Reducing Hardships: Student Motivations, Educational Workflows, and Technology Choices in Academic Settings

Objective – This study examines The University of Manitoba student attitudes toward technology’s role in University study spaces and in their own educational workflows. Methods - A series of semi-structured group interviews were conducted with current undergraduate and graduate students at The University of Manitoba. Three group interviews were conducted with questions about individual technology and space use while studying in the library, and three group interviews were conducted with questions about group collaboration using technologies and tools in group study spaces. Transcripts were coded iteratively and separately by the researchers, analyzed for interrater reliability, categorized, and reviewed using axial coding to identify major themes. Through continued examination of these themes, a single theory emerged. Results - The participants expressed a strong need for independence and feelings of control over their workflows, technological tools, and environments. They discussed how interpersonal concerns and anxieties motivated their workflow choices and acknowledged the (often conflicting) motivational forces of personal necessity and personal preference. When examining the motivations behind the selection of technologies and work practices, it became clear that the respondents make technology and workflow decisions in an attempt to minimize their experience of perceived hardships. These perceived hardships could be social, emotional, educational, environmental, or temporal in nature, and the weight of any one hardship on decision making varied according to the individual. Conclusions - Libraries should be aware of this foundational user motivation and make choices accordingly - identifying and minimizing hardships whenever possible, unless they are necessary to achieve learning or service-specific goals. Additional research is required to help articulate the nuances experienced by particular student demographics. Librarians and future researchers should also consider investigating the potential disconnect between librarian and user attitudes toward technology, the prioritization of user-centered decision-making, and whether or not systematically disadvantaged social groups have different attitudes toward technology and its place in library spaces and academic work.https://journal.lib.uoguelph.ca/index.php/perj/article/view/545

Functional diversification of Argonautes in nematodes:an expanding universe

In the last decade, many diverse RNAi (RNA interference) pathways have been discovered that mediate gene silencing at epigenetic, transcriptional and post-transcriptional levels. The diversity of RNAi pathways is inherently linked to the evolution of Ago (Argonaute) proteins, the central protein component of RISCs (RNA-induced silencing complexes). An increasing number of diverse Agos have been identified in different species. The functions of most of these proteins are not yet known, but they are generally assumed to play roles in development, genome stability and/or protection against viruses. Recent research in the nematode Caenorhabditis elegans has expanded the breadth of RNAi functions to include transgenerational epigenetic memory and, possibly, environmental sensing. These functions are inherently linked to the production of secondary siRNAs (small interfering RNAs) that bind to members of a clade of WAGOs (worm-specific Agos). In the present article, we review briefly what is known about the evolution and function of Ago proteins in eukaryotes, including the expansion of WAGOs in nematodes. We postulate that the rapid evolution of WAGOs enables the exceptional functional plasticity of nematodes, including their capacity for parasitism

Rasch analysis of the Patient Rated Elbow Evaluation questionnaire

© 2015 Vincent et al. Background: The Patient Rated Elbow Evaluation (PREE) was developed as an elbow joint specific measure of pain and disability and validated with classical psychometric methods. More recently, Rasch analysis has contributed new methods for analyzing the clinical measurement properties of self-report outcome measures. The objective of the study was to determine aspects of validity of the PREE using the Rasch model to assess the overall fit of the PREE data, the response scaling, individual item fit, differential item functioning (DIF), local dependency, unidimensionality and person separation index (PSI). Methods: A convenience sample of 236 patients (Age range 21-79 years; M: F- 97:139) with elbow disorders were recruited from the Roth|McFarlane Hand and Upper Limb Centre, London, Ontario, Canada. The baseline scores of the PREE were used. Rasch analysis was conducted using RUMM 2030 software on the 3 sub scales of the PREE separately. Results: The 3 sub scales showed misfit initially with disordered thresholds on17 out of 20 items), uniform DIF was observed for two items ( Carrying a 10lbs object from specific activities subscale for age group; and household work from the usual activities subscale for gender); multidimensionality and local dependency. The Pain subscale satisfied Rasch expectations when item 2 Pain - At rest was split for age group, while the usual activities subscale readily stood up to Rasch requirements when the item 2 household work was split for gender. The specific activities subscale demonstrated fit to the Rasch model when sub test analysis accounted for local dependency. All three subscales of the PREE were well targeted and had high reliability (PSI \u3e0.80). Conclusion: The three subscales of the PREE appear to be robust when tested against the Rasch model when subject to a few alterations. The value of changing the 0-10 format is questionable given its widespread use; further Rasch-based analysis of whether these findings are stable in other samples is warranted

Unsupervised Adaptation for High-Dimensional with Limited-Sample Data Classification Using Variational Autoencoder

High-dimensional with limited-sample size (HDLSS) datasets exhibit two critical problems: (1) Due to the insufficiently small-sample size, there is a lack of enough samples to build classification models. Classification models with a limited-sample may lead to overfitting and produce erroneous or meaningless results. (2) The 'curse of dimensionality' phenomena is often an obstacle to the use of many methods for solving the high-dimensional with limited-sample size problem and reduces classification accuracy. This study proposes an unsupervised framework for high-dimensional limited-sample size data classification using dimension reduction based on variational autoencoder (VAE). First, the deep learning method variational autoencoder is applied to project high-dimensional data onto lower-dimensional space. Then, clustering is applied to the obtained latent-space of VAE to find the data groups and classify input data. The method is validated by comparing the clustering results with actual labels using purity, rand index, and normalized mutual information. Moreover, to evaluate the proposed model strength, we analyzed 14 datasets from the Arizona State University Digital Repository. Also, an empirical comparison of dimensionality reduction techniques shown to conclude their applicability in the high-dimensional with limited-sample size data settings. Experimental results demonstrate that variational autoencoder can achieve more accuracy than traditional dimensionality reduction techniques in high-dimensional with limited-sample-size data analysis

