2011
DOI: 10.1176/appi.ps.62.8.900
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Five-Year Trajectories of Long-Term Benzodiazepine Use by Adolescents: Patient, Provider, and Medication Factors

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Cited by 5 publications
(19 citation statements)
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“…However, prevalence of BZD use (1.9 %) among Finnish young adults in 2014 was similar to that reported in France (1.8 %) but lower than reported in studies in the U.S. (2.6 %), Norway (4.0 %) and Taiwan (6.7 %) (Lagnaoui et al 2004, Yeh et al 2011,Nordfjaern et al 2012, Olfson et al 2015).…”
Section: Discussionsupporting
confidence: 73%
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“…However, prevalence of BZD use (1.9 %) among Finnish young adults in 2014 was similar to that reported in France (1.8 %) but lower than reported in studies in the U.S. (2.6 %), Norway (4.0 %) and Taiwan (6.7 %) (Lagnaoui et al 2004, Yeh et al 2011,Nordfjaern et al 2012, Olfson et al 2015).…”
Section: Discussionsupporting
confidence: 73%
“…Among Taiwanese incident BZD users (aged 16-19), 5 % were long-term users (Yeh et al 2011) There is limited population-based knowledge on the use of BZDs among young people due to the fact that most research has been conducted either among adults in general or among older adults (Kurko et al 2016). The objective of this study was to assess nationwide trends in the prevalence of BZD use and long-term use among young adults 18-25 years of age over a nine-year period of 2006-2014 overall and according to gender and active substance.…”
Section: Introductionmentioning
confidence: 99%
“…From a broad perspective, studies have identified similar covariates, including mental health disorders, severity of pain conditions, and healthcare utilization, associated with dissimilar classes of controlled substance users. 8,20 Key covariate differences between C2 and C3 suggest that declines in C3 opioid dispensing post-spike could be attributed to the higher prevalence of overdose events and MAT in this class. Specifically, overdose events could have served as an impetus for MAT and the observed decline in MMEs prior to and during enrollment for some beneficiaries clustering around C3.…”
Section: Covariate Associations With Trajectoriesmentioning
confidence: 99%
“…While understanding the average impact of the program across the LIP‐enrolled population is important, this approach can also mask heterogeneous patterns of LIP response. Indeed, prior research indicates that trajectories of substance use vary markedly across populations . Analyzing variation in opioid dispensing patterns across the LIP‐enrolled population can help us better understand who responds to LIPs and in turn help more effectively target limited program resources.…”
Section: Introductionmentioning
confidence: 99%
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