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. Author manuscript; available in PMC: 2026 May 26.
Published in final edited form as: Exp Clin Psychopharmacol. 2025 Jul 24;33(5):503–512. doi: 10.1037/pha0000792

Subjective Response to Alcohol Predicts Motivation to Self-Administer Alcohol in a Progressive Ratio Task

Malia A Belnap 1,2, Dylan E Kirsch 2, Erica N Grodin 2,3,4, Lara A Ray 2,3,4
PMCID: PMC13200834  NIHMSID: NIHMS2171605  PMID: 40705616

Abstract

Subjective responses to alcohol, which encompass the subjective feelings and experiences elicited by alcohol consumption, are important factors implicated in the etiology of alcohol use disorder. Previous human-laboratory studies have investigated how subjective responses to priming doses of alcohol influence alcohol self-administration but have not accounted for responses throughout the task. The current study investigated how subjective responses to alcohol, measured at multiple timepoints during a progressive ratio self-administration task, impacted subsequent motivation to self-administer alcohol. Participants (n=67; 36M/31F) who drank heavily completed a 120-minute progressive-ratio alcohol intravenous self-administration paradigm. Every 15 minutes, participants were breathalyzed and completed self-report questionnaires to measure alcohol-induced stimulation, sedation, alcohol wanting, alcohol liking, negative mood, and positive mood. Alcohol self-administration was indicated by an increase in breath alcohol concentration. Time-lagged subjective response outcomes were examined as predictors of subsequent self-administration using multilevel modeling. Sex and family history of alcohol-related problems were investigated as potential moderators of the impact of subjective response measures on self-administration. Higher levels of alcohol-induced stimulation, as well as wanting and liking alcohol, predicted increased self-administration of alcohol. An increase in time, as a proxy for task demand, predicted a decreased likelihood of subsequent self-administration, and moderated the effect of liking on self-administration. Family history of alcohol-related problems moderated the impact of alcohol-induced wanting and negative mood on motivation to consume alcohol. Overall, these findings emphasize the significant role of subjective responses to alcohol, as well as their interactions with task demand and family history, in influencing alcohol consumption behaviors.

Keywords: Intravenous alcohol administration, subjective responses to alcohol, alcohol use disorder, human laboratory

INTRODUCTION

Alcohol use disorder (AUD) is a complex and heterogeneous condition that can develop through multiple pathways. A critical aspect of AUD research involves identifying and understanding the risk factors that contribute to its development and maintenance. Subjective responses (SR) to alcohol are among the factors implicated in the etiology of AUD and encompass the subjective feelings and experiences elicited by alcohol consumption (Ray et al., 2016). Acute alcohol consumption interacts with various brain systems, producing both stimulating and sedative effects as well as alterations in mood states (Morean & Corbin, 2010; Ray et al., 2016). Additionally, alcohol is known to produce rewarding effects, such as the pleasurable effects (liking) and the desire to consume more (wanting) (Berridge & Robinson, 2016). Subjective experiences during alcohol consumption vary with changing blood alcohol levels (Morean & Corbin, 2010). Increasing blood alcohol content (BAC) is associated with feelings of stimulation, whereas decreasing BAC is associated with feelings of sedation (Martin et al., 1993). Notably, SR to alcohol are dose-dependent, vary widely across individuals, and individual differences in acute SR influence the likelihood of experiencing subsequent alcohol-related problems, including the development of AUD (A. C. King et al., 2014; Morean & Corbin, 2010; Ray et al., 2016). Understanding how these individual differences contribute to drinking-related outcomes and interact with other risk factors can provide valuable insights into the mechanisms underlying heightened risk for AUD.

Longitudinal work on SR to alcohol in humans has demonstrated that heightened feelings of alcohol stimulation and rewarding effects of alcohol, as well as lower sensitivity to alcohol sedation, during alcohol administration, predict heavy alcohol use and the development of AUD symptomatology over time (A. C. King et al., 2011, 2014; Schuckit, 1994). Furthermore, alcohol-induced stimulation and alcohol ‘wanting’ become amplified over time among individuals who develop AUD (A. King et al., 2021). Overall, these data indicate that SR to alcohol is a phenotype capable of predicting risk for heavy alcohol use and AUD, and that SR may change over time as individuals increase their alcohol use.

Preclinical models have provided critical insights into the basic biological and behavioral mechanisms that may influence SR and underly aspects of AUD, including alcohol seeking and consummatory behaviors (Cyders et al., 2021; Nentwig et al., 2017; Nieto et al., 2021). In animal models, operant alcohol self-administration paradigms capture the reinforcing properties of alcohol by measuring an animal’s motivation to obtain an alcohol reward (Lopez & Becker, 2014). A widely used preclinical paradigm is the progressive-ratio design, in which the effort required to obtain the alcohol reward increases progressively. This paradigm captures motivation to consume alcohol by evaluating the point at which the subject stops attempting to obtain it (Lopez & Becker, 2014). While preclinical studies have yielded significant insights into the mechanisms of alcohol motivation, translating preclinical findings to humans remains challenging due to the unique complexities of AUD as a human condition. This may be particularly salient for SR, which is an inherently human experience requiring enteroception and verbal reporting.

Human laboratory studies serve as a “bridge” between preclinical and clinical research on AUD, allowing researchers to conduct controlled experimental manipulations in human subjects (Nieto et al., 2021). To that end, the alcohol intravenous self-administration paradigm offers a promising avenue for applying insights from preclinical operant-response studies to study AUD in humans (Nieto et al., 2021). This method bypasses the significant variability in alcohol absorption and metabolism associated with oral consumption by infusing alcohol intravenously (Zimmermann et al., 2008). The progressive-ratio self-administration paradigm in animals can be translated using this model in humans, such that individuals can press a button on an escalating scale to receive an alcohol reward to measure motivation to consume alcohol. While this paradigm has been successfully implemented in human samples, there is limited research examining subjective responses throughout the duration of the task itself (Stangl et al., 2022; Zimmermann et al., 2008). Consequently, these studies do not consider how the increasing task duration and task demand might influence or interact with the motivation to self-administer alcohol. Thus, the influence of SR to alcohol throughout the course of the progressive-ratio paradigm on subsequent motivation to consume alcohol remains poorly understood.

The current study is a secondary analysis of a human laboratory study conducted by Bujarski, and colleagues (Bujarski et al., 2018), in which we test the association between SR and motivation to self-administer alcohol at multiple timepoints throughout the progressive ratio task. In the original study, Bujarski and colleagues demonstrated that alcohol use severity predicted greater overall alcohol self-administration and craving for alcohol during a progressive-ratio self-administration task in individuals who drank heavily (Bujarski et al., 2018). Subjective feelings of sedation predicted overall lower self-administration. Interestingly, neither feelings of stimulation nor negative affect predicted overall self-administration. In this study, alcohol self-administration was quantified based on the overall breath alcohol concentration (BrAC) curve. The SR measures were captured during the alcohol priming challenge at baseline and when participants reached target BrAC levels of 20, 40, and 60 mg% during the alcohol priming, which was completed prior to the self-administration task.

The present study addresses this gap in the literature by examining the relationship between SR measures and the motivation to self-administer alcohol across multiple timepoints throughout the duration of a progressive-ratio self-administration task. By incorporating multiple observations per subject throughout the course of the task, our analyses examine the interaction of SR measures with the influence of an increasing task demand. Clinically, it provides insights into how SR to alcohol influences the motivation to continue consuming alcohol during a “drinking episode.” Specifically, the effects of stimulation, sedation, wanting, liking, positive mood, and negative mood on self-administration behavior were assessed in 15-minute intervals across a 2-hour period.

Further, this study investigated the moderating effect of family history of alcohol-related problems on motivation to self-administer alcohol, both of which have been previously implicated in the development of AUD (Agabio et al., 2017; Schuckit & Smith, 2000). An analysis of six alcohol administration studies found that males reported higher levels of alcohol-induced stimulation and a stronger craving for alcohol compared to females (Nieto et al., 2022). Additionally, research has also demonstrated sex-specific differences in the impact of negative mood states on alcohol self-administration, indicating that men work significantly harder for alcohol than women to obtain alcohol when in a negative mood state (Cyders et al., 2016). However, other studies report no differences in subjective responses to alcohol based on sex (A. King et al., 2021; Schuckit, 2000). Family history (FH) of alcohol-related problems also contributes to higher-risk patterns of SR (Gowin et al., 2017; Quinn & Fromme, 2011; Ramchandani et al., 1999; Schuckit, 2009; Viken et al., 2003; Zimmermann et al., 2009). Initial work in this area found that FH of alcohol-related problems is associated with low sensitivity to the intoxicating and sedative effects of alcohol (Quinn & Fromme, 2011; Schuckit, 1994). More recently, studies have broadened this research scope, examining the relationship between FH of alcohol-related problems and other SR domains. These studies have demonstrated that a FH of alcohol-related problems is associated with greater alcohol-induced craving, as well as higher levels of alcohol self-administration in the laboratory (Gowin et al., 2017; Nieto et al., 2022; Ramchandani et al., 1999; Viken et al., 2003; Zimmermann et al., 2009). In brief, FH of alcohol-related problems and sex at birth represent plausible moderators of SR and may impact the effects of SR on motivation to self-administer alcohol.

Based on the available literature, we hypothesized that individuals who drink heavily and experienced greater subjective feelings of stimulation, positive mood, liking, and wanting in response to alcohol, as well as lower levels of sedation and negative mood, would be more motivated to self-administer alcohol during the task. We also predicted that as the effort required (i.e., task demand) to self-administer alcohol increased, participants would exhibit a decrease in the frequency of self-administration. Finally, we hypothesized that FH of alcohol-related problems and sex would moderate the impact of SR on motivation to self-administer alcohol.

METHODS

Participants

Participants (n = 67; 36 M/31F) were recruited between April 2015 and August 2016 from the greater Los Angeles metropolitan area through fliers and online advertisements. Eligibility screening was initially conducted through online and telephone surveys, followed by an in-person screening visit. Participants provided written informed consent following a comprehensive explanation of all study procedures. All participants underwent a breathalyzer test and provided urine samples for toxicology screening and were required to have a breath alcohol concentration of 0 mg% and test negative for all substances on a urine drug screen, except for cannabis. Female participants were also required to test negative on a urine pregnancy test. The study was approved by the University of California Los Angeles Institutional Review Board.

Participants met the following inclusion criteria: (1) between the ages of 21 and 45 (upper limit set to minimize potential risks associated with IV alcohol administration), (2) Caucasian ethnicity (due to an exploratory genetic analysis not reported here), (3) current heavy alcohol use of 14+ drinks per week for men or 7+ for women (based on National Institute on Alcohol Abuse and Alcoholism (NIAAA) recommendations. Participants were excluded if the met the following exclusion criteria: (1) currently seeking treatment for AUD, (2) diagnosed with a current substance use disorder for substances other than nicotine or alcohol, (3) current use of illicit drugs, other than cannabis (4) and a Clinical Institute Withdrawal Assessment for Alcohol-Revised (CIWA-Ar) score of score≥10, which indicates clinically significant alcohol withdrawal requiring medical treatment. A full description of participant inclusion and exclusion criteria can be found in the primary publication of the study (Bujarski et al., 2018). Participant demographics, substance use, and self-administration characteristic information is in Table 2.

Table 2.

Pearson Correlations Between Subjective Response Measures

Measure 1 Measure 2 r p-value
Positive Mood Stimulation 0.82 <.0001
Like Want 0.77 <.0001
Stimulation Like 0.46 <.0001
Stimulation Want 0.40 <.0001
Positive Mood Like 0.39 <.0001
Positive Mood Want 0.32 <.0001
Positive Mood Sedation −0.31 <.0001
Stimulation Sedation −0.26 <.0001
Negative Mood Sedation 0.16 .0007
Positive Mood Negative Mood −0.08 .08
Sedation Want −0.08 .08
Negative Mood Want 0.06 .17
Sedation Like −0.04 .39
Negative Mood Like 0.02 .67
Negative Mood Stimulation −0.01 .83
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Note. Correlations are ordered by magnitude (absolute value). Correlations are based on data collapsed across timepoints.

