MSCC 2022

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https://hdl.handle.net/20.500.11868/3670

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    Comparing the Effects of Victimization, School Connectedness, and Social Support on Heterosexual and Sexual Minority Adolescent Suicidality: A Partial Test of Minority Stress Theory
    (MSCC, The University of Tampa, 2022-12) Mandatori, Flavia; Dr. Gabriel Paez; Dr. Rhissa Briones Robinson; Dr. Rachel Severson
    Rising rates of suicide among adolescents constitute a pressing social concern, with extant research emphasizing that sexual minority adolescents are at significantly higher risk for suicide compared to their heterosexual counterparts. Thus, the current study aimed to gain a deeper understanding of the impact that victimization, school connectedness, and social support have on heterosexual and sexual minority adolescent suicidality within the context of Minority Stress Theory (MST). The additional focus of the current study on multiple types of victimization allowed for a comparison of general stressors as predictors of adolescent suicidality. Findings highlighted significant effects of the three abovementioned components of MST on adolescent suicidality. Thus, recommended policy implications include implementing effective strategies to minimize adolescent suicide rates and prevent negative mental health outcomes.
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    Using “Barriers” in Kernel Density Estimation to Improve the Predictive Accuracy of Crime Forecasts: A Case Study of Three Florida Cities
    (MSCC, The University of Tampa, 2022-12) Coates, Kehara; Dr. Timothy C. Hart,; Dr. Gabriel R. Paez; Dr. Chivon H. Fitch
    Kernel density estimation (KDE) is one of the most popular crime hot spot mapping methods used to reduce and prevent crime. However, this technique does not consider where crime cannot occur within a study area when a crime risk surface is interpolated. Therefore, a knowledge gap exists as to how effective incorporating barriers into KDE analysis can be in producing more accurate prospective crime hot spot maps. Therefore, the current study investigated whether the predictive accuracy of crime forecasts based on KDE will improve when barriers to crime are incorporated into the analytic process.