Behavioral economic indicators of risky drinking among community-dwelling emerging adults.

Abstract

Objective: Behavioral economic (BE) approaches to understanding and reducing risky drinking among college students are well established, but little is known about the generalizability of prior findings to peers who currently are not traditional college students and are more difficult to reach for assessment and intervention. This cross-sectional survey investigated whether drinking practices and negative consequences were associated with greater alcohol demand, alcohol reward value, and delay discounting in this target population. Method: Community-dwelling emerging adult drinkers aged 21 to 29 (N = 357) were recruited using Respondent-Driven Sampling adapted to a digital platform (Mage = 23.6 years, 64% women). Peers recruited peers in an iterative fashion. Participants completed a web-based survey of drinking practices, negative alcohol-related consequences, and BE measures of alcohol demand, alcohol reward value, and delay discounting. Results: Regression analyses supported the study hypotheses. Higher alcohol demand (intensity and elasticity) predicted higher drinks per drinking day, more past-month drinking days, and more negative consequences. Higher alcohol reward value (discretionary alcohol spending and alcoholinvolved activities) and stronger preference for sooner smaller versus later larger rewards predicted select drinking risk variables in the hypothesized direction ( p < .05). Conclusions: BE risk characteristics were generalized to community-dwelling emerging adult risky drinkers, with the most consistent associations found between alcohol demand and drinking risk measures. The findings lay a foundation for extending successful BE interventions with college drinkers to this underserved population. Public Health Significance StatementThis cross-sectional survey found that established associations of behavioral economic variables with risky drinking among traditional college students are generalizable to young adults who currently reside in the community. It lays a foundation for extending behavioral economic interventions with college drinkers to the underserved population of community-dwelling young adult risky drinkers. The study also showed that online peer-driven sample recruitment using Respondent-Driven Sampling is an efficient, effective method to recruit community-dwelling risky drinkers who are harder to reach than groups accessible by location.

Utility of digital Respondent Driven Sampling to recruit community-dwelling emerging adults for assessment of drinking and related risks

“…In-person recruitment of seeds ensured that the sample was generated by members of the target population of interest; regular checks on chain development ensured that peer recruits retained for analysis also met the eligibility criteria; and all participants were required to enter valid unique referral codes and correct passwords and provide a physical address to compensate them using Visa™ cards delivered by mail. Furthermore, study measures selected for conceptual relevance, predictive utility, measurement quality, brevity, and ease of online administration yielded findings in line with behavioral economic theory and previous research on substance use (see Tucker, Lindstrom et al, 2020).…”

“…Homophily for race/ethnicity (Whites, Asians, other) indicated a moderate bias in favor of Asian participants recruiting among themselves (0.665), but it was below levels at which weighting is considered necessary (Schonlau, & Liebau, 2012). As recommended (Johnston & Sabin, 2010), a weighting variable based on the reciprocal of participants' peer online social network size was created using the Volz and Heckathorn (2008) RDSII estimator (http://wiki.stat.ucla.edu/hpmrg/index.php/RDS_ Analyst_Install) and applied in analyses evaluating hypothesized associations between behavioral economic and drinking risk indicators, as reported elsewhere (Tucker, Lindstrom et al, 2020).…”

Contextual decision-making and alcohol use disorder criteria: Delayed reward, delayed loss, and probabilistic reward discounting.

“…While AUD is often conceptualized as a unitary, graded construct based on a sum score of criteria met, recent work suggests that AUD has significant heterogeneity (even within criteria). Behavioral economics suggests that some symptoms of AUD may not be internal states but rather are temporally extended patterns of behavior in which utility is maximized in the immediate rather than over a longer temporal span (Rachlin, 1995; Rachlin et al, 1991; Tucker, Cheong, et al, 2021; Tucker, Lindstrom, et al, 2021; Vuchinich & Tucker, 1983). This study quantifies relationships between individual AUD symptoms and behavioral economic discounting to inform nuanced and accurate etiological models accounting for specific risk factors for distinct elements of AUD.…”

Perceptions of childhood unpredictability, delay discounting, risk-taking, and adult externalizing behaviors: A life-history approach

“…The dependent variable of interest is the discount rate, k. Larger k values indicate that participants were less willing to wait for a delayed, higher reward, and instead prioritized more immediate, lesser rewards. The DDT provides a well-validated measure of delay discounting (e.g., Friedel et al, 2016;Koffarnus & Bickel, 2014;Stein et al, 2018;Tucker et al, 2021). In both Studies 1a and 1b, we used a priori exclusion criteria to exclude participants whose k scores were 3SD above the mean (this criterion was preregistered in Study 1b).…”