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‘Beauty is in the eye of the beer holder’: People
who think they are drunk also think
they are attractive
Laurent Bègue1∗ , Brad J. Bushman2,3, Oulmann Zerhouni1,
Baptiste Subra4 and Medhi Ourabah5
1University of Grenoble 2, France
2The Ohio State University, Columbus, Ohio, USA
3VU University, Amsterdam, The Netherlands
4University of Paris Descartes, France
5University of Paris 8, Saint-Denis, France
This research examines the role of alcohol consumption on self-
perceived attractiveness.
Study 1, carried out in a barroom (N = 19), showed that the
more alcoholic drinks
customers consumed, the more attractive they thought they
were. In Study 2, 94 non-
student participants in a bogus taste-test study were given either
an alcoholic beverage
(target BAL [blood alcohol level] = 0.10 g/100 ml) or a non-
alcoholic beverage, with
half of each group believing they had consumed alcohol and
half believing they had
not (balanced placebo design). After consuming beverages, they
delivered a speech and
rated how attractive, bright, original, and funny they thought
they were. The speeches
were videotaped and rated by 22 independent judges. Results
showed that participants
who thought they had consumed alcohol gave themselves more
positive self-evaluations.
However, ratings from independent judges showed that this
boost in self-evaluation was
unrelated to actual performance.
‘Beauty is in the eye of the beer holder’
—Kinky Friedman
Alcohol has many consequences on social perception and
relationships. After a drink,
intoxicated people see members of the opposite sex through
‘beer goggles’, which makes
them look especially attractive (Jones, Jones, Thomas, & Piper,
2003; Lyvers, Cholakians,
Puorro, & Sundram, 2011; Neave, Tsang, & Heather, 2008). But
alcohol can also influence
self-perceptions. Previous research on alcohol and self-
awareness has found that alcohol
reduces self-awareness by inhibiting self-relevant encoding
processes (Hull, Levenson,
Young, & Sher, 1983). The purpose of the present research is to
test the hypothesis
∗Correspondence should be addressed to Laurent Bègue,
University of Grenoble 2, LIP, 1251, Av. Centrale, BP47, 38040
Grenoble, France (e-mail: [email protected]).
DOI:10.1111/j.2044-8295.2012.02114.x
British Journal of Psychology (2013), 104, 225–234
© 201 The British Psychological Society
www.wileyonlinelibrary.com
225
2
that alcohol consumption increases self-perceived
attractiveness. Whereas meta-analytic
reviews indicate that alcohol consumption enhances mood and
sexual arousal (Hull &
Bond, 1986), the link between alcohol consumption and self-
perceived attractiveness
remains to be clarified and theoretically developed.
In order to understand the link between alcohol and self-
processes, we relied
on the dual-process model of alcohol-related behaviour (Moss &
Albery, 2009; see
also Moss & Albery, 2010; Wiers & Stacy, 2010). This model
suggests that although
alcohol consumption disrupts cognitive controlled processes,
the mind may still become
‘intoxicated’ even in the absence of alcohol consumption (Moss
& Albery, 2009). For
example, when people believe that they are intoxicated, they
behave more aggressively
(Bègue et al., 2009), and show more sexually disinhibited
behaviours (Crowe & Georges,
1989). Various studies indicate that the effects of alcohol on
human cognition and
behaviour should distinguish pharmacological and social
psychological consequences
of alcohol consumption. In the field of sexual arousal, for
example, a meta-analytic
review indicated that alcohol consumption had a non-significant
effect on sexual arousal,
whereas the mere expectation of drinking alcohol significantly
increased sexual arousal
(Hull & Bond, 1986). From this perspective, behaviours that are
disinhibited after
drinking a placebo can be understood as a consequence of the
activation of alcohol-
related concepts in memory. In one study, the mere subliminal
activation of alcohol-
related concepts caused men to rate the faces of women as more
sexually attractive
(Friedman, McCarty, Forster, & Denzler, 2005).
Drunkenness is thus not merely a physiological consequence of
alcohol, but involves
complex interactions of both limited processing capacities
(myopia theory, see below)
and chronically and temporarily activated mental
representations that make certain
patterns of responding more accessible (expectancy theory, see
below). According to the
dual-process model of the alcohol behaviour (Moss & Albery,
2009), a full understanding
of alcohol effects has to integrate both pharmacological and
extra-pharmacological
consequences of alcohol on human cognition and behaviour.
Expectancies are the first
component of the model. They are considered as the result of
learned associations
between alcohol-related representations in memory. The sources
of this associative
process could be referred to as conditioning (Hull & Bond,
1986) or vicarious learning
(Bandura, 1965). For example, content analyses show that
media characters who
drink alcohol are generally depicted as more attractive than
those who do not drink
alcohol (McIntosh, 1999). Hence, to the extent that people
strongly endorse alcohol-
self-enhancement expectancies, concepts of ‘alcohol’ and
‘attractiveness’ would be
linked together in memory. According to alcohol expectancy
theory, alcohol-related cues
could implicitly activate alcohol-related expectancies, which
could, in turn, affect social
judgements and behaviours that are in line with these alcohol-
related expectancies. The
concept of alcohol expectancy is based on a semantic network
model of memory (Collins
& Quillian, 1969), which posits that concepts that frequently
co-occur, or share a similar
meaning, are stored close together in memory. When one
concept is activated, other
related concepts also become more accessible through a
spreading activation process
(Collins & Loftus, 1975). For instance, social knowledge
regarding alcohol effects is
automatically activated in memory during the natural course of
perception, without
awareness or intention. Knowledge activation, in turn, shapes
and guides people’s
impressions, judgements, feelings, and intentions without
awareness that such influence
is occurring (see Bargh & Erin, 2006; Bargh & Ferguson, 2000;
Ferguson & Bargh, 2004).
