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. Author manuscript; available in PMC: 2026 Sep 3.
Published before final editing as: Psychol Addict Behav. 2026 Aug 13:10.1037/adb0001178. doi: 10.1037/adb0001178

Effects of Alcohol on Emotion Recognition: An Alcohol-Administration Trial

Annis Byram a,*, Silvia Murgia a,*, Alexa Boland a, Catharine Fairbairn a
PMCID: PMC13537755  NIHMSID: NIHMS2194150  PMID: 42593990

Abstract

Objective

Alcohol consumption is widely recognized for its complex effects on social behavior, simultaneously fostering social connections in some individuals while heightening aggression in others. However, the underlying mechanisms for this effect, including emotion recognition, remain disputed among researchers. This study examined how alcohol influences the accuracy of emotion recognition, with particular attention to sex differences.

Method

Individuals who regularly consume alcohol (n = 390; 180 females; MAge = 23; 48.97% White) were randomly assigned to either an alcohol (targeting a BrAC of 0.08%) or control condition. They were assessed using the shortened version of the Geneva Emotion Recognition Task (GERT), which evaluates recognition of 14 emotions through dynamic videos.

Results

Alcohol consumption significantly reduced overall emotion recognition accuracy, b = 0.038, SE = 0.012, p = .002. Males exhibited significantly lower emotion identification accuracy than females, regardless of beverage condition, M = 0.511, SD = 0.123. Regarding individual emotions, alcohol significantly impaired the recognition of anger and irritation across both sexes, and specifically impaired interest, pride, and relief among male participants.

Conclusions

Our findings indicate that alcohol impairs the ability to interpret emotional expressions, with potential implications for impaired social interactions and heightened aggression.

Keywords: alcohol, emotion recognition, aggression

Alcohol is widely consumed in social contexts and prized for its social effects. Yet the effects of alcohol on interpersonal processes are highly variable. Alcohol can induce connection in some while heightening aggression in others (Goodwin & Sayette, 2022; Knox et al., 2019; Sudhinaraset et al., 2016). Alcohol’s popularity is attributed to its ability to reduce stress, bolster positive emotions (Cooper et al., 1995; Sayette, 2017), and enhance social interactions (Fairbairn et al., 2018). At the same time, alcohol has been linked to heightened aggression, impulsivity, and impaired emotional processing (Ito et al., 1996; Wells & Graham, 2002). One possible explanation for these divergent social effects is that alcohol alters how people perceive and interpret emotional cues during interpersonal interactions. For instance, acute alcohol use has been shown to significantly increase the likelihood of bar fights and verbal and physical aggression in both sexes (Swahn & Donovan, 2006), with intoxicated males exhibiting greater levels of aggression (Giancola et al., 2009). Such effects may be partly related to alcohol-related difficulties in interpreting social signals, including an increased tendency to misread ambiguous cues as antagonistic (Klein Tuente et al., 2019). In addition, general emotion recognition accuracy tends to decline as intoxication level increases, with this negative relationship being significantly more pronounced among male participants (Melkonian et al., 2021).

One widely-researched potential explanation for alcohol’s impact on both affiliative and aggressive social behaviors centers on alcohol-related shifts in social cognition, particularly in the perceptual domain. Specifically, alcohol has been theorized to impair higher-order cognitive skills required for the recognition of emotion. Alcohol Myopia Theory provides one framework for understanding these effects, positing that alcohol impairs cognitive function in a manner that narrows attention to the most salient cues in the environment (Steele & Josephs, 1990). This process may increase sociability and aggression by impairing the brain’s ability to read others’ reactions, causing individuals to spend less time interpreting social cues. Fairbairn and Sayette (2013) tested this theory by exploring how alcohol impacts emotional shifts in social contexts. Their results showed that intoxicated participants demonstrated lower levels of emotional inertia, showing enhanced ability to rebound and engage with pleasurable immediate stimuli following instances of low social pleasure. Consequently, the same narrowing of attention to the immediate environment may also reduce sensitivity to subtle emotions (i.e., low-intensity expressions that fall outside of the six basic emotions: happiness, anger, sadness, disgust, fear, and surprise) during social interactions (Ekman, 1992; Kohler et al., 2004; Honan et al., 2018 & Nagar et al., 2021). Given alcohol’s narrowing of attention (myopia), it is especially important to employ naturalistic, dynamic stimuli when assessing recognition of subtle emotions. Cognitive load and/or the intoxicated persons’ current mood may also change how these variables interact with one another (Reed & Steed, 2019; Schmid & Schmid Mast, 2010).

Studies investigating the relationship between acute alcohol use and emotion recognition have yielded mixed results. Honan et al. (2018) reported that individuals at the legal intoxication limit of 0.08% breath alcohol concentration (BrAC) were significantly less likely to identify fear and sadness, emotions generally conveyed with subtle facial expressions, compared to anger or happiness. Results from Eastwood et al. (2020) echoed these prior findings, suggesting that impaired recognition of these emotions may contribute to alcohol-induced aggression by limiting awareness of distress signals in others. In contrast, other studies have found low and moderate doses to cause participants to more frequently misidentify emotional facial expressions (Kamboj et al., 2013; Khouja et al., 2019). A meta-analysis by Sanov et al. (2023) examining the effect of alcohol concluded that the majority of studies reported no significant effect of alcohol on emotion recognition accuracy across a range of emotions, though some studies did report inconsistent effects, particularly for negative emotions. This may be due in part to small sample sizes across some studies in the analysis (e.g., Felisberti & Terry (2015) n = 18, and Kamboj et al. (2013) n = 48).

A potential key factor contributing to inconsistencies across studies is the methodological approach used to assess emotion recognition. Many studies rely on static images of facial expressions, which may not adequately reflect the complexity of emotional communication. A recent systematic review by Sanov et al. (2023) analyzed data from 19 studies on emotion recognition and alcohol use, the majority of which reported no consistent evidence that alcohol selectively impaired recognition of any of the six basic emotions. The authors suggested that reliance on still images likely reduced ecological validity, making it difficult for participants to perceive emotion as they would in real-world social contexts (Eastwood et al., 2020; Felisberti & Terry, 2015; Honan et al., 2018; Kamboj et al., 2013; Khouja et al., 2019; Walter et al., 2011). In contrast, dynamic stimuli, such as video clips, provide a more natural representation of emotion (Schlegel et al., 2019; Grainger et al., 2015), leading to more accurate identification of nuanced expressions compared to image-based tasks (Grainger et al., 2015). Notably, Sanov et al. (2023) reported that studies using video-based tasks more often found decreased recognition of sadness and fear. Schlegel et al. (2019) similarly showed that multimodal actor-based clips, such as those used in the GERT, can validly assess emotion-recognition ability by capturing facial, vocal, and bodily cues that more closely resemble real social interactions. However, many of these video-based studies still relied on pictures of faces, morphed together to create video clips, or a restricted range of emotion categories, and none used real actors or a broad emotional range. Emotion recognition is inherently complex, involving not just basic expressions but also more subtle emotions often experienced in real-life interactions.

