Unique aspects of impulsive traits in substance use and overeating: specific contributions of common assessments of impulsivity

Abstract

Background: Impulsivity is a complex trait often studied in substance abuse and overeating disorders, but the exact nature of impulsivity traits and their contribution to these disorders are still debated. Thus, understanding how to measure impulsivity is essential for comprehending addictive behaviors. Objectives: Identify unique impulsivity traits specific to substance use and overeating. Methods: Impulsive Sensation Seeking (ImpSS) and Barratt’s Impulsivity scales (BIS) Scales were analyzed with a non-parametric factor analytic technique (discriminant correspondence analysis) to identify group-specific traits on 297 individuals from five groups: Marijuana (n = 88), Nicotine (n = 82), Overeaters (n = 27), Marijuauna + Nicotine (n = 63), and Controls (n = 37). Results: A significant overall factor structure revealed three components of impulsivity that explained respectively 50.19% (p_perm < 0.0005), 24.18% (p_perm < 0.0005), and 15.98% (p_perm < 0.0005) of the variance. All groups were significantly different from one another. When analyzed together, the BIS and ImpSS produce a multi-factorial structure that identified the impulsivity traits specific to these groups. The group specific traits are (1) Control: low impulse, avoids thrill-seeking behaviors; (2) Marijuana: seeks mild sensation, is focused and attentive; (3) Marijuana + Nicotine: pursues thrill-seeking, lacks focus and attention; (4) Nicotine: lacks focus and planning; (5) Overeating: lacks focus, but plans (short and long term). Conclusions: Our results reveal impulsivity traits specific to each group. This may provide better criteria to define spectrums and trajectories – instead of categories – of symptoms for substance use and eating disorders. Defining symptomatic spectrums could be an important step forward in diagnostic strategies.

• Impulsivity
• overeating
• psychometrics
• statistics
• substance use

Acknowledgements

Part of this work was supported by grants from NIDA for marijuana studies (K01 DA021632-01A1 to FMF) and The Mind Research Network for control, nicotine, and obesity studies (Institutional Grant to FMF). FMF and DB are currently supported by NIDA (R01 DA030344-01 and F31 DA035039-01A1, respectively). DB and HA created some of the open source software used for analysis in this manuscript (TExPosition and TInPosition). The authors would like to thank Ursula Myers and Michelle Coyazo for their role in data collection. They would also like to thank two anonymous reviewers and the editor for useful comments on previous drafts of this paper.