Another aspect of the dual-process model is related to the
physiological consequences
of alcohol consumption. According to the attention allocation
model, alcohol has a
226 Laurent B�egue et al.
‘myopic’ or narrowing effect on attention (Giancola & Corman,
2007; Steele & Josephs,
1990), which causes people to focus attention on the most
salient cues and to not
pay attention to more subtle or distal cues. Alcohol myopia is
therefore defined as
a state of short-sightedness in which superficially understood,
immediate aspects of
experience have a disproportionate influence on behaviours and
emotions (Steele &
Josephs, 1990). Although a sober individual can consider a
range of information more
or less salient before responding to a social situation, an
intoxicated individual will be
less concerned with consideration distal in time and place
because he will be captive
of an impoverished version of reality in which the breadth,
depth, and timeline of his
understanding will be affected. Various studies show that
intoxicated people no longer
have the prerequisite processing skills to attend to all of the
multiple cues involved in
social behaviour (Streufert, Pogash, & Gingrich, 1993) and seek
cognitive closure (Lange,
2002).
In our study on perceived attractiveness, two hypotheses were
possible. First, alcohol
could lead to a general increase of perceived attractiveness,
because being attractive is a
salient feature of the self. Second, alcohol could produce more
polarized responses such
that attractive people would judge themselves even more
attractive, whereas unattractive
people would judge themselves as even less attractive.
Overview of present research
The present research investigates the effects of alcohol
consumption on self-perceived
attractiveness. In Study 1, carried out in a barroom, we analyse
the relationship between
an objective measure of intoxication (i.e., breathalyser reading)
and self-perceived
attractiveness. Study 2, an experimental study, clarifies the
causal link between alcohol
consumption and self-perceived attractiveness using a balanced
placebo design (Marlatt
& Rohsenow, 1980), which allows one to separate the
pharmacological effects of alcohol
from the psychological effects of alcohol. In Study 2, objective
measure of attractiveness
were also obtained by independent raters to determine whether
the effects of alcohol
consumption on self-perceived attractiveness are grounded in
reality, or whether they
are simply an illusion of the drinker.
STUDY 1
Study 1 provided an initial test of the hypothesis that
intoxicated people think they
are more attractive than sober people do. One major strength of
Study 1 is that it was
conducted in a naturalistic setting – a barroom.
Method
Participants
Participants were 19 customers (63% males; Mage = 22.5, SD =
5.0, range = 19–40)
in a barroom in Grenoble, France. They received a lottery ticket
in exchange for their
voluntary participation.
Procedure
Participants rated how attractive, bright, original, and funny
they felt at the moment
(1 = not at all to 7 = extremely; Cronbach’s � = .71; M = 4.27,
SD = 1.11). Next, we
Alcohol and perceived attractiveness 227
estimated blood alcohol level (BAL) using a breathalyser
(Draeger 5100S; M = 0.34%,
SD = 0.38). A debriefing followed.
Results and Discussion
Because they were not normally distributed, BAL values were
transformed using a natural
log function. As expected, the higher the BAL, the more
attractive participants thought
they were, r = .56, p = .012.
These results are consistent with the hypothesis that intoxicated
people think they
are more attractive than sober people do. Because of the
correlational nature of Study
1, however, we cannot rule out the possibility that individuals
who think they are
attractive tend to drink more in barrooms, or that some third
factor is related to perceived
attractiveness and alcohol consumption.
Study 1 also does not allow one to determine whether it is the
actual consumption
of alcohol or the mere belief that one has consumed alcohol that
relates to perceived
attractiveness. In the real world it is impossible to separate the
pharmacological and
expectancy effects of alcohol, but in the laboratory it is possible
to separate them using a
balanced placebo design (Marlatt & Rohsenow, 1980). Study 2
was therefore carried
out to disentangle both possible origins of the alcohol-self-
perceived attractiveness
relationship.
Study 1 also did not allow us to test whether intoxicated
participants were, in fact,
more attractive. We wanted to conduct videotaped interviews
with barroom patrons,
and then show these interviews to independent judges, but this
was not possible. Study
2 also overcomes this weakness of Study 1.
STUDY 2
In Study 2, we experimentally tested the expectancy and
pharmacological effects of
alcohol consumption on self-evaluated attractiveness.
Participants drank a beverage that
contained or did not contain alcohol. Within each group, half
were told the beverage
contained alcohol and half were told it contained no alcohol.
Next, participants delivered
a message that was filmed, supposedly to be used in future
advertisements for the
beverage. After watching the filmed message, participants rated
how attractive, bright,
original, and funny they thought they were. We predicted that
alcohol consumption
would increase self-perceived attractiveness, as in Study 1.
However, we were unsure
whether this effect would be due to the pharmacological effects
of alcohol, the
expectancy effects of alcohol, or both.
As an objective measure of how attractive participants were,
independent judges,
blind to beverage conditions, also rated participants on the same
dimensions. Because
the judges were sober, we predicted that alcohol consumption
would be unrelated to
this objective measure of attractiveness.
Method
Participants
Participants were 94 French men. Three did not follow
instructions, and two in placebo
condition and three participants in anti-placebo condition
suspected a discrepancy
between what they were told concerning their beverage and
what they were actually
228 Laurent B�egue et al.
given. We therefore excluded them from the sample. Thus, the
final sample included
86 men (Mage = 27, SD = 7). Participants were recruited via
newspaper advertisements
for a taste-test study and were paid 14€ ($21) per hour. Men
who responded to the ads
were interviewed over the phone, ostensibly to determine if they
were allergic to any
foods, including alcohol. Potential at-risk drinkers were
identified by the CAGE screening
test for alcohol dependence (Beresford, Blow, Hill, Singer, &
Lucey, 1990), and were
excluded from the study.
Procedure
Participants were told the private research firm Stat-Food
(actually a bogus company)
was conducting a taste-test study at a community health centre.
Participants fasted from
food and drink (except water) for 3 hr prior to their scheduled
appointment (Millar,
Hammersley, & Finnigan, 1992). A physician verified that each
participant was healthy.
After informed consent was obtained, participants were
randomly assigned to
beverage conditions in a balanced placebo design. The balanced
placebo design is a
2 × 2 factorial design that crosses alcohol content (participants
drink a beverage that
contains either alcohol or no alcohol) with alcohol-related
expectancies (participants
are told that their beverage either contains or does not contain
alcohol). The major
strength of the balanced placebo design is that it allows
researchers to untangle the
pharmacological effects of alcohol from the expectancy effects
of alcohol.
