{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:15:45Z","timestamp":1787022945787,"version":"build-2736575974"},"reference-count":65,"publisher":"Akademiai Kiado Zrt.","issue":"3","license":[{"start":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T00:00:00Z","timestamp":1664150400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"French Institute for Public Health Research"},{"DOI":"10.13039\/501100006364","name":"French National Cancer Institute","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006364","id-type":"DOI","asserted-by":"crossref"}]},{"name":"French National Health Insurance Fund"},{"name":"French Directorate General of Health"},{"name":"Arc Foundation for Cancer Research"},{"DOI":"10.13039\/501100006364","name":"French National Cancer Institute","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006364","id-type":"DOI","asserted-by":"crossref"}]},{"name":"French National Institute for Prevention and Education in Health"},{"name":"French National Institute of Health and Medical Research"},{"name":"French Inter\u2010Departmental Agency for the Fight against Drugs and Addictive Behaviors"},{"name":"French Social Security Scheme for Liberal Professionals"}],"content-domain":{"domain":["akjournals.com"],"crossmark-restriction":true},"short-container-title":["JBA"],"published-print":{"date-parts":[[2022,9,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and aims<\/jats:title>\n                    <jats:p>Gambling disorder is characterized by problematic gambling behavior that causes significant problems and distress. This study aimed to develop and validate a predictive model for screening online problem gamblers based on players' account data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Two random samples of French online gamblers in skill-based (poker, horse race betting and sports betting,\n                      <jats:italic>n<\/jats:italic>\n                      = 8,172) and pure chance games (scratch games and lotteries,\n                      <jats:italic>n<\/jats:italic>\n                      = 5,404) answered an online survey and gambling tracking data were retrospectively collected for the participants. The survey included age and gender, gambling habits, and the Problem Gambling Severity Index (PGSI). We used machine learning algorithms to predict the PGSI categories with gambling tracking data. We internally validated the prediction models in a leave-out sample.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>When predicting gambling problems binary based on each PGSI threshold (1\u00a0for low-risk gambling, 5 for moderate-risk gambling and 8 for problem gambling), the predictive performances were good for the model for skill-based games (AUROCs from 0.72 to 0.82), but moderate for the model for pure chance games (AUROCs from 0.63 to 0.76, with wide confidence intervals) due to the lower frequency of problem gambling in this sample. When predicting the four PGSI categories altogether, performances were good for identifying extreme categories (non-problem and problem gamblers) but poorer for intermediate categories (low-risk and moderate-risk gamblers), whatever the type of game.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We developed an algorithm for screening online problem gamblers, excluding online casino gamblers, that could enable the setting of prevention measures for the most vulnerable gamblers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1556\/2006.2022.00063","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T09:10:15Z","timestamp":1663665015000},"page":"874-889","update-policy":"https:\/\/doi.org\/10.1556\/policypage.crossmark.crossref.1","source":"Crossref","is-referenced-by-count":19,"title":["Development and validation of a prediction model for online gambling problems based on players' account data"],"prefix":"10.1556","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3701-6693","authenticated-orcid":true,"given":"Bastien","family":"Perrot","sequence":"first","affiliation":[{"name":"Nantes Universit\u00e9, Univ Tours, CHU Nantes, CHU Tours, INSERM, MethodS in Patients Centered Outcomes and HEalth ResEarch, SPHERE, F-44000, Nantes, France"},{"name":"Nantes Universit\u00e9, CHU Nantes, Biostatistics and Methodology Unit, Department of Clinical Research and Innovation, F-44000, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8664-623X","authenticated-orcid":true,"given":"Jean-Benoit","family":"Hardouin","sequence":"additional","affiliation":[{"name":"Nantes Universit\u00e9, Univ Tours, CHU Nantes, CHU Tours, INSERM, MethodS in Patients Centered Outcomes and HEalth ResEarch, SPHERE, F-44000, Nantes, France"},{"name":"Nantes Universit\u00e9, CHU Nantes, Biostatistics and Methodology Unit, Department of Clinical Research and Innovation, F-44000, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5253-3595","authenticated-orcid":true,"given":"Elsa","family":"Thiabaud","sequence":"additional","affiliation":[{"name":"Nantes