Otolaryngology Patient Satisfaction with In-Office Appointments and Virtual Visits Due to COVID-19.

BACKGROUND: The COVID-19 pandemic forced otolaryngologists to seek new methods of providing patient care in a remote setting. The effect of this paradigm shift on patient satisfaction, however, remains unelucidated. This study compares patient satisfaction with telehealth visits during the COVID-19 pandemic to that with in-office visits during the same period in 2019. METHODS: Press Ganey survey responses of patients seen by otolaryngologists within a large, academic, multicenter hospital system were gathered. Responses were included in analyses if they corresponded with a visit that occurred either in clinic March to December 2019 or via telehealth March to December 2020. Chi-Square Test of Independence and Fisher's Exact Test were employed to detect differences between years. Binary logistic regressions were performed to detect the factors most predictive of positive telehealth experiences. RESULTS: Patient overall satisfaction with in-office and telehealth visits did not differ significantly (76.4% in 2019 vs 78.0% in 2020 rated visit overall as "very good," P = .09). Patients seen by a Head and Neck (odds ratio 4.13, 95% confidence interval 1.52-11.26, P = .005), Laryngology (OR 5.96, 95% CI 1.51-23.50, P = .01), or Rhinology (OR 4.02, 95% CI 1.55-10.43, P = .004) provider were significantly more likely to report a positive telehealth experience. CONCLUSIONS: Patients seen via telehealth during COVID-19 reported levels of satisfaction similar to those seen in-office the year prior. These telehealth satisfaction levels, however, are contextualized within the expected confines of a pandemic. Further research is required to determine whether satisfaction remains consistent as telemedicine becomes a ubiquitous component of medical practice.

Making Sense of Uncertainty in the Science Classroom : A Bayesian Approach

Uncertainty is ubiquitous in science, but scientific knowledge is often represented to the public and in educational contexts as certain and immutable. This contrast can foster distrust when scientific knowledge develops in a way that people perceive as a reversals, as we have observed during the ongoing COVID-19 pandemic. Drawing on research in statistics, child development, and several studies in science education, we argue that a Bayesian approach can support science learners to make sense of uncertainty. We provide a brief primer on Bayes’ theorem and then describe three ways to make Bayesian reasoning practical in K-12 science education contexts. There are a) using principles informed by Bayes’ theorem that relate to the nature of knowing and knowledge, b) interacting with a web-based application (or widget—Confidence Updater) that makes the calculations needed to apply Bayes’ theorem more practical, and c) adopting strategies for supporting even young learners to engage in Bayesian reasoning. We conclude with directions for future research and sum up how viewing science and scientific knowledge from a Bayesian perspective can build trust in science. Supplementary Information The online version contains supplementary material available at 10.1007/s11191-022-00341-3.

COVID-19 impact on SADC labour markets: Evidence from high-frequency data and other sources.

We assess the impact of the coronavirus disease 2019 (COVID-19) pandemic on the labour markets and economies of 16 SADC member states using a qualitative risk assessment on the basis of high-frequency Google Mobility data, monthly commodity price data, annual national accounts, and households survey labour market data. Our work highlights the ways in which these complementary datasets can be used by economists to conduct near real-time macroeconomic surveillance work covering labour market responses to macroeconomic shocks, including for seemingly information scarce African economies. We find that Angola, South Africa and Zimbabwe are at greatest risk across several labour market dimensions from the COVID-19 shock, followed by a second group of countries consisting of Comoros, DRC, Madagascar and Mauritius. Angola faces relatively less general employment risk than South Africa and Zimbabwe due to more muted decreases in mobility, though faces large pressure in its primary sector. These countries all face high risk in their youth populations, with Angola and Zimbabwe seeing high risks for women. South Africa faces more sector-specific risks in their secondary and tertiary sectors, as does Mauritius. Comoros, DRC and Madagascar all face high risks of employment loss for women and youth, with Comoros and Mauritius facing severe general employment risks.

Hypothetical case replacement can be used to quantify the robustness of trial results.

