Navigating Adolescent Risk-Taking: The Dual System Model in Decision-Making - Essay Sample

Introduction: Dual System Model

People often face various choices in life. Some choices are more tempting, but they may also produce bad results. For example, when teenagers first come into contact with tobacco and alcohol, they still want to try it out of temptations although their parents or teachers have warned them. The choice made is a risky decision. To a large extent, risk-taking behavior is the performance of risky decision-making in specific behaviors, and teenagers are often a group of risk-taking behaviors. Steinberg (2010) found that teenagers (11-20 years old) have significantly more risk-taking behaviors than children and adults.

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Although traditionally risk-prone behaviors during adolescence have been associated with intellectual limitations in adolescents, new evidence suggests that these difficulties may be related to asynchronies in the development of brain structures (Steinberg, 2009). According to the “Dual System Model,” there are two fundamental systems, the Socio-emotional System and the Cognitive Control System, which, as they are not balanced in their development, favor risky behaviors and inefficient decision-making (Steinberg, 2010). In this sense, certain prefrontal structures have a later development, causing the Cognitive Control System to not be able to adequately exercise its behavioral regulatory function.

The idea of two cognitive systems is essential, which explains cognitive-behavioral development leading to fluctuations in risk throughout different age groups, but which age group holds the highest risk due to incorrect decisions and why? Could it have higher infliction in middle adolescence or late adolescence? Understanding how risk and age are correlated with cognitive development could explain many risk-taking attitudes occurring during middle adolescence or late adolescence. The hypothesis that will be tested is that under low time constraints low anxiety, the risk will be significantly lower compared to the pressure of time constraints. The second hypothesis is that high anxiety will dissolve system 2, leading to higher risk results in both age groups while middle adolescence due to underdeveloped frontal cortex will conclude the highest results in both independent variables.

Dual System Theory

Adolescence is a development stage characterized by risky behaviors. According to Paiget and Inhelder (1975) (as cited by Leather, 2009), these behaviors are because of immaturity in reasoning skills. However, an alternative explanation for these behavioral peculiarities of adolescence has recently been offered. According to this new theory, the difficulties of adolescents to make adequate decisions do not lie exactly in their cognitive immaturity, but in the imbalance between the emotional and rational processing of situations (Steinberg, 2009). This new approach, called the “Dual System Model”, proposes that the characteristic immaturity in adolescents' decisions is due to the interaction between two neural systems with different degrees of development: an essentially emotional system, oriented towards the search for rewards (Socioemotional System), and a system of a logical and rational nature (Cognitive Control System).

Reasoning systems can be explained by the dual system theory. The dual theory of reasoning is a theory about human reasoning processes. According to this theory, the results from cognitive psychology that have been interpreted pessimistically can be explained by postulating two different systems of reasoning (Steinberg, 2010). A first system that is tacit or implicit (called system1 or S1) allows complex information processing to be carried out quickly. S1 offers a quick but not always correct answer (from the standard view of rationality) to different reasoning problems.

In general terms, dual-process theories coincide in proposing two different systems to explain human reasoning and thought, instead of a single universal inference mechanism. According to Turel and Qahri-Saremi (2018), both processes present differences: a) functional in cognitive processing (automatic and in parallel in system 1, compared to controlled and sequential processing in system 2); b) in processing speed (they are fast in the first system and slow in the second); c) in the access to consciousness (while only the final products or results of system 1 reach consciousness, in system 2 there is conscious processing); and d) in the computational capacity or resources that they demand (low in the first system and highly demanding in the second system)

System 1 allows a quick and almost immediate reaction to the environment, in such a way that it allows people to make decisions that can save their lives (Steinberg, 2010). It is the system that allows people to form a first impression of the situation and act accordingly, making a decision based more on the contextual and their internal nature and not on logic (Bago & De Neys, 2017). It is the oldest mechanism phylogenetically speaking, forming part not only of people but also of other animals.

The second system, the explicit system - also called system2 or S2 is a slow system, but capable of producing outputs that can systematically satisfy the normative requirements stipulated by the standard view of rationality. The implementation of this system implies decision-making and processing, requiring a conscious and voluntary process. This system is considered to be typically human, being one of the most novel at the phylogenetic level (Turel and Qahri-Saremi (2018). It is based on logic and requires explicit processing, requires a large amount of cognitive resources and time to be used and allows the analysis and conscious control of thought and behavior. According to Duell and Steinberg (2019), although system 2 does not allow an immediate response and in imminent situations, it has the great utility of allowing reflection on the different courses of action, the implications of each situation and works with more abstract elements. This affects people to plan and predict, as well as to assess not only emotionally but also logically the different options.

