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Analyzing staphylococcal contamination on surfaces and bedside areas of a neonatal intensive care unit of a children\u27s hospital
Get PDFStaphylococci species are known to be a cause of Healthcare-Associated Infections (HAIs) in neonatal intensive care units (NICU). There is limited research about the surveillance and identification of staphylococci bacteria from NICUs. Surveillance of bacteria within the NICU helps to identify areas acting as reservoirs for bacteria so that new cleaning policies and techniques can be put in place to stop the spread of HAIs. The objective of this study was to swab sample sites in a local level IV hospital NICU and identify locations of staphylococci presence throughout the NICU. Forty-one swabs were selected from over 900 swabs collected from the NICU at Erlanger Hospital for testing at the University of Tennessee Chattanooga’s Clinical Infectious Disease Control lab. Using aseptic technique and standard microbiological procedures swab samples from the NICU were regrown as pure subcultures and tested using a variety of different tests, including the Remel RapID™ STAPH PLUS identification system to provide genus and species identities for the isolates. Of the 41 swabs selected, 17 different staphylococci species were observed, including Staphylococcus aureus and Staphylococcus epidermidis. The 17 different identified species were found on 45% of the swab sites throughout the NICU, with the most contaminated device being the suction yankauer (53%), and the highest contaminated surface being floors near sinks (41%). Further study for bacterial surveillance in the NICU will help to determine the best disinfection policies and cleaning practices for the decreased transmission of HAIs
The Future of Performance Management in a Remote/Hybrid World of Work
Get PDFWith the many recognized benefits of remote/hybrid work, it is expected that many organizations will never go back to the traditional office model in the wake of the COVID-19 pandemic. With this in mind, many themes from the traditional performance management literature will need to be revisited with an eye toward the future. These themes include a) the increased importance of job analysis for identifying current and future requirements of remote/hybrid work, b) an integration of work-family dynamics into our models of job performance, c) a better understanding of optimal productivity windows and the timing of when work happens, d) implications for the opportunity to observe performance of hybrid/remote workers, e) a better understanding of contextual performance in hybrid/remote work environments, and f) implications of motivation to give and receive feedback in remote/hybrid work environments. In this talk, I will reflect on these themes and provide recommendations for organizations who are likely wrestling with these important considerations
Ambergris
Get PDFThis thesis contains the first three chapters of my novel in progress, Ambergris, and a craft essay on sentence construction titled, “Narrative on the Level of the Line.” In the craft essay I explore the mechanisms of sentences in creative writing and their function to craft narrative in unique ways through sentence structure, dialog, and imagery. I examine methods of redefining grammar as it pertains to writing fiction works, such as whether or not to use traditional structural rules to keep the reader engaged. I have used these creative methods in constructing the specific language of my characters, deploying supernatural elements, crafting imagery-laden exposition, and the overall flow of the narrative in Ambergris. If I have crafted it well, it will translate into an engaging, fantastical, dark fairy tale that imparts a subliminal message on the power of free will and what can happen when that agency is tested
Into the Inferno: a television screenplay adaptation of Dante\u27s Inferno
No full textInto the Inferno is a nine-episode screenplay loose adaptation of Dante’s Inferno. It follows the story of Ophelia Ariti as she is tasked by her family to travel through the depths of the Inferno to bring her deceased twin back to life. During this journey, she encounters each circle of the Inferno and meets its dwellers and demons with a suspiciously helpful guide named Lyon. To pass through each circle, she must commit the sin associated with it. Throughout the journey, Ophelia discovers who she is, for better or for worse. The show’s theme is living life selfishly. The thesis included the show “Bible” and the pilot episode; it is a start of a larger project. The “Bible” provided a section describing the research by a literature review and creative decisions that went into the show. It included a proposal and treatment which can be used when proposing the show to streaming services like Disney + and HBO. Character write-ups are provided to help understand the main characters, Ophelia and Lyon. The rest of the “Bible” has outlines for the rest of the nine episodes in the series. The pilot episode is written in the traditional screenwriting format with roughly an hour runtime
Exploring Diversity with Statistics: Step-by-step JASP Guides
Get PDFThese resources were created to complement our undergraduate statistics lab manual, Applied Data Analysis in Psychology: Exploring Diversity with Statistics, published by Kendall Hunt publishing company. Like our lab manual, these JASP walk-through guides meaningfully and purposefully integrate and highlight diversity research to teach students how to analyze data in an open-source statistical program. The data sets utilized in these guides are from open-access databases (e.g., Pew Research Center, PLoS One, ICPSR, and more). Guides with step-by-step instructions, including annotated images and examples of how to report findings in APA format, are included for the following statistical tests: independent samples t test, paired samples t test, one-way ANOVA, two factor ANOVA, chi-square test, Pearson correlation, simple regression, and multiple regression. Additionally, you will find instructor resources added with our Summer 2023 update. Please feel free to use our added instructor PowerPoint slides highlighting additional research focused on equity, diversity, and inclusion topics. If you are new to incorporating diversity-focused research, you may benefit from some of the resources shared in our newly added instructor resources list. If you are interested in partnering with us to adapt these resources for other statistical software programs, have suggestions for revisions or additions, or would like additional information on how to best integrate these materials into your courses, please contact [email protected]://scholar.utc.edu/open-textbooks/1000/thumbnail.jp
