Evidence map›Paper›PMID 24210772›Full record

ArticleDrug and alcohol dependence2014

Latent class analysis of non-opioid dependent illegal pharmaceutical opioid users in Ohio.

Robert G Carlson, Ramzi W Nahhas, Raminta Daniulaityte, Silvia S Martins, Linna Li, Russel Falck

Open access · greenAbstract read
In one paragraph

Article in Drug and alcohol dependence, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Robert G CarlsonCenter for Interventions, Treatment, and Addiction Research, Department of Community Health, Boonshoft School of Medicine, Wright State University, 3640 Colonel Glenn Highway, Dayton, OH 45435, United States. Electronic address: robert.carlson@wright.edu.
Ramzi W NahhasDivision of Morphological Sciences and Biostatistics, Lifespan Health Research Center, Department of Community Health, Boonshoft School of Medicine, Wright State University, 3171 Research Boulevard, Dayton, OH 45420, United States.
Raminta DaniulaityteCenter for Interventions, Treatment, and Addiction Research, Department of Community Health, Boonshoft School of Medicine, Wright State University, 3640 Colonel Glenn Highway, Dayton, OH 45435, United States.
Silvia S MartinsDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, United States.
Linna LiCenter for Interventions, Treatment, and Addiction Research, Department of Community Health, Boonshoft School of Medicine, Wright State University, 3640 Colonel Glenn Highway, Dayton, OH 45435, United States.
Russel FalckCenter for Interventions, Treatment, and Addiction Research, Department of Community Health, Boonshoft School of Medicine, Wright State University, 3640 Colonel Glenn Highway, Dayton, OH 45435, United States.
Wright State University · USColumbia University · US

Funding

Opioid Use Trajectories and HIV Risk among Young Adults in OhioR01DA023577 · NIDA · WRIGHT STATE UNIVERSITY · PI CARLSON, ROBERT GEOFFREY · 2008 to 2012
$3.1M
NIDA NIH HHS R01 DA023577NIDA NIH HHS R01DA023577
6 · The paper itself

Abstract

backgroundIncreases in non-medical use of pharmaceutical opioids in the U.S. have resulted in increases in opioid dependence and unintentional overdose deaths. We characterize heterogeneity in opioid use patterns among a community-based sample of 18-23 year-olds who use non-medical pharmaceutical opioids, yet are not opioid dependent.

methodsRespondent-driven sampling recruited 390 participants. Latent class analysis stratified by racial/ethnic group identified subgroups of non-medical opioid users based on: six-month frequency of use; number of opioid disorder criteria; oral vs. non-oral administration; number of types of opioids used; use of CNS depressants while under using opioids; and reason for opioid use. Multinomial logistic regression estimated the significance of covariates in predicting class membership.

resultsWithin whites and non-white groups, three classes emerged that were, generally, hierarchically ordered with respect to negative characteristics associated with non-medical opioid use. Within each group, the class with the least negative characteristics also had the highest proportion of individuals who use opioids only to self-medicate a health problem. Within each group's three classes, a larger proportion who had ≥ 2 opioid abuse and dependence disorder criteria always coincided with a larger proportion who use opioids ≥ 3 days per week, a larger proportion who used CNS depressants while under the influence of opioids, and a smaller proportion who used opioids only to self-medicate.

conclusionDifferences in patterns of opioid use within each racial/ethnic group of young people who are not opioid dependent suggest the need for tailored interventions designed to reduce the risk of transition to opioid dependence.

Indexed as

Prescription Drug MisuseAdolescentAnalgesics, OpioidData CollectionFemaleHumansMaleOhioOpioid-Related DisordersSubstance Abuse DetectionYoung AdultAnalgesics, OpioidEmerging adultsLatent class analysisNon-medical pharmaceutical opioid useOpioid dependence

Identifiers

PMID24210772
PMCPMC3865109
OpenAlexW1978327625

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.