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2017
DOI: 10.1007/s10461-017-1929-9
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Latent Class Analysis of HIV Risk Behaviors Among Russian Women at Risk for Alcohol-Exposed Pregnancies

Abstract: The number of HIV cases attributed to heterosexual contact and the proportion of women among HIV positive individuals has increased worldwide. Russia is a country with the highest rates of newly diagnosed HIV infections in the region, and the infection spreads beyond traditional risk groups. While young women are affected disproportionately, knowledge of HIV risk behaviors in women in the general population remains limited. The objectives of this study were to identify patterns of behaviors that place women of… Show more

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Cited by 3 publications
(3 citation statements)
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“…Latent class analysis (LCA) is a statistical methodology that permits detection of groups (latent classes) that cannot be directly observed on the basis of categorical indicator variables alone [ 11 , 12 ]. This methodology has been increasingly used in the behavioral sciences to detect otherwise unobservable at-risk subgroups within a population based on patterns of individual risk-associated behaviors [ 13 , 14 ]. For example, LCA was used to better define substance abuse patterns among women living with HIV and to associate those patterns with likelihood of antiretroviral adherence [ 13 ] The use of computational methods like LCA to deconstruct complex patient decision-making associated with care disengagement may enrich our ability to detect patients at highest risk of falling out of HIV care and subsequently help target retention interventions to appropriate individuals.…”
mentioning
confidence: 99%
“…Latent class analysis (LCA) is a statistical methodology that permits detection of groups (latent classes) that cannot be directly observed on the basis of categorical indicator variables alone [ 11 , 12 ]. This methodology has been increasingly used in the behavioral sciences to detect otherwise unobservable at-risk subgroups within a population based on patterns of individual risk-associated behaviors [ 13 , 14 ]. For example, LCA was used to better define substance abuse patterns among women living with HIV and to associate those patterns with likelihood of antiretroviral adherence [ 13 ] The use of computational methods like LCA to deconstruct complex patient decision-making associated with care disengagement may enrich our ability to detect patients at highest risk of falling out of HIV care and subsequently help target retention interventions to appropriate individuals.…”
mentioning
confidence: 99%
“…chemical substances other than ethanol should be investigated [28,41]. The mechanisms discussed above probably contributed to the growing HIV prevalence in the former SU [63]. Among predisposing social factors, currently becoming more conspicuous in Russia and some other countries, are militarist and machismo ideology [64], whereas promiscuity is sometimes seen as an attribute of "manliness".…”
Section: Discussionmentioning
confidence: 99%
“…One approach to understanding subpopulation profiles is the application of latent class analysis (LCA), a statistical tool that has been utilized to identify and characterize meaningful subpopulations, herein referred to as “classes.” Earlier studies have applied LCA to better understand subpopulation HIV risk profiles (3335), with a primacy of literature focused specifically on class differences in HIV risk based on substance use behaviors (3640). These studies have largely focused on characterizing substance using populations in both San Diego and Tijuana, identifying distinct classes of PWID with varying HIV risk profiles (36, 37, 40).…”
Section: Introductionmentioning
confidence: 99%