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This study examined maternal depression status from month 1 to 36 after birth using data from the NICHD Study of Early Child Care and Youth Development. Maternal depression was assessed with the Center of Epidemiological Studies Depression Scale. The prevalence of maternal depression was highest at 1 month, decreased at 6 months, and then kept fairly stable to 36 months. The prevalence was higher in blacks than other races, in 18-24 than 25-46 years old, and in single mothers than non-single mothers. Mothers with better physical health, social support, or employed had a lower prevalence than their counterparts. Mothers in poverty, receiving public assistance, or who had more parental stress had a higher prevalence. Social support and parental stress had a statistically significant relationship with maternal depression even after adjusting for other variables. In conclusion, this longitudinal study found that several maternal, child, and family factors were associated with maternal depression.

Suicide is a significant public health concern worldwide and the 10th leading cause of death in the United States. Risk factors for suicide include depression, anxiety, hopelessness, and previous suicide attempts, among others. Some vulnerable groups may have unique risk factors that exacerbate suicide risk; for instance, college students experience academic stress, and individuals with chronic illnesses, such as fibromyalgia and cancer, face persistent health complications. However, protective characteristics, such as self-compassion, may reduce suicide risk. Comprised of self-kindness, mindfulness, and common humanity, self-compassion is beneficially associated with mental and physical health, and to the task of suicide prevention. As such, we examined the relation between self-compassion and suicidal behavior, and the potential parallel mediating effects of depression, anxiety, and hopelessness across four samples (community, N = 632; collegiate, N = 338; fibromyalgia, N = 508; cancer, N = 241). Across all four samples, the combined effect of depression, anxiety, and hopelessness mediated the relation between self-compassion and suicidal behavior. Our findings provide support for the notion that self-compassion has a beneficial association with suicidal behavior directly, as well as indirectly via its influence on the suicide risk factors of depression, anxiety, and hopelessness. Increasing self-compassion through interventions such as Compassion-Focused Therapy and Mindful Self-Compassion may not only increase self-compassion, but may also facilitate adaptive coping, particularly in times of distress, that ameliorates symptoms of psychopathology and suicide risk. Future prospective, longitudinal studies, and randomized control trials, are needed to examine causal effects of self-compassion on emotional dysfunction and suicidal behavior.

The purpose of the current study was to develop and test a methodology for assessing the effect of outdoor activity context on level of physical activity in preschool children. The Observational System for Recording Physical Activity in Children (OSRAC) was used to define the test conditions and various levels of physical activity within a multi-element experimental design. Consequences were not programmed. Pedometers were used as a convergent measure of physical activity. In general, all participants were fairly sedentary during the analysis. Fixed playground equipment produced the most moderate-to-vigorous physical activity, a finding that does not correspond to the descriptive assessment literature. Implications of the results and suggestions for future research are offered.

he software engineering community has advanced the field in the past few decades towards making the software development life cycle more efficient, robust, and streamlined. Advances such as better integrated development environments and agile workflows have made the process more efficient as well as more flexible. Despite these many achievements software engineers still spend a great deal of time writing, reading and reviewing code. These tasks require a lot of attention from the engineer with many different variables affecting the performance of the tasks. In recent years many researchers have come to investigate how emotion and the way we think about code affect our ability to write and understand another’s code. In this work we look at how developers’ emotions affect their ability to solve software engineering tasks such as code writing and review. We also investigate how and to what extent emotions differ with the software engineering experience of the subject. The methodologies we employed utilize the Emotiv Epoc+ to take readings of subjects’ brain patterns while they perform code reviews as well as write basic code. We then examine how the electrical signals and patterns in the participants differ with experience in the field, as well as their efficiency and correctness in solving the software engineering tasks. We found in our study that senior students had much smaller distribution of emotions than novices with a few different emotion groups emerging. The novices, while able to be grouped, had a much wider dispersion of the emotion aspects recorded.

In this dissertation, two exemplar-based models of categorization, the General Context Model (GCM) and the Exemplar Based Random Walk model (EBRW), were used to describe between-group categorization differences in artificial and natural language categories. Prior research has shown that political Conservatives in avoidance mode are more exclusive categorizers of natural language category members than Conservatives in approach mode, but this effect was absent for Liberals (Rock & Janoff-Bulman, 2010). In Experiment 1, experimenter-generated stimuli were used to show that the EBRW could account for between-group differences in categorization decisions. In Experiment 2, the data collected by Rock and Janoff-Bulman were used to develop techniques allowing the GCM to account for between-group differences in natural language categorization decisions. Experiment 3 extends these methods to allow the EBRW to account for between-group differences in natural language categorization decisions. Across these experiments, the models identify between-group differences in determining similarity, bias to give an "in-the-category" decision, and the amount of information required to make a categorization decision. Techniques for modeling natural language categorization decisions are discussed.

