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Traditional lecture-centered classrooms are being challenged by active learning hybrid curricula. In small graduate programs with limited resources and primarily non-traditional students, exploring how to use online technology to optimize the role of the professor in the classroom is imperative. However, very little research exists in this area. In this study, the use of short statistical computing video tutorials was explored using a pilot study in a small Public Health Program at the University of New Mexico. The videos were implemented in two Master's-level biostatistics courses and student perception of the videos was assessed using quantitative surveys and qualitative focus groups. The results from 16 survey respondents and 12 focus group participants are presented across the two courses. Viewing rates for the videos were high, with 15 out of 16 respondents reporting usually or always viewing the videos. Overall perception of the videos as a learning tool was positive, with 14 out of 16 respondents agreeing that the videos offer advantages to them. Two prominent themes emerged in our analysis: (1) the usability and convenience of the videos and (2) the deeper learning facilitated by having the videos available.We conclude that the short video tutorials were a useful learning tool in our study population.

Well-constructed epidemiologic studies provide information about environmental risks and inform interventions and public health policies. Using focus groups, this pilot project examined the attitudes, beliefs, and concerns of rural-dwelling adults toward participating in a longitudinal cohort study. Focus group participants who were 40 years or older, residents in the Grants Mining District, and had no previous diagnosis of diabetes (except gestational diabetes) were recruited from a local physician's office in the Grants Mining District. Participants provided insight into local health concerns, willingness to participate in long-term research and to provide biological specimens, and consent form expectations. For this population, the uranium mining legacy in the Grants Mining District is a contextual factor that can be addressed via community engagement and in the study design to minimize misinterpretation or bias and to maximize the ability to detect causal risk factors for health outcomes., Introduction The three core public health functions (assessment, policy, and assurance) rest upon the foundation of the public health sciences of epidemiology and biostatistics. Well-constructed epidemiologic studies provide information about [...]

We develop a novel approach for quantifying small effects in regression models. Our method is based on variation in the mean function, in contrast to methods that focus on regression coefficients. Our idea applies in diverse settings such as testing for a negligible trend and quantifying differences in regression functions across strata. Straightforward Bayesian methods are proposed for inference. Four examples are used to illustrate the ideas. [ABSTRACT FROM AUTHOR]

Objective: While prenatal 3D ultrasonography results in improved diagnostic accuracy, no data are available on biometric assessment of the fetal frontal lobe. This study was designed to assess feasibility of a standardized approach to biometric measurement of the fetal frontal lobe and to construct frontal lobe growth trajectories throughout gestation., Study Design: A sonographic 3D volume set was obtained and measured in 101 patients between 16.1 and 33.7 gestational weeks. Measurements were obtained by two independent raters. To model the relationship between gestational age and each frontal lobe measurement, flexible linear regression models were fit using penalized regression splines., Results: The sample contained an ethnically diverse population (7.9% Native Americans, 45.5% Hispanic/Latina). There was high inter-rater reliability (correlation coefficients: 0.95, 1.0, and 0.87 for frontal lobe length, width, and height; p-values < 0.001). Graphs of the growth trajectories and corresponding percentiles were estimated as a function of gestational age. The estimated rates of frontal lobe growth were 0.096 cm/week, 0.247 cm/week, and 0.111 cm/week for length, width, and height., Conclusion: To our knowledge, this is the first study to examine fetal frontal lobe growth trajectories through 3D prenatal ultrasound examination. Such normative data will allow for future prenatal evaluation of a particular disease state by 3D ultrasound imaging.

Introduction: The regulatory and policy environment surrounding air quality management warrants new types of epidemiological evidence. Whereas air pollution epidemiology has typically informed previous policies with estimates of exposure-response relationships between pollution and health outcomes, new types of evidence can inform current debates about the actual health impacts of air quality regulations. Directly evaluating specific regulatory strategies is distinct from and complements estimating exposure-response relationships; increased emphasis on assessing the effectiveness of well-defined regulatory interventions will enhance the evidence supporting policy decisions. The goal of this report is to provide new analytic perspectives and statistical methods for what we refer to as "direct"-accountability assessment of the effectiveness of specific air quality regulatory interventions. Toward this end, we sharpened many of the distinctions surrounding accountability assessment initially raised by the HEI Accountability Working Group (2003) through discussion, development, and deployment of statistical methods for drawing causal inferences from observational data. The methods and analyses presented here are unified in their focus on anchoring accountability assessment to the estimation of the causal consequences of well-defined actions or interventions. These analytic perspectives are discussed in the context of two direct-accountability case studies pertaining to four different links in the so-called chain of accountability, the related series of events leading from the intervention to the expected outcomes (see Preface; HEI Accountability Working Group 2003)., Methods: The statistical methods described in this report consist of both established methods for drawing causal inferences from observational data and newly developed methods for assessing causal accountability. We have sharpened the analytic distinctions between studies that directly evaluated the effectiveness of specific policies and those that estimated exposure-response relationships between pollution and health. We emphasized how a potential-outcomes paradigm for causal inference can elevate policy debates by means of more direct evidence of the extent to which complex regulatory interventions affect pollution and health outcomes. We also outlined the potential-outcomes perspective and promoted its use as a means to frame observational studies as approximate randomized experiments. Our newly developed methods for assessing causal accountability draw on propensity scores, principal stratification, causal mediation analysis, spatial hierarchical models, and Bayesian estimation. The first case study made use of health outcomes among approximately four million Medicare beneficiaries living in the Western United States to estimate the causal health impacts of areas designated as being in nonattainment for particulate matter ≤10 μm in aerodynamic diameter (PM10*) according to the 1987 National Ambient Air Quality Standards (NAAQS). The second case study focused on developing and testing our new, advanced methodology for multipollutant accountability assessment by examining the extent to which sulfur dioxide (SO2) scrubbers on coal-fired power plants causally affect emissions of SO2, nitrogen oxides (NO(x)), and carbon dioxide (CO2) as well as the extent to which emissions reductions mediate the causal effect of a scrubber on ambient concentrations of PM2.5. Both case studies were anchored in our compilation of national, linked data on ambient air quality monitoring, weather, population demographics, Medicare hospitalization and mortality outcomes, continuous-emissions monitoring for electricity-generating units (EGUs) in power plants, and a variety of regulatory control interventions. The resulting database has unprecedented accuracy and granularity for conducting the types of accountability assessments presented in this report. A key component of our work was the creation of tools to help distribute our linked database and to facilitate reproducible research., Results: In the first case study, we focused on illustrating the most fundamental features of a causal-inference perspective on direct-accountability assessment. The results indicated that all-cause Medicare mortality and respiratory-related hospitalization rates were causally reduced in areas designated as nonattainment for PM10 during 1990 to 1995 compared with the rates that would have occurred without the designation. In the second case study, which examined power-plant emissions and illustrated our newly developed statistical methods, the results indicated that the presence of an SO2 scrubber causally reduced ambient PM2.5 and that this reduction was mediated almost entirely through causal reductions in SO2 emissions. The results were interpreted in light of the well-documented relationships between scrubbers, power-plant emissions, and PM2.5., Conclusion: By grounding accountability research in a potential-outcomes framework and applying our new methods to our collection of national data sets, we were able to provide additional sound evidence of the health effects of long-term, large-scale air quality regulations. This additional, rigorous evidence of the causal effects of well-defined actions augments the existing body of research and ensures that the highest-level epidemiological evidence will continue to support regulatory policies. Ultimately, our research contributed to the evidence available to support to the U.S. Environmental Protection Agency (U.S. EPA) and other stakeholders for incorporating health outcomes research into policy development.