Promoting an Operation Cease Fire Approach in Classrooms

This study explores the problem oriented and public health models of youth crime prevention and how to better promote it in the average classroom through strategies and interventions in order to reduce gun violence.

Health beliefs and health care options of disparate black communities in the United States

According to the 1999 U.S. Census, there were approximately thirty-three million African Americans and approximately 1.8 million non-Hispanic black immigrants in the United States. The 1997 U.S. Census estimated that there were as many as 554,000 foreign-born Haitians and 505,000 foreign-born Jamaicans living in the United States, mainly residing in Florida and New York. The U.S. Census claims that blacks are one of the largest emerging ethnic groups in America constituting at least twelve percent of this country's population. Because of this increase, their specific health beliefs and health care options are increasingly nationally significant. ^ In the present intra-black and inter-ethnic study, two hundred seventy African Americans, Haitian immigrants, and Jamaican immigrants residing in South Florida were quantitatively and qualitatively surveyed in order to investigate their health beliefs and health care options. According to the reviewed literature, the three black ethnic groups researched in this study have not been compared or contrasted before in relation to these beliefs and health care choices. ^ As was discovered by the present research, differing health beliefs and health care options were the cultural products of the ethnic differences of the researched communities. It was expected that differing health beliefs among the researched black groups might indicate disparate patterns of health care utilization of either western or non-western models. Additionally, it was projected that by investigating the health beliefs and the health care options of these emerging black ethnic groups, western health care providers in the United States could become better versed in medically servicing growing ethnically-disparate black populations. The study yielded results about the researched groups that supported major findings in the reviewed literature. The data were reported and examined, and theoretical generalizations from the data were discussed. The most important of these findings was that, within a race, health beliefs and health care options were determined by specific ethno-cultural variables dependent on national origins. ^

The role of the health care organization in supporting nurses in the delivery of culturally competent care

This study was designed to explore ways in which health care organizations (HCOs) can support nurses in their delivery of culturally competent care. While cultural competence has become a priority for the federal government as well as the major health professional organizations, its integration into care delivery has not yet been realized. Health professionals cite a lack of educational preparation, time, and organizational resources as barriers. Most experts in the field agree that the cultural and linguistic needs of ethnic minorities pose challenges that individual care providers are unable to manage without the support of the health care organizations within which they practice. While several studies have identified implications for HCOs, there is a paucity of research on their role in this aspect of care delivery. Using a qualitative design with a case study approach, data collection included face-to-face interviews with 23 registered nurses, document analysis, and reports of critical incidents. The site chosen was a large health care system in South Florida that serves a culturally diverse population. Major findings from the study included language barriers, lack of training, difficulty with cultural differences, lack of organizational support, and reliance on culturally diverse staff members. Most nurses thought the ethnic mix was adequate, but rated other supports such as language services, training, and patient education materials as inadequate. Some of the recommendations for organizational performance were to provide the expectations and support for culturally competent care. Implications and recommendations for practice include nurses using trained interpreters instead of relying on coworkers or trying to "wing it", pursuing training, and advocating for organizational supports for culturally competent care. Implications and recommendations for theory included a blended model that combines both models in the conceptual framework. Recommendations for future research were for studies on the impact of language bathers on care delivery, develop and test a quantitative instrument, and to incorporate Gilbert's model into nursing research.

The influence of neighbourhood formality status and socio-economic position on self-rated health among adult men and women: a multilevel, cross sectional, population study from Aleppo, Syria

