A path analysis of an after-school health and exercise program for elementary school children in El Paso, Texas

As schools are pressured to perform on academics and standardized examinations, schools are reluctant to dedicate increased time to physical activity. After-school exercise and health programs may provide an opportunity to engage in more physical activity without taking time away from coursework during the day. The current study is a secondary data analysis of data from a randomized trial of a 10-week after-school program (six schools, n = 903) that implemented an exercise component based on the CATCH physical activity component and health modules based on the culturally-tailored Bienestar health education program. Outcome variables included BMI and aerobic capacity, health knowledge and healthy food intentions as assessed through path analysis techniques. Both the baseline model (χ2 (df = 8) = 16.90, p = .031; RMSEA = .035 (90% CI of .010–.058), NNFI = 0.983 and the CFI = 0.995) and the model incorporating intervention participation proved to be a good fit to the data (χ2 (df = 10) = 11.59, p = .314. RMSEA = .013 (90% CI of .010–.039); NNFI = 0.996 and CFI = 0.999). Experimental group participation was not predictive of changes in health knowledge, intentions to eat healthy foods or changes in Body Mass Index, but it was associated with increased aerobic capacity, β = .067, p < .05. School characteristics including SES and Language proficiency proved to be significantly associated with changes in knowledge and physical indicators. Further effects of school level variables on intervention outcomes are recommended so that tailored interventions can be developed aimed at the specific characteristics of each participating school. ^

Hypogonadism in male cancer patients: A cross-sectional study

Introduction. Cancer is the second most common cause of death in the USA (2). Studies have shown a coexistence of cancer and hypogonadism (9,31,13). The majority of patients with cancer develop cachexia, which cannot be solely explained by anorexia seen in these patients. Testosterone is a male sex hormone which is known to increase muscle mass and strength, maintain cancellous bone mass, and increase cortical bone mass, in addition to improving libido, sexual desire, and fantasy (14). If a high prevalence of hypogonadism is detected in male cancer patients, and a significant difference exists in testosterone levels in cancer patients with cachexia versus those without cachexia, testosterone may be administered in future randomized trials to help alleviate cachexia. Study group and design The study group consisted of male cancer patients and non-cancer controls aged between 40 and 70 years. The primary study design was cross-sectional with a sample size of 135. The present data analysis is done on a subset convenience sample of 72 patients recruited between November 2006 and January 2010. ^ Methods. Patients aged 40-70 years with or without a diagnosis of cancer were recruited into the study. All patients with a BMI over 35, significant edema, non-melanomatous skin cancer, current alcohol or illicit drug abuse, concomitant usage of medications interfering with gonadal axis, and anabolic agents, patients on tube feeds or parenteral nutrition within 3 months prior to enrollment were excluded from the study. The study was approved by the Institutional Review Board of Baylor College of Medicine and is being conducted at the Michael E. DeBakey Veterans Affairs Medical Center at Houston. My thesis is a pilot data analysis that employs a smaller subset convenience sample of 72 patients determined by using the data available for the 72 patients (of the intended sample of 135 patients) recruited between November 2006 and January 2010. The primary aim of this analysis is to compare the proportion of patients with hypogonadism in the male cancer and non-cancer control groups, and to evaluate if a significant difference exists with respect to testosterone levels in male cancer patients with cachexia versus those without cachexia. The procedures of the study relevant to the current data analysis included blood collection to measure levels of testosterone and measurement of body weight to categorize cancer patients into cancer cachexia and cancer non-cachexia sub-groups. ^ Results. After logarithmic transformation of data of cancer and control groups, the unpaired t test with unequal variances was done. The proportion of patients with hypogonadism in the male cancer and non-cancer control groups was 47.5% and 22.7% with a Pearson chi2 statistic of 1.6036 and a p value of 0.205. Comparing the mean calculated Bioavailable testosterone in male cancer patients and non-cancer controls resulted in a t statistic of 21.83 and a p value less than 0.001. When the cancer group alone was taken, the mean free testosterone, calculated bioavailable testosterone and total testosterone levels in the cancer non-cachexia sub-group were 3.93, 5.09, 103.51 respectively and in the cancer cachexia sub-group were 3.58, 4.17, 84.08 respectively. The unpaired t test with equal variances showed that the two sub-groups had p values of 0.2015, 0.1842, and 0.4894 with respect to calculated bioavailable testosterone, free testosterone, and total testosterone respectively. ^ Conclusions. The small sample size of this exploratory study, resulting in a small power, does not allow us to draw definitive conclusions. For the given sub-sample, the proportion of patients with hypogonadism in the cancer group was not significantly different from that of patients with hypogonadism in the control group. Inferences on prevalence of hypogonadism in male cancer patients could not be made in this paper as the sub-sample is small and therefore not representative of the general population. However, there was a statistically significant difference in calculated Bioavailable testosterone levels in male cancer patients versus non-cancer controls. Analysis of cachectic and non-cachectic patients within the male cancer group showed no significant difference in testosterone levels (total, free, and calculated bioavailable testosterone) between both sub-groups. However, to re-iterate, this study is exploratory and the results may change once the complete dataset is obtained and analyzed. It however serves as a good template to guide further research and analysis.^

Secondary analysis of effectivness of tinidazole-containing-quadruple eradication therapy in asymptomatic H. pylori infected children in El Paso

