The Effect of Online Training on Teams

Many organizations recognize the importance of utilizing teams to accomplish work (Chuboda et al., 2005; Devine et al., 1999; Ilgen, 1999; Martins et al., 2004). As technology has advanced, many of these organizations have recently become more reliant on virtual project work, which allows work teams to communicate across geographical distances (Driskell et al., 2003). Considering the growing prevalence of virtual teams in organizations, more needs to be known about how to facilitate virtual team effectiveness. In addition, the increased use of teams in organizations has identified and created the need for team training (Ilgen, 1999). Creating a training environment where the appropriate knowledge and skills transfer to a team should be taken into consideration for team performance (Marks et al., 2001). However, the literature provides inconclusive evidence on the effectiveness of the virtual team’s training environment. The goal of the current study is to add to existing knowledge regarding training and virtual teams. It is expected, based on previous research, that virtual teams who receive online training will yield the best performance results, while virtual teams who receive in-person training will yield the worst performance results. Sixty-four undergraduate students from Minnesota State University, Mankato participated in the study. Participants were placed in two person teams and were trained either on-line using web-based conferencing software or were trained in-person. Team members collaborated either virtually or face to-face. Results of the research will be discussed along with implications and future directions

Superbugs Versus Outsourced Cleaners: Employment Arrangements and the Spread of Health Care-Associated Infections

On any given day, about one in 25 hospital patients in the United States has a health care–associated infection (HAI) that the patient contracts as a direct result of his or her treatment. Fortunately, the spread of most HAIs can be halted through proper disinfection of surfaces and equipment. Consequently, cleaners—“environmental services” (EVS) in hospital parlance—must take on the important task of defending hospital patients (as well as staff and the broader community) from the spread of HAIs. Despite the importance of this task, hospitals frequently outsource this function, increasing the likelihood that these workers are under-rewarded, undertrained, and detached from the organization and the rest of the care team. As a result, the outsourcing of EVS workers could have the unintended consequence of increasing the incidence of HAIs. The authors demonstrate this relationship empirically, finding support for their theory by using a self-constructed data set that marries infection data to structural, organizational, and workforce features of California’s general acute care hospitals. The study thus advances the literature on nonstandard work arrangements—outsourcing in particular—while sounding a cautionary note to hospital administrators and health care policymakers

Deep splitting method for parabolic PDEs

In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational graph for each of the subproblems is comparatively small, the approach can handle extremely high-dimensional PDEs. We test the method on different examples from physics, stochastic control and mathematical finance. In all cases, it yields very good results in up to 10,000 dimensions with short run times.Comment: 25 page

Quasi-experimental study designs series –Paper 9: Collecting Data from Quasi-Experimental Studies

Objective: To identify variables that must be coded when synthesizing primary studies that use quasi-experimental designs.  Study Design and Setting: All quasi-experimental (QE) designs.  Results: When designing a systematic review of QE studies potential sources of heterogeneity – both theory-based and methodological – must be identified. We outline key components of inclusion criteria for syntheses of quasi-experimental studies. We provide recommendations for coding content-relevant and methodological variables, and outlined the distinction between bivariate effect sizes and partial (i.e., adjusted) effect sizes. Designs used and controls employed are viewed as of greatest importance. Potential sources of bias and confounding are also addressed.  Conclusion: Careful consideration must be given to inclusion criteria and the coding of theoretical and methodological variables during the design phase of a synthesis of quasi-experimental studies. The success of the meta-regression analysis relies on the data available to the meta-analyst. Omission of critical moderator variables (i.e., effect modifiers) will undermine the conclusions of a meta-analysis

Quasi-experimental study designs series – Paper 10: Synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges

Objective: To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs), and to provide a statistical model for use in analysis. Study Design and Setting: We drew on the literatures of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of quasi-experiments, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Results: Biases, confounding, design complexities and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Conclusion: Meta-analyses of quasi-experiments provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences

Quasi-experimental study designs series-paper 6: risk of bias assessment.

OBJECTIVES: Rigorous and transparent bias assessment is a core component of high-quality systematic reviews. We assess modifications to existing risk of bias approaches to incorporate rigorous quasi-experimental approaches with selection on unobservables. These are nonrandomized studies using design-based approaches to control for unobservable sources of confounding such as difference studies, instrumental variables, interrupted time series, natural experiments, and regression-discontinuity designs. STUDY DESIGN AND SETTING: We review existing risk of bias tools. Drawing on these tools, we present domains of bias and suggest directions for evaluation questions. RESULTS: The review suggests that existing risk of bias tools provide, to different degrees, incomplete transparent criteria to assess the validity of these designs. The paper then presents an approach to evaluating the internal validity of quasi-experiments with selection on unobservables. CONCLUSION: We conclude that tools for nonrandomized studies of interventions need to be further developed to incorporate evaluation questions for quasi-experiments with selection on unobservables

Variations in the patients’ hospital care experience by states’ strategy for Medicaid expansion: 2009-2013

