Frequency of Black and American Indian/Alaskan Native US Residents Screened for Firearm Access.

Objective: This study evaluates Black and AIAN individuals' self-reported history of being screened for firearm access by healthcare providers, and identifies factors that influence screening.

Methods: A cross-sectional, nationally representative survey of included 3015 Black and 527 AIAN adults in the US. Participants were recruited via probability-based sampling.

"Did I do the right thing?" Nurses' experiences of caring for victims of child maltreatment: A qualitative study.

Purpose: The purpose of this study is to explore and gain insight into pediatric nurses' lived experiences in caring for children who experienced maltreatment.

Design And Method: A qualitative descriptive phenomenological approach using Giorgi's method was used to support the inquiry of this study. Participants were recruited through the Society of Pediatric Nurses (SPN) and the International Association of Forensic Nursing (IAFN).

An equity and environmental justice assessment of anti-science actions during the Trump administration.

In the United States, science shapes federal health and safety protections, but political officials can and do politicize federal science and science-based safeguards. Many presidential administrations have politicized science, but under the administration of President Trump, these attacks on science-such as buried research, censored scientists, halted data collection-increased in number to unprecedented levels. Underserved communities bore the brunt of the harms.

The disinformation playbook: how industry manipulates the science-policy process-and how to restore scientific integrity.

For decades, corporate undermining of scientific consensus has eroded the scientific process worldwide. Guardrails for protecting science-informed processes, from peer review to regulatory decision making, have suffered sustained attacks, damaging public trust in the scientific enterprise and its aim to serve the public good. Government efforts to address corporate attacks have been inadequate.

Perceived losses of scientific integrity under the Trump administration: A survey of federal scientists.

President Trump and his administration have been regarded by news outlets and scholars as one of the most hostile administrations towards scientists and their work. However, no study to-date has empirically measured how federal scientists perceive the Trump administration with respect to their scientific work. In 2018, we distributed a survey to over 63,000 federal scientists from 16 federal agencies to assess their perception of scientific integrity.

Hazardous air pollutant emissions implications under 2018 guidance on U.S. Clean Air Act requirements for major sources.

On January 25, 2018, the United States Environmental Protection Agency withdrew a 1995 policy that mandates the use of maximum achievable control technology (MACT) to regulate emissions from major sources of hazardous air pollutants (HAPs), a category of toxic chemicals that may be carcinogenic, mutagenic, or cause other adverse health effects. To better understand the implications and scope of the change in regulatory guidance for HAP emissions of major sources that may reclassify as area sources, the increase in emissions that could legally occur under the new policy is assessed here. Based on facility-level data from a 2014 HAP national emissions inventory, it is estimated that 70% of major sources of HAPs qualify for reclassification as area sources, which could result in a maximum of 35,030 tons per year (tpy) of additional HAP emissions if all sources successfully reclassified.

Defending the scientific integrity of conservation-policy processes.

Government agencies faced with politically controversial decisions often discount or ignore scientific information, whether from agency staff or nongovernmental scientists. Recent developments in scientific integrity (the ability to perform, use, communicate, and publish science free from censorship or political interference) in Canada, Australia, and the United States demonstrate a similar trajectory. A perceived increase in scientific-integrity abuses provokes concerted pressure by the scientific community, leading to efforts to improve scientific-integrity protections under a new administration.

Characterization of Ambient Air Pollution Measurement Error in a Time-Series Health Study using a Geostatistical Simulation Approach.

In recent years, geostatistical modeling has been used to inform air pollution health studies. In this study, distributions of daily ambient concentrations were modeled over space and time for 12 air pollutants. Simulated pollutant fields were produced for a 6-year time period over the 20-county metropolitan Atlanta area using the Stanford Geostatistical Modeling Software (SGeMS).

Effects of ambient air pollution measurement error on health effect estimates in time-series studies: a simulation-based analysis.

In this study, we investigated bias caused by spatial variability and spatial heterogeneity in outdoor air-pollutant concentrations, instrument imprecision, and choice of daily pollutant metric on risk ratio (RR) estimates obtained from a Poisson time-series analysis. Daily concentrations for 12 pollutants were simulated for Atlanta, Georgia, at 5 km resolution during a 6-year period. Viewing these as being representative of the true concentrations, a population-level pollutant health effect (RR) was specified, and daily counts of health events were simulated.

Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies.

Background: Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.

Ambient air pollutant measurement error: characterization and impacts in a time-series epidemiologic study in Atlanta.

In time-series studies of ambient air pollution and health in large urban areas, measurement errors associated with instrument precision and spatial variability vary widely across pollutants. In this paper, we characterize these errors for selected air pollutants and estimate their impacts on epidemiologic results from an ongoing study of air pollution and emergency department visits in Atlanta. Error was modeled for daily measures of 12 air pollutants using collocated monitor data to characterize instrument precision and data from multiple study area monitors to estimate population-weighted spatial variance.