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. Author manuscript; available in PMC: 2024 Feb 1.
Published in final edited form as: Alcohol Clin Exp Res (Hoboken). 2023 Jan 1;47(2):414–424. doi: 10.1111/acer.15003

Heightened motor impairment as a protective factor against heavy drinking in those with high alcohol-induced disinhibition

Holley C Allen 1, Jessica Weafer 1, Michael J Wesley 2, Mark T Fillmore 1
PMCID: PMC9991985  NIHMSID: NIHMS1861609  PMID: 36549890

Abstract

Background:

Behavioral disinhibition and motor impairment are both acutely elevated following alcohol consumption, and individual differences in sensitivity to alcohol-induced increases in these effects are associated with drinking habits. Specifically, high alcohol-induced disinhibition and low motor impairment have been identified as separate markers for alcohol-related problems. This study tested the degree to which alcohol-induced disinhibition and motor impairment jointly predict heavy drinking. We hypothesized that heavier drinkers would exhibit a combination of high sensitivity to alcohol-induced disinhibition and low sensitivity to its motor impairing effect.

Methods:

Data from three studies were aggregated to comprise a sample of 96 young adults. Participants’ motor coordination (grooved pegboard) and behavioral disinhibition (cued go/no-go) were assessed following consumption of 0.65 g/kg alcohol and a placebo.

Results:

As BAC was ascending, alcohol increased motor impairment and disinhibition compared to placebo. Combined effects at this time of alcohol on motor impairment and disinhibition predicted typical drinking habits. Specifically, a combination of high sensitivity to alcohol’s disinhibiting effect and low sensitivity to its motor impairing effect was associated with heavy drinking. As BAC was descending, only reduced sensitivity to motor impairment remained as a predictor of heavy drinking.

Conclusions:

The findings suggest that although motor impairment following alcohol consumption is associated with certain negative outcomes (e.g., increased risk for physical injury and motor vehicle accidents), such heightened motor impairment from alcohol may actually serve as a protective factor against the excessive drinking that can accompany the disinhibiting effect of alcohol.

Keywords: Alcohol Sensitivity, Acute Tolerance, Behavioral Disinhibition, Motor Coordination, Cued Go/No-Go

Introduction

Traditional theories regarding the addictive properties of alcohol focus primarily on the positive or rewarding effects of the drug (Stewart et al., 1984; di Chiara et al., 1996; Koob, 2003). For example, it has been posited that excessive alcohol consumption is a result of alcohol priming effects such that initial drinking reinforces or “primes” continued alcohol consumption (Ludwig et al., 1974). Pre-clinical studies and studies in humans have demonstrated that, after a small dose of alcohol, laboratory animals and humans are “primed” to consume greater amounts (de Wit & Chutuape, 1993; Fillmore & Rush, 2001; Fillmore, 2001; Ludwig et al., 1974). This is thought to reflect alcohol effects on reward mechanisms whereby the positive subjective effects of alcohol reinforce additional consumption (Stewart et al., 1984; Koob & Le Moal, 1997; Gilman et al., 2008). Moreover, there are many studies showing that rewarding or pleasurable effects of alcohol are associated with heavy drinking (King et al., 2011) and heightened risk for alcohol use disorder (AUD; Evans & Levin, 2003; Newlin & Thomson, 1990). Indeed, evidence of a heightened sensitivity to the rewarding effect of alcohol is considered a valid indication of risk for drinking-related problems. The evidence is not entirely consistent, however, as survey studies have found that drinkers often report fewer rewarding effects from alcohol as they begin to escalate their drinking over time (Ostafin et al., 2010; Tibboel et al., 2015). Such reports raise questions about alcohol’s rewarding effects as a sufficient explanation for drinkers’ escalation of alcohol use over time and the development of AUD.

In recent years, other acute responses to alcohol have become implicated in the escalation of drinking and development of AUD. One such effect is the acute impairing effect of alcohol on inhibitory control of behavior. Alcohol has a well-known impairing effect on behavioral inhibition, increasing likelihood of acting impulsively and engaging in potentially dangerous or socially inappropriate actions while drinking (e.g., continuing to drink, driving under the influence, aggression, risky sexual behavior). In the laboratory, behavioral disinhibition is measured with behavioral tasks such as stop-signal and cued go/no-go tasks. These tasks are primarily reaction time measures that require participants to quickly respond (i.e., button press) to a series of go cues but also to intermittently suppress their response to the occasional occurrence of a stop cue. The frequent display of go signals makes responding prepotent, requiring participants to overcome this response prepotency to inhibit action to the occasional occurrence of a stop cue. Disinhibition is measured by participants’ failure to inhibit responses to stop cues. These tasks are sensitive to the acute disinhibiting effect of alcohol such that even moderate alcohol doses that yield BACs at or below 80 mg/dl significantly decrease the drinker’s ability to suppress inappropriate reactions (e.g., Fillmore & Vogel-Sprott, 1999; de Wit et al., 2000; Fillmore et al., 2005; McCarthy et al., 2012; Weafer & Fillmore, 2016). There is evidence of marked individual differences in the degree to which alcohol increases behavioral disinhibition (Weafer & Fillmore, 2008; Gan et al., 2014; Allen et al., 2021). Some drinkers display modest disinhibiting effects to alcohol whereas others show pronounced behavioral disinhibition following the same dose. Moreover, there is growing evidence that individual differences in alcohol-induced disinhibition might be meaningful predictors of the drinker’s risk for developing AUD. For example, greater disinhibition following alcohol consumption is associated with increased ad libitum consumption in the laboratory (Weafer & Fillmore, 2008; Gan et al., 2014) and with a history of heavy binge drinking (Marczinski et al., 2007).

Adding to the complexity of the acute disinhibition-drinking relationship is the dynamic nature of alcohol effects over time. Chronic alcohol tolerance, or reduced sensitivity to the effects of alcohol over repeated and regular use, is observed among a range of alcohol effects including sensory, motor, and cognitive functions (Goldberg, 1943; LeBlanc et al., 1973). Tolerance can also accrue over the time-course of a single dose of alcohol. (Mellanby, 1919; Martin & Moss, 1993). Such “acute tolerance” is indicated by a rapid decrease in sensitivity to the alcohol effect simply as a function of exposure time and independent of BAC. Acute tolerance is evident in a variety of cognitive, behavioral, and psychological effects of alcohol whereby they tend to decline over the time course of a dose of alcohol when measured at the same BAC on the ascending and descending limbs of the BAC curve (Fillmore et al., 2005; Hendershot et al., 2015).

