Aniko Maraz1,2, Mark D Griffiths3, Zsolt Demetrovics1. 1. Institute of Psychology, Eötvös Loránd University, Budapest, Hungary. 2. Doctoral School of Psychology, Eötvös Loránd University, Budapest, Hungary. 3. Psychology Division, Nottingham Trent University, Nottingham, UK.
Abstract
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.
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.
Authors: Daniel Zarate; Lana Fullwood; Maria Prokofieva; Mark D Griffiths; Vasileios Stavropoulos Journal: Int J Ment Health Addict Date: 2022-06-20 Impact factor: 11.555
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Authors: Roser Granero; Fernando Fernández-Aranda; Trevor Steward; Gemma Mestre-Bach; Marta Baño; Amparo Del Pino-Gutiérrez; Laura Moragas; Neus Aymamí; Mónica Gómez-Peña; Núria Mallorquí-Bagué; Salomé Tárrega; José M Menchón; Susana Jiménez-Murcia Journal: Front Psychol Date: 2016-04-29
Authors: Roser Granero; Fernando Fernández-Aranda; Gemma Mestre-Bach; Trevor Steward; Marta Baño; Amparo Del Pino-Gutiérrez; Laura Moragas; Núria Mallorquí-Bagué; Neus Aymamí; Mónica Gómez-Peña; Salomé Tárrega; José M Menchón; Susana Jiménez-Murcia Journal: Front Psychol Date: 2016-06-15