{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T19:49:01Z","timestamp":1775850541615,"version":"3.50.1"},"reference-count":64,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T00:00:00Z","timestamp":1751846400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Drug and Alcohol Review"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Introduction<\/jats:title><jats:p>The period post\u2010residential treatment for opioid use is associated with heightened risk of overdose. The current study aims to: (i) describe characteristics of men and women attending residential treatment for primary opioid use; (ii) identify classes of clients based on primary opioid and other substance\/s of concern and (iii) identify relationships between substance use profile and sociodemographic risk factors for opioid overdose, including differences by gender.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data from 2994 clients (29.6% women) attending residential treatment for opioid use in the non\u2010government sector in New South Wales, Australia, were included in the analysis. Descriptive and chi\u2010square statistics analysed demographic, clinical, substance use and service use characteristics of participants. Participants were grouped using latent class analysis based on their primary opioid of concern and other substance\/s of concern. Multinomial logistic regression examined the relationship between latent classes and sociodemographic risk factors for overdose, including interactions with gender.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Men and women presented to residential treatment with different demographic, clinical, substance use and service use characteristics. A five\u2010class model of polysubstance use was identified: <jats:italic>heroin\u2009+\u2009lower polysubstance use<\/jats:italic> (52.3%), <jats:italic>heroin\u2009+\u2009polysubstance use<\/jats:italic> (22.2%), <jats:italic>pharmaceutical\u2009+\u2009lower polysubstance use<\/jats:italic> (10.1%)<jats:italic>, pharmaceutical\u2009+\u2009polysubstance use<\/jats:italic> (6.7%) and <jats:italic>OAT\u2009+\u2009polysubstance use<\/jats:italic> (8.7%). There were some associations between sociodemographic risk factors and class membership, though limited interactions between sociodemographic risk and gender.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion and Conclusions<\/jats:title><jats:p>Effective overdose prevention and harm reduction strategies during and post\u2010residential treatment need to consider individuals' complex and unique accumulation of risk.<\/jats:p><\/jats:sec>","DOI":"10.1111\/dar.70004","type":"journal-article","created":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T01:24:04Z","timestamp":1751937844000},"page":"1786-1804","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Gender and Overdose Risk Factors Among Clients Entering Residential Treatment for Opioid Use"],"prefix":"10.1111","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2779-5950","authenticated-orcid":false,"given":"Chloe 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