To address the limitations of the current literature (Ambady et al., 2000; Elfenbein & Ambady, 2002), the present study uses the Geneva Emotion Recognition Test (GERT, Schlegel et al., 2019), a validated, video-based emotion recognition measure featuring real actors expressing 14 distinct emotions, offering a more ecologically valid and comprehensive approach. To date, only a single alcohol-administration study (Kumar et al., 2025) assessed emotion recognition using the GERT to measure dynamic stimuli. However, this study only examined six of the GERT’s fourteen emotions in their analysis. As such, additional research is needed to understand causal effects of alcohol on emotion perception using dynamic stimuli of the type participants might encounter in everyday life.

Another prominent factor that may affect emotion recognition accuracy is sex. Survey results across multiple countries found assaults perpetrated by men to worsen after consuming alcohol, and women to be at an increased risk of abuse when living with partners who regularly consumed large amounts of alcohol (Graham et al., 2010; Callinan et al., 2018). Research indicates that males tend to perform worse than females on emotion recognition tasks, particularly under intoxication (Sanov et al., 2023; Melkonian et al., 2021; Thompson & Voyer, 2014), with male misinterpretation potentially contributing to inappropriate or aggressive behavior in drinking contexts (Beck & Heinz, 2013; Kret & De Gelder, 2012). Sex differences in emotion recognition may reflect, in part, gendered socialization processes, whereby women are often encouraged to attend more closely to emotional expression and interpersonal cues (Hall et al., 2025). In addition to social conditioning, behavioral processing research has found female brains to exhibit an enhanced ability to comprehend body language (Goldberg et al., 2015; Proverbio et al., 2010; Proverbio, 2022). Research using dynamic avatars suggests that neural responses during emotion perception may differ by sex, underscoring the importance of ecologically valid methods for examining differences in emotion recognition between female and male participants. Examining sex differences using ecologically valid emotion-recognition measures may help clarify which emotions are most vulnerable to misidentification under alcohol intoxication.

The Current Research

The present study aims to fill several gaps in the existing literature by examining how acute alcohol consumption influences emotion recognition, while also accounting for sex. To our knowledge, this is one of the first studies to use the GERT in an alcohol research context. By leveraging a broader emotional range and more naturalistic stimuli, this study offers a deeper understanding of how alcohol affects social perception and interaction. We hypothesize that (1) participants in the alcohol condition will show reduced emotion recognition accuracy compared to controls, and (2) males will perform less accurately than females overall and especially under intoxication. In addition, we also included exploratory analyses examining whether cognitive (e.g., executive functioning) and affective (e.g., mood) factors account for the relationships between alcohol, sex, and emotion recognition.

Methods

Participants

Study hypotheses were preregistered (see osf.io/5rjf3). Individuals who regularly consume alcohol were recruited via flyers, posted notices, and online announcements posted in the local community. The sample consisted of 3901 individuals (180 females), averaging 23 years old (SD = 2.136). Sex was assessed using a binary item with male and female response options and was used to characterize the sample and examine differences in emotion-recognition performance. We conducted a sensitivity power analysis for the achieved sample size in the 2 × 2 between-subjects design crossing beverage condition and sex. Assuming α = .05 and power = .90, the available sample provided adequate power to detect small effects for the main effects of beverage condition and sex, approximately equivalent to Cohen’s d = 0.33 for each two-group comparison. Because interaction effects typically require greater statistical power than main effects, the beverage × sex interaction was interpreted cautiously. Data from two participants were excluded due to technical issues during data collection, resulting in a final analyzed sample of 388. Most participants identified as not Hispanic or Latino (74.10%). Additionally, 48.97% identified as White, 45.38% Asian, 2.31% Black or African American, 1.54% Multiracial, 1.03% Native Hawaiian or Other Pacific Islander, and 0.77% American Indian/Alaska Native. Eligible participants were aged 21–30 and reported drinking at least two drinks biweekly or four drinks once monthly over the past year. Exclusion criteria included: BMI <18 or >40, pregnancy, history of significant brain injury, severe psychiatric diagnoses (e.g., schizophrenia, bipolar disorder, chronic major depression, or psychiatric hospitalization), drugs or medications contraindicated with alcohol, and DSM-V severe alcohol use disorder (AUD) diagnosis (Fairbairn et al., 2019). Participants received up to $100 for completing study procedures.

Procedure

The study procedures were approved by the University of Illinois Urbana-Champaign’s Institutional Review Board (IRB#16263). The current study’s data were drawn from a broader study examining alcohol’s effects in social contexts (NCT03449095; Gurrieri et al., 2021). Using a referral-based recruitment process, eligible subjects were matched with a same-sex friend and invited to the lab. Participants were asked to abstain from alcohol for twelve hours and food for three hours before the experiment. A BrAC of 0.00% was required before study procedures began. Participants then completed baseline measures and ingested a weight-adjusted meal before beverage administration.

Subjects were randomly assigned to either the alcohol (n = 192) or control (n = 198) condition. Biological sex, height, and weight were assessed and used to calculate individualized alcohol dosages to achieve a target peak BrAC of .08% following beverage consumption. Dosages were determined using personalized total body water estimates based on the Watson et al. (1981) formula, a method commonly employed in prior alcohol-administration research (Ariss et al., 2023; Fairbairn et al., 2018). Participants in the alcohol condition received beverages consisting of one part 100-proof vodka and three parts Sprite, whereas those in the control condition received only Sprite. All participants were made aware of the beverage type they received. Beverages were administered in a dyadic context, divided into three equal portions delivered every 12 minutes over a 36-minute period. To ensure consistency across alcohol and control groups, participants were given the same amount of time to consume their drinks and were administered tasks at consistent times after beverage administration. No placebo condition was included in this study as previous research suggests that such conditions may elicit compensatory social behaviors (Fairbairn et al., 2015; Testa et al., 2006 ).

