research.edgehill.ac.uk et al.E… · Web viewAllocating under the influence: Effects of alcohol...
Transcript of research.edgehill.ac.uk et al.E… · Web viewAllocating under the influence: Effects of alcohol...
Running head: ALCOHOL INTOXICATION AND GROUP BIAS 1
Allocating under the influence: Effects of alcohol intoxication and social identification on in-
group favouritism
Jin Zhoua,1, PhD
Derek Heima, PhD
Rebecca Monka, PhD
Andrew Levya, PhD
Paul Pollardb, PhD
aEdge Hill University, Ormskirk, Lancashire, United Kingdom
bUniversity of Central Lancashire, Preston, Lancashire, United Kingdom
1Corresponding author: Jin Zhou (present address), Centre for Education Statistics and
Evaluation, Department of Education, NSW 2000, Australia, [email protected],
+61(0)295641024
Tables: 4
Figures: 1
ALCOHOL INTOXICATION AND GROUP BIAS 2
Abstract
The ‘social lubrication’ function of alcohol during interpersonal interactions is well
documented. However, less is known about the effects of alcohol consumption on group-level
behaviour. Empirical findings from social psychological literature suggest that individuals
tend to favour those who are considered as members of their own social group. Not yet
evaluated is how alcohol intoxication interacts with this group-level bias. Therefore, the
current study examined experimentally the effects of intoxication on group bias. Ninety-four
individuals (Mage = 20.18, SD = 2.36, female = 55) were randomly assigned to consume an
alcoholic (n = 48) or a placebo (n = 46) drink before completing manipulated allocation
matrices, a task which measured the distribution of hypothetical monetary awards based on
social groups. Results point to an interaction between drink condition and social
identification, whereby social identification was significantly associated with in-group
favouritism among intoxicated individuals only. Following alcohol consumption, participants
with higher identification with their social group were more likely to demonstrate allocation
strategies that favoured their own group members. However, non-significant effects were
observed for those in the placebo condition. The findings highlight how alcohol intoxication
may facilitate group bias that results from social group identification.
Keywords: alcohol intoxication; social identification; in-group favouritism; group bias
ALCOHOL INTOXICATION AND GROUP BIAS 3
Public significance statement
This study provides laboratory evidence that alcohol intoxication may magnify group biases
that are based on our social group affiliation. When it comes to managing drinking
environments and drinkers’ behaviours, it is important to consider how intoxication affects
group-level processes that may contribute to discriminatory intergroup behaviour.
ALCOHOL INTOXICATION AND GROUP BIAS 4
Disclosures and Acknowledgements
This work was financially supported by an Alcohol Research UK PhD Studentship grant
awarded to the lead author.
All authors have contributed significantly to the writing, analyses, and the interpretations
provided in the paper and have read and approved the final manuscript.
No conflicts of interest are reported.
We would like to thank Maddison Barnes, Lydia Suffling, and Keelan Donohue from Edge
Hill University for their research assistance during this study.
Author Note
This study forms part of a doctoral programme of research and is included in an archived
thesis at the lead author’s institution.
ALCOHOL INTOXICATION AND GROUP BIAS 5
Allocating under the influence: Effects of alcohol intoxication and social identification on in-
group favouritism
Alcohol consumption is often a social activity (Dietler, 2006; Douglas, 1987), and
researchers have begun to examine the mechanisms that may help explain its social
lubricating effects (Frings, Hopthrow, Abrams, Hulbert, & Gutierrez, 2008; Kirchner,
Sayette, Cohn, Moreland, & Levine, 2006; Sayette et al., 2012). However, although alcohol
can prompt social bonding and improve interpersonal interactions (de Visser, Wheeler,
Abraham, & Smith, 2013; Fairbairn, Sayette, Aalen, & Frigessi, 2015; Monahan & Lannutti,
2000), concurrently, its consumption is also associated with interpersonal and intergroup
hostility and violence (Graham et al., 1998; Hunt & Laidler, 2001; Levine, Lowe, Best, &
Heim, 2012). In this respect, remarkably little is known about how alcohol consumption
affects the psychological processes that may underpin adverse group-level behaviours. To
examine this, the present research utilises a classic social psychological experimental
paradigm to examine the psychopharmacological effects of intoxication on group bias.
A considerable amount of research has revealed that alcohol consumption can
powerfully shape a range of social behaviours such as flirtation (Monahan & Lannutti, 2000),
group formation (Kirchner et al., 2006), and even business negotiations (Au & Zhang, 2016).
Researchers have observed groups of unacquainted participants to display an increased
amount of positive behaviours, such as more expressive speech patterns and smiling,
following a moderate dose of alcohol (Sayette et al., 2012). It was also found that smiles were
more likely to be “caught” and reciprocated when the group had consumed alcohol, with this
mutual smiling more pronounced among heavier drinking participants (Fairbairn et al., 2015).
Together, such work indicates that alcohol consumption may increase people's expression of
and response to socially directed behaviours.
ALCOHOL INTOXICATION AND GROUP BIAS 6
Of note from the literature is that acute intoxication can lead to different outcomes
depending on determinants related to both the individual and the contextual cues. Alcohol’s
“myopic” effects are posited to be the result of impaired attentional capacity due to
intoxication (Steele & Josephs, 1990). This alcohol-induced impairment creates a narrowing
focus of attention to the most salient cues in one’s environment. As a consequence, the acute
effects of alcohol may result in, for example, increased cooperative or competitive behaviours
(Hopthrow, Abrams, Frings, & Hulbert, 2007) or increased or decreased aggression
(Giancola, Duke, & Ritz, 2011), depending on the cues in the drinker’s environment. From
this perspective, it is not unreasoned to suggest that the social attributes of alcohol along with
the myopic effects of intoxication can lead a drinker’s attention to the salient intergroup cues
in one’s environment.
The acute effects of alcohol on intergroup responses have been principally examined
in studying racial bias. Some studies suggest that alcohol increases the expression of
prejudice and discrimination based on racial categories (Bartholow, Dickter, & Sestir, 2006;
Reeves & Nagoshi, 1993; Schlauch, Lang, Plant, Christensen, & Donohue, 2009; Schofield,
Unkelbach, & Denson, 2015). For example, Schofield and colleagues (2015) reported
increased participants’ bias to shoot Middle Eastern targets during a computerised shooter
task following alcohol consumption, compared to participants who received a placebo dose.