Development of tolerance is not consistent across all alcohol effects. In fact, some effects, like the disinhibiting effect of alcohol, fail to reliably exhibit chronic or acute tolerance in all drinkers (Fillmore et al., 2005; Allen et al., 2021; Weafer & Fillmore, 2008). Recent research from our laboratory assessed how these individual differences in sensitivity to the effects of a single dose of alcohol could be a marker for heavy “at-risk” drinking (Allen et al., 2021). We showed that, compared with lighter drinkers, heavy drinkers displayed heightened sensitivity to the rewarding effect of alcohol as BAC was rising, and showed little attenuation of the rewarding and disinhibiting effects of alcohol later after drinking, when BAC was declining and acute tolerance would normally have time to accrue. These findings demonstrate the potential complex manner in which different alcohol effects and their time courses of action from a single alcohol dose can operate jointly to predict heavy drinking.

Acute motor impairment from alcohol is another effect that might interact with alcohol’s disinhibiting effect to elevate the risk for heavy drinking. Heavy drinkers develop tolerance to the impairing effects of alcohol on motor coordination including body sway, slowed reaction time, and impaired fine motor control (Brumback et al., 2017; Fillmore & Weafer, 2012; Goldberg, 1943; Miller et al., 2012). Heightened chronic and acute tolerance to these effects is associated with increased risk for AUD (Schuckit, 1985, 1994; Lex et al., 1988; Evans & Levin, 2003) and driving under the influence (Vogel-Sprott, 1992; Weafer & Fillmore, 2012). The ability to maintain motor coordination after alcohol consumption might also perpetuate a drinking episode because the drinker retains the physical capability to continue drinking (Fillmore & Weafer, 2012). As such, sensitivity to alcohol’s motor impairing effect could serve as either a risk or protective factor when considered in conjunction with drinkers’ degree of alcohol-induced disinhibition. For example, some individuals might be highly sensitive to alcohol’s disinhibiting effect, which contributes to subsequent excessive alcohol consumption. However, if they are also highly sensitive to alcohol-induced motor impairment, they might be physically unable to continue drinking. By contrast, those who experience heightened disinhibition from alcohol but are less sensitive to its motor impairing effect might be at elevated risk for excessive drinking as they are physically able to act on their disinhibition to continue drinking in the situation.

The current study tested the acute disinhibiting and motor impairing effect of a controlled dose of 0.65 g/kg alcohol in a large sample of young adult drinkers who reported a broad range of typical alcohol consumption. The study tested the degree to which individual differences in the motor impairing and disinhibiting effect of the dose were predictive of the participants’ drinking habits. The study aimed to identify specific alcohol response profiles that predicted heavy drinking. We hypothesized that heavier drinkers would exhibit high sensitivity to alcohol’s disinhibiting effect coupled with low sensitivity to its motor impairing effect.

Method

Participants

Alcohol administration studies are typically limited in terms of sample size in large part because they are time-consuming and resource intensive. Small sample size precludes the ability to test the relationship of peoples’ drinking habits with individual differences in their acute responses to alcohol. Therefore, we aggregated data from three prior studies to comprise a sufficiently large sample size (N = 96) to test our hypothesis. The aggregate sample of young adult social drinkers was comprised of participants from three separate studies conducted in the investigators’ laboratory (Weafer & Fillmore, 2012; Roberts et al., 2013; Miller & Fillmore, 2014). Sample sizes from these studies were N = 54 (Weafer & Fillmore, 2012), N = 24 (Miller & Fillmore, 2014), and N = 20 (Roberts et al., 2013), totaling 96 participants. Participants were between 21- and 33-years-old (M = 23.43, SD = 2.88) and were recruited for participation in research projects assessing the effects of alcohol on behavioral and cognitive functions. The only participants included in these three parent studies that were excluded from the current study was a clinical sample of those diagnosed with and taking medication for ADHD (n = 19) recruited for a study by Roberts et al. (2013). All other participants from these studies were included.

All experiments measured acute effects of alcohol on disinhibition and motor coordination in healthy young adults. Studies included the two counterbalanced dose conditions (0.65 g/kg abs. alc. and a placebo). Responses were assessed at two time points selected to occur during the ascending and descending limbs of the blood alcohol curve in the active dose condition. This allowed for the evaluation of participants’ sensitivity at two time points after drinking: an early point when BAC was rising, and a later point when BAC began to decline, and acute tolerance was expected to accrue. Participants in all studies were drawn from the same population using the same inclusion and exclusion criteria. These criteria included young adult participants between 21 and 35 years old with no history of AUD. Volunteers were excluded from participation if they self-reported a history of head trauma or other central nervous system injury. Potential participants were also excluded if they reported a psychiatric disorder or substance use disorder (SUD). To further screen for AUD, the Short-Michigan Alcohol Screening Test (S-MAST; Selzer et al., 1975) was administered, and volunteers with a score of five or higher were excluded from participation. Volunteers who screened positive for recent drug administration using urinalysis were also excluded. No volunteers who were pregnant or breast feeding participated in the research, as was determined by self-report measures and urine human chorionic gonadotropin levels.

Participants were recruited from the community using flyers, posters, online advertisements, and newspaper advertisements. All volunteers responded to advertisements by calling the laboratory. All volunteers completed a phone screen procedure conducted by a research assistant and provided informed consent prior to participation and all parent studies were approved by the University of Kentucky Medical Institutional Review Board. All participants were compensated for their participation. Eligible volunteers were told that the purpose of the study was to examine the effects of alcohol on behavior. The aggregate sample was comprised of 43 women and 53 men. In terms of racial makeup, participants self-identified as Caucasian (n = 82), African American/Black (n = 10), or as other (n = 4).

Measures

Drinking Habits

Drinking habits were measured using the Personal Drinking Habits Questionnaire (PDHQ; Vogel-Sprott, 1992). This self-report questionnaire was used to assess participants’ typical drinking patterns. The PDHQ measured two aspects of participants’ current and typical drinking behavior including (1) frequency, or the typical number of drinking occasions per week and (2) quantity per occasion, the number of standard drinks consumed during a typical drinking episode. All participants were provided with an infographic defining one standard drink (i.e., 12 oz beer, 5 oz wine, 1.5 oz liquor, 8–10 oz malt liquor; (NIAAA, 2000). From these measures, we calculated participants’ quantity per week by multiplying their typical drinking frequency and number of standard drinks per typical drinking episode.

