Salutogénesis, sanación y curación

Introducció n: En salud aún prevalece, a escala mundial, el modelo patogénico, el cual acentúa la etiopatogenia de la enfermedad, la curación o rehabilitación. Progresivamente se viene introduciendo el modelo de salutogénesis, que preconiza la importancia de la prevención primaria, el bienestar y la sanidad. El objetivo del artículo consiste en argumentar los nexos entre salutogénesis, curación y sanación, como categorías conectadas a la condición saludable de los sujetos, tomándose como fuente de sustentación el criterio de profesionales de la salud y la consulta de fuentes bibliográficas acreditadas acerca de la temática. Material y métodos: Se emplearon métodos y técnicas teóricos, empíricos y estadísticos. La sistematización teórica permitió caracterizar y relacionar los procesos de salutogénesis, curación y sanación. Se aplicó un cuestionario en línea a profesionales vinculados con el sector de la salud para indagar acerca de las categorías de sanación y curación, de los que se obtuvo respuesta de 35 especialistas. Los datos fueron procesados mediante la estadística descriptiva. Resultados: La exploración develó algunas diferencias y semejanzas entre los procesos curativo y sanador; destacándose el carácter más restringido del primero; en tanto la metodología más versátil y creativa, el carácter transformador y los efectos más duraderos del segundo. Se advierte que el nivel de dominio relativo a ambos procesos no es suficientemente extendido ni notorio, como se requeriría para una labor asistencial más efectiva.

Introduction: In health, the pathogenic model still prevails worldwide, which emphasizes the etiopathogenesis of the disease, cure or rehabilitation. The salutogenesis model has been progressively introduced, which advocates the importance of primary prevention, well-being and health. The objective of the article is to argue the links between salutogenesis, healing and curing, as categories connected to the healthy condition of the subjects, taking as a source of support the criteria of health professionals and the consultation of accredited bibliographic sources on the subject. Material and method: Theoretical, empirical and statistical methods and techniques were used. The theoretical systematization allowed to characterize and relate the processes of salutogenesis, healing and curing. An online questionnaire was applied to professionals linked to the health sector to inquire about the categories of healing and curing, from which responses were obtained from 35 specialists. The data was processed using descriptive statistics. Results: The exploration revealed some differences and similarities between the curative and healing processes; highlighting the more restricted character of the first; as the most versatile and creative methodology, the transformative character and the most lasting effects of the latter. It is noted that the level of mastery related to both processes is not sufficiently widespread or notorious, as would be required for a more effective care work.

Forecasting of the unknown end-of-life tire flow for control and decision making in urban solid waste management: A case study.

Efficient urban planning requires managers' experience and knowledge of reverse logistics in solid urban waste processes. Forecasting tools are needed to control, select and manage municipal solid waste. This paper presents the application of dynamic modeling approaches, namely, a linear autoregressive seasonal model, a model based on a FeedForward Artificial Neural Network and a Recurrent Neural Networks model, in order to forecast the unknown flows of end-of-life tires 12 months ahead. The models were identified using a database comprising four years of historical series related to the unknown flows of end-of-life tires. These were obtained through an exploratory analysis based on the annual sales reports of new tires issued by the Brazilian Institute of Geography and Statistics and reports related to the number of vehicles in circulation issued by Brazil's National Traffic Department. The results show that the models are able to carry out consistent forecasts over the horizon of a year ahead and the predictions are capable of identifying seasonalities and supporting decision making in urban waste management.