Applying information theory to small groups assessment: emotions and well-being at work

• Antonio León García Izquierdo ^[1] ; Blanca Moreno ^[1] ; Mariano García Izquierdo ^[2]
  1. [1] Universidad de Oviedo

     Universidad de Oviedo

     Oviedo, España

     
  2. [2] Universidad de Murcia

     Universidad de Murcia

     Murcia, España

     
• Localización: The Spanish Journal of Psychology, ISSN 1138-7416, Vol. 13, Nº. 1, 2010, págs. 309-328
• Idioma: inglés
• DOI: 10.1017/s1138741600003887
• Enlaces
  • Texto completo
• Dialnet Métricas: 6 Citas
• Resumen
  • español

    En este artículo analizamos las relaciones entre las emociones y el bienestar en una muestra de trabajadores del sector aeronáutico, en concreto de tripulantes de cabina de pasajeros (TCP). De este modo respondemos al creciente papel que las emociones están teniendo en los riesgos psicosociales en el trabajo, de modo que pueden influir como agentes facilitadotes o como amortiguadores. Dado que la mayoría de las empresas en Europa poseen una plantilla media de pequeño tamaño, la aplicación de las técnicas paramétricas habituales presenta fuertes limitaciones a la hora de estimar los coeficientes que indican la relación entre las variables. En consecuencia, hemos optado por la aplicación del principio de la máxima entropía de la teoría de la información, que ha permitido obtener unas estimaciones óptimas sacando el máximo provecho a la escasa información disponible. Asimismo, los resultados son coherentes con la investigación previa, lo que comprueba su adecuación y hace que sea un procedimiento recomendable para los casos similares.

  • English

    This paper explores and analyzes the relations between emotions and well-being in a sample of aviation personnel, passenger crew (flight attendants). There is an increasing interest in studying the influence of emotions and its role as psychosocial factors in the work environment as they are able to act as facilitators or shock absorbers. The contrast of the theoretical models by using traditional parametric techniques requires a large sample size to the efficient estimation of the coefficients that quantify the relations between variables. Since the available sample that we have is small, the most common size in European enterprises, we used the maximum entropy principle to explore the emotions that are involved in the psychosocial risks. The analyses show that this method takes advantage of the limited information available and guarantee an optimal estimation, the results of which are coherent with theoretical models and numerous empirical researches about emotions and well-being.

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