Valoración de la Credibilidad del TestimonioAplicación del Modelo Reality Monitoring

  1. Soto, María José Valverde
  2. Hernández, José Antonio Ruiz
  3. Estéban, Bartolomé Llor
Revista:
Revista Internacional de Psicología

ISSN: 1818-1023

Año de publicación: 2013

Volumen: 12

Número: 2

Tipo: Artículo

DOI: 10.33670/18181023.V12I02.68 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Revista Internacional de Psicología

Objetivos de desarrollo sostenible

Resumen

In order to administer justice, throughout History, some procedures about Statement Content Analysis have been developed to help the investigators to determine the credibility of a statement: the well-known CBCA, the Reality Monitoring model, or the SCAN tool. Being aware of the huge number of investigations about the CBCA tool and the limited information about the SCAN technique, in this study we decided to analyze the capability of the Reality Monitoring approach setting out this question: ¿How could the Reality Monitoring model contribute to the Statement Credibility Assessment in the context of Forensic Psychology? To answer this question we suggest two objectives: (1) establish the validity of the Reality Monitoring model as a tool for discriminate between truthful and false statements and, (2) determine which combination of the Reality Monitoring's criteria is the most useful for the Statement Credibility Analysis. According to the theoretical foundations from Johnson and Raye's paper (1981), we designed an empirical investigation, with 40 young participants, in which we evaluated the differences between some truthful and false accounts using the Sporer and Kuepper's JMCQ (1995, 2004). The main results show that the Reality Monitoring tool could determinate the level of a statement's credibility above the level of change, being more useful in detecting true than false events. We can conclude that the Reality Monitoring model could be established as a tool to support the Statement Credibility Assessment, but it can't be used as a final tool to discriminate between truthful and false accounts.