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Modelo G-DINA aplicado al diagnóstico de desórdenes mentales

Authors: Villena Guzmán, Denisse;

Modelo G-DINA aplicado al diagnóstico de desórdenes mentales

Abstract

Actualmente, uno de los modelos de diagnóstico cognitivo (MDC) más usados es el modelo DINA. Sin embargo, este modelo presenta varias restricciones que hacen que en muchas ocasiones, no sea el que mejor se ajusta a la realidad. En ese contexto, nace una generalización del modelo DINA, denominado G-DINA (Generalized deterministic input, noisy and gate). En el presente estudio se presentan los fundamentos y propiedades del modelo G-DINA y su aplicación en un área en el que su uso todavía no es muy común: la psicología. Así, se evaluaron los resultados de una muestra de pacientes de un hospital general de Lima a los que se les aplicó el test SRQ-18 que evalúa la presencia de desórdenes mentales. Se muestra el proceso de selección del mejor modelo para cada ítem, los resultados de los parámetros obtenidos, los diagnósticos para los 10 primeros pacientes y una distribución de los perfiles de estos pacientes. Finalmente se presenta un estudio de simulación que tiene por finalidad estudiar el efecto del tamaño de muestra en la estimación de los parámetros en el contexto de la aplicación de este estudio.

Country
Peru
Keywords

Estimación, Psicometría, https://purl.org/pe-repo/ocde/ford#1.01.03, Enfermedades mentales--Diagnóstico, Estimación de parámetros

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green