Personality patterns predict the risk of antisocial behavior in Spanish-speaking adolescents.

INTRODUCTION: There is a renewed interest in incorporating personality variables in criminology theories in order to build models able to integrate personality variables and biological factors with psychosocial and sociocultural factors. The aim of this article is the assessment of personality dimensions that contribute to the prediction of antisocial behavior in adolescents. METHODS: For this purpose, a sample of adolescents from El Salvador, Mexico, and Spain was obtained. The sample consisted of 1035 participants with a mean age of 16.2. There were 450 adolescents from a forensic population (those who committed a crime) and 585 adolescents from the normal population (no crime committed). All of participants answered personality tests about neuroticism, extraversion, psychoticism, sensation seeking, impulsivity, and violence risk. RESULTS: Principal component analysis of the data identified two independent factors: (i) the disinhibited behavior pattern (PDC), formed by the dimensions of neuroticism, psychoticism, impulsivity and risk of violence; and (ii) the extrovert behavior pattern (PEC), formed by the dimensions of sensation risk and extraversion. Both patterns significantly contributed to the prediction of adolescent antisocial behavior in a logistic regression model which properly classifies a global percentage of 81.9%, 86.8% for non-offense and 72.5% for offense behavior. CONCLUSIONS: The classification power of regression equations allows making very satisfactory predictions about adolescent offense commission. Educational level has been classified as a protective factor, while age and gender (male) have been classified as risk factors.

Los patrones de personalidad predicen el riesgo de la conducta antisocial en adolescentes hispanohablantes / Personality patterns predict the risk of antisocial behavior in Spanish-speaking adolescents

Introducción. En los últimos años existe un renovado interés por incorporar las variables de personalidad en las teorías criminológicas para construir modelos que integren variables de personalidad y factores biológicos con factores psicosociales y socioculturales. Recientes estudios revelan que las relaciones entre dimensiones de personalidad y delincuencia podrían representar un continuo dentro de las conductas antisociales. El objetivo del presente estudio ha sido la evaluación de las dimensiones de personalidad que contribuyan a la predicción de la conducta antisocial de los adolescentes. Metodología. Para ello se obtuvo una muestra de adolescentes de El Salvador, México y España formada por 1035 participantes con una edad media de 16,2 años. Los adolescentes que han cometido delito han sido 450 y los que no lo han cometido han sido 585. Todos los participantes contestaron cuestionarios de personalidad que miden las dimensiones de neuroticismo, extraversión, psicoticismo, búsqueda de sensaciones, impulsividad y riesgo de violencia. Resultados. El patrón desinhibido de conducta (PDC) se forma con las dimensiones de neuroticismo, psicoticismo, impulsividad y riesgo de violencia. El patrón extravertido de conducta (PEC) se forma con las dimensiones de búsqueda de sensaciones y extraversión. Ambos patrones permiten predecir la conducta antisocial de los adolescentes mediante un modelo de regresión logística que clasifica correctamente un porcentaje global del 81,9%, siendo para el caso del no delito 86,8% y en el caso de delito 72,5%. Conclusiones. Se establecieron relaciones entre el nivel educativo, la edad, el género y la conducta antisocial. De forma que el nivel educativo resulta como un factor de protección y la edad y el género masculino como factores de riesgo para la conducta antisocial (AU)

Introduction. There is a renewed interest in incorporating personality variables in criminology theories in order to build models able to integrate personality variables and biological factors with psychosocial and sociocultural factors. The aim of this article is the assessment of personality dimensions that contribute to the prediction of antisocial behavior in adolescents. Methods. For this purpose, a sample of adolescents from El Salvador, Mexico, and Spain was obtained. The sample consisted of 1035 participants with a mean age of 16.2. There were 450 adolescents from a forensic population (those who committed a crime) and 585 adolescents from the normal population (no crime committed). All of participants answered personality tests about neuroticism, extraversion, psychoticism, sensation seeking, impulsivity, and violence risk. Results. Principal component analysis of the data identified two independent factors: (II) the disinhibited behavior pattern (PDC), formed by the dimensions of neuroticism, psychoticism, impulsivity and risk of violence; and (ii) the extrovert behavior pattern (PEC), formed by the dimensions of sensation risk and extraversion. Both patterns significantly contributed to the prediction of adolescent antisocial behavior in a logistic regression model which properly classifies a global percentage of 81.9%, 86.8% for non-offense and 72.5% for offense behavior. Conclusions. The classification power of regression equations allows making very satisfactory predictions about adolescent offense commission. Educational level has been classified as a protective factor, while age and gender (male) have been classified as risk factors (AU)