Background There is substantial evidence from high income countries that neighbourhoods have an influence on health independent of individual characteristics. However, neighbourhood characteristics are rarely taken into account in the analysis of urban health studies from developing countries. Informal urban neighbourhoods are home to about half of the population in Aleppo, the second largest city in Syria (population>2.5 million). This study aimed to examine the influence of neighbourhood socioeconomic status (SES) and formality status on self-rated health (SRH) of adult men and women residing in formal and informal urban neighbourhoods in Aleppo. Methods The study used data from 2038 survey respondents to the Aleppo Household Survey, 2004 (age 18–65 years, 54.8% women, response rate 86%). Respondents were nested in 45 neighbourhoods. Five individual-level SES measures, namely education, employment, car ownership, item ownership and household density, were aggregated to the level of neighbourhood. Multilevel regression models were used to investigate associations. Results We did not find evidence of important SRH variation between neighbourhoods. Neighbourhood average of household item ownership was associated with a greater likelihood of reporting excellent SRH in women; odds ratio (OR) for an increase of one item on average was 2.3 (95% CI 1.3-4.4 (versus poor SRH)) and 1.7 (95% CI 1.1-2.5 (versus normal SRH)), adjusted for individual characteristics and neighbourhood formality. After controlling for individual and neighbourhood SES measures, women living in informal neighbourhoods were less likely to report poor SRH than women living in formal neighbourhoods (OR= 0.4; 95% CI (0.2- 0.8) (versus poor SRH) and OR=0.5; 95%; CI (0.3-0.9) (versus normal SRH). Conclusions Findings support evidence from high income countries that certain characteristic of neighbourhoods affect men and women in different ways. Further research from similar urban settings in developing countries is needed to understand the mechanisms by which informal neighbourhoods influence women’s health.

Potential for Cell-Transplant Therapy with Human Neuronal Precursors to Treat Neuropathic Pain in Models of PNS and CNS Injury: Comparison of hNT2.17 and hNT2.19 Cell Lines

Effective treatment of sensory neuropathies in peripheral neuropathies and spinal cord injury (SCI) is one of the most difficult problems in modern clinical practice. Cell therapy to release antinociceptive agents near the injured spinal cord is a logical next step in the development of treatment modalities. But few clinical trials, especially for chronic pain, have tested the potential of transplant of cells to treat chronic pain. Cell lines derived from the human neuronal NT2 cell line parentage, the hNT2.17 and hNT2.19 lines, which synthesize and release the neurotransmitters gamma-aminobutyric acid (GABA) and serotonin (5HT), respectively, have been used to evaluate the potential of cell-based release of antinociceptive agents near the lumbar dorsal (horn) spinal sensory cell centers to relieve neuropathic pain after PNS (partial nerve and diabetes-related injury) and CNS (spinal cord injury) damage in rat models. Both cell lines transplants potently and permanently reverse behavioral hypersensitivity without inducing tumors or other complications after grafting. Functioning as cellular minipumps for antinociception, human neuronal precursors, like these NT2-derived cell lines, would likely provide a useful adjuvant or replacement for current pharmacological treatments for neuropathic pain.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Syndemic health disparities and resilience processes related to HIV transmission risk among African American/Black men in south Florida

Rates of HIV infection continue to climb among minority populations and men who have sex with men (MSM), with African American/Black MSM being especially impacted. Numerous studies have found HIV transmission risk to be associated with many health and social disparities resulting from larger environmental and structural forces. Using anthropological and social environment-based theories of resilience that focus on individual agency and larger social and environmental structures, this dissertation employed a mixed methods design to investigate resilience processes among African American/Black MSM.^ Quantitative analyses compared African American/Black (N=108) and Caucasian/White (N=250) MSM who participated in a previously conducted randomized controlled trial (RCT) of sexual and substance use risk reduction interventions. At RCT study entry, using past 90 day recall periods, there were no differences in unprotected sex frequency, however African American/Black MSM reported higher frequencies of days high (P<0.000), and drugs and sex used in combination (P<0.000), and substance dependence (P<0.000) and lower levels of social support (P<0.024) compared to Caucasian/White MSM. At 12- month follow-up, multi-level statistical models found that African American/Black MSM reduced their frequencies of days high and unprotected sex at greater rates than Caucasian/White MSM (P<0.001).^ Qualitative data collected among a sub-sample of African American/Black MSM from the RCT (N=21) described the men's experiences of living with multiple health and social disparities and the importance of RCT study assessments in facilitating reductions in risk behaviors. A cross-case analysis showed different resilience processes undertaken by men who experienced low socioeconomic status, little family support, and homophobia (N=16) compared to those who did not (N=5).^ The dissertation concludes that resilience processes to HIV transmission risk and related health and social disparities among African American/Black MSM varies and are dependent on specific social environmental factors, including social relationships, structural homophobia, and access to social, economic, and cultural capital. Men define for themselves what it means to be resilient within their social environment. These conclusions suggest that both individual and structural-level resilience-based HIV prevention interventions are needed.^

