Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-23T21:07:05.222Z Has data issue: false hasContentIssue false
  • English
  • Français

Age Differences in Trade-off Decisions: Different Strategies but Similar Outcomes

Published online by Cambridge University Press:  13 March 2015

Xiaodong Ma  and
Yiwei Chen
Xiaodong Ma*
Affiliation:
University of Houston-Clear Lake
Yiwei Chen
Affiliation:
Bowling Green State University
*
*La correspondance et les demandes de tirés-à-part doivent être adressées à: / Correspondence and requests for offprints should be sent to: Xiaodong Ma, Ph.D. Department of Psychology University of Houston–Clear Lake 2700 Bay Area Blvd. Houston, TX 77058 ([email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

The primary purpose of this study was to examine age differences in processing strategies of emotionally difficult trade-off decisions. In addition, the study tested the relevant contributions of the cognitive and emotional mechanisms to age differences in processing strategies. Altogether, 40 younger adults and 40 older adults were randomly assigned to either a high or low emotionally difficult condition of a car-purchasing decision task. MouselabWEB software was used to trace participants’ processing strategies. Results showed that older adults were more likely to use attribute-based processing strategies, whereas younger adults were more likely to use alternative-based processing strategies in the high-emotion condition. In the low-emotion condition, on the other hand, both younger and older adults preferred to use alternative-based processing strategies. Furthermore, the results suggested that the cognitive measure (i.e., digit symbol coding) was not correlated with the age effects on processing strategies.

Résumé

L'objectif principal de cette étude était d'examiner les différences conditionnées par l'âge dans le traitement des stratégies de décisions émotionnellement difficiles. En outre, l'étude a testé les contributions pertinentes des mécanismes cognitifs et émotionnels à des différences dans le traitement de ces stratégies conditionnées par l'âge. Quarante jeunes adultes et quarante adultes plus âgés, en tout, ont été assignés au hasard soit à un niveau élevé ou à un niveau bas de difficulté émotionnelle qu'implique la décision d'acheter une automobile. MouselabWEB logiciel a été utilisé pour tracer les stratégies de traitement des partici- pants. Les résultats ont montré que les personnes âgées étaient plus susceptibles d'utiliser des stratégies de traitement basées sur les attributs, tandis que les jeunes adultes étaient plus susceptibles d'utiliser des stratégies de traitement basées sur des solutions de rechange à l'état très émotive. D'autre part, les jeunes adultes et les adultes plus âgés ont préféré utiliser des stratégies de traitement fondées sur des alternatives dans des conditions d'émotion faible. De plus, les résultats suggèrent que la mesure cognitive (c'est à dire, programmation de chiffres-symboles) n'était pas corrélée avec les effets de l'âge sur les stratégies de traitement.

Keywords

agingemotionprocessing strategiesvieillissmentémotionstratégies de traitement
Type
Articles
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 34 , Issue 2 , June 2015 , pp. 247 - 256
Copyright
Copyright © Canadian Association on Gerontology 2015 