Helicobacter pylori infection is frequently acquired during childhood. This microorganism is known to cause gastritis, and duodenal ulcer in pediatric patients, however most children remain completely asymptomatic to the infection. Currently there is no consensus in favor of treatment of H. pylori infection in asymptomatic children. The firstline of treatment for this population is triple medication therapy including two antibacterial agents and one proton pump inhibitor for a 2 week duration course. Decreased eradication rate of less than 75% has been documented with the use of this first-line therapy but novel tinidazole-containing quadruple sequential therapies seem worth investigating. None of the previous studies on such therapy has been done in the United States of America. As part of an iron deficiency anemia study in asymptomatic H. pylori infected children of El Paso, Texas, we conducted a secondary data analysis of study data collected in this trial to assess the effectiveness of this tinidazole-containing sequential quadruple therapy compared to placebo on clearing the infection. Subjects were selected from a group of asymptomatic children identified through household visits to 11,365 randomly selected dwelling units. After obtaining parental consent and child assent a total of 1,821 children 3-10 years of age were screened and 235 were positive to a novel urine immunoglobulin class G antibodies test for H. pylori infection and confirmed as infected using a 13C urea breath test, using a hydrolysis urea rate >10 μg/min as cut-off value. Out of those, 119 study subjects had a complete physical exam and baseline blood work and were randomly allocated to four groups, two of which received active H. pylori eradication medication alone or in combination with iron, while the other two received iron only or placebo only. Follow up visits to their houses were done to assess compliance and occurrence of adverse events and at 45+ days post-treatment, a second urea breath test was performed to assess their infection status. The effectiveness was primarily assessed on intent to treat basis (i.e., according to their treatment allocation), and the proportion of those who cleared their infection using a cut-off value >10 μg/min of for urea hydrolysis rate, was the primary outcome. Also we conducted analysis on a per-protocol basis and according to the cytotoxin associated gene A product of the H. pylori infection status. Also we compared the rate of adverse events across the two arms. On intent-to-treat and per-protocol analyses, 44.3% and 52.9%, respectively, of the children receiving the novel quadruple sequential eradication cleared their infection compared to 12.2% and 15.4% in the arms receiving iron or placebo only, respectively. Such differences were statistically significant (p<0.001). The study medications were well accepted and safe. In conclusion, we found in this study population, of mostly asymptomatically H. pylori infected children, living in the US along the border with Mexico, that the quadruple sequential eradication therapy cleared the infection in only half of the children receiving this treatment. Research is needed to assess the antimicrobial susceptibility of the strains of H. pylori infecting this population to formulate more effective therapies. ^

Demographic analysis of Certified Industrial Hygienists (CIH) with the use of survival analysis techniques

Objective. The goal of this study is to characterize the current workforce of CIHs, the lengths of professional practice careers of the past and current CIHs.^ Methods. This is a secondary data analysis of data compiled from all of the nearly 50 annual roster listings of the American Board of Industrial Hygiene (ABIH) for Certified Industrial Hygienists active in each year since 1960. Survival analysis was performed as a technique to measure the primary outcome of interest. The technique which was involved in this study was the Kaplan-Meier method for estimating the survival function.^ Study subjects: The population to be studied is all Certified Industrial Hygienists (CIHs). A CIH is defined by the ABIH as an individual who has achieved the minimum requirements for education, working experience and through examination, has demonstrated a minimum level of knowledge and competency in the prevention of occupational illnesses. ^ Results. A Cox-proportional hazards model analysis was performed by different start-time cohorts of CIHs. In this model we chose cohort 1 as the reference cohort. The estimated relative risk of the event (defined as retirement, or absent from 5 consecutive years of listing) occurred for CIHs for cohorts 2,3,4,5 relative to cohort 1 is 0.385, 0.214, 0.234, 0.299 relatively. The result show that cohort 2 (CIHs issued from 1970-1980) has the lowest hazard ratio which indicates the lowest retirement rate.^ Conclusion. The manpower of CIHs (still actively practicing up to the end of 2009) increased tremendously starting in 1980 and grew into a plateau in recent decades. This indicates that the supply and demand of the profession may have reached equilibrium. More demographic information and variables are needed to actually predict the future number of CIHs needed. ^

Descriptive analysis of Ben Taub Pediatric Weight Management Program

The purpose of this study is to descriptively analyze the current program at Ben Taub Pediatric Weight Management Program in Houston, Texas, a program designed to help overweight children ages three to eighteen to lose weight. In Texas, approximately one in every three children is overweight or obese. Obesity is seen at an even greater level within Ben Taub due to the hospital's high rate of service for underserved minority populations (Dehghan et al, 2005; Tyler and Horner, 2008; Hunt, 2009). The weight management program consists of nutritional, behavioral, physical activity, and medical counseling. Analysis will focus on changes in weight, BMI, cholesterol levels, and blood pressure from 2007–2010 for all participants who attended at least two weight management sessions. Recommendations will be given in response to the results of the data analysis.^

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Development of a standard sign-out procedure for clinicians in a pediatric intensive care unit

