Prevalencia de estrés académico, factores de riesgo y su relación con el rendimiento académico en los estudiantes de la escuela de medicina de la Universidad de Cuenca en el 2015

La Escuela de Medicina de la Universidad de Cuenca ha sido reconocida por sus logros y trayectoria deviniendo en una de las facultades más prestigiosas del Ecuador, este renombre ha sido el resultado de la excelente preparación académica que los docentes aplican en sus alumnos que si bien ha dado buenos resultados esta preparación pudiese exceder el umbral de tolerancia del alumno y generar lo que hoy en día se conoce como “Estrés Académico”. El presente estudio es descriptivo, cuantitativo y transversal, el mismo se conformó con una muestra de 285 alumnos de la Facultad desde primero hasta décimo ciclo. El objetivo del estudio fue determinar la prevalencia de Estrés Académico, sus Factores de Riesgo y la influencia del Estrés Académico sobre el Rendimiento Académico de los estudiantes de la Escuela de Medicina de la Universidad de Cuenca según el I.E.A (Inventario de Estrés Académico) modificado, desde primero hasta décimo ciclo en el año 2015. Resultados: La prevalencia de estrés académico en los estudiantes de medicina de la Universidad de Cuenca es del 91.58%, de estos el 46.7% se ubicó en un nivel moderado de intensidad, seguido del 36.48% quienes se ubicaron en una intensidad alta. El total de prevalencia de estrés académico en mujeres es del 95.45% sobrepasando al sexo masculino el cual demostró una prevalencia de 85.32%. Niveles altos de estrés académico se ven asociados significativamente con un rendimiento académico bajo. Conclusión: La prevalencia de Estrés Académico es alta y su nivel de intensidad es moderada, su intensidad alta se asocia significativamente a un rendimiento académico bajo, siendo las mujeres más susceptibles a sufrir estrés académico

Optimal resource allocation and budgeting in libraries

Libraries since their inception 4000 years ago have been in a process of constant change. Although, changes were in slow motion for centuries, in the last decades, academic libraries have been continuously striving to adapt their services to the ever-changing user needs of students and academic staff. In addition, e-content revolution, technological advances, and ever-shrinking budgets have obliged libraries to efficiently allocate their limited resources among collection and services. Unfortunately, this resource allocation is a complex process due to the diversity of data sources and formats required to be analyzed prior to decision-making, as well as the lack of efficient integration methods. The main purpose of this study is to develop an integrated model that supports libraries in making optimal budgeting and resource allocation decisions among their services and collection by means of a holistic analysis. To this end, a combination of several methodologies and structured approaches is conducted. Firstly, a holistic structure and the required toolset to holistically assess academic libraries are proposed to collect and organize the data from an economic point of view. A four-pronged theoretical framework is used in which the library system and collection are analyzed from the perspective of users and internal stakeholders. The first quadrant corresponds to the internal perspective of the library system that is to analyze the library performance, and costs incurred and resources consumed by library services. The second quadrant evaluates the external perspective of the library system; user’s perception about services quality is judged in this quadrant. The third quadrant analyses the external perspective of the library collection that is to evaluate the impact of the current library collection on its users. Eventually, the fourth quadrant evaluates the internal perspective of the library collection; the usage patterns followed to manipulate the library collection are analyzed. With a complete framework for data collection, these data coming from multiple sources and therefore with different formats, need to be integrated and stored in an adequate scheme for decision support. A data warehousing approach is secondly designed and implemented to integrate, process, and store the holistic-based collected data. Ultimately, strategic data stored in the data warehouse are analyzed and implemented for different purposes including the following: 1) Data visualization and reporting is proposed to allow library managers to publish library indicators in a simple and quick manner by using online reporting tools. 2) Sophisticated data analysis is recommended through the use of data mining tools; three data mining techniques are examined in this research study: regression, clustering and classification. These data mining techniques have been applied to the case study in the following manner: predicting the future investment in library development; finding clusters of users that share common interests and similar profiles, but belong to different faculties; and predicting library factors that affect student academic performance by analyzing possible correlations of library usage and academic performance. 3) Input for optimization models, early experiences of developing an optimal resource allocation model to distribute resources among the different processes of a library system are documented in this study. Specifically, the problem of allocating funds for digital collection among divisions of an academic library is addressed. An optimization model for the problem is defined with the objective of maximizing the usage of the digital collection over-all library divisions subject to a single collection budget. By proposing this holistic approach, the research study contributes to knowledge by providing an integrated solution to assist library managers to make economic decisions based on an “as realistic as possible” perspective of the library situation.