Alcohol Self-Administration Procedure

The alcohol self-administration procedures were conducted at the UCLA Clinical and Translational Research Center (CTRC). Upon arrival at the UCLA CTRC, a nurse measured the participant’s height, weight, and vital signs, and then inserted an intravenous (IV) line into the participant’s arm. Study staff were present throughout the duration of the infusion to breathalyze the participants and administer questionnaires. The IV alcohol infusion procedures lasted approximately 180 minutes. Alcohol was administered through the IV line (6% ethanol v/v in saline) using the Computer-Assisted Self-Infusion of Ethanol (CASE) and the IMED Gemini PC-2TX dual channel volumetric infusion pump (Zimmermann et al., 2008). Participants were breathalyzed every 5 minutes throughout the duration of the infusion procedures, and all BrACs were input into the CASE software system. Prior to starting the self-administration paradigm, participants completed questionnaires and were provided priming doses of alcohol to reach a target BrAC of 60 mg% which took approximately 60 minutes. Participants then began the progressive ratio self-administration paradigm. The progressive ratio followed a log-linear schedule. The button press requirements were as follows: 20 responses (first completion), 33 responses (second), 47 responses (third), 64 responses (fourth), 83 responses (fifth), 107 responses (sixth), 136 responses (seventh), 173 responses (eighth), 219 responses (ninth), 279 responses (10th), 358 responses (11th), 460 responses (12th), 597 responses (13th), 777 responses (14th), 1019 responses (15th), 1342 responses (16th), 1775 responses (17th), 2357 responses (18th), and 3139 responses (final completion). Each dose of alcohol following a completion increased BrAC by 7.5 mg% over 2.5 min, followed by a descent of −1 mg%/min (Grodin et al., 2021). A 120 mg% BrAC safety threshold was established such that the self-administration button was temporarily deactivated when the CASE algorithm predicted that BrAC would exceed this threshold. At the beginning of the self-administration period, participants were instructed to press the button to receive the first dose of alcohol but were not provided with further instructions. The self-administration procedures lasted approximately 120 minutes. Participants completed SR questionnaires every 15 minutes at 8 time points throughout the duration of the self-administration procedure. After the infusion ended, participants were monitored at the UCLA CTRC and were discharged when their BrAC returned to 0 mg%, if driving, or below 40 mg% if taking public transportation. To disincentivize low levels of self-administration, all participants were initially told that they would need to remain at the UCLA CTRC for 4 hours regardless of their BrAC following the alcohol administration.

MEASURES

Demographics

A Demographics Questionnaire was used to collect information on age, sex, income, education, and ethnicity.

Subjective response to alcohol (SR) measures

Participants completed SR assessments at eight time points (every 15 minutes) during the duration of the progressive ratio self-administration task. Subjective feelings of stimulation and sedation were assessed using the six-item Brief Biphasic Alcohol Effects Scale (B-BAES (Martin et al., 1993; Rueger et al., 2009; Rueger & King, 2013), with three items each for stimulation (Cronbach’s α =0.93) and sedation (Cronbach’s α =0.74). A subset of 12 items from the Profile of Mood States (POMS) was administered to evaluate negative and positive mood, consistent with previous applications of the scale (Bujarski et al., 2015; McNair et al., 1971). Negative mood was assessed using the items: Tense, Nervous, Anxious, Downhearted, Sad, and Self-doubting (Cronbach’s α =0.90). Positive mood was assessed using the items: Active, Bold Energetic, Jolly, Joyful, and Cheerful (Cronbach’s α =0.94). Participants also rated their current ‘liking’ of the alcohol exposure (“How much did you like the exposure to alcohol?”) and ‘wanting’ of more alcohol (“Do you want to be infused with more alcohol?”). These questions were adapted from the Drug Effects Questionnaire to reference alcohol specifically (Morean et al., 2013).

Family History

Family history (FH) of alcohol-related problems was categorized as either FH− (0) or FH+ (1). Individuals were assigned a score of 1 (FH+) if they reported on the Family History Questionnaire that at least one biological parent had a history of alcohol-related problems (Mann et al., 1985). A score of 0 (FH−) was assigned if they reported that neither biological parent had a history of alcohol-related problems.

Alcohol Use Measures

Masters-level clinicians administered the Structured Clinical Interview for DSM-5 to assess for lifetime and current AUD, and exclusionary diagnoses (First et al., 2015). A timeline follow-back (TLFB) assessed drinking quantity and frequency for the 30 days prior to the visit (Sobell & Sobell, 1992).

DATA ANALYSIS

BrAC was measured every 15-minute intervals, concurrent with self-report (SR) measures, throughout the duration of 120-minute self-administration task (Figure 1). To determine whether a participant had successfully earned the alcohol infusion during a given interval, the BrAC from one timepoint (TP) was subtracted from the previous timepoint (e.g., TP2 - TP1). A positive result indicated that a participant’s BrAC had increased and therefore had received an alcohol infusion. Thus, receiving the infusion indicated that the participant had performed the required number of button-presses for that interval and therefore was motivated to work for alcohol. Self-administration outcomes were then categorized as either a value of ‘1’, indicating self-administration, or a value of ‘0’ indicating no self-administration had occurred.

Figure 1.

Figure 1.