Background: Poor communication among health care providers is cited as the most common cause of sentinel events involving patients. Sign-out of patient data at the change of clinician shifts is a component of communication that is especially vulnerable to errors. Sign-outs are particularly extensive and complex in intensive care units (ICUs). There is a paucity of validated tools to assess ICU sign-outs. ^ Objective: To design a valid and reliable survey tool to assess the perceptions of Pediatric ICU (PICU) clinicians about sign-out. ^ Design: Cross-sectional, web-based survey ^ Setting: Academic hospital, 31-bed PICU ^ Subjects: Attending faculty, fellows, nurse practitioners and physician assistants. ^ Interventions: A survey was designed with input from a focus group and administered to PICU clinicians. Test-retest reliability, internal consistency and validity of the survey tool were assessed. ^ Measurements and Main Results: Forty-eight PICU clinicians agreed to participate. We had 42(88%) and 40(83%) responses in the test and retest phases. The mean scores for the ten survey items ranged from 2.79 to 3.67 on a five point Likert scale with no significant test-retest difference and a Pearson correlation between pre and post answers of 0.65. The survey item scores showed internal consistency with a Cronbach's Alpha of 0.85. Exploratory factor analysis revealed three constructs: efficacy of sign-out process, recipient satisfaction and content applicability. Seventy eight % clinicians affirmed the need for improvement of the sign-out process and 83% confirmed the need for face- to-face verbal sign-out. A system-based sign-out format was favored by fellows and advanced level practitioners while attendings preferred a problem-based format (p=0.003). ^ Conclusions: We developed a valid and reliable survey to assess clinician perceptions about the ICU sign-out process. These results can be used to design a verbal template to improve and standardize the sign-out process.^

Self -management behavior in patients with cystic fibrosis

Self-management is being promoted in cystic fibrosis (CF). However, it has not been well studied. Principal aims of this research were (1) to evaluate psychometric properties of a CF disease status measure, the NIH Clinical Score; (2) to develop and validate a measure of self-management behavior, the SMQ-CF scale, and (3) to examine the relation between self-management and disease status in CF patients over two years.^ In study 1, NIH Clinical Scores for 200 patients were used. The scale was examined for internal consistency, interrater reliability, and content validity using factor analysis. The Cronbach's alpha (.81) and interrater reliability (.90) for the total scale were high. General scale items were less reliable. Factor analysis indicated that most of the variance in disease status is accounted for by Factor 1 which consists of pulmonary disease items.^ The SMQ-CF measures the performance of CF self-management. Pilot testing was done with 98 CF primary caregivers. Internal consistency reliability, social desirability bias, and content validity using factor analysis were examined. Internal consistency was good (alpha =.95). Social desirability correlation was low (r =.095). Twelve factors identified were consistent with conceptual groupings of behaviors. Around two hundred caregivers from two CF centers were surveyed and multivariate analysis of variance was used to assess construct validity. Results confirmed expected relations between self-management, patient age, and disease status. Patient age accounted for 50% and disease status 18% of the variance in the SMQ-CF scale.^ It was hypothesized that self-management would positively affect future disease status. Data from 199 CF patients (control and education intervention groups) were examined. Models of hypothesized relations were tested using LISREL structural equation modeling. Results indicated that the relations between baseline self-management and Time 1 disease status were not significant. Significant relations were observed in self-management behaviors from time 1 to time 2 and patterns of significant relations differed between the two groups.^ This research has contributed to refinements in the ability to measure self-management behavior and disease status outcomes in cystic fibrosis. In addition, it provides the first steps in exploratory behavioral analysis with regard to self-management in this disease. ^

Generating Automated News to Explain the Meaning of Sensor Data

An important competence of human data analysts is to interpret and explain the meaning of the results of data analysis to end-users. However, existing automatic solutions for intelligent data analysis provide limited help to interpret and communicate information to non-expert users. In this paper we present a general approach to generating explanatory descriptions about the meaning of quantitative sensor data. We propose a type of web application: a virtual newspaper with automatically generated news stories that describe the meaning of sensor data. This solution integrates a variety of techniques from intelligent data analysis into a web-based multimedia presentation system. We validated our approach in a real world problem and demonstrate its generality using data sets from several domains. Our experience shows that this solution can facilitate the use of sensor data by general users and, therefore, can increase the utility of sensor network infrastructures.

Modelos de análisis econométrico espacial aplicados al desarrollo económico

Los modelos de desarrollo regional, rural y urbano arrancaron en la década de los 90 en Estados Unidos, modelando los factores relacionados con la economía que suministran información y conocimiento acerca de cómo los parámetros geográficos y otros externos influencian la economía regional. El desarrollo regional y en particular el rural han seguido diferentes caminos en Europa y España, adoptando como modelo los programas estructurales de la UE ligados a la PAC. El Programa para el Desarrollo Rural Sostenible, recientemente lanzado por el Gobierno de España (2010) no profundiza en los modelos económicos de esta economía y sus causas. Este estudio pretende encontrar pautas de comportamiento de las variables de la economía regional-rural, y como el efecto de distribución geográfica de la población condiciona la actividad económica. Para este propósito, y utilizando datos espaciales y económicos de las regiones, se implementaran modelos espaciales que permitan evaluar el comportamiento económico, y verificar hipótesis de trabajo sobre la geografía y la economía del territorio. Se utilizarán modelos de análisis espacial como el análisis exploratorio espacial y los modelos econométricos de ecuaciones simultáneas, y dentro de estas los modelos ampliamente utilizados en estudios regionales de Carlino-Mills- Boarnet. ABSTRACT The regional development models for rural and urban areas started in USA in the ´90s, modeling the economy and the factors involved to understand and collect the knowledge of how the external parameters influenced the regional economy. Regional development and in particular rural development has followed different paths in Europe and Spain, adopting structural programs defined in the EU Agriculture Common Policy. The program for Sustainable Rural Development recently implemented in Spain (2010) is short sighted considering the effects of the regional economy. This study endeavors to underline models of behavior for the rural and regional economy variables, and how the regional distribution of population conditions the economic activities. For that purpose using current spatial regional economic data, this study will implement spatial economic models to evaluate the behavior of the regional economy, including the evaluation of working hypothesis about geography and economy in the territory. The approach will use data analysis models, like exploratory spatial data analysis, and spatial econometric models, and in particular for its wide acceptance in regional analysis, the Carlino-Mills-Boarnet equations model.

Maintenance management model for industrial Smes

This paper presents the design and results of the implementation of a model for the evaluation and improvement of maintenance management in industrial SMEs. A thorough review of the state of the art on maintenance management was conducted to determine the model variables; to characterize industrial SMEs, a questionnaire was developed with Likert variables collected in the previous step. Once validated the questionnaire, we applied the same to a group of seventy-five (75) SMEs in the industrial sector, located in Bolivar State, Venezuela. To identify the most relevant variables maintenance management, we used exploratory factor analysis technique applied to the data collected. The score obtained for all the companies evaluated (57% compliance), highlights the weakness of maintenance management in industrial SMEs, particularly in the areas of planning and continuous improvement; most SMEs are evaluated in corrective maintenance stage, and its performance standard only response to the occurrence of faults.

Modelo de gestión logística para pymes industriales

This paper presents the design and results of applying a model for logistics management in industrial SMEs. To identify the variables in the model, we conducted a thorough review of the state of the art logistics management; to characterize SMEs, developed a Likert questionnaire with the variables collected in the previous step. Once validated the questionnaire, was applied the same to a group of seventy-five (75) SMEs in the industrial sector, located in Bolivar State, Venezuela. To determine statistically the most relevant variables of management was used exploratory factor analysis technique applied to the data collected. The qualification obtained for all companies evaluated (47% compliance), highlights the weakness of logistics management in industrial SME.

Análisis de los factores de adopción de comercio electrónico en segmentos de consumidores finales. Aplicación al caso español

