Do people detect deception the way they think they do? Replication and extensions

  1. Nuria Sánchez 1
  2. Jaume Masip 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revista:
Psicothema

ISSN: 0214-9915,  1886-144X

Año de publicación: 2020

Volumen: 32

Número: 3

Páginas: 329-336

Tipo: Artículo

DOI: 10.7334/PSICOTHEMA2019.405 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Psicothema

Objetivos de desarrollo sostenible

Resumen

Antecedentes: la investigación muestra que las personas creen que la mentira se detecta a partir de claves conductuales pese a haber detectado mentiras en el pasado a partir de información contextual (evidencias, información de terceros...). En dicha investigación previa, la pregunta sobre creencias ha sido general, mientras que la referente a información reveladora ha sido sobre una mentira concreta. Este estudio resuelve este problema. Método: los participantes indicaron cómo creían que se pueden detectar mentiras (creencias; Cuestionario 1 o C1). Luego describieron cómo, en el pasado, habían descubierto una mentira, varias mentiras, o cómo, en general, suelen detectar mentiras en su vida cotidiana (información reveladora; C2). Resultados: independientemente de la modalidad de C2, y en línea con la investigación previa, las claves conductuales se mencionaron menos, y los indicadores contextuales más, al responder a C2 que a C1. Sin embargo, se mencionaron más indicios conductuales que contextuales incluso en C2. Conclusiones: no hallamos evidencia de que el foco específico o general de las preguntas cambiara el patrón de resultados, que al parecer dependió solo de si se mencionaban creencias o información reveladora. Ofrecemos explicaciones para la prevalencia de claves conductuales en C2 y hacemos sugerencias para la investigación futura.

Referencias bibliográficas

  • Blair, J. P., Levine, T. R., & Shaw, A. S. (2010). Content in context improves deception detection accuracy. Human Communication Research, 36, 423-442. https://doi.org/10.1111/j.1468-2958.2010.01382.x
  • Blair, J. P., Levine, T. R., Reimer, T. O., & McCluskey, J. D. (2012). The gap between reality and research. Another look at detecting deception in field settings. Policing: An International Journal, 35, 723-740. https://doi.org/10.1108/13639511211275553
  • Blair, J. P., Reimer, T. O., & Levine, T. R. (2018). The role of consistency in detecting deception: The superiority of correspondence over coherence. Communication Studies, 69, 483-498. https://doi.org/10.1080/10510974.2018.1447492
  • Bond, C. F., Jr., & DePaulo, B. M. (2006). Accuracy of deception judgments. Personality and Social Psychology Review, 10, 214- 234. https://doi.org/10.1207/s15327957pspr1003_2
  • Bond, C. F., Jr., Howard, A. R., Hutchison, J. L., & Masip, J. (2013). Overlooking the obvious: Incentives to lie. Basic and Applied Social Psychology, 35, 212-221. https://doi.org/10.1080/01973533.2013.764302
  • Brunner, E., Domhof, S., & Langer, F. (2002). Nonparametric analysis of longitudinal data in factorial experiments. New York: Wiley.
  • Brunner, E., & Puri, M. L. (2001). Nonparametric methods in factorial designs. Statistical Papers, 42, 1-52. https://doi.org/10.1007/s003620000039
  • Cliff, N. (1993). Dominance statistics: Ordinal analyses to answer ordinal questions. Psychological Bulletin, 114, 494-509. https://doi.org/10.1037/0033-2909.114.3.494
  • Cliff, N. (1996). Ordinal methods for behavioral data analysis. Mahwah, NJ: Lawrence Erlbaum.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York, NY: Academic Press.
  • DePaulo, B. M., Lindsay, J. J., Malone, B. E., Muhlenbruck, L., Charlton, K., & Cooper, H. (2003). Cues to deception. Psychological Bulletin, 129, 74-118. https://doi.org/10.1037/0033-2909.129.1.74
  • Erceg-Hurn, D. M., & Mirosevich, V. M. (2008). Modern robust statistical methods. An easy way to maximize the accuracy and power of your research. American Psychologist, 63, 591-601. https://doi.org/10.1037/0003-066X.63.7.591
  • Global Deception Research Team (2006). A world of lies. Journal of Cross-Cultural Psychology, 37, 60-74. https://doi.org/10.1177/0022022105282295
  • Levine, T. R. (2018). Ecological validity and deception detection research design. Communication Methods and Measures, 12, 45-54. https://doi.org/10.1080/19312458.2017.1411471
  • Levine, T. R. (2020). Duped. Truth-default theory and the social science of lying and deception. Tuscaloosa, AL: University of Alabama Press.
  • Luke, T. J. (2019). Lessons from Pinocchio: Cues to deception may be highly exaggerated. Perspectives on Psychological Science, 14, 646- 671. https://doi.org/10.1177/1745691619838258
  • Masip, J. (2017). Deception detection: State of the art and future prospects. Psicothema, 29, 149-159. https://doi.org/10.7334/psicothema2017.34
  • Masip, J., & Herrero, C. (2015). Police detection of deception: Beliefs about behavioral cues to deception are strong even though contextual evidence is more useful. Journal of Communication, 65, 125-145. https://doi.org/10.1111/jcom.12135
  • Masip, J., & Sánchez, N. (2019). How people really suspect lies: A re-examination of Novotny et al.’s (2018) data. Journal of Nonverbal Behavior, 43, 481-492. https://doi.org/10.1007/s10919-019-00309-y
  • Noguchi, K., Gel, Y. R., Brunner, E., & Konietschke, F. (2012). nparLD: An R software package for the nonparametric analysis of longitudinal data in factorial experiments. Journal of Statistical Software, 50(12), 1-23.
  • Nortje, A., & Tredoux, C. (2019). How good are we at detecting deception? A review of current techniques and theories. South African Journal of Psychology, 49, 491-504. https://doi.org/10.1177/0081246318822953
  • Novotny, E., Carr, Z., Frank, M. G., Dietrich, S. B., Shaddock, T., Cardwell, M., & Decker, A. (2018). How people really suspect and discover lies. Journal of Nonverbal Behavior, 42, 41-52. https://doi.org/10.1007/s10919-017-0263-2
  • Park, H. S., Levine, T. R., McCornack, S. A., Morrison, K., & Ferrara, S. (2002). How people really detect lies. Communication Monographs, 69, 144-157. https://doi.org/10.1080/714041710
  • Reinhard, M.-A., & Sporer, S. L. (2008). Verbal and nonverbal behavior as a basis for credibility attribution: The impact of task involvement and cognitive capacity. Journal of Experimental Social Psychology, 44, 477-488. https://doi.org/10.1016/j.jesp.2007.07.012
  • Reinhard, M.-A., & Sporer, S. L. (2010). Content versus source cue information as a basis for credibility judgments: The impact of task involvement. Social Psychology, 41, 93-104. https://doi.org/10.1027/1864-9335/a000014
  • Reinhard, M.-A., Sporer, S. L., Scharmach, M., & Marksteiner, T. (2011). Listening, not watching: Situational familiarity and the ability to detect deception. Journal of Personality and Social Psychology, 101, 467-484. https://doi.org/10.1037/a0023726
  • Rogmann, J. (2013). orddom: Ordinal dominance statistics. R package. Retrieved from https://cran.r-project.org/web/packages/orddom/
  • Sporer, S. L., & Schwandt, B. (2006). Paraverbal indicators of deception: A meta-analytic synthesis. Applied Cognitive Psychology, 20, 421-446. https://doi.org/10.1002/acp.1190
  • Sporer, S. L., & Schwandt, B. (2007). Moderators of nonverbal indicators of deception: A meta-analytic synthesis. Psychology, Public Policy, and Law, 13, 1-34. https://doi.org/10.1037/1076-8971.13.1.1
  • Stiff, J. B., Miller, G. R., Sleight, C., Mongeau, P., Garlick, R., & Rogan, R. (1989). Explanations for visual cue primacy in judgments of honesty and deceit. Journal of Personality and Social Psychology, 56, 555- 564. https://doi.org/10.1037/0022-3514.56.4.555
  • Vrij, A. (2008). Detecting lies and deceit: Pitfalls and opportunities. Chichester, UK: Wiley.
Fuente de los datos: Dialnet