The dual theory of reasoning considers that human cognition cannot be understood as being composed of two completely independent systems, but as a continuous interaction between them. The interaction arises from the fact that S2 is shaped by S1. S2 requires S1 to save time and identify potential problems or errors. The point is that S1 is primary, in the sense that it permeates all human thought (Stanovich & West, 2000). The interactive nature of processes rests on the fact that a person’s conscious thought is always shaped, directed, and limited by tacit processes.

Adolescence is an extremely important stage that individuals experience during their growth in life. During this period, individuals began to be more exposed to various environments outside the home, from family life to school life and social life. At the same time, the physical and psychological changes of adolescents urge them to participate in social activities behaviorally and cognitively that is different from the naive childhood and adulthood with stable personality (Steinberg, 2009). A more defined understanding of how the two systems differentiate throughout the growing cycle of frontal cortex development and evolves towards risk management during middle adolescence or late adolescence could explain behavioral issues and disorders.

There might be a correlation between higher anxiety resulting in higher-risk behaviors due to poor decision making resulting from system one processing. There is also a likelihood that middle adolescent has more notable sublevels scores caused by the underdeveloped frontal cortex, resulting in higher anxiety and higher risk due to the lack of operational system 2 in the dual system model. Consequently, under low time constraints low anxiety, the risk will be significantly lower compared to the pressure of time constraints. High anxiety will dissolve system 2, leading to higher risk results in both age groups. Exploring the formation and changes of individual risk-taking behaviors in adolescence in cognitive neuroscience is of great significance for exploring the formation, development, and changing trends of adolescents' risk-taking behaviors, and also for society, schools, and families to guide youths to cope with and regulate the risk situations they face.

Method

Data will be obtained by administering a short UPPS-P-C questionnaire (urgency-premeditation-perseverance-sensation seeking-positive urgency). It will consist of 20 participants who will be randomly selected, 10 girls and 10 boys whose ages will range from 14-20 years. The short UPPS-P-C version of the scale contains 40 understandable administered questionnaire items rated on a 4-point Likert-type scale indicating agreement levels. The agreement levels range from 1, not like me at all, to 4, very much like me. The participants will be allowed to ask for help if they are items they do not understand.

Performing experiments with two levels, one level is high anxiety of timed constraints and low anxiety, no time constraints are used as an independent variable. Recording results from the short UPPS-P-C will produce a dependent variable. The results will show a correlation between higher anxiety resulting in higher-risk behaviors due to poor decision making resulting from system one processing. The results will also show whether middle adolescent responses to the questionnaire will have more notable sublevels scores caused by the underdeveloped frontal cortex, resulting in higher anxiety and higher risk due to the lack of operational system 2 in the dual system model.

The short UPPS-P-C is not only a valid instrument but a reliable one. Moreover, it measures impulsivity facets and its subscales have adequate internal consistency coefficients. According to Cyders et al. (2014), the internal consistency of UPPS-P-C ranges from 0.61 to 0.88 which is acceptable. Its test-retest reliability is about 0.87 which is between good and very good while its external validity ranges between 0.80 to 0.87 which is very good. According to Dugre et al. (2019), although UPPS-P-C is a valid instrument and has good psychometric features, it does not have the best optimal psychometric features for assessing gender differences in taking risky behaviors.

References

Bago, B., & De Neys, W. (2017). Fast logic? Examining the time course assumption of dual process theory. Cognition, 158, 90-109. https://doi.org/10.1016/j.cognition.2016.10.014

Cyders, M. A., Littlefield, A. K., Coffey, S., & Karyadi, K. A. (2014). Examination of a short English version of the UPPS-P Impulsive Behavior Scale. Addictive Behaviors, 39(9), 1372-1376. https://doi.org/10.1016/j.addbeh.2014.02.013

Duell, N., & Steinberg, L. (2019). Positive risk-taking in adolescence. Child Development Perspectives, 13(1), 48-52. https://doi.org/10.1111/cdep.12310

Dugre, J. R., Giguére, C. É., Percie du Sert, O., Potvin, S., & Dumais, A. (2019). The Psychometric Properties of a Short UPPS-P Impulsive Behavior Scale Among Psychiatric Patients Evaluated in an Emergency Setting. Frontiers in Psychiatry, 10, 139. https://doi.org/10.3389/fpsyt.2019.00139

Leather, N. C. (2009). Risk-taking behavior in adolescence: a literature review. Journal of Child Health Care, 13(3), 295-304. https://doi.org/10.1177/1367493509337443

Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 23(5), 645-665. https://psycnet.apa.org/doi/10.1017/S0140525X00003435

Steinberg, L. (2010). A Dual Systems Model of Adolescent Risk-taking. Developmental Psychology, 52 (3), 216-224. https://doi.org/10.1002/dev.20445