Tobacco consumption behavior change during the COVID-19 pandemic is associated with perceived COVID threat

RationaleTobacco use is a risk factor for COVID-19 adverse outcomes. Despite health implications, data conflict regarding COVID-19 and tobacco consumption. We present results from a survey of health behaviors during the pandemic to identify how COVID-19 influenced tobacco behaviors.MethodsA nationally administered, internet-based survey was deployed between May-September 2020. Of respondents, we analyzed participants who reported current smoking and/or vaping. Our primary outcome of interest was change in tobacco or vape use using measures from the Behavioral Risk Factor Surveillance System, as well as whether participants reported that these changes were related to COVID-19. Our principal exposures were previously psychometrically evaluated measures of anxiety, depression, and novel perceived COVID-19 threat scale with additional adjustment for age. We employed multinomial logistic regression to determine associations between these factors and tobacco consumption.ResultsWe identified 500 respondents who reported ever smoking in their lifetime, 150 of which reported currently smoking at the time of the survey. Of 220 participants who reported any use of vapes, 110 reported currently vaping. Increased perceived threat of COVID-19 was associated with both increased (aRRincrease 1.75, 95% CI [1.07-2.86], P = 0.03) and decreased (aRRdecrease 1.72 [1.04-2.85], P = 0.03) tobacco consumption relative to no change. There were no significant relationships found between perceived threat of COVID-19 and vaping behavior.ConclusionsAs perceived COVID-19 threat increased, people were more likely to increase or decrease their smoking as opposed to continue at the same amount of use, even after controlling for anxiety and depression, both of which are known to affect smoking in either direction. Further study into motivators of changing tobacco consumption behaviors, and how barriers to care from safer-at-home policies and changes in care delivery moderate change in tobacco use will aid planning tobacco reduction interventions during the ongoing and future respiratory viral pandemics.Trial registrationThis manuscript is derived from baseline survey data obtained in the "Understanding Community Considerations, Opinions, Values, Impacts, and Decisions in COVID-19" study.Clinicaltrialsgov registration NCT04373135, registered 04/30/2020

Navigating Digital Geographies and Trauma Contexts: Conceptions of Online Communities and Experiences Among LGBTQ+ People During COVID-19

The coronavirus pandemic shaped challenges for marginalized groups. Specifically, lesbian, gay, bisexual, transgender, and/or queer (LGBTQ+) people experienced community-building constraints, notably in predominantly rural regions. People are also navigating digital geographies, or online social environments, in novel ways to develop virtual communities in the face of prejudice, discrimination, and potential trauma. Through a minority coping approach, the present study explored LGBTQ+ people’s experiences navigating the dynamics of digital geographies during the pandemic while residing in socially conservative, highly rural physical spaces where they may be exposed to vicarious trauma. Using qualitative semi-structured interviews, data were gathered from 43 LGBTQ+ identifying individuals between 19 and 59 years old (M/SD = 27.7/9.2) between October 2020 and January 2021. Nearly 14% identified as transgender, nonbinary, or queer individuals, 35% as bisexual individuals, and 21% as people of color including Hispanic/Latina/o. Thematic analysis of the narratives described participants’ exposures to online discrimination and stigmatization of minority groups (racial and/or sexual/gender minority groups) during the COVID-19 pandemic, institutional constraints to identity expression, utilizing social technologies to manage their identities, and negotiating digital strategies to promote social ties. Findings emphasize improving marginalized people’s experiences with digital geographies through identity affirmation and community relationship-building to offset potentially traumatic experiences. Furthermore, service providers can utilize the findings to tailor effective virtual LGBTQ+ community programming to support underserved, marginalized populations

Patient Perception of Physician Attire Before and After Disclosure of the Risks of Microbial Contamination

Background: The white coat is traditionally considered to be the appropriate attire for physicians but it may also be contaminated with microbes and act as a potential source of infection. We aimed to study patients’ acceptance of physicians’ attire, their underlying reasons, and their reactions to an educational intervention with regards to the risks of contamination. Methods: We conducted a voluntary ques­tionnaire survey at a university teaching hospital in Hong Kong from February to July 2012. 262 patient-responses from adult inpatients and outpatients across various specialties were analysed. Results: White coats were highly favoured (90.8%) when compared with scrubs (22.1%), smart casual (7.6%) and formal (7.3%) wears. ’Professional image’ and ‘ease of identification’ were the main attributes of the white coat. Most patients (92.2%) would prefer doctors washing their white coats every few days, whilst 80.9% believed that doctors were actually doing so. After patients were informed of the potential risk of microbial contamination, white coats remained as the most favoured attire (66.4%), but with scrubs doubling in popularity (45.8%). Smart casual (9.2%) and formal attire (4.6%) remain the least accepted. Conclusion: Despite cross-infections being a significant concern within the healthcare environments, patients’ predominant acceptance and perceived attributes towards the white coat were maintained after an educational intervention on the risks of microbial contamination

Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes

Background: Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. Results: Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. Conclusion: We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single “optimal” pubertal growth pattern