Lifestyle Behaviors and Self-Rated Health: The Living for Health Program

Background. Lack of adherence to dietary and physical activity guidelines has been linked to an increase in chronic diseases in the United States (US). The aim of this study was to assess the association of lifestyle behaviors with self-rated health (SRH). Methods. This cross-sectional study used self-reported data from Living for Health Program ( 1,701) which was conducted from 2008 to 2012 in 190 health fair events in South Florida, US. Results. Significantly higher percent of females as compared to males were classified as obese (35.4% versus 27.0%), reported poor/fair SRH (23.4% versus 15.0%), and were less physically active (33.9% versus 25.4%). Adjusted logistic regression models indicated that both females and males were more likely to report poor/fair SRH if they consumed 2 servings of fruits and vegetables per day (, 95% CI 1.30–3.54; , 95% CI 1.12–7.35, resp.) and consumed mostly high fat foods (, 95% CI 1.03–2.43; , 95% CI 1.67–2.43, resp.). The association of SRH with less physical activity was only significant in females (, 95% CI 1.17–2.35). Conclusion. Gender differences in health behaviors should be considered in designing and monitoring lifestyle interventions to prevent cardiovascular diseases.

Diabetes Self Management: Are Cuban Americans Receiving Quality Health Care?

Objectives: We investigated the relationship among factors predicting inadequate glucose control among 182 Cuban-American adults (Females=110, Males=72) with type 2 diabetes mellitus (CAA). Study Design: Cross-sectional study of CAA from a randomized mailing list in two counties of South Florida Methods: Fasted blood parameters and anthropometric measures were collected during the study. BMI was calculated (kg/ m2). Characteristics and diabetes care of CAA were self-reported Participants were screened by trained interviewers for heritage and diabetes status (inclusion criteria: self-reported having type 2 diabetes; age  35 years, male and female; not pregnant or lactating; no thyroid disorders; no major psychiatric disorders). Participants signed informed consent form. Statistical analyses used SPSS and included descriptive statistic, multiple logistic and ordinal logistic regression models, where all CI 95%. Results: Eighty-eight percent of CAA had BMI of ≥ 25 kg/ m2. Only 54% reported having a diet prescribed/told to schedule meals. We found CAA told to schedule meals were 3.62 more likely to plan meals (1.81, 7.26), p<0.001) and given a prescribed diet, controlling for age, corresponded with following a meal plan OR 4.43 (2.52, 7.79, p<0.001). The overall relationship for HbA1c < 8.5 to following a meal plan was OR 9.34 (2.84, 30.7. p<0.001). Conclusions: The advantage of having a medical professional prescribe a diet seems to be an important environmental support factor in this sample’s diabetes care, since obesity rates are well above the national average. Nearly half CAA are not given dietary guidance, yet our results indicate CAA may improve glycemic control by receiving dietary instructions.

Developing brownfields ranking models using decision analytic methods

The redevelopment of Brownfields has taken off in the 1990s, supported by federal and state incentives, and largely accomplished by local initiatives. Brownfields redevelopment has several associated benefits. These include the revitalization of inner-city neighborhoods, creation of jobs, stimulation of tax revenues, greater protection of public health and natural resources, the renewal and reuse existing civil infrastructure and Greenfields protection. While these benefits are numerous, the obstacles to Brownfields redevelopment are also very much alive. Redevelopment issues typically embrace a host of financial and legal liability concerns, technical and economic constraints, competing objectives, and uncertainties arising from inadequate site information. Because the resources for Brownfields redevelopment are usually limited, local programs will require creativity in addressing these existing obstacles in a manner that extends their limited resources for returning Brownfields to productive uses. Such programs may benefit from a structured and defensible decision framework to prioritize sites for redevelopment: one that incorporates the desired objectives, corresponding variables and uncertainties associated with Brownfields redevelopment. This thesis demonstrates the use of a decision analytic tool, Bayesian Influence Diagrams, and related decision analytic tools in developing quantitative decision models to evaluate and rank Brownfields sites on the basis of their redevelopment potential.