False memories of expectancy-consistent and expectancy-inconsistent images in a paired-association memory task
Get PDFThe current research utilized a paired-association task previously developed to evoke false memories to determine whether people would be more likely to falsely recall having viewed expectancy-consistent vs. expectancy-inconsistent images. Participants were shown a series of 60 expectancy-consistent and expectancy-inconsistent images and were then asked whether they recognized 120 partially redacted images (60 previously seen, 60 new). When they reported seeing a redacted image, they were asked which version (either the expectancy-consistent or the expectancy-inconsistent) they remembered having seen. We found that when participants falsely recognized redacted images, they were significantly more likely to select the expectancy-consistent version of the image. Surprisingly, we also found that accurate memories were more likely for expectancy-consistent images. These findings suggest that this paired-association task can be useful in evoking false memories of images
The effects of the COVID-19 pandemic on the fear of missing out, anxiety, and loneliness
Get PDFThe unprecedented nature of the COVID-19 pandemic implores consideration for how the psychopathological constructs the fear of missing out, anxiety, and loneliness are affected within this context (Liverant et al., 2004; Rajkumar, 2020). These mental well-being variables also all appear in association with social media (Hunt et al., 2018; Caplan, 2007). While previous research has explored the initial impacts of the pandemic on mental well-being (Wang, Pan et al., 2020; Bu et al., 2020), this research further examines the effect on college students’ mental well-being in the pandemic alongside social media usage. I hypothesize that levels of the fear of missing out, anxiety, and loneliness in college students will be higher during the COVID-19 pandemic than previous historical samples. I hypothesize that there will be a significant relationship between social media and these variables. I hypothesize that social media usage explains the variance in levels of the fear of missing out, anxiety, and loneliness in college students. Results of this study found increased levels of the fear of missing out, anxiety, and loneliness in college students. These variables also were strongly correlated between each other and social media. Social media usage only explained 11.8% of the variance in the fear of missing out and less for loneliness and anxiety, 7.1% and 4.8% respectively (p \u3c 0.05). Social media is contributing to the issue, but the pandemic poses a much larger issue that might be weighing more heavily on students
Do age and media type influence the effects of pretrial publicity on verdicts?
Get PDFConcerns about Pretrial Publicity (PTP) have grown with the rise of the internet and social media, leading to a near impossibility of selecting a jury that can ignore PTP and focus only on facts presented at trial. Previous research has shown participants exposed to negative PTP were more likely to find the defendant guilty, and tended to misattribute PTP as having been evidence presented during the trial. This study compared jury verdicts among older and younger jurors when PTP was presented in different media formats (text vs video). Results suggest both older and younger jurors tend to misattribute PTP information as trial information, which leads to more guilty verdicts. However, younger adults exposed to PTP were significantly more likely to render a guilty verdict and scored lower on a source memory test compared to older adults. Finally, format (text vs video) did not significantly moderate these effects
Understanding the lived experiences of immigrants in the United States
Get PDFWhen it comes to diversity research, immigrants have a long history of falling into an invisible group of people. This paper serves as an important first step into the vast amount of research that has yet to be done in regard to the lived experiences of immigrants that are legally living and working in the United States. Research for this project included open-ended, semi-structured individual interviews that took place with five immigrants. The participants immigrated to the U.S. on different visas, work in different industries, and are from different countries - thus allowing the interviews to reveal patterns of lived experiences of immigrants that are not based upon another minority trait, such as race or sex. Findings from this study include countless barriers, hoops, and complications that immigrants face and are forced to overcome in their everyday lives, that the everyday American Citizen would never even think about. This paper is a first step into the depth of information we as researchers have yet to uncover when it comes to this “invisible” group of people
Machine learning-enabled classification of climbers using small data
Get PDFAthlete performance scoring within climbing presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill level is valuable as it can be used to mark training progress and help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. Solutions to the classification problem included light-weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill