The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

Assessment of anastomotic leakage: A Novel System for the Training of Surgeons to Perform a Tubular Anastomosis and Objectively Evaluate Anastomotic Leak

Introduction: Dehiscence of the suture line of an anastomosis can lead to reoperation, temporary or permanent stoma, and even sepsis or death. Few techniques for the laboratory training of tubular anastomosis use ex-vivo animal tissues. We describe a novel model that can be used in the laboratory for the training of anastomosis in tubular tissues and objectively assess any anastomotic leak. [See PDF for complete abstract]

Assessment of readiness to initiate antiretroviral therapy

An important factor in determining a patient's adherence to antiretroviral therapy is the patient's commitment to follow the regimen. This suggests that therapy should be initiated when the patient is willing to commit to the regimen. Starting when the patient is ready may be more important than the laboratory values suggested by various guidelines. In order to increase understanding of patient readiness for antiretroviral therapy HIV infected patients were surveyed to determine the factors that influenced their decision to initiate antiretroviral therapy and to continue to adhere to therapy once started. A sample of 83 HIV infected patients who were currently on antiretroviral regimens completed a 25-item investigator-developed questionnaire. The questionnaire sought information on the length of time from learning of HIV positive status and readiness to initiate therapy. The questionnaire also addressed demographic, psychological and social factors thought to be associated with readiness for adhering to therapy. (Abstract shortened by UMI.)^

The application of latent variable models to the assessment of determinants of HIV risk behavior

Studies on the relationship between psychosocial determinants and HIV risk behaviors have produced little evidence to support hypotheses based on theoretical relationships. One limitation inherent in many articles in the literature is the method of measurement of the determinants and the analytic approach selected. ^ To reduce the misclassification associated with unit scaling of measures specific to internalized homonegativity, I evaluated the psychometric properties of the Reactions to Homosexuality scale in a confirmatory factor analytic framework. In addition, I assessed the measurement invariance of the scale across racial/ethnic classifications in a sample of men who have sex with men. The resulting measure contained eight items loading on three first-order factors. Invariance assessment identified metric and partial strong invariance between racial/ethnic groups in the sample. ^ Application of the updated measure to a structural model allowed for the exploration of direct and indirect effects of internalized homonegativity on unprotected anal intercourse. Pathways identified in the model show that drug and alcohol use at last sexual encounter, the number of sexual partners in the previous three months and sexual compulsivity all contribute directly to risk behavior. Internalized homonegativity reduced the likelihood of exposure to drugs, alcohol or higher numbers of partners. For men who developed compulsive sexual behavior as a coping strategy for internalized homonegativity, there was an increase in the prevalence odds of risk behavior. ^ In the final stage of the analysis, I conducted a latent profile analysis of the items in the updated Reactions to Homosexuality scale. This analysis identified five distinct profiles, which suggested that the construct was not homogeneous in samples of men who have sex with men. Lack of prior consideration of these distinct manifestations of internalized homonegativity may have contributed to the analytic difficulty in identifying a relationship between the trait and high-risk sexual practices. ^

An assessment of the relative influence of a vapor recovery system in reducing occupational exposure to volatile organic compounds in high performance liquid chromatography

Occupational exposures to organic solvents, specifically acetonitrile and methanol, have the potential to cause serious long-term health effects. In the laboratory, these solvents are used extensively in protocols involving the use of high performance liquid chromatography (HPLC). Operators of HPLC equipment may be potentially exposed to these organic solvents when local exhaust ventilation is not employed properly or is not available, which can be the case in many settings. The objective of this research was to characterize the various sites of vapor release in the HPLC process and then to determine the relative influence of a novel vapor recovery system on the overall exposure to laboratory personnel. The effectiveness of steps to reduce environmental solvent vapor concentrations was assessed by measuring exposure levels of acetonitrile and methanol before and after installation of the vapor recovery system. With respect to acetonitrile, the concentration was not statistically significant with p=0.938; moreover, exposure after the intervention was actually higher than prior to intervention. With respect to methanol, the concentration was not statistically significant with p=0.278. This indicates that the exposure to methanol after the intervention was not statistically significantly higher or lower than prior to intervention. Thus, installation of the vapor recovery device did not result in statistically significant reduction in exposures in the settings encountered, and acetonitrile actually increased significantly.^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^