El comercio electrónico ha experimentado un fuerte crecimiento en los últimos años, favorecido especialmente por el aumento de las tasas de penetración de Internet en todo el mundo. Sin embargo, no todos los países están evolucionando de la misma manera, con un espectro que va desde las naciones pioneras en desarrollo de tecnologías de la información y comunicaciones, que cuentan con una elevado porcentaje de internautas y de compradores online, hasta las rezagadas de rápida adopción en las que, pese a contar con una menor penetración de acceso, presentan una alta tasa de internautas compradores. Entre ambos extremos se encuentran países como España que, aunque alcanzó hace años una tasa considerable de penetración de usuarios de Internet, no ha conseguido una buena tasa de transformación de internautas en compradores. Pese a que el comercio electrónico ha experimentado importantes aumentos en los últimos años, sus tasas de crecimiento siguen estando por debajo de países con características socio-económicas similares. Para intentar conocer las razones que afectan a la adopción del comercio por parte de los compradores, la investigación científica del fenómeno ha empleado diferentes enfoques teóricos. De entre todos ellos ha destacado el uso de los modelos de adopción, proveniente de la literatura de adopción de sistemas de información en entornos organizativos. Estos modelos se basan en las percepciones de los compradores para determinar qué factores pueden predecir mejor la intención de compra y, en consecuencia, la conducta real de compra de los usuarios. Pese a que en los últimos años han proliferado los trabajos de investigación que aplican los modelos de adopción al comercio electrónico, casi todos tratan de validar sus hipótesis mediante el análisis de muestras de consumidores tratadas como un único conjunto, y del que se obtienen conclusiones generales. Sin embargo, desde el origen del marketing, y en especial a partir de la segunda mitad del siglo XIX, se considera que existen diferencias en el comportamiento de los consumidores, que pueden ser debidas a características demográficas, sociológicas o psicológicas. Estas diferencias se traducen en necesidades distintas, que sólo podrán ser satisfechas con una oferta adaptada por parte de los vendedores. Además, por contar el comercio electrónico con unas características particulares que lo diferencian del comercio tradicional –especialmente por la falta de contacto físico entre el comprador y el producto– a las diferencias en la adopción para cada consumidor se le añaden las diferencias derivadas del tipo de producto adquirido, que si bien habían sido consideradas en el canal físico, en el comercio electrónico cobran especial relevancia. A la vista de todo ello, el presente trabajo pretende abordar el estudio de los factores determinantes de la intención de compra y la conducta real de compra en comercio electrónico por parte del consumidor final español, teniendo en cuenta el tipo de segmento al que pertenezca dicho comprador y el tipo de producto considerado. Para ello, el trabajo contiene ocho apartados entre los que se encuentran cuatro bloques teóricos y tres bloques empíricos, además de las conclusiones. Estos bloques dan lugar a los siguientes ocho capítulos por orden de aparición en el trabajo: introducción, situación del comercio electrónico, modelos de adopción de tecnología, segmentación en comercio electrónico, diseño previo del trabajo empírico, diseño de la investigación, análisis de los resultados y conclusiones. El capítulo introductorio justifica la relevancia de la investigación, además de fijar los objetivos, la metodología y las fases seguidas para el desarrollo del trabajo. La justificación se complementa con el segundo capítulo, que cuenta con dos elementos principales: en primer lugar se define el concepto de comercio electrónico y se hace una breve retrospectiva desde sus orígenes hasta la situación actual en un contexto global; en segundo lugar, el análisis estudia la evolución del comercio electrónico en España, mostrando su desarrollo y situación presente a partir de sus principales indicadores. Este apartado no sólo permite conocer el contexto de la investigación, sino que además permite contrastar la relevancia de la muestra utilizada en el presente estudio con el perfil español respecto al comercio electrónico. Los capítulos tercero –modelos de adopción de tecnologías– y cuarto –segmentación en comercio electrónico– sientan las bases teóricas necesarias para abordar el estudio. En el capítulo tres se hace una revisión general de la literatura de modelos de adopción de tecnología y, en particular, de los modelos de adopción empleados en el ámbito del comercio electrónico. El resultado de dicha revisión deriva en la construcción de un modelo adaptado basado en los modelos UTAUT (Unified Theory of Acceptance and Use of Technology, Teoría unificada de la aceptación y el uso de la tecnología) y UTAUT2, combinado con dos factores específicos de adopción del comercio electrónico: el riesgo percibido y la confianza percibida. Por su parte, en el capítulo cuatro se revisan las metodologías de segmentación de clientes y productos empleadas en la literatura. De dicha revisión se obtienen un amplio conjunto de variables de las que finalmente se escogen nueve variables de clasificación que se consideran adecuadas tanto por su adaptación al contexto del comercio electrónico como por su adecuación a las características de la muestra empleada para validar el modelo. Las nueve variables se agrupan en tres conjuntos: variables de tipo socio-demográfico –género, edad, nivel de estudios, nivel de ingresos, tamaño de la unidad familiar y estado civil–, de comportamiento de compra – experiencia de compra por Internet y frecuencia de compra por Internet– y de tipo psicográfico –motivaciones de compra por Internet. La segunda parte del capítulo cuatro se dedica a la revisión de los criterios empleados en la literatura para la clasificación de los productos en el contexto del comercio electrónico. De dicha revisión se obtienen quince grupos de variables que pueden tomar un total de treinta y cuatro valores, lo que deriva en un elevado número de combinaciones posibles. Sin embargo, pese a haber sido utilizados en el contexto del comercio electrónico, no en todos los casos se ha comprobado la influencia de dichas variables respecto a la intención de compra o la conducta real de compra por Internet; por este motivo, y con el objetivo de definir una clasificación