Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-27T21:44:21.121Z Has data issue: false hasContentIssue false
  • English
  • Français

Evaluating Risk Propensity Using an Objective Instrument

Published online by Cambridge University Press:  10 January 2013

Manuel J. Sueiro Abad ,
Iván Sánchez-Iglesias  and
Alejandra Moncayo de Tella
Manuel J. Sueiro Abad*
Affiliation:
Universidad Complutense de Madrid (Spain)
Iván Sánchez-Iglesias
Affiliation:
Universidad Complutense de Madrid (Spain)
Alejandra Moncayo de Tella
Affiliation:
Universidad Autónoma de Madrid (Spain)
*
Correspondence concerning this article should be addressed to Manuel J. Sueiro Abad. Departamento de Metodología y Ciencias del Comportamiento. Universidad Complutense de Madrid. Campus de Somosaguas. 28223 Pozuelo de Alarcón. Madrid. (Spain). E-mail: msueiro@psi.ucm.es
Get access Rights & Permissions [Opens in a new window]

Abstract

Risk propensity is the stable tendency to choose options with a lower probability of success, but greater rewards. Its evaluation has been approached from various perspectives: from self-report questionnaires to objective tests. Self-report questionnaires have often been criticized due to interference from voluntary and involuntary biases, in addition to their lack of predictive value. Objective tests, on the other hand, require resources that make them difficult to administer to large samples. This paper presents an easy-to-administer, 30-item risk propensity test. Each item is itself an objective test describing a hypothetical situation in which the subject must choose between three options, each with a different gain function but equivalent in expected value. To assess its psychometric fit, the questionnaire was administered to 222 subjects, and we performed a test of its reliability as well as exploratory factor analysis. The results supported a three-factor model of risk (Sports and Gambling, Long-term Plans, and Loss Management). After making the necessary adjustments and incorporating a global factor of risk propensity, confirmatory factor analysis was done, revealing that the data exhibited adequate goodness of fit.

La tendencia al riesgo es una propensión estable a elegir opciones con menores probabilidades de éxito pero   mayores recompensas. Su evaluación se ha abordado desde diferentes perspectivas: mediante cuestionarios de autoinforme y pruebas objetivas. El autoinforme ha sido frecuentemente criticado por la interferencia de sesgos voluntarios e involuntarios, y falta de validez predictiva. Las pruebas objetivas requieren recursos que hacen que sean difíciles de aplicar a grandes muestras de sujetos. Este trabajo presenta un test de tendencia al riesgo de treinta ítems de fácil aplicación. Cada ítem es en sí mismo una prueba objetiva que presenta al sujeto una situación hipotética en la que tiene que elegir entre tres opciones, cada una con una función de ganancia diferente pero equivalentes en su esperanza matemática. Para valorar sus bondades psicométricas, se aplicó el cuestionario a 222 sujetos y se realizaron análisis de fiabilidad y de validez factorial exploratorio. Los resultados apoyaron un modelo del riesgo en tres factores (deportes y juegos de azar, planes a largo plazo y prevención de pérdidas). Tras los ajustes necesarios al adoptar este modelo, e incluyendo un factor global de tendencia al riesgo, un análisis factorial confirmatorio mostró que los datos presentaban un ajuste adecuado.

