Decision‐making heuristics and biases across the life span

Abstract

We outline a contextual and motivational model of judgment and decision-making (JDM) biases across the life span. Our model focuses on abilities and skills that correspond to deliberative, experiential, and affective decision-making processes. We review research that addresses links between JDM biases and these processes as represented by individual differences in specific abilities and skills (e.g., fluid and crystallized intelligence, executive functioning, emotion regulation, personality traits). We focus on two JDM biases—the sunk-cost fallacy (SCF) and the framing effect. We trace the developmental trajectory of each bias from preschool through middle childhood, adolescence, early adulthood, and later adulthood. We conclude that life-span developmental trajectories differ depending on the bias investigated. Existing research suggests relative stability in the framing effect across the life span and decreases in the SCF with age, including in later life. We highlight directions for future research on JDM biases across the life span, emphasizing the need for process-oriented research and research that increases our understanding of JDM biases in people’s everyday lives.

The Multifold Relationship Between Memory and Decision Making: An individual-differences study

“…Finally, other decision-making tasks were not affected by age (Consistency in Risk Perception) or a positive role of age on performance was observed (Resistance to Sunk Costs), even after controlling for the influence of semantic memory (see also Strough et al, 2008). Taken overall, the present findings extend previous investigations on the relation between age and decision making, strengthening our conclusions on the multifold relationship between memory and decision making and providing further evidence of how decision-making competence depends on multiple abilities, which can be differentially affected by age Mather, 2006;Peters et al, 2007;Strough, Karns et al, 2011).…”

“…Given that the Betula dataset currently does not include direct measures of task-specific knowledge, performance in semantic memory tests will be used as a proxy. 3 Previous studies also observed a positive correlation between age and the capacity to resist sunk costs Strough, Mehta, McFall & Schuller, 2008), explaining this finding with older adults' greater tendency to avoid focusing on painful unrecoverable past costs in the attempt of maintaining a positive emotional state (Strough et al, 2008;Strough, Karns et al, 2011;Strough, Schlosnagle & DiDonato, 2011). In line with previous studies, a positive correlation between age and Resistance to Sunk Costs is expected.…”

“…Additionally, the ability to resist sunk costs is not only related to semantic memory, but also positively associated with age. Previous studies explained this positive relation by referring to older adults' reduced tendency to focus on painful unrecoverable past costs, due to their increased desire to maintain a positive emotional state (Strough et al, 2008;Strough, Karns et al, 2011;.…”

“…This has been explained by assuming that decision makers do not want to waste time or money already invested in a course of action (cf. Baron, 2008;Hastie & Dawes, 2001), and thus they go on with the existing course of action even if taking a new one would be the better choice, although various other explanations have been proposed (see Strough, Karns & Schlosnagle, 2011). Researchers have hypothesized that knowledge of the principle that unrecoverable costs need to be ignored can help in avoiding sunk costs (e.g., Fennema & Perkins.…”

Decision Making Across the Life Span

“…Notably, however, other studies show that aged adults can actually be less likely than young to choose low-risk options in some circumstances . Broadly speaking, whether decisionmaking improves, declines, or remains stable across the lifespan seems to depend on the type of decision-making and the context in which decisions are framed Mienaltowski, 2011;Strough et al, 2011). Indeed, relationships between some aspects of decision-making and aging may be non-linear, with decision quality increasing up to approximately age 50 and then declining thereafter (Agarwal et al, 2007).…”