Estudio exploratorio de evaluación de ideación suicida en pacientes oncológicos
Tesis Materias > Psicología Universidad Europea del Atlántico > Docencia > Trabajos finales de Grado Cerrado Español La motivación de este trabajo se desarrolla desde el interés y análisis encauzado dentro del ámbito psicooncológico. Más específicamente, el estudio se enfoca en explorar la ideación suicida en población con diagnóstico oncológico. Cabe destacar que, además, debido al escenario actual de incertidumbre que se vive a nivel mundial a raíz de la COVID-19, la inestabilidad psicológica y emocional generada, ha hecho emerger una evidente y explícita construcción social de vulnerabilidad, provocando un aumento de casos orientados a la ideación y acto suicida en la sociedad. Esta situación se agrava aún más, ya que durante los últimos años encontramos que, en España, los medios de comunicación exhiben un solapado déficit en cuanto a la estructura informativa y abordaje de los suicidios. El resultado, origina un profundo estigma social y ostracismo en torno a todas aquellas personas involucradas con la ideación o el acto suicida. Frente a estos agravantes, en el contexto clínico oncológico, la sobrecarga psicológica y emocional a la que se encuentran sometidos enfermos en la larga duración de los tratamientos y su vulnerable condición crónica, generalmente promueve un replanteo en su condición de ser y resignificación de su actual experiencia de vida. Estas reformulaciones también pueden sesgar el estilo funcional de afrontamiento de la enfermedad, afectando su percepción de futuro y derecho a la vida. Por tales motivos, el presente trabajo intentará explorar la posible existencia de ideación suicida en el paciente oncológico terminal y con pronóstico favorable, analizando también el grado de intensidad de la misma. metadata Eremián Pérez, Marcelo mail marcelo.eremian@master.uneatlantico.es (2022) Estudio exploratorio de evaluación de ideación suicida en pacientes oncológicos. Diploma thesis, Universidad Europea del Atlántico.
Texto completo no disponible.Resumen
La motivación de este trabajo se desarrolla desde el interés y análisis encauzado dentro del ámbito psicooncológico. Más específicamente, el estudio se enfoca en explorar la ideación suicida en población con diagnóstico oncológico. Cabe destacar que, además, debido al escenario actual de incertidumbre que se vive a nivel mundial a raíz de la COVID-19, la inestabilidad psicológica y emocional generada, ha hecho emerger una evidente y explícita construcción social de vulnerabilidad, provocando un aumento de casos orientados a la ideación y acto suicida en la sociedad. Esta situación se agrava aún más, ya que durante los últimos años encontramos que, en España, los medios de comunicación exhiben un solapado déficit en cuanto a la estructura informativa y abordaje de los suicidios. El resultado, origina un profundo estigma social y ostracismo en torno a todas aquellas personas involucradas con la ideación o el acto suicida. Frente a estos agravantes, en el contexto clínico oncológico, la sobrecarga psicológica y emocional a la que se encuentran sometidos enfermos en la larga duración de los tratamientos y su vulnerable condición crónica, generalmente promueve un replanteo en su condición de ser y resignificación de su actual experiencia de vida. Estas reformulaciones también pueden sesgar el estilo funcional de afrontamiento de la enfermedad, afectando su percepción de futuro y derecho a la vida. Por tales motivos, el presente trabajo intentará explorar la posible existencia de ideación suicida en el paciente oncológico terminal y con pronóstico favorable, analizando también el grado de intensidad de la misma.
Tipo de Documento: | Tesis (Diploma) |
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Palabras Clave: | ideación suicida, oncología, psicología oncológica, psicooncología |
Clasificación temática: | Materias > Psicología |
Divisiones: | Universidad Europea del Atlántico > Docencia > Trabajos finales de Grado |
Depositado: | 20 Dic 2022 23:30 |
Ultima Modificación: | 20 Dic 2022 23:30 |
URI: | https://repositorio.uneatlantico.es/id/eprint/4727 |
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The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria.
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Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%.
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