{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T16:32:52Z","timestamp":1787761972369,"version":"build-2784847793"},"reference-count":22,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Opioid use disorder (OUD) is a global concern with a reported shift in changing demographic and biopsychosocial profiles. Characterization of clusters based on diagnostic symptom criteria can help to understand the underlying associations between these criteria.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim:<\/jats:title>\n                    <jats:p>The present study identifies clusters based on OUD diagnostic criteria, which may reveal clinically relevant subgroups of individuals with OUDs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods:<\/jats:title>\n                    <jats:p>The DSM5 diagnostic system OUD diagnosis was made for 204 male participants. An unsupervised clustering analysis focused on the individual 11 DSM5 diagnostic criteria.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Using the DSM5 diagnostic criteria, we obtained two clusters based on severity. Further, analyzing clinical information along with DSM5 criteria, two groups varying in OUD severity, presence of injecting drug use, and employment were identified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Based on cluster analysis, two main clusters of DSM5 criteria emerged. Rather than DSM5 symptoms clustering with each other based on the similarity of symptomatology, they aggregate numerically reflecting severity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/ipj.ipj_430_24","type":"journal-article","created":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T07:00:13Z","timestamp":1744959613000},"page":"32-38","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Classifying opioid use disorder based on diagnostic criteria items using cluster analysis"],"prefix":"10.4103","volume":"34","author":[{"given":"Shweta","family":"Birla","sequence":"first","affiliation":[{"name":"Translational Bioinformatics Group, International Centre for Genetic Engineering Biotechnology (ICGEB), New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vinit","family":"Patel","sequence":"additional","affiliation":[{"name":"National Drug Dependence Treatment Centre, 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