After beverage administration, participants engaged in a number of tasks, including EEG and extended vigilance tasks (Yang et al., 2025; Kang et al., 2025), which are not relevant to the present study and are therefore not examined in this analysis. Upon completion of these preliminary procedures, the primary task of interest, the shortened version of the Geneva Emotion Recognition Test (GERT-S; Schlegel & Scherer, 2016), was administered. This occurred after an absorption period of 1 hour and 44 minutes, designed to accommodate the broader study protocol while allowing sufficient time for alcohol absorption and peak BrAC stabilization (Garrison et al., 2024). All participants completed the GERT-S in separate rooms, with those in the alcohol condition breathalyzed beforehand. At the conclusion of study procedures, all participants were compensated for their time. Individuals in the alcohol condition remained in the laboratory and were breathalyzed every 30 minutes until their BrAC declined to a safe level (.03%), in accordance with National Institute on Alcohol Abuse and Alcoholism (NIAAA, 2025) guidelines, after which they were permitted to leave.

Measures

Emotion Recognition

Researchers implemented the shortened version of the GERT (GERT-S) (Schlegel & Scherer, 2016) to examine the role of alcohol on emotion recognition accuracy across 14 different emotions (Udayar et al., 2020; Voruz et al., 2023). The GERT-S consists of 42 short-form video clips featuring 10 White actors (five women and five men between the ages of 25 and 57). Each clip depicts one of 14 emotions using synchronized facial, vocal, and bodily cues over the course of approximately 10 minutes. Participants viewed all 42 short-form clips, which featured both women and men actors, and all participants viewed the same set of videos regardless of participant sex. After each clip, participants were asked to choose which emotion was depicted from the following list: joy, amusement, pride, pleasure, relief, interest, anger, fear, despair, irritation, anxiety, sadness, disgust, and surprise. Scores were coded as correct (1) and incorrect (0); participants could receive up to 3 points for each emotion, corresponding to the three clips presented per emotion, with total accuracy scores ranging from 0 to 42. Each emotion was portrayed by three different actors. For overall emotion-recognition analyses, total scores were converted to proportion correct to facilitate interpretation of accuracy across the full 42-item task. For emotion-specific analyses, correct responses were summed separately within each emotion category. Thus, for each participant, we created one composite accuracy score for each of the 14 emotions, ranging from 0 to 3 and reflecting the number of correctly identified clips for that emotion. Because each emotion was represented by the same number of clips, this summed score was mathematically equivalent to a proportion-correct score for that emotion, but it retained the original item-count scale and allowed model estimates to be interpreted as differences in the number of clips correctly identified within each emotion category. Results from Olderbak et al. (2021) found satisfactory psychometrics with substantial internal consistency reliability of ω = .89, and Cronbach’s alpha ranging from .80 to .83.

Mood

The 8-Item Mood Measure (8MM) (Venerable & Fairbairn, 2020; Fairbairn & Sayette, 2013) was included in exploratory analyses to gain a better understanding of the potential covariates through which alcohol impacts emotion recognition. As part of the broader experimental protocol, the 8MM was administered at multiple time points. For the present analyses, we used the 8MM assessment administered closest to the GERT-S, immediately before GERT-S administration. Participants rated how they were feeling by indicating the extent to which they experienced each emotion using a 6-point Likert scale ranging from 0 (not at all) to 5 (extremely), covering 4 negative emotions (annoyed, sad, irritated, bored) and 4 positive emotions (cheerful, upbeat, happy, content).

Executive Function

The Stroop Color and Word Test (Stroop, 1935) was administered immediately before the GERT-S as an exploratory index of executive functioning. The task requires participants to name the ink color of printed words, while ignoring the word itself, thereby assessing selective attention and interference suppression. In the present study, Stroop performance was used in exploratory analyses as a covariate to examine whether alcohol-related differences in emotion recognition accuracy were explained by broader differences in cognitive control or task performance. Performance time on incongruent trials was used as the primary Stroop covariate, as these trials place the greatest demands on interference control. Incongruent trials elicited slower (M = 42.86 s incongruent and M = 20.36 s congruent), and less accurate responses, known as the “Stroop Effect.”

Data Analysis

Linear regression models were used to test the relationship between alcohol consumption and overall emotion recognition accuracy, using participants’ total GERT-S scores. Additional regression models assessed the independent and interactive effects of sex on GERT-S performance. For exploratory emotion-specific analyses, responses to the three clips corresponding to each emotion were summed within participant, yielding one score per emotion per participant (range = 0–3). These 14 emotion-level scores were then analyzed using a linear mixed-effects model fit with the lmer function from the lme4 package with Emotion type (e.g., joy, sadness, etc.), Beverage (Control vs. Alcohol), and sex as fixed effects and a random intercept for participant (ID) to account for the repeated emotion scores contributed by each participant. Fixed effects were evaluated using Type III F-tests with Satterthwaite’s approximation for degrees of freedom, as implemented in the lmerTest package. Estimated marginal means (EMMs) were computed using the emmeans package. Pairwise comparisons between the Alcohol and Control conditions were conducted for each combination of sex and emotion, with p-values adjusted using the Tukey method.

To explore whether mood and executive function contributed to the relationship between alcohol consumption and emotion recognition, additional linear models were estimated with positive and negative mood and Stroop task performance as covariates. These models were applied both to overall GERT-S scores and to individual emotion categories (e.g., Anger, Relief, etc.).

Transparency and Openness

All data and analytic code have been made publicly available at the Open Science Framework (OSF) and can be accessed at https://osf.io/jeb2q/files/osfstorage. We followed JARS (Kazak, 2018) and sample size, manipulations, measures, and data exclusions were reported. All analyses were conducted using R.

Results

Beverage Manipulation Check and GERT-S Descriptives

The final included sample of individuals randomly assigned to the alcohol condition (n = 191) had an average BrAC of .065%, SD = 0.012, immediately before GERT-S administration. Additionally, all control participants registered a 0.00% BrAC following the drinking period. The overall mean GERT-S score for all participants was M = 0.537, SD = 0.123.

Effect of Beverage and Sex on Emotion Recognition

A main effect of beverage condition emerged, b = 0.038, SE = 0.012, p = .002. Participants in the alcohol condition correctly identified emotions on an average of 52% of items (M = 0.519, SD = 0.127), whereas participants in the control condition correctly identified emotions on an average of 56% of items (M = 0.555, SD = 0.117, Figure 1). This difference corresponded to a small-to-moderate effect, Cohen’s d = 0.30, 95% CI [0.10, 0.50]. A main effect of sex was also observed, b = −0.058, SE = 0.012, p < .001, with females, M = 0.568, SD = 0.117, scoring higher than males, M = 0.511, SD = 0.123, regardless of beverage condition (see Figure 2). This sex difference was somewhat larger, Cohen’s d = 0.48, 95% CI [0.27, 0.68]. The interaction between sex and beverage was not significant, b = 0.028, SE = 0.024, p = .256.

