The daily association between affect and alcohol use: a meta-analysis of individual participant data

Influential psychological theories hypothesize that people consume alcohol in response to the experience of both negative and positive emotions. Despite two decades of daily diary and ecological momentary assessment research, it remains unclear whether people consume more alcohol on days they experience higher negative and positive affect in everyday life. In this preregistered meta-analysis, we synthesized the evidence for these daily associations between affect and alcohol use. We included individual participant data from 69 studies (N = 12,394), which used daily and momentary surveys to assess affect and the number of alcoholic drinks consumed. Results indicate that people are not more likely to drink on days they experience high negative affect, but are more likely to drink and drink heavily on days high in positive affect. People self-reporting a motivational tendency to drink-to-cope and drink-to-enhance consumed more alcohol, but not on days they experienced higher negative and positive affect. Results were robust across different operationalizations of affect, study designs, study populations, and individual characteristics. These findings challenge the long-held belief that people drink more alcohol following increases in negative affect. Integrating these findings under different theoretical models and limitations of this field of research, we collectively propose an agenda for future research to explore open questions surrounding affect and alcohol use.The present study was funded by the Canadian Institutes of Health Research Grant MOP-115104 (Roisin M. O’Connor), Canadian Institutes of Health Research Grant MSH-122803 (Roisin M. O’Connor), John A. Hartford Foundation Grant (Paul Sacco), Loyola University Chicago Research Support Grant (Tracy De Hart), National Institute for Occupational Safety and Health Grant T03OH008435 (Cynthia Mohr), National Institutes of Health (NIH) Grant F31AA023447 (Ryan W. Carpenter), NIH Grant R01AA025936 (Kasey G. Creswell), NIH Grant R01AA025969 (Catharine E. Fairbairn), NIH Grant R21AA024156 (Anne M. Fairlie), NIH Grant F31AA024372 (Fallon Goodman), NIH Grant R01DA047247 (Kevin M. King), NIH Grant K01AA026854 (Ashley N. Linden-Carmichael), NIH Grant K01AA022938 (Jennifer E. Merrill), NIH Grant K23AA024808 (Hayley Treloar Padovano), NIH Grant P60AA11998 (Timothy Trull), NIH Grant MH69472 (Timothy Trull), NIH Grant K01DA035153 (Nisha Gottfredson), NIH Grant P50DA039838 (Ashley N. Linden-Carmichael), NIH Grant K01DA047417 (David M. Lydon-Staley), NIH Grant T32DA037183 (M. Kushner), NIH Grant R21DA038163 (A. Moore), NIH Grant K12DA000167 (M. Potenza, Stephanie S. O’Malley), NIH Grant R01AA025451 (Bruce Bartholow, Thomas M. Piasecki), NIH Grant P50AA03510 (V. Hesselbrock), NIH Grant K01AA13938 (Kristina M. Jackson), NIH Grant K02AA028832 (Kevin M. King), NIH Grant T32AA007455 (M. Larimer), NIH Grant R01AA025037 (Christine M. Lee, M. Patrick), NIH Grant R01AA025611 (Melissa Lewis), NIH Grant R01AA007850 (Robert Miranda), NIH Grant R21AA017273 (Robert Miranda), NIH Grant R03AA014598 (Cynthia Mohr), NIH Grant R29AA09917 (Cynthia Mohr), NIH Grant T32AA07290 (Cynthia Mohr), NIH Grant P01AA019072 (P. Monti), NIH Grant R01AA015553 (J. Morgenstern), NIH Grant R01AA020077 (J. Morgenstern), NIH Grant R21AA017135 (J. Morgenstern), NIH Grant R01AA016621 (Stephanie S. O’Malley), NIH Grant K99AA029459 (Marilyn Piccirillo), NIH Grant F31AA022227 (Nichole Scaglione), NIH Grant R21AA018336 (Katie Witkiewitz), Portuguese State Budget Foundation for Science and Technology Grant UIDB/PSI/01662/2020 (Teresa Freire), University of Washington Population Health COVID-19 Rapid Response Grant (J. Kanter, Adam M. Kuczynski), U.S. Department of Defense Grant W81XWH-13-2-0020 (Cynthia Mohr), SANPSY Laboratory Core Support Grant CNRS USR 3413 (Marc Auriacombe), Social Sciences and Humanities Research Council of Canada Grant (N. Galambos), and Social Sciences and Humanities Research Council of Canada Grant (Andrea L. Howard)

Factors predicting smoking in a laboratory-based smoking-choice task

This study aimed to expand the current understanding of smoking maintenance mechanisms by examining how putative risk factors of relapse relate to a single behavioral smoking choice using a novel laboratory smoking-choice task. After 12 hours of nicotine deprivation, participants were exposed to smoking cues and given the choice between smoking up to two cigarettes in a 15-minute window or waiting and receiving four cigarettes after a delay of 45 minutes. This single behavioral choice was meant to model real-world choices to forgo the immediate gratification of smoking to achieve delayed benefits associated with abstinence. Greater nicotine dependence, higher impulsivity, and lower distress tolerance were hypothesized to predict earlier and more intensive smoking. Out of 35 participants, 26 chose to smoke with a median time to a first puff of 1.22 minutes (standard deviation=2.62 min, range=0.03-10.62 min). Survival analyses examined latency to first puff, and results indicated that greater pre-task craving and smoking more cigarettes per day were significantly related to smoking sooner in the task. Greater behavioral disinhibition was a significant risk factor predicting shorter smoking latency in the first two minutes of the task, but not at a delay of more than two minutes. Lower distress tolerance (reporting greater regulation efforts to alleviate distress) was related to more puffs smoked during the task. This novel laboratory smoking-choice paradigm may be a useful laboratory analog for the choices smokers make during cessation attempts and may help identify factors that influence smoking lapses.M.S.Includes bibliographical referencesby Krysten Williams Bol

