Publications on Chronic Disease in Coal Dependent Communities in Central Appalachia

CONTEXT: Agency and nonprofit reports have traditionally been the source of health information in Appalachia. Recently, publications have appeared in the literature associating coal mining, specifically mountain top mining, with numerous chronic health conditions spurring debate among environmental and industry interest groups. Publication quantity and quality were objectively assessed. This article reports on a literature review and analysis of publications on chronic disease in coal dependent communities in Appalachia. OBJECTIVE: To conduct a review and analysis of original, peer reviewed research publications on chronic health conditions in communities dependent on coal mining with a focus on central Appalachia and report on publication and research quantity and quality. DATA SOURCES: Thorough searches were conducted using PubMed, EBSCO, and CiNAHL computerized databases to identify original, peer-reviewed research articles addressing ‘Appalachia’, ‘health’ and ‘coal’. STUDY SELECTION: The computerized database search identified original research publications relevant to chronic health conditions (heart disease, lung disease, kidney disease, cancers, diabetes, obesity, etc.) and coal mining in central Appalachia. DATA EXTRACTION: Quantitative measures of the literature review provided information on author collaborations, year of publication, frequency of publication by contributing authors, etc. Journal impact factors were noted and other objective qualitative criteria were considered. DATA SYNTHESIS: Over 60 publications relevant to mining with 38 publications specific to Appalachia and health were identified. The publications were reviewed relative to relevance and article quality i.e., current, original research, application to central Appalachia and discussions of chronic human health and coal mining. Over the past five years most of the publications relevant to chronic disease and coal mining in central Appalachia resulted from a research group with a single common author. CONCLUSIONS: Science based evidence is needed and data must be provided by independent researchers from various disciplines of study to share different perspectives on how to alleviate the longstanding health disparities in central Appalachia. Studies will require the application of sound methodologies to validate the findings and support future interventions

Job Satisfaction Indicators and Their Correlates

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67361/2/10.1177_000276427501800303.pd

Managers’ Family-Supportive Supervisory Behaviors: A Multilevel Perspective

Using a combination of trait and situational variables we develop a model to explore the antecedents of managers’ family-supportive behaviors. Our model hypotheses were tested using data gathered from a sample of 312 subordinates matched to 92 managers. Hierarchical linear modeling (HLM) of the nested data yielded results that show both an individual manager’s trait (i.e., empathy) and situational variables (i.e., subordinate’s family-to-work conflict and leader–subordinate exchange quality) significantly predicted managers’ supportive behaviors. Additional HLM analyses showed that the manager’s gender (trait) and group work-to-family conflict (situation) moderated the relationship between manager’s empathy and family-supportive behaviors. Our results suggest that managers’ family-supportive behaviors are related to individual characteristics of the manager and to subordinate workgroup contexts, but not to organizational culture

355— Topographical Individualized Neuromarkers in the Analysis of the Brain Functioning of Social-Emotional Development

Topographical Individualized Neuromarkers (TIN) are spatially arranged patterns of brain function used to develop novel brain markers of social-emotional functioning and development. The current study focuses on developing markers of risk for psychological problems in children. We are expanding on previous research that indicates the brains of shy children differ from the brains of non-shy children, where shy children present with a topographical pattern of brain function that may be considered an internally hypervigilant neuromarker (Taber-Thomas et al., 2016). Using the online software, Neurosynth, we will extend our research into neuromarkers for other disorders using publicly available data. This program allows for the examination of internally hypervigilant neuromarkers in several regions of the brain. The regions we will be specifically examining are the insula, cingulate gyrus, hippocampus, and amygdala. This model will be explored further by calculating topographical maps from fMRI data and examining how differences in the maps are related to social-emotional functioning and development

351— Social Attention Bias in the Real World - Pilot Study

Attention bias is defined as the elevated processing of certain stimuli over others. Past research has discovered that attention bias is related to anxiety through behavioral experiments. Studies found that in a lab setting those who are more anxious are more vigilant towards a threat. Previous research is however limited in the study of examining how these behavioral experiments relate to a real-world context since most of the experiments that have been done occurred in a lab setting. To address this phenomenon, two Empatica E4 Wristbands were utilized in order to measure a participant’s anxiety through skin conductance, electrodermal activity, and heart rate. The current study is pilot work done to test the equipment’s accuracy and reliability as well as create a protocol for data collection. To assess the equipment, SED lab members have been following safe covid practices in order to minimize the risk of contracting or spreading the virus. Based on data collected by the Empatica E4 wristbands, we hypothesize that when put in a real-world situation, a more anxious person will focus their attention on threatening stimuli rather than non-threatening stimuli

039— Daily Attention Bias

Previous research has shown a correlation between anxiety and attentional bias to threat. For anxious individuals, attentional bias to threat has been shown to activate areas in the brain such as the amygdala. The amygdala is (i) associated with fear and anxiety, (ii) involved in the link between anxiety and hyper-vigilance for threat, and (iii) exerts excitatory influence on the release of cortisol, the stress hormone, which follows a daily (diurnal) pattern. Previous research has yet to study the diurnal patterns of attention bias to threat and its association with levels of anxiety. To address this gap, we examined whether attention biases to threat follows a similar pattern of daily fluctuations, and if the variation in that pattern relates to levels of anxiety. To assess this relationship, SUNY Geneseo students completed the Dot-Probe paradigm, which is a commonly used method to measure attention to threat, at five time periods in one day. The hypothesis is that attentional biases will follow a similar diurnal pattern as seen with cortisol levels, and this pattern will be related to daily fluctuations in anxiety. The study’s findings showed that participants with higher levels of anxiety had a greater threat bias

The first total synthesis of (+)-mucosin

The first total synthesis of (+)-mucosin has been completed allowing assignment of the absolute stereochemistry of the natural product. A zirconium induced co-cyclisation was utilised to install the correct stereochemistry of the four contiguous stereocentres around the unusual bicyclo[4.3.0]nonene core

Utilizing Weightlifting for Cycling Performance

Abstract available in the 9th Annual Coaches and Sport Science College

Optimal inference with suboptimal models:Addiction and active Bayesian inference

When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent's beliefs - based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment - as opposed to the agent's beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less 'optimally' than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject's generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described 'limited offer' task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work