Common liability to addiction and “gateway hypothesis”: Theoretical, empirical and evolutionary perspective

Abstract

Background Two competing concepts address the development of involvement with psychoactive substances: the “gateway hypothesis” (GH) and common liability to addiction (CLA). Method The literature on theoretical foundations and empirical findings related to both concepts is reviewed. Results The data suggest that drug use initiation sequencing, the core GH element, is variable and opportunistic rather than uniform and developmentally deterministic. The association between risks for use of different substances, if any, can be more readily explained by common underpinnings than by specific staging. In contrast, the CLA concept is grounded in genetic theory and supported by data identifying common sources of variation in the risk for specific addictions. This commonality has identifiable neurobiological substrate and plausible evolutionary explanations. Conclusions Whereas the “gateway” hypothesis does not specify mechanistic connections between “stages”, and does not extend to the risks for addictions, the concept of common liability to addictions incorporates sequencing of drug use initiation as well as extends to related addictions and their severity, provides a parsimonious explanation of substance use and addiction co-occurrence, and establishes a theoretical and empirical foundation to research in etiology, quantitative risk and severity measurement, as well as targeted non-drug-specific prevention and early intervention.

Risk and resistance perspectives in translation-oriented etiology research

“…The factors involved in the physiological response to drugs, on the other hand, are less influenced by social environment, as they include drug metabolism and neurochemistry of drug response. Many of behavior regulation mechanisms, however, are also involved in the development of physical dependence [29][30][31][32], placing premorbid behavior, dependence, and addiction to a substantial degree on the same dimension.…”

“…These characteristics combine with affect change and other incentives for drug use. Euphoria may have evolved as an indicator of the positive Darwinian value of an experience, but it is possible that the true indicator of a Darwinian fitnesssignificant behavior is any positive affect change rather than necessarily euphoria [31]. Norm violation and rebelliousness, elevated novelty-seeking and risk-taking, are common features of adolescence [47], especially when exacerbated by maturational mistiming [48].…”

Preventing Smoking Progression in Young Adults: the Concept of Prevescalation

“…We introduce the concept of Bprevescalation^(pronounced Bpri-ves-kuh-ley-shuhn^) to capture the need and opportunity to prevent the escalation of risk behaviors that typically occur during young adulthood, with a focus on the example of cigarette smoking. However, since risky behaviors often travel together because of shared vulnerability (Vanyukov et al 2012), the core concept of prevescalation may apply to other risky behaviors that support one another and become entrenched and harder to change in later adulthood. We discuss the need to target this transitional phase, what we know about behavioral pathways and predictors of cigarette smoking, and potential intervention considerations and research challenges.…”

Visited a vape shop? Prevalence and correlates from a national sample of U.S. young adults

“…Secondly, we describe, associations of vape shop visitation with quitting intentions and behaviors among tobacco users. In line with the common liability model, 12,13 we would expect that young adult vape shop visitors would be more likely than non-visitors to use e-cigarettes, other tobacco products, and other substances. Findings from this study will inform future research on reasons for visiting vape shops, the impact of federal and state regulation on these establishments, and how visiting vape shops affects health behavior.…”

“…7 Young adult past 30-day e-cigarette users compared with those with no past-month use have also reported higher prevalence of marijuana use (some days or ever day 10 or in the past 12 months 11 ), some days or every day alcohol use, 10 past 30-day binge drinking, 11 and past 30-day other tobacco (defined as use of cigars, pipes, chewing tobacco, snuff, snus, hookah, clove cigarettes, bidis, or other) product use 11 . This pattern of e-cigarette co-use with a variety of other substances may indicate a common liability to use addictive substances based on genetic, neurochemical, physiological, behavioral, and/ or environmental factors [12][13] . Additionally, over half of U.S. adults (55%) who tried e-cigarettes report that they used them to try to quit smoking cigarettes and e-cigarette users were significantly more likely to quit cigarettes for 24 hours than non-users.…”