Staffing and job satisfaction: nurses and nursing assistants

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106848/1/jonm12012.pd

Exploring Spatial Variations in the Relationship between National Park Visitation and Associated Factors in Texas Counties

Recreation demand such as national park visitation is influenced by various social, demographic, and economic factors. These key variables are important indicators in predicting future trends and provide beneficial information about potential park visitors for managers and planners. As parks and protected areas become impacted by socio-economic changes, it is important to understand the relationship between specific factors of recreation participation and national park visitation. From a practitioner perspective, recreation agencies require multi-scale levels of information in order to address visitor and facility needs. While site-based research or using disaggregated models are helpful to satisfy specific purposes for a park, they often do not provide this information in spatially distributed data on a statewide or regional level. Recreation planners and managers need recreation demand forecasts at levels of spatial aggregations. This study tried to identify the spatial relationships between national park visitation and its associated factors using large aggregated data. Guided by the idea of opportunity theory and Pigram’s conceptual framework, this study empirically investigated what and how factors associated with national park visitation influence demand within the Texas boundary. Specifically, this study developed a spatial regression model of national park visitation demand in Texas using Geographically Weighted Regression (GWR). This model estimated the strength of the relationship between visitation and selected demographic, socioeconomic and situational factors. Methodologically, traditional regression models (e.g., OLS) yield only a single estimate in a relationship. In comparison, GWR allows an estimate of the spatial variation of the relationship within the study area. Several private and public data sources were used in the model to create reliably aggregated data. Several explanatory variables, e.g., poverty rate, family structures, recreation-related spending patterns and level of education, were hypothesized to influence the level of national park visitation for spatially varying relationships across the study area. From a methodological perspective, this study found interesting methodological implications (e.g., rethinking the traditional regression model for recreation demand estimation) and the potential associated with the use of spatial statistics to analyze the relationships between recreation participation and societal factors. This research demonstrated the importance of including spatial variables as part of recreation demand analysis. Relatively little work has used spatial models in the field of recreation. The results of this study demonstrate the usefulness of spatial analysis for detecting various relationships within the state over traditional statistical analysis

Relationship of Emotion and Cognition to Wandering Behaviors of People with Dementia.

Wandering is one of the most frequently encountered dementia-related behavioral disturbances and has been associated with negative consequences such as higher morbidity and mortality. In terms of relating factors of wandering, it has become increasingly clear that a close relationship exists between emotion, cognition, and behavior. However, little research has focused on the influence of emotion on wandering of people with dementia (PWD). The purpose of this study was to explore the relationship of emotion and cognition to wandering behaviors of PWD. This study applied a secondary data analysis utilizing a parent study that used a cross-sectional design with repeated measure nested within subjects. A total of 115 PWD in 17 nursing homes and six assisted living facilities in Michigan and Pennsylvania were included. Subjects were randomly assigned to six 20 minute observation periods, conducted on two non-consecutive days; their behaviors were videotaped. Poisson hierarchical linear modeling (HLM) was utilized to determine factors associated with wandering. Positive emotional expression increased wandering rates whereas negative emotional expression and higher MMSE score decreased wandering rates after controlling for other predictors (i.e., age, education, gender, and time of day). Therefore, both positive/negative emotional expression and cognition influence wandering; a tailored intervention that addresses both emotional and cognitive functioning may be required to improve wandering behaviors of PWD.Ph.D.NursingUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89700/1/kheelee_1.pd

Two-dimensional heterogeneous photonic bandedge laser

We proposed and realized a two-dimensional (2D) photonic bandedge laser surrounded by the photonic bandgap. The heterogeneous photonic crystal structure consists of two triangular lattices of the same lattice constant with different air hole radii. The photonic crystal laser was realized by room-temperature optical pumping of air-bridge slabs of InGaAsP quantum wells emitting at 1.55 micrometer. The lasing mode was identified from its spectral positions and polarization directions. A low threshold incident pump power of 0.24mW was achieved. The measured characteristics of the photonic crystal lasers closely agree with the results of real space and Fourier space calculations based on the finite-difference time-domain method.Comment: 14 pages, 4 figure

A TEXT MINING APPROACH TO THE ANALYSIS OF INFORMATION SECURITY AWARENESS: KOREA, UNITED STATES, AND CHINA

Recently in Korea, the importance of information security awareness has been receiving a growing attention. Attacks such as social engineering and ransomware are hard to prevent because it cannot be solved by information security technology. Also, the profitability of information security industry has been decreasing for years. Because of this, many companies try to find a new growth-engine and an entry to the foreign market. The main purpose of this paper is to draw out some information security issues that people of each country think and to analyze it. Finally, this study identifies issues and suggests how to improve the situation in Korea. For this, Topic Modeling analysis has been used to find information security issues of each country. Moreover, the score of sentiment analysis has been used to compare each country. The study contributes to the literature by exploring and explaining what critical issues are and how to improve the situation based on the identified issues of the Korean information security industry. Also, this study adds to the literature by demonstrating how text mining can be applied to the context of information security awareness. From a pragmatic perspective, the study has the implications for information security enterprises. This study is expected to provide a new and realistic method of analyzing domestic and foreign issues using the analyzing real data of the Twitter API