![]() ![]() As an example of decision-making under risk, an alcohol-dependent has to reach a metro-station and has to choose between a short-length walk but with plenty of alcohol-liquor stores throughout (low physical effort but high risk of relapse) or a longer but “alcohol-safe” path. In light of the limited research, further studies were needed in order to provide a close contrast between impairments of decision-making under ambiguity and under risk in alcohol dependence, as both situations decision-making under risk account for poor decision-making outside of the laboratory. The study found alcohol-dependent individuals exhibit a stubborn preference for options featuring high but uncertain rewards instead of options featuring lower but certain rewards ( Bowden-Jones et al., 2005). So far, only one study has examined decision-making under risk in alcohol-dependent individual ( Bowden-Jones et al., 2005) using the Cambridge Gambling Task ( Rogers et al., 1999), which provides choices with explicit probabilities of risk, i.e., it measures decisions under risk. Other tasks are more direct measures of risk taking because probabilities of reward and loss are simply given to the participant (e.g., the Cups task, Levin et al., 2007 the Coin Flipping Task, Tom et al., 2007). Even though in the latter trials of the IGT (e.g., from trials 60 to 100 Brand et al, 2006 Brevers et al., 2012) the subject may acquire some sense of the probabilities of reward and loss, thus requiring mental calculation, working memory, the knowledge of these probabilities is not explicit and remains largely unknown (notion of ambiguity), thus requiring an decision-maker to rely more on intuition and emotion than on the logic ( Bechara et al., 1997). The IGT represents a complex task, for which a number of cognitive and affective processes are involved (e.g., working memory, episodic memory, inhibition, mental flexibility, automatic emotional activation during the deliberation phase Dunn et al., 2006). Indeed, depending on the quality of information available for elaborating a decision, decisional context could be totally ambiguous because of the absence of any useful information to anticipate a given outcome or a risk could be estimated, because of either provided to the decision-maker (e.g., one chance in two to win) or calculated through practice (e.g. ![]() One limitation of these findings is that they cannot be generalized to the general spectrum of situations of decision-making under uncertainty. These findings highlight that impaired decision-making process measured by the IGT does not recover over time, i.e., after abstinence from using alcohol and may impact on the risk of relapse even after months and years. Kornreich et al., 2013 Noël et al., 2007) or even for several years ( Fein et al., 2004) make more choices than healthy participants that bring immediate reward, but then lead to more severe delayed punishment. For instance, a high proportion of alcohol-dependent patients detoxified and abstinent from alcohol for a few weeks (e.g. drugs, alcohol, tobacco) and non-substance addictions (e.g. A key feature of the IGT is that participants have to forgo short-term benefits for long-term benefits, a process that is presumably severely hampered in substance (e.g. This aberrant profile of decision-making has been further evidenced in laboratory settings, through, for instance, the use of the Iowa Gambling Task (IGT Bechara et al., 1994). Poor decision making is associated with an increased risk of mortality in old age even after accounting for cognitive function.Alcohol dependent individuals exhibit poor decision making as reflected by their continued alcohol use despite encountering problems directly linked to these drinking habits ( APA, 2013). Further, the association of decision making with mortality persisted after adjustment for the level of cognitive function. Thus, a person who performed poorly on the measure of decision making (score = 3, 10th percentile) was about 4 times more likely to die compared to a person who performed well (score = 11, 90th percentile). In a proportional hazards model adjusted for age, sex and education, the risk of mortality increased by about 20% for each additional decision making error (HR = 1.19, 95% CI = 1.07-1.32, p = 0.002). During up to 4 years of follow-up (mean = 1.7 years), 40 (6% of 675) persons died. The mean score on the decision making measure at baseline was 7.1 (SD = 2.9, range: 0-12), with lower scores indicating poorer decision making. Baseline assessments of decision making were used to predict the risk of mortality during up to 4 years of follow-up. Participants were 675 older persons without dementia from the Rush Memory and Aging Project, a longitudinal cohort study of aging. Decision making is thought to be an important determinant of health and well-being across the lifespan, but little is known about the association of decision making with mortality. ![]()
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