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Multidimensional latent structure of risk-related phenotypes in healthy young adults.

Elisa PabonJames MacKillopAbraham A PalmerHarriet de Wit
Published in: Experimental and clinical psychopharmacology (2020)
Risk-taking behavior can result in a range of maladaptive behaviors such as illicit substance use, unsafe driving, and high-risk sexual behavior. Perception of risk and preference for engaging in risky behaviors have been measured using both self-report measures and a range of behavioral tasks designed for the purpose, and these may predict future risk-taking behavior. However, the interrelationships between these measures and the latent constructs underlying them are poorly understood. In the present study, we examined data from over 1,000 men and women who completed measures of risk-related behaviors, including self-reports of perception of risk, propensity to engage in risky behaviors, and incentivized performance on tasks that involve risk. We conducted principal component analyses (PCAs) to understand the underlying latent structure of these measures. A PCA with the full sample revealed 5 distinct components, corresponding to measures of (a) health/ethical risks, (b) discounting of uncertain rewards, (c) risk of personal finances, (d) preferences in recreational hobbies and social interactions that involve risk, and (e) behavior involving risks in interpersonal interactions. Although we found sex differences on several of the measures, the sex-adjusted PCA components were similar to those of the unadjusted full sample PCA. These findings add to a growing literature revealing different components of the broad category of risk perception and risk-taking behaviors. A better understanding of the multidimensionality of risk preference will help lay the foundation for more refined measures, develop better predictors of future risk-taking behavior, and ultimately to study the genetic or other biological basis of risk-taking. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
Keyphrases
  • healthcare
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  • social media
  • electronic health record