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An intelligent ecosystem to support the psychological diagnosis and intervention of children under social vulnerability

Authors :
Estefanía Borck-Vintimilla
Vladimir Robles-Bykbaev
Verónica Cevallos León Wong
A. Pacurucu-Pacurucu
Yenner Pineda-Villa
F. Pesantez-Aviles
Santiago Flores-Andrade
Source :
11th International Symposium on Medical Information Processing and Analysis.
Publication Year :
2015
Publisher :
SPIE, 2015.

Abstract

When children are taken apart from their parents because of many violence situations, they are taken to foster homes, where they share place with kids who have lived similar situations. United Nations Children’s Fund (2014) refer that Children who have been abused or neglected, often may have low self-esteem and other emotional problems, which can lead, at worst, to risky behaviors and self-harm . They also could tend to internalize that behavior, repeating the pattern of violence and abuse as a response to their environment. In this line, the latest estimates provided by SOS Children's Village International show a global complex picture: around 24 million of children in the world live in foster homes, one billion of children live in conflict-affected areas; and, furthermore, there is a lack of mental health professionals in most of the countries. On those grounds, in this paper we propose an intelligent ecosystem to provide support for psychologists during the psychodiagnosis and intervention with children, especially the ones who are in foster homes. Currently, the system is able to automatically determine some psychological traits, according to responses provided by each patient. One part of the diagnostic system is based on two psychological tests: the Draw-A-Person test and the Draw-A-Family test. The results obtained on the first stage let the system establish different challenges according to the skills that the evaluated child needs to develop. Our proposed approach was tested in a population of 124 children (93 school students, and 31 living in shelters), and has achieved encouraging results (80% of precision in patient's profile determination).

Details

ISSN :
0277786X
Database :
OpenAIRE
Journal :
11th International Symposium on Medical Information Processing and Analysis
Accession number :
edsair.doi...........bf00b866b48b5b65ea39b2f688a6a012
Full Text :
https://doi.org/10.1117/12.2211490