Teachers’ Perception of Empowerment in Christian Schools Accredited by Tennessee Association of Christian Schools

The purpose of the study was to examine the perception of teacher empowerment in Christian schools in order to ascertain if teachers were encouraged to take on more leadership responsibilities. One hundred forty-four teachers from 9 Christian schools (K-12) that are accredited by the Tennessee of Association of Christian Schools (TACS) participated in the study. The statistical analysis reported in the study was based on 5 research questions. Two instruments were used to collect data. A survey using a 5-point Likert Scale was used to collect data on teacher responsibilities, training, experiences, affiliation, and professional practices. Student achievement test scores from SAT-10 for the 2010-2011, 2011-2012, and 2012-2013 school years for grades 5, 8, and 11 were used to see if there is a correlation between teachers’ perception of empowerment and student achievement. A series of single sample t-tests were used to determine if there were significant differences between 2 independent groups. A Pearson correlation coefficient was computed to measure the relationship between teachers’ empowerment scores and their averaged student achievement test scores

Mining the FX electronic inter-dealer market

This paper examines the feasibility of applying data mining techniques to testing market efficiency hypothesis using a high frequency, up to one thousand of a second, electronic brokerage data. Results suggest the existence of a pattern of negative autocorrelation in returns of DEM/USD over relative short lags (less than 40 seconds). However, this pattern is not feasible by two reasons: (1) the structure of autocorrelation pattern is inconsistent and changes too rapidly (2) the largest potential speculative profit is smaller than the regulated tick size. These results indicate that dealers have engaged in any potential profitable speculations based on past price information

Campus & alumni news

Boston University Medicine was published by the Boston University Medical Campus, and presented stories on events and topics of interest to members of the BU Medical Campus community. It followed the discontinued publication Centerscope as Boston University Medicine from 1991-2005, then continued as Campus & Alumni News from 2006-2013 before returning to the title Boston University Medicine from 2014-present

Impact of multiscale dynamical processes and mixing on the chemical composition of the upper troposphere and lower stratosphere during the Intercontinental Chemical Transport Experiment–North America

We use high-frequency in situ observations made from the DC8 to examine fine-scale tracer structure and correlations observed in the upper troposphere and lower stratosphere during INTEX-NA. Two flights of the NASA DC-8 are compared and contrasted. Chemical data from the DC-8 flight on 18 July show evidence for interleaving and mixing of polluted and stratospheric air masses in the vicinity of the subtropical jet in the upper troposphere, while on 2 August the DC-8 flew through a polluted upper troposphere and a lowermost stratosphere that showed evidence of an intrusion of polluted air. We compare data from both flights with RAQMS 3-D global meteorological and chemical model fields to establish dynamical context and to diagnose processes regulating the degree of mixing on each day. We also use trajectory mapping of the model fields to show that filamentary structure due to upstream strain deformation contributes to tracer variability observed in the upper troposphere. An Eulerian measure of strain versus rotation in the large-scale flow is found useful in predicting filamentary structure in the vicinity of the jet. Higher-frequency (6–24 km) tracer variability is attributed to buoyancy wave oscillations in the vicinity of the jet, whose turbulent dissipation leads to efficient mixing across tracer gradients

A Decision Support System for Market Segmentation - A Neural Networks Approach

Market segmentation refers to the subdividing of a market into distinct subsets of customers where any subset may conceivably be selected as a market target to be reached with a distinct marketing mix [Kotler 1980]. The reason for segmenting a market is that consumers are often numerous, geographically dispersed, and heterogeneous, and therefore seek varying benefits from the products they buy. Consumers within a segment are expected to have homogeneous buying preferences whereas those in different segments tend to behave differently. By properly identifying the benefit segment of a firm\u27s product, the marketing manager can target the sales effort at specific groups of consumers rather than at the total population. The identification of consumer segments is of critical importance for key strategic issues in marketing involving the assessment of a firm\u27s opportunities and threats. The marketing manager must evaluate the potential of the firm\u27s products in the target segment and ultimately select the most promising strategy for the segment. In thisresearch, we introduce a new approach, a neural networks based method, to discover market segments and configure them into meaningful structures. The particular type of neural networks, the Self-Organizing Map networks, can be used as a decision support tool for supporting strategic decisions involving identifying and targeting market segments. The Self-Organizing Map (SOM) network, a variation of neural computing networks, is a categorization network developed by Kohonen. The theory of the SOM network is motivated by the observation of the operation of the brain. This paper presents the technique of SOM and shows how it may be applied as a clustering tool to market segmentation. A computer program for implementing the SOM neural networks is developed and the results will be compared with other clustering approaches. The study demonstrates the potential of using the Self-Organizing Map as the clustering tool for market segmentation

Is Low Health Literacy Associated with Increased Emergency Department Utilization and Recidivism?

OBJECTIVES: The objective was to determine whether patients with low health literacy have higher emergency department (ED) utilization and higher ED recidivism than patients with adequate health literacy. METHODS: The study was conducted at an urban academic ED with more than 95,000 annual visits that is part of a 13-hospital health system, using electronic records that are captured in a central data repository. As part of a larger, cross-sectional, convenience sample study, health literacy testing was performed using the short test of functional health literacy in adults (S-TOFHLA) and standard test thresholds identifying those with inadequate, marginal, and adequate health literacy. The authors collected patients' demographic and clinical data, including items known to affect recidivism. This was a structured electronic record review directed at determining 1) the median number of total ED visits in this health system within a 2-year period and 2) the proportion of patients with each level of health literacy who had return visits within 3, 7, and 14 days of index visits. Descriptive data for demographics and ED returns are reported, stratified by health literacy level. The Mantel-Haenszel chi-square was used to test whether there is an association between health literacy and ED recidivism. A negative binomial multivariable model was performed to examine whether health literacy affects ED use, including variables significant at the 0.1 alpha level on bivariate analysis and retaining those significant at an alpha of 0.05 in the final model. RESULTS: Among 431 patients evaluated, 13.2% had inadequate, 10% had marginal, and 76.3% had adequate health literacy as identified by S-TOFHLA. Patients with inadequate health literacy had higher ED utilization compared to those with adequate health literacy (p = 0.03). Variables retained in the final model included S-TOFHLA score, number of medications, having a personal doctor, being a property owner, race, insurance, age, and simple comorbidity score. During the study period, 118 unique patients each made at least one return ED visit within a 14-day period. The proportion of patients with inadequate health literacy making at least one return visit was higher than that of patients with adequate health literacy at 14 days, but was not significantly higher within 3 or 7 days. CONCLUSIONS: In this single-center study, higher utilization of the ED by patients with inadequate health literacy when compared to those with adequate health literacy was observed. Patients with inadequate health literacy made a higher number of return visits at 14 days but not at 3 or 7 days

Do subjective measures improve the ability to identify limited health literacy in a clinical setting?

BACKGROUND: Existing health literacy assessments developed for research purposes have constraints that limit their utility for clinical practice, including time requirements and administration protocols. The Brief Health Literacy Screen (BHLS) consists of 3 self-administered Single-Item Literacy Screener (SILS) questions and obviates these clinical barriers. We assessed whether the addition of SILS items or the BHLS to patient demographics readily available in ambulatory clinical settings reaching underserved patients improves the ability to identify limited health literacy. METHODS: We analyzed data from 2 cross-sectional convenience samples of patients from an urban academic emergency department (n = 425) and a primary care clinic (n = 486) in St. Louis, Missouri. Across samples, health literacy was assessed using the Rapid Estimate of Adult Literacy in Medicine-Revised (REALM-R), Newest Vital Sign (NVS), and the BHLS. Our analytic sample consisted of 911 adult patients, who were primarily female (62%), black (66%), and had at least a high school education (82%); 456 were randomly assigned to the estimation sample and 455 to the validation sample. RESULTS: The analysis showed that the best REALM-R estimation model contained age, sex, education, race, and 1 SILS item (difficulty understanding written information). In validation analysis this model had a sensitivity of 62%, specificity of 81%, a positive likelihood ratio (LR(+)) of 3.26, and a negative likelihood ratio (LR(−)) of 0.47; there was a 28% misclassification rate. The best NVS estimation model contained the BHLS, age, sex, education and race; this model had a sensitivity of 77%, specificity of 72%, LR(+) of 2.75, LR(−) of 0.32, and a misclassification rate of 25%. CONCLUSIONS: Findings suggest that the BHLS and SILS items improve the ability to identify patients with limited health literacy compared with demographic predictors alone. However, despite being easier to administer in clinical settings, subjective estimates of health literacy have misclassification rates >20% and do not replace objective measures; universal precautions should be used with all patients