Subtypes in Patients Taking Prescribed Opioid Analgesics and Their Characteristics: A Latent Class Analysis
AffiliationDepartment of Psychology, University of Arizona
latent class analysis
opioid use disorder
MetadataShow full item record
PublisherFrontiers Media S.A.
CitationRauschert, C., Seitz, N.-N., Olderbak, S., Pogarell, O., Dreischulte, T., & Kraus, L. (2022). Subtypes in Patients Taking Prescribed Opioid Analgesics and Their Characteristics: A Latent Class Analysis. Frontiers in Psychiatry, 13.
JournalFrontiers in Psychiatry
RightsCopyright © 2022 Rauschert, Seitz, Olderbak, Pogarell, Dreischulte and Kraus. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractBackground: Owing to their pharmacological properties the use of opioid analgesics carries a risk of abuse and dependence, which are associated with a wide range of personal, social, and medical problems. Data-based approaches for identifying distinct patient subtypes at risk for prescription opioid use disorder in Germany are lacking. Objective: This study aimed to identify distinct subgroups of patients using prescribed opioid analgesics at risk for prescription opioid use disorder. Methods: Latent class analysis was applied to pooled data from the 2015 and 2021 Epidemiological Survey of Substance Abuse. Participants were aged 18–64 years and self-reported the use of prescribed opioid analgesics in the last year (n = 503). Seven class-defining variables based on behavioral, mental, and physical health characteristics commonly associated with problematic opioid use were used to identify participant subtypes. Statistical tests were performed to examine differences between the participant subtypes on sociodemographic variables and prescription opioid use disorder. Results: Three classes were extracted, which were labeled as poor mental health group (43.0%, n = 203), polysubstance group (10.4%, n = 50), and relatively healthy group (46.6%, n = 250). Individuals within the poor mental health group (23.2%, n = 43) and the polysubstance group (31.1%, n = 13) showed a higher prevalence of prescription opioid use disorder compared to those of the relatively healthy group. Conclusion: The results add further evidence to the knowledge that patients using prescribed opioid analgesics are not a homogeneous group of individuals whose needs lie in pain management alone. Rather, it becomes clear that these patients differ in their individual risk of a prescription opioid use disorder, and therefore identification of specific risks plays an important role in early prevention. Copyright © 2022 Rauschert, Seitz, Olderbak, Pogarell, Dreischulte and Kraus.
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VersionFinal published version
Except where otherwise noted, this item's license is described as Copyright © 2022 Rauschert, Seitz, Olderbak, Pogarell, Dreischulte and Kraus. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).