Keywords

risk propensityobjective testingtendencia al riesgoevaluación objetiva
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 14 , Issue 1 , May 2011 , pp. 392 - 410
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arend, I., Botella, J., Contreras, M. J., Hernández, J. M., & Santacreu, J. (2003). A Betting Dice Test to Study the Interactive Style of Risk-Taking Behavior. The Psychological Record, 53, 217–230.CrossRefGoogle Scholar
Bernoulli, D. (1954). Exposition of a New Theory on the Measurement of Risk. Econometrica, 22, 23–36. doi:10.2307/1909829CrossRefGoogle Scholar
Botella, J., Narváez, M., Martínez-Molina, A., Rubio, V. J., & Santacreu, J. (2008). A Dilemmas task for eliciting Risk Propensity. The Psychological Record, 58, 529–546.CrossRefGoogle Scholar
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In Bollen, K. A., & Long, J. S. (Eds.) Testing structural equation models. Newbury Park, CA: Sage Publications.Google Scholar
Chau, P. Y. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28, 309–334. doi:10.1111/j.1540-5915.1997.tb01313.xCrossRefGoogle Scholar
Costa, P. T., & McCrae, R. R. (1995). Primary traits of Eysenck's P-E-N System: Three- and five factor solutions. Journal of Personality and Social Psychology, 69, 308–317. doi:10.1037//0022-3514.69.2.308CrossRefGoogle ScholarPubMed
Doval, E. (1995). Estudio del estilo interactivo tendencia al riesgo [A study of the interactive style of risk propensity]. (Unpublished doctoral dissertation). Universidad Autónoma de Barcelona, Barcelona.Google Scholar
Eysenck, H. J. (1967). The biological basis of personality. Springfield, IL: Charles C. Thomas.Google Scholar
Fagley, N. S. & Miller, P. M. (1997). Framing Effects and Arenas of Choice: Your Money or Your Life? Organizational behavior and human decision processes, 71(3), 355–373. doi:10.1006/obhd.1997.2725CrossRefGoogle Scholar
Feldt, L. S. (1980). A test of the hypothesis that Cronbach's alpha reliability coefficient is the same for two tests administered to the same sample. Psychometrika, 45, 99–105. doi:10.1007/BF02293600CrossRefGoogle Scholar
Froján, M. X., & Santacreu, J. (1999). Qué es un tratamiento psicológico [What is a psychological treatment]. Madrid: Biblioteca Nueva.Google Scholar
Hernández, J. M., Santacreu, J., & Rubio, V. J. (1999). Evaluación de la personalidad: una alternativa teórico-metodológica [Personality assessment: a theorical-methodological alternative]. Escritos de Psicología, 3, 20–28.CrossRefGoogle Scholar
Lancaster, H. O., & Hamdan, M. A. (1964). Estimation of the correlation coefficient in contingency tables with possibly nonmetrical characters. Psychometrika, 29, 383–391. doi:10.1007/BF02289604CrossRefGoogle Scholar
Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey, S. E., Stuart, G. L., … Brown, R. A. (2002). Evaluation of a behavioral measure of risk-taking: The Balloon Analogue Risk Task (BART). Journal of Experimental Psychology: Applied, 8, 75–84. doi:10.1037//1076-898X.8.2.75Google ScholarPubMed
León, O. G. (1987). La toma de decisiones individuales con riesgo desde la psicología [A psychological perspective for individual risky decision taking]. Infancia y Aprendizaje, 30, 81–94.Google Scholar
León, O. G., & Lopes, L. L. (1988). Risk preference and feedback. Bulletin of the Psychonomic Society, 26, 343–346.CrossRefGoogle Scholar
Lopes, L. L. (1987). Between hope and fear: the psychology of risk. Advances in Experimental Social Psychology, 20, 255–295. doi:10.1016/S0065-2601(08)60416-5CrossRefGoogle Scholar
Muthén, L. K., & Muthén, B. O. (2007). Mplus User's Guide. Fifth Edition. Los Angeles, CA: Muthén & Muthén.Google Scholar
Neuman, P. J., & Politser, P. E. (1992). Risk and optimality. In Yates, J. F. (Ed.), Risk-taking behavior. Chichester, UK: Wiley.Google Scholar
Nunnally, J. C. (1981). Psychometric theory. New York, NY: McGraw-Hill.Google Scholar
Olsson, U. (1979). Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 44, 443–460. doi:10.1007/BF02296207CrossRefGoogle Scholar
Pardo, A., & San Martín, R. (2001). Análisis de datos en Psicología II [Data analysis in Psychology II]. Madrid: Pirámide.Google Scholar
Ribes, E. (1990). La individualidad como problema psicológico: El estudio de la personalidad [Individuality as a psychological issue: the study of personality]. Revista Mexicana de Análisis de Conducta, 16, 7–24.Google Scholar
Ribes, E., & Sánchez, S. (1990). Problemas conceptuales en el análisis del comportamiento humano [Conceptual issues in human behavioral assessment]. México: Trillas.Google Scholar
Ribes, E., & Sánchez, S. (1992). Individual behavior consistencies as interactive styles: Their relation to personality. The Psychological Record, 42, 369–387.CrossRefGoogle Scholar
Robie, C., Born, M. P., & Schmit, M. J. (2001). Personal and situational determinants of personality responses: A partial reanalysis and reinterpretation of the Schmit et al. (1995) data. Journal of Business and Psychology, 16, 101–117. doi:10.1023/A:1007843906550CrossRefGoogle Scholar
Rubio, V. J. & Santacreu, J. (1998). Test de riesgo asumido mediante dados [A betting dice test to study the interactive style of risk-taking behavior]. Nº R.P.I.: M-70573.Google Scholar
Ruiz, M. A. (2000). Introducción a los modelos de ecuaciones estructurales [Introduction to structural equation models]. Madrid: UNED Ediciones.Google Scholar
Sánchez-Iglesias, I., & Sueiro, M. J. (2010). FORT: Factorial Objective Risk Test. Unpublished manuscript, Universidad Complutense de Madrid, Madrid, Spain.Google Scholar
Santacreu, J., Froján, M. X., & Santé, L. (1997). El riesgo asumido mediante el TRAD (Test de Riesgo Asumido con Dados) [Assumed risk in BDT (Betting Dice Test)]. Unpublished research paper, Universidad Autónoma de Madrid, Madrid, Spain.Google Scholar
Santacreu, J., & Rubio, V. J. (1998). Test de riesgo asumido al cruzar. Nº R.P.I.: M-70573.Google Scholar
Santacreu, J., Rubio, V. J., & Hernández, J. M. (2006). The objective assessment of personality: Cattells's T-data revisited and more. Psychology Science, 48, 53–68.Google Scholar
Santé, L. (1999). Evaluación del estilo interactivo de tendencia al riesgo [Assessment of risk taking intereactive style]. ) Unpublished doctoral dissertation). Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.Google Scholar
Savage, L. J. (1954). The foundations of statistics. New York, NY: Wiley.Google Scholar
Schreiber, J. B. Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review. The Journal of Educational Research, 99, 323–338. doi:10.3200/JOER.99.6.323-338CrossRefGoogle Scholar
Seiwald, B. B. (2002). Replicability and generalizability of Kubinger's results: Some more studies on faking personality inventories. Psychologische Beiträge, 44, 17–23.Google Scholar
Sherman, S. J., & Fazio, R. H. (1983). Parallels between attitudes and traits as predictors of behavior. Journal of personality, 51 308–345. doi:10.1111/j.1467-6494.1983.tb00336.xCrossRefGoogle ScholarPubMed
Trimpop, R. (1994). The psychology of risk taking behavior. Amsterdam: North Holland.Google Scholar
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453–458. doi:10.1126/science.7455683CrossRefGoogle ScholarPubMed
Wheaton, B., Muthén, B., Alwin, D. F., & Summers, G. F. (1977). Assessing Reliability and Stability in Panel Models. Sociological Methodology, 8, 84–136. doi:10.2307/270754CrossRefGoogle Scholar
Zuckerman, M. (1979). Sensation seeking and risk taking. In Izard, C. E. (Ed.), Emotions in personality and psychopathology. New York, NY: Plenun.Google Scholar