Disinhibition

A cued go/no-go reaction time task was used to measure participants’ response inhibition to no-go targets and their reaction time to go targets (e.g., Fillmore & Weafer 2004). The task required finger presses on a keyboard and measured the ability to inhibit prepotent behavioral responses of executing a key press. Cues (vertical and horizontal rectangles) provided preliminary information regarding the type of target stimulus (i.e., go or no-go) that was likely to follow, and the cues had a high probability of signaling the correct target. Participants were instructed to press the forward slash (/) key on the keyboard as soon as a go (green rectangle) target appeared and to suppress the response when a no-go (blue rectangle) target was presented. The go cue conditions were of particular interest. Go cues generate response prepotency which speeds response time to go targets. However, subjects must overcome this response prepotency to inhibit the response if a no-go target is subsequently displayed. Response inhibition was measured by the proportion of no-go targets in which subjects failed to inhibit a response (p-inhibition failures) during the test. Disinhibition was indicated by a higher proportion of inhibition failures (i.e., greater p-inhibition failure score). Reaction time (RT) was measured in milliseconds from the onset of the target until the key was pressed. A test required approximately 15 min to complete. The validity of these types of tasks is well-established through studies showing that go/no-go tasks are sensitive to inhibitory deficits characteristic of dementia (O’Callaghan et al., 2013), ADHD (Tannock, 1998), and the impairing effects of alcohol (Fillmore & Weafer, 2012; Weafer & Fillmore, 2016).

Motor Coordination

Motor coordination was measured using a grooved pegboard task (Lafayette Instruments, Lafayette, IN). During this task, participants place pegs into keyhole-shaped holes. The grooved pegboard contains a rectangular metal surface with 25 holes arranged in five rows of five holes. Each of the holes has a rounded side and smaller square side (a groove). The orientation of the groove in each hole varies so that no two adjacent holes have the same orientation. Each peg is 3 mm in diameter and 2.5 cm long and has a rounded side and grooved side. Pegs fit into the holes like a key would fit into a lock. Participants are required to pick up pegs one at a time and place them in holes. They fill one row at a time and work from left to right. A trial on the grooved pegboard task was completed when all 25 holes were filled, and the time to complete a trial was the measure of interest. A grooved pegboard test consisted of four trials, and the time to complete each of the trials was averaged to calculate the measure of motor coordination.

Procedure

All studies employed common methodology and procedures for testing alcohol effects on inhibitory control and motor coordination. Studies used a counterbalanced, repeated dose design with two alcohol dose conditions (0.65 g/kg and placebo), and all studies used the same time course of response testing under the doses. All sessions were conducted at the Human Behavioral Pharmacology Laboratory at the University of Kentucky between the hours of 10 AM and 6 PM. Participants were required to abstain from alcohol for 24 h prior to each session and fast for 4 h prior to each session. Before testing sessions began, body weight was measured, a BAC of 0.0 mg/dl was verified using a breathalyzer [Intoxilyzer, Model 400 (CMI Inc., Owensboro, KY)], and urine samples were collected to ensure that participants were negative for recent drug use and pregnancy. Urine samples were tested for the presence of metabolites of amphetamine, methamphetamine, barbiturates, benzodiazepines, cocaine, opiates, methadone, phencyclidine, tricyclic antidepressants, and tetrahydrocannabinol (THC; ICUP Drugscreen; Instant Technologies, Norfolk, VA). Volunteers who tested positive for cannabis use and reported use within the past 4 days and those who tested positive for any other drug metabolites were excluded from participation

Familiarization

All participants attended a familiarization session, during which they were introduced to laboratory procedures and completed practice trials of the cued go/no-go and grooved pegboard tasks. Participants also completed questionnaires on which they reported their drug and alcohol use history, health status, and general demographic information.

Test sessions

Participants were tested on two separate occasions under different doses of alcohol, 0.0 g/kg (placebo) and 0.65 g/kg. Sessions were conducted on different days separated by a minimum of 1 day and a maximum of 7 days. The dose order was counterbalanced across participants.

The active dose (0.65 g/kg) was calculated based on participants’ body weight and was divided equally into two glasses, each containing one part alcohol (96.4%) and three parts carbonated soda. Participants consumed the dose within 6 mins. This dose administration typically produces an average peak BAC of 80 mg/100 ml about 60–70 minutes after consumption (Marczinski & Fillmore, 2003). The placebo administration was identical except the beverage was comprised of 4 parts carbonated soda of equal volume to the active dose. Additionally, a small amount of alcohol (3 ml) was floated on the surface of the beverage after dividing it into two equal glasses. The glasses were sprayed with an alcohol mist that resembled condensation and provided a strong scent of alcohol. Prior research indicates that participants believe these beverages contain alcohol although they do not cause increases in BAC (Fillmore & Vogel-Sprott, 1998).

Following beverage consumption, participants completed behavioral tasks at two separate time points. These time points corresponded to points on the ascending (test 1) and descending limbs (test 2) of the BAC curve during which participants’ BAC is expected to be comparable. Test 1 began 30–35 minutes following administration and test 2 began 90–95 minutes after administration. Participants’ BACs during test times were measured using a breathalyzer, and BAC was also measured 60 minutes after administration, when peak BAC (0.65 g/kg) was expected. All participants remained in the laboratory until their BAC fell below 20 mg/100 ml. Transportation home by taxi was provided after sessions. After completing the final test session, participants were debriefed and paid for their participation.

Data Analyses

To confirm that our measures of disinhibition and motor impairment were sensitive to the effects of 0.65 g/kg alcohol a 2 Dose (alcohol and placebo) × 2 Test (test 1 and test 2) analysis of variance (ANOVA) was conducted. This ANOVA also tested for acute tolerance to the disinhibiting and motor impairing effects of alcohol. Regression analyses tested the degree to which individual differences in participants’ sensitivity to alcohol-induced motor impairment and disinhibition at times 1 and 2 were predictive of their typical drinking habits. Sensitivity to the disinhibiting and motor impairing effects of alcohol were tested separately and jointly as predictors of drinking habits. All analyses were tested using a significance threshold of p < 0.05 and were completed using SYSTAT 13.