Cigarette Smoking in Response to COVID-19: Examining Co-Morbid Medical Conditions and Risk Perceptions

During the initial wave of the Coronavirus Disease 2019 (COVID-19) pandemic in the U.S., information was mixed about the relative COVID-19 risks and potential benefits associated with cigarette smoking. Therefore, we sought to understand individual differences in the impact of COVID-19 on cigarette smoking in a sample of adults who reported recent use, with a particular focus on chronic medical conditions likely associated with increased COVID-19 risk. Participants completed an online survey of smoking behavior, demographic variables, medical history, and COVID-19 risk perceptions between July and August 2020 (N = 286). We examined whether medical conditions, COVID-19 risk perceptions and/or demographic characteristics were related to smoking changes in response to the pandemic (i.e., no change, decrease, increase) using multinomial logistical regression. Younger age, higher COVID-19 risk perceptions and Black versus White race were associated with greater odds of decreased smoking compared to no smoking change. Moreover, having at least one chronic medical condition was associated with greater odds of increased smoking relative to no change. The results have important implications for tobacco cessation treatment and preventive healthcare during the ongoing COVID-19 pandemic and other public health threats

Appeal and Use of Customizable E-cigarette Product Features in Adolescents

Objectives: We evaluated the appeal and use of e-cigarette product features in a sample of high school students in Connecticut. Methods: In 2015, we conducted school-wide surveys in 8 high schools and analyzed data from 1765 students (877 susceptible tobacco-naïve never-e-cigarette users, 315 susceptible tobacco-exposed never-e-cigarette users, and 656 current e-cigarette users). Students were asked: What is cool about e-cigarettes? Response options included e-liquid ingredients (eg, flavors, nicotine content, propylene glycol/vegetable glycerin ratio [ie, PG/VG), the heating source (eg, battery), and physical design (eg, color, shape, appearance). Students were asked: How do you customize your e-cigarette? (Change flavors, voltage, PG/VG levels, temperature, skin/tank color, other) and use of nicotine in the e-liquid (yes/no). Multivariable regression assessed associations between current e-cigarette users\u27 customization and e-cigarette use frequency (#days/month). Results: Flavors were the most appealing product feature among all groups. Among current users, using nicotine e-liquid was more prevalent than changing flavors (44.2% vs 29.6%). Using nicotine e-liquids and changing PG/VG ratios were associated with more frequent e-cigarette use among current users. Conclusions: These findings can inform tobacco regulatory actions that put forth evidence-based recommendations to manufacture e-liquid flavors, nicotine concentrations and PG/VG ratios that prevent e-cigarette initiation and escalation of use

Daily relationship between positive affect and drinking to cope: the moderating role of difficulties regulating positive emotions

Background: Alcohol use is highly prevalent and linked to a wide range of negative outcomes among college students. Although emotion dysregulation has been theoretically and empirically linked to alcohol use, few studies have examined emotion dysregulation stemming from positive emotions. Objective: The goal of the current study was to extend extant research by using daily diary methods to examine the potentially moderating role of difficulties regulating positive emotions in the daily relation between positive affect and alcohol use to cope with social and non-social stressors. Methods: Participants were 165 college students (M age = 20.04; 55.2% male) who completed a baseline questionnaire assessing difficulties regulating positive emotions. Participants then responded to questions regarding state positive emotions and alcohol use once a day for 14 days. Results: Difficulties regulating positive emotions moderated the daily relation between positive affect stemming from social stressors and alcohol use to cope with social stressors. Positive affect stemming from social stressors predicted alcohol use to cope with social stressors with high (but not low) levels of difficulties regulating positive emotions. Conclusions: Findings underscore the potential utility of targeting difficulties regulating positive emotions in treatments aimed at reducing alcohol use to cope with social stressors among college students

Trauma exposure and heavy drinking and drug use among college students: Identifying the roles of negative and positive affect lability in a daily diary study

Trauma exposure is linked to heavy drinking and drug use among college students. Extant research reveals positive associations between negative affect lability and both trauma exposure and alcohol use. This study aimed to extend past research by using daily diary methods to test whether (a) individuals with (versus without) trauma exposure experience greater negative and positive affect lability, (b) negative and positive affect lability are associated with heavy drinking and drug use, and (c) negative and positive affect lability mediate the relations between trauma exposure and heavy drinking and drug use. Participants were 1640 college students (M age = 19.2, 54% female, 80% European American) who provided daily diary data for 30 days via online surveys. Daily diaries assessed negative and positive affect and substance use (i.e., percent days of heavy drinking, percent days of drug use, total number of drugs used). Individuals with (versus without) a history of trauma exposure demonstrated higher levels of negative and positive affect lability. Negative, but not positive, affect lability was associated with percent days of heavy drinking, percent days of drug use, and total number of drugs used, and mediated the associations between trauma exposure and heavy drinking and drug use outcomes. Findings provide support for the underlying role of negative affect lability in the relations between trauma exposure and heavy drinking and drug use among college students, suggesting that treatments targeting negative affect lability may potentially serve to reduce heavy drinking and drug use among trauma-exposed college students