Cognitive functions, such as perception, attention, memory, or decision making, are mental abilities necessary for the performance of any activity. They vary from person to person, depending on factors referred to as “individual differences. One of these differences is the subject of the model developed by U.S. psychologist Raymond Cattell, who in 1963 postulated the existence of two types of intelligence: fluid and crystallized. Fluid intelligence refers to the ability of individuals to adapt to new situations and to think logically, solving problems independently of learned knowledge. According to the author, this type of intelligence depends on biological factors and is therefore naturally acquired. Crystallized intelligence, on the other hand, is the ability to use skills, knowledge, and experience acquired over a lifetime. It is the product of one’s educational and cultural experiences and is in constant interaction with fluid intelligence. While crystallized intelligence remains stable throughout life, fluid intelligence tends to decline with age. That is, as people age, they tend to rely more on crystallized intelligence than on fluid intelligence.
This phenomenon mainly affects decision making. Over the past two decades, scientific research has shown a strong interest in studying decision-making processes in relation to the effects of aging.
Since the consequences of non-rational decision making can be risky, it is worth investigating how much of it can be attributed to aging. Scientific evidence has shown that when it comes to decision making, certain individual characteristics attributable to aging are associated with a greater tendency to make biases (i.e., cognitive errors in reasoning) and heuristics (i.e., automatic shortcuts in reasoning). However, little is known about this topic.To address this lack, APRESO has joined a strand of research aimed at investigating the relationship between aging and the implementation of risky health behaviors. Specifically, by integrating the literature from the above perspectives, the antecedents of the development of optimal decision making have been identified. In this sense, the research allowed the development of a comprehensive taxonomy of heuristics and biases based on an empirical evidence-based approach. Contrary to the idea that there is only one element of decision-making competence (Ceschi et al., 2017), the results allowed the implementation of an intervention aimed at improving decision-making through the teaching of debiasing strategies, which allow the elimination or minimization of the influence of individual factors, such as age, on decision-making. A debiasing intervention can improve decision making in individuals who are more likely to use biases and heuristics as they age (Larrick, 2004).
Cattell, R.B., (1963) Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54, 1-22
Peters, E., Dieckmann, N. F., & Weller, J. (2011). Age differences in complex decision making. In Handbook of the Psychology of Aging (pp. 133-151). Academic Press.
Bruine de Bruin, W., Parker, A. M., & Fischhoff, B. (2007). Individual differences in adult decision-making competence. Journal of personality and social psychology, 92(5), 938.
Larrick, R. P. (2004). Debiasing. Blackwell handbook of judgment and decision making, 316-338.
Weller, J. A., Levin, I. P., Rose, J. P., & Bossard, E. (2012). Assessment of decision‐making competence in preadolescence. Journal of Behavioral Decision Making, 25(4), 414-426.
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Formazione e organizzazioni
work and organizational psychology
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