Unfortunately, suspicion is often very high in the balanced
placebo design, as high
as 90% in some studies (Martin & Sayette, 1993). Three
different types of cues can make
participants suspicious: (1) internal cues (i.e., participants in
the placebo condition
do not feel intoxicated even though they are told their beverage
contains alcohol;
participants in the anti-placebo condition feel intoxicated even
though they are told
their beverage contains no alcohol); (2) gustative cues (i.e.,
participants in the placebo
condition expect to taste alcohol, but do not taste it;
participants in the anti-placebo
condition do not expect to taste alcohol, but they taste it), and
(3) instructional cues
(e.g., manipulation checks make participants question the actual
content of the beverage,
cover stories are not believable). In Study 2, as in our previous
research (e.g., Bègue
et al., 2009), we attempt to reduce suspicion by focusing on all
three cues. We handled
the issue of internal cues indirectly by using several distracting
tasks to divert participants’
attention away from their bodily sensations. Previous alcohol
research has shown that
distraction decreases the salience of interoceptive cues
(Rohsenow & Marlatt, 1981).
The issue of gustative cues was handled by a major change in
typical procedures used
in alcohol-related research. In the anti-placebo condition,
participants were told that
we were testing a new non-alcoholic beverage that tasted like
alcohol, for people who
appreciated the taste of alcohol but wished to avoid drinking
alcohol. In the placebo
group, we mixed a small quantity of alcohol in the beverage,
placed alcohol on the surface
of the beverage, and sprayed alcohol on the rim of the glass. We
handled the issue of
instructional cues by disguising the study as a taste-test study.
In addition to handling
these three cues, we also used people from the general
population as participants,
because they are far less suspicious about psychological studies
than college students
are.
Each participant was given three cold isovolemic glasses that
contained a cocktail of
grapefruit and grenadine cordial, mint, and lemon concentrate.
For half the participants,
the beverage contained 2.01 oz of pure alcohol to target a peak
BAL of 0.10 g/100 ml.
The dose was not adjusted, except when the participant’s weight
was more than 20 kg
Alcohol and perceived attractiveness 229
under or over the median weight (75 kg). Within each group,
half the participants were
told that the beverage contained alcohol (the equivalent of five
to six shots of vodka),
whereas the remaining participants were told that the beverage
contained no alcohol.
In the expected alcohol conditions, the rims of the glasses were
sprayed with alcohol
immediately prior to serving. The drinks were mixed by a
research assistant, allowing
the experimenter to be blind to beverage condition.
Participants were given 10 min to consume their beverage.
Next, they were given
5 min to write an advertising message that would allegedly be
used by the (bogus)
company Stat-Food to promote their products. Participants then
evaluated their drinks,
which took 15 additional minutes (giving time for alcohol
absorption for participants
who consumed an alcoholic beverage and distracting
participants who consumed a
placebo beverage from focusing on internal cues). Next,
participants delivered their
advertising message on a stage while a female experimenter
filmed them. After the
recording, participants viewed their advertising message and, as
in Study 1, rated how
attractive, bright, original, and funny they thought they were (1
= not at all to 7 =
extremely; Cronbach’s � = .70).
Participants then left the main room, were offered some food
and drink, and were
kept busy with various tasks. When their BAL was theoretically
near to 0, an experimenter
posing as the person in charge of the food evaluation agency
took them to another room
and asked various questions about the agency’s hostess and the
tasting experience. By
that pre-debriefing procedure, we expected to hinder the
participants’ propensity to
answer consistently with what another experimenter had
previously told them (see
Knight, Barbaree, & Boland, 1986 for a description of this
debriefing procedure). The
experimenter doing the debriefing pretended not to be informed
of what they had drunk
and the participants had simply to inform him at the beginning
of the interview (see
Knight et al., 1986). If there was a discrepancy between the
quantity of alcohol said to
be in the drink and what the participant reported in the
debriefing, or if the participant
expressed doubts about the content of the drink, he was
considered suspicious and
was discarded from the sample. Five participants were
discarded, two in the placebo
condition and three in anti-placebo condition.
When the manipulation verification phase was complete, each
participant received
a thorough debriefing. All participants agreed that the collected
data could be used for
research purposes. We then estimated BAL with a breath
alcohol testing device (Draeger
5100S). Once BAL was equal to 0.00, participants were
thanked, paid, and released from
the lab.
Validation of self-evaluations of attractiveness by independent
judges
To obtain an objective measure of how attractive speakers were,
an independent group
also evaluated the filmed messages. Judges were 22 university
students (36% males;
Mage = 20, SD = 3). Each judge evaluated the filmed messages
from all 86 participants.
The judges were blind to any information about the alcohol
consumption/expectancy
status of the participant. They used the same rating dimensions
and rating scales as
participants did. Judges rated whether the person in the filmed
performance was
attractive, bright, original, and funny (1 = not at all to 7 =
extremely; Cronbach’s
� = .95).
230 Laurent B�egue et al.
Results and Discussion
Self-evaluations
Data were analysed using a 2 (given alcohol vs. given no
alcohol) × 2 (expected alcohol
vs. expected no alcohol) ANOVA. Results showed that
participants who thought they had
consumed alcohol expressed more positive self-evaluations than
did those who thought
they had not consumed alcohol, Ms = 3.91 and 3.42,
respectively, F(1,85) = 4.03, p =
.04, d = 0.44. The main effect of alcohol content was non-
significant, and the interaction
between alcohol content and alcohol expectancy, were both non-
significant, F(1,82) =
2.46, p = .12, and F(1,82) = 1.38, p = .24, respectively. A
Levene’s test showed that
alcohol and non-alcohol group variances did not differ (p =
.55), which suggested that no
polarization effect of alcohol of self-perceived attractiveness
was observed. Descriptive
statistics are in Table 1. These results suggest that alcohol
related expectancies, but not
actual alcohol content, influenced self-evaluations of
attractiveness.
Validation of self-evaluations by independent judges
Judges’ ratings of speeches were analysed using a 2 (given
alcohol vs. given no alcohol) ×
2 (expected alcohol vs. expected no alcohol) ANOVA. No
significant effects were found.
