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Supplementary Material for: Factors Contributing to Criminal Behavior in the Context of Buying-Shopping Behavior

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Figshare2026-01-06 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Supplementary_Material_for_Factors_Contributing_to_Criminal_Behavior_in_the_Context_of_Buying-Shopping_Behavior/31007428
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Introduction: Individuals with compulsive buying-shopping disorder (CBSD) often engage in criminal behaviors like fraud and theft, influenced by materialistic values, impaired moral judgment, and low self-control. Psychological mechanisms linking CBSD and criminality are yet not well understood. This study examines psychological/personality factors contributing to criminal tendencies in individuals with CBSD. Methods: An online survey recruited participants through social media, websites, and academic institutions. Eligible participants were ≥18 years with German language skills. Ethical approval was granted by Hannover Medical School. Measures included the Pathological Buying Screener (PBS), Materialistic Value Scale, Big Five Inventory, Rosenberg Self-Esteem Scale, the Dirty Dozen for Dark Triad traits, and a self-developed questionnaire on criminal behavior. Results: Forty-three participants scored above (CBSD+) and 166 participants below (CBSD-) the PBS cutoff for CBSD. The CBSD+ group showed higher materialism, lower self-esteem, elevated Dark Triad traits, and more criminal behaviors compared to the CBSD- group. Nearly 70% of the CBSD+ group reported at least one criminal behavior. A multiple linear regression (enter method) identified higher PBS scores, younger age, and lower extraversion as predictors of more criminal buying-shopping-related behaviors. Conclusion: The findings reveal the intricate factors contributing to criminal behavior in CBSD. The lack of significant association between neuroticism, dark personality features and the amount of criminal behaviors needs further investigation. The explained variance of 39% indicates that additional influences on criminal behavior remain to be explored. Future research should aim for more diverse samples and longitudinal designs to enhance generalizability and understanding of these complex relationships.
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2026-01-06
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