Dangerous Speech: A Cross-Cultural Study of Dehumanization and Revenge

Dehumanization is routinely invoked in social science and law as the primary factor in explaining how propaganda encourages support for, or participation in, violence against targeted outgroups. Yet the primacy of dehumanization is increasingly challenged by the apparent influence of revenge on collective violence. This study examines critically how various propaganda influence audiences. Although previous research stresses the dangers of dehumanizing propaganda, a recently published study found that only revenge propaganda significantly lowered outgroup empathy. Given the importance of these findings for law and the behavioral sciences, this research augments that recent study with two additional samples that were culturally distinct from the prior findings, showing again that only revenge propaganda was significant. To explore this effect further, we also conducted a facial electromyography (fEMG) among a small set of participants, finding that revenge triggered significantly stronger negative emotions against outgroups than dehumanization

The power prior: theory and applications

The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A to Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Prequentist properties of power priors in posterior inference are established and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials

The Association between Drought Exposure and Respiratory-Related Mortality in the United States from 2000 to 2018

Climate change has brought increasing attention to the assessment of health risks associated with climate and extreme events. Drought is a complex climate phenomenon that has been increasing in frequency and severity both locally and globally due to climate change. However, the health risks of drought are often overlooked, especially in places such as the United States, as the pathways to health impacts are complex and indirect. This study aims to conduct a comprehensive assessment of the effects of monthly drought exposure on respiratory mortality for NOAA climate regions in the United States from 2000 to 2018. A two-stage model was applied to estimate the location-specific and overall effects of respiratory risk associated with two different drought indices over two timescales (the US Drought Monitor and the 6-month and 12-month Evaporative Demand Drought Index). During moderate and severe drought exposure, respiratory mortality risk ratio in the general population increased up to 6.0% (95% Cr: 4.8 to 7.2) in the Northeast, 9.0% (95% Cr: 4.9 to 13.3) in the Northern Rockies and Plains, 5.2% (95% Cr: 3.9 to 6.5) in the Ohio Valley, 3.5% (95% Cr: 1.9 to 5.0) in the Southeast, and 15.9% (95% Cr: 10.8 to 20.4) in the Upper Midwest. Our results showed that age, ethnicity, sex (both male and female), and urbanicity (both metro and non-metro) resulted in more affected population subgroups in certain climate regions. The magnitude and direction of respiratory risk ratio differed across NOAA climate regions. These results demonstrate a need for policymakers and communities to develop more effective strategies to mitigate the effects of drought across regions

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations

Background: Exposure to air pollutants is known to exacerbate asthma, with prior studies focused on associations between single pollutant exposure and asthma exacerbations. As air pollutants often exist as a complex mixture, there is a gap in understanding the association between complex air pollutant mixtures and asthma exacerbations. We evaluated the association between the air pollutant mixture (52 pollutants) and pediatric asthma exacerbations. Method: This study focused on children (age ≤ 19 years) who lived in Douglas County, Nebraska, during 2016–2019. A seasonal- scale joint association between the outdoor air pollutant mixture adjusting for potential confounders (temperature, precipitation, wind speed, and wind direction) in relation to pediatric asthma exacerbation-related emergency department (ED) visits was evaluated using the generalized weighted quantile sum (qWQS) regression with repeated holdout validation. Results: We observed associations between air pollutant mixture and pediatric asthma exacerbations during spring (lagged by 5 days), summer (lag 0–5 days), and fall (lag 1–3 days) seasons. The estimate of the joint outdoor air pollutant mixture effect was higher during the summer season (adjusted-βWQS = 1.11, 95% confidence interval [CI]: 0.66, 1.55), followed by spring (adjusted-βWQS = 0.40, 95% CI: 0.16, 0.62) and fall (adjusted-βWQS = 0.20, 95% CI: 0.06, 0.33) seasons. Among the air pollutants, PM2.5, pollen, and mold contributed higher weight to the air pollutant mixture. Conclusion: There were associations between outdoor air pollutant mixture and pediatric asthma exacerbations during the spring, summer, and fall seasons. Among the 52 outdoor air pollutant metrics investigated, PM2.5, pollen (sycamore, grass, cedar), and mold (Helminthosporium, Peronospora, and Erysiphe) contributed the highest weight to the air pollutant mixture

New Methods and Innovations in Network Meta Regression for Ordinal Response Outcomes with Applications

