Oscar E. Cariceo

Publications

1 Effects of Polyvictimization in Suicidal Ideation among Children and Adolescents in Chile

Authors: Oscar E. Cariceo

Abstract:

In Chile, there is a lack of evidence about the impact of polyvictimization on the emergence of suicidal thoughts among children and young people. Thus, this study aims to explore the association between the episodes of polyvictimization suffered by Chilean children and young people and the manifestation of signs related to suicidal tendencies. To achieve this purpose, secondary data from the First Polyvictimization Survey on Children and Adolescents of 2017 were analyzed, and a binomial logistic regression model was applied to establish the probability that young people are experiencing suicidal ideation episodes. The main findings show that women between the ages of 13 and 15 years, who are in seventh grade and second in subsidized schools, are more likely to express suicidal ideas, which increases if they have suffered different types of victimization, particularly physical violence, psychological aggression, and sexual abuse.

Keywords: suicidal ideation, Youth, Chile, polyvictimization

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Abstracts

3 Effects of Polyvictimization in Suicidal Ideation among Children and Adolescents in Chile

Authors: Oscar E. Cariceo

Abstract:

In Chile, there is a lack of evidence about the impact of polyvictimization on the emergence of suicidal thoughts among children and young people. Thus, this study aims to explore the association between the episodes of polyvictimization suffered by Chilean children and young people and the manifestation of signs related to suicidal tendencies. To achieve this purpose, secondary data from the First Polyvictimization Survey on Children and Adolescents of 2017 were analyzed, and a binomial logistic regression model was applied to establish the probability that young people are experiencing suicidal ideation episodes. The main findings show that women between the ages of 13 and 15 years, who are in seventh grade and second in subsidized schools, are more likely to express suicidal ideas, which increases if they have suffered different types of victimization, particularly physical violence, psychological aggression, and sexual abuse.

Keywords: suicidal ideation, Youth, Chile, polyvictimization

Procedia PDF Downloads 35
2 Machine Learning Techniques to Predict Cyberbullying and Improve Social Work Interventions

Authors: Oscar E. Cariceo, Claudia V. Casal

Abstract:

Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: Machine Learning, Social Work Research, Evidence Based Practice, Cyberbullying

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1 Chilean Social Work Students and Their Options to Access to College Financial Aid: Policy Implications on Equity and Professional Training

Authors: Oscar E. Cariceo

Abstract:

In Chile, social workers´ professional training is developed in the undergraduate level, mainly. Despite the fact that several schools have been launched Master of Social Work programs, the Bachelor in Social Work is the minimum qualification to start a professional career. In the current Chilean higher education system, there exist different financial aid options in order to guarantee equal access to higher education. These policies, which are student loans and scholarships, basically, are applied and distributed by Government agencies. They are linked to academic performance and socio-economic needs, in terms of standardized test scores and social vulnerability criteria. In addition, institutions that enroll students with high scores, also receive direct financial support. In other words, social work students must compete for the resources to pay for college tuitions and fees with other students from different programs and knowledge fields and, as a consequence, they can indirectly enhance schools´ money income. This work aims to describe the reality of social work students to access to financial aid in Chile. The analysis presents the results of the University Selection Test of students, who were accepted in social work undergraduate programs during 2014 related to their qualifications to apply to three main financial aid programs, and their contribution to attracting resources to their schools. In general, data show that social work students participate in a low proportion in the distribution of financial aid, both student loans and scholarships. Few of them reach enough scores to guarantee direct financial resources to their institutions. Therefore, this situation has deep implications on equal access to higher education for vulnerable students and affects equal access to training options for young social workers, due to the highly competitive financial aid system.

Keywords: Higher Education, Social Work, Equity, professional training, financial aid

Procedia PDF Downloads 176