Universit\u00e9, CHU Nantes, UIC Psychiatrie et Sant\u00e9 Mentale, F-44000, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7482-9597","authenticated-orcid":true,"given":"Ana\u00efs","family":"Saillard","sequence":"additional","affiliation":[{"name":"Nantes Universit\u00e9, CHU Nantes, UIC Psychiatrie et Sant\u00e9 Mentale, F-44000, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0722-7243","authenticated-orcid":true,"given":"Marie","family":"Grall-Bronnec","sequence":"additional","affiliation":[{"name":"Nantes Universit\u00e9, Univ Tours, CHU Nantes, CHU Tours, INSERM, MethodS in Patients Centered Outcomes and HEalth ResEarch, SPHERE, F-44000, Nantes, France"},{"name":"Nantes Universit\u00e9, CHU Nantes, UIC Psychiatrie et Sant\u00e9 Mentale, F-44000, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2238-8005","authenticated-orcid":true,"given":"Ga\u00eblle","family":"Challet-Bouju","sequence":"additional","affiliation":[{"name":"Nantes Universit\u00e9, Univ Tours, CHU Nantes, CHU Tours, INSERM, MethodS in Patients Centered Outcomes and HEalth ResEarch, SPHERE, F-44000, Nantes, France"},{"name":"Nantes Universit\u00e9, CHU Nantes, UIC Psychiatrie et Sant\u00e9 Mentale, F-44000, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"425","reference":[{"issue":"2","key":"B1","series-title":"MOJ Addiction Medicine & Therapy","first-page":"31","article-title":"Should voluntary \u201cself-exclusion\u201d by gamblers be used as a proxy measure for problem gambling?","volume":"2","author":"Auer, M.","year":"2016","unstructured":"Auer, M.\n                  , & \n                     Griffiths, M. D.\n                  \n                (2016). Should voluntary \u201cself-exclusion\u201d by gamblers be used as a proxy measure for problem gambling? \n               \n                  MOJ Addiction Medicine & Therapy\n               , 2(2), 31\u201333, 00019. https:\/\/doi.org\/10.15406\/mojamt.2016.02.00019."},{"key":"B2","series-title":"Journal of Gambling Studies","doi-asserted-by":"publisher","DOI":"10.1007\/s10899-022-10139-1","article-title":"Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting","author":"Auer, M.","year":"2022","unstructured":"Auer, M.\n                  , & \n                     Griffiths, M. D.\n                  \n                (2022). Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting. \n                  Journal of Gambling Studies\n               . https:\/\/doi.org\/10.1007\/s10899-022-10139-1.10.1007\/s10899-022-10139-1"},{"key":"B3","series-title":"Computers in Human Behavior","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.chb.2017.02.004","article-title":"Is gambling involvement a confounding variable for the relationship between Internet gambling and gambling problem severity?","volume":"71","author":"Baggio, S.","year":"2017","unstructured":"Baggio, S.\n                  , \n                     Dupuis, M.\n                  , \n                     Berchtold, A.\n                  , \n                     Spilka, S.\n                  , \n                     Simon, O.\n                  , & \n                     Studer, J.\n                  \n                (2017). Is gambling involvement a confounding variable for the relationship between Internet gambling and gambling problem severity? \n               \n                  Computers in Human Behavior\n               , 71, 148\u2013152. https:\/\/doi.org\/10.1016\/j.chb.2017.02.004.10.1016\/j.chb.2017.02.004"},{"issue":"4","key":"B4","series-title":"Perspectives on Psychological Science","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1111\/j.1745-6916.2007.00051.x","article-title":"Psychology as the science of self-reports and finger movements: Whatever happened to actual behavior?","volume":"2","author":"Baumeister, R. F.","year":"2007","unstructured":"Baumeister, R. F.\n                  , \n                     Vohs, K. D.\n                  , & \n                     Funder, D. C.\n                  \n                (2007). 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Modeling early gambling behavior using indicators from online lottery gambling tracking data: Longitudinal analysis. \n                  Journal of Medical Internet Research\n               , 22(8), e17675. https:\/\/doi.org\/10.2196\/17675.3225404110.2196\/17675"},{"key":"B12","series-title":"Addictive Behaviors","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.addbeh.2019.02.002","article-title":"An experimental investigation of the role of delay discounting and craving in gambling chasing behavior","volume":"93","author":"Ciccarelli, M.","year":"2019","unstructured":"Ciccarelli, M.\n                  , \n                     Cosenza, M.\n                  , \n                     D\u2019Olimpio, F.\n                  , \n                     Griffiths, M. D.\n                  , & \n                     Nigro, G.\n                  \n                (2019). 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