These findings indicate that the boost in self-perceived
attractiveness experienced by
people who thought they were drunk was unrelated to the way
they were perceived
by independent raters. Judges blind to beverage condition gave
similar attractiveness
ratings to people who thought they were drunk and to people
who thought they were
sober, Ms = 3.51 and 3.45, respectively, F(1,85) = 0.09, p > .80,
d = 0.065. Descriptive
statistics are in Table 2.
Table 1. Self-perceived attractiveness as a function of alcohol
consumption and alcohol expectancy
Expected
Alcohol No alcohol
M SD M SD
Alcohol 3.96 1.33 3.42 1.12
No alcohol 3.86 1.00 3.09 1.11
Table 2. Judges evaluations of attractiveness as a function of
target’s alcohol consumption and alcohol
expected
Expected
Alcohol No alcohol
M SD M SD
Alcohol 3.61 1.13 3.55 0.87
No alcohol 3.40 0.78 3.35 0.73
Alcohol and perceived attractiveness 231
GENERAL DISCUSSION
Our results showed that when people drink alcohol, they
evaluate themselves as
more attractive (or at least, less unattractive), but this self-
perception appears to
be an illusion. When independent judges evaluate attractiveness,
the ratings are not
influenced by expected or actual alcohol consumption. Our use
of the balanced
placebo design in Study 2 showed that the boost in self-
perceived attractiveness
can be interpreted as a consequence of the activation of mental
representations
implicitly related to alcohol in long-term memory. These
findings are consistent with
dual-process alcohol models that propose that the mind may still
become ‘intoxi-
cated’ if people expect to consume alcohol, even if they do not
consume a single
drop (Moss & Albery, 2009). These results are consistent with
the hypothesis that
alcohol stimuli operate on implicit expectancies, which, in turn,
influence explicit
self-perception.
Our findings also indicate that alcohol-related expectancies lead
to a general
increase of perceived attractiveness. There was no evidence that
alcohol-related
expectancies decreased perceived attractiveness in unattractive
individuals. Indeed,
almost everyone thinks they are more attractive after they think
they have con-
sumed alcohol. Moreover, our analysis showed that alcohol and
non-alcohol group
variances did not differ, which suggested that no polarization
effect of alcohol of
self-perceived attractiveness was observed. In order to find such
a polarization, we
maybe should have introduced salient cues referring to body
self-esteem. According
to the alcohol myopia theory (Steele & Josephs, 1990), in such a
case, attractive
people could have perceived themselves as even more attractive,
whereas the re-
verse may have occurred with less attractive people. Future
research is needed
to clarify the interesting issue of polarization under the
physiological influence of
alcohol.
Our study has also indicated that the quantity of alcohol
ingested was not related
to self-perceived attractiveness. We may hypothesize that pre-
experimental individuals’
alcohol use and chronic self-representations should be further
investigated to understand
such a result. A within-subjects experiment could provide useful
information regarding
this issue.
Previous studies have shown that alcohol consumption increases
the attractiveness
of members of the opposite sex (Jones, Jones, Thomas, & Piper,
2003). Our studies
provide complementary results showing that the mere belief that
one has consumed
alcohol increases self-perceived attractiveness. This is an
important topic to deal with
because self-perceived attractiveness has been shown to
significantly influence intimate
interactions. For example, in one diary study it was observed
that people who thought
they were attractive had more intimate interactions of all types
than did those who
thought they were less attractive (Nezlek, 1999).
In summary, the present research shows that alcohol-related
expectancies can
significantly boost self-perceived attractiveness. However, the
perceived attractiveness
lies in the eyes of the ‘beer holder’ and is not shared by anyone
else.
Acknowledgement
We would like to thank the editor and three anonymous
reviewers for their insightful
comments and their very useful suggestions.
232 Laurent B�egue et al.
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234 Laurent B�egue et al.
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YO16XLCH05GRADERPS1HW_-
_University_Call_Center_13_Instructions.docx
Office 2016 – myitlab:grader – Instructions Excel Project
YO16_XL_CH05_GRADER_PS1_HW - University Call Center
1.3
Project Description:
The University’s call center needs a workbook developed that
will use data to analyze the performance of the call center. The
call center contacted your professor and she recommended you
for the task. The workbook will set up a variety of tools that
will help assess the efficiency of the center and its staff. Your
will develop a workbook for the call center manager that will
help with the center's data analysis.
Instructions:
For the purpose of grading the project you are required to
perform the following tasks:
Step Instructions Points Possible
1 Start Excel. Open the downloaded Excel file named
e03ch05_grader_h1_CallCenter.xlsx. Save the file with the
name e03_grader_h1_CallCenter_LastFirst, using your last and
first name. 0.000
2 On the Lists worksheet, create the following named ranges
to use within formulas:
A2:A6 as Department
A14:B18 as GradeScale
B9:H9 as DayofWeek
Select the range E1:I5, and create named ranges using the top
row as the range values. 4.000
3 Select the CallData worksheet. In cell A9, format the data
as an Excel table with headers using the current data set. Apply
White, Table Style Light 1.
In cell H9, type Issue as the field label.
In cell I9, type Grade as the field label.
In cell J9, type Weekday as the field label.
Note, depending upon the Office version used, the table style
name may be Table Style Light 1. 9.000
4 On the CallData worksheet, select range A9:J128, and then
name the entire data set, including the labels, as CallDataAll.
Next, create named ranges using the top row as the range
values.
6.000
5 In cell H10, enter an INDEX function that will use a
nested INDIRECT reference to the Dept named range listed in
column C (C10), and use the Reason field in column B (B10) as
the row number to return for the department name in the
referenced named range.
Nest the function inside an IF function so that issues currently
displaying as a 0 will display as a blank cell. Resize the column
width as needed. 4.000
6 In cell I10, enter a VLOOKUP function that will convert
the Satisfaction Rating to a grade found in the second column of
the GradeScale named range. The formula is not looking for an
exact match.
4.000
7 In cell J10, enter an INDEX function that will convert the
Call Day to the actual weekday found in row 1 of the
DayofWeek named range. Resize the column width as needed.