robusta y abordable de tipos de productos, en el capitulo cinco se lleva a cabo una validación de las variables de clasificación de productos mediante un experimento previo con 207 muestras. Seleccionando sólo aquellas variables objetivas que no dependan de la interpretación personal del consumidores y que determinen grupos significativamente distintos respecto a la intención y conducta de compra de los consumidores, se obtiene un modelo de dos variables que combinadas dan lugar a cuatro tipos de productos: bien digital, bien no digital, servicio digital y servicio no digital. Definidos el modelo de adopción y los criterios de segmentación de consumidores y productos, en el sexto capítulo se desarrolla el modelo completo de investigación formado por un conjunto de hipótesis obtenidas de la revisión de la literatura de los capítulos anteriores, en las que se definen las hipótesis de investigación con respecto a las influencias esperadas de las variables de segmentación sobre las relaciones del modelo de adopción. Este modelo confiere a la investigación un carácter social y de tipo fundamentalmente exploratorio, en el que en muchos casos ni siquiera se han encontrado evidencias empíricas previas que permitan el enunciado de hipótesis sobre la influencia de determinadas variables de segmentación. El capítulo seis contiene además la descripción del instrumento de medida empleado en la investigación, conformado por un total de 125 preguntas y sus correspondientes escalas de medida, así como la descripción de la muestra representativa empleada en la validación del modelo, compuesta por un grupo de 817 personas españolas o residentes en España. El capítulo siete constituye el núcleo del análisis empírico del trabajo de investigación, que se compone de dos elementos fundamentales. Primeramente se describen las técnicas estadísticas aplicadas para el estudio de los datos que, dada la complejidad del análisis, se dividen en tres grupos fundamentales: Método de mínimos cuadrados parciales (PLS, Partial Least Squares): herramienta estadística de análisis multivariante con capacidad de análisis predictivo que se emplea en la determinación de las relaciones estructurales de los modelos propuestos. Análisis multigrupo: conjunto de técnicas que permiten comparar los resultados obtenidos con el método PLS entre dos o más grupos derivados del uso de una o más variables de segmentación. En este caso se emplean cinco métodos de comparación, lo que permite asimismo comparar los rendimientos de cada uno de los métodos. Determinación de segmentos no identificados a priori: en el caso de algunas de las variables de segmentación no existe un criterio de clasificación definido a priori, sino que se obtiene a partir de la aplicación de técnicas estadísticas de clasificación. En este caso se emplean dos técnicas fundamentales: análisis de componentes principales –dado el elevado número de variables empleadas para la clasificación– y análisis clúster –del que se combina una técnica jerárquica que calcula el número óptimo de segmentos, con una técnica por etapas que es más eficiente en la clasificación, pero exige conocer el número de clústeres a priori. La aplicación de dichas técnicas estadísticas sobre los modelos resultantes de considerar los distintos criterios de segmentación, tanto de clientes como de productos, da lugar al análisis de un total de 128 modelos de adopción de comercio electrónico y 65 comparaciones multigrupo, cuyos resultados y principales consideraciones son elaboradas a lo largo del capítulo. Para concluir, el capítulo ocho recoge las conclusiones del trabajo divididas en cuatro partes diferenciadas. En primer lugar se examina el grado de alcance de los objetivos planteados al inicio de la investigación; después se desarrollan las principales contribuciones que este trabajo aporta tanto desde el punto de vista metodológico, como desde los punto de vista teórico y práctico; en tercer lugar, se profundiza en las conclusiones derivadas del estudio empírico, que se clasifican según los criterios de segmentación empleados, y que combinan resultados confirmatorios y exploratorios; por último, el trabajo recopila las principales limitaciones de la investigación, tanto de carácter teórico como empírico, así como aquellos aspectos que no habiendo podido plantearse dentro del contexto de este estudio, o como consecuencia de los resultados alcanzados, se presentan como líneas futuras de investigación. ABSTRACT Favoured by an increase of Internet penetration rates across the globe, electronic commerce has experienced a rapid growth over the last few years. Nevertheless, adoption of electronic commerce has differed from one country to another. On one hand, it has been observed that countries leading e-commerce adoption have a large percentage of Internet users as well as of online purchasers; on the other hand, other markets, despite having a low percentage of Internet users, show a high percentage of online buyers. Halfway between those two ends of the spectrum, we find countries such as Spain which, despite having moderately high Internet penetration rates and similar socio-economic characteristics as some of the leading countries, have failed to turn Internet users into active online buyers. Several theoretical approaches have been taken in an attempt to define the factors that influence the use of electronic commerce systems by customers. One of the betterknown frameworks to characterize adoption factors is the acceptance modelling theory, which is derived from the information systems adoption in organizational environments. These models are based on individual perceptions on which factors determine purchase intention, as a mean to explain users’ actual purchasing behaviour. Even though research on electronic commerce adoption models has increased in terms of volume and scope over the last years, the majority of studies validate their hypothesis by using a single sample of consumers from which they obtain general conclusions. Nevertheless, since the birth of marketing, and more specifically from the second half of the 19th century, differences in consumer behaviour owing to demographic, sociologic and psychological characteristics have also been taken into account. And such differences are generally translated into different needs that can only be satisfied when sellers adapt their offer to their target market. Electronic commerce has a number of features that makes it different when compared to traditional commerce; the best example