Shifts in behavioral allocation patterns as a natural recovery mechanism: Postresolution expenditure patterns

Abstract

Background Behavioral economics predicts that recovery from Alcohol Use Disorder involves shifts in resource allocation away from drinking, toward valuable nondrinking rewards that reinforce and stabilize recovery behavior patterns. Further, these shifts should distinguish nonproblem drinking (moderation) outcomes from outcomes involving abstinence or relapse. To evaluate these hypotheses, 5 prospective studies of recent natural recovery attempts were integrated to examine changes in monetary spending during the year following the initial cessation of heavy drinking as a function of 1‐year drinking outcomes. Methods Problem drinkers from Southeastern U.S. communities (N = 493, 67% male, 65% white, mean age = 46.5 years) were enrolled soon after stopping heavy drinking without treatment and followed prospectively for a year. An expanded Timeline Followback interview assessed daily drinking and monetary spending on alcohol and nondrinking commodities during the year before and after recovery initiation. Results Longitudinal associations between postresolution drinking and spending were evaluated using MPlus v.8. Initial models evaluated whether changes in spending at 4‐month intervals predicted drinking outcomes at 1 year and showed significant associations in 6 commodity categories (alcohol, consumable goods, gifts, entertainment, financial/legal affairs, housing/durable goods/insurance; ps < 0.05). Cross‐lagged models showed that the moderation outcome group shifted spending mid‐year to obtain large rewards with enduring benefits (e.g., housing), whereas the abstinent and relapsed groups spent less overall and purchased smaller rewards (e.g., consumable goods, entertainment, and gifts) throughout the year. Conclusions Dynamic changes in monetary allocation occurred during the postresolution year. As hypothesized, compared to the groups who abstained or relapsed, the moderation group shifted spending in ways that, overall, yielded higher value alcohol‐free reinforcement that should reinforce recovery while they enjoyed some limited nonproblem drinking below heavy drinking thresholds. These findings add to evidence that moderation entails different behavioral regulation processes than abstinent and relapse outcomes, which were more similar to one another.

Bidirectional prospective associations between behavioral economic indicators and drinking patterns during alcohol use disorder natural recovery attempts.

“…Longitudinal analyses were then conducted using Mplus v.8 (Muthén & Muthén, 1998 following the approach used in Tucker et al (2021). To examine postresolution quarter-to-quarter bidirectional relations between BE indicators and drinking status, cross-lagged models were estimated separately for each BE indicator by relating the indicator assessed in a given quarter (time t) to drinking status in the subsequent quarter (time t + 1), and vice This document is copyrighted by the American Psychological Association or one of its allied publishers.…”

Addictive behavior as molar behavioral allocation: Distinguishing efficient and final causes in translational research and practice.

“…Rates of behavioral and environmental events over long intervals under varied conditions are the primary empirical interpretations of relevant theoretical terms in basic behavioral economic science (Green & Freed, 1993;Hursh, 1980;Rachlin et al, 1981) and directly support an analysis of final causes. Some applied human behavioral economic measures assess patterns of behavior or monetary allocation (either retrospectively or prospectively) related to drug use and substance-free activities in order to connect these molar patterns of behavior with controlling variables (Murphy et al, 2015;Tucker et al, 2016Tucker et al, , 2021.…”

“…For example, the applied alcohol field has sound measurement tools such as the Timeline Followback (TLFB) interview (Sobell & Sobell, 1992) that capture daily behavior and environmental characteristics over long intervals in the natural environment, commonly assessed using ratio scales that have meaning apart from a population distribution (e.g., frequency and quantity of drinking). Some research has used these data to model the temporal patterning of environment-behavior associations (e.g., Tucker et al, 2021), but most have reduced or eliminated concern with variability in rates of behavior over weeks, months, or years by computing summary indices of addictive behavior over intervals that vary from relatively long (1 year) to short (1 month). Clinically, the TLFB has been used both ways.…”

“…These measurement challenges notwithstanding, as discussed next relevant empirical work on addictive behavior includes animal research that is decidedly molar in its level of analysis (e.g., Ainslie & Herrnstein, 1981; Carroll, 1996) and human research that is variously molar (e.g., Murphy et al, 2019; Tucker et al, 2021; Vuchinich & Tucker, 1996) or uses concepts and measures from molar animal and human research applied within an efficient cause framework (e.g., Amlung et al, 2015; cf. Acuff et al, 2020).…”

“…However, their validity as proxies for the temporally extended choice profiles that characterize substance use disorders has yet to be directly evaluated. Moreover, an unfortunate byproduct of the convenience of brief hypothetical measures of demand and delayed reward discounting is that the number of studies using these approaches dwarfs the number that assessed molar behavioral patterns of substance use in relation to substance-free behavior and environmental events over time (Murphy et al, 2015; Tucker et al, 2021).…”