Results

Drinking Habits

The sample reported a mean drinking frequency of 2.2 days per week (SD = 1.1), and a mean quantity of 4.8 standard drinks per drinking occasion (SD = 2.1). The mean duration of participants’ drinking occasions was 3.5 hours (SD = 1.4). The average quantity per week was 10.7 standard drinks (SD = 7.3). Minimum and maximum values are reported in Table 1 and demonstrate marked individual differences in typical drinking habits among the sample.

Table 1.

Descriptive statistics of participants’ alcohol drinking habits (N = 96)

Alcohol Use Mean SD Minimum Maximum
Frequency (Days/Week) 2.2 1.3 0.3 7.0
Duration (Hours/Occasion) 3.5 1.4 0.5 8.0
Quantity per Occasion 4.8 2.2 1.0 10.0
Quantity per Week 10.7 7.3 1.0 35.0
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Frequency, typical number of days alcohol consumed per week; Duration, typical duration of a drinking occasion in hours; Quantity per Occasion; Quantity per Week, calculated by multiplying participants’ typical number of drinking occasions and drinks consumed per occasion.

Blood Alcohol Concentrations

The mean BAC during test 1 on the ascending limb of the BAC curve was 68.9 mg/100 ml (SEM = 2.1). The mean BAC during test 2 on the descending limb was 65.5 mg/100 ml (SEM = 1.131). Mean BACs during tests 1 and 2 did not differ statistically (t(95) = 1.8, p = 0.078) nor did they differ beyond the measurement error of the breathalyzer device (< +/− 4 mg per 100 ml). The mean peak BAC was 74.0 mg/100 ml (SEM = 1.2).

Acute Sensitivity and Tolerance

Figure 1A plots the mean time to complete the pegboard. The figure shows that alcohol prolonged time to complete the task (i.e., impaired motor coordination) compared with placebo on test 1 and test 2. However, the figure also shows that motor impairment decreased from test 1 to test 2 under alcohol consistent with acute tolerance while showing little change over the same time period following placebo. Acute sensitivity and tolerance to alcohol effects on motor coordination were tested by a 2 Dose × 2 Test ANOVA. A main effect of dose was obtained confirming alcohol impairment compared with placebo, F(1, 95) = 46.6, p < 0.001. Moreover, a Dose × Test interaction was also obtained, (F(1, 95) = 15.8, p < 0.001) indicative of the acute tolerance observed from test 1 to test 2 under alcohol. A paired samples t test comparing motor impairment measured on tests 1 and 2 under alcohol confirmed that the time to complete the pegboard task was significantly greater on test 1 (M = 55.0, SD = 7.4) than on test 2 (M = 53.1, SD = 6.8; t(95) = 6.9, p < 0.001).

Figure 1.

Figure 1.

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Measures under placebo (0.0-g/kg; white box) and alcohol (0.65-g/kg; lined box) conditions at times corresponding to the ascending (Time 1) and descending (Time 2) limbs of the BAC curve during which participants’ BAC is expected to be comparable. Panel A reports mean pegboard completion times in seconds (s) for each condition at each time testing time. Panel B reports mean p-inhibition failures for each condition at each testing time. The capped vertical lines show standard errors of the mean.

Figure 1B plots the mean p-inhibition failures on no-go trials of the cued go/no-go task. The figure shows that alcohol increased p-inhibition failures compared with placebo on both test 1 and test 2. Acute sensitivity and tolerance to alcohol effects on behavioral disinhibition were tested by a 2 Dose × 2 Test ANOVA. A main effect of dose was obtained, confirming increased disinhibition following alcohol relative to placebo, F(1, 95) = 26.9, p < 0.001. A main effect of test was also observed, indicating that participants tended to perform better on test 2 regardless of dose condition, F(1, 95) = 10.3, p = 0.002. No acute tolerance was observed as indicated by the lack of a Dose × Test interaction (p = 0.229).

A 2 Dose × 2 Test ANOVA tested for acute sensitivity and tolerance to alcohol effects on reaction time on go cue trials of the cued go/no-go task. No main effects were obtained for dose or test (ps > 0.21), and no acute tolerance was observed as indicated by the lack of a Dose × Test interaction (p = 0.22). When averaged across tests 1 and 2, mean reaction times following placebo and active alcohol beverages were 301.9 ms (SD = 28.4) and 304.3 ms (SD = 31.2) respectively. Based on these results, a speed-accuracy tradeoff is not a plausible explanation for the disinhibiting effect of alcohol observed by this task.

Acute Alcohol Sensitivity in Relation to Drinking Habits

To examine the degree to which alcohol sensitivity to motor impairment and disinhibition predicted individual differences in participants’ drinking habits, sensitivity scores were generated. Acute sensitivity scores were calculated for each participant by subtracting their response following placebo from their response following alcohol on tests 1 and 2. Scores were calculated for motor impairment and disinhibition with a higher score indicating greater sensitivity to the effect of alcohol. Sensitivity scores were then z-transformed, allowing scores across measures to be compared as predictors of drinking habits in a simultaneous multiple linear regression equation.

Multiple linear regression models tested the degree to which sensitivity to the acute effects of alcohol on inhibitory control and motor coordination predicted drinkers’ typical quantity of alcohol consumption per week and the typical frequency of drinking occasion per week. Sensitivity scores at time 1 and time 2 as predictors of typical quantity and frequency of alcohol consumption per week are presented in Table 2.

Table 2.

β-coefficients and statistics obtained from simultaneous regression of sensitivity scores to motor impairment, disinhibition (i.e., p-inhibition failures, and their interaction) at times 1 and 2 predicting typical quantity per week

Variable b SE t p
Time 1
 Motor impairment −1.82 0.82 −2.22 0.029*
 Disinhibition 0.73 0.91 0.80 0.425
 Motor impairment x disinhibition −2.11 1.02 −2.06 0.042*
Time 2
 Motor impairment −1.85 0.79 −2.34 0.022*
 Disinhibition −0.73 1.04 −0.70 0.484
 Motor impairment x disinhibition −1.50 1.23 −1.22 0.226
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Time 1: R2 = 0.11, adjusted R2 = 0.08, SE estimate = 6.99, df = 92

Time 2: R2 = 0.07, adjusted R2 = 0.04, SE estimate = 7.15, df = 92

Prior to regression analyses, we examined the distributions of key variables and completed outlier analyses. Figure 2 illustrates the distribution of each key variable (i.e., sensitivity to motor impairment at times 1 and 2, sensitivity to disinhibition at times 1 and 2, and typical weekly quantity). The figure shows that the key variables are relatively normally distributed. Normality was confirmed by analyses of skewness and kurtosis, which obtained values that did not violate the assumption of normality for all key variables (±2 skew, ±7 kurtosis; West et al., 1996). Outlier analyses were conducted, and no outlying values had a significant influence on the relationships of interest, therefore all subsequent analyses include these values.

Figure 2.

Figure 2.

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Box-and-whisker plots showing the distributions of variables: sensitivity to alcohol-induced motor impairment, sensitivity to alcohol-induced disinhibition, and typical quantity per week). Sensitivity scores for times 1 and 2 were calculated by subtracting participants scores following placebo from their scores following alcohol at each time point.

Typical quantity per week = the number of standard drinks participants self-reported consuming in a typical week; Box = interquartile range (IQR) where the line represents the median value; Whiskers = minimum and maximum values excluding outliers; X = mean value; Single Points = outliers.

Alcohol Response Early After Drinking (i.e., Time 1)

A multiple linear regression model tested the degree to which alcohol sensitivity to disinhibition and motor impairment at time 1 predicted participants’ typical quantity per week. Results showed that, early after drinking, alcohol sensitivity to disinhibition and motor impairment interacted as predictors of participants’ weekly consumption. Figure 3A plots this interaction, and it shows that among those with high sensitivity to the disinhibiting effect, those with little sensitivity to its motor impairing effect drank more compared to those with more sensitivity to the motor impairing effects. For typical frequency of consumption, lower sensitivity to motor impairment at time 1 was associated with more frequent drinking (b = −0.34, p = 0.010). Neither sensitivity to motor impairment nor the interaction of sensitivity scores at time 1 were related to typical frequency (ps > 0.27).

Figure 3.

Figure 3.

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Regression lines relating typical number of drinks consumed per week to sensitivity to alcohol-induced disinhibition and motor impairment. Panel A shows the relationship between sensitivity scores at time 1, and panel B shows this relationship at time 2. Low sensitivity to alcohol-induced disinhibition represents typical weekly quantity for those 1 SD below the mean value. High sensitivity to alcohol-induced disinhibition represents typical weekly quantity for those 1 SD above the mean value.

Alcohol Response Later After Drinking (i.e., Time 2)

A multiple linear regression model tested the degree to which sensitivity to the acute effects of alcohol on inhibitory control and motor coordination at time 2 predicted participants’ typical weekly quantity of alcohol consumption and showed that alcohol sensitivity to motor impairment predicted quantity (Figure 3B). The figure shows that those with little sensitivity to the motor impairing effect of alcohol at time 2 drank more than those who were highly sensitive to motor impairment. Neither sensitivity to alcohol-induced disinhibition nor the interaction of sensitivity scores predicted weekly quantity of alcohol consumption (ps > 0.22). For frequency of consumption the regression model showed that reduced alcohol sensitivity to motor impairment at time 2 was associated with more frequent drinking (b = −0.28, p = 0.028). Neither sensitivity to disinhibition nor the interaction of sensitivity scores at times 1 or 2 predicted typical weekly frequency of drinking (ps > 0.38).

Discussion

This study examined how the combined sensitivity to alcohol impairment of motor coordination and inhibitory control could indicate patterns of heavy drinking among young adults between 21 and 33 years old. Data were aggregated across several laboratory studies to overcome common limitations of alcohol administration studies, namely small sample sizes. The study showed that 0.65 g/kg alcohol increased participants’ motor impairment and disinhibition compared to placebo. At time 1, the combined effects of alcohol on motor impairment and disinhibition predicted participants’ typical drinking habits. Specifically, a combination of high sensitivity to alcohol’s disinhibiting effect coupled with low sensitivity to its motor impairing effect was associated with heavy drinking and at time 2, low sensitivity to motor impairment continued to predict to heavy drinking.

Our findings are consistent with prior literature establishing the relationship between heavy drinking and reduced sensitivity to alcohol-induced motor impairment (Brumback et al., 2017; Fillmore & Weafer, 2012; Goldberg, 1943; Miller et al., 2012). They add to this literature by indicating that, as BAC is rising, low sensitivity to alcohol impairment of motor coordination might best predict heavy drinking in those who are highly sensitive to the disinhibiting effect of alcohol. These data also build upon previous findings from our laboratory which suggest alcohol-induced disinhibition may be especially important as an important risk factor for heavy drinking when considered in conjunction with other acute alcohol effects (Allen et al., 2021). At time 1, sensitivity to alcohol-induced disinhibition alone did not predict drinking habits in our sample, further underscoring the importance of examining multiple acute alcohol effects simultaneously.

These findings also have important implications in terms of risky drinking patterns such as binge drinking. Heightened disinhibition and intact motor control early in a drinking episode may increase the likelihood of continued drinking such that the drinker will experience elevated impulsivity and retain the motor coordination needed to act on these impulses (i.e., take the next drink). Moreover, the disinhibiting effect of alcohol itself can be perceived as rewarding and contribute to further drinking, especially among young adults (Leeman et al., 2009). Therefore, increased drinking accompanied by tolerance to motor impairment may be compounded by high levels of disinhibition following alcohol consumption.

At time 2, reduced sensitivity to alcohol-induced motor impairment continued to be an important predictor of heavy drinking. This may relate to escalation of alcohol use such that repeated drinking contributes to the development of chronic tolerance to alcohol’s motor impairing effects over time. In turn, sustained motor coordination after drinking may contribute to overconsumption as drinkers maintain the physical capacity needed to continue drinking. By contrast, heightened sensitivity to motor impairment may operate as a protective factor against risk of overconsumption of the drug. This finding is rather counterintuitive, as motor impairment following alcohol consumption is generally considered to increase risk (e.g., Chikritzhs & Livingston, 2021; Mundt et al., 2009). However, future research is needed to examine the role of sensitivity to other alcohol effects as BAC is declining, as they may interact with alcohol’s motor impairing effects to contribute to heavy drinking and increased risk.