4.000
8 On the CallData worksheet:
In cell C2, type Public_Affairs
In cell G2, type Y
Run an advanced filter on the table data set using the criteria
range A1:J2. 2.000
9 On the CallCenterReport worksheet, add formulas that will
summarize the issues for the department entered in cell B3.
In cell B6, add an INDEX function that will use an INDIRECT
function to retrieve the department issue list for the department
listed in cell B3. Use an absolute reference to B3, and then use
a relative cell reference to A6 as the row_num argument. Copy
the formula down to cell B9. 4.000
10 In cell C6, add a COUNTIFS function that will count the
number of departments on the CallData worksheet. Use the Dept
named range as criteria_range1, and then use an absolute
reference to B3 as criteria1. Use the Reason named range as
criteria_range2, and then use cell A6 as criteria2. Copy the
formula down to cell C9. 4.000
11 In cell D6, add a COUNTIFS function that will count the
number of calls coming from the department listed in B3. Use
the Dept named range as criteria_range1, and then use an
absolute reference to B3 as criteria1. Use the Reason named
range as criteria_range2, and then use cell A6 as criteria2. Use
the On_Hold named range as criteria_range3, and then use "Y"
as criteria3. Copy the formula down to cell D9. 4.000
12 In cell E6, add an IF statement with a nested AND that will
enter a status notice. If the number of calls on issue in cell C6
is greater than 3 and the number of calls on hold in cell D6 is
greater than 2, then "Check Hold Issue" should display.
Otherwise, nothing should display. Copy the formula down to
cell E9. 4.000
13 In cell B12, add an AVERAGEIF function that will find
the average call length for the Dept named range and the criteria
specified in cell A12.
In cell C12, add a COUNTIF function that will count the
number of calls for the Dept named range and the criteria
specified in cell A12.
8.000
14 In cell D12, add a formula that sums two COUNTIFS
formulas. The first COUNTIFS will count the number of calls
associated with the Dept named range and criteria specified in
cell A12 that received a grade F, and the second COUNTIFS
will do the same for grade D. 4.000
15 In cell E12, add an IF statement using a nested OR
function that will return any notes associated with the issue. If
there are more than 10 issues reported with a grade below a C in
cell D12, or when the number of scores less than C divided by
the total calls in cell C12 is greater than 50%, then "Explore
Issues" should display. Otherwise, the result will be blank.
Copy the formulas in B12:E12 down through row B16:E16.
4.000
16 In cell H11, add a MAX function that will show the
maximum call length minutes using the Call_Length named
range.
In cell H12, add an INDEX function that will use the Dept
named range as the array associated with a MATCH function to
determine the lookup array for the longest call referenced in
H11 from the Call_Length named range with an exact match.
8.000
17 In cell H13, add an INDEX function that will pull the
satisfaction rating associated with a MATCH function to
determine the lookup array for the longest call referenced in
H11 from the Call_Length range with an exact match. 4.000
18 On the CallCenterReport worksheet, in cell G19, type Y.
In cell J19, type Friday. Name the range A18:J19 Call_Criteria.
In cell B22, add a DCOUNT function for the CallDataAll
database to find the count of the satisfaction rating currently
listed in cell B21 using the Call_Criteria named range. 7.000
19 In B23:B26, add database functions that find the
DAVERAGE (B23), DSUM (B24), DMAX (B25), and DMIN
(B26) for the CallDataAll named range. Use named ranges in
the formulas.
Select the cell range B22:B26, and then copy the formulas to
column C.16.000
20 Save the workbook, exit Excel, and then submit your file
as directed by your instructor. 0.000
Total Points 100.000
Updated: 10/17/2017 1 Current_Instruction.docx
li_e03ch05_grader_h1_CallCenter.xlsx
CallDataCall HourReasonDeptCall LengthSatisfaction
RatingCall DayOn HoldIssueGradeWeekdayCall
HourReasonDeptCall LengthSatisfaction RatingCall DayOn
Hold82Accounting64.54Y161Public_Affairs6.73.75Y152Accou
nting5.55.91N31Public_Affairs3.79.22N211Admissions6.55.91
N153Public_Affairs8.863N221Human_Resources6.36.44N122A
dmissions27.22Y193Accounting5.47.66N151Financial_Aid5.94.
25Y191Public_Affairs3.39.23N142Accounting4.95.13N124Publ
ic_Affairs45.95N202Public_Affairs4.38.22N142Public_Affairs5
.36.75N112Public_Affairs5.16.85N151Admissions3.56.52Y161
Admissions5.48.46N102Public_Affairs3.66.85Y152Admissions7
.24.27Y12Public_Affairs3.39.97N93Admissions6.38.36N132Pu
blic_Affairs2.66.54Y203Admissions7.26.65N172Admissions1.8
7.52N111Admissions2.58.31N142Admissions4.76.62N173Publi
c_Affairs7.65.33N211Financial_Aid5.75.47Y161Public_Affairs
36.75Y21Admissions3.79.44N131Accounting1.57.81N113Publi
c_Affairs3.39.31N183Admissions4.45.45Y202Accounting541Y2
32Public_Affairs3.283Y81Public_Affairs4.54.95Y82Admissions
8.14.14Y51Human_Resources6.56.24N211Public_Affairs5.78.5
6N202Admissions4.55.67N193Admissions4.892N41Admissions
5.98.24N222Admissions4.44.57Y201Public_Affairs3.29.47N203
Admissions43.83Y164Financial_Aid4.96.52N111Public_Affairs
5.76.25Y72Public_Affairs59.95N122Public_Affairs4.68.84N161
Financial_Aid3.58.31N202Public_Affairs5.77.11N144Admissio
ns46.12N121Admissions3.19.65N62Admissions3.5107N172Ad
missions2.78.11N212Human_Resources557Y64Admissions2.77.
