Abstract
The rapid diffusion of the Internet has made doing things online in addition to in person possible. This has also lead to the emergence of new potential behavioural addictions related to the digital world, such as online shopping addiction. Given the peculiar features of cyberspace, the development of specific instruments for asseessing online shopping addiction appears to be of great importance to promote a better understanding of the phenomenon and effective clinical interventions. On this basis, this research aims to translate and validate the Compulsive Online Shopping Scale (COSS) for the Italian context. A sample of 397 Italian participants (Mage = 32.54 years, SD = 11.16) completed an online survey consisting of the Italian COSS, Edwards Compulsive Buying Scale, Internet Addiction Test, Yale‑Brown Obsessive Compulsive Scale‑ Second Edition, and Barratt Impulsiveness Scale-11. The Confirmatory Factor Analysis (CFA) showed the adequacy of the model fit to the data for a correlational solution with the same 7 factors of the original version: Salience¸ Mood modification¸ Conflict¸ Tolerance¸ Relapse¸ Withdrawal¸ and Problems. Furthermore, good indications of internal consistency, convergent and discriminant validity emerged from the results. Therefore, the Italian COSS seems to be a valid and reliable self-report scale that can be used to assess the risk of compulsive online shopping among Italian-speaking individuals and may be useful for both research and clinical practice.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.