Relatedly, Mitchell et al. (2015) found that alcohol consumption led to an increase in ingroup
ratings, whereby Caucasian participants were significantly more likely to rate White-faced
stimuli as more attractive and physically healthy after drinking alcohol compared to sober
participants. However, the authors noted no differences in ratings for Black-face stimuli
between sober individuals or following alcohol, suggesting that the effects of alcohol on
intergroup bias in this study may be driven by increases in ingroup liking following
consumption (as opposed to outgroup derogation). With such work, researchers have begun
ALCOHOL INTOXICATION AND GROUP BIAS 7
to emphasise the effect of alcohol in amplifying people’s predispositions of group-related
attitudes and evaluations, rather than universally arousing hostility (Loersch, Bartholow,
Manning, Calanchini, & Sherman, 2015). However, it is increasingly apparent that there is a
paucity of research that is dissociated from the domain of race bias and relations. A crucial
gap remains in how we may apply social psychological theory to better understand
generalised social behaviours when under the influence of alcohol.
One of the most established findings in social psychological literature highlights how
the formation of individuals into groups can prompt the pursuit of in-group identity
enhancement and belonging through actions that favour one’s own group vis-à-vis others
(Diehl, 1990; Hogg & Abrams, 1990; Tajfel, 1982). Tajfel and colleagues first revealed that,
when faced with the task of distributing rewards to anonymous members from two groups,
participants tended to favour the members belonging to their own group, despite this
distribution strategy providing no personal advantage (Tajfel, Billig, Bundy, & Flament,
1971; Tajfel & Turner, 1979).
Since its conception, a substantial bank of research supports the notion that, when
given the opportunity, those with greater identification with their group enact behaviours that
differentiate between their own (in-group) and other groups (out-group) by displaying in-
group favouritism (Gagnon & Bourhis, 1996; Jetten, Spears, & Manstead, 1996; Sidanius,
Pratto, & Mitchell, 1994). This display of bias behaviour is theorised to arise from social
identification, the process whereby people believe they share a group membership with
others, and this has consequences for their interactions within their social environment
(Turner, 1985). In application, Reicher’s analysis of crowd behaviour provides a framework
for understanding the dynamics of unfolding intergroup hostilities through the theoretical lens
of social identity processes (Reicher, 1984, 1996).
ALCOHOL INTOXICATION AND GROUP BIAS 8
The social identity approach has been applied to describe and explain the mechanisms
underpinning a range of behaviours (Haslam, 2014). Most pertinent to the present topic is the
empirical research highlighting the moderating influence of individuals’ social identities on
their alcohol behaviours. For instance, studies find that the extent to which an individual feel
similar and close to their social group(s) affects how strongly referent normative beliefs
around drinking predicts actual personal consumption (Neighbors et al., 2010; Reed, Lange,
Ketchie, & Clapp, 2007). Interventions, such as reducing alcohol intake and drinking
intentions, are found to be more effective when social identities are taken into consideration
(Berger & Rand, 2008; Livingstone & McCafferty, 2015; Tarrant & Butler, 2011). Primarily,
what the findings demonstrate is that behavioural outcomes can be influenced by social
identification. Low identifiers are less likely to respond to group-relevant information, while
high identifiers are more likely to express attitude and behaviour alignment when presented
with the same information (Livingstone, Haslam, Postmes, & Jetten, 2011).
When considering the findings from the social identity and alcohol literature in
combination, it seems likely that alcohol has the potential to magnify group differentiating
behaviours that arise due to social identity mechanisms, as the evidence suggests that
intoxication facilitates people’s automatic or predisposed cognitive processes (Bartholow et
al., 2006; Hopthrow et al., 2007; Loersch et al., 2015). Previous alcohol administration and
group processes research has examined intoxicated social behaviours through a variety of
paradigms (see Frings et al., 2008; Hopthrow et al., 2007; Loersch et al., 2015). However, no
research to date has examined how alcohol affects the underlying psychological processes
related to group bias behaviour that is substantiated in the social identity literature.
The aim of the current study was to examine experimentally the effects of alcohol
intoxication on group bias. Here, we adopt the Tajfel matrices as an operationalised measure
of discrimination in order to examine how alcohol affects intergroup bias behaviour (Bourhis,
ALCOHOL INTOXICATION AND GROUP BIAS 9
Sachdev, & Gagnon, 1994; Tajfel et al., 1971; Turner, Brown, & Tajfel, 1979). We
hypothesised that, relative to those receiving a placebo, intoxicated individuals who identify
with their social group would be more likely to demonstrate group bias in the form of in-
group favouritism.
To test this notion, we recruited participants from the general undergraduate student
cohort and, in addition, purposefully recruited students who were members of a university-
affiliated sports team. Emergent theoretical perspectives suggest that identity processes are
particularly defined and salient for those participating in sport (Rees, Haslam, Coffee, &
Lavallee, 2015; Zhou & Heim, 2014). For instance, sportspeople typically report a strong
identification with their sporting group, and this connectedness is important for both sporting
and social elements of sports involvement (Miller, 2009) and can drive their alcohol
behaviours (Zhou, Heim, & Levy, 2016). Recruiting from a highly identified group such as
those involved in sport was therefore deemed to be a useful strategy for examining the
interaction between intoxication and social group identification, in comparison with a
(hypothetically) less defined group members (undergraduate coursemates).
Methods
Participants
Ethical guidelines ensured that alcohol administration procedures were in line with
recommended practice (NIAAA, 2004) and institutional approval was obtained. Study
recruitment attempted to recruit as many participants as possible within a three-month period
(February to April 2015) and sample sizes were not predetermined. Opportunity sampling
and recruitment yielded 121 individuals interested in participating in the study. The Alcohol
Use Disorders Identification Test (AUDIT; Saunders, Aasland, Babor, & Grant, 1993) was
used to screen the alcohol behaviours of potential participants. The process excluded
ALCOHOL INTOXICATION AND GROUP BIAS 10
respondents with scores of 20 or more (indicating a clinical dependency score of problematic
drinking; Babor, Higgins-Biddle, Saunders, & Monteiro, 2001) and less than three (indicating
non-regular drinkers). Female participants confirmed that they were not pregnant (with
pregnancy tests made available). All participants completed a medical questionnaire to
identify contraindications for alcohol consumption and medications known to react
negatively with alcohol that would warrant medical exclusion.
During participant screening procedures, 15 participants were deemed ineligible due
to medical factors and nine were excluded due to resulting AUDIT scores of 20 and above. A
total of 97 participants were admitted to the study. No statistical analyses were conducted
before the conclusion of data collection. Preliminary data cleaning removed three participants
due to incomplete or incorrect task responses. The final sample used for the main analyses
included 94 participants (55 female, 39 male; 91.6% White British), ranging in age between
18 and 32 years (Mage = 20.18, SD = 2.36). Among the total cohort, 40 were individuals who
indicated currently participating in sport and belonging to a sports club; 54 were non-sporting
undergraduate students. All participants were recruited from the same university.
Design and Materials
Drink conditions
The study implemented a 2 (Group: sports, non-sports) x 2 (Drink: alcohol, placebo)
between-participants design. Random allocation assigned 21 sports participants to the alcohol
condition (placebo = 19). The same procedure assigned 27 non-sports participants to the
alcohol condition (placebo = 27).