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Sequence of the intravenous self-administration paradigm. Following an alcohol priming challenge, where BrACs reached 60 mg%, participants began the progressive ratio alcohol self-administration task. Subjective response measures and BrAC were measured every 15 minutes.

SR measures (BAES and POMS) were aligned with the subsequent self-administration outcome. For example, SR measures at TP1 were aligned with the self-administration outcome calculated from TP2-TP1. TP8 was not utilized in the analyses since there was no subsequent BrAC data recorded. In total, the data from 67 participants across 7 timepoints resulted in 461 data points (8 data points are missing from two participants who ended the self-administration early).

Multilevel modeling (MLM) was conducted using the ‘GLIMMIX’ procedure in SAS 9.4 to analyze the data, with the binary dependent variable of self-administration (1=self-administration, 0=no self-administration). The fixed effects included SR measures and time, as well as their interactions, to examine their influence on self-administration behavior. Covariates tested in each model included age, sex, and AUD severity. Only those that reached statistical significance or improved model fit were retained in the final models. Separate models examined sex and FH of alcohol-related as potential moderators of the effect of SR measures and time on self-administration. A random intercept was included to account for within-subject correlation due to repeated measures and individual differences in baseline likelihood of self-administration. The model utilized a binary distribution with a logit link function to account for the binary nature of the outcome. Main effects and interaction effects on self-administration were visualized using the ‘PROC PLM’ procedure in SAS, with effect plots displaying predicted probabilities and their 95% confidence limits. Each SR variable was tested for its association with motivation to self-administer alcohol in an independent statistical model. After examining each SR predictor independently, we included all predictors in a single model to assess their impact on self-administration while controlling for the effects of the other predictors. Results were considered statistically significant at p<.05.

Transparency and Openness

A report of how sample size was determined was previously published in Bujarski et al. (2018). Data exclusion, all manipulations, and study measures have been reported, and we followed Journal Article Reporting Standards. All data, analysis code, and research materials are available upon request to the corresponding author (LAR). This study’s design and its analysis were not preregistered.

RESULTS

Participant characteristics are reported in Table 1. Additionally, prior to testing the effects of subjective response measures on alcohol self-administration, we examined the relationships among subjective response constructs (Table 2). Specifically, we computed Pearson correlations using data collapsed across all timepoints. Significant positive correlations were observed between stimulation and liking (r(459)=0.46, p<.0001), stimulation and wanting (r(459)=0.40, p<.0001), wanting and liking (r(459)=0.77, p<.0001), and negative mood and sedation r(459)=0.16, p=.0007). Positive mood was significantly positively correlated with stimulation r(459)=0.82, p<.0001), wanting r(459)=0.32, p<.0001), and liking r(459)=0.39, p<.0001). Significant negative correlations were observed between positive mood and sedation r(459)=−0.31, p<.0001) and stimulation and sedation r(459)=−0.26, p<.0001). All other pairwise correlations were non-significant.

Table 1.

Participants demographic, substance use, and self-administration characteristics

Participant Demographics
Age (years) 29.11 ± 6.62
Gender (M/F) 36/31
Ethnicity
 White, non-Hispanic 57
 White, Hispanic 10
Education
 <12 years 1
 12 years (high school) 19
 14 years (associates) 11
 16 years (college) 27
 18 years (masters) 8
 20+ years (MD, JD, PhD) 1
Income
 <$15,000 15
 $15,000–$29,999 19
 $30,000–$44,999 9
 $45,000–$59,999 10
 $60,000–$74,999 5
 $75,000–$89,999 2
 $90,000–$104,999 3
 $105,000–$119,999 1
 >$120,000 3
Cigarettes Per Day (30 Days) 1.85 ± 4.31
AUD Current Symptom Count 2.43 ± 2.09
AUD Severity
 No AUD (0-1 AUD symptoms) 29
 Mild AUD (2-3 AUD Symptoms) 15
 Moderate AUD (4-5 AUD Symptoms) 16
 Severe AUD (6+ AUD Symptoms) 7
Family History (Positive/Negative) 20/47
Total Drinks (Past 30 Days; TLFB) 94.47 ± 56.53
Drinks Per Drinking Day (30 days) 5.3 ± 2.56
Total Self-Administration Button Presses 2806.22 ± 2587.19
Drinks Administered During Self-Administration 10.85 ± 4.95
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Stimulation as a predictor of self-administration

Higher stimulation levels were significantly associated with an increase in the likelihood of self-administration (Figure 2) (b=0.04, SE=0.02, t=2.26, p=.03). An increase in time, as a proxy for task demand, was significantly associated with a decrease in the likelihood of self-administration in this model (b=−0.3, SE=0.05, t=−5.9, p=<.0001). No significant interaction was observed between stimulation and time (p=.64). Sex and FH of alcohol-related problems, tested in separate models, did not moderate the effects of stimulation on self-administration (ps>.17).

