Mind the gap: A review and recommendations for statistically evaluating Dual Systems models of adolescent risk behavior

• Published in: Developmental cognitive neuroscience 2019-10, Vol.39, p.100681-100681, Article 100681
• Main Authors: Meisel, Samuel N., Fosco, Whitney D., Hawk, Larry W., Colder, Craig R.
• Format: Article
• Language: English
• Subjects: Adolescent; Adolescent Behavior - physiology; Adolescent Behavior - psychology; Brain - diagnostic imaging; Brain - growth & development; Dual systems models; Female; Growth mixture modeling; Humans; Imbalance hypothesis; Latent difference scores; Male; Review; Risk-Taking; Self-Control - psychology; Self-Regulation; Sensation seeking
• ISSN: 1878-9293; 1878-9307
• DOI: 10.1016/j.dcn.2019.100681

According to Dual Systems models (Casey et al., 2008; Luna and Wright, 2016; Steinberg, 2008), a rapidly-developing socioemotional system and gradually-developing cognitive control system characterize adolescent brain development. The imbalance hypothesis forwarded by Dual Systems models posits that the magnitude of the imbalance between these two developing systems should predict the propensity for engaging in a variety of risk behaviors. The current integrative review argues that the excitement generated by the imbalance hypothesis and its implications for explaining adolescent risk behaviors has not been meet with equal efforts to rigorously test this hypothesis. The goal of the current review is to help guide the field to consider appropriate and rigorous methods of testing the imbalance hypothesis. First, we review the analytic approaches that have been used to test the imbalance hypothesis and outline statistical and conceptual limitations of these approaches. Next, we discuss the utility of two longitudinal analytic approaches (Latent Difference Scores and Growth Mixture Modeling) for testing the imbalance hypothesis. We utilize data from a large community adolescent sample to illustrate each approach and argue that Latent Difference Scores and Growth Mixture Modeling approaches enhance the specificity and precision with which the imbalance hypothesis is evaluated.