Browsing by Author "Moya Dabed, Claudia Andrea"

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    ¿Por Qué No Me Suicidaría? Comparación Entre Pacientes Hospitalizados en un Servicio de Psiquiatría con Distinta Conducta Suicida
    (2015) Echavárri Vesperinas, María Orietta; Morales Silva, Susana; Bedregal, Paula; Barros Beck, Jorge Alejandro; Maino, María de la Paz; Fischman, Ronit; Peñaloza, Fernanda; Moya Dabed, Claudia Andrea
    Se presenta un estudio exploratorio transversal de factores asociados al riesgo suicida en 193 pacientes hospitalizados en Chile. La muestra intencionada incluyó grupos de pacientes con: (a) intento de suicidio, (b) ideación suicida y (c) otras causas psiquiátricas sin manifestación suicida. Por medio de c2, prueba de diferencia de proporciones y ANOVA, fueron comparados según el diagnóstico psiquiátrico y de la personalidad y las razones para vivir. Los resultados confirman la alta asociación entre trastorno del ánimo y de la personalidad límite con manifestaciones suicidas. Se utilizó la Escala Reasons for Living que, aunque no está validada en Chile, mostró que el grupo sin manifestación suicida presenta mayor cantidad de razones para vivir; el grupo con intento de suicidio le otorga mayor importancia a motivos relacionados con el cuidado de amigos cercanos y el grupo con ideación suicida le otorga mayor importancia al miedo a fallar en el intento e ir al infierno. Esto indicaría que existen motivos disuasivos de la conducta suicida que podrían diferenciar una población clínica con menor y mayor riesgo suicida.
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    Recognizing states of psychological vulnerability to suicidal behavior: a Bayesian network of artificial intelligence applied to a clinical sample
    (2020) Barros Beck, Jorge Alejandro; Morales Silva, Susana; Echavárri Vesperinas, María Orietta; Szmulewicz Espinosa, Marta Adelina; Núñez, Catalina; García, Arnol; Fischman, Ronit; Moya Dabed, Claudia Andrea; Tomicic S., Alemka
    Abstract Background This study aimed to determine conditional dependence relationships of variables that contribute to psychological vulnerability associated with suicide risk. A Bayesian network (BN) was developed and applied to establish conditional dependence relationships among variables for each individual subject studied. These conditional dependencies represented the different states that patients could experience in relation to suicidal behavior (SB). The clinical sample included 650 mental health patients with mood and anxiety symptomatology. Results Mainly indicated that variables within the Bayesian network are part of each patient’s state of psychological vulnerability and have the potential to impact such states and that these variables coexist and are relatively stable over time. These results have enabled us to offer a tool to detect states of psychological vulnerability associated with suicide risk. Conclusion If we accept that suicidal behaviors (vulnerability, ideation, and suicidal attempts) exist in constant change and are unstable, we can investigate what individuals experience at specific moments to become better able to intervene in a timely manner to prevent such behaviors. Future testing of the tool developed in this study is needed, not only in specialized mental health environments but also in other environments with high rates of mental illness, such as primary healthcare facilities and educational institutions.