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Employee Salary Report [University of Missouri - St. Louis] 2024
Get PDFhttps://irl.umsl.edu/salary/1025/thumbnail.jp
Unlocking the Age-Barrier: Mental Health Professional Capacities in Addressing the Needs of Aging Populations
No full textThere is growing concern about an inadequacy in the level of preparedness of mental health professionals to address the unique needs of individuals aged 65 years and older. This raises doubts about whether clinicians possess the necessary knowledge and skills to effectively address mental health challenges within this population, which is particularly significant given the continuous growth in numbers of older adults within the United States. The explicit and implicit ageism perpetuated within our society dissuades mental health professionals from working with older adults, and may be compounded by broad dissemination of misinformation about aging. Data from three separate UMSL survey studies were pooled to examine knowledge of aging among licensed psychologists, social workers, and counselors (N= 665). Correlations examined the relationship between the Facts on Aging Quiz (Palmore, 1998; Breytspraak & Badura, 2015) and years since licensure, as well as various aging-related professional training experiences. Results reveal that social workers had the lowest scores on aging knowledge, significantly differing from those of psychologists and counselors. There were no significant differences between counselors and psychologists. Findings emphasize the need for interventions to improve the competence of mental health professionals, for future work with older adults across various behavioral health specialties
Who to Host: Competition Interactions between Parasitoid Wasp Species
Get PDFThe availability of resources plays an important role in the survival and fitness of all organisms, one\u27s ability to find and utilize resources can impact interactions between them and their environments. The interaction between organisms for resources can lead to interspecific competition, amongst two different species, or intraspecific competition, amongst the same species. In an experiment to test for competitive interactions between the parasitoid wasp species of N. vitripennis and M. digitata that utilize a fresh fly papua as their host to aid in the reproduction of their offspring. Over a period of time testing for conditions of interspecific and intraspecific competition by measuring their mean offspring produced we set up five vials to isolate each respective competition interaction. In vials one and two used as a control for the experiment, one wasp from one wasp species was placed inside one vial with its own host. For vials two and three, two wasps from one wasp species were placed inside one vial with a host to test for intraspecific competition interactions. To test for interspecific competition interactions one wasp from each species\u27 was placed inside vial five with a host. From the analysis of our results through the excel software we determined that the two species while in competition have a predicted outcome of unstable coexistence. Further, both wasp species mean offspring produced were significantly impacted by interspecific competition. Overall the impact of competition interactions among both species impacts their overall fitness which sets up a model to further test how competition influences an organism\u27s availability and success with utilizing resources in their environments
User Polarization from AI Social Media Algorithms
Get PDFThis research project delves into the contemporary phenomenon of political polarization exacerbated by artificial intelligence (AI) algorithms in online content consumption using scholarly articles and survey data. The research investigates how AI-driven recommendation systems influence the selection and exposure to politically charged content across various digital platforms. The findings of this study are intended for a deeper understanding of the societal implications of AI algorithms and provide insights into potential strategies for mitigating political polarization in online environments
Simulating Mass Extinctions in an Agent-Based Evolutionary Model
Get PDFIn an agent-based model of evolutionary dynamics which has been shown to undergo a nonequilibrium phase transition from extinction to survival, we apply coalescent theory to investigate the responses of population lineages to simulated mass extinctions. In the model, organisms reproduce via assortative mating on a neutral fitness landscape; parameters including the mutability (distance offspring may be distributed away from their parents in the fitness landscape) and the death parameter (percentage of organisms randomly removed during each generation) control the phase transition. Lineage structure can be characterized using the time to most recent common ancestor (TMRCA). We examine how this measure is affected by mass extinction applied in the critical regime of the phase transition, as opposed to in the survival regime. These results have implications for predicting population recovery and designing strategies for evolutionary rescue
A Primer of Evolution—An Introduction to Evolutionary Thought through Theory, Evidence, and Practice
No full textA Primer of Evolutionis an open educational resource designed for upper-level college students. It provides a succinct introduction to evolutionary thought revolving around theory, evidence, and practice: It introduces some of the theoretical cornerstones and core concepts of modern evolutionary biology. The goal is for students to be able to apply these concepts and articulate testable hypotheses that explain natural phenomena from an evolutionary perspective. It highlights the diversity of empirical approaches and lines of evidence that scientists use to address evolutionary hypotheses. It helps students to practice approaching problems like scientists and evaluate data to address evolutionary hypotheses. To do so, students learn how to program in R to analyze and visualize data and articulate your interpretations and conclusions.
Each chapter provides a conceptual introduction to the topic and includes R-based exercises that allow students to visualize relevant datasets to practice the testing of evolutionary hypotheses. To help with the R exercises, each chapter also provides additional background on case studies and R programming tutorials that help students to develop the necessary skills.
A Primer of Evolution is entirely written in R Markdown and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Anyone is free to copy and redistribute the material in any medium or format, and to remix, transform, and build upon the material provided they give the original author credit (attribution), they are not using the material for commercial purposes (NonCommerical), and they distribute their work under the same license as the original (ShareAlike). If you would like to adopt and use this resource in any way, feel free to contact Michi Tobler to obtain a copy of all source files.
A Primer of Evolution was made possible with the support of a grant from the The Open/Alternative Textbook Initiative at Kansas State University. Chapters What Evolution Is Evidence for Evolution A Mechanism for Change The Raw Materials for Evolution Evolutionary Mechanisms I: Modeling Selection Evolutionary Mechanisms II: Mutation, Genetic Drift, Migration, and Non-Random Mating Evolution of DNA Sequences Evolution of Quantitative Traits Adaptation and Phenotypic Plasticity Social Behavior and Sexual Selection Speciation Evolutionary Medicine I: Aging and Diseases of Civilizations Evolutionary Medicine II: Evolving Pathogens Human Evolution
Source available at: https://github.com/michitobler/primer-of-evolutio
Moving Forward by Looking Back: How Family Firms Create Competitive Advantage by Embracing Their History
Get PDFFamily businesses are the engine that drives the United States economy. While extensive implications have been made in the literature about the advantages or disadvantages of family-owned businesses compared to non-family-owned businesses, the focus of this study was to show how small to medium-sized family-owned firms (FF SMEs) based in the United States can use their unique history to create a competitive advantage. Drawing on imprint theory and the resource-based view (RBV), this history-informed study helped identify the impact that founder imprints, business traditions, and storytelling have on the business performance of FF SMEs. Using quantitative methods, the findings of this study show that as FF SMEs place an increased focus on their business traditions and build their competency for storytelling, they create a competitive advantage and positively impact their performance. Additionally, a moderating effect was found between the variables of business traditions and storytelling and the variables of founder imprints and business performance, which demonstrates that the moderating effect can be controlled by leadership, can influence business performance, and can reduce the impact of founder imprints. Therefore, the findings of this study extend the literature on founder imprints and rhetorical history and provide a roadmap for how FF SME owners can curate traditions and develop a competency for storytelling competency among its leaders
Understanding the Ethical Decision-Making Processes of Equine-Assisted Psychotherapy Practitioners
Get PDFEquine-assisted psychotherapy is a unique field in which interdisciplinary teams of practitioners provide mental health services to clients. These teams are comprised of at least two practitioners, one licensed mental health specialist and one certified equine specialist. While ethics and ethical decision-making are significant issues in the mental health industry, there exists a significant gap in the literature pertaining to the ethical decision-making processes of interdisciplinary teams of equine-assisted psychotherapy practitioners. This dissertation aimed to address the gap through the development of an understanding of how teams of equine-assisted psychotherapy practitioners engage in ethical decision making. Further, the researcher sought to identify whether an existing decision-making model could be useful for teams of equine-assisted psychotherapy practitioners. This qualitative study utilized Modified Grounded Theory techniques to analyze the experiences of fifteen (15) participant teams of equine-assisted psychotherapy practitioners. Each participant team analyzed a hypothetical scenario containing numerous ethical issues and then participated in a semi-structured interview with the researcher. The findings of this study yielded five categories of ethical decision-making processes and numerous sub-categories. In addition, the findings provided a basis for a proposed ethical decision-making model geared toward the equine-assisted psychotherapy industry. This dissertation presents the findings and limitations of this study, along with opportunities for further research. It presents the implications for equine-assisted psychotherapy practitioners and the mental health industry
Transition to the New Revenue Standard: A Study of Firms’ Decisions to Adopt ASC 606 Early
Get PDFThe Financial Accounting Standards Board has issued a new revenue standard through a series of updates since May 2014 (collectively, ASC 606). The standard allowed firms to adopt it a year early before the required effective date. This study provides evidence of the adoption effects of ASC 606 on firms’ financials and examines the relationship between the likelihood of early adopting ASC 606 and firm-specific characteristics. The results show that early adopters are distributed across 12 industries and 40% of them are concentrated in the computer programming and software industry. Early adopters in the software industry reported the largest cumulative adoption effects in dollars on retained earnings. Overall, the majority of the sample firms (83%) reported positive adoption effects on financial statements and the adoption of ASC 606 increased their retained earnings by 2.95% on average. The results also show that most early adopters chose the full retrospective method while the majority of industry-size-matched non-early adopting peers chose the modified retrospective method. Finally, the multivariate regression analyses suggest that early adopters are associated with decreased earnings in the year before adoption and more favorable adoption effects than non-early adopting peers
Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium
Get PDFBackground: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable