Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries - a machine learning approach

Aug 4, 2026

Adolescents are vulnerable to problematic gambling, with prevalence and risk factors varying by country. This study identifies cross-jurisdictional predictors of higher gambling frequency across 28 European nations using a machine learning framework. Data come from ESPAD, analyzing gambling frequency in the past 12 months as the target classification variable. The dataset includes 7,765 sixteen-year-olds who reported gambling in the previous year.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Article information

Citation and publication details

License and rights

Journal and author affiliations

Abstract and keywords

Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries Citation for published version (APA): Testa, G. , Ruiz-Iniesta, A. , García, O. , Tarragón, E. , Soriano, V. , Benedetti, E. , Cerrai, S. , Molinaro, S. , Brand, M. , Potenza, M. N. , & Mestre-Bach, G. (2025) . Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach. Psychiatry Research, 351, Article 116602. [https://doi.org/10.1016/j.psychres.2025.116602](https://doi.org/10.1016/j.psychres.2025.116602) Document status and date: Published: 01/09/2025 DOI: 10.1016/j.psychres.2025.116602 Document Version: Publisher's PDF, also known as Version of record Document license: Taverne Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement: [www.umlib.nl/taverne-license](www.umlib.nl/taverne-license) Take down policy If you believe that this document breaches copyright please contact us at: [repository@maastrichtuniversity.nl](repository@maastrichtuniversity.nl) providing details and we will investigate your claim. Download date: 03 Aug. 2026 Psychiatry Research 351 (2025) 116602 Contents lists available at ScienceDirect Psychiatry Research journal [homepage: www.elsevier.com/locate/psychres](homepage: www.elsevier.com/locate/psychres) | Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach
Giulia Testa a,1 , Almudena Ruiz-Iniesta b,1 , Oscar Garcíab , Ernesto Tarrag´on b ,
Vicente Soriano b , Elisa Benedetti c, Sonia Cerrai c,d , Sabrina Molinaro c ,
Matthias Brand e,f,g, Marc N. Potenza h,i,j,k,l,m,*, Gemma Mestre-Bach a,*
a Instituto de Transferencia e Investigaci´on (ITEI) -Universidad Internacional de la Rioja, La Rioja, Spain b Universidad Internacional de La Rioja, La Rioja, Spain
c Institute of Clinical Physiology, National Research Council, Italy
d Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, The Netherlands e General Psychology: Cognition, Faculty of Computer Science, University of Duisburg-Essen, Germany
f Center for Behavioral Addiction Research (CeBAR), Center for Translational Neuro-and Behavioral Sciences, University Hospital Essen, University of Duisburg-Essen, Germany
g Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany h Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA i Child Study Center, Yale University Scho

FAQs

What is the purpose of the study?

To identify cross-jurisdictional factors associated with higher gambling frequency among adolescents across 28 European countries using machine learning.

What data source and outcome measure were used?

Data were obtained from ESPAD, and gambling frequency in the past 12 months was used as the objective classification variable.

How was the analysis performed?

A random forest machine learning approach was used to determine the most significant statistical predictors across the 28 countries.

Aug 4, 2026

Upload by Theodora