In the alcohol condition, the drink mixture was calculated for vodka 37.5% ABV at
0.6 g/kg for males and 0.5 g/kg for females, mixed with equal parts orange juice and tonic
ALCOHOL INTOXICATION AND GROUP BIAS 11
water (methodological replication, see Hopthrow et al., 2007; Rose & Grunsell, 2008). This
measurement of alcohol allows for intoxication at the average level of 0.35 Breath Alcohol
Concentration (BrAC): This converts to 0.08% Blood Alcohol Concentration (BAC), the UK
drink-and-drive limit. The placebo drink was a mixture of orange juice, tonic water, and 2ml
of surface vodka with a vodka ‘mist’ sprayed across the glass to support the placebo
manipulation. To further support the alcohol-placebo manipulation, all participants ingested a
strong mint lozenge prior to drinks consumption in order to disguise the flavour of the
beverages (e.g., Frings et al., 2008; Hopthrow et al., 2007). The mixture was divided into two
drinks of equal quantities, and participants were instructed to consume each drink spaced
across 3-4 minutes to help ensure a consistent drinking pace across all participants.
Task materials
The task booklet presented to participants contained a series of allocation matrices.
Each matrix consisted of 13 boxes containing pairs of numbers, displaying the choices of
possible payoffs. The receiver of the pay-offs, identified only by their group membership,
was either an in-group member (‘a fellow team- or course-mate’) or an out-group member (‘a
member from another institution’). For each matrix, participants chose a distribution pairing
that best determines how they wished to allocate the monetary payoffs. Hence, the matrices
provided a situation where moving from one end to the other offered a range of strategies that
required participants to decide to what extent they wished to maximise and compromise on
allocation amounts. Three types of matrices were used to pit different strategies of
distribution against each other to measure the strength, or ‘pull’, of specific strategies (see
Online Supplementary Material for illustrated examples; see also Bourhis et al., for a
comprehensive discussion of matrix construction and pull scores calculation):
ALCOHOL INTOXICATION AND GROUP BIAS 12
(a) In-group Favouritism (FAV = MD + MIP) versus Maximum Joint Profit (MJP) – distinguishes
between allocations that reflects in-group favouritism in terms of allocating the most amount
available for in-group profit while maximising the difference between the amount allocated to the
out-group, against allocating the maximum amount of total points for both groups when combined.
(b) Maximising Difference in favour of in-group (MD) versus Maximum In-group Profit (MIP) –
distinguishes between allocations that maximise the quantity difference between groups in a way
that favours the in-group, against awarding the highest amount available for the in-group overall.
(c) Parity (P) versus In-group Favouritism (FAV) – distinguishes between allocations that give
numerically equal amounts to each group, against in-group favouritism in terms of providing
maximum amount available for in-group profit while maximising the difference between the
amounts allocated to the out-group.
We presented each of the aforementioned matrices twice using the same number sequencing
as Turner and Tajfel (1979) and as exampled in Bourhis et al. (1994), with the labels of “in-
group” and “out-group” inverted on the second presentation for counter-balancing. In
addition, we included a direct measure of in/out-group favouritism: (d) Direct FAV, with a
matrix that moved from out-group favouritism, through to parity, through to in-group
favouritism (Moghaddam & Stringer, 1986). Finally, each matrix type was repeated with a
different sequence of numbers (although pairing strategies were unchanged). Thus, in total,
each participant completed 14 matrices. We report all measures, manipulations, and
exclusions in this study.
Procedure
There was no mention of the group bias interests of the research during the
recruitment process and throughout the experiment to ensure that participants were unaware
of the intent of the matrices. Instead, to explain the use of the allocation matrices, the study
protocol informed participants that the experiment sought to explore the effects of alcohol on
economic-related decision making.
ALCOHOL INTOXICATION AND GROUP BIAS 13
Recruited respondents completed the medical screening to determine their eligibility
for the study. Once confirmed, participants were requested to abstain from consuming alcohol
for 12 hours and to refrain from eating for three hours prior to attending their designated
laboratory session. Due to the consumption requirements, participants were also required to
consent to abstain from driving or exercising following study participation. Upon arrival,
participants completed consent forms and demographics questionnaire and were weighed
(kg). Using the Lion SD400 Alcometer®, participants provided a breathalyser reading to
check for baseline BrAC and confirm none had consumed alcohol before the study (all study
participants scored 0).
Following this, participants completed a questionnaire that contained items asking
them to confirm their group membership. The sports group members indicated the sport they
played and the sports club to which they belonged. The non-sports group members identified
the degree/course in which they were currently enrolled. Social identification was assessed
across three items using a seven-point Likert scale (1=strongly disagree, to 7=strongly agree):
“I have a lot in common with other members of my sports club/course”, “I feel strong ties to
other members of my sports club/course”, and “In general, being a sportsperson/student is an
important part of my self-image” (items taken from Cameron, 2004). The three items were
averaged to provide a single index of social identification (current α = .72).
The consumption phase lasted approximately 10 minutes. During the subsequent
absorption phase, participants left alone to watch an American sitcom television show for 20
minutes as a distraction activity. Following this, a further breathalysation to check for alcohol
intoxication was performed. The results of these readings were purposely masked from the
participants across all the conditions to uphold the placebo condition and so that none knew
their current BrAC levels prior to the commencement of the task.
ALCOHOL INTOXICATION AND GROUP BIAS 14
We framed the task as an economic-related exercise that gave participants the
responsibility of apportioning a hypothetical fund. Participants were instructed to use the
matrices to divide funding points between two individuals, only identified by their
designation as a fellow sports teammate /coursemate or someone from an external institution.
We instructed the participants to convert the points into monetary terms, whereby one point
was valued at £10 [approximately $15]. Thus, instead of distributing one and seven points,
for example, the ‘real’ amounts were £10 and £701. Instructions also stressed that these
allocations would be anonymous, and participants could not award these points to
themselves. No time constraints were in place and participants were left alone to complete the
task (approximated average task time to be five minutes). Only after completing the task
booklet were participants asked to provide a subjective intoxication rating via the scale “how
intoxicated do you feel right now?” (1=not at all, to 10=extremely), to check for the alcohol
manipulation.
On completion of the task, participants were fully debriefed on the true aims of the
study and compensated for the hour session (£6 [approximately $8] or undergraduate course
credits). In line with standard practice (NIAAA, 2004), those in the alcohol condition were
breathalysed and permitted to leave the laboratory when their BrAC scored below 0.14
(converts to a BAC level of 0.028%). Entertainment and refreshments were made available
while the participants waited for their BrAC to fall: disclaimers were signed if participants
wished to remove themselves from the study area before they had reached this recommended
level.
Task analysis
1 This methodological step was included in order to address previous concerns of using point allocations for distribution versus monetary amounts (Gaertner & Insko, 2001). Specifically, it has been argued that allocations represented by arbitrary points are relatively valued only against a quantity possessed by either group (Rabbie & Schot, 1990; Rabbie, Schot, & Visser, 1989). However, the allocation of money represents absolute terms where its value does not depreciate in relation to distribution choices. In an effort to address these methodological considerations, the current study instructed participants to consider both representations during the decision-making task.
ALCOHOL INTOXICATION AND GROUP BIAS 15
Each matrix choice (the paired allocations) was scored in terms of ranks from zero to
12; the ‘pull’ of one strategy will receive the highest, with the competing strategy receiving
the lowest score (Bourhis et al., 1994; Tajfel & Turner, 1979). When presented with the
labels of “in-group” and “out-group” inverted, the matrix score calculations ranged between -
12 and zero. Therefore, each strategy score (excluding Direct FAV) had a theoretical range of
-12 to 12, where zero epitomised parity (equal distribution), positive scores represented a
greater exhibition of the strategy, and negative scores characterised a greater intent to avoid
the strategy. For matrix type (d) Direct FAV, the intent was to directly measure in-/out-group
favouritism without the presence of a competing strategy, i.e., it was impossible to maximise
joint profits (Moghaddam & Stringer, 1986). Here, scores ranged from zero to 12, where zero
represented extreme out-group favouritism and 12 represented extreme in-group favouritism,
with parity scored at six. Responses from this matrix were analysed separately in the
manipulation checks.
Analytic strategy
Preliminary univariate tests compared group and drink conditions across the study
variables. Missing values were handled as listwise deletions. A within-treatment analysis of
the matrix types was conducted to determine if the ‘pull’ score from participants were
significantly different from 0 on the theoretical range of -12 to 12 (as described in Task
Analysis above). That is, the analysis determined whether the participant adopted a strategy
that pulled them away from parity (i.e., a score of 0) and engaged with the differentiation
strategies presented within each matrix. Prior to the main analyses, an examination of social
identification z-scores revealed one participant scoring more than three standard deviations
below the mean. The subsequent factor analysis and regression modelling was performed on
the full cohort and again with the outlier removed. No differences were observed across
outcomes and therefore, for completeness, the results with the full sample are presented.
ALCOHOL INTOXICATION AND GROUP BIAS 16
An exploratory factor analysis was used to reduce the seven allocation strategies into
latent factors in order to simplify analysis and interpretation (e.g., Jetten et al., 1996). For the
main analyses, interaction terms were calculated with mean centred continuous variables and
dummy-coded categorical variables. Main and interaction effects were entered into a
regression model examining the association between the study variables on the extracted
latent allocation strategies identified in the factor analysis. All multivariate analyses were
conducted with bootstrapping to fit significant models onto 10,000-sampled population to
adjust for unequal samples and non-normal distributions within our dependent measures.
Results
For those in the alcohol condition, BrAC readings taken after the absorption phrase
indicated that the intoxication level for the current study protocol was reached (M = .33, SD =
.09). BrAC readings confirmed no detectable intoxication levels among those in the placebo
condition. Those in the alcohol condition (M = 5.19, SD = 1.94) perceived themselves to be
significantly more intoxicated than the placebo group (M = 2.02, SD = 1.89), F(1,90) = 59.60,
p < .001, ηp2 = .398. No differences were found on subjective intoxication ratings between
cohort groups.
Two-way ANOVAs were performed to assess cohort and condition differences on
study dependent variables (see Table 1). The sports participants (M = 6.04, SD = .80) scored
significantly higher on social identification than the non-sports cohort (M = 5.30, SD = 1.04),
F(1,87) = 12.77, p = .001, ηp2 = .128. No differences were found on social identification
scores between drink conditions. A check for gender differences revealed no significant
differences among our study variables (inter-variable correlations can be found in the
supplementary material).
[TABLE 1 HERE]
ALCOHOL INTOXICATION AND GROUP BIAS 17
Strategy analyses within each treatment condition
A Wilcoxon matched pairs test analysed the differences among the ranked paired
allocations across the three matrix types (see Table 2). The pull of parity (P on FAV) was
statistically significant across all conditions, with the pull of fairness over in-group
favouritism representing the most utilised strategy for all groups. This suggests that when
faced with the choice of distributing in an equal manner or a differentiating manner, most
participants tended to opt for fairness. There was also a significant pull of in-group
favouritism across all groups when pitted against maximum joint profit (FAV on MJP),
suggesting that when presented with the choice of favouring one’s in-group at the expense of
the out-group, most participants would demonstrate some pull towards in-group favouritism.
[TABLE 2 HERE]
Factor analysis
Exploratory factor analysis was performed on the seven allocation strategies to
identify the underlying latent relationships representing group bias. Maximum likelihood
factor analysis performed with varimax rotation opted for an orthogonal rotation in
anticipation of emergent factors (in-group vs. out-group favouritism) to be uncorrelated.
Kaiser-Meyer-Olkin statistic reflected a good sample size adequate for factor analysis (KMO
= .76) and Bartlett’s test of sphericity indicated that the correlations between items were
sufficiently large for exploratory factor analysis, χ2 (21) = 303.83, p < .001.
The analysis revealed a two-factor solution, which accounted for 69.60% of the initial
variance and 56.97% of the extracted variance. The clustered strategies suggest that the first
factor contained four items that measured the pull of in-group favouritism strategies (see
ALCOHOL INTOXICATION AND GROUP BIAS 18
Table 3). This factor accounted for 48.98% of the initial variance and 44.39% of the extracted
variance. The second factor contained two items that measured the pull of overall profit gains
(profit maximising), accounting for an additional 20.62% of the initial variance and 12.58%
of the extracted variance. As the two identified factors were theoretically divergent strategies,
the Anderson-Rubin method calculated factor scores representing each participant’s
placement on the factors identified in the extraction (Anderson & Rubin, 1956).
[TABLE 3 HERE]
Interactions between drink condition and social identification
A regression model was computed for each extracted factor. Interaction terms were
derived from mean-centred social identification scores multiplied with dummy-coded groups
(control = 0, sports = 1; placebo = 0, alcohol = 1). Step 1 involved the main effects (group,
condition), Step 2 added social identification scores, and their interactions terms were
included in Step 3.
A significant regression model (see Table 4) was found for in-group favouritism,
F(5,84) = 12.53, p = .028, R2 = 13.8% (see Table 4). In the final step, only the interaction
between drink condition and social identification was significant, b = .42, p = .028, CI
[.08, .83]. Examination of the interaction slopes revealed that social identification was
associated with increased in-group favouritism for those in the alcohol condition only (b
= .56, p < .002, CI [.21, 390]. Non-significant effects were observed for those in the placebo
condition (b = .14, p = .211, CI [-.08, .36]. A check of simple contrasts revealed non-
significant differences on in-group favouritism between those in the alcohol versus the
placebo condition at above (+1 SD; p = .135) and below (-1 SD; p = .095) the mean value of
social identification. Posthoc power analysis was conducted using G*Power 3.1.9.2 on the
ALCOHOL INTOXICATION AND GROUP BIAS 19
significant effects revealed. This found that the power (1 – β error probability) was .71 –
acceptably close to the traditional standard of 0.8.