of this is the lack of physical contact between customers and products, and between customers and vendors. Other than that, some differences that depend on the type of product may also play an important role in electronic commerce. From all the above, the present research aims to address the study of the main factors influencing purchase intention and actual purchase behaviour in electronic commerce by Spanish end-consumers, taking into consideration both the customer group to which they belong and the type of product being purchased. In order to achieve this goal, this Thesis is structured in eight chapters: four theoretical sections, three empirical blocks and a final section summarizing the conclusions derived from the research. The chapters are arranged in sequence as follows: introduction, current state of electronic commerce, technology adoption models, electronic commerce segmentation, preliminary design of the empirical work, research design, data analysis and results, and conclusions. The introductory chapter offers a detailed justification of the relevance of this study in the context of e-commerce adoption research; it also sets out the objectives, methodology and research stages. The second chapter further expands and complements the introductory chapter, focusing on two elements: the concept of electronic commerce and its evolution from a general point of view, and the evolution of electronic commerce in Spain and main indicators of adoption. This section is intended to allow the reader to understand the research context, and also to serve as a basis to justify the relevance and representativeness of the sample used in this study. Chapters three (technology acceptance models) and four (segmentation in electronic commerce) set the theoretical foundations for the study. Chapter 3 presents a thorough literature review of technology adoption modelling, focusing on previous studies on electronic commerce acceptance. As a result of the literature review, the research framework is built upon a model based on UTAUT (Unified Theory of Acceptance and Use of Technology) and its evolution, UTAUT2, including two specific electronic commerce adoption factors: perceived risk and perceived trust. Chapter 4 deals with client and product segmentation methodologies used by experts. From the literature review, a wide range of classification variables is studied, and a shortlist of nine classification variables has been selected for inclusion in the research. The criteria for variable selection were their adequacy to electronic commerce characteristics, as well as adequacy to the sample characteristics. The nine variables have been classified in three groups: socio-demographic (gender, age, education level, income, family size and relationship status), behavioural (experience in electronic commerce and frequency of purchase) and psychographic (online purchase motivations) variables. The second half of chapter 4 is devoted to a review of the product classification criteria in electronic commerce. The review has led to the identification of a final set of fifteen groups of variables, whose combination offered a total of thirty-four possible outputs. However, due to the lack of empirical evidence in the context of electronic commerce, further investigation on the validity of this set of product classifications was deemed necessary. For this reason, chapter 5 proposes an empirical study to test the different product classification variables with 207 samples. A selection of product classifications including only those variables that are objective, able to identify distinct groups and not dependent on consumers’ point of view, led to a final classification of products which consisted on two groups of variables for the final empirical study. The combination of these two groups gave rise to four types of products: digital and non-digital goods, and digital and non-digital services. Chapter six characterizes the research –social, exploratory research– and presents the final research model and research hypotheses. The exploratory nature of the research becomes patent in instances where no prior empirical evidence on the influence of certain segmentation variables was found. Chapter six also includes the description of the measurement instrument used in the research, consisting of a total of 125 questions –and the measurement scales associated to each of them– as well as the description of the sample used for model validation (consisting of 817 Spanish residents). Chapter 7 is the core of the empirical analysis performed to validate the research model, and it is divided into two separate parts: description of the statistical techniques used for data analysis, and actual data analysis and results. The first part is structured in three different blocks: Partial Least Squares Method (PLS): the multi-variable analysis is a statistical method used to determine structural relationships of models and their predictive validity; Multi-group analysis: a set of techniques that allow comparing the outcomes of PLS analysis between two or more groups, by using one or more segmentation variables. More specifically, five comparison methods were used, which additionally gives the opportunity to assess the efficiency of each method. Determination of a priori undefined segments: in some cases, classification criteria did not necessarily exist for some segmentation variables, such as customer motivations. In these cases, the application of statistical classification techniques is required. For this study, two main classification techniques were used sequentially: principal component factor analysis –in order to reduce the number of variables– and cluster analysis. The application of the statistical methods to the models derived from the inclusion of the various segmentation criteria –for both clients and products–, led to the analysis of 128 different electronic commerce adoption models and 65 multi group comparisons. Finally, chapter 8 summarizes the conclusions from the research, divided into four parts: first, an assessment of the degree of achievement of the different research objectives is offered; then, methodological, theoretical and practical implications of the research are drawn; this is followed by a discussion on the results from the empirical study –based on the segmentation criteria for the research–; fourth, and last, the main limitations of the research –both empirical and theoretical– as well as future avenues of research are detailed.