Figure 1.

Figure 1

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Single Emotion Recognition Rates Across Beverage Conditions

Figure 2. GERT-S Score Distribution by Beverage Condition and Sex.

Figure 2

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Note. Boxplot depicts average GERT scores by beverage and sex. The horizontal line in each box represents the median, with whiskers extended to 1.5 x IQR. Outliers are plotted as individual diamonds. Females showed higher median GERT accuracy than males across beverage conditions.

As an exploratory measure, and in recognition that between-subject moderation findings are not always detectable within tests of statistical significance due to high power demands, we further fit a linear mixed-effects model including a three-way interaction between emotion, beverage, and sex. A significant main effect of Emotion type on GERT scores was observed, F (13, 5031) = 77.349, p < .001. Estimated marginal means and pairwise comparisons were conducted using Tukey-adjusted p-values to control for multiple comparisons. Significant beverage effects were found in both male and female participants for specific emotions (see Figure 3). Among female participants, GERT scores were significantly higher in the Control condition compared to the Alcohol condition for Anger, b = −0.348, SE = 0.134, p = .009, Irritation, b = −0.315, SE = 0.134, p = .019, and Surprise, b = −0.371, SE = 0.134, p = .006. Among male participants, GERT scores were significantly higher in the Control condition for Anger, b = −0.368, SE = 0.123, p = .003, Interest, b = −0.247, SE = 0.123, p = .045, Irritation, b = −0.321, SE = 0.123, p = .009, Pride, b = −0.299, SE = 0.123, p = .015, and Relief, b = −0.257, SE = 0.123, p = .037. No significant beverage effects were observed for other emotion categories after Tukey correction.

Figure 3.

Figure 3

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Single Emotion Recognition Rates Across Sex and Beverage Conditions

Supplementary Analysis: Controlling for Mood, Executive Function and BrAC

Further mixed-effects models were conducted to examine whether the observed effect of alcohol on emotion recognition could be accounted for by differences in mood or executive functioning. When positive and negative mood were included as covariates, neither mood variable significantly predicted GERT performance, positive mood: b = 0.0002, SE = 0.002, p = .895; negative mood: b = −0.0011, SE = 0.002, p = .524. Importantly, the effect of beverage condition remained significant, b = 0.0383, SE = 0.013, p = .003. Similarly, in a model including Stroop task performance as an index of executive function, both beverage condition, b = 0.0403, SE = 0.012, p = .001, and Stroop performance in the incongruent condition, b = −0.0141, SE = 0.004, p = .001, remained significant predictors of GERT scores. For additional exploratory analysis results see Table 1.

Table 1.

Exploratory Analyses of the Inclusion of Covariates (Stroop test and mood) on Single Emotions

Emotion Model Type Predictor Estimate (b) SE t p Sig.
Anger Mood Model Beverage 0.352 0.084 4.19 <.001 ***
PosMM3 0.001 0.01 0.13 0.897
NegMM3 0.007 0.012 0.58 0.562
Stroop Model Beverage 0.365 0.083 4.39 <.001 ***
Stroop_C −0.184 0.107 −1.72 0.086 .
Stroop_I −0.051 0.028 −1.81 0.072 .
Irritation Mood Model Beverage 0.325 0.095 3.41 <.001 ***
PosMM3 0.001 0.011 −0.06 0.954
NegMM3 −0.012 0.013 −0.92 0.358
Stroop Model Beverage 0.325 0.094 3.46 <.001 ***
Stroop_C 0.105 0.121 0.87 0.386
Stroop_I −0.103 0.032 −3.23 0.001 **
Surprise Mood Model Beverage 0.272 0.082 3.31 0.001 **
PosMM3 −0.002 0.01 −0.18 0.86
NegMM3 0.001 0.011 0.05 0.962
Stroop Model Beverage 0.266 0.082 3.25 0.001 **
Stroop_C −0.063 0.105 −0.6 0.551
Stroop_I 0.002 0.028 0.06 0.951
Interest Mood Model Beverage 0.186 0.091 2.03 0.043 *
PosMM3 0.007 0.011 0.67 0.502
NegMM3 −0.008 0.013 −0.65 0.517
Stroop Model Beverage 0.167 0.092 1.82 0.069 .
Stroop_C 0.129 0.118 1.1 0.274
Stroop_I −0.021 0.031 −0.68 0.496
Pride Mood Model Beverage 0.195 0.085 2.29 0.022 *
PosMM3 −0.01 0.01 −0.97 0.331
NegMM3 0.011 0.012 0.95 0.345
Stroop Model Beverage 0.253 0.084 3 0.003 **
Stroop_C 0.21 0.108 1.94 0.053 .
Stroop_I 0.008 0.029 0.29 0.773
Relief Mood Model Beverage 0.103 0.088 1.18 0.24
PosMM3 0.001 0.01 0.1 0.92
NegMM3 −0.023 0.012 −1.9 0.058 .
Stroop Model Beverage 0.091 0.088 1.03 0.304
Stroop_C 0.109 0.113 0.96 0.336
Stroop_I −0.006 0.03 −0.19 0.853
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Note. The “Mood Model” is the model including positive and negative mood as covariates (PosMM3, NegMM3). The “Stroop Model” is model including Stroop Congruent (Stroop_C) and Stroop Incongruent (Stroop_I) task performance as covariates.

*

p < .05

**

p < .01

***

p < .001

.

= marginal (p < .10).

Additional analyses within the alcohol group examined whether BrAC at the time of testing predicted GERT performance. When BrAC was entered as the sole predictor, higher BrAC was associated with lower GERT performance, b = −1.81, SE = 0.71, p = .012. However, this association was no longer significant after accounting for other relevant predictors. BrAC was not a significant predictor in the model including sex, b = −1.02, SE = 0.78, p = .192; the model additionally controlling for positive and negative mood, b = −0.90, SE = 0.79, p = .256; or the model including Stroop congruent and incongruent performance, b = −1.36, SE = 0.78, p = .081. Sex remained a significant predictor in the basic and mood-adjusted models, and Stroop incongruent performance remained a significant predictor in the executive-function model.

Discussion

The present study examined the effects of beverage consumption and sex on emotion recognition using actor-portrayed videos depicting 14 emotional states. Our findings suggest that both alcohol and sex significantly influence emotion recognition performance. Specifically, participants in the alcohol condition scored lower on the GERT-S, supporting our hypothesis that intoxicated participants experience greater difficulty in identifying emotions. Consistent with previous work, our analysis revealed that male participants demonstrated lower overall GERT-S scores regardless of beverage condition. Although the percentage difference in accuracy across conditions was modest, the alcohol effect was statistically significant and corresponded to a small-to-moderate effect size. Further analysis of individual emotions suggested that alcohol was associated with lower recognition accuracy for anger, interest, irritation, pride, and relief among male participants and for anger, irritation, and surprise among female participants. Future research should examine whether these alcohol-related and sex-linked patterns replicate across other emotion-recognition tasks and drinking contexts, particularly given the exploratory nature of the emotion-specific analyses.

