Effects of Religiosity and Self-Control on At-Risk Adolescent Substance Use and Delinquency

The adolescent period is one of growth, increased autonomy, and increased risk-taking. Common examples of these risky behaviors include substance use and engagement in delinquent activity. Adolescent substance use and delinquent behavior can lead to a range of negative outcomes, some of which carry into adulthood. These negative consequences are especially evident among at-risk adolescents such as those who have dropped out of school or who come into contact with the juvenile justice system, as these youth often demonstrate higher rates of substance use and delinquent behavior. Understanding the nature and development of these problem behaviors is essential to developing appropriate prevention and intervention tools. In the current study, adolescents’ self-control abilities and religiosity were evaluated as predictors of substance use and delinquency. For the purposes of this study, religiosity was defined as a general valuing of religious or spiritual identity (i.e., religiosity is not restricted to Christianity). Adolescent personality domains were also evaluated in relation to substance use and delinquency, as many theories indicate the importance of personality in the development of such problem behaviors. The sample included a local group of at-risk adolescents who have faced academic, educational, vocational, and/or behavioral complications. Results contribute to a greater understanding of the development of problem behaviors during adolescence, especially among at-risk youths

The Impact of ‘Non-Clinical’ Patient Factors (NCpF) on Clinical Decision-making: Uncovering the Impact on Mental Health

This thesis aimed to understand the influence of non-clinical patient factors on mental health-related diagnostic, treatment, and referral decisions. Non-clinical patient factors are characteristics of the patient that are not known to be relevant for the clinical diagnosis or prognosis. Examples of non-clinical patient factors in mental health care include gender, age, and socioeconomic status. Focus groups were conducted to understand the perceptions of patient’s mental health care experiences and identify any NCpF that varied from past literature. Then, using the Secure Anonymised Information Linkage Databank, administrative data for participants with a gold standard indicator of mental health were linked with their healthcare records to determine associations between NCpF and being diagnosed, treated, or referred for mental health-related conditions. Finally, an experimental clinical vignette study was conducted. General practitioners were invited to answer clinical decisions based on the clinical vignettes which depicted patients with bulimia, anxiety, and bipolar disorder. All participants saw one of each disorder, however they were randomly allocated to either male, female or a control condition for bulimia, young, old or control condition for age, or high- or low- socioeconomic status or no reference for bipolar disorder. Utilising a combined methodological approach, gender, age and socioeconomic status were found to impact the clinical decision-making process. The effect of this influence varied depending on the clinical decision and disorder type. This thesis demonstrated the feasibility of using administrative and health care records to study mental health-related clinical decision-making

Unified Methods for Feature Selection in Large-Scale Genomic Studies with Censored Survival Outcomes

One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease\u27s process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards (PH), which is unlikely to hold for each feature. When applied to genomic features exhibiting some form of non-proportional hazards (NPH), these methods could lead to an under- or over-estimation of the effects. We propose a broad array of marginal screening techniques that aid in feature ranking and selection by accommodating various forms of NPH. First, we develop an approach based on Kullback-Leibler information divergence and the Yang-Prentice model that includes methods for the PH and proportional odds (PO) models as special cases. Next, we propose R2 indices for the PH and PO models that can be interpreted in terms of explained variation. Lastly, we propose a generalized pseudo-R2 measure that includes PH, PO, crossing hazards and crossing odds models as special cases and can be interpreted as the percentage of separability between subjects experiencing the event and not experiencing the event according to feature expression. We evaluate the performance of our measures using extensive simulation studies and publicly available data sets in cancer genomics. We demonstrate that the proposed methods successfully address the issue of NPH in genomic feature selection and outperform existing methods. The proposed information divergence, R2 and pseudo-R2 measures were implemented in R (www.R-project.org) and code is available upon request

Supervised Dimension Reduction for Large-scale Omics Data with Censored Survival Outcomes Under Possible Non-proportional Hazards

The past two decades have witnessed significant advances in high-throughput ``omics technologies such as genomics, proteomics, metabolomics, transcriptomics and radiomics. These technologies have enabled simultaneous measurement of the expression levels of tens of thousands of features from individual patient samples and have generated enormous amounts of data that require analysis and interpretation. One specific area of interest has been in studying the relationship between these features and patient outcomes, such as overall and recurrence-free survival, with the goal of developing a predictive ``omics profile. Large-scale studies often suffer from the presence of a large fraction of censored observations and potential time-varying effects of features, and methods for handling them have been lacking. In this paper, we propose supervised methods for feature selection and survival prediction that simultaneously deal with both issues. Our approach utilizes continuum power regression (CPR) - a framework that includes a variety of regression methods - in conjunction with the parametric or semi-parametric accelerated failure time (AFT) model. Both CPR and AFT fall within the linear models framework and, unlike black-box models, the proposed prognostic index has a simple yet useful interpretation. We demonstrate the utility of our methods using simulated and publicly available cancer genomics data