An Empirical Analysis of the Spanish Gas Price Structure

We can say without hesitation that in energy markets a throughout data analysis is crucial when designing sophisticated models that are able to capture most of the critical market drivers. In this study we will attempt to investigate into Spanish natural gas prices structure to improve understanding of the role they play in the determination of electricity prices and decide in the future about price modelling aspects. To further understand the potential for modelling, this study will focus on the nature and characteristics of the different gas price data available. The fact that the existing gas market in Spain does not incorporate enough liquidity of trade makes it even more critical to analyze in detail available gas price data information that in the end will provide relevant information to understand how electricity prices are affected by natural gas markets. In this sense representative Spanish gas prices are typically difficult to explore given the fact that there is not a transparent gas market yet and all the gas imported in the country is negotiated and purchased by private companies at confidential terms.

Desarrollo de un modelo integral de evaluación para instituciones de educación superior y análisis de su impacto en la planificación y gestión institucional

El propósito de esta tesis doctoral es el desarrollo de un modelo integral de evaluación de la gestión para instituciones de educación superior (IES), fundamentado en valorar la gestión de diferentes subsistemas que la integran, así como estudiar el impacto en la planificación y gestión institucional. Este Modelo de Evaluación Institucional fue denominado Modelo Integral de Evaluación de Gestión de las IES (MIEGIES), que incorpora la gestión de la complejidad, los aspectos gerenciales, el compromiso o responsabilidad social, los recursos, además de los procesos propios universitarios con una visión integral de la gestión. Las bases conceptuales se establecen por una revisión del contexto mundial de la educación superior, pasando por un análisis sobre evaluación y calidad en entornos universitarios. La siguiente reflexión conceptual versó sobre la gestión de la complejidad, de la gestión gerencial, de la gestión de responsabilidad social universitaria, de la gestión de los recursos y de la gestión de los procesos, seguida por un aporte sobre modelaje y modelos. Para finalizar, se presenta un resumen teórico sobre el alcance de la aplicación de ecuaciones estructurales para la validación de modelos. El desarrollo del modelo conceptual, dimensiones e indicadores, fue efectuado aplicando los principios de la metodología de sistemas suaves –SSM. Para ello, se identifica la definición raíz (DR), la razón sistémica de ser del modelo, para posteriormente desarrollar sus componentes y principios conceptuales. El modelo quedó integrado por cinco subsistemas, denominados: de la Complejidad, de la Responsabilidad Social Universitaria, Gerencial, de Procesos y de Recursos. Los subsistemas se consideran como dimensiones e indicadores para el análisis y son los agentes críticos para el funcionamiento de una IES. Los aspectos referidos a lo Epistemetodológico, comenzó por identificar el enfoque epistemológico que sustenta el abordaje metodológico escogido. A continuación se identifican los elementos clásicos que se siguieron para llevar a cabo la investigación: Alcance o profundidad, población y muestra, instrumentos de recolección de información y su validación, para finalizar con la explicación procedimental para validar el modelo MIEGIES. La población considerada para el estudio empírico de validación fueron 585 personas distribuidas entre alumnos, docentes, personal administrativo y directivos de una Universidad Pública Venezolana. La muestra calculada fue de 238 individuos, número considerado representativo de la población. La aplicación de los instrumentos diseñados y validados permitió la obtención de un conjunto de datos, a partir de los cuales se validó el modelo MIEGIES. La validación del Modelo MIGEIES parte de sugerencias conceptuales para el análisis de los datos. Para ello se identificaron las variables relevantes, que pueden ser constructos o conceptos, las variables latentes que no pueden ser medidas directamente, sino que requiere seleccionar los indicadores que mejor las representan. Se aplicó la estrategia de modelación confirmatoria de los Modelos de Ecuaciones Estructurales (SEM). Para ello se parte de un análisis descriptivo de los datos, estimando la fiabilidad. A continuación se aplica un análisis factorial exploratorio y un análisis factorial confirmatorio. Para el análisis de la significancia del modelo global y el impacto en la planificación y gestión, se consideran el análisis de coeficientes de regresión y la tabla de ANOVA asociada, la cual de manera global especifica que el modelo planteado permite explicar la relación entre las variables definidas para la evaluación de la gestión de las IES. Así mismo, se encontró que este resultado de manera global explica que en la evaluación institucional tiene mucha importancia la gestión de la calidad y las finanzas. Es de especial importancia destacar el papel que desarrolla la planificación estratégica como herramienta de gestión que permite apoyar la toma de decisiones de las organizaciones en torno al quehacer actual y al camino que deben recorrer en el futuro para adecuarse a los cambios y a las demandas que les impone el entorno. El contraste estadístico de los dos modelos ajustados, el teórico y el empírico, permitió a través de técnicas estadísticas multivariables, demostrar de manera satisfactoria, la validez y aplicación del modelo propuesto en las IES. Los resultados obtenidos permiten afirmar que se pueden estimar de manera significativa los constructos que definen la evaluación de las instituciones de educación superior mediante el modelo elaborado. En el capítulo correspondiente a Conclusiones, se presenta en una de las primeras instancias, la relación conceptual propuesta entre los procesos de evaluación de la gestión institucional y de los cinco subsistemas que la integran. Posteriormente se encuentra que los modelos de ecuaciones estructurales con base en la estrategia de modelación confirmatoria es una herramienta estadística adecuada en la validación del modelo teórico, que fue el procedimiento propuesto en el marco de la investigación. En cuanto al análisis del impacto del Modelo en la Planificación y la Gestión, se concluye que ésta es una herramienta útil para cerrar el círculo de evaluación institucional. La planificación y la evaluación institucional son procesos inherentes a la filosofía de gestión. Es por ello que se recomienda su práctica como de necesario cumplimiento en todas las instancias funcionales y operativas de las Instituciones de Educación Superior. ABSTRACT The purpose of this dissertation is the development of a comprehensive model of management evaluation for higher education institutions (HEIs), based on evaluating the management of different subsystems and study the impact on planning and institutional management. This model was named Institutional Assessment Comprehensive Evaluation Model for the Management of HEI (in Spanish, MIEGIES). The model incorporates the management of complexity, management issues, commitment and social responsibility and resources in addition to the university's own processes with a comprehensive view of management. The conceptual bases are established by a review of the global context of higher education, through analysis and quality assessment in university environments. The following conceptual discussions covered the management of complexity, management practice, management of university social responsibility, resources and processes, followed by a contribution of modeling and models. Finally, a theoretical overview of the scope of application of structural equation model (SEM) validation is presented. The development of the conceptual model, dimensions and indicators was carried out applying the principles of soft systems methodology (SSM). For this, the root definition (RD), the systemic rationale of the model, to further develop their components and conceptual principles are identified. The model was composed of five subsystems, called: Complexity, University Social Responsibility, Management, Process and Resources. The subsystems are considered as dimensions and measures for analysis and are critical agents for the functioning of HEIs. In matters relating to epistemology and methodology we began to identify the approach that underpins the research: Scope, population and sample and data collection instruments. The classic elements that were followed to conduct research are identified. It ends with the procedural explanation to validate the MIEGIES model. The population considered for the empirical validation study was composed of 585 people distributed among students, faculty, staff and authorities of a public Venezuelan university. The calculated sample was 238 individuals, number considered representative of the population. The application of designed and validated instruments allowed obtaining a data set, from which the MIEGIES model was validated. The MIGEIES Model validation is initiated by the theoretical analysis of concepts. For this purpose the relevant variables that can be concepts or constructs were identified. The latent variables cannot be measured directly, but require selecting indicators that best represent them. Confirmatory modeling strategy of Structural Equation Modeling (SEM) was applied. To do this, we start from a descriptive analysis of the data, estimating reliability. An exploratory factor analysis and a confirmatory factor analysis were applied. To analyze the significance of the overall models the analysis of regression coefficients and the associated ANOVA table are considered. This comprehensively specifies that the proposed model can explain the relationship between the variables defined for evaluating the management of HEIs. It was also found that this result comprehensively explains that for institutional evaluation quality management and finance are very important. It is especially relevant to emphasize the role developed by strategic planning as a management tool that supports the decision making of organizations around their usual activities and the way they should evolve in the future in order to adapt to changes and demands imposed by the environment. The statistical test of the two fitted models, the theoretical and the empirical, enabled through multivariate statistical techniques to demonstrate satisfactorily the validity and application of the proposed model for HEIs. The results confirm that the constructs that define the evaluation of HEIs in the developed model can be estimated. In the Conclusions section the conceptual relationship between the processes of management evaluation and the five subsystems that comprise it are shown. Subsequently, it is indicated that structural equation models based on confirmatory modeling strategy is a suitable statistical tool in validating the theoretical model, which was proposed in the framework of the research procedure. The impact of the model in Planning and Management indicates that this is a useful tool to complete the institutional assessment. Planning and institutional assessment processes are inherent in management philosophy. That is why its practice is recommended as necessary compliance in all functional and operational units of HEIs.