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) interven- tions 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].

A State and Territorial Survey Regarding Utilization of Environmental Health Shelter Assessments during Disasters, and a Secondary Analysis of Available Shelter Assessment Data

Disasters are complex events characterized by damage to key infrastructure and population displacements into disaster shelters. Assessing the living environment in shelters during disasters is a crucial health security concern. Until now, jurisdictional knowledge and preparedness on those assessment methods, or deficiencies found in shelters is limited. A cross-sectional survey (STUSA survey) ascertained knowledge and preparedness for those assessments in all 50 states, DC, and 5 US territories. Descriptive analysis of overall knowledge and preparedness was performed. Fisher’s exact statistics analyzed differences between two groups: jurisdiction type and population size. Two logistic regression models analyzed earthquakes and hurricane risks as predictors of knowledge and preparedness. A convenience sample of state shelter assessments records (n=116) was analyzed to describe environmental health deficiencies found during selected events. Overall, 55 (98%) of jurisdictions responded (states and territories) and appeared to be knowledgeable of these assessments (states 92%, territories 100%, p = 1.000), and engaged in disaster planning with shelter partners (states 96%, territories 83%, p = 0.564). Few had shelter assessment procedures (states 53%, territories 50%, p = 1.000); or training in disaster shelter assessments (states 41%, 60% territories, p = 0.638). Knowledge or preparedness was not predicted by disaster risks, population size, and jurisdiction type in neither model. Knowledge: hurricane (Adjusted OR 0.69, 95% C.I. 0.06-7.88); earthquake (OR 0.82, 95% C.I. 0.17-4.06); and both risks (OR 1.44, 95% C.I. 0.24-8.63); preparedness model: hurricane (OR 1.91, 95% C.I. 0.06-20.69); earthquake (OR 0.47, 95% C.I. 0.7-3.17); and both risks (OR 0.50, 95% C.I. 0.06-3.94). Environmental health deficiencies documented in shelter assessments occurred mostly in: sanitation (30%); facility (17%); food (15%); and sleeping areas (12%); and during ice storms and tornadoes. More research is needed in the area of environmental health assessments of disaster shelters, particularly, in those areas that may provide better insight into the living environment of all shelter occupants and potential effects in disaster morbidity and mortality. Also, to evaluate the effectiveness and usefulness of these assessments methods and the data available on environmental health deficiencies in risk management to protect those at greater risk in shelter facilities during disasters.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Structural Health Monitoring Inside Concrete and Grout Using the Wireless Identification and Sensing Platform (WISP)

This research investigates the implementation of battery-less RFID sensing platforms inside lossy media, such as, concrete and grout. Both concrete and novel grouts can be used for nuclear plant decommissioning as part of the U.S. Department of Energy’s (DOE’s) cleanup projects. Our research examines the following: (1) material characterization, (2) analytical modeling of transmission and propagation losses inside lossy media, (3) maximum operational range of RFID wireless sensors embedded inside concrete and grout, and (4) best positioning of antennas for achieving longer communication range between RFID antennas and wireless sensors. Our research uses the battery-less Wireless Identification and Sensing Platform (WISP) which can be used to monitor temperature, and humidity inside complex materials. By using a commercial Agilent open-ended coaxial probe (HP8570B), the measurements of the dielectric permittivity of concrete and grout are performed. Subsequently, the measured complex permittivity is used to formulate analytical Debye models. Also, the transmission and propagation losses of a uniform plane wave inside grout are calculated. Our results show that wireless sensors will perform better in concrete than grout. In addition, the maximum axial and radial ranges for WISP are experimentally determined. Our work illustrates the feasibility of battery-less wireless sensors that are embedded inside concrete and grout. Also, our work provides information that can be used to optimize the power management, sampling rate, and antenna design of such sensors.