A multi-site pilot test study to measure safety climate in the university work setting

Next to leisure, sport, and household activities, the most common activity resulting in medically consulted injuries and poisonings in the United States is work, with an estimated 4 million workplace related episodes reported in 2008 (U.S. Department of Health and Human Services, 2009). To address the risks inherent to various occupations, risk management programs are typically put in place that include worker training, engineering controls, and personal protective equipment. Recent studies have shown that such interventions alone are insufficient to adequately manage workplace risks, and that the climate in which the workers and safety program exist (known as the "safety climate") is an equally important consideration. The organizational safety climate is so important that many studies have focused on developing means of measuring it in various work settings. While safety climate studies have been reported for several industrial settings, published studies on assessing safety climate in the university work setting are largely absent. Universities are particularly unique workplaces because of the potential exposure to a diversity of agents representing both acute and chronic risks. Universities are also unique because readily detectable health and safety outcomes are relatively rare. The ability to measure safety climate in a work setting with rarely observed systemic outcome measures could serve as a powerful means of measure for the evaluation of safety risk management programs. ^ The goal of this research study was the development of a survey tool to measure safety climate specifically in the university work setting. The use of a standardized tool also allows for comparisons among universities throughout the United States. A specific study objective was accomplished to quantitatively assess safety climate at five universities across the United States. At five universities, 971 participants completed an online questionnaire to measure the safety climate. The average safety climate score across the five universities was 3.92 on a scale of 1 to 5, with 5 indicating very high perceptions of safety at these universities. The two lowest overall dimensions of university safety climate were "acknowledgement of safety performance" and "department and supervisor's safety commitment". The results underscore how the perception of safety climate is significantly influenced at the local level. A second study objective regarding evaluating the reliability and validity of the safety climate questionnaire was accomplished. A third objective fulfilled was to provide executive summaries resulting from the questionnaire to the participating universities' health & safety professionals and collect feedback on usefulness, relevance and perceived accuracy. Overall, the professionals found the survey and results to be very useful, relevant and accurate. Finally, the safety climate questionnaire will be offered to other universities for benchmarking purposes at the annual meeting of a nationally recognized university health and safety organization. The ultimate goal of the project was accomplished and was the creation of a standardized tool that can be used for measuring safety climate in the university work setting and can facilitate meaningful comparisons amongst institutions.^

UNDERSTANDING NURSE CREATED COGNITIVE ARTIFACTS: PERSONALLY-CREATED-COGNITIVE-ARTIFACTS AS EXTERNAL REPRESENTATIONS OF DISTRIBUTED COGNITION

Manuscript 1: “Conceptual Analysis: Externalizing Nursing Knowledge” We use concept analysis to establish that the report tool nurses prepare, carry, reference, amend, and use as a temporary data repository are examples of cognitive artifacts. This tool, integrally woven throughout the work and practice of nurses, is important to cognition and clinical decision-making. Establishing the tool as a cognitive artifact will support new dimensions of study. Such studies can characterize how this report tool supports cognition, internal representation of knowledge and skills, and external representation of knowledge of the nurse. Manuscript 2: “Research Methods: Exploring Cognitive Work” The purpose of this paper is to describe a complex, cross-sectional, multi-method approach to study of personal cognitive artifacts in the clinical environment. The complex data arrays present in these cognitive artifacts warrant the use of multiple methods of data collection. Use of a less robust research design may result in an incomplete understanding of the meaning, value, content, and relationships between personal cognitive artifacts in the clinical environment and the cognitive work of the user. Manuscript 3: “Making the Cognitive Work of Registered Nurses Visible” Purpose: Knowledge representations and structures are created and used by registered nurses to guide patient care. Understanding is limited regarding how these knowledge representations, or cognitive artifacts, contribute to working memory, prioritization, organization, cognition, and decision-making. The purpose of this study was to identify and characterize the role a specific cognitive artifact knowledge representation and structure as it contributed to the cognitive work of the registered nurse. Methods: Data collection was completed, using qualitative research methods, by shadowing and interviewing 25 registered nurses. Data analysis employed triangulation and iterative analytic processes. Results: Nurse cognitive artifacts support recall, data evaluation, decision-making, organization, and prioritization. These cognitive artifacts demonstrated spatial, longitudinal, chronologic, visual, and personal cues to support the cognitive work of nurses. Conclusions: Nurse cognitive artifacts are an important adjunct to the cognitive work of nurses, and directly support patient care. Nurses need to be able to configure their cognitive artifact in ways that are meaningful and support their internal knowledge representations.

