Sti, infection, risk, model, sexual network, individual behavior, women
Developing a comprehensive model of Sexually Transmitted Infection (STI) risk factors and their inter-relationships is vital to improving methods of risk identification and treatment delivery. The CDC posed three general categories that may serve as a framework for such a model: sexual network, individual behavior, and social/ structural risk. None of the extant risk models incorporate measures from all three categories. Additionally, none of these models, generally focused on individual behavior, use medical data on infection as their outcome variable. This is problematic because the ultimate outcome of infection is also influenced by sexual network and social/ structural variables, in addition to individual behaviors. Therefore the current study aimed to develop a comprehensive model of risk incorporating sexual network, individual behavior, and social/ structural risk variables, using medical data on infection status as the outcome variable. The sample consisted of 506 women in a court-ordered substance treatment program. An Exploratory Factor Analysis provided preliminary evidence for a three factor model corresponding to the CDC framework. However, a Confirmatory Factor Analysis failed to confirm this model. Additionally, a logistic regression suggested that this model has limited clinical utility for this sample. Future studies may more conclusively determine the importance of various STI risk variables, the relationships between them, and whether they mirror the CDC theoretical framework. With rates of infection still high in the United States, and even increasing among women for certain STIs, this is a critical public health issue that should continue to be examined.
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Master of Science (M.S.)
College of Sciences
Length of Campus-only Access
Masters Thesis (Open Access)
Dissertations, Academic -- Sciences; Sciences -- Dissertations, Academic
Deavers, Frances, "Modeling Risk for Sexually Transmitted Infections in Women in a Court-Ordered Substance Treatment Program" (2014). Electronic Theses and Dissertations. 4829.