A separate regression analysis performed on profit maximising resulted in a non-
significant model and bared no significant mains or interaction effects in the final model.
Finally, posthoc probes were conducted to examine differences due to gender or group
membership. No main (p = .775) or two- or three-interaction effects (all p’s > .10) were
found for gender. Three-way interaction checks for drink condition x group x social
identification effects also yielded non-significant findings (p = .345).
[TABLE 4 HERE]
[FIGURE 1 HERE]
Discussion
The current study implemented an experimental design to examine the effects of
intoxication on group bias behaviour. The significant interaction between drink condition and
social identification demonstrated that participants who reported higher identification with
their social group were significantly more likely to engage in distribution strategies that
favoured their in-group members following alcohol consumption. However, this pattern was
not observed among those in the placebo condition. Results also indicate that there are lower
levels of in-group favouritism among those less identified with their group following alcohol
intoxication. In this regard, low identifiers may be insufficiently interested in or aware of
their group membership to engage in group discriminating strategies. The social identity
literature does suggest that significant in-group devaluation can occur when individuals do
not feel strong ties to their social group (Karasawa, 1991). If we consider the myopic effects
of alcohol, the group-level differentiation strategies required during the study’s task may
ALCOHOL INTOXICATION AND GROUP BIAS 20
have accentuated low identifiers’ lack of group identification and resulted in a reduced
tendency to engage in group bias behaviour. In-line with the alcohol myopic model (Steele &
Josephs, 1990), the findings of the present study indicate that the psychopharmacological
effects of alcohol may perhaps facilitate drinkers’ preferences (or lack of) for their social
group members.
While previous research outlines how alcohol consumption can increase positive
perceptions of group relations (Kirchner et al., 2006; Sayette et al., 2012), the current study
contributes to this body of literature by suggesting how group bias behaviour may also occur
following intoxication. These results may help to provide a theoretically grounded
understanding of intoxicated social behaviours. Favouring members from one’s own group
over out-group members may provide individuals with a greater sense of in-group identity
and positive self-esteem (Amiot, Sansfaçon, & Louis, 2014; Hogg & Abrams, 1988; Lemyre
& Smith, 1985; Oakes & Turner, 1980). However, these processes and motivations also
underpin the literature that describes the antecedents of intergroup discrimination and conflict
(Tajfel, 1982). The current findings suggest that such group-level processes may be
heightened following intoxication and, when taken together with theoretical applications and
evidence from social psychological literature, begin to identify the mechanisms through
which intoxicated social behaviours can precipitate intergroup hostilities (Ostrowsky, 2014;
Schofield et al., 2015). By indicating that intoxication can heighten (or disinhibit) intergroup
bias, particularly among those with strong and salient group identities, our findings suggest
that strategies aimed at minimising alcohol-fuelled intergroup hostilities may be usefully
informed by considering these group-level cognitions and responses. Delineating how alcohol
consumption may facilitate an ‘us’ versus ‘them’ mentality (Tajfel, 1982) potentially offers a
complementary approach to interventions aimed at tackling alcohol-related violence which
hitherto typically target individual drinkers (Plant, Plant, & Thornton, 2002).
ALCOHOL INTOXICATION AND GROUP BIAS 21
It should be noted that, in the present study, there was no inclusion of a non-alcoholic
drink control condition. To clarify, the current study specifically sought to examine how
alcohol consumption affects group-level behaviour. With this research aim in mind, it was
deemed appropriate to use the placebo manipulation to compare with the
psychopharmacological impact of intoxication on participants’ task responses. The current
study employed a number methodological steps to ensure an effective placebo manipulation
and, at the debrief, participants in the placebo condition were asked whether they suspected
the deception with none disclosing any strong suspicions. However, the lack of the expected
behavioural responses on the task for those in the placebo condition suggest that there may be
some degree of compensatory response where our participants’ expectancies around the acute
effects of alcohol consumption lead to behavioural monitoring to counteract such effects
(Marczinski & Fillmore, 2005; Schlauch et al., 2010). Given the small sample, and the
methodological obscuring of the veritable alcohol effects on group bias in the present study,
further research incorporating a non-alcohol condition is necessary in order to interpret fully
the psychopharmacological effects of intoxication from the expectancy-based alcohol effects
(Testa et al., 2006) in this paradigm.
Although the present findings indicate that intoxicated group members were more
likely to exhibit in-group favouring behaviour, we also acknowledge that behaviours are
often influenced by social (Abrams, Hopthrow, Hulbert, & Frings, 2006) and contextual
(Monk & Heim, 2013) cues. This interaction between alcohol and social processes requires
further interrogation away from a laboratory-based setting in order to evaluate how groups,
and individuals in groups, react to interpersonal interactions and the social context
(Hopthrow, Randsley de Moura, Meleady, Abrams, & Swift, 2014; Monk & Heim, 2014;
Sayette et al., 2012). Relatedly, there is existing commentary on the individual difference
factors that may affect the individual’s behaviours and/or their response to intoxication itself
ALCOHOL INTOXICATION AND GROUP BIAS 22
(see Sher & Wood, 2005). Previous research notes that, when in a similar economic-decision
making paradigm, individuals who demonstrate psychopathic traits, such as recklessness and
impulsivity, offer more money to their ingroup (members affiliated with their university),
relative to an outgroup (Gillespie, Mitchell, Johnson, Dawson, & Beech, 2013). Additionally,
aggression following alcohol is more likely among participants who have high levels of
dispositional aggressivity (Giancola, 2002). These form alternative perspectives on how
individual differences may factor in how intergroup behaviours are evaluated and expressed.
Finally, while the social identification items in the present study were selected to
represent the proposed three dimensions of social identification (Cameron, 2004), it should be
noted that there are short validated scales that have since been developed to assess social
identification (Postmes, Haslam, & Jans, 2013; Reysen, Katzarska‐Miller, Nesbit, & Pierce,
2013). Future research could take advantage of the brevity of these validated scales when
examining these socio-cognitive processes alongside alcohol intoxication in the field.
To conclude, the current study found that in-group bias behaviours increased among
intoxicated individuals who identified with their social group. The current research presents a
first look at the interplay between the psychopharmacological state of intoxication and social
identity mechanisms, and explores a novel yet fundamental social psychological perspective
of the behavioural consequences associated with alcohol. Replication and further
experimental research are necessary to investigate further how various contexts and alcohol
states interact with social identity processes to qualify the findings of this preliminary study.
