Substance Use and Attendance Motives of Electronic Dance Music (EDM) Event Attendees: A Survey Study.

EDM event attendees are a high-risk population for substance use and associated adverse effects. The aim of this study was to examine substance use at EDM events, focusing on associations between attendance motives and substance use. Sociodemographic characteristics, event specifics, past-year use, and attendance motives were assessed through an online survey.

Core muscle strength can be reliably measured using a novel isokinetic device: An intra-observer study.

Background: Core strength is an important aspect of physical fitness. A dynamometer was developed to measure isokinetic core muscle strength in multiple planes of motion. Establishing the reliability is needed before it can be used in practice.

A Wilcoxon-Mann-Whitney Test for Latent Variables.

We propose an extension of the Wilcoxon-Mann-Whitney test to compare two groups when the outcome variable is latent. We empirically demonstrate that the test can have superior power properties relative to tests based on Structural Equation Modeling for a variety of settings. In addition, several other advantages of the Wilcoxon-Mann-Whitney test are retained such as robustness to outliers and good small sample performance.

The 4MOTHERS trial of the impact of a mobile money-based intervention on maternal and neonatal health outcomes in Madagascar: study protocol of a cluster-randomized hybrid effectiveness-implementation trial.

Background: Mobile money-a service enabling users to receive, store, and send electronic money using mobile phones-has been widely adopted across low- and middle-income economies to pay for a variety of services, including healthcare. However, evidence on its effects on healthcare access and health outcomes are scarce and the possible implications of using mobile money for financing and payment of maternal healthcare services-which generally require large one-time out-of-pocket payments-have not yet been systematically assessed in low-resource settings. The aim of this study is to determine the impact on health outcomes, cost-effectiveness, feasibility, acceptability, and usefulness of mobile phone-based savings and payment service, the Mobile Maternal Health Wallet (MMHW), for skilled healthcare during pregnancy and delivery among women in Madagascar.

Estimating Structural Equation Models Using James-Stein Type Shrinkage Estimators.

We propose a two-step procedure to estimate structural equation models (SEMs). In a first step, the latent variable is replaced by its conditional expectation given the observed data. This conditional expectation is estimated using a James-Stein type shrinkage estimator.

Semiparametric linear transformation models for indirectly observed outcomes.

We propose a regression framework to analyze outcomes that are indirectly observed via one or multiple proxies. Semiparametric transformation models, including Cox proportional hazards regression, turn out to be well suited to model the association between the covariates and the unobserved outcome. By coupling this regression model to a semiparametric measurement model, we can estimate these associations without requiring calibration data and without imposing strong functional assumptions on the relationship between the unobserved outcome and its proxy.

Expansion of HIV testing in Eswatini: stakeholder perspectives on reaching the first 90.

Achieving the United Nations' 90-90-90 goals has proven challenging in most settings and the ambitious 95-95-95 goals seem even more elusive. However, in Eswatini - a lower-middle-income country in sub-Saharan Africa with the highest HIV prevalence in the world - an estimated 92% of people living with HIV know their status. We conducted 26 in-depth interviews with stakeholders from policy, implementation, donor, local advocacy and academic sectors to elicit the facilitators and inhibitors to HIV testing uptake in Eswatini.

Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping.

Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes.

On the interpretation of the hazard ratio in Cox regression.

We argue that the term "relative risk" should not be used as a synonym for "hazard ratio" and encourage to use the probabilistic index as an alternative effect measure for Cox regression. The probabilistic index is the probability that the event time of an exposed or treated subject exceeds the event time of an unexposed or untreated subject conditional on the other covariates. It arises as a well known and simple transformation of the hazard ratio and nicely reveals the interpretational limitations.

Semiparametric linear transformation models: Effect measures, estimators, and applications.

Semiparametric linear transformation models form a versatile class of regression models with the Cox proportional hazards model being the most well-known member. These models are well studied for right censored outcomes and are typically used in survival analysis. We consider transformation models as a tool for situations with uncensored continuous outcomes where linear regression is not appropriate.

A tutorial on probabilistic index models: Regression models for the effect size P(Y1 < Y2).

The probabilistic index (PI), also known as the probability of superiority or the common language effect size, refers to the probability that the outcome of a randomly selected subject exceeds the outcome of another randomly selected subject, conditional on the covariate values of both subjects. This summary measure has a long history, especially for the 2-sample design where the covariate value typically refers to 1 of 2 treatments. Despite some of the attractive features of the PI, it is often not used beyond the 2-sample design.

