Intoxication rate in the last 30 days for U.S. adolescents was 18%, compared to 61% in Denmark, 53% in Ireland, 48% in Austria, and 46% in Britain. Adolescence is a period of life during which peers play a pivotal role in decision-making. Thus, fuzzy-trace theory offers a view of decision makers that is antithetical to classical decision theory's probability-calculating, utility-maximizing individuals. A narrated list of findings, however, would be insufficient to address this topic. Using an information-processing approach, Klayman (1985), for example, highlighted continuities between 12-year-olds' multiattribute decision making in a bicycle-selection task and adults' decision making. Although perceived risks and especially benefits predict behavioral intentions and risk-taking behavior, behavioral willingness is an even better predictor of susceptibility to risk taking—and has unique explanatory power—because adolescents are willing to do riskier things than they either intend or expect to do. Traditional theories of rational decision making indicate that either risk taking or risk aversion can be rational, as long as the decision process is coherent (i.e., internally consistent). Although adolescents appear to have full access to many of the cognitive foundations of decision-making, several aspects of decision-making such as intertemporal choice, prospective evaluation, and integration of positive and negative feedback are not yet tuned to typical adult levels. Although optimistic bias is not invariably found for adolescents, many studies have documented a tendency for them to see their own vulnerability as lower than that of comparable others (e.g., Arnett, 2000; Chapin, 2000, 2001a; Greening & Stoppelbein, 2000; Romer & Jamieson, 2001). By continuing to browse There is also the problem of reinventing the wheel. However, additional research is needed to examine the effects of behavioral management interventions implemented in school settings, given various methodological limitations … (In experiential tasks, people learn about the magnitudes of outcomes and their probabilities by making choices and experiencing outcomes, whereas in verbal tasks, the probabilities and outcomes are simply described to them.) (Our use of the term normative may be confusing to social scientists who use the same term to refer to the concept of the average, or norm, rather than the ideal; however, because use of the term to mean ideal is standard in decision research, we have adopted that usage here. However, Fischhoff and Quadrel (1991) compared 86 matched pairs of adolescents and parents and found that adolescents did not exhibit the optimistic bias more than adults did (see also Millstein, 1993; Quadrel, Fischhoff, & Davis, 1993). Because mature decision making involves gist-based qualitative reasoning (e.g., avoid catastrophic risk), per fuzzy-trace theory, adults do not trade off quantitatively under specific circumstances. However, research has shown that across situations of gain and loss, the global tendency to avoid risk increases from childhood to adulthood, and this robust trend cannot be ignored in deciding which behaviors and decision processes are likely to be rational. These developmental studies included risks that involved both gains and losses, and children were more likely to take risks overall (i.e., the results were not limited to taking risks involving gains). The coherence view of rationality revolves around such questions as the following: Is reasoning logical—does it obey the rules of logic? Data from Europe were collected as part of the European School Survey Project on Alcohol and Other Drugs, and the U.S. data were from the Monitoring the Future survey conducted annually among 8th, 10th, and 12th graders in the United States. However, younger children are able to demonstrate sophisticated quantitative competence in social judgment tasks, and, according to fuzzy-trace theory, they would be more likely to approach such a task quantitatively than older children and adults, who are more likely to be qualitative gist processors. 11). Its constructs include perceived vulnerability and severity, response efficacy (the belief that the recommended action is effective in reducing the threat), and perceived self-efficacy (the belief that one can successfully perform the recommended action). For example, it was speculated that participants rated a woman as more likely to be a feminist bank teller than a bank teller because they made the pragmatic inference that “bank teller” must refer to nonfeminist bank tellers. Moadab et al. Because of this lack of opportunity to learn self-regulation and other self-control strategies, some theorists (e.g., Byrnes, 1998) have suggested that “sheltered, inexperienced” (p. 153) children would be at higher risk (Byrnes' self-regulation model). Evolutionary theory, and the construct of adaptive behavior, is central to understanding rationality in the correspondence sense (i.e., which decision processes and behaviors promote positive long-term outcomes). study. Hence, a cross-cutting analysis is urgently needed to identify the findings and explanatory models that generalize across domains, as well as the domain-specific limits to generalization. In contemporary Western societies, these