The purpose of this study, a formative program evaluation, was to provide an overview of treatment integrity rates, attitudes, and assessment methods within a specialized school for children and adolescents with Autism Spectrum Disorder. The study utilized a partnership model whereby the evaluators worked collaboratively with primary stakeholders (school administrators) to determine areas of focus for the evaluation. The program evaluation was conducted between August 2009 and August 2010, spanning one school year. The evaluation participants were the school's teachers. The evaluation was based on an exploratory case study design and included both quantitative and qualitative data. Quantitative data consisted of direct observations of treatment adherence to behavior plans in classrooms, teacher knowledge of treatment content assessed in quizzes, and observations of teacher engagement with students at recess. Qualitative data consisted of teacher surveys and focus groups. The evaluation yielded an in-depth assessment of treatment integrity within the school; an intervention to define and enhance teacher engagement during recess was also developed and implemented.

Derived from the ancient mind-body practice and congruent with western scientific studies, the 8-Week Program to Support Undergraduate Academic Aptitude draws specific modalities from the 5,000-year-old Yoga tradition for helping lower undergraduate anxiety, depression, and stress. The program emphasizes use of physical postures, breathing exercises, basic mediation, and philosophy. Selectively chosen, the clinically researched techniques create physiological shifts for offsetting anxiety and depression in undergraduates, two factors known for adversely affecting students’ health and academic readiness. The main goal of the program is to educate a student to use Yogic tools intelligently and effectively for emotional, mental, and physical health to support quality of life and flourishing academically. A student’s health, wellness, and happiness are key contributing factors to staying engaged with an institution and student attainment.

Alcohol-impaired driving is a major cause of motor vehicle accident and death in the United States. People who are arrested for DUI (Driving under the Influence) are at high risk to reoffend; approximately one in three of these individuals will commit another DUI offense in the three years following their first conviction (Nochajski & Stasiewicz, 2006). This high risk for recidivism in these individuals suggests that cognitive characteristics may contribute to a pattern of pathological decision making leading to impaired driving. Indeed, individuals with a history of DUI report higher rates of impulsiveness and behavioral dysregulation compared to their nonoffending peers. Relatively little research, however, has used laboratory methods to identify the specific behavioral characteristics, such as poor inhibitory control or heightened sensitivity to immediate reward, which may differentiate DUI offenders from nonoffenders. Further, little is known about how individuals with a history of DUI respond following an acute dose of alcohol. Study 1 examined impulsivity in 20 adults with a recent DUI conviction and 20 adults with no history of DUI using self-report and behavioral measures of impulsivity. This study also used a novel decision-making paradigm to examine how different levels of risk and reward influenced the decision to drive after drinking in both groups. Results of this study found that DUI offenders did not differ from controls in their performance on behavioral measures of impulsivity. They did, however, report higher levels of impulsivity and demonstrated a greater willingness to tolerate higher levels of risk for more modest rewards. Study 2 examined the acute effects of alcohol and expectancy manipulation on driving performance and decision making in the same group of participants. Neither alcohol nor expectancy manipulation exerted a systematic effect on decision making in either group. Alcohol impaired driving performance equally in both groups, but the DUI group perceived themselves as less impaired by alcohol. Expectancy manipulation eliminated this group difference in perceived driving ability. Taken together, these findings identify processes that risk of impaired driving in DUI offenders. They may perceive themselves as less impaired by alcohol, leading to risky decision making when drinking. Expectancy manipulation may be a viable method of reducing risky decision making in DUI offenders.

The purpose of this research was to develop a questionnaire to be used to identify barriers and facilitators to women faculty in science, technology, engineering, and mathematics (STEM) academics. The phenomenon known as the leaky pipeline, a theoretical model describing why women are underrepresented in STEM disciplines, was examined. Women have long been underrepresented in STEM professions despite an increase in the number of women earning STEM degrees, suggesting women are faced with barriers that prevent them from achieving equal representation with men. The literature has identified several potential barriers, both historical and new, such as biological inequalities, family responsibilities, commitment differences, competitive differences, gender stereotypes and implicit biases, work environments, and job preference. Major facilitators included mentors and specific policy/program implementation. Barriers and facilitators to faculty members at Western Kentucky University will be identified objectively through the use of this questionnaire in a future study.