One limitation of this study is that we tested participants’ motor impairment and disinhibition at only two time points. Testing alcohol effects at multiple time points along the BAC curve would help to elucidate the time course of alcohol effects as they relate to drinking habits. Additionally, although data aggregation allowed for the composition of a large sample size, the current study was still underpowered to test sex differences in the observed relationships. Prior research supports the presence of sex differences in acute alcohol responses (e.g., Haut et al., 1989; Mills & Bisgrove, 1983; Nolen-Hoeksema, 2004; Weafer et al., 2010). Although extant literature shows mixed findings, some studies suggest that women tend to show higher sensitivity to alcohol-induced motor impairment (Wang et al., 2003; Miller et al., 2009) whereas men tend to show greater sensitivity to alcohol-induced disinhibition (Weafer & de Wit, 2014). Future research is needed to examine the potential role of sex differences in the relationship between alcohol-induced disinhibition, motor impairment, and heavy drinking.

Another limitation was the inclusion of single measures of motor coordination and disinhibition. The grooved pegboard task is sensitive to the motor impairing effects of alcohol but captures impairment of only fine motor coordination. Alcohol intoxication is also associated, at higher doses, with gross motor impairment (Nieschalk et al., 1999; Zoethout et al., 2012). Gross motor impairment likely plays a more direct role in drinkers’ ability to physically continue drinking as opposed to deficits in fine motor skills. To improve external validity, future research may integrate measures of alcohol impairment on gross motor skills (e.g., Heel-to-Toe Walking Task, the Standard Field Sobriety Test, dynamic balance tasks) to examine their role in heavy drinking in conjunction with the disinhibiting effect of alcohol. Regarding disinhibition, the cued go/no-no task models a very specific aspect of impulsive behavior, the ability to inhibit a prepotent behavioral response. Our findings might not generalize to other aspects of impulsivity, such as choice impulsivity and reward sensitivity which have also been linked to increased risk for AUD (Pardo et al., 2007; Hamilton et al., 2015). Additionally, we did not test the role that personality-level impulsivity may play in this relationship. A final issue of consideration is the correlational nature of this study. Because these data are cross-sectional and do not account for genetic factors, environmental, and personality characteristics of participants, no conclusions can be made regarding the direction of the relationship between acute alcohol effects and drinking habits.

In conclusion, the current study indicates that a pattern of heavy drinking can be marked by a combination of high sensitivity to alcohol’s disinhibiting effect coupled with low sensitivity to its motor impairing effect. The evidence highlights the dynamic nature of behavioral alcohol effects, how alcohol effects may work in conjunction, and the complex relationship between acute alcohol effects and drinking habits. Moreover, our findings suggest that although increased motor impairment following alcohol consumption is associated with certain negative outcomes (e.g., increased risk for physical injury and motor vehicle accidents), it may actually serve as a protective factor against alcohol overconsumption, especially among drinkers who are highly disinhibited following drinking.

Acknowledgments

This research was supported by Grant T32 AA027488 from the National Institute on Alcohol Abuse and Alcoholism. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institute on Alcohol Abuse and Alcoholism or the National Institutes of Health.