particular self-binding choices are rare but not unheard of. However, research has also shown that social influence can lead to increased prosocial behaviours (Van Hoorn, Crone, & Van Leijenhorst, … Correspondence refers to correspondence to reality, which outcomes reflect. For example, challenges to the association between dopamine receptor D4 (DRD4) gene polymorphism and novelty seeking were quickly followed by a study producing evidence for this association but showing that it was moderated by sociodemographic characteristics (Lahti et al., 2006). Unfortunately, having large sample sizes with many variables that are correlated with one another does not compensate for the absence of a predictive process model of risky decision making. (Empirically supported explanations for this flawed reasoning include an increasing and, mostly adaptive, reliance on gist representations with development.) A key question is whether adolescents are developmentally competent to make decisions about risks. Prescriptive approaches bridge the gap between the normative and the descriptive accounts, focusing on those decisions that matter most. Other methodological advances have similarly shown quantitative trading off for probability judgments in children as young as 5 or 6 (Davidson, 1991; Jacobs & Potenza, 1991; Kerkman & Wright, 1988). Crucially, interventions to improve risk perceptions must be designed to address the source of the distortions—for example, denial of risk to rationalize behavior versus lack of awareness that others' risk-reduction strategies are similar to one's own (and do not sufficiently lower risk). Loewenstein, Weber, Hsee, and Welch (2001), for example, distinguish between anticipated and anticipatory emotions. In this monograph, we review scientific evidence concerning the causes and remediation of unhealthy risk taking in adolescence. On the contrary, there is ample evidence favoring such models and, simultaneously, evidence indicating that they have important gaps. Thus, the argument could be made that a generally adaptive tendency to weight recent more than distant outcomes occasionally backfires by encouraging immediate feel-good behaviors, such as smoking, drug use, overeating, and risky sexual behavior. We have argued that developmental trends can be used as clues about what is rational; specific behaviors or thought processes that increase with maturity and experience are likely to be more advanced than those that decrease. Motor-vehicle accidents are the leading cause of deaths among those aged 15 to 20 years; 31% of young drivers killed in motor-vehicle crashes in 2003 had been drinking (National Center for Statistics and Analysis, 2003; Turner & McClure, 2003). Hence, the mature adult (or adolescent) may have lapses of maturity. We reject the argument that behaviors are adaptive simply because people engage in them, which is a misunderstanding of evolutionary theory. View or download all the content the society has access to. The laboratory pattern (although qualified by individual differences) has been replicated and, ironically, suggests that adolescents' preference for risks declines during the period in which exploration and opportunity (and thus, risk-taking behaviors) increase. Clearly, development of psychometric instruments, including behavioral measures, that successfully distinguished the different kinds of risk takers and avoiders would be crucial for matching adolescents with the kinds of programs that are likely to be effective for them (although these mappings may change over time and decision domains, in contrast to those for stable traits such as thrill seeking). The prototype/willingness model, which incorporates the behavioral-willingness construct, has been supported by studies showing that much adolescent risk behavior is not planned and that willingness and intention are related but independent constructs that separately predict risk behavior (Gibbons et al., 1998; Gibbons et al., 2004). and correspondence (are the outcomes of the decisions positive?). If you have access to a journal via a society or association membership, please browse to your society journal, select an article to view, and follow the instructions in this box. One of the barriers to more comprehensive use of the scientific literature is the fragmentation of research. Failures to experience bad outcomes may instill similar complacency in real life. Protection motivation refers to the motivation to protect oneself against a health threat and is usually measured as the intention to adopt some recommended action. Many of the developmental differences we have discussed thus far are contingent on knowledge and experience. Specifically, people are much more willing to take risks in experiential tasks than in verbal tasks (choosing a risky option, such as taking a one-in-four chance of winning $100, rather than choosing a sure thing, such as winning $25 with certainty), apparently becoming inured to the possibility of bad outcomes when such outcomes have not happened recently. Thus, based on the literature as a whole, we can conclude that there is an overall tendency (we discuss exceptions presently) to view oneself as more invulnerable to risk than unspecified others are, whether this perception is due to