OBJECTIVES: We apply a general case replacement framework for quantifying the robustness of causal inferences to characterize the uncertainty of findings from clinical trials. STUDY DESIGN AND SETTING: We express the robustness of inferences as the amount of data that must be replaced to change the conclusion and relate this to the fragility of trial results used for dichotomous outcomes. We illustrate our approach in the context of an RCT of hydroxychloroquine on pneumonia in COVID-19 patients and a cumulative meta-analysis of the effect of antihypertensive treatments on stroke. RESULTS: We developed the Robustness of an Inference to Replacement (RIR), which quantifies how many treatment cases with positive outcomes would have to be replaced with hypothetical patients who did not receive a treatment to change an inference. The RIR addresses known limitations of the Fragility Index by accounting for the observed rates of outcomes. It can be used for varying thresholds for inference, including clinical importance. CONCLUSION: Because the RIR expresses uncertainty in terms of patient experiences, it is more relatable to stakeholders than P-values alone. It helps identify when results are statistically significant, but conclusions are not robust, while considering the rareness of events in the underlying data.

#Mathathome during the COVID-19 Pandemic: Exploring and Reimagining Resources and Social Supports for Parents

During the COVID-19 pandemic, schools abruptly transitioned to emergency remote instruction. Consequently, expectations for parental involvement in school mathematics rose to unprecedented levels. We sought to understand the experiences of parents to reimagine possibilities for engagement in mathematics during and beyond the pandemic. Leveraging data from tweets using #mathathome and survey responses from parents, we identified who supported continued mathematics learning at home and explored the nature of the mathematics taught there. We found that Twitter and survey data sources described two largely distinct groups of those supporting parents to continue mathematics education at home, but similar findings emerged from analyses of each data source, suggesting that themes were common among different groups. Namely, we saw a commitment to continued mathematics learning and engagement with a range of mathematics topics. These topics mostly focused on elementary-level content, especially counting, through everyday activities/objects and mathematical sense-making. Most parents used resources provided by the school alongside resources they identified and provided on their own. School responses to emergency remote instruction were mostly asynchronous, and parents expressed a need for more opportunities to interact directly with their children’s teachers. We discuss what the mathematics education community might learn from these experiences to support parental engagement during and beyond periods of remote emergency instruction.

Balancing' privacy and open science in the context of COVID-19: a response to Ifenthaler & Schumacher (2016).

Privacy and confidentiality are core considerations in education, while at the same time, using and sharing data-and, more broadly, open science-is increasingly valued by editors, funding agencies, and the public. This manuscript responds to an empirical investigation of students' perceptions of the use of their data in learning analytics systems by Ifentahler and Schumacher (Educational Technology Research and Development, 64: 923-938, 2016). We summarize their work in the context of the COVID-19 pandemic and the resulting shift to digital modes of teaching and learning by many teachers, using the tension between privacy and open science to frame our response. We offer informed recommendations for educational technology researchers in light of Ifentahler and Schumacher's findings as well as strategies for navigating the tension between these important values. We conclude with a call for educational technology scholars to meet the challenge of studying learning (and disruptions to learning) in light of COVID-19 while protecting the privacy of students in ways that go beyond what Institutional Review Boards consider to be within their purview.

Characterization of Critically Ill COVID-19 Patients at a Brooklyn Safety-Net Hospital.

Background The novel coronavirus disease 2019 (COVID-19) pandemic continues to spread across the country with over 3 million cases and 150,000 deaths in the United States as of July 2020. Outcomes have been poor, with reported admission rates to the intensive care team of 5% in China and mortality among critically ill patients of 50% in Seattle. Here we explore the disease characteristics in a Brooklyn safety-net hospital affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Methods A retrospective chart review of COVID-19 positive patients at The Brooklyn Hospital Center who were treated by the intensive care team prior to April 20, 2020. Data was extracted from the electronic health record, analyzed and correlated for outcome. Results Impact of various clinical treatments was assessed, showing no change in median overall survival (OS) of both hydroxychloroquine with azithromycin or vitamin C with zinc. Supplemental therapies were used in selected patients, and some were shown to increase median OS and patients requiring vasopressor support or invasive mechanical ventilation showed decreased OS. There was no statistically significant difference in overall survival based on ethnicity, healthcare status, or individual medical comorbidities, although a negative trend exists for diabetes. Despite this, there is a trend towards increasingly poor prognosis based on the number of comorbidities and Class 3 obesity.  Conclusions Despite the fact that we show no significant differences in mortality based on ethnicity, insurance status, or individual medical comorbidities, we show a high overall mortality. There is also a trend towards increased overall mortality in Class 3 obesity, which should be further investigated. We suggest that these findings may be attributed to both socioeconomic factors and an increased incidence of total medical comorbidities in our patient population.