In this dissertation research, we develop models and carry out statistical inference for meta ordinal outcomes under both frequentist and Bayesian frameworks. Specifically, we develop new regression models based on aggregate trial-level and treatment-level covariates for the underlying cut-off points of the ordinal outcomes as well as for the variances of the random effects to capture heterogeneity across trials. In the frequentist approach, we develop Pearson residuals to detect outlying trials and construct an invariant test statistic to evaluate goodness-of-fit. We also develop a new computational algorithm to compute ranking probabilities to rank multiple treatments. Under the Bayesian framework, we examine the importance of links in fitting ordinal responses in the middle categories. The novel theoretical development allows for incorporating a variety of links regardless of symmetry or asymmetry. We develop an efficient Markov chain Monte Carlo sampling algorithm under different links using latent variables for Bayesian computation. To incorporate high-dimensional random effects for multi-arm trials, we develop a different data augmentation strategy via the Polya-Gamma mixture distribution, under the logit link. We develop another efficient computational algorithm to deal with high-dimensional random effects and it allows for more flexible modeling strategy of variances for the random effects. We then develop Bayesian model comparison measures and model diagnostic tools to facilitate the choices of links, the assessment of goodness-of-fit, and the determination of outlying trials. A case study demonstrating the proposed methodology is conducted using aggregate ordinal outcome data to assess the effectiveness of different treatments in treating Crohn\u27s Disease

Prediction of Stability during Walking at Simulated Ship’s Rolling Motion Using Accelerometers

Due to a ship’s extreme motion, there is a risk of injuries and accidents as people may become unbalanced and be injured or fall from the ship. Thus, individuals must adjust their movements when walking in an unstable environment to avoid falling or losing balance. A person’s ability to control their center of mass (COM) during lateral motion is critical to maintaining balance when walking. Dynamic balancing is also crucial to maintain stability while walking. The margin of stability (MOS) is used to define this dynamic balancing. This study aimed to develop a model for predicting balance control and stability in walking on ships by estimating the peak COM excursion and MOS variability using accelerometers. We recruited 30 healthy individuals for this study. During the experiment, participants walked for two minutes at self-selected speeds, and we used a computer-assisted rehabilitation environment (CAREN) system to simulate the roll motion. The proposed prediction models in this study successfully predicted the peak COM excursion and MOS variability. This study may be used to protect and save seafarers or passengers by assessing the risk of balance loss

Role of social determinants of health in differential respiratory exposure and health outcomes among children

Abstract Background Attributes defining the Social Determinants of Health (SDoH) are associated with disproportionate exposures to environmental hazards and differential health outcomes among communities. The dynamics between SDoH, disproportionate environmental exposures, and differential health outcomes are often specific to micro-geographic areas. Methods This study focused on children less than 20 years of age who lived in Douglas County, Nebraska, during 2016–2019. To assess the role of SDoH in differential exposures, we evaluated the association between SDoH metrics and criteria pollutant concentrations and the association between SDoH and pediatric asthma exacerbations to quantify the role of SDoH in differential pediatric asthma outcomes. The Bayesian Poisson regression model with spatial random effects was used to evaluate associations. Results We identified significant positive associations between the annual mean concentration of criteria pollutants (carbon monoxide, particulate matter2.5, nitrogen dioxide, sulfur dioxide) with race (Non-Hispanic Black and Hispanic/Latino), financial stability, and literacy. Additionally, there were significant positive associations between higher rates of pediatric asthma emergency department visits and neighborhoods with more Non-Hispanic Black children, children without health insurance coverage, and households without access to a vehicle. Conclusions Non-Hispanic Black and Hispanic/Latino children living in Douglas County, NE experience disproportionately higher exposure to criteria pollutant concentrations. Additionally, higher rates of asthma exacerbations among Non-Hispanic Black children could be due to reduced access to respiratory care that is potentially the result of financial instability and vehicle access. These results could inform city planners and health care providers to mitigate respiratory risks among these higher at-risk populations

Wearable Sensor-Based Prediction Model of Timed up and Go Test in Older Adults

The Timed Up and Go (TUG) test has been frequently used to assess the risk of falls in older adults because it is an easy, fast, and simple method of examining functional mobility and balance without special equipment. The purpose of this study is to develop a model that predicts the TUG test using three-dimensional acceleration data collected from wearable sensors during normal walking. We recruited 37 older adults for an outdoor walking task, and seven inertial measurement unit (IMU)-based sensors were attached to each participant. The elastic net and ridge regression methods were used to reduce gait feature sets and build a predictive model. The proposed predictive model reliably estimated the participants’ TUG scores with a small margin of prediction errors. Although the prediction accuracies with two foot-sensors were slightly better than those of other configurations (e.g., MAPE: foot (0.865 s) > foot and pelvis (0.918 s) > pelvis (0.921 s)), we recommend the use of a single IMU sensor at the pelvis since it would provide wearing comfort while avoiding the disturbance of daily activities. The proposed predictive model can enable clinicians to assess older adults’ fall risks remotely through the evaluation of the TUG score during their daily walking