Although the systematic review by Sanov et al. (2023), suggested that acute alcohol consumption does not significantly affect one’s ability to recognize emotions, our results demonstrate that participants who consumed alcohol had lower GERT-S scores compared to those in the control condition, indicating a potential impairment in emotional recognition associated with alcohol intake. Additional analyses indicated that intoxicated participants’ BrAC readings were not a significant predictor of GERT performance, suggesting that the observed impairment in emotion recognition was not driven by variability in intoxication levels at the time of testing.

These findings are broadly consistent with Alcohol Myopia Theory (Steele & Josephs, 1990), which suggests that alcohol narrows attention to the most salient cues in the environment and may reduce processing of more subtle emotional information. However, the present study did not directly test alcohol myopia as a mechanism. Stroop incongruent-trial performance was included as a general index of executive functioning and interference control, not as a direct measure of alcohol-induced attentional narrowing. The persistence of the beverage effect after controlling for Stroop performance suggests that alcohol-related differences in emotion recognition were not fully explained by general executive-function differences as captured by this task. Recognition of subtle affective states such as interest, irritation, pride, and relief may require careful integration of facial, vocal, and bodily cues. Honan et al. (2018) similarly noted that less definitive emotional expressions require greater attention to detail. The use of dynamic video stimuli in the present study may have been especially useful for capturing these nuanced recognition processes, as video enactments provide a more naturalistic representation of emotional communication than the static images used in many studies summarized by Sanov et al. (2023). In addition, the observed alcohol-related impairment for anger and irritation aligns with recent findings by Kumar et al. (2025), who also reported impaired identification of anger under alcohol.

Due in part to the broader range of emotions assessed in the GERT-S, the present study identified alcohol-related impairments in several emotions that have received less attention in prior alcohol-administration research. Across the emotion-specific analyses, alcohol-related differences emerged most consistently for anger and irritation, with additional exploratory differences observed for surprise, interest, pride, and relief in sex-stratified follow-up analyses. These findings suggest that the GERT-S may be useful for detecting alcohol-related impairment across a broader set of emotional cues, although these emotion-specific patterns should be interpreted cautiously and replicated in future work. The large sample size in this study may explain the observed lower scores, especially considering that earlier research, such as Felisberti & Terry (2015), n = 18 and Kamboj et al. (2013), n = 48, flagged the use of small samples as a potential limitation. Beyond expanding the emotion set, these results also speak to alcohol’s broader social-cognitive effects. By demonstrating that acute alcohol intoxication was associated with lower recognition accuracy for anger and irritation, our findings shed light on one mechanism by which alcohol may paradoxically promote both communal bonding and aggressive behavior. Individuals tend to be hypervigilant to signs of social rejection or disapproval in social interactions, a reaction that has evolutionary advantages but nonetheless, within the context of regular day-to-day conversations, can come at a cost for social bonding (Williams, 2007). However, when intoxicated individuals have difficulty detecting cues of anger or irritation, they may misread social intent, overlooking warning signals that normally constrain approach behaviors, and thus behave in ways that can escalate conflict. Conversely, such misperception may also lead intoxicated individuals to underestimate others’ disapproval when facilitating social interactions in group settings. In this way, alcohol-related impairment in emotion recognition may contribute to alcohol’s double-edged role in social affiliation versus confrontation, although future work should directly test these downstream social outcomes.

Female participants showed higher overall GERT-S accuracy than male participants across beverage conditions, consistent with prior evidence that women often show an advantage in emotion-recognition tasks (Hoffmann et al., 2010; Lin et al., 2025; Thompson & Voyer, 2014). This advantage may reflect both biological factors and gendered socialization processes that encourage greater attention to emotional and interpersonal cues. This finding also parallels Melkonian et al. (2021), who found that intoxicated female participants performed better than intoxicated male participants on a video-based emotion-recognition task. Emotion-specific exploratory analyses suggested that alcohol-related recognition difficulties were observed for anger, irritation, and surprise among female participants and for anger, interest, irritation, pride, and relief among male participants. However, because the beverage × sex interaction on total GERT-S accuracy was not significant, these findings should not be interpreted as evidence that alcohol produced stronger overall impairment in men than in women. Rather, they suggest that the specific emotional cues affected by alcohol may vary by sex, a possibility that should be tested directly in future work. Because anger and irritation may serve as warning signals during interpersonal interactions, alcohol-related difficulty recognizing these emotions across both male and female participants may be especially relevant for understanding conflict escalation in drinking contexts (Attwood et al., 2009; Giancola et al., 2009; Giancola et al., 2011).

An additional point to address is that controlling for individual differences in mood and executive function (Stroop performance) had no impact on our results, suggesting that results of our supplemental analyses are more likely mediated by more specific perceptual processes versus simply a broad error-proneness or alcohol-related cognitive inhibition.

Findings from this study carry implications for understanding the impact of alcohol on emotional recognition and have potential real-world consequences, particularly in social and interpersonal settings where effective emotional communication is crucial. Situations of enhanced aggression due to inebriated misinterpretations of emotional reactions could occur in both sexes (Giancola et al., 2009). Lower levels of emotion recognition cause individuals to be less empathetic within social interactions, leading to a diminished care for other people (Kyranides et al., 2022). Understanding the role alcohol plays in these circumstances will help diffuse the potential negative physical, emotional, and mental effects that occur during moments of aggression and violence. Furthermore, the observed sex differences in GERT-S scores highlight the need for sex-sensitive approaches in research related to emotional recognition.

Despite its contributions, the current study has some limitations. Firstly, while our study primarily involved young adults, future research should use more diverse samples, both in age and in racial and cultural background, to enhance generalizability. Second, the study focused solely on the GERT-S for measuring emotion recognition, and future work should incorporate measures with racially diverse actors to constitute a natural environment. Elfenbein & Ambady (2002) discuss the importance of diversified actors in emotion recognition tasks, with failure to meet this factor leading to potentially lower scores from non-represented participants. Because the GERT-S videos featured only White actors, demographic mismatch between actors and participants may have influenced emotion-recognition accuracy, particularly given evidence that emotional expressions can be interpreted differently across racial and cultural contexts. Additionally, sex was assessed using a binary item with male and female response options; therefore, the present study could not examine gender identity or gender diversity in emotion-recognition performance. Future work should use more comprehensive measures of sex assigned at birth and gender identity to better distinguish these constructs.