Our investigation evaluates the extent of differences in the patient’s hospital experience due to variations among state strategies to adopt, or not adopt, their Medicaid plans to the 2010 ACA legislation. Using ten HCAHPS measures, we analyze patient hospital experience data for the 2009 - 2013 period for all 50 states and the District of Columbia grouped by those states that (1) did not expand, (2) expanded Medicaid through Section 1115 waivers, (3) expanders early, and (4) expanded Medicaid concurrent with the new ACA legislation. Our findings reveal that those states that opted out of Medicaid expansion typically started with higher patient experience scores in 2009 on all 10 HCAHPS hospital measures and maintained their higher scores levels for all five years over the other three state expansion strategies for most measures. While states that were early expanders and those that expanded concurrent with the ACA implementation generally show higher growth rates over the five-year period for most HCAHPS measures when compared to states that opted out of the Medicaid expansion, our multivariate results indicate that their rates of growth were not statistically superior to those states that opted out of the expansion. We conclude that while there have been concerns that the patients in opt-out states would experience lower levels of satisfaction from their state’s actions, the patient experience scores in these states show that they perform better or as well as those states that expanded early, expanded under waivers, and expanded with the implementation of the ACA legislation

ARGUMENTOS DA DECISÃO DE VOTO DE DEPUTADOS DURANTE A VOTAÇÃO DO IMPEACHMENT

The advances in techniques for analyzing unstructured data can help to better understand the positioning and votes of politicians who represent a population. This article analyses the underlying semantic relationship between the themes present in the arguments for the voting decision of parliamentarians of different political parties. For this, it uses discourse data from all the deputies during the impeachment voting, which took place in 2015. Weiss's (1983) perspective on the decision-making of politicians, and Festinger's (1957) theory of cognitive dissonance were used as the theoretical basis for the analysis. Additionally, using the technique of LSA (Latent semantic analysis) — a text mining technique based on matrix decomposition¬¬¬¬ — it aims to contribute to the analyses by bringing results related to the main associated terms, and the use of certain words in the political context. It was found that for the case presented, the deputies' discourse is not an element that enables the different voting groups to be distinguished, indicating that in order to understand the position of a politician, and better choose their representative, citizens need to go beyond the politicians’ discourse.El avance de técnicas para análisis de datos no estructurados puede ayudar a comprender mejor el posicionamiento y los votos de los políticos que representan una población. El objetivo del presente artículo es analizar la relación semántica latente de las temáticas presentes en los argumentos de la decisión de voto de los parlamentarios de diferentes partidos políticos. Para esto, se utilizaron datos de discurso de todos los diputados durante la votación del impeachment, ocurrida en 2015. En ese sentido, se utilizó como base teórica para la realización de los análisis la perspectiva de Weiss (1983) sobre la toma de decisión de políticos y la teoría de la disonancia cognitiva de Festinger (1957). Además, a partir del uso de la técnica LSA (Latent semantic analysis), técnica de minería de texto basada en descomposición matricial, se buscó contribuir con los análisis al traer resultados relacionados a los principales términos asociados y uso de determinadas palabras en el contexto político. Como resultados, se constató que, para el caso presentado, el discurso de los diputados no es elemento que permite separar a los diferentes grupos votantes, lo que indica que para comprender la posición de un político y elegir mejor su representante, los ciudadanos deben ir más allá de su discurso.O avanço de técnicas para análise de dados não estruturados pode auxiliar a compreender melhor o posicionamento e os votos dos políticos que representam uma população. O objetivo do presente artigo é analisar a relação semântica latente das temáticas presentes nos argumentos da decisão de voto dos parlamentares de diferentes partidos políticos. Para tal, foram utilizados dados de discurso de todos os deputados durante a votação do impeachment, ocorrida em 2015. Nesse sentido, utilizaram-se como base teórica para a realização das análises a perspectiva de Weiss (1983) sobre a tomada de decisão de políticos e a teoria da dissonância cognitiva de Festinger (1957). Adicionalmente, a partir do uso da técnica LSA (Latent semantic analysis), técnica de mineração de texto baseada em decomposição matricial, buscou-se contribuir com as análises ao trazer resultados relacionados aos principais termos associados e uso de determinadas palavras no contexto político. Como resultados, verificou-se que, para o caso apresentado, o discurso dos deputados não é um elemento que permite separar os diferentes grupos votantes, o que indica que, para compreender a posição de um político e escolher melhor seu representante, os cidadãos precisam ir além do seu discurso

Impact of hospital characteristics on patients’ experience of hospital care: Evidence from 14 states, 2009-2011

This paper uses patient responses to the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey for three years (2009-2011) from 1,333 acute-care hospitals in fourteen states to analyze patterns in 10 hospital-reported patient experience-of-care scores by 29 characteristics classified as: patient characteristics, payer source, patient severity, hospital characteristics, hospital operations, and market characteristics. We also evaluate how scores have changed over the three-year period. We find significant differences in patient experience-of-care scores by hospital characteristics for 250 out of 290 HCAHPS-hospital characteristic combinations measured. We find fewer significant differences in changes in scores from 2009-2011 (135 out of 290), with hospitals categorized as high scoring also reporting consistently greater improvement. We conclude that patient experience-of-care scores vary by hospital characteristics, although improvements in scores show less variety by hospital categorization