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Students in statistics, data science, analytics, and related fields study the theory and methodology of data-related topics. Some, but not all, are exposed to experiential learning courses that cover essential parts of the life cycle of practical problem-solving. Experiential learning enables students to convert real-world issues into solvable technical questions and effectively communicate their findings to clients. We describe several experiential learning course designs in statistics, data science, and analytics curricula. We present findings from interviews with faculty from the U.S., Europe, and the Middle East and surveys of former students. We observe that courses featuring live projects and coaching by experienced faculty have a high career impact, as reported by former participants. However, such courses are labor-intensive for both instructors and students. We give estimates of the required effort to deliver courses with live projects and the perceived benefits and tradeoffs of such courses. Overall, we conclude that courses offering live-project experiences, despite being more time-consuming than traditional courses, offer significant benefits for students regarding career impact and skill development, making them worthwhile investments. Supplementary materials for this article are available online.

Objective The COVID-19 pandemic in the U.S. has exhibited a distinct multiwave pattern beginning in March 2020. Paradoxically, most counties do not exhibit this same multiwave pattern. We aim to answer three research questions: (1) How many distinct clusters of counties exhibit similar COVID-19 patterns in the time-series of daily confirmed cases? (2) What is the geographic distribution of the counties within each cluster? and (3) Are county-level demographic, socioeconomic and political variables associated with the COVID-19 case patterns? Materials and methods We analyzed data from counties in the U.S. from March 1, 2020 to January 2, 2021. Time series clustering identified clusters in the daily confirmed cases of COVID-19. An explanatory model was used to identify demographic, socioeconomic and political variables associated with the outbreak patterns. Results Three patterns were identified from the cluster solution including counties in which cases are still increasing, those that peaked in the late fall, and those with low case counts to date. Several county-level demographic, socioeconomic, and political variables showed significant associations with the identified clusters. Discussion The pattern of the outbreak is related both to the geographic location within the U.S. and several variables including population density and government response. Conclusion The reported pattern of cases in the U.S. is observed through aggregation of the daily confirmed COVID-19 cases, suggesting that local trends may be more informative. The pattern of the outbreak varies by county, and is associated with important demographic, socioeconomic, political and geographic factors.

In order for the Open Access (OA) to learning concept to a have wider impact in formal education, it is important that faculty members intent to adopt new educational innovations. However, little is known about which variables influence the intention of faculty members. Therefore, the purposes of this study are to empirically determine: 1) which of the characteristics of the educational innovation significantly influence the intention to adopt educational innovations, 2) which variables influence the readiness of faculty members intention to adopt educational innovations, and 3) how the characteristics of the innovations moderate the relationship between faculty readiness and intention to adopt the innovations. Participants of this study include 335 faculty members in ABET certified computer science and electrical engineering programs in the United States. The results show that ease of use is positively related to the intention of faculty members to adopt an educational innovation. We conclude that Open-CourseWare developers need to ensure that ease of use is emphasized in the CourseWare and they need to propagate these initially in institutions where faculty members have positive attitude to the CourseWare and care about student learning. In addition, a new method of identifying, building, and funding “open access grant” universities that develop easy-to-use educational innovations, make them available on an open access platform, and spread them widely by embedding agents in community colleges, schools, and other educational institutions is essential. Such an initiative may lead to wider adoption of MOOCS and other open access materials.

BackgroundSocially vulnerable communities are at increased risk for adverse health outcomes during a pandemic. Although this association has been established for H1N1, Middle East respiratory syndrome (MERS), and COVID-19 outbreaks, understanding the factors influencing the outbreak pattern for different communities remains limited. ObjectiveOur 3 objectives are to determine how many distinct clusters of time series there are for COVID-19 deaths in 3108 contiguous counties in the United States, how the clusters are geographically distributed, and what factors influence the probability of cluster membership. MethodsWe proposed a 2-stage data analytic framework that can account for different levels of temporal aggregation for the pandemic outcomes and community-level predictors. Specifically, we used time-series clustering to identify clusters with similar outcome patterns for the 3108 contiguous US counties. Multinomial logistic regression was used to explain the relationship between community-level predictors and cluster assignment. We analyzed county-level confirmed COVID-19 deaths from Sunday, March 1, 2020, to Saturday, February 27, 2021. ResultsFour distinct patterns of deaths were observed across the contiguous US counties. The multinomial regression model correctly classified 1904 (61.25%) of the counties’ outbreak patterns/clusters. ConclusionsOur results provide evidence that county-level patterns of COVID-19 deaths are different and can be explained in part by social and political predictors.