Mean structure analysis from an IRT approach: an application in the context of organizational psychology / Análisis de estructura de medias mediante un modelo TRI: una aplicación en el contexto de la psicología de las organizaciones

The application of mean and covariance structure analysis with quantitative data is increasing. However, latent means analysis with qualitative data is not as widespread. This article summarizes the procedures to conduct an analysis of latent means of dichotomous data from an item response theory approach. We illustrate the implementation of these procedures in an empirical example referring to the organizational context, where a multi-group analysis was conducted to compare the latent means of three employee groups in two factors measuring personal preferences and the perceived degree of rewards from the organization. Results show that higher personal motivations are associated with higher perceived importance of the organization, and that these perceptions differ across groups, so that higher-level employees have a lower level of personal and perceived motivation. The article shows how to estimate the factor means and the factor correlation from dichotomous data, and how to assess goodness of fi t. Lastly, we provide the M-Plus syntax code in order to facilitate the latent means analyses for applied researchers (AU)

La aplicación de modelos de análisis de estructura de medias y covarianzas en datos cuantitativos está extendiéndose. Sin embargo, el análisis de medias latentes a partir de datos cualitativos es menos habitual. Este artículo resume los procedimientos para llevar a cabo un análisis de estructura de medias latentes con ítems dicotómicos desde un enfoque de la teoría de respuesta al ítem. Se ilustra la implementación de dichos procedimientos en un ejemplo con datos empíricos referidos al contexto organizacional, donde se lleva a cabo un análisis multi-grupo para comparar las medias latentes de tres grupos de empleados en dos factores que miden preferencias personales y el grado percibido en que la organización las refuerza. Los resultados indican que a mayor motivación personal, se necesita mayor refuerzo por parte de la organización, y que existen diferencias entre grupos, ocurriendo que los empleados que ocupan posiciones más altas tienen menor nivel de motivaciones personales y organizacionales. El artículo muestra cómo estimar las medias y correlaciones de los factores de ítems dicotómicos, y cómo evaluar la bondad de ajuste. Por último, se muestra la sintaxis M-Plus para facilitar la aplicación de este tipo de análisis a los investigadores AU)

Mean structure analysis from an IRT approach: an application in the context of organizational psychology.

The application of mean and covariance structure analysis with quantitative data is increasing. However, latent means analysis with qualitative data is not as widespread. This article summarizes the procedures to conduct an analysis of latent means of dichotomous data from an item response theory approach. We illustrate the implementation of these procedures in an empirical example referring to the organizational context, where a multi-group analysis was conducted to compare the latent means of three employee groups in two factors measuring personal preferences and the perceived degree of rewards from the organization. Results show that higher personal motivations are associated with higher perceived importance of the organization, and that these perceptions differ across groups, so that higher-level employees have a lower level of personal and perceived motivation. The article shows how to estimate the factor means and the factor correlation from dichotomous data, and how to assess goodness of fit. Lastly, we provide the M-Plus syntax code in order to facilitate the latent means analyses for applied researchers.

Requerimientos, afiliaciones e investigación en test adaptativos informatizados / Requeriments, applications and research on computerized adaptative testing

En este trabajo se resumen los principales requerimientos y aplicaciones de un Test Adaptativo Informatizado (TAI). Se comentan las principales diferencias entre los Test Convencionales Informatizados y los TAIs, tanto en relación a los modelos psicométricos en que se sustentan como en las diferentes estrategias de presentación de ítems y estimación de los niveles de habilidad. Se describen además los principales resultados obtenidos por nuestro grupo de investigación, que ha desarrollado un conjunto de programas para la aplicación adaptativa de bancos de ítems, un TAI para evaluar el nivel de vocabulario inglés, y que además han realizado varios estudios para resolver algunos de los problemas técnicos y aplicados que presentan este tipo de pruebas (AU)