Furthermore, emotion recognition was tested after peak BrAC levels, at the beginning of the descending limb, whereas effects could differ on the ascending phase of intoxication. BrAC at the time of testing was associated with lower GERT-S performance in an unadjusted model within the alcohol group, but this association was no longer significant after accounting for sex, mood, or executive-function covariates. Future research should use designs that either match participants on BrAC at task administration or include a wider range of intoxication levels and alcohol dosages to clarify whether emotion-recognition deficits vary as a function of acute alcohol dose. Lastly, the non-significant interaction effect between beverage consumption and sex suggests the need for further exploration of potential moderating variables, such as personality traits and social anxiety.

Conclusion

The present study provides evidence that acute alcohol consumption is associated with lower emotion-recognition accuracy on a dynamic, video-based task. Alcohol-related impairment was especially evident for anger and irritation, two emotions that may serve as important warning signals during social interactions. Exploratory analyses also suggested that alcohol-related recognition difficulties may vary across specific emotions and participant sex, although these patterns should be interpreted cautiously given the non-significant beverage × sex interaction. Overall, these findings suggest that alcohol may disrupt social perception in ways that could contribute to misunderstanding, reduced interpersonal sensitivity, and conflict in drinking contexts. Future research should examine whether these emotion-recognition impairments predict real-world social outcomes, including aggression, relationship conflict, and risky drinking-related interactions.

Public health significance statements.

This study shows that alcohol can make it harder for young adults to recognize other people’s emotions, including anger and irritation. Missing these social warning signals may increase misunderstandings, risky interactions, and conflict in drinking settings. These findings highlight emotion recognition as a potential target for efforts to reduce alcohol-related interpersonal harm.

Acknowledgments

This research was supported by National Institutes of Health Grant R01AA025969 and R01AA028488–05 to Catharine E. Fairbairn. Special thanks to Brynne Velia and also Dr. Judith Hall, as well as all of the students and staff of the Alcohol Research Laboratory at the University of Illinois at Urbana-Champaign for their aid in the conduct of this research.

Footnotes

1

The present analytic sample represents a subset of participants from a larger alcohol-administration study. Specifically, analyses were limited to participants recruited after the COVID-19 pandemic, when the GERT-S was included in the study protocol and emotion-recognition data were available.

