Acogimiento en familia extensa: un estudio desde la perspectiva de los acogedores, de los niños y niñas acogidos y de los profesionales que intervienen. = Kinship foster care: a study from the perspective of the caregivers, the children and the child welfare workers

Desde hace aproximadamente dos décadas, en la mayoría de los países occidentales, los acogimientos en familia extensa han entrado a formar parte de los sistemas de protección infantil, siguiendo una evolución creciente en cuanto a número y peso especifico como recurso de acogimiento. Las investigaciones sobre este fenómeno son aún recientes y escasas como también lo son los programas dirigidos a esta población. En el presente artículo presentamos los resultados de un estudio descriptivo sobre los acogimientos en familia extensa en la ciudad de Barcelona, donde se recogen datos de los principales agentes implicados en este fenómeno. Desde la perspectiva de los estudios de la calidad de vida se analizan las percepciones, evaluaciones, y satisfacción expresada, por parte de los acogedores, los niños/as acogidos y los profesionales de los Equipos de Atención a la Infancia y Adolescencia (EAIA) que se encargan del estudio y seguimiento de estos acogimientos. La investigación presenta unos resultados acordes con los estudios que actualmente se realizan en este ámbito y sienta las bases para el despliegue futuro de programas dirigidos a los acogimientos en familia extensa

Kinship foster care: a study from the perspective of the of the caregivers, the children and the child welfare workers

In the last twenty years, in most Western countries, kinship foster care has become an integral part of childcare systems, growing progressively with regard to the numbers of children involved and relative weight as a care resource within the system; indeed, in some countries it is even more common than other placement options, such as non-kinship foster care and residential care. Research on this phenomenon is still recent and scarce, and there are few programmes targeting this population. In this article we present the results of a descriptive study on kinship foster care in the city of Barcelona, including information and data from the different stakeholders involved. From a quality of life research perspective we analyze the perceptions, evaluation and expressed satisfaction of caregivers, children and practitioners from the specialist Child and Adolescent Teams (EAIAs) responsible for the study and follow-up of kinship foster care cases. The research presented results are in line with those of current research in this field, and lays the basis for the future development of kinship foster care programmes

Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach