ArticleAIDS and behavior2018
Patterns of Substance Use and Arrest Histories Among Hospitalized HIV Drug Users: A Latent Class Analysis.
Article in AIDS and behavior, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
The trial behind it
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Latent health behavior classes and associations with depressive symptoms and metabolic syndrome among women with and without HIV in the MACS/WIHS Combined Cohort Study.Journal of health psychology · 2026Article
- Grade-Level Differences in the Profiles of Substance Use and Behavioral Health Problems: A Multi-Group Latent Class Analysis.International journal of environmental research and public health · 2024Article
- High-dose benzodiazepine use and QTc interval prolongation, a latent class analysis study.Scientific reports · 2024Article
- Polysubstance Use Patterns Associated With HIV Disease Severity Among Those With Substance Use Disorders: A Latent Class Analysis.Journal of studies on alcohol and drugs · 2023Article
- Polysubstance Use Patterns among Outpatients Undergoing Substance Use Disorder Treatment: A Latent Class Analysis.International journal of environmental research and public health · 2022Article
- Categorizing Comorbid Risk for People Living With HIV: A Latent Profile Analysis.Journal of acquired immune deficiency syndromes (1999) · 2022Article
- Polysubstance Use Patterns Among High Dose Benzodiazepine Users: A Latent Class Analysis and Differences Between Male and Female Use.Frontiers in psychiatry · 2022Article
- Hispanic participants in the National Institute on Drug Abuse's Clinical Trials Network: A scoping review of two decades of research.Addictive behaviors reports · 2020Article
- Polysubstance use in rural West Virginia: Associations between latent classes of drug use, overdose, and take-home naloxone.The International journal on drug policy · 2020Article
- Substance Use Stigma and Antiretroviral Therapy Adherence Among a Drug-Using Population Living with HIV.AIDS patient care and STDs · 2019Article
- A latent class analysis of the past-30-day substance use patterns among lifetime cocaine users: Findings from a community sample in North Central Florida.Addictive behaviors reports · 2019Article
Corrections and comments
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Authors and funding
9 authors at 8 institutions in 1 country.
Funding
Abstract
Using baseline data from the NIDA Clinical Trials Network 0049 study (Project HOPE), we performed latent class analyses (LCA) to identify discrete classes, or clusters, of people living with HIV (PLWH) based on their past year substance use behaviors and lifetime arrest history. We also performed multinomial logistic regressions to identify key characteristics associated with class membership. We identified 5 classes of substance users (minimal drug users, cocaine users, substantial cocaine/hazardous alcohol users, problem polysubstance users, substantial cocaine/heroin users) and 3 classes of arrest history (minimal arrests, non-drug arrests, drug-related arrests). While several demographic variables such as age and being Black or Hispanic were associated with class membership for some of the latent classes, participation in substance use treatment was the only covariate that was significantly associated with membership in all classes in both substance use and arrest history LCA models. Our analyses reveal complex patterns of behaviors among substance using PLWH and suggest that HIV intervention strategies may need to take into consideration such nuanced differences to better inform future studies and program implementation.
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Registered trials
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.