73N202Public_Affairs6.16.76N201Admissions64.41Y222Public
_Affairs4.78.13N31Public_Affairs5.354Y91Admissions3.48.96
N132Accounting4.96.32Y231Accounting5.57.23N242Admission
s4.57.13N103Admissions7.33.86Y204Human_Resources4.56.51
N93Human_Resources5.84.92Y142Accounting4.27.63N111Hum
an_Resources3.8105N182Public_Affairs4.58.12N202Admission
s3.5102N62Accounting1.49.54N62Admissions3.8102N131Acco
unting4.56.12N211Accounting4.66.83N231Admissions4.56.65Y
101Admissions2.67.34Y191Public_Affairs6.37.71N133Admissi
ons1.38.84N182Human_Resources4.95.52N182Human_Resourc
es4.85.46Y122Accounting3.981N192Accounting6.86.64Y111Pu
blic_Affairs6.28.77N44Human_Resources56.22N243Human_Re
sources2.48.16N212Accounting6.864N123Human_Resources3.1
8.36N142Human_Resources3.27.41N143Admissions7.86.91N93
Admissions5.44.82N142Public_Affairs6.65.86Y123Admissions3
.58.65Y193Human_Resources5.77.23N41Public_Affairs6.36.55
N83Admissions8.366N72Human_Resources47.26N12Human_Re
sources4.87.74N111Accounting3.19.86N152Accounting54.63Y1
01Public_Affairs5.58.95N121Admissions5.257Y92Public_Affai
rs4.68.91N53Admissions2.27.31Y204Accounting6.17.86N241A
ccounting4.48.34N203Admissions64.75Y93Financial_Aid3.910
7N103Accounting5.27.22N142Accounting4.65.53N224Accounti
ng6.58.33N153Financial_Aid7.15.11Y24Financial_Aid6.36.67N
101Admissions4.58.54N21Admissions7.46.45N183Financial_Ai
d5.46.95N231Financial_Aid5.352Y
&F
ListsDepartmentPublic AffairsHuman
ResourcesAdmissionsAccountingFinancial AidPublic
Affairs1Frozen
screenBlackboardBannerBlackboardInternetHuman
Resources2VoicemailElectricalIntranetInternetBlackboardAdmi
ssions3OtherInternetBlackboardIntranetAccounting4IntranetInte
rnetFinancial AidDay of
WeekSundayMondayTuesdayWednesdayThursdayFridaySaturda
yFinancial AidSatisfaction RatingGrade0F4D6C8B9A+
&F
CallCenterReportCall Center ReportDepartmentFinancial_Aid
Your Office: Public_Affairs
Human_Resources
Admissions
Accounting
Financial_Aid
Student_LifeIssues# Calls on Issue# On
HoldStatus1234DepartmentAverage Call LengthTotal
CallsBelow CNotesLongest
CallPublic_AffairsDepartmentHuman_ResourcesScoreAdmissio
nsAccountingFinancial_AidCall HourReasonDeptCall
LengthSatisfaction RatingCall DayOn
HoldIssueGradeWeekdaySatisfaction RatingCall
LengthCountAverageSumMaxMin
&F

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‘Beauty is in the eye of the beer holder’ Peoplewho think t.docx

  • 1. ‘Beauty is in the eye of the beer holder’: People who think they are drunk also think they are attractive Laurent Bègue1∗ , Brad J. Bushman2,3, Oulmann Zerhouni1, Baptiste Subra4 and Medhi Ourabah5 1University of Grenoble 2, France 2The Ohio State University, Columbus, Ohio, USA 3VU University, Amsterdam, The Netherlands 4University of Paris Descartes, France 5University of Paris 8, Saint-Denis, France This research examines the role of alcohol consumption on self- perceived attractiveness. Study 1, carried out in a barroom (N = 19), showed that the more alcoholic drinks customers consumed, the more attractive they thought they were. In Study 2, 94 non- student participants in a bogus taste-test study were given either an alcoholic beverage (target BAL [blood alcohol level] = 0.10 g/100 ml) or a non- alcoholic beverage, with half of each group believing they had consumed alcohol and half believing they had not (balanced placebo design). After consuming beverages, they delivered a speech and rated how attractive, bright, original, and funny they thought they were. The speeches were videotaped and rated by 22 independent judges. Results showed that participants who thought they had consumed alcohol gave themselves more positive self-evaluations.
  • 2. However, ratings from independent judges showed that this boost in self-evaluation was unrelated to actual performance. ‘Beauty is in the eye of the beer holder’ —Kinky Friedman Alcohol has many consequences on social perception and relationships. After a drink, intoxicated people see members of the opposite sex through ‘beer goggles’, which makes them look especially attractive (Jones, Jones, Thomas, & Piper, 2003; Lyvers, Cholakians, Puorro, & Sundram, 2011; Neave, Tsang, & Heather, 2008). But alcohol can also influence self-perceptions. Previous research on alcohol and self- awareness has found that alcohol reduces self-awareness by inhibiting self-relevant encoding processes (Hull, Levenson, Young, & Sher, 1983). The purpose of the present research is to test the hypothesis ∗Correspondence should be addressed to Laurent Bègue, University of Grenoble 2, LIP, 1251, Av. Centrale, BP47, 38040 Grenoble, France (e-mail: [email protected]). DOI:10.1111/j.2044-8295.2012.02114.x British Journal of Psychology (2013), 104, 225–234 © 201 The British Psychological Society www.wileyonlinelibrary.com 225
  • 3. 2 that alcohol consumption increases self-perceived attractiveness. Whereas meta-analytic reviews indicate that alcohol consumption enhances mood and sexual arousal (Hull & Bond, 1986), the link between alcohol consumption and self- perceived attractiveness remains to be clarified and theoretically developed. In order to understand the link between alcohol and self- processes, we relied on the dual-process model of alcohol-related behaviour (Moss & Albery, 2009; see also Moss & Albery, 2010; Wiers & Stacy, 2010). This model suggests that although alcohol consumption disrupts cognitive controlled processes, the mind may still become ‘intoxicated’ even in the absence of alcohol consumption (Moss & Albery, 2009). For example, when people believe that they are intoxicated, they behave more aggressively (Bègue et al., 2009), and show more sexually disinhibited behaviours (Crowe & Georges, 1989). Various studies indicate that the effects of alcohol on human cognition and behaviour should distinguish pharmacological and social psychological consequences of alcohol consumption. In the field of sexual arousal, for example, a meta-analytic review indicated that alcohol consumption had a non-significant effect on sexual arousal, whereas the mere expectation of drinking alcohol significantly increased sexual arousal
  • 4. (Hull & Bond, 1986). From this perspective, behaviours that are disinhibited after drinking a placebo can be understood as a consequence of the activation of alcohol- related concepts in memory. In one study, the mere subliminal activation of alcohol- related concepts caused men to rate the faces of women as more sexually attractive (Friedman, McCarty, Forster, & Denzler, 2005). Drunkenness is thus not merely a physiological consequence of alcohol, but involves complex interactions of both limited processing capacities (myopia theory, see below) and chronically and temporarily activated mental representations that make certain patterns of responding more accessible (expectancy theory, see below). According to the dual-process model of the alcohol behaviour (Moss & Albery, 2009), a full understanding of alcohol effects has to integrate both pharmacological and extra-pharmacological consequences of alcohol on human cognition and behaviour. Expectancies are the first component of the model. They are considered as the result of learned associations between alcohol-related representations in memory. The sources of this associative process could be referred to as conditioning (Hull & Bond, 1986) or vicarious learning (Bandura, 1965). For example, content analyses show that media characters who drink alcohol are generally depicted as more attractive than those who do not drink alcohol (McIntosh, 1999). Hence, to the extent that people strongly endorse alcohol-
