Primary healthcare clinicians' positive perceptions of the implementation of telehealth during the COVID-19 pandemic using normalisation process theory

The objective of the study was to measure implementation of telehealth for client consultations from Allied Health and Community Health clinicians' perspectives during the COVID-19 pandemic. Purposeful sampling was used to invite allied and community health clinicians to complete the survey. An online survey design, underpinned by normalisation process theory, utilising the NoMAD tool, which consists of 19 implementation assessment items. Descriptive statistics are reported. A 66% (n = 24) response rate was obtained. Fifty-two percent indicated they were using telehealth for the first time. Despite the rapid implementation of telehealth for client consultations due to the pandemic crisis, participants reported positive perceptions of the use of telehealth when measured using the NoMAD. Fifty-eight percent (n = 14) of respondents agreed or strongly agreed that telehealth will become a normal part of their work. Despite unplanned and under-resourced implementation of telehealth, Allied Health and Community Health clinicians reported very positive perceptions. However, further education and training to ensure 'normalisation' of this model may be required. </p

A new survey tool for evaluating pandemic preparedness in health services

BACKGROUND: Rapid decision-making with limited resources and prior research to draw upon posed challenges for health service leaders globally when preparing for COVID-19. How do health services prepare for a pandemic and evaluate if the preparation has been effective? This study aimed to explore health workers’ perceptions and knowledge regarding preparedness for COVID-19 at a regional health service in Australia. METHODS: A 32-item online survey was developed to evaluate preparedness across five scales: 1) Clinical, 2) Communication, 3) Environment, 4) Human Resources, and 5) General Preparedness. Data were analyzed using parametric and non-parametric statistics and qualitative content analysis. RESULTS: Ninety-three employees completed the survey, with most working in clinical roles (58.1%). Respondents largely felt the health service was well-prepared (84.0%) and they were personally prepared (74.4%) to respond to COVID-19. Clinical and communication scale scores varied by role type. Respondents faced personal risk and resource shortages impacted their sense of safety; others felt adequately supported. CONCLUSIONS: A coordinated “whole hospital response”, accessible and inclusive communication, education, adequate resourcing, and employee wellbeing supports are necessary when preparing health services for sentinel events. This survey tool offers health services an approach to evaluating pandemic preparation. Continued advocacy for resources and wellbeing needs of health workers is paramount in future preparations

Spectral embedding finds meaningful (relevant) structure in image and microarray data

BACKGROUND: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA) is a linear dimensionality reduction (DR) method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s) fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. RESULTS: We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method). This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent classification method, enabling the possibility of valid cross-experiment comparisons. CONCLUSION: Results from the spectral method presented here exhibit the desirable properties of preserving meaningful nonlinear relationships in lower dimensional space and requiring minimal parameter fitting, providing a useful algorithm for purposes of visualization and classification across diverse datasets, a common challenge in systems biology

AffyMAPSDetector: a software tool to characterize Affymetrix GeneChip™ expression arrays with respect to SNPs

<p>Abstract</p> <p>Background</p> <p>Affymetrix gene expression arrays incorporate paired perfect match (PM) and mismatch (MM) probes to distinguish true signals from those arising from cross-hybridization events. A MM signal often shows greater intensity than a PM signal; we propose that one underlying cause is the presence of allelic variants arising from single nucleotide polymorphisms (SNPs). To annotate and characterize SNP contributions to anomalous probe binding behavior we have developed a software tool called AffyMAPSDetector.</p> <p>Results</p> <p>AffyMAPSDetector can be used to describe any Affymetrix expression GeneChip™ with respect to SNPs. When AffyMAPSDetector was run on GeneChip™ HG-U95Av2 against dbSNP-build-123, we found 7286 probes (belonging to 2,582 probesets) containing SNPs, out of which 325 probes contained at least one SNP at position 13. Against dbSNP-build-126, 8758 probes (belonging to 3,002 probesets) contained SNPs, of which 409 probes contained at least one SNP at position 13. Therefore, depending on the expressed allele, the MM probe can sometimes be the transcript complement. This information was used to characterize probe measurements reported in a published, well-replicated lung adenocarcinoma study. The total intensity distributions showed that the SNP-containing probes had a larger negative mean intensity difference (PM-MM) and greater range of the difference than did probes without SNPs. In the sample replicates, SNP-containing probes with reproducible intensity ratios were identified, allowing selection of SNP probesets that yielded unique sample signatures. At the gene expression level, use of the (MM-PM) value for SNP-containing probes resulted in different Presence/Absence calls for some genes. Such a change in status of the genes has the clear potential for influencing downstream clustering and classification results.</p> <p>Conclusion</p> <p>Output from this tool characterizes SNP-containing probes on GeneChip™ microarrays, thus improving our understanding of factors contributing to expression measurements. The pattern of SNP binding examined so far indicates distinct behavior of the SNP-containing probes and has the potential to help us identify new SNPs. Knowing which probes contain SNPs provides flexibility in determining whether to include or exclude them from gene-expression intensity calculations; selected sets of SNP-containing probes produce sample-unique signatures.</p> <p>AffyMAPSDetector information is available at <url>http://www.binf.gmu.edu/weller/BMC_bioinformatics/AffyMapsDetector/index.html</url></p

