Predictors of Opioid Use in Individuals with Pain

Predictors of Opioid Use in Individuals with Pain | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Predictors of Opioid Use in Individuals with Pain Etienne Vachon-Presseau, Azin Zare, Matt Fillingim, Christophe Tanguay-Sabourin, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7538834/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The opioid epidemic remains a major global health crisis. To better understand who is most vulnerable to opioid prescribing, misuse, and opioid-related disorders, we analyzed data from the UK Biobank (n=195,808) and the All of Us Research Program (n=48,390). Opioids were more frequently prescribed to individuals with widespread pain and comorbid clinical conditions. We applied machine learning to evaluate both pain-related and non-pain risk factors separately, and the two models predicted opioid use with good accuracy in both cohorts (AUC 0.70–0.78). Longitudinal analyses showed that psychosocial and functional factors contributed as strongly as pain measurements, predicted opioid initiation nearly nine years later, and were elevated in individuals with opioid misuse and opioid-related disorders. These findings demonstrate that psychiatric, psychosocial, and functional vulnerabilities are sufficient to predict opioid use, and that integrating psychosocial risk profiling into routine pain care could support safer prescribing and mitigate opioid-related harms. Health sciences/Risk factors Health sciences/Health care/Public health/Epidemiology Full Text Additional Declarations There is NO Competing Interest. Supplementary Files supplementarymaterialNatureMed.pdf Supplementary material for Predictors of opioid use in individuals with pain Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7538834","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":512422247,"identity":"1c76048b-f4f8-453e-9ba3-61394179a573","order_by":0,"name":"Etienne 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