Figure 2.

Figure 2.

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Higher subjective feelings of stimulation are associated with an increased likelihood of self-administration (p=0.03). An increase in time, which is a proxy for task demand, is associated with a decreased likelihood of self-administration (p<0.0001). The graph shows predicted probabilities of alcohol self-administration with 95% confidence intervals.

Sedation as a predictor of self-administration

There was no significant effect of sedation on the likelihood of self-administration (p=.85). An increase in time, as a proxy for task demand, was significantly associated with a decrease in the likelihood of self-administration in this model (b=−0.32, SE=0.05, t=−6.03, p<.0001). No significant interaction was observed between sedation and time (p=.26). Sex and FH of alcohol-related problems, tested in separate models, did not moderate the effects of sedation on self-administration (ps>.24).

Alcohol liking as a predictor of self-administration

Higher alcohol liking scores were significantly associated with an increase in the likelihood of self-administration (b=0.26, SE=0.05, t=5.15, p<.0001; Figure 3). An increase in time, as a proxy for task demand, was significantly associated with a decrease in the likelihood of self-administration in this model (b=−0.34, SE=0.06, t=−6.26, p<.0001). There was a significant interaction between liking and time such that as task demand increased, the influence of liking on self-administration decreased (b=−0.05, SE=0.02, t=−2.10, p=.04; Figure 3). Sex and FH of alcohol-related problems, tested in separate models, did not moderate the effects of liking on self-administration (ps>.49).

Figure 3.

Figure 3.

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Higher subjective feelings of liking alcohol are significantly associated with an increased likelihood of self-administration (p<0.0001). An increase in time, as a proxy for task demand, is associated with a decreased likelihood of self-administration (p<0.0001). At later timepoints, the impact of liking on self-administration decreased (p=0.04). The graph shows predicted probabilities of alcohol self-administration with 95% confidence intervals.

Alcohol wanting as a predictor of self-administration

Higher alcohol wanting scores were significantly associated with an increase in the likelihood of self-administration (b=0.22, SE=0.04, t=5.84, p<.0001; Figure 4). An increase in time, as a proxy for task demand, was significantly associated with a decrease in the likelihood of self-administration in this model (b=−0.31, SE=0.05, t=−5.77, p<.0001). No significant interaction was observed between wanting and time (p=.33). FH of alcohol-related problems significantly moderated the influence of wanting on self-administration, such that wanting scores significantly predicted the probability of self-administration more strongly in FH− individuals compared to FH+ individuals (b=−0.18, SE=0.08, t=−2.15, p=.03). A post hoc analysis tested the impact of wanting in individuals with and without a FH of alcohol-related problems separately. In FH− individuals, wanting levels were significantly associated with an increase in the likelihood of self-administration (b=0.22, SE=0.04, t=5.84, p<.0001). However, in FH+ individuals, the impact of wanting levels on self-administration only approached significance (b=0.11, SE=0.06, t=1.90, p=.06). Sex did not moderate the effects of wanting on self-administration (p=.61).

Figure 4.

Figure 4.

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Higher subjective feelings of wanting are associated with an increased likelihood of self-administration (p<0.0001). An increase in time, as a proxy for task demand, is associated with a decreased likelihood of self-administration (p< 0.0001). The effect of wanting on self-administration differs between individuals with and without a FH of alcohol-related problems such that wanting score significantly predicted the probability of self-administration better in individuals without a FH of alcohol-related problems compared to individuals with a FH (p=0.03). The graph shows predicted probabilities of alcohol self-administration with 95% confidence intervals.

Negative mood as a predictor of self-administration

There was no significant effect of negative mood on the likelihood of self-administration (p=.95). An increase in time, which is a proxy for task demand, was significantly associated with a decrease in the likelihood of self-administration in this model (b=−0.32, SE=0.05, t=−6.05, p<.0001). No significant interaction was observed between negative mood and time (p=.79). There was a significant three-way interaction between negative mood, time, and FH (b=0.08, SE=0.04, t=2.09, p=.04). Among FH− individuals, higher levels of negative mood at earlier timepoints were associated with an increased likelihood of self-administration compared to FH+ individuals (Figure 5). However, this relationship was no longer observed as time progressed and task demands increased. In other words, as task demand increased, negative mood was no longer associated with self-administration in either FH+ or FH− individuals. Sex did not moderate the effects of negative mood on the likelihood of self-administration (p=.11).

Figure 5.

Figure 5.

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For FH- individuals, higher levels of negative mood at earlier timepoints, but not later time points, was associated with an increased likelihood of self-administration in comparison to FH+ individuals (p=0.04). The graph shows predicted probabilities of alcohol self-administration with 95% confidence intervals.

Positive mood as a predictor of self-administration

There was no significant effect of positive mood states on the probability of self-administration (p=.12). An increase in time, as a proxy for task demand, was associated with a decrease in the likelihood of self-administration in this model (b=−0.31, SE=0.05, t=−5.90, p<.0001). No significant interaction was observed between positive mood and time (p=.54). Sex and FH of alcohol-related problems, tested in separate models, did not moderate the effects of positive mood on self-administration (ps >.19).

Combined Predictors Model

When all SR predictor variables were included in a single model, wanting emerged as the only significant SR predictor of self-administration. Higher levels of wanting were associated with a greater likelihood of self-administration (b=0.14, SE=0.05, t=2.64, p=.009). An increase in time, as a proxy for task demand, was associated with a decrease in the probability of self-administration in this model (b=−0.33, SE=0.06, t=−5.89, p<.0001). Liking demonstrated a trend towards significance such that an increase in liking was associated with an increased likelihood of self-administration (b=0.13, SE=0.08, t=1.79, p=.08).

DISCUSSION

In the current study, we investigated how subjective responses to alcohol impact the motivation to self-administer alcohol during a progressive ratio task in individuals who drink heavily, the majority of whom meet criteria for AUD. By examining these relationships across multiple time points during the task, this study offers deeper insight into how subjective responses and motivation to self-administer alcohol interact as the task demand increases. We found that greater levels of stimulation, as well as wanting and liking alcohol, predicted increased self-administration. Additionally, we found that family history of alcohol-related problems moderated the impact of alcohol-induced negative mood and wanting on motivation to self-administer alcohol. We did not observe that sex moderated the relationships between SR to alcohol and self-administration, contributing to the existing mixed findings in the literature (Cyders et al., 2016; A. King et al., 2021; Nieto et al., 2022; Schuckit, 2000).

Our study identified that stimulation in response to alcohol was a significant predictor of increased self-administration throughout the duration of the task (i.e., across increasing levels of task demand). These findings align with our hypothesis and support prior research, which has demonstrated that heightened alcohol-induced stimulation predicts heavy alcohol use and the development of AUD symptomatology over time (A. C. King et al., 2011, 2014). Interestingly, in the primary study, stimulation to alcohol, which was measured during the alcohol priming phase prior to the progressive ratio task, did not predict overall self-administration (Bujarski et al., 2018). The differences in these findings suggest that levels of stimulation captured during the self-administration task itself may be more sensitive to motivation to self-administer alcohol, compared to levels of stimulation captured during the initial alcohol priming period. Contrary to our hypothesis, sedation was not a significant predictor of self-administration. Our findings differ from the previous analysis that focused exclusively on the priming dose response, which found that higher levels of sedation during the priming phase of the paradigm predicted overall lower self-administration (Bujarski et al., 2018). Thus, feelings of sedation captured during the initial alcohol priming may better predict the motivation to self-administer alcohol, compared to feelings of sedation captured later during the self-administration task. Taken together, these findings suggest that the impact of SR on motivation to self-administer alcohol may vary across the duration of a “drinking episode.”

