{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T09:27:17Z","timestamp":1793698037561,"version":"4.5.1"},"reference-count":50,"publisher":"Wiley","issue":"15-17","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"vor","delay-in-days":6,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Substance use disorders (SUDs) are a serious public health concern in the United States. Alcohol and cannabis are two of the most widely used substances. For adolescent\/youth users of alcohol or cannabis, we propose a joint Bayesian learning model to predict their risks of developing alcohol use disorder (AUD) and cannabis use disorder (CUD) in adulthood based on their personal risk factors. The model is trained on nationally representative longitudinal data from Add Health (). It consists of sub\u2010models that predict the two SUDs for three groups of users\u2014those who use alcohol only, cannabis only, and both substances\u2014based on shared as well as unique risk factors. The model comprises ten predictors. We externally validate the model on two independent datasets. The areas under the receiver operating characteristic curves (and 95% CIs) for AUD and CUD, respectively, are: (a) 0.72 (0.70, 0.73) and 0.69 (0.66, 0.70) based on 5\u2010fold cross\u2010validation, (b) 0.75 (0.68, 0.81) and 0.71 (0.62, 0.79) based on validation dataset 1, and (c) 0.65 (0.60, 0.71) and 0.75 (0.70, 0.79) based on validation dataset 2. A simulation study shows that the proposed joint modeling approach generally performs better than separate univariate modeling of the corresponding dependent outcomes in terms of predictive accuracy. Our model may help in identifying adolescent substance users at high risk of developing SUD in adulthood, who can then be helped with appropriate intervention.<\/jats:p>","DOI":"10.1002\/sim.70656","type":"journal-article","created":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T02:31:12Z","timestamp":1783477872000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Bayesian Learning Model for Joint Risk Prediction of Alcohol and Cannabis Use Disorders"],"prefix":"10.1002","volume":"45","author":[{"given":"Rajapaksha Mudalige Dhanushka S.","family":"Rajapaksha","sequence":"first","affiliation":[{"name":"Department of Mathematical Sciences University of Texas at Dallas  Richardson Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingfang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Mathematical Sciences University of Texas at Dallas  Richardson Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thanthirige Lakshika M.","family":"Ruberu","sequence":"additional","affiliation":[{"name":"Department of Mathematical Sciences University of Texas at Dallas  Richardson Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph M.","family":"Boden","sequence":"additional","affiliation":[{"name":"Department of Psychological Medicine University of Otago  Christchurch New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pankaj K.","family":"Choudhary","sequence":"additional","affiliation":[{"name":"Department of Mathematical Sciences University of Texas at Dallas  Richardson Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7758-4460","authenticated-orcid":false,"given":"Swati","family":"Biswas","sequence":"additional","affiliation":[{"name":"Department of Mathematical Sciences University of Texas at Dallas  Richardson Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,7]]},"reference":[{"key":"e_1_2_12_2_1","unstructured":"SAMHSA (Substance Abuse and Mental Health Services Administration) \u201cKey Substance Use and Mental Health Indicators in the United States: Results From the 2024 National Survey on Drug Use and Health \u201d(2025) https:\/\/www.samhsa.gov\/data\/sites\/default\/files\/reports\/rpt56287\/2024\u2010nsduh\u2010annual\u2010national\/2024\u2010nsduh\u2010annual\u2010national\u2010html\u2010071425\u2010edited\/2024\u2010nsduh\u2010annual\u2010national.htm."},{"key":"e_1_2_12_3_1","unstructured":"NIDA (National Institute on Drug Abuse) \u201cCosts of Substance Abuse \u201d(2023) https:\/\/archives.nida.nih.gov\/research\u2010topics\/trends\u2010statistics\/costs\u2010substance\u2010abuse."},{"key":"e_1_2_12_4_1","unstructured":"CDC (Centers for Disease Control and Prevention) \u201cHigh\u2010Risk Substance Use Among Youth \u201d(2023) https:\/\/www.cdc.gov\/healthyyouth\/substance\u2010use\/index.htm."},{"key":"e_1_2_12_5_1","volume-title":"Monitoring the Future National Survey Results on Drug Use, 1975\u20132018","author":"Johnston L. 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