ALCOHOL INTOXICATION AND GROUP BIAS 23
References
Abrams, D., Hopthrow, T., Hulbert, L., & Frings, D. (2006). ‘Groupdrink’? The effect of alcohol on
risk attraction among groups versus individuals. Journal of Studies on Alcohol, 67(4), 628–
636.
Amiot, C. E., Sansfaçon, S., & Louis, W. R. (2014). How normative and social identification
processes predict self‐determination to engage in derogatory behaviours against outgroup
hockey fans. European Journal of Social Psychology, 44(3), 216–230.
https://doi.org/10.1002/ejsp.2006
Anderson, T. W., & Rubin, H. (1956). Statistical inference in factor analysis (Vol. 5, p. 1). Presented
at the Proceedings of the third Berkeley symposium on mathematical statistics and
probability.
Au, P. H., & Zhang, J. (2016). Deal or no deal? The effect of alcohol drinking on bargaining. Journal
of Economic Behavior & Organization, 127, 70–86.
Babor, T. F., Higgins-Biddle, J. C., Saunders, J. B., & Monteiro, M. G. (2001). The Alcohol Use
Disorders Identification Test (AUDIT): Guidelines for use in primary care. Geneva: World
Health Organisation.
Bartholow, B. D., Dickter, C. L., & Sestir, M. A. (2006). Stereotype activation and control of race
bias: cognitive control of inhibition and its impairment by alcohol. Journal of Personality and
Social Psychology, 90(2), 272–287.
Berger, J., & Rand, L. (2008). Shifting signals to help health: Using identity signaling to reduce risky
health behaviors. Journal of Consumer Research, 35(3), 509–518.
https://doi.org/10.1086/587632
Bourhis, R. Y., Sachdev, I., & Gagnon, A. (1994). Intergroup research with the Tajfel matrices:
Methodological notes (Vol. 7, pp. 209–232). Presented at the The psychology of prejudice:
The Ontario symposium, Erlbaum Mahwah.
Cameron, J. E. (2004). A three-factor model of social identity. Self and Identity, 3(3), 239–262.
ALCOHOL INTOXICATION AND GROUP BIAS 24
de Visser, R. O., Wheeler, Z., Abraham, C., & Smith, J. A. (2013). ‘Drinking is our modern way of
bonding’: Young people’s beliefs about interventions to encourage moderate drinking.
Psychology & Health, 28(12), 1460–1480. https://doi.org/10.1080/08870446.2013.828293
Diehl, M. (1990). The minimal group paradigm: Theoretical explanations and empirical findings.
European Review of Social Psychology, 1(1), 263–292.
Dietler, M. (2006). Alcohol: anthropological/archaeological perspectives. Annu. Rev. Anthropol., 35,
229–249.
Douglas, M. (1987). Constructive Drinking: Perspectives on Drink from Anthropology. Cambridge:
Cambridge University Press.
Fairbairn, C. E., Sayette, M. A., Aalen, O. O., & 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. https://doi.org/10.1177/2167702614548892
Frings, D., Hopthrow, T., Abrams, D., Hulbert, L., & Gutierrez, R. (2008). Groupdrink: The effects of
alcohol and group process on vigilance errors. Group Dynamics: Theory, Research, and
Practice, 12(3), 179.
Gaertner, L., & Insko, C. A. (2001). On the measurement of social orientations in the minimal group
paradigm: Norms as moderators of the expression of intergroup bias. European Journal of
Social Psychology, 31(2), 143–154.
Gagnon, A., & Bourhis, R. Y. (1996). Discrimination in the minimal group paradigm: Social identity
or self-interest? Personality and Social Psychology Bulletin, 22(12), 1289–1301.
Giancola, P. R. (2002). Alcohol-related aggression in men and women: the influence of dispositional
aggressivity. Journal of Studies on Alcohol, 63(6), 696–708.
Giancola, P. R., Duke, A. A., & Ritz, K. Z. (2011). Alcohol, violence, and the alcohol myopia model:
Preliminary findings and implications for prevention. Addictive Behaviors, 36(10), 1019–
1022.
Gillespie, S. M., Mitchell, I. J., Johnson, I., Dawson, E., & Beech, A. R. (2013). Exaggerated
intergroup bias in economical decision making games: differential effects of primary and
secondary psychopathic traits. PloS One, 8(8), e69565.
ALCOHOL INTOXICATION AND GROUP BIAS 25
Graham, K., Leonard, K. E., Room, R., Wild, T. C., Pihl, R. O., Bois, C., & Single, E. (1998). Current
directions in research on understanding and preventing intoxicated aggression. Addiction,
93(5), 659–676.
Haslam, S. A. (2014). Making good theory practical: Five lessons for an Applied Social Identity
Approach to challenges of organizational, health, and clinical psychology. British Journal of
Social Psychology, 53(1), 1–20.
Hogg, M. A., & Abrams, D. (1988). Social identifications: A social psychology of intergroup
relations and group processes. London, UK: Taylor & Frances/Routledge.
Hogg, M. A., & Abrams, D. (1990). Social motivation, self-esteem and social identity. In Social
Identity Theory: Constructive and Critical Advances (pp. 28–47). New York: Harvester
Wheatsheaf.
Hopthrow, T., Abrams, D., Frings, D., & Hulbert, L. G. (2007). Groupdrink: The effects of alcohol on
intergroup competitiveness. Psychology of Addictive Behaviors, 21(2), 272–276.
Hopthrow, T., Randsley de Moura, G., Meleady, R., Abrams, D., & Swift, H. J. (2014). Drinking in
social groups. Does ‘groupdrink’provide safety in numbers when deciding about risk?
Addiction, 109(6), 913–921.
Hunt, G. P., & Laidler, K. J. (2001). Alcohol and violence in the lives of gang members. Alcohol
Research and Health, 25(1), 66–71.
Jetten, J., Spears, R., & Manstead, A. S. (1996). Intergroup norms and intergroup discrimination:
distinctive self-categorization and social identity effects. Journal of Personality and Social
Psychology, 71(6), 1222–1233.
Karasawa, M. (1991). Toward an assessment of social identity: The structure of group identification
and its effects on in‐group evaluations. British Journal of Social Psychology, 30(4), 293–307.
Kirchner, T. R., Sayette, M. A., Cohn, J. F., Moreland, R. L., & Levine, J. M. (2006). Effects of
alcohol on group formation among male social drinkers. Journal of Studies on Alcohol and
Drugs, 67(5), 785–793.
Lemyre, L., & Smith, P. M. (1985). Intergroup discrimination and self-esteem in the minimal group
paradigm. Journal of Personality and Social Psychology, 49(3), 660–670.
