<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title type="main" level="a">Potential risk of gambling products and online gambling among European adolescents</title>
        <author>
          <persName n="1" ref="https://orcid.org/0000-0002-7345-3962" type="ORCID">
            <forename>Elisa</forename>
            <surname>Benedetti</surname>
            <placeName type="affiliation">CNR, National Research Council of Italy, Italy</placeName>
          </persName>
          <persName n="2" ref="https://orcid.org/0000-0003-4337-569X" type="ORCID">
            <forename>Gabriele</forename>
            <surname>Lombardi</surname>
            <placeName type="affiliation">University of Florence, Italy</placeName>
          </persName>
          <persName n="3" ref="https://orcid.org/0000-0002-3586-1033" type="ORCID">
            <forename>Rodolfo</forename>
            <surname>Cotichini</surname>
            <placeName type="affiliation">CNR, National Research Council of Italy, Italy</placeName>
          </persName>
          <persName n="4" ref="https://orcid.org/0000-0002-0774-8586" type="ORCID">
            <forename>Sonia</forename>
            <surname>Cerrai</surname>
            <placeName type="affiliation">CNR, National Research Council of Italy, Italy</placeName>
          </persName>
          <persName n="5" ref="https://orcid.org/0000-0002-7470-2422" type="ORCID">
            <forename>Marco</forename>
            <surname>Scalese</surname>
            <placeName type="affiliation">CNR, National Research Council of Italy, Italy</placeName>
          </persName>
          <persName n="6" ref="https://orcid.org/0000-0001-7221-0873" type="ORCID">
            <forename>Sabrina</forename>
            <surname>Molinaro</surname>
            <placeName type="affiliation">CNR, National Research Council of Italy, Italy</placeName>
          </persName>
        </author>
        <respStmt>
          <resp>This is a section of <title>ASA 2022 Data-Driven Decision Making</title>(DOI: <idno type="DOI">10.36253/979-12-215-0106-3</idno>) by </resp>
          <name>Enrico di Bella, Luigi Fabbris, Corrado Lagazio</name>
        </respStmt>
      </titleStmt>
      <publicationStmt>
        <publisher>Firenze University Press</publisher>
        <pubPlace>Firenze</pubPlace>
        <date when="2023">2023</date>
        <idno type="DOI">https://doi.org/10.36253/979-12-215-0106-3.50</idno>
        <availability>
          <p>Available for academic research purposes</p>
          <p>Open Access</p>
          <p>Copyright Author(s)</p>
          <licence source="text" target="https://creativecommons.org/licenses/by/4.0/legalcode">
            <p>Content licence CC BY 4.0</p>
          </licence>
          <licence source="metadata" target="https://creativecommons.org/publicdomain/zero/1.0/legalcode">
            <p>Metadata licence CC0 1.0</p>
          </licence>
        </availability>
      </publicationStmt>
      <sourceDesc>
        <p>This is original content, published for academic research purposes</p>
      </sourceDesc>
    </fileDesc>
    <encodingDesc>
      <appInfo>
        <application version="2.2" ident="Booksflow">
          <desc>Digital edition XML powered by Booksflow</desc>
        </application>
      </appInfo>
    </encodingDesc>
    <profileDesc>
      <abstract xml:lang="en">
        <p>he increased availability of gambling opportunities resulting from the progressive liberalisation of the gambling sector coupled with the widespread access to online gambling, is raising concerns regarding adolescents’ participation in gambling and possible increase in problem-gambling. However, the influence of the different gambling products commercialised across countries is less known. This is the first study estimating problem gambling (PG) prevalence and examining the contribution of individual factors and gambling products on gambling engagement and PG development among European adolescents. The study used data from a representative cohort of 16-year-old students (n= 85,000) in 33 European countries participating in the 2019 ESPAD survey. In order to control for self-selection a Heckman probit model is estimated, first controlling for the probability of being gambler and then for the correlated probability of becoming a problem gambler. The influence of individual and country-level factors is estimated on both outcomes, as well as among gamblers using each type of gambling products. Participants who reported stronger family support had lower risk of gambling engagement, whilst friends’ support, lack of school connectedness, low monitoring, higher parental education and access to money increased the risk. At the country-level, the