Cultivating Community in a Sixth-Grade Classroom: An Action Research Study

Students who experience trauma bring this trauma to school with them in the form of exaggerated behaviors—acting out or withdrawing, being violent or extremely passive, or exhibiting rudeness or academic difficulty. Because students react to trauma in many ways, there is no one way for teachers to respond. The classroom community is vulnerable to the sheer unpredictability of behaviors. Grounded in ecological systems theory, whole-child theory, and compassionate teaching theory, this study explored my efforts to mitigate the results of trauma and increase the sense of community and well-being in my sixth-grade classroom. During the last few weeks of the 2021–2022 school year, I implemented interventions based on principles of mindfulness, restorative practices, and positivity. Students experienced lessons in regulating breathing, learned to reflect on behavior, and participated in community circles three times a week, as I collected data through journaling and observation. Despite students’ struggles to adapt to these new techniques and setbacks along the way, the overall classroom community improved

Secondary structure in the target as a confounding factor in synthetic oligomer microarray design

BACKGROUND: Secondary structure in the target is a property not usually considered in software applications for design of optimal custom oligonucleotide probes. It is frequently assumed that eliminating self-complementarity, or screening for secondary structure in the probe, is sufficient to avoid interference with hybridization by stable secondary structures in the probe binding site. Prediction and thermodynamic analysis of secondary structure formation in a genome-wide set of transcripts from Brucella suis 1330 demonstrates that the properties of the target molecule have the potential to strongly influence the rate and extent of hybridization between transcript and tethered oligonucleotide probe in a microarray experiment. RESULTS: Despite the relatively high hybridization temperatures and 1M monovalent salt imposed in the modeling process to approximate hybridization conditions used in the laboratory, we find that parts of the target molecules are likely to be inaccessible to intermolecular hybridization due to the formation of stable intramolecular secondary structure. For example, at 65°C, 28 ± 7% of the average cDNA target sequence is predicted to be inaccessible to hybridization. We also analyzed the specific binding sites of a set of 70mer probes previously designed for Brucella using a freely available oligo design software package. 21 ± 13% of the nucleotides in each probe binding site are within a double-stranded structure in over half of the folds predicted for the cDNA target at 65°C. The intramolecular structures formed are more stable and extensive when an RNA target is modeled rather than cDNA. When random shearing of the target is modeled for fragments of 200, 100 and 50 nt, an overall destabilization of secondary structure is predicted, but shearing does not eliminate secondary structure. CONCLUSION: Secondary structure in the target is pervasive, and a significant fraction of the target is found in double stranded conformations even at high temperature. Stable structure in the target has the potential to interfere with hybridization and should be a factor in interpretation of microarray results, as well as an explicit criterion in array design. Inclusion of this property in an oligonucleotide design procedure would change the definition of an optimal oligonucleotide significantly

Teaching Physical Concepts in Oceanography: An Inquiry-Based Approach

This supplement to Oceanography magazine focuses on educational approaches to help engage students in learning and offers a collection of hands-on/minds-on activities for teaching physical concepts that are fundamental in oceanography. These key concepts include density, pressure, buoyancy, heat and temperature, and gravity waves. We focus on physical concepts for two reasons. First, students whose attraction to marine science stems from an interest in ocean organisms are typically unaware that physics is fundamental to understanding how the ocean, and all the organisms that inhabit it, function. Second, existing marine education and outreach programs tend to emphasize the biological aspects of marine sciences. While many K–12 activities focus on marine biology, comparatively few have been developed for teaching about the physical and chemical aspects of the marine environment (e.g., Ford and Smith, 2000, and a collection of activities on the Digital Library for Earth System Education Web site [DLESE; http://www.dlese.org/library/index.jsp]). The ocean provides an exciting context for science education in general and physics in particular. Using the ocean as a platform to which specific physical concepts can be related helps to provide the environmental relevance that science students are often seeking. The activities described in this supplement were developed as part of a Centers for Ocean Sciences Education Excellence (COSEE) collaboration between scientists and education specialists, and they were implemented in two undergraduate courses that targeted sophomores, juniors, and seniors (one for marine science majors and one including both science and education majors) and in four, week-long workshops for middle- and high-school science teachers. Support for this project was provided by the National Science Foundation\u27s Division of Ocean Sciences Centers for Ocean Sciences Education Excellence (COSEE), grant number OCE-0528702. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of NSF