Objective: This article describes the National Institute for Occupational Safety and Health's (NIOSH) development of a conceptual framework for worker well-being. While well-being research is growing, there is a need to translate theoretical concepts into practical models for measurement and action. Methods: Multidisciplinary literature reviews informed development of the worker well-being framework and major domains and subdomains. An expert panel helped prioritize constructs for measurement. Results: The framework includes five domains and 20 subdomains and conceptualizes worker well-being as a subjective and objective phenomenon inclusive of experiences both within and beyond work contexts. Conclusion: Well-being is a positive and unifying concept that captures multiple factors that contribute to workers’ health and quality of life. This work lays the foundation for larger well-being measurement efforts and will provide tools for NIOSH partners to help workers flourish.

Objective: This article describes development of the National Institute for Occupational Safety and Health (NIOSH) Worker Well-Being Questionnaire (WellBQ). Methods: The NIOSH WellBQ was developed through literature reviews and expert panel recommendations. We drew from a representative sample of the civilian, noninstitutionalized, US working population to pilot the questionnaire. Psychometric analyses were performed on data from 975 respondents to finalize items and optimize the NIOSH WellBQ's psychometric properties. Results: The final questionnaire consists of 16 scales, 5 indices, and 31 single items across 5 domains: (1) work evaluation and experience; (2) workplace policies and culture; (3) workplace physical environment and safety climate; (4) health status; and (5) home, community, and society (experiences and activities outside of work). The instrument demonstrated adequate reliability and validity. Conclusions: The NIOSH WellBQ is a reliable and valid instrument that comprehensively measures worker well-being.

Background: Disaster citizen science, or the use of scientific principles and methods by “non-professional” scientists or volunteers, may be a promising way to enhance public health emergency preparedness (PHEP) and build community resilience. However, little research has focused on understanding this emerging field and its implications for PHEP. To address research gaps, this paper: (1) assesses the state of disaster citizen science by developing an inventory of disaster citizen science projects; (2) identifies different models of disaster citizen science; and (3) assesses their relevance for PHEP. Methods: We searched the English-language peer-reviewed and grey literature for disaster citizen science projects with no time period specified. Following searches, a team of three reviewers applied inclusion/exclusion criteria that defined eligible disasters and citizen science activities. Reviewers extracted the following elements from each project: project name and description; lead and partner entities; geographic setting; start and end dates; type of disaster; disaster phase; citizen science model; and technologies used. Results: A final set of 209 projects, covering the time period 1953–2017, were included in the inventory. Projects were classified across five citizen science models: distributed or volunteer sensing (n = 19; 9%); contributory (n = 98; 47%); distributed intelligence (n = 52; 25%); collaborative research (n = 32; 15%); and collegial research (n = 8; 4%). Overall, projects were conducted across all disaster phases and most frequently for earthquakes, floods, and hurricanes. Although activities occurred globally, 40% of projects were set in the U.S. Academic, government, technology, and advocacy organizations were the most prevalent lead entities. Although a range of technologies were used, 77% of projects (n = 161) required an internet-connected device. These characteristics varied across citizen science models revealing important implications for applications of disaster citizen science, enhancement of disaster response capabilities, and sustainability of activities over time. Conclusions: By increasing engagement in research, disaster citizen science may empower communities to take collective action, improve system response capabilities, and generate relevant data to mitigate adverse health impacts. The project inventory established a baseline for future research to capitalize on opportunities, address limitations, and help disaster citizen science achieve its potential.

Susceptibility to chemical toxins has not been adequately addressed in risk assessment methodologies. As a result, environmental policies may fail to meet their fundamental goal of protecting the public from harm. This study examines how characterization of risk may change when susceptibility is explicitly considered in policy development; in particular we examine the process used by the U.S. Environmental Protection Agency (EPA) to set a National Ambient Air Quality Standard (NAAQS) for lead. To determine a NAAQS, EPA estimated air lead-related decreases in child neurocognitive function through a combination of multiple data elements including concentration-response (CR) functions. In this article, we present alternative scenarios for determining a lead NAAQS using CR functions developed in populations more susceptible to lead toxicity due to socioeconomic disadvantage. The use of CR functions developed in susceptible groups resulted in cognitive decrements greater than original EPA estimates. EPA’s analysis suggested that a standard level of 0.15 µg/m³ would fulfill decision criteria, but by incorporating susceptibility we found that options for the standard could reasonably be extended to lower levels. The use of data developed in susceptible populations would result in the selection of a more protective NAAQS under the same decision framework applied by EPA. Results are used to frame discussion regarding why cumulative risk assessment methodologies are needed to help inform policy development.

The ability of academic medical centers (AMCs) to fulfill their triple mission of patient care, medical education, and research is increasingly being threatened by rising financial pressures and resource constraints. Many AMCs are, therefore, looking to expand into academic medical systems , increasing their scale through consolidation or affiliation with other health care systems. As clinical operations grow, though, the need for effective governance becomes even more critical to ensure that the business of patient care does not compromise the rest of the triple mission. Multi-AMC systems, a model in which multiple AMCs are governed by a single body, pose a particular challenge in balancing unity with the needs of component AMCs, and therefore offer lessons for designing AMC governance approaches. This article describes the development and application of a set of criteria to evaluate governance options for one multi-AMC system—the University of California (UC) and its five AMCs. Based on a literature review and key informant interviews, the authors identified criteria for evaluating governance approaches (structures and processes), assessed current governance approaches using the criteria, identified alternative governance options, and assessed each option using the identified criteria. The assessment aided UC in streamlining governance operations to enhance their ability to respond efficiently to change and to act collectively. Although designed for UC and a multi-AMC model, the criteria may provide a systematic way for any AMC to assess the strengths and weaknesses of its governance approaches.

The decline of the traditional U.S. shopping mall and a focus on more consumer- centered care have created an opportunity for “medical malls”. Medical malls are defined as former retail spaces repurposed for healthcare tenants or mixed-use medical/retail facilities.