  • 5. self-enhancement expectancies, concepts of ‘alcohol’ and ‘attractiveness’ would be linked together in memory. According to alcohol expectancy theory, alcohol-related cues could implicitly activate alcohol-related expectancies, which could, in turn, affect social judgements and behaviours that are in line with these alcohol- related expectancies. The concept of alcohol expectancy is based on a semantic network model of memory (Collins & Quillian, 1969), which posits that concepts that frequently co-occur, or share a similar meaning, are stored close together in memory. When one concept is activated, other related concepts also become more accessible through a spreading activation process (Collins & Loftus, 1975). For instance, social knowledge regarding alcohol effects is automatically activated in memory during the natural course of perception, without awareness or intention. Knowledge activation, in turn, shapes and guides people’s impressions, judgements, feelings, and intentions without awareness that such influence is occurring (see Bargh & Erin, 2006; Bargh & Ferguson, 2000; Ferguson & Bargh, 2004). Another aspect of the dual-process model is related to the physiological consequences of alcohol consumption. According to the attention allocation model, alcohol has a 226 Laurent B�egue et al.
  • 6. ‘myopic’ or narrowing effect on attention (Giancola & Corman, 2007; Steele & Josephs, 1990), which causes people to focus attention on the most salient cues and to not pay attention to more subtle or distal cues. Alcohol myopia is therefore defined as a state of short-sightedness in which superficially understood, immediate aspects of experience have a disproportionate influence on behaviours and emotions (Steele & Josephs, 1990). Although a sober individual can consider a range of information more or less salient before responding to a social situation, an intoxicated individual will be less concerned with consideration distal in time and place because he will be captive of an impoverished version of reality in which the breadth, depth, and timeline of his understanding will be affected. Various studies show that intoxicated people no longer have the prerequisite processing skills to attend to all of the multiple cues involved in social behaviour (Streufert, Pogash, & Gingrich, 1993) and seek cognitive closure (Lange, 2002). In our study on perceived attractiveness, two hypotheses were possible. First, alcohol could lead to a general increase of perceived attractiveness, because being attractive is a salient feature of the self. Second, alcohol could produce more polarized responses such that attractive people would judge themselves even more attractive, whereas unattractive people would judge themselves as even less attractive.
  • 7. Overview of present research The present research investigates the effects of alcohol consumption on self-perceived attractiveness. In Study 1, carried out in a barroom, we analyse the relationship between an objective measure of intoxication (i.e., breathalyser reading) and self-perceived attractiveness. Study 2, an experimental study, clarifies the causal link between alcohol consumption and self-perceived attractiveness using a balanced placebo design (Marlatt & Rohsenow, 1980), which allows one to separate the pharmacological effects of alcohol from the psychological effects of alcohol. In Study 2, objective measure of attractiveness were also obtained by independent raters to determine whether the effects of alcohol consumption on self-perceived attractiveness are grounded in reality, or whether they are simply an illusion of the drinker. STUDY 1 Study 1 provided an initial test of the hypothesis that intoxicated people think they are more attractive than sober people do. One major strength of Study 1 is that it was conducted in a naturalistic setting – a barroom. Method Participants Participants were 19 customers (63% males; Mage = 22.5, SD = 5.0, range = 19–40) in a barroom in Grenoble, France. They received a lottery ticket in exchange for their voluntary participation.
  • 8. Procedure Participants rated how attractive, bright, original, and funny they felt at the moment (1 = not at all to 7 = extremely; Cronbach’s � = .71; M = 4.27, SD = 1.11). Next, we Alcohol and perceived attractiveness 227 estimated blood alcohol level (BAL) using a breathalyser (Draeger 5100S; M = 0.34%, SD = 0.38). A debriefing followed. Results and Discussion Because they were not normally distributed, BAL values were transformed using a natural log function. As expected, the higher the BAL, the more attractive participants thought they were, r = .56, p = .012. These results are consistent with the hypothesis that intoxicated people think they are more attractive than sober people do. Because of the correlational nature of Study 1, however, we cannot rule out the possibility that individuals who think they are attractive tend to drink more in barrooms, or that some third factor is related to perceived attractiveness and alcohol consumption. Study 1 also does not allow one to determine whether it is the actual consumption of alcohol or the mere belief that one has consumed alcohol that relates to perceived attractiveness. In the real world it is impossible to separate the
  • 9. pharmacological and expectancy effects of alcohol, but in the laboratory it is possible to separate them using a balanced placebo design (Marlatt & Rohsenow, 1980). Study 2 was therefore carried out to disentangle both possible origins of the alcohol-self- perceived attractiveness relationship. Study 1 also did not allow us to test whether intoxicated participants were, in fact, more attractive. We wanted to conduct videotaped interviews with barroom patrons, and then show these interviews to independent judges, but this was not possible. Study 2 also overcomes this weakness of Study 1. STUDY 2 In Study 2, we experimentally tested the expectancy and pharmacological effects of alcohol consumption on self-evaluated attractiveness. Participants drank a beverage that contained or did not contain alcohol. Within each group, half were told the beverage contained alcohol and half were told it contained no alcohol. Next, participants delivered a message that was filmed, supposedly to be used in future advertisements for the beverage. After watching the filmed message, participants rated how attractive, bright, original, and funny they thought they were. We predicted that alcohol consumption would increase self-perceived attractiveness, as in Study 1. However, we were unsure whether this effect would be due to the pharmacological effects of alcohol, the
  • 10. expectancy effects of alcohol, or both. As an objective measure of how attractive participants were, independent judges, blind to beverage conditions, also rated participants on the same dimensions. Because the judges were sober, we predicted that alcohol consumption would be unrelated to this objective measure of attractiveness. Method Participants Participants were 94 French men. Three did not follow instructions, and two in placebo condition and three participants in anti-placebo condition suspected a discrepancy between what they were told concerning their beverage and what they were actually 228 Laurent B�egue et al. given. We therefore excluded them from the sample. Thus, the final sample included 86 men (Mage = 27, SD = 7). Participants were recruited via newspaper advertisements for a taste-test study and were paid 14€ ($21) per hour. Men who responded to the ads were interviewed over the phone, ostensibly to determine if they were allergic to any foods, including alcohol. Potential at-risk drinkers were identified by the CAGE screening test for alcohol dependence (Beresford, Blow, Hill, Singer, & Lucey, 1990), and were excluded from the study.