illusions of control, motivated belief or self-enhancement, or nonmotivational information-processing constraints (Chambers & Windschitl, 2004). In the absence of stereotypes, object judgments remained unbiased. Fig. As noted earlier, results demonstrating effectiveness suggest that assumed explanatory mechanisms have merit. Interest in the role that decision making plays in adolescents' involvement in high-risk behaviors led the Office of the Assistant Secretary of Planning and Evaluation of the U.S. Department of Health and Human Services to request the Board on Children, Youth, and Families to convene a workshop on adolescent decision making. As Kotchik et al. 5. Research has revealed that the discrepancy between what we think adolescents should do and what they actually do is not because they are incapable of making good decisions. This shortcoming of traditional decision theory is another reason why we include correspondence (healthy outcomes) as well as internal coherence as criteria for rationality. In brief, behavioral decision theory is a general term for descriptive theories to explain the psychological knowledge related to decision-making behavior. (, Galvan, A., Hare, T.A., Parra, C.E., Penn, J., Voss, H., Glover, G, Casey, B.J. We do not conclude that traditional models are worthless. Although the literature comparing risk perceptions of low- and high-risk adolescents has yielded contradictory findings, a clearer picture has emerged from comparing risk perceptions across age groups. CBT a… (2002), Chapin (2001b), and Gerrard et al. Although we undertook such a conventional review before writing this paper, to ensure that our judgments are firmly grounded in current work, space does not permit us to discuss or even to mention every scientific article on adolescent risk taking. As we have noted, feelings can be treated as just another input to a cognitive equation—and Loewenstein et al. 8) is an experiential-learning task in which risks emerge as a result of card choices (outcomes are experienced as the cards are selected from one of four decks). It has generally been assumed—and we present pertinent data later—that adolescents' risk perceptions are distorted. People are more discomfited by the possibility of loss or of winning nothing when a gamble is described verbally, but tolerate a possibility of loss or of winning nothing when outcomes of the same gamble are experienced. In sum, there are some fundamental principles that emerge from our review of theory and data. Predicting future feelings, Risk perceptions and alcohol consumption among young people, Examining delinquency in adolescents differentially prenatally exposed to alcohol: The role of proximal and distal risk factors, Bounded rationality, ambiguity, and the engineering of choice, Developmental patterns in the understanding of social and physical transitivity, The value of the theory of planned behavior, perceived control, and self-efficacy expectations for predicting health-protective behaviors, What does the phrase “safer sex” mean to you? (1997) found that perceived benefits were a stronger predictor of behavioral intention and change than were perceived risks for five risk-behavior categories; Benthin, Slovic, and Severson (1993) reported similar results for a larger sample of 30 activities but a smaller sample of students. HIV knowledge, personal contact and sexual risk behavior of psychiatrically referred Latino adolescent girls, Adolescents' perceived risk for STDs and HIV infection, Integration of the cognitive and psychodynamic unconscious, A genetic model of creativity and the Type T personality complex with educational implications, Alcohol misuse and adolescent sexual behaviors and risk taking, Judgment and decision making: The dance of affect and reason, Development of and in behavioral decision research, Teen expectations for significant life events, Fault trees: Sensitivity of assessed failure probabilities to problem representation, Toward an understanding of the role of perceived risk in HIV prevention research, Understanding and promoting AIDS-preventive behavior: Insights from the theory of reasoned action, A meta-analysis of research on protection motivation theory, Risk-taking and contraceptive behavior among unmarried college students, Anatomy of a decision: Striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal, Outcome expectancies and risk-taking behavior, Risk taking in adolescence: A decision-making perspective, Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk-taking behavior in adolescents, Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: An experimental study, Complex decision-making in early childhood, A longitudinal study of the reciprocal nature of risk behaviors and cognitions in adolescents: What you do shapes what you think and vice versa, A theory-based dual focus alcohol intervention for pre-adolescents: The strong African-American families program, Reasoned action and social reaction: Willingness and intention as independent predictors of health risk, A social reaction model of adolescent health risk, Context and cognitions: Environmental risk, social influence, and adolescent substance use, How do we tell an association from a rule? 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