higher diffusion of some gambling products was positively associated with gambling engagement. Once controlling for the influence on gambling engagement, factors that still increase the risk of becoming problem gambler independently from the country of origin were the lack of school connectedness and parental monitoring. Specific gambling products and online games increased PG risk. The influence of such factors on PG development is also analysed among gamblers using each product. Supportive family environments, school connectedness and limited access to money appear to be associated with a lower risk of PG among adolescents. At the country-level, governments should better enforce barriers to underage access to gambling products, particularly online.</p>
      </abstract>
      <textClass>
        <keywords>
          <list>
            <item>Gambling</item>
            <item>Adolescents</item>
            <item>Addiction</item>
            <item>Heckprobit</item>
          </list>
        </keywords>
      </textClass>
    </profileDesc>
  </teiHeader>
  <text>
    <body>
      <p>It is available online at https://doi.org/10.36253/979-12-215-0106-3.50<ref target="https://doi.org/10.36253/979-12-215-0106-3.50" /></p>
      <div>
        <listBibl>
          <head>References</head>
          <bibl n="112245">Blanco, C., Moreyra, P., Nunes, E.V., Saiz-Ruiz, J., Ibanez, A. (2001) Pathological gambling: addiction or compulsion?, in Seminars in clinical neuropsychiatry, 6(3), pp. 167-176.</bibl>
          <bibl n="112246">Ch&amp;#180;oliz, M. (2016). The challenge of online gambling: the effect of legalization on the increase in online gambling addiction Journal of Gambling Studies, 32(2), pp. 749-756.</bibl>
          <bibl n="112247">Colasante, E., Pivetta, E., Canale, N., Vieno, A., Marino, C., Lenzi, M., Benedetti, E., King, D.L., Molinaro, S. (2022). Problematic gaming risk among European adolescents: a crossˆanational evaluation of individual and socioˆaeconomic factors. Addiction</bibl>
          <bibl n="112248">Griffiths, M. D., Parke, J. (2010). Adolescent gambling on the Internet: A review. International journal of adolescent medicine and health, 22(1), pp. 59-75.</bibl>
          <bibl n="112249">Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica: Journal of the econometric society, pp. 153-161.</bibl>
          <bibl n="112250">Hardoon, K. K., Derevensky, J. L. (2002). Child and adolescent gambling behavior: Currentmknowledge. Clinical Child Psychology and Psychiatry, 7(2), pp. 263-281.</bibl>
          <bibl n="112251">Lopez-Fernandez, O., Williams, A. J., Griffiths, M. D., Kuss, D. J. (2019). Female gaming, gaming addiction, and the role of women within gaming culture: A narrative literature review. Frontiers in Psychiatry, 10, pp. 454.</bibl>
          <bibl n="112252">Miranda, A., Rabe-Hesketh, S. (2006). Maximum likelihood estimation of endogenous switchingmand sample selection models for binary, ordinal, and count variables. The Stata Journal, 63, pp. 285-308.</bibl>
          <bibl n="112253">
            <bibl>Molinaro, S., Vicente, J., Benedetti, E. (2020). ESPAD Report 2019 Results from the European School Survey Project on Alcohol and Other Drugs. Luxembourg: Publications Office of the European Union, isbn: 978-92-9497-546-1.</bibl>
            <idno type="DOI">10.2810/877033.</idno>
          </bibl>
          <bibl n="112254">Resce, G., Lagravinese, R., Benedetti, E., Molinaro, S. (2019). Income-related inequality in gambling: evidence from Italy. Review of Economics of the Household, 17(4), pp. 1107-1131.</bibl>
          <bibl n="112255">Rockloff, M. J. (2012). Validation of the consumption screen for problem gambling (CSPG). Journal of Gambling Studies, 28(2), pp. 207-216.</bibl>
          <bibl n="112256">Van de Ven, W. P., Van Praag, B. M. (1981). The demand for deductibles in private health insurance: A probit model with sample selection. Journal of Econometrics, 17(2), pp. 229-252.</bibl>
          <bibl n="112257">Welte, J. W., Barnes, G. M., Wieczorek, W. F., Tidwell, M. C. O., Hoffman, J. H. (2007). Type of gambling and availability as risk factors for problem gambling: A Tobit regression analysis by age and gender. International Gambling Studies, 72, pp. 183-198</bibl>
          <bibl n="112258">Williams, R. (2012). Using the margins command to estimate and interpret adjusted predictions and marginal effects. The Stata Journal, 122, pp. 308-331.</bibl>
          <bibl n="112259">Winters, K. C., Stinchfield, R., Fulkerson, J. (1993). Patterns and characteristics of adolescent gambling. Journal of Gambling Studies, 9(4), pp. 371-386.</bibl>
        </listBibl>
      </div>
    </body>
  </text>
</TEI>