Our findings revealed that both liking and wanting alcohol were significant predictors of alcohol self-administration. Notably, in preclinical studies, where subjective measures cannot be used, the concept of ‘wanting’ alcohol is often assessed through behaviors that indicate a desire to consume alcohol, such as self-administration (Cyders et al., 2021; Foo et al., 2019). Our study confirms that the wanting alcohol, as measured by a subjective question, is significantly correlated with the observable behavior of working for alcohol, thus highlighting its translational relevance. Liking, but not wanting alcohol, interacted with time, such that as time increased, which is a proxy for task demand, liking alcohol no longer predicted self-administration. These findings align with the incentive salience theory of addiction, which posits that wanting and liking associated with substance use are distinct but interrelated processes (Berridge & Robinson, 2016). Additionally, this theory proposes, as addiction progresses, wanting for the substance becomes amplified independent of liking (Berridge & Robinson, 2016). Our results suggest that while both liking and wanting alcohol initially predicted motivation to self-administer alcohol, the influence of liking, but not wanting, diminished as the effort required for self-administration increased. Additionally, wanting emerged as the only significant SR predictor of self-administration when SR variables were combined into a single model. These findings suggest that the desire or craving for alcohol may be a key factor driving alcohol consumption behaviors. Interestingly, wanting scores predicted self-administration more strongly in FH-individuals, suggesting that those with a family history may be self-administering alcohol for reasons that extend beyond the experience of craving/wanting. These findings suggest that the desire or craving for alcohol may be a primary driver of effort-demanding self-administration behavior, overshadowing other subjective response predictors such as liking, stimulation, and mood. This highlights the potential importance of targeting ‘wanting’ in interventions aimed at reducing self-administration, as it appears to be the most robust factor influencing the likelihood of substance use in this context.

Neither positive nor negative mood significantly predicted self-administration, which aligns with findings from the previous study focused on the priming dose effects (Bujarski et al., 2018). Our analysis, however, revealed a significant three-way interaction between negative mood, FH of alcohol-related problems, and time. At earlier time points, when task demands were low, negative mood predicted increased self-administration in FH− individuals, but not in FH+ individuals. These findings suggest that individuals with a family history of alcohol-related problems may have other factors influencing their alcohol consumption behaviors beyond negative mood. Indeed, the development of AUD has been associated with both the ‘internalizing’ pathway, which involves difficulties in emotion regulation, and the ‘externalizing’ pathway, characterized by impaired behavioral control (Hardee et al., 2018). Previous research indicates that individuals with a FH of alcohol-related problems may be more likely to develop AUD through an externalizing pathway (Kendler et al., 2021). Our results align with these findings, indicating that individuals with a FH of alcohol-related problems may not be motivated to consume alcohol in response to internalizing symptoms, such as negative mood, compared to individuals without a FH.

The results of this study should be considered in light of both its strengths and limitations. While the sample size is relatively small (n=67), a notable strength is the use of seven data points per subject, which increases statistical power and allows us to examine the temporal dynamics of the data. Another major strength of this study was the use of the progressive-ratio self-administration task, which is a relevant translational paradigm from preclinical models of addiction. Moreover, analyzing multiple time points throughout the task offers a more nuanced and detailed examination of how SR influences the motivation to self-administer alcohol and how these interactions evolve as task demands increase. This approach extends beyond previous studies by providing a more comprehensive understanding of the dynamic relationship between SR and motivation to consume alcohol. It is important to consider that while all participants met the heavy drinking inclusion criteria, not all had an AUD. There was a small representation of individuals with severe AUD, and therefore results might vary in a sample with a larger proportion of individuals with severe AUD. Another consideration is the difference between the route of alcohol administration and the environment in which alcohol self-administration occurred. While intravenous alcohol administration in a controlled lab setting allows for precise measurement and control over alcohol exposure, it differs from typical oral consumption in real-world environments. These differences may influence how participants experience subjective responses to alcohol, which may limit the generalizability of our findings to naturalistic drinking settings. Finally, future research should include a more ethnically diverse sample to improve the generalizability of the findings.

Overall, the current study provided evidence that SR to alcohol predicted self-administration of alcohol during a progressive-ratio task. Specifically, stimulation, wanting, and liking of alcohol were predictors of increased self-administration during the progressive ratio task. We did not observe that sex moderated the relationships between SR to alcohol and self-administration. On the other hand, the absence of having FH of alcohol-related problems influenced the impact of wanting and negative mood on self-administration, highlighting the importance of considering family history when investigating SR. This indicates that individuals with a FH may experience differences in how SR impact their motivation to consume alcohol and the potential for subsequent problems, possibly indicating distinct pathways or risk factors for developing alcohol-related issues. In closing, this dynamic analysis of SR and motivation for alcohol expands the literature on SR as a maintenance factor for AUD. It revealed that stimulation, liking, and wanting of alcohol predict subsequent alcohol self-administration under progressive ratio demand and in a sample of individuals who drink heavily.

Public Health Significance:

This study demonstrates that subjective responses to alcohol can predict motivation to continue consuming alcohol in a laboratory setting, and that family history of alcohol-related problems may influence these associations.

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