Mothers with a Cause: The Political Las Madres de la Plaza de Mayo

Research paper about Las Madres de la Plaza de Mayo. Even today, women engaging in the political arena face intense criticism. Las Madres were widely discredited by the Argentine media and government. The archetype of the hysterical woman was employed to discredit their argument and organizing efforts. However, Las Madres by using their status as mothers to their advantage, the women gained international recognition and even won the United Nations Prize for Peace Education. Whether they adopted the feminist label or not, Las Madres worked tirelessly to work for the betterment of their society and accepted some basic feminist principles

Renewables & Refugees: A Solution for Jordan

As the Hashemite Kingdom of Jordan continues to host the third largest Syrian refugee population in the world, the state’s infrastructure and its people are taking a toll. Before the war in Syria began, Jordan was already suffering from a weak economy, resource scarcity, and an enormous population boom. Since accepting nearly 2.5 million refugees, these issues have compounded year after year—nearly reaching a breaking point. I propose an unconventional solution to some aspects of the refugee crisis: renewable energy. Renewables are cheaper than fossil fuels, consume less water in electricity generation, emit fewer greenhouse gases, and promote job creation and diversification. Better yet, Jordan has enormous potential for renewable energy, especially in solar photovoltaics (PV) and wind. In this study, I evaluate Jordan’s readiness to implement renewable energy, analyze a case study of the Za’atari refugee camp (which recently transitioned to running entirely on solar energy), and make basic projections on potential job creation and water conservation by switching from coal and natural gas to PV and wind. I find that Jordan has successfully paved the way for jumpstarting its renewable sector, Za’atari has benefitted from solar energy, and the outlook for job creation is good, and water conservation even better. There are also some smaller, indirect positive impacts that renewable energy can have on combating the Syrian refugee crisis in Jordan

Expectation Versus Reality: Perceived Differences in Cognitive Ability Between Men and Women

In Western society, there is a common belief that there are clear differences between male and female brains. In our project, we hope to gain insight into the beliefs of undergraduate students regarding this very idea. We are surveying Binghamton University students about their perceptions regarding the differences in cognitive ability between cis-gender men and women. Our survey asks students if certain skills are gendered, which gender these skills are more closely associated with, and where students learned these stereotypes. These results will be compared to the current state of knowledge about cognitive differences between the sexes. We anticipate that students will overestimate the extent of brain differences between the sexes, as our culture has conditioned us to believe. Our goal is to enlighten others about the pervasiveness of neurosexism.https://orb.binghamton.edu/research_days_posters_2022/1097/thumbnail.jp

A Candidate Gene Study of Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease (LOAD) is a multifactorial disease with the potential involvement of multiple genes. Complex diseases such as LOAD have a large affect on public health due to the significant financial burden of health care for these individuals. Genetics plays a significant role in the etiology of the disease, therefore it is of public health importance that the genetics of LOAD be investigated. There is a known association between APOE gene variants and LOAD. No additional genes have been consistently demonstrated to be associated with risk of LOAD. Multiple recent genome-wide association studies (GWAS) have found variants showing significant association with LOAD. Twelve SNPs were chosen from four GWAS for a replication study to determine if the associations seen between SNPs and AD risk in the respective studies were present in our population. Ten additional positional candidate SNPs were chosen on chromosome 10 because of observed linkage peaks for AD and predicted imprinted genes in this region. We genotyped these 22 SNPs as well the E2/E3/E4 APOE polymorphism in up to 993 Caucasian Americans with LOAD and up to 976 age-matched healthy Caucasian Americans. Our data showed no statistically significant associations between the 22 SNPs examined and the risk of AD. Stratification by APOE*4 carrier status also failed to reveal statistically significant associations. Additional analyses were performed to examine the potential associations between the 22 SNPs and age-at-onset, disease duration, and baseline MMSE score. The analysis revealed significant associations between two SNPs, rs3746319 (p=0.002) and rs16934131 (p=0.045), and age-at-onset. One SNP, rs16934131 (p=0.0002), was found to be significantly associated with disease duration. Three SNPs, rs16934131 (p=0.002), rs12781609 (p=0.012), and rs5984894 (p=0.009), were found to be associated with baseline MMSE score in controls. Of note, rs16934131, demonstrated statistically significant association with age at onset, disease duration, and MMSE score. Further study may be necessary to definitively rule out associations between these variants and LOAD