disorders, and much of the self-report data comprise small self-selected convenience samples.
“In relation to self-report data, there are very few largescale nationally representative epidemiological studies in any of the three proposed disorders, and much of the self-report data comprise small self-selected convenience samples (Fernandez & Griffiths, 2021; Kuss & Griffiths, 2017; Maraz, Griffiths, & Demetrovics, 2016).”
From Disorders due to addictive behaviors: Further issues, debates, and controversies •: Commentary to the debate: “Behavioral addictions in the ICD-11” (2022) · cites this paper as Maraz, Griffiths, & Demetrovics, 2016
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- Authors
- Maraz, A., Griffiths, M. D., & Demetrovics, Z.
- Affiliations
- Institute of Psychology Eötvös Loránd University Budapest Hungary
- Nottingham Trent University (GB)
- Eötvös Loránd University (HU)
- Venue
- Addiction
- Publisher
- Wiley
- Published
- 2016-01-08
- Volume
- 111
- Issue
- 3
- Pages
- 408-419
- ISSN
- 0965-2140 (ISSN-L)
- 1360-0443
- OpenAlex
- W1921532565
- Cited by
- 380
- References
- 68
- Citations by year
- 2026: 29 · 2025: 42 · 2024: 36 · 2023: 36 · 2022: 52 · 2021: 43 · 2020: 79 · 2019: 15 · 2018: 23 · 2017: 11 · 2016: 14
- FWCI
- 4.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Addiction (publishedVersion)
- PubMed (publishedVersion)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
- Funders
- Eötvös Loránd Tudományegyetem
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Retail Behavior Studies
- Social Sciences › Psychology › Clinical Psychology › Obsessive-Compulsive Spectrum Disorders
- Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Keywords
- compulsive buying, prevalence, university students, age and gender differences, screening tool, publication bias, heterogeneity of prevalence estimates
- MeSH terms
- Australia, Brazil, Commerce, Compulsive Behavior, Europe, Female, Humans, Male, Regression Analysis, Students, Taiwan, United States, Universities, Prevalence, Age Distribution, Sex Distribution, Republic of Korea
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