Impact of traffic pollution on telomere length and chronic diseases: Results from the multi-ethnic study of atherosclerosis and the Mexican-American cohort study

Exposure to air pollutants in urban locales has been associated with increased risk for chronic diseases including cardiovascular disease (CVD) and pulmonary diseases in epidemiological studies. The exact mechanism explaining how air pollution affects chronic disease is still unknown. However, oxidative stress and inflammatory pathways have been posited as likely mechanisms. ^ Data from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Mexican-American Cohort Study (2003-2009) were used to examine the following aims, respectively: 1) to evaluate the association between long-term exposure to ambient particulate matter (PM) (PM10 and PM2.5) and nitrogen oxides (NO x) and telomere length (TL) among approximately 1,000 participants within MESA; and 2) to evaluate the association between traffic-related air pollution with self-reported asthma, diabetes, and hypertension among Mexican-Americans in Houston, Texas. ^ Our results from MESA were inconsistent regarding associations between long-term exposure to air pollution and shorter telomere length based on whether the participants came from New York (NY) or Los Angeles (LA). Although not statistically significant, we observed a negative association between long-term air pollution exposure and mean telomere length for NY participants, which was consistent with our hypothesis. Positive (statistically insignificant) associations were observed for LA participants. It is possible that our findings were more influenced by both outcome and exposure misclassification than by the absence of a relationship between pollution and TL. Future studies are needed that include longitudinal measures of telomere length as well as focus on effects of specific constituents of PM and other pollutant exposures on changes in telomere length over time. ^ This research provides support that Mexican-American adults who live near a major roadway or in close proximity to a dense street network have a higher prevalence of asthma. There was a non-significant trend towards an increased prevalence of adult asthma with increasing residential traffic exposure especially for residents who lived three or more years at their baseline address. Even though the prevalence of asthma is low in the Mexican-origin population, it is the fastest growing minority group in the U.S. and we would expect a growing number of Mexican-Americans who suffer from asthma in the future. Future studies are needed to better characterize risks for asthma associated with air pollution in this population.^

A simulation study of the effects of small center enrollment in multi -center clinical trials

Multi-center clinical trials are very common in the development of new drugs and devices. One concern in such trials, is the effect of individual investigational sites enrolling small numbers of patients on the overall result. Can the presence of small centers cause an ineffective treatment to appear effective when treatment-by-center interaction is not statistically significant?^ In this research, simulations are used to study the effect that centers enrolling few patients may have on the analysis of clinical trial data. A multi-center clinical trial with 20 sites is simulated to investigate the effect of a new treatment in comparison to a placebo treatment. Twelve of these 20 investigational sites are considered small, each enrolling less than four patients per treatment group. Three clinical trials are simulated with sample sizes of 100, 170 and 300. The simulated data is generated with various characteristics, one in which treatment should be considered effective and another where treatment is not effective. Qualitative interactions are also produced within the small sites to further investigate the effect of small centers under various conditions.^ Standard analysis of variance methods and the "sometimes-pool" testing procedure are applied to the simulated data. One model investigates treatment and center effect and treatment-by-center interaction. Another model investigates treatment effect alone. These analyses are used to determine the power to detect treatment-by-center interactions, and the probability of type I error.^ We find it is difficult to detect treatment-by-center interactions when only a few investigational sites enrolling a limited number of patients participate in the interaction. However, we find no increased risk of type I error in these situations. In a pooled analysis, when the treatment is not effective, the probability of finding a significant treatment effect in the absence of significant treatment-by-center interaction is well within standard limits of type I error. ^