References

  1. Ambady N, Bernieri FJ, & Richeson JA (2000). Toward a histology of social behavior: Judgmental accuracy from thin slices of the behavioral stream. Advances in Experimental Social Psychology, 32, 201–271. Elsevier. 10.1016/S0065-2601(00)80006-4 [DOI] [Google Scholar]
  2. Attwood A, Ohlson C, Benton C, Penton-Voak I, & Munafò M (2009). Effects of acute alcohol consumption on processing of perceptual cues of emotional expression. Journal of Psychopharmacology, 23(1), 23–30. 10.1177/0269881108089604 [DOI] [PubMed] [Google Scholar]
  3. Ariss T, Fairbairn CE, Sayette MA, Velia BA, Berenbaum H, & Brown-Schmidt S (2023). Where to look? Alcohol, affect, and gaze behavior during a virtual social interaction. Clinical Psychological Science, 11(2), 239–252. 10.1177/21677026221096449 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Beck A, & Heinz A (2013). Alcohol-Related Aggression. Deutsches Ärzteblatt International. 10.3238/arztebl.2013.0711 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Byram A, Fairbairn C, & Boland A (2024, November 13). The Effects of Acute Alcohol Consumption on Emotion Recognition. 10.17605/OSF.IO/2ACM7 [DOI] [Google Scholar]
  6. Byram A, Fairbairn C, & Boland A (2025). The Effects of Acute Alcohol Consumption on Emotion Recognition. https://osf.io/jeb2q/files/osfstorage [Google Scholar]
  7. Cooper ML, Frone MR, Russell M, & Mudar P (1995). Drinking to regulate positive and negative emotions: a motivational model of alcohol use. Journal of Personality and Social Psychology, 69(5), 990. 10.1037/0022-3514.69.5.990 [DOI] [PubMed] [Google Scholar]
  8. Eastwood AP, Penton-Voak IS, Munafò MR, & Attwood AS (2020). Effects of acute alcohol consumption on emotion recognition in high and low trait aggressive drinkers. Journal of Psychopharmacology, 34(11), 1226–1236. 10.1177/0269881120922951 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Ekman P (1992). Are There Basic Emotions? Psychological Review, 99(3), 550–553. 10.1037/0033-295X.99.3.550 [DOI] [PubMed] [Google Scholar]
  10. Elfenbein HA, & Ambady N (2002). On the universality and cultural specificity of emotion recognition: A meta-analysis. Psychological Bulletin, 128(2), 203–235. 10.1037/0033-2909.128.2.203 [DOI] [PubMed] [Google Scholar]
  11. Fairbairn CE, Bresin K, Kang D, Rosen IG, Ariss T, Luczak SE, Barnett NP, & Eckland NS (2018). A multimodal investigation of contextual effects on alcohol’s emotional rewards. Journal of Abnormal Psychology, 127(4), 359–373. 10.1037/abn0000346 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fairbairn CE, Rosen IG, Luczak SE, & Venerable WJ (2019). Estimating the quantity and time course of alcohol consumption from transdermal alcohol sensor data: A combined laboratory-ambulatory study. Alcohol, 81, 111–116. 10.1016/j.alcohol.2018.08.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fairbairn CE, & Sayette MA (2013). The effect of alcohol on emotional inertia: A test of alcohol myopia. Journal of Abnormal Psychology, 122(3), 770–781. 10.1037/a0032980 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Fairbairn CE, Sayette MA, Aalen OO, & Frigessi A (2015). Alcohol and Emotional Contagion: An Examination of the Spreading of Smiles in Male and Female Drinking Groups. Clinical Psychological Science, 3(5), 686–701. 10.1177/2167702614548892 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Felisberti F, & Terry P (2015). The effects of alcohol on the recognition of facial expressions and microexpressions of emotion: Enhanced recognition of disgust and contempt. Human Psychopharmacology: Clinical and Experimental, 30(5), 384–392. 10.1002/hup.2488 [DOI] [PubMed] [Google Scholar]
  16. Garrison A, Yoon SO, Brown-Schmidt S, Ariss T, & Fairbairn CE (2024). Alcohol and common ground: The effects of intoxication on linguistic markers of shared understanding during social exchange. Psychology of Addictive Behaviors, 38(1), 79–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Giancola PR, Levinson CA, Corman MD, Godlaski AJ, Morris DH, Phillips JP, & Holt JCD (2009). Men and women, alcohol and aggression. Experimental and Clinical Psychopharmacology, 17(3), 154–164. 10.1037/a0016385 [DOI] [PubMed] [Google Scholar]
  18. Giancola PR, Duke AA, & Ritz KZ (2011). Alcohol, violence, and the alcohol myopia model: Preliminary findings and implications for prevention. Addictive Behaviors, 36(10), 1019–1022. 10.1016/j.addbeh.2011.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Goldberg H, Christensen A, Flash T, Giese M, & Malach R (2015). Brain activity correlates with emotional perception induced by dynamic avatars. NeuroImage, 122, 306–317. 10.1016/j.neuroimage.2015.07.056 [DOI] [PubMed] [Google Scholar]
  20. Goodwin ME, & Sayette MA (2022). A social contextual review of the effects of alcohol on emotion. Pharmacology Biochemistry and Behavior, 221, 173486. 10.1016/j.pbb.2022.173486 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Grainger SA, Henry JD, Phillips LH, Vanman EJ, & Allen R (2015). Age Deficits in Facial Affect Recognition: The Influence of Dynamic Cues. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, gbv100. 10.1093/geronb/gbv100 [DOI] [PubMed] [Google Scholar]
  22. Gurrieri L, Fairbairn CE, Sayette MA, & Bosch N (2021). Alcohol narrows physical distance between strangers. Proceedings of the National Academy of Sciences, 118(20), e2101937118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hall JA, Gunnery SD, & Schlegel K (2025). Gender and accuracy in decoding affect cues: A meta-analysis. Journal of Intelligence, 13(3), 38. 10.3390/jintelligence13030038 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hoffmann H, Kessler H, Eppel T, Rukavina S, & Traue HC (2010). Expression intensity, gender and facial emotion recognition: Women recognize only subtle facial emotions better than men. Acta Psychologica, 135(3), 278–283. 10.1016/j.actpsy.2010.07.012 [DOI] [PubMed] [Google Scholar]
  25. Honan CA, Skromanis S, Johnson EG, & Palmer MA (2018). Alcohol intoxication impairs recognition of fear and sadness in others and metacognitive awareness of emotion recognition ability. Emotion, 18(6), 842–854. 10.1037/emo0000404 [DOI] [PubMed] [Google Scholar]
  26. Ito TA, Miller N, & Pollock VE (1996). Alcohol and Aggression: A Meta-Analysis on the Moderating Effects of Inhibitory Cues, Triggering Events, and Self-Focused Attention. Psychological Bulletin, 120(1), 60–82. 10.1037/0033-2909.120.1.60 [DOI] [PubMed] [Google Scholar]
  27. Kamboj SK, Joye A, Bisby JA, Das RK, Platt B, & Curran HV (2013). Processing of facial affect in social drinkers: A dose–response study of alcohol using dynamic emotion expressions. Psychopharmacology, 227(1), 31–39. 10.1007/s00213-012-2940-5 [DOI] [PubMed] [Google Scholar]
  28. Kang D, Fairbairn CE, Han J, & Federmeier KD (2025). The impact of alcohol on brain response in social context: A hyperscanning alcohol-administration trial. NeuroImage, 121450. 10.1016/j.neuroimage.2025.121450 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Kazak AE (2018). Editorial: Journal article reporting standards. American Psychologist, 73(1), 1–2. 10.1037/amp0000263 [DOI] [PubMed] [Google Scholar]
  30. Khouja JN, Attwood AS, Penton-Voak IS, & Munafò MR (2019). Effects of acute alcohol consumption on emotion recognition in social alcohol drinkers. Journal of Psychopharmacology, 33(3), 326–334. 10.1177/0269881118822169 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Klein Tuente S, Bogaerts S, & Veling W (2019). Hostile attribution bias and aggression in adults—A systematic review. Aggression and Violent Behavior, 46, 66–81. 10.1016/j.avb.2019.01.009 [DOI] [Google Scholar]
  32. Knox J, Schneider J, Greene E, Nicholson J, Hasin D, & Sandfort T (2019). Using social network analysis to examine alcohol use among adults: A systematic review. PLOS ONE, 14(8), e0221360. 10.1371/journal.pone.0221360 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kohler CG, Turner T, Stolar NM, Bilker WB, Brensinger CM, Gur RE, & Gur RC (2004). Differences in facial expressions of four universal emotions. Psychiatry Research, 128(3), 235–244. 10.1016/j.psychres.2004.07.003 [DOI] [PubMed] [Google Scholar]