References

  1. Allen HC, Weafer J, Wesley MJ, Fillmore MT (2021) Acute rewarding and disinhibiting effects of alcohol as indicators of drinking habits. Psychopharmacology 238:181–191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Brumback T, Cao D, McNamara P, King A (2017) Alcohol-induced performance impairment: a 5-year re-examination study in heavy and light drinkers. Psychopharmacology 234(11):1749–1759. Available at: 10.1007/s00213-017-4577-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. de Wit H, Chutuape MA (1993) Increased ethanol choice in social drinkers following ethanol preload. Behavioural Pharmacology 4(1):29–36. Available at: 10.1097/00008877-199302000-00003. [DOI] [PubMed] [Google Scholar]
  4. de Wit H, Crean J, Richards JB (2000) Effects of d-amphetamine and ethanol on a measure of behavioral inhibition in humans. Behavioral Neuroscience 114(4):830–837. Available at: 10.1037/0735-7044.114.4.830. [DOI] [PubMed] [Google Scholar]
  5. di Chiara G, Acquas E, Tanda G (1996) Ethanol as a neurochemical surrogate of conventional reinforcers: The dopamine-opioid link. Alcohol 13(1):13–17. Available at: 10.1016/0741-8329(95)02034-9. [DOI] [PubMed] [Google Scholar]
  6. Chikritzhs T, Livingston M (2021) Alcohol and the risk of injury. Nutrients, 13(8):2777. Available at: 10.3390/nu13082777. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Evans SM, Levin FR (2003) Response to alcohol in females with a paternal history of alcoholism. Psychopharmacology 169(1):10–20. Available at: 10.1007/s00213-003-1474-2. [DOI] [PubMed] [Google Scholar]
  8. Fillmore MT, Rush CR (2001) Alcohol effects on inhibitory and activational response strategies in the acquisition of alcohol and other reinforcers: priming the motivation to drink. Journal of Studies on Alcohol 62(5):646–656. Available at: 10.15288/jsa.2001.62.646. [DOI] [PubMed] [Google Scholar]
  9. Fillmore MT (2001) Cognitive preoccupation with alcohol and binge drinking in college students: alcohol-induced priming of the motivation to drink. Psychology of Addictive Behaviors 15(4):325–332. Available at: 10.1037/0893-164X.15.4.325. [DOI] [PubMed] [Google Scholar]
  10. Fillmore MT, Marczinski CA, Bowman AM (2005) Acute tolerance to alcohol effects on inhibitory and activational mechanisms of behavioral control. Journal of Studies on Alcohol 66(5):663–672. Available at: 10.15288/jsa.2005.66.663. [DOI] [PubMed] [Google Scholar]
  11. Fillmore MT, Vogel-Sprott M (1998) Behavioral impairment under alcohol: cognitive and pharmacokinetic factors. Alcoholism: Clinical and Experimental Research 22(7):1476–1482. Available at: 10.1111/j.1530-0277.1998.tb03938.x. [DOI] [PubMed] [Google Scholar]
  12. Fillmore MT, Vogel-Sprott M (1999) An alcohol model of impaired inhibitory control and its treatment in humans. Experimental and Clinical Psychopharmacology 7(1):49–55. Available at: 10.1037/1064-1297.7.1.49. [DOI] [PubMed] [Google Scholar]
  13. Fillmore MT, Weafer J (2004) Alcohol impairment of behavior in men and women. Addiction 99(10):1237–1246. Available at: 10.1111/j.1360-0443.2004.00805.x. [DOI] [PubMed] [Google Scholar]
  14. Fillmore MT, Weafer J (2012) Acute tolerance to alcohol in at-risk binge drinkers. Psychology of Addictive Behaviors 26(4):693–702. Available at: 10.1037/a0026110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Gan G, Guevara A, Marxen M, Neumann M, Jünger E, Kobiella A, Mennigen E, Pilhatsch M, Schwarz D, Zimmerman US, Smolka MN (2014) Alcohol-induced impairment of inhibitory control is linked to attenuated brain responses in right fronto-temporal cortex. Biological Psychiatry 76(9):698–707. Available at: 10.1016/j.biopsych.2013.12.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gilman JM, Ramchandani VA, Davis MB, Bjork JM, Hommer DW (2008) Why we like to drink: a functional magnetic resonance imaging study of the rewarding and anxiolytic effects of alcohol. Journal of Neuroscience 28(18):4583–4591. Available at: 10.1523/JNEUROSCI.0086-08.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Goldberg L (1943) Quantitative studies on alcohol tolerance in man. The influence of ethyl alcohol on sensory, motor and psychological functions referred to blood alcohol in normal and habituated individuals. Acta Physiologica Scandinavica 5(Supplement XVI). [Google Scholar]
  18. Hamilton K, Mitchell M, Wing V, Balodis I, Bickel W, Fillmore MT, Lane S, Lejuez C, Littlefield A, Luijten M, Mathias C, Mitchell S, Napier T, Reynolds B, Schütz C, Setlow B, Sher K, Swann A, Tedford S, Moeller F (2015) Choice impulsivity: definitions, measurement issues, and clinical implications. Personality Disorders 6:182–198. Available at: 10.1037/per0000099. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Haut JS, Beckwith BE, Petros TV, Russell S (1989) Gender differences in retrieval from long-term memory following acute intoxication with ethanol. Physiology & Behavior 45(6):1161–1165. Available at: 10.1016/0031-9384(89)90103-0. [DOI] [PubMed] [Google Scholar]
  20. Hendershot CS, Wardell JD, Strang NM, Markovich MSD, Ramchandani VA (2015) Application of an alcohol clamp paradigm to examine inhibitory control, subjective responses, and acute tolerance in late adolescence. Experimental and Clinical Psychopharmacology 23(3):147–158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. King AC, de Wit H, McNamara PJ, Cao D (2011) Rewarding, stimulant, and sedative alcohol responses and relationship to future binge drinking. Archives of General Psychiatry 68(4):389–399. Available at: 10.1001/archgenpsychiatry.2011.26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Koob GF (2003) Neuroadaptive mechanisms of addiction: studies on the extended amygdala. European Neuropsychopharmacology 13(6):442–452. Available at: 10.1016/j.euroneuro.2003.08.005. [DOI] [PubMed] [Google Scholar]
  23. Koob GF, Le Moal M (1997) Drug abuse: hedonic homeostatic dysregulation. Science 278(5335):52–58. [DOI] [PubMed] [Google Scholar]
  24. LeBlanc AE, Gibbins RJ, Kalant H (1973) Behavioral augmentation of tolerance to ethanol in the rat. Psychopharmacologia 30(2):117–122. Available at: 10.1007/BF00421426. [DOI] [PubMed] [Google Scholar]
  25. Leeman RF, Toll BA, Taylor LA, Volpicelli JR (2009) Alcohol-induced disinhibition expectancies and impaired control as prospective predictors of problem drinking in undergraduates. Psychology of Addictive Behaviors 23(4):553–563. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lex BW, Lukas SE, Greenwald NE, Medelson JH (1988) Alcohol-induced changes in body sway in women at risk for alcoholism: a pilot study. Journal of Studies on Alcohol 49(4):346–356. Available at: 10.15288/jsa.1988.49.346. [DOI] [PubMed] [Google Scholar]
  27. Ludwig AM, Wikler A, Stark LH (1974) The first drink: psychobiological aspects of craving. Archives of General Psychiatry 30(4):539–547. Available at: 10.1001/archpsyc.1974.01760100093015. [DOI] [PubMed] [Google Scholar]
  28. Marczinski CA, Combs SW, Fillmore MT (2007) Increased sensitivity to the disinhibiting effects of alcohol in binge drinkers. Psychology of Addictive Behaviors 21(3):346–354. Available at: 10.1037/0893-164X.21.3.346. [DOI] [PubMed] [Google Scholar]
  29. Marczinski CA, Fillmore MT (2003) Preresponse cues reduce the impairing effects of alcohol on the execution and suppression of responses. Experimental and Clinical Psychopharmacology 11(1):110–117. Available at: 10.1037/1064-1297.11.1.110. [DOI] [PubMed] [Google Scholar]
  30. Martin C, Moss H (1993) Measurement of acute tolerance to alcohol in human subjects. Alcoholism: Clinical and Experimental Research 17(2):211–216. Available at: 10.1111/j.1530-0277.1993.tb00751.x. [DOI] [PubMed] [Google Scholar]