ALCOHOL INTOXICATION AND GROUP BIAS 26
Levine, M., Lowe, R., Best, R., & Heim, D. (2012). ‘We police it ourselves’: Group processes in the
escalation and regulation of violence in the night‐time economy. European Journal of Social
Psychology, 42(7), 924–932. https://doi.org/10.1002/ejsp.1905
Livingstone, A. G., Haslam, S. A., Postmes, T., & Jetten, J. (2011). ‘We Are, Therefore We Should’:
Evidence That In‐Group Identification Mediates the Acquisition of In‐Group Norms1.
Journal of Applied Social Psychology, 41(8), 1857–1876.
Livingstone, A. G., & McCafferty, S. (2015). Explaining reactions to normative information about
alcohol consumption: A test of an extended social identity model. International Journal of
Drug Policy, 26(4), 388–395.
Loersch, C., Bartholow, B. D., Manning, M., Calanchini, J., & Sherman, J. W. (2015). Intoxicated
prejudice: The impact of alcohol consumption on implicitly and explicitly measured racial
attitudes. Group Processes & Intergroup Relations, 18(2), 256–268.
https://doi.org/10.1177/1368430214561693
Marczinski, C. A., & Fillmore, M. T. (2005). Compensating for alcohol-induced impairment of
control: effects on inhibition and activation of behavior. Psychopharmacology, 181(2), 337–
346.
Miller, K. E. (2009). Sport-related identities and the ‘toxic jock’. Journal of Sport Behavior, 32(1),
69–91.
Mitchell, I. J., Gillespie, S. M., Leverton, M., Llewellyn, V., Neale, E., & Stevenson, I. (2015). Acute
alcohol consumption and secondary psychopathic traits increase ratings of the attractiveness
and health of ethnic ingroup faces but not outgroup faces. Frontiers in Psychiatry, 6, 25.
Moghaddam, F. M., & Stringer, P. (1986). Trivial and important criteria for social categorization in
the minimal group paradigm. The Journal of Social Psychology, 126(3), 345–354.
Monahan, J. L., & Lannutti, P. J. (2000). Alcohol as social lubricant. Human Communication
Research, 26(2), 175–202.
Monk, R. L., & Heim, D. (2013). Environmental context effects on alcohol-related outcome
expectancies, efficacy, and norms: a field study. Psychology of Addictive Behaviors, 27(3),
814–818. https://doi.org/10.1037/a0033948
ALCOHOL INTOXICATION AND GROUP BIAS 27
Monk, R. L., & Heim, D. (2014). A systematic review of the Alcohol norms literature: A focus on
context. Drugs: Education, Prevention and Policy, 21(4), 263–282.
Neighbors, C., LaBrie, J. W., Hummer, J. F., Lewis, M. A., Lee, C. M., Desai, S., … Larimer, M. E.
(2010). Group identification as a moderator of the relationship between perceived social
norms and alcohol consumption. Psychology of Addictive Behaviors, 24(3), 522.
Oakes, P. J., & Turner, J. C. (1980). Social categorization and intergroup behaviour: Does minimal
intergroup discrimination make social identity more positive? European Journal of Social
Psychology, 10(3), 295–301.
Ostrowsky, M. K. (2014). The social psychology of alcohol use and violent behavior among sports
spectators. Aggression and Violent Behavior, 19(4), 303–310.
Plant, M., Plant, M., & Thornton, C. (2002). People and places: some factors in the alcohol-violence
link. Journal of Substance Use, 7(4), 207–213.
Postmes, T., Haslam, S. A., & Jans, L. (2013). A single‐item measure of social identification:
Reliability, validity, and utility. British Journal of Social Psychology, 52(4), 597–617.
Rabbie, J. M., & Schot, J. C. (1990). Group behavior in the minimal group paradigm: Fact or fiction?
In European Perspectives in Psychology: Work and Organizational, Social and Economic,
Cross-cultural (Vol. 3, pp. 251–263). Oxford, England: John Wiley & Sons.
Rabbie, J. M., Schot, J. C., & Visser, L. (1989). Social identity theory: A conceptual and empirical
critique from the perspective of a behavioural interaction model. European Journal of Social
Psychology, 19(3), 171–202.
Reed, M. B., Lange, J. E., Ketchie, J. M., & Clapp, J. D. (2007). The relationship between social
identity, normative information, and college student drinking. Social Influence, 2(4), 269–
294. https://doi.org/10.1080/15534510701476617
Rees, T., Haslam, S. A., Coffee, P., & Lavallee, D. (2015). A social identity approach to sport
psychology: Principles, practice, and prospects. Sports Medicine, 45(8), 1083–1096.
https://doi.org/10.1007/s40279-015-0345-4
Reeves, S. B., & Nagoshi, C. T. (1993). Effects of alcohol administration on the disinhibition of racial
prejudice. Alcoholism: Clinical and Experimental Research, 17(5), 1066–1071.
ALCOHOL INTOXICATION AND GROUP BIAS 28
Reicher, S. (1984). The St. Pauls’ riot: An explanation of the limits of crowd action in terms of a
social identity model. European Journal of Social Psychology, 14(1), 1–21.
Reicher, S. (1996). ‘The Battle of Westminster’: developing the social identity model of crowd
behaviour in order to explain the initiation and development of collective conflict. European
Journal of Social Psychology, 26(1), 115–134.
Reysen, S., Katzarska‐Miller, I., Nesbit, S. M., & Pierce, L. (2013). Further validation of a single‐item
measure of social identification. European Journal of Social Psychology, 43(6), 463–470.
Rose, A. K., & Grunsell, L. (2008). The subjective, rather than the disinhibiting, effects of alcohol are
related to binge drinking. Alcoholism: Clinical and Experimental Research, 32(6), 1096–
1104.
Saunders, J. B., Aasland, O. G., Babor, T. F., & Grant, M. (1993). Development of the alcohol use
disorders identification test (AUDIT): WHO collaborative project on early detection of
persons with harmful alcohol consumption‐II. Addiction, 88(6), 791–804.
Sayette, M. A., Creswell, K. G., Dimoff, J. D., Fairbairn, C. E., Cohn, J. F., Heckman, B. W., …
Moreland, R. L. (2012). Alcohol and Group Formation: A Multimodal Investigation of the
Effects of Alcohol on Emotion and Social Bonding. Psychological Science, 23(8), 869–878.
Schlauch, R. C., Lang, A. R., Plant, E. A., Christensen, R., & Donohue, K. F. (2009). Effect of
alcohol on race-biased responding: The moderating role of internal and external motivations
to respond without prejudice. Journal of Studies on Alcohol and Drugs, 70(3), 328–336.
Schlauch, R. C., Waesche, M. C., Riccardi, C. J., Donohue, K. F., Blagg, C. O., Christensen, R. L., &
Lang, A. R. (2010). A meta-analysis of the effectiveness of placebo manipulations in alcohol-
challenge studies. Psychology of Addictive Behaviors, 24(2), 239–253.