Background: Lifting of masking restrictions at key periods during the COVID-19 pandemic may have disproportionately negatively impacted the mental health of individuals with disabilities., Objective: This study examines the prevalence of depression-related symptoms in individuals with and without disabilities preceding and following the US rollback of COVID-19 masking mandates., Methods: Pandemic-era data on reported symptoms of depression from the federal Household Pulse Survey from dates surrounding two major announcements on masking relaxations were analyzed. Possible interactions between disability status and type, age grouping, educational attainment, race/Hispanic ethnicity, and sex variables were considered., Results: Following relaxation of major masking restrictions, people with disabilities experienced elevation in depression symptom presence while people without disabilities experienced lessening in these symptoms. Differences between people with and without disabilities were significant., Conclusions: Direct causation between masking mandate relaxations and changes in symptoms of depression cannot be drawn from the available data. However, when considered with greater vulnerabilities to COVID-19 experienced by many individuals with disabilities and dismissive rhetoric surrounding masking decisions, negative feelings arising from mandate changes may have led to elevations in symptoms of depression in people with disabilities in sharp contrast to people without disabilities who may have felt relief. Findings indicate future public health decision making, even in times of crisis, should be undertaken with as much caution as possible regarding and in partnership with populations already at risk., (Copyright © 2024 Elsevier Inc. All rights reserved.)

WHAT IS KNOWN ON THE SUBJECT?: Individuals experiencing mental illness make up a significant portion of the world's population. Individuals with mental illness experience higher rates of morbidity and die on average at least a decade earlier than individuals without mental health disorders. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: Issues of stigma, diagnostic overshadowing, premature closure, inadequate workup, fear and lack of training negatively impact the care of individuals with mental illness. Issues impacting the care of individuals experiencing mental illness cross geographic and care setting boundaries. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Partnerships between physical and mental health practitioners are needed to thoroughly assess and accurately diagnose symptoms experienced by individuals with mental illness. Educational interventions can help prepare practitioners to care for individuals with mental illness. Nurses can better advocate for effective patient care by learning about the phenomenon of diagnostic overshadowing and calling attention to its occurrence. ABSTRACT: Introduction Individuals with mental illness experience significantly higher overall rates of morbidity and mortality than counterparts without mental illness. Misdiagnosis of symptoms emanating from physical illnesses as psychiatric in nature presents one important cause. Aim This integrative review explores research on healthcare professionals' misattribution of physical health symptoms to patients' comorbid psychiatric issues and seeks to identify unifying themes, shared causes, and possible strategies for addressing the issue. Method This review uses Whittemore and Knafl's 2005 integrative review methodology coupled with vetted quality appraisal tools. Results Following a systematic search of allied health, medical, psychological, sociological and general literature, 24 publications employing qualitative, quantitative, mixed and synthesis research methodologies were selected. Each study was appraised according to design, and relevant data were extracted. Discussion Themes of stigmatization, diagnostic overshadowing, incomplete medical examination, insufficient training, and fears experienced by providers and patients emerged. Implications for Practice Increased partnering between physical and mental health practitioners, continuing education, and improving patient-provider communication are key to providing equitable care. Nurses play primary roles in empathizing with patients, advocating for appropriate care and educating others on the dangers of misattributing physical symptoms to psychiatric cause., (© 2023 The Authors. Journal of Psychiatric and Mental Health Nursing published by John Wiley & Sons Ltd.)

The well-documented shortage of nurses and the impact of educational preparation of nurses on patient care outcomes provide a compelling argument for the need to increase the number of registered nurses and to advance their educational preparation. This article describes the application of human capital theory in a creative venture between a health system and a school of nursing that has demonstrated success in addressing these issues. A tuition advancement program was developed to support interested personnel in attaining the associate degree in nursing and to support current RNs in attaining the baccalaureate degree. The venture included support for graduate preparation of nurses interested in becoming faculty.