Gender Differences in the Influence of Protective Factors, Risk Factors, and Health Risk Behaviors on HIV Risk Behaviors Among Youth in South Florida

Adolescents engage in a range of risk behaviors during their transition from childhood to adulthood. Identifying and understanding interpersonal and socio-environmental factors that may influence risk-taking is imperative in order to meet the Healthy People 2020 goals of reducing the incidence of unintended pregnancies, HIV, and other sexually transmitted infections among youth. The purpose of this study was to investigate gender differences in the predictors of HIV risk behaviors among South Florida youth. More specifically, this study examined how protective factors, risk factors, and health risk behaviors, derived from a guiding framework using the Theory of Problem Behavior and Theory of Gender and Power, were associated with HIV risk behavior. A secondary analysis of 2009 Youth Risk Behavior Survey data sets from Miami-Dade, Broward, and Palm Beach school districts tested hypotheses for factors associated with HIV risk behaviors. The sample consisted of 5,869 high school students (mean age 16.1 years), with 69% identifying as Black or Hispanic. Logistic regression analyses revealed gender differences in the predictors of HIV risk behavior. An increase in the health risk behaviors was related to an increase in the odds that a student would engage in HIV risk behavior. An increase in risk factors was also found to significantly predict an increase in the odds of HIV risk behavior, but only in females. Also, the probability of participation in HIV risk behavior increased with grade level. Post-hoc analyses identified recent sexual activity (past 3 months) as the strongest predictor of condom nonuse and having four or more sexual partners for both genders. The strongest predictors of having sex under the influence of drugs/alcohol were alcohol use in both genders, marijuana use in females, and physical fighting in males. Gender differences in the predictors of unprotected sex, multiple sexual partners, and having sex under the influence were also found. Additional studies are warranted to understand the gender differences in predictors of HIV risk behavior among youth in order to better inform prevention programming and policy, as well as meet the national Healthy People 2020 goals.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Investigation of Escape and Negative Student Behaviors Related to Florida State High Stakes Test Preparation in Miami-Dade County Public High Schools, having been approved in respect to style and intellectual content, is referred to you for judgment

The purpose of this study was to determine whether there was a relationship between pressure to perform on state mandated, high-stakes tests and the rate of student escape behavior defined as the number of school suspensions and absences. The state assigned grade of a school was used as a surrogate measure of pressure with the assumption that pressure increased as the school grade decreased. Student attendance and suspension data were gathered from all 33 of the regular public high schools in Miami-Dade County Public Schools. The research questions were: Is the number of suspensions highest in the third quarter, when most FCAT preparation takes place for each of the 3 school years 2007-08 through 2009-10? How accurately does the high school’s grade predict the number of suspensions and number of absences during each of the 4 school years 2005-06 through 2008-09? The research questions were answered using repeated measures analysis of variance for research question #1 and non-linear multiple regression for research question #2. No significant difference could be found between the numbers of suspensions in each of the grading periods nor was there a relationship between the number of suspensions and school grade. A statistically significant relationship was found between student attendance and school grade. When plotted, this relationship was found to be quadratic in nature and formed a loose inverted U for each of the four years during which data were collected. This indicated that students in very high and very low performing schools had low levels of absences while those in the midlevel of the distribution of school performance (C schools) had the greatest rates of absence. Identifying a relationship between the pressures associated with high stakes testing and student escape behavior suggests that it might be useful for building administrators to reevaluate test preparation activities and procedures being used in their building and to include anxiety reducing strategies. As a relationship was found, it sets the foundation for future studies to identify whether testing related activities are impacting some students emotionally and are causing unintended consequences of testing mandates.