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

Bruine de Bruin, W., Parker, A. M., & Fischhoff, B. (2010). Explaining adult age differences in decision-making competence. Journal of Behavioral Decision Making, 25(4), 352–360.Google Scholar
Carstensen, L. L. (1993). Motivation for social contact across the life span: A theory of socioemotional selectivity. In Jacobs, J. E. (Ed.), Nebraska Symposium on Motivation, 1992: Developmental Perspectives on Motivation (pp. 209–254). Lincoln, NE, United States: University of Nebraska Press.Google Scholar
Carstensen, L. L. (1995). Evidence for a life-span theory of socioemotional selectivity. Current Directions in Psychological Science, 4, 151–156.Google Scholar
Carstensen, L. L., Mikels, J. A., & Mather, M. (2006). Aging and the intersection of cognition, motivation, and emotion. In Birren, J. E., & Schaie, K. W. (Eds.), Handbook of the psychology of aging (6th ed.) (pp. 343–362). Amsterdam: Elsevier Academic Press.Google Scholar
Chen, Y., & Ma, X. (2009). Age differences in risky decisions: The role of anticipated emotions. Educational Gerontology, 35(7), 575–586.Google Scholar
Chen, Y., Ma, X., & Pethtel, O. (2011). Age differences in tradeoff decisions: Older adults prefer choice deferral. Psychology and Aging, 26, 269–273.Google Scholar
Chen, Y., & Sun, Y. (2003). Age differences in financial decision-making: Using simple heuristics. Educational Gerontology, 29, 627–635.Google Scholar
Frisch, D., & Clemen, R. T. (1994). Beyond expected utility: Rethinking behavioral decision research. Psychological Bulletin, 116, 46–54.Google Scholar
Gruber, J. (2009). Choosing a Medicare Part D plan: Are Medicare beneficiaries choosing low-cost plans? Retrieved 19 August 2014 fromhttp://www.kff.org/Medicare/upload/7864.pdf.Google Scholar
Hanoch, Y., Wood, S., & Rice, T. (2007). Bounded rationality, emotions and older adults decision making; not so fast and yet so frugal. Human Development, 50, 333–358.Google Scholar
Hartley, A. A. (1989). The cognitive ecology of problem-solving. In Poon, L. W., , D. C., Rubin, , & Wilson, B. A. (Eds.), Everyday cognition in adulthood and late life (pp. 300–329). Cambridge, England: Cambridge University Press.Google Scholar
Henninger, D., Madden, D. J., & Huettel, S. (2010). Processing speed and memory mediate age-related differences in decision making. Psychology and Aging, 25, 262–270.Google Scholar
Johnson, M. M. (1990). Age differences in decision making: A process methodology for examining strategic information processing. Journal of Gerontology, 45, 75–78.Google Scholar
Johnson, M. M. (1993). Thinking about strategies during, before, and after making a decision. Psychology and Aging, 8, 231–241.Google Scholar
Johnson, M. M. (1997). Individual differences in the voluntary use of a memory aid during decision making. Experimental Aging Research, 23, 33–43.Google Scholar
Joy, S., Kaplan, E., & Fein, D. (2004). Speed and memory in the WAIS-III Digit Symbol Coding subtest across the adult lifespan. Archives of Clinical Neuropsychology, 19, 759–767.Google Scholar
Kaiser Family Foundation. (2009). The Medicare prescription drug benefit: Fact sheet. Retrieved 19 August 2014 fromhttp://www.kff.org/Medicare/upload/7044-09.pdf.Google Scholar
Keeney, R. L., & Raiffa, H. (1976). Decisions with multiple objectives: Preferences and value tradeoffs. New York, NY: Wiley.Google Scholar
Kim, S., & Hasher, L. (2005). The attraction effect in decision making: Superior performance by older adults. The Quarterly Journal of ExperimentalPsychology A: Human Experimental Psychology, 58A(1), 120–133.CrossRefGoogle Scholar
Löckenhoff, C. E., & Carstensen, L. (2007). Aging, emotion, and health-related decision strategies: Motivational manipulations can reduce age differences. Psychology and Aging, 22(1), 134–146.Google Scholar
Luce, M. F., Bettman, J. R., & Payne, J. W. (1997). Choice processing in emotionally difficult decisions. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 384–405.Google Scholar
Mata, R., Schooler, L., & Rieskamp, J. (2007). The aging decision maker: Cognitive aging and the adaptive selection of decision strategies. Psychology and Aging, 22, 796–810.Google Scholar
Mather, M., Knight, M., & McCaffrey, M. (2005). The allure of the alignable: Younger and older adults’ false memories of choice features. Journal of Experimental Psychology: General, 134, 38–51.Google Scholar
Payne, J. W. (1976). Task complexity and contingent processing in decision making: An information search and protocol analysis. Organizational Behavior and Human Performance, 16, 366–387.Google Scholar
Payne, J. W., Bettman, J. R., & Johnson, E. (1993). The adaptive decision maker. Cambridge, England: Cambridge University Press.Google Scholar
Reisen, N., Hoffrage, U., & Mast, F. W. (2008). Identifying decision strategies in a consumer choice situation. Judgment and Decision Making, 3, 641–658.Google Scholar
Salthouse, T. A. (1991). Theoretical perspectives on cognitive aging. Hillsdale, NJ: Erlbaum.Google Scholar
Samanez-Larkin, G. R., Kuhnen, C. M., Yoo, D. J., & Knutson, B. (2010). Variability in nucleus accumbens activity mediates age-related suboptimal financial risk taking. The Journal of Neuroscience, 30, 1426–1434.Google Scholar
Tversky, A. (1972). Elimination by aspects: A theory of choice. Psychological Review, 79, 281–299.Google Scholar
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.Google Scholar
Watson, D., & Tellegen, A. (1985). Toward a consensual structure of mood. Psychological Bulletin, 98, 219–235.Google Scholar
Willemsen, M. C., & Johnson, E. J. (2006). MouselabWEB: Monitoring information acquisition processes on the web. Retrieved 15 August 2006 fromhttp://www.mouselabweb.org/.Google Scholar
Wood, S., Busemeyer, J., Koling, A., Cox, C. R., & Davis, H. (2005). Older adults as adaptive decision makers: Evidence from the Iowa Gambling Task. Psychology and Aging, 20, 220–225.Google Scholar