582 research outputs found
Support, School Climate and Teacher Wellbeing in the Wake of COVID-19: A National Study Using NTSP Data
Research indicates a significant number of teachers planned to leave the profession following the COVID-19 pandemic, with national surveys in 2021 revealing about 25% considering departure. Stress, low pay, remote teaching demands, and lack of support contributed to attrition, impacting school climate, which influences productivity, collaboration, and job satisfaction, and is inversely related to turnover. The shift to remote learning also demanded new skills and exposed technological disparities. This quantitative study examined the pandemic\u27s impact on teachers\u27 perceptions of school climate, support, resources, job satisfaction, burnout, and intent to leave using the 2020–2021 National Teacher and Principal Survey. Factor analyses revealed two school climate constructs: administrative tasks/outcomes and shared belief systems. While a weak positive relationship existed between resources/support and school climate, organizational climate positively correlated with job satisfaction and negatively with burnout and intent to leave. Similarly, staff collaboration/cohesiveness negatively correlated with burnout/intent to leave and positively with job satisfaction. These findings emphasize the importance of positive administrative interactions, fair policies, and shared values in supporting teacher well-being and reducing turnover in the post-pandemic educational context.Advisor: Jiangang Xi
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Relationship of Estrous Cycle to Herpes Simplex Virus Type 2 Susceptibility in Female Mice
In CBA/NJ mice, splenic natural killer (NK) cell activity varies with stages of estrous. Susceptibility of ICR mice to intravaginal inoculation of herpes simplex virus type 2 (HSV-2) decreases with age. Susceptibility of female ICR and CBA/NJ mice to HSV-2 inoculated intravaginally and intraperitoneally was examined during the estrous cycle. In cycling ICR mice, greatest susceptibility to intravaginal inoculation was observed during diestrous and the least during metestrous. CBA/NJ mice were most susceptible to intravaginal inoculation of HSV-2 during diestrous. ICR mice were ovariectomized to mimic diestrous and found to be highly susceptible to intravaginal inoculation at all virus doses. No difference in susceptibility among phases of the estrous cycle was seen following intraperitoneal inoculation
Explainable Model-Agnostic Similarity and Confidence in Face Verification
Recently, face recognition systems have demonstrated remarkable performances
and thus gained a vital role in our daily life. They already surpass human face
verification accountability in many scenarios. However, they lack explanations
for their predictions. Compared to human operators, typical face recognition
network system generate only binary decisions without further explanation and
insights into those decisions. This work focuses on explanations for face
recognition systems, vital for developers and operators. First, we introduce a
confidence score for those systems based on facial feature distances between
two input images and the distribution of distances across a dataset. Secondly,
we establish a novel visualization approach to obtain more meaningful
predictions from a face recognition system, which maps the distance deviation
based on a systematic occlusion of images. The result is blended with the
original images and highlights similar and dissimilar facial regions. Lastly,
we calculate confidence scores and explanation maps for several
state-of-the-art face verification datasets and release the results on a web
platform. We optimize the platform for a user-friendly interaction and hope to
further improve the understanding of machine learning decisions. The source
code is available on GitHub, and the web platform is publicly available at
http://explainable-face-verification.ey.r.appspot.com
Postmarketing Follow-Up of a Digital Home Exercise Program for Back, Hip, and Knee Pain: Retrospective Observational Study With a Time-Series and Matched-Pair Analysis
Background: Musculoskeletal conditions are the main drivers of global disease burden and cause significant direct and indirect health care costs. Digital health applications improve the availability of and access to adequate care. The German health care system established a pathway for the approval of “Digitale Gesundheitsanwendungen” (DiGAs; Digital Health Applications) as collectively funded medical services through the “Digitale-Versorgung-Gesetz” (Digital Health Care Act) in 2019.
Objective: This article presents real-world prescription data collected through the smartphone-based home exercise program “Vivira,” a fully approved DiGA, regarding its effect on self-reported pain intensity and physical inability in patients with unspecific and degenerative pain in the back, hip, and knee.
Methods: This study included 3629 patients (71.8% [2607/3629] female; mean age 47 years, SD 14.2 years). The primary outcome was the self-reported pain score, which was assessed with a verbal numerical rating scale. The secondary outcomes were self-reported function scores. To analyze the primary outcome, we used a 2-sided Skillings-Mack test. For function scores, a time analysis was not feasible; therefore, we calculated matched pairs using the Wilcoxon signed-rank test.
Results: Our results showed significant reductions in self-reported pain intensity after 2, 4, 8, and 12 weeks in the Skillings-Mack test (T3628=5308; P<.001). The changes were within the range of a clinically relevant improvement. Function scores showed a generally positive yet more variable response across the pain areas (back, hip, and knee).
Conclusions: This study presents postmarketing observational data from one of the first DiGAs for unspecific and degenerative musculoskeletal pain. We noted significant improvements in self-reported pain intensity throughout the observation period of 12 weeks, which reached clinical relevance. Additionally, we identified a complex response pattern of the function scores assessed. Lastly, we highlighted the challenges of relevant attrition at follow-up and the potential opportunities for evaluating digital health applications. Although our findings do not have confirmatory power, they illustrate the potential benefits of digital health applications to improve the availability of and access to medical care
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