High-dimensional prediction of binary outcomes in the presence of between-study heterogeneity.

Many prediction methods have been proposed in the literature, but most of them ignore heterogeneity between populations. Either only data from a single study or population is available for model building and evaluation, or when data from multiple studies make up the training dataset, studies are pooled before model building. As a result, prediction models might perform less than expected when applied to new subjects from new study populations.

Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts.

Purpose: To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate.

Methods And Materials: Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia.

ddpcRquant: threshold determination for single channel droplet digital PCR experiments.

Digital PCR is rapidly gaining interest in the field of molecular biology for absolute quantification of nucleic acids. However, the first generation of platforms still needs careful validation and requires a specific methodology for data analysis to distinguish negative from positive signals by defining a threshold value. The currently described methods to assess droplet digital PCR (ddPCR) are based on an underlying assumption that the fluorescent signal of droplets is normally distributed.

Robust regression methods for real-time polymerase chain reaction.

Current real-time polymerase chain reaction (PCR) data analysis methods implement linear least squares regression methods for primer efficiency estimation based on standard curve dilution series. This method is sensitive to outliers that distort the outcome and are often ignored or removed by the end user. Here, robust regression methods are shown to provide a reliable alternative because they are less affected by outliers and often result in more precise primer efficiency estimators than the linear least squares method.

Variability in interpretation of the electrocardiogram in young athletes: an unrecognized obstacle for electrocardiogram-based screening protocols.

Aims: To assess in young athletes (i) the variability in the percentage of abnormal electrocardiograms (ECGs) using different criteria and (ii) the variability in ECG interpretation among cardiologists and sport physicians.

Methods And Results: Electrocardiograms of 138 athletes were categorized by seven cardiologists according to the original European Society of Cardiology (ESC) criteria by Corrado (C), subsequently modified by Uberoi (U), Marek (M), and the Seattle criteria (S); seven sports physicians only used S criteria. The percentage of abnormal ECGs for each physician was calculated and the percentage of complete agreement was assessed.

Comparison of the abiotic preferences of macroinvertebrates in tropical river basins.

We assessed and compared abiotic preferences of aquatic macroinvertebrates in three river basins located in Ecuador, Ethiopia and Vietnam. Upon using logistic regression models we analyzed the relationship between the probability of occurrence of five macroinvertebrate families, ranging from pollution tolerant to pollution sensitive, (Chironomidae, Baetidae, Hydroptilidae, Libellulidae and Leptophlebiidae) and physical-chemical water quality conditions. Within the investigated physical-chemical ranges, nine out of twenty-five interaction effects were significant.

unifiedWMWqPCR: the unified Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data in R.

Motivation: Recently, De Neve et al. proposed a modification of the Wilcoxon-Mann-Whitney (WMW) test for assessing differential expression based on RT-qPCR data. Their test, referred to as the unified WMW (uWMW) test, incorporates a robust and intuitive normalization and quantifies the probability that the expression from one treatment group exceeds the expression from another treatment group.

The more, the merrier: heterotroph richness stimulates methanotrophic activity.

Although microorganisms coexist in the same environment, it is still unclear how their interaction regulates ecosystem functioning. Using a methanotroph as a model microorganism, we determined how methane oxidation responds to heterotroph diversity. Artificial communities comprising of a methanotroph and increasing heterotroph richness, while holding equal starting cell numbers were assembled.

Dietary arsenic consumption and urine arsenic in an endemic population: response to improvement of drinking water quality in a 2-year consecutive study.

We assessed the association between arsenic intake through water and diet, and arsenic levels in first morning-void urine under variable conditions of water contamination. This was done in a 2-year consecutive study in an endemic population. Exposure of arsenic through water and diet was assessed for participants using arsenic-contaminated water (≥50 μg L(-1)) in a first year (group I) and for participants using water lower in arsenic (<50 μg L(-1)) in the next year (group II).

An extension of the Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data.

Classical approaches for analyzing reverse transcription quantitative polymerase chain reaction (RT-qPCR) data commonly require normalization before assessing differential expression (DE). Normalization often has a substantial effect on the interpretation and validity of the subsequent analysis steps, but at the same time it causes a reduction in variance and introduces dependence among the normalized outcomes. These effects can be substantial, however, they are typically ignored.