  31. McCarthy DM, Niculete ME, Treloar HR, Morris DH, Bartholow BD (2012) Acute alcohol effects on impulsivity: associations with drinking and driving behavior. Addiction 107(12):2109–2114. Available at: 10.1111/j.1360-0443.2012.03974.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Mellanby E (1919) Alcohol: its absorption into and disappearance from the blood under different conditions, in Special Report Series Monograph No. 31. Medical Research Committee, London. [Google Scholar]
  33. Miller MA, Fillmore MT (2014) Protracted impairment of impulse control under an acute dose of alcohol: a time-course analysis. Addictive Behaviors 39(11):1589–1596. Available at: 10.1016/j.addbeh.2013.10.035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Miller MA, Hays LR, Fillmore MT (2012) Lack of tolerance to the disinhibiting effects of alcohol in heavy drinkers. Psychopharmacology 224(4):511–518. Available at: 10.1007/s00213-012-2786-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Miller MA, Weafer J, Fillmore MT (2009) Gender differences in alcohol impairment of simulated driving performance and driving-related skills. Alcohol and Alcoholism 44(6):586–593. Available at: 10.1093/alcalc/agp051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Mills KC, Bisgrove EZ (1983) Body sway and sivided attention performance under the influence of alcohol: Dose-response differences between males and females. Alcoholism: Clinical and Experimental Research 7(4):393–397. Available at: 10.1111/j.1530-0277.1983.tb05492.x. [DOI] [PubMed] [Google Scholar]
  37. Mundt MP, Zakletskaia LI, Fleming MF (2009) Extreme college drinking and alcohol-related injury risk. Alcoholism: Clinical and Experimental Research 33(9):1532–1538. Available at: 10.1111/j.1530-0277.2009.00981.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Newlin DB, Thomson JB (1990) Alcohol challenge with sons of alcoholics: a critical review and analysis. Psychological Bulletin 108(3):383–402. Available at: 10.1037/0033-2909.108.3.383 [DOI] [PubMed] [Google Scholar]
  39. NIAAA (2000) 10th Special Report to the U.S. Congress on Alcohol and Health. National Institutes of Health; (NIH Publication No. 00–1583), Washington DC. [Google Scholar]
  40. Nieschalk M, Ortmann C, Schmäl F, Stoll W, Fechner G (1999) Effects of alcohol on body-sway patterns in human subjects. International Journal of Legal Medicine 112(4):253–260. Available at: 10.1007/s004140050245. [DOI] [PubMed] [Google Scholar]
  41. Nolen-Hoeksema S (2004) Gender differences in risk factors and consequences for alcohol use and problems. Clinical Psychology Review 24(8):981–1010. Available at: 10.1016/j.cpr.2004.08.003. [DOI] [PubMed] [Google Scholar]
  42. O’Callaghan C, Hodges JR, Hornberger M (2013) Inhibitory dysfunction in frontotemporal dementia: a review. Alzheimer Disease & Associated Disorders 27(2):102–108. Available at: 10.1097/WAD.0b013e318265bbc9. [DOI] [PubMed] [Google Scholar]
  43. Ostafin B, Marlatt G, Troop-Gordon W (2010) Testing the incentive-sensitization theory with at-risk drinkers: wanting, liking, and alcohol consumption. Psychology of Addictive Behaviors 24:157–162. Available at: 10.1037/a0017897. [DOI] [PubMed] [Google Scholar]
  44. Pardo Y, Aguilar R, Molinuevo B, Torrubia R (2007) Alcohol use as a behavioural sign of disinhibition: evidence from J.A. Gray’s model of personality. Addictive Behaviors 32(10):2398–2403. Available at: 10.1016/j.addbeh.2007.02.010. [DOI] [PubMed] [Google Scholar]
  45. Roberts W, Milich R, Fillmore MT (2013) Reduced acute recovery from alcohol impairment in adults with ADHD. Psychopharmacology 228(1):65–74. Available at: 10.1007/s00213-013-3016-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Schuckit MA (1985) Ethanol-induced changes in body sway in men at high alcoholism risk. Archives of General Psychiatry 42(4):375–379. Available at: 10.1001/archpsyc.1985.01790270065007. [DOI] [PubMed] [Google Scholar]
  47. Schuckit MA (1994) Low level of response to alcohol as a predictor of future alcoholism. American Journal of Psychiatry 151(2):184–189. Available at: 10.1176/ajp.151.2.184. [DOI] [PubMed] [Google Scholar]
  48. Selzer ML, Vinokur A, van Rooijen L (1975) A self-administered Short Michigan Alcoholism Screening Test (SMAST). Journal of Studies on Alcohol 36(1):117–126. Available at: 10.15288/jsa.1975.36.117. [DOI] [PubMed] [Google Scholar]
  49. Stewart J, de Wit H, Eikelboom R (1984) The neural basis of drug craving: an incentive-sensitization theory of addiction. Psychological Review 91(3):251–268.6571424 [Google Scholar]
  50. Tannock R, Schachar R, Chajczyk D, Logan G (1989) Effects of methylphenidate on inhibitory control in hyperactive children. Journal of Abnormal Child Psychology 17:473–491. Available at: 10.1007/BF00916508. [DOI] [PubMed] [Google Scholar]
  51. Tibboel H, De Houwer J, Spruyt A, Brevers D, Roy E, Noël X (2015) Heavy social drinkers score higher on implicit wanting and liking for alcohol than alcohol-dependent patients and light social drinkers. Journal of Behavior Therapy and Experimental Psychiatry 48:185–191. Available at: 10.1016/j.jbtep.2015.04.003. [DOI] [PubMed] [Google Scholar]
  52. Vogel-Sprott M (1992) Alcohol tolerance and social drinking: learning the consequences. Psychiatric Services 44:596–597. [Google Scholar]
  53. Wang G-J, Volkow ND, Fowler JS, Franceschi D, Wong CT, Pappas NR, Netusil N, Zhu W, Felder C, Ma Y (2003) Alcohol intoxication induces greater reductions in brain metabolism in male than in female subjects. Alcoholism: Clinical and Experimental Research 27(6):909–917. Available at: 10.1111/j.1530-0277.2003.tb04415.x. [DOI] [PubMed] [Google Scholar]
  54. Weafer J, Miller M, Fillmore MT (2010) Response conflict as an environmental determinant of gender differences in sensitivity to alcohol impairment. Current Drug Abuse Reviews 3(3):147–155. [DOI] [PubMed] [Google Scholar]
  55. Weafer J, Fillmore MT (2016) Low-dose alcohol effects on measures of inhibitory control, delay discounting, and risk-taking. Current Addictive Reports 3:75–84. [Google Scholar]
  56. Weafer J, Fillmore MT (2008) Individual differences in acute alcohol impairment of inhibitory control predict ad libitum alcohol consumption. Psychopharmacology 201(3):315–324. Available at: 10.1007/s00213-008-1284-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Weafer J, Fillmore MT (2012) Acute tolerance to alcohol impairment of behavioral and cognitive mechanisms related to driving: drinking and driving on the descending limb. Psychopharmacology 220(4): 697–706. Available at: 10.1007/s00213-011-2519-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Weafer J, de Wit H (2014) Sex differences in impulsive action and impulsive choice. Addictive Behaviors 39(11):1573–1579. Available at: 10.1016/j.addbeh.2013.10.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. West S, Finch J, Curran P (1996) Structural equation models with nonnormal variables: Problems and remedies, in Structural Equation Modeling: Concepts, Issues, and Applications (Hoyle RH ed), pp 56–75. SAGE Publications, Inc., California, USA. [Google Scholar]
  60. Zoethout RWM, de Kam ML, Dahan A, Cohen AF, van Gerven JMA (2012) A comparison of the central nervous system effects of alcohol at pseudo-steady state in Caucasian and expatriate Japanese healthy male volunteers. Alcohol 46(7):657–664. Available at: 10.1016/j.alcohol.2012.06.004. [DOI] [PubMed] [Google Scholar]

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