Schofield, T. P., Unkelbach, C., & Denson, T. F. (2015). Alcohol consumption increases bias to shoot
at Middle Eastern but not White targets. Group Processes & Intergroup Relations, Early
Online Print. https://doi.org/10.1177/1368430215603461
Sher, K. J., & Wood, M. D. (2005). Subjective effects of alcohol II: Individual differences. In Mind
altering Drugs: Scientific Evidence for Subjective Experience. M. Earleywine (Ed.). (pp. 135–
153). New York: Oxford Press.
ALCOHOL INTOXICATION AND GROUP BIAS 29
Sidanius, J., Pratto, F., & Mitchell, M. (1994). In-group identification, social dominance orientation,
and differential intergroup social allocation. The Journal of Social Psychology, 134(2), 151–
167.
Steele, C. M., & Josephs, R. A. (1990). Alcohol myopia: Its prized and dangerous effects. American
Psychologist, 45(8), 921–933.
Tajfel, H. (1982). Social psychology of intergroup relations. Annual Review of Psychology, 33(1), 1–
39.
Tajfel, H., Billig, M. G., Bundy, R. P., & Flament, C. (1971). Social categorization and intergroup
behaviour. European Journal of Social Psychology, 1(2), 149–178.
Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In The Social
Psychology of Intergroup Relations (pp. 33–47). Monterey, CA: Brooks/Cole.
Tarrant, M., & Butler, K. (2011). Effects of self‐categorization on orientation towards health. British
Journal of Social Psychology, 50(1), 121–139. https://doi.org/10.1348/014466610X511645
Testa, M., Fillmore, M. T., Norris, J., Abbey, A., Curtin, J. J., Leonard, K. E., … George, W. H.
(2006). Understanding alcohol expectancy effects: Revisiting the placebo condition.
Alcoholism: Clinical and Experimental Research, 30(2), 339–348.
Turner, J. C. (1985). Social categorization and the self-concept: A social cognitive theory of group
behavior. Advances in Group Processes, 2, 77–122.
Turner, J. C., Brown, R. J., & Tajfel, H. (1979). Social comparison and group interest in ingroup
favouritism. European Journal of Social Psychology, 9(2), 187–204.
Zhou, J., & Heim, D. (2014). Sports and Spirits: A Systematic Qualitative Review of Emergent
Theories for Student-Athlete Drinking. Alcohol and Alcoholism, 49(6), 604–617.
Zhou, J., Heim, D., & Levy, A. (2016). Sports Participation and Alcohol Use: Associations With
Sports-Related Identities and Well-Being. Journal of Studies on Alcohol and Drugs, 77(1),
170–179. https://doi.org/10.15288/jsad.2016.77.170
ALCOHOL INTOXICATION AND GROUP BIAS 30
Table 1.Participant demographics and scores across study variables.
Study variables Conditions
Non-sports Sports Placebo Alcohol
Age, mean (SD) 20.22 (2.87) 20.13 (1.45) 20.46 (2.90) 19.92 (1.68)
Gender, female (%) 38 (70.4%) 17 (42.5%) 26 (56.5%) 29 (60.4%)
Social identification, mean (SD) 5.30 (1.04) 6.04 (.80) 5.52 (1.19) 5.69 (.82)
BrAC, mean (SD) 0.34 (.09) 0.33 (.08) 0.00 0.33 (.09)
Subjective intoxication, mean (SD) 2.04 (1.89) 5.19 (1.94)
Non-sports - - 2.00 (1.66) 5.52 (2.12)
Sports - - 2.11 (2.21) 4.72 (1.64)
Note. BrAC = Breath Alcohol Concentration taken after absorption phase.
ALCOHOL INTOXICATION AND GROUP BIAS 31
Table 2.Means pull scores of participants' matrix strategies as a function of condition (placebo vs. alcohol) and group (non-sports vs. sports participants).
Study conditions
Allocation strategy Non-sports Sports Placebo Alcohol
FAV on MJPMJP on FAV
1.92 (3.12)*0.32 (1.57)
3.56 (3.92)**-0.14 (1.80)
2.30 (3.07)**0.13 (2.07)
2.92 (3.98)**0.13 (1.20)
MD on MIPMIP on MD
1.32 (2.76)1.17 (3.83)
2.74 (3.84)*-0.19 (4.15)
1.71 (3.13)0.76 (4.85)
2.11 (3.50)*0.45 (3.01)
FAV on PP on FAV
1.72 (3.75) 8.15 (3.51)**
2.38 (3.89) 8.76 (3.77)**
1.86 (2.93) 9.07 (3.10)**
2.14 (4.55) 7.76 (4.00)**
Direct FAV₸ 7.98 (1.92) 8.75 (2.01) 8.31 (1.78) 8.30 (2.19)
NOTE: Possible pull scores for each strategy range from -12 to 12. FAV = in-group favouritism; MJP = maximum joint profit; MD = maximum difference; MIP = maximum in-group profit; P = parity.
₸ Separate direct measure of favouritism. Scores range from 0 to 12.* p < .01; **p < .001; Wilcoxon matched-pairs test (two-tailed)
ALCOHOL INTOXICATION AND GROUP BIAS 32
Table 3.Rotated factor matrix (maximum likelihood) with orthogonal component loading (varimax with Kaiser Normalization) for seven distribution strategies (N = 94).
Factor
(1) In-group favouritism (2) Profit maximising
Fav on MJP .95 -.11
Direct FAV .84 -.24
FAV on P .80 .09
P on FAV -.65 -.15
MD on MP .59 -.17
MP on MD .12 .65
MJP on FAV -.21 .61
Note. Values in boldface type indicate the item’s primary factor loading.
ALCOHOL INTOXICATION AND GROUP BIAS 33
Table 4.Hierarchical regression model to compare mains effect of group and drink condition, and interaction effects on in-group favouritism, bias-corrected 95% confidence intervals indicated in brackets.
(1) In-group favouritism
b [BCa 95% CI]
Step 1
Group .31 [-0.08-0.70]
Drink condition .07 [-0.30-0.45]
Step statistics F(2,88) = 1.27, p = .286, R2 = .028
Step 2
Group .12 [-0.29-0.57]
Drink condition .04 [-0.33-0.40]
Social identification .24 [0.08-0.44]**
Step statistics F(1,87)=5.75, p = .019, ΔR2 = .06
Step 3
Group -.01 [-0.40-0.43]
Drink condition .01 [-0.34-0.38]
Social identification .08 [-0.17-0.28]
Group x social identification .14 [-0.27-0.56]
Drink x social identification .42 [0.08-0.83]*
Step statistics F(2,85)=2.48, p = .09, ΔR2 = .05
*p < .05, **p < .01
ALCOHOL INTOXICATION AND GROUP BIAS 34
Figure 1.Graphed interaction between social identification and alcohol/placebo drink condition.
-1-.5
0.5
1In
-gro
up F
avou
ritis
m
-1 1Social Identification (-/+SD)
placebo alcohol