  34. Kret ME, & De Gelder B (2012). A review on sex differences in processing emotional signals. Neuropsychologia, 50(7), 1211–1221. 10.1016/j.neuropsychologia.2011.12.022 [DOI] [PubMed] [Google Scholar]
  35. Kumar L, Creswell KG, Brown KW, Lyons G, & Feeney BC (2025). Alcohol’s acute effects on emotion recognition and empathy in heavy-drinking young adults. Scientific Reports, 15(1), 13807. 10.1038/s41598-025-98153-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Kyranides MN, Christofides D, & Çetin M (2022). Difficulties in facial emotion recognition: Taking psychopathic and alexithymic traits into account. BMC Psychology, 10(1), 239. 10.1186/s40359-022-00946-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Lin Y, Xu F, Ye X, Zhang H, Ding H, & Zhang Y (2025). Age and sex differences in emotion perception are influenced by emotional category and communication channel. Psychology and Aging, 40(1), 17–31. 10.1037/pag0000828 [DOI] [PubMed] [Google Scholar]
  38. Melkonian A, Ham L, & Mobley A (2021). Gender moderates the association between acute alcohol intoxication and facial emotion recognition in a naturalistic field study setting. Alcoholism: Clinical and Experimental Research, 45(8), 1684–1692. 10.1111/acer.14653 [DOI] [PubMed] [Google Scholar]
  39. Morgenroth T, & Ryan MK (2018). Gender trouble in social psychology: How can Butler’s work inform experimental social psychologists’ conceptualization of gender? Frontiers in Psychology, 9, Article 1320. 10.3389/fpsyg.2018.01320 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Nagar M, Weller A, & Rabinovitz S (2021). The dosing procedure that “makes the poison”: Comparing the effects of single versus cumulative alcohol administration methods on emotion recognition. Journal of Psychopharmacology, 35(11), 1411–1419. 10.1177/02698811211032466 [DOI] [PubMed] [Google Scholar]
  41. National Institute on Alcohol Abuse and Alcoholism. (2025, February). Understanding Binge Drinking. U.S. Department of Health and Human Services, National Institutes of Health. https://www.niaaa.nih.gov/publications/brochures-and-fact-sheets/binge-drinking [Google Scholar]
  42. Olderbak S, Riggenmann O, Wilhelm O, & Doebler P (2021). Reliability generalization of tasks and recommendations for assessing the ability to perceive facial expressions of emotion. Psychological Assessment, 33(10), 911–926. 10.1037/pas0001030 [DOI] [PubMed] [Google Scholar]
  43. Proverbio AM, Riva F, & Zani A (2010). When neurons do not mirror the agent’s intentions: Sex differences in neural coding of goal-directed actions. Neuropsychologia, 48(5), 1454–1463. 10.1016/j.neuropsychologia.2010.01.015 [DOI] [PubMed] [Google Scholar]
  44. Proverbio AM (2023). Sex differences in social cognition. In Boggio PS, Wingenbach TSH, da Silveira Coêlho ML, Comfort WE, Murrins Marques L, & Alves MVC (Eds.), Social and affective neuroscience of everyday human interaction: From theory to methodology (pp. 83–101). Springer. 10.1007/978-3-031-08651-9_6 [DOI] [PubMed] [Google Scholar]
  45. Reed P, & Steed I (2019). The effects of concurrent cognitive task load on recognising faces displaying emotion. Acta Psychologica, 193, 153–159. 10.1016/j.actpsy.2019.01.001 [DOI] [PubMed] [Google Scholar]
  46. Sanov BN, Kumar L, & Creswell KG (2023). A systematic review of the acute effects of alcohol on emotion recognition of facial expressions. Addiction Biology, 28(12), e13345. 10.1111/adb.13345 [DOI] [PubMed] [Google Scholar]
  47. Sayette MA (2017). The effects of alcohol on emotion in social drinkers. Behaviour Research and Therapy, 88, 76–89. 10.1016/j.brat.2016.06.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Schlegel K, Fontaine JRJ, & Scherer KR (2019). The Nomological Network of Emotion Recognition Ability: Evidence from the Geneva emotion recognition Test. European Journal of Psychological Assessment, 35(3), 352–363. 10.1027/1015-5759/a000396 [DOI] [Google Scholar]
  49. Schmid PC, & Schmid Mast M (2010). Mood effects on emotion recognition. Motivation and Emotion, 34(3), 288–292. 10.1007/s11031-010-9170-0 [DOI] [Google Scholar]
  50. Steele CM, & Josephs RA (1990). Alcohol myopia: Its prized and dangerous effects. American psychologist, 45(8), 921. 10.1037/0003-066X.45.8.921 [DOI] [PubMed] [Google Scholar]
  51. Stroop JR (1935). Studies of interference in serial verbal reactions. J. Exp. Psychology. 18, 643–662. doi: 10.1037/h0054651 [DOI] [Google Scholar]
  52. Sudhinaraset M, Wigglesworth C, & Takeuchi D (2016). Social and Cultural Contexts of Alcohol Use: Influences in a Social-Ecological Framework. Alcohol research: current reviews, 38(1), 35–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Swahn MH, & Donovan JE (2006). Alcohol and violence: Comparison of the psychosocial correlates of adolescent involvement in alcohol-related physical fighting versus other physical fighting. Addictive Behaviors, 31(11), 2014–2029. 10.1016/j.addbeh.2006.02.001 [DOI] [PubMed] [Google Scholar]
  54. Testa M, Fillmore MT, Norris J, Abbey A, Curtin JJ, Leonard KE, Mariano KA, Thomas MC, Nomensen KJ, George WH, VanZile-Tamsen C, Livingston JA, Saenz C, Buck PO, Zawacki T, Parkhill MR, Jacques AJ, & Hayman LW (2006). Understanding Alcohol Expectancy Effects: Revisiting the Placebo Condition. Alcoholism, Clinical and Experimental Research, 30(2), 339–348. 10.1111/j.1530-0277.2006.00039.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Thompson AE, & Voyer D (2014). Sex differences in the ability to recognise non-verbal displays of emotion: A meta-analysis. Cognition and Emotion, 28(7), 1164–1195. 10.1080/02699931.2013.875889 [DOI] [PubMed] [Google Scholar]
  56. Udayar S, Fiori M, & Bausseron E (2020). Emotional intelligence and performance in a stressful task: The mediating role of self-efficacy. Personality and Individual Differences, 156, 109790. 10.1016/j.paid.2019.109790 [DOI] [Google Scholar]
  57. Venerable WJ, & Fairbairn CE (2020). A multimodal, longitudinal investigation of alcohol’s emotional rewards and drinking over time in young adults. Psychology of Addictive Behaviors, 34(5), 601–612. 10.1037/adb0000567 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Voruz P, Cionca A, Jacot De Alcântara I, Nuber-Champier A, Allali G, Benzakour L, Lalive PH, Lövblad KO, Braillard O, Nehme M, Coen M, Serratrice J, Reny J, Pugin J, Guessous I, Ptak R, Landis BN, Adler D, Griffa A, … Péron JA (2023). Brain functional connectivity alterations associated with neuropsychological performance 6–9 months following SARS-CoV -2 infection. Human Brain Mapping, 44(4), 1629–1646. 10.1002/hbm.26163 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Walter NT, Mutic S, Markett S, Montag C, Klein AM, & Reuter M (2011). The Influence of Alcohol Intake and Alcohol Expectations on the Recognition of Emotions. Alcohol and Alcoholism, 46(6), 680–685. 10.1093/alcalc/agr082 [DOI] [PubMed] [Google Scholar]
  60. Watson PE, Watson ID, & Batt RD (1981). Prediction of blood alcohol concentrations in human subjects. Updating the Widmark Equation. Journal of Studies on Alcohol, 42(7), 547–556. 10.15288/jsa.1981.42.547 [DOI] [PubMed] [Google Scholar]
  61. Wells S, & Graham K (2002). Aggression involving alcohol: Relationship to drinking patterns and social context. Addiction, 98(1), 33–42. 10.1046/j.1360-0443.2003.00253.x [DOI] [PubMed] [Google Scholar]
  62. Williams KD (2007). Ostracism. Annual Review of Psychology, 58, 425–452. 10.1146/annurev.psych.58.110405.085641 [DOI] [PubMed] [Google Scholar]
  63. Yang R, Patel TN, Fairbairn CE, & Benjamin AS (2025). The impact of alcohol intoxication on extended vigilance and rest-break recovery. Attention, Perception, & Psychophysics, 87, 998–1009. [DOI] [PMC free article] [PubMed] [Google Scholar]

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