Optimizing CBCA and RM research: recommendations for analyzing and reporting data on content cues to deception
For more than a century, verbal content cues to deception have been investigated to assess the credibility of statements in judicial contexts. Among the many cues investigated, Criteria-based Content Analysis (CBCA) and criteria based on the reality monitoring (RM) approach have been most prominent....
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| Otros Autores: | ; |
| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2021
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| En: |
Psychology, crime & law
Año: 2021, Volumen: 27, Número: 1, Páginas: 1-39 |
| Acceso en línea: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | Gargar...
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| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | For more than a century, verbal content cues to deception have been investigated to assess the credibility of statements in judicial contexts. Among the many cues investigated, Criteria-based Content Analysis (CBCA) and criteria based on the reality monitoring (RM) approach have been most prominent. However, research with these cues used as ‘tools’ has not fully exploited their potential. We critically discuss statistical approaches used in past research and recommend a series of 12 principles or guidelines researchers should follow to design, analyze and report future studies on detecting deception with verbal content cues. To illustrate some of these points, we present analyses from two separate studies: A quasi-experiment in a field setting conducted with adults with intellectual disabilities who truthfully or deceptively described a negative autobiographical event to an interviewer, and a large-scale simulation study where adults wrote an account of either an experienced or an invented significant life event. Accounts in both studies were rated with CBCA and RM criteria, as well as by ‘naive’ raters. The guidelines should help to increase the quality and transparency of research in this area. |
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| ISSN: | 1477-2744 |
| DOI: | 10.1080/1068316X.2020.1757097 |