Advancing experimental models of complex decision environments to better understand risky behaviors

This article discusses the experimental models of complex decision environments to better understand risky behaviors. Risky behaviors-such as substance misuse, aggression, and rule breaking-span many clinical conditions, including attention deficit/hyperactivity disorder, substance use disorders, antisocial personality disorder, and bipolar disorder. A robust body of research indicates that these behaviors are often rooted in impairments in decision making. This conclusion is supported by experimental research that estimates how people evaluate and respond to information. Experimental methods are particularly powerful because they enable researchers to observe decision making as it unfolds in real time, while also providing precise control over aspects of the decision environment that shape behavior. Despite these strengths, the experimental tasks traditionally used to study decision making as it relates to risky behavior have remained relatively static over the past three decades. The authors argue for developing innovative experimental tasks that better capture the complex real-world environments where risky decisions occur and their implications for clinical conditions. The authors highlight the initial steps for capturing conditions where momentary decisions are embedded within context. This work still needs to be extended to the study of risky behaviors relevant to clinical conditions. By more richly representing the landscape of decision making, one may better understand which environments promote, or even discourage, risky behaviors across clinical populations. (PsycInfo Database Record (c) 2026 APA, all rights reserved).