Role of Cerebral Embolic Protection Devices in Patients Undergoing Transcatheter Aortic Valve Replacement: An Updated Meta‐Analysis

Background Cerebral embolic protection devices (CEPD) capture embolic material in an attempt to reduce ischemic brain injury during transcatheter aortic valve replacement. Prior reports have indicated mixed results regarding the benefits of these devices. With new data emerging, we performed an updated meta‐analysis examining the effect of CEPD during transcatheter aortic valve replacement on various clinical, neurological, and safety parameters. Methods and Results A comprehensive review of electronic databases was performed comparing CEPD and no‐CEPD in transcatheter aortic valve replacement. Primary clinical outcome was all‐cause stroke. Secondary clinical outcomes were disabling stroke and all‐cause mortality. Neurological outcomes included worsening of the National Institutes of Health Stroke Scale score, Montreal Cognitive Assessment score from baseline at discharge, presence of new ischemic lesions, and total lesion volume on neuroimaging. Safety outcomes included major or minor vascular complications and stage 2 or 3 acute kidney injury. Seven randomized controlled trials with 4016 patients met the inclusion criteria. There was no statistically significant difference in the primary clinical outcome of all‐cause stroke; secondary clinical outcomes of disabling stroke, all‐cause mortality, neurological outcomes of National Institutes of Health Stroke Scale score worsening, Montreal Cognitive Assessment worsening, presence of new ischemic lesions, or total lesion volume on diffusion‐weighted magnetic resonance imaging between CEPD versus control groups. There was no statistically significant difference in major or minor vascular complications or stage 2 or 3 acute kidney injury between the groups. Conclusions The use of CEPD in transcatheter aortic valve replacement was not associated with a statistically significant reduction in the risk of clinical, neurological, and safety outcomes

Multivessel Versus Culprit-Only Revascularization in STEMI and Multivessel Coronary Artery Disease: Meta-Analysis of Randomized Trials

OBJECTIVES: The goal of this systematic review and meta-analysis was to provide a comprehensive evaluation of contemporary randomized trials addressing the efficacy and safety of multivessel versus culprit vessel-only percutaneous coronary intervention (PCI) among patients presenting with ST-segment elevation myocardial infarction and multivessel coronary artery disease. BACKGROUND: Multivessel coronary artery disease is present in about one-half of patients with ST-segment elevation myocardial infarction. Randomized controlled trials comparing multivessel and culprit vessel-only PCI produced conflicting results regarding the benefits of a multivessel PCI strategy. METHODS: A comprehensive search for published randomized controlled trials comparing multivessel PCI with culprit vessel-only PCI was conducted on ClinicalTrials.gov, PubMed, Web of Science, EBSCO Services, the Cochrane Central Register of Controlled Trials, Google Scholar, and scientific conference sessions from inception to September 15, 2019. A meta-analysis was performed using a random-effects model to calculate the risk ratio (RR) and 95% confidence interval (CI). Primary efficacy outcomes were all-cause mortality and reinfarction. RESULTS: Ten randomized controlled trials were included, representing 7,030 patients: 3,426 underwent multivessel PCI and 3,604 received culprit vessel-only PCI. Compared with culprit vessel-only PCI, multivessel PCI was associated with no significant difference in all-cause mortality (RR: 0.85; 95% CI: 0.68 to 1.05) and lower risk for reinfarction (RR: 0.69; 95% CI: 0.50 to 0.95), cardiovascular mortality (RR: 0.71; 95% CI: 0.50 to 1.00), and repeat revascularization (RR: 0.34; 95% CI: 0.25 to 0.44). Major bleeding (RR: 0.92; 95% CI: 0.50 to 1.67), stroke (RR: 1.15; 95% CI: 0.65 to 2.01), and contrast-induced nephropathy (RR: 1.25; 95% CI: 0.80 to 1.95) were not significantly different between the 2 groups. CONCLUSIONS: Multivessel PCI was associated with a lower risk for reinfarction, without any difference in all-cause mortality, compared with culprit vessel-only PCI in patients with ST-segment elevation myocardial infarction