  • 11. Procedure Participants were told the private research firm Stat-Food (actually a bogus company) was conducting a taste-test study at a community health centre. Participants fasted from food and drink (except water) for 3 hr prior to their scheduled appointment (Millar, Hammersley, & Finnigan, 1992). A physician verified that each participant was healthy. After informed consent was obtained, participants were randomly assigned to beverage conditions in a balanced placebo design. The balanced placebo design is a 2 × 2 factorial design that crosses alcohol content (participants drink a beverage that contains either alcohol or no alcohol) with alcohol-related expectancies (participants are told that their beverage either contains or does not contain alcohol). The major strength of the balanced placebo design is that it allows researchers to untangle the pharmacological effects of alcohol from the expectancy effects of alcohol. Unfortunately, suspicion is often very high in the balanced placebo design, as high as 90% in some studies (Martin & Sayette, 1993). Three different types of cues can make participants suspicious: (1) internal cues (i.e., participants in the placebo condition do not feel intoxicated even though they are told their beverage contains alcohol; participants in the anti-placebo condition feel intoxicated even though they are told
  • 12. their beverage contains no alcohol); (2) gustative cues (i.e., participants in the placebo condition expect to taste alcohol, but do not taste it; participants in the anti-placebo condition do not expect to taste alcohol, but they taste it), and (3) instructional cues (e.g., manipulation checks make participants question the actual content of the beverage, cover stories are not believable). In Study 2, as in our previous research (e.g., Bègue et al., 2009), we attempt to reduce suspicion by focusing on all three cues. We handled the issue of internal cues indirectly by using several distracting tasks to divert participants’ attention away from their bodily sensations. Previous alcohol research has shown that distraction decreases the salience of interoceptive cues (Rohsenow & Marlatt, 1981). The issue of gustative cues was handled by a major change in typical procedures used in alcohol-related research. In the anti-placebo condition, participants were told that we were testing a new non-alcoholic beverage that tasted like alcohol, for people who appreciated the taste of alcohol but wished to avoid drinking alcohol. In the placebo group, we mixed a small quantity of alcohol in the beverage, placed alcohol on the surface of the beverage, and sprayed alcohol on the rim of the glass. We handled the issue of instructional cues by disguising the study as a taste-test study. In addition to handling these three cues, we also used people from the general population as participants, because they are far less suspicious about psychological studies than college students
  • 13. are. Each participant was given three cold isovolemic glasses that contained a cocktail of grapefruit and grenadine cordial, mint, and lemon concentrate. For half the participants, the beverage contained 2.01 oz of pure alcohol to target a peak BAL of 0.10 g/100 ml. The dose was not adjusted, except when the participant’s weight was more than 20 kg Alcohol and perceived attractiveness 229 under or over the median weight (75 kg). Within each group, half the participants were told that the beverage contained alcohol (the equivalent of five to six shots of vodka), whereas the remaining participants were told that the beverage contained no alcohol. In the expected alcohol conditions, the rims of the glasses were sprayed with alcohol immediately prior to serving. The drinks were mixed by a research assistant, allowing the experimenter to be blind to beverage condition. Participants were given 10 min to consume their beverage. Next, they were given 5 min to write an advertising message that would allegedly be used by the (bogus) company Stat-Food to promote their products. Participants then evaluated their drinks, which took 15 additional minutes (giving time for alcohol absorption for participants who consumed an alcoholic beverage and distracting
  • 14. participants who consumed a placebo beverage from focusing on internal cues). Next, participants delivered their advertising message on a stage while a female experimenter filmed them. After the recording, participants viewed their advertising message and, as in Study 1, rated how attractive, bright, original, and funny they thought they were (1 = not at all to 7 = extremely; Cronbach’s � = .70). Participants then left the main room, were offered some food and drink, and were kept busy with various tasks. When their BAL was theoretically near to 0, an experimenter posing as the person in charge of the food evaluation agency took them to another room and asked various questions about the agency’s hostess and the tasting experience. By that pre-debriefing procedure, we expected to hinder the participants’ propensity to answer consistently with what another experimenter had previously told them (see Knight, Barbaree, & Boland, 1986 for a description of this debriefing procedure). The experimenter doing the debriefing pretended not to be informed of what they had drunk and the participants had simply to inform him at the beginning of the interview (see Knight et al., 1986). If there was a discrepancy between the quantity of alcohol said to be in the drink and what the participant reported in the debriefing, or if the participant expressed doubts about the content of the drink, he was considered suspicious and was discarded from the sample. Five participants were
  • 15. discarded, two in the placebo condition and three in anti-placebo condition. When the manipulation verification phase was complete, each participant received a thorough debriefing. All participants agreed that the collected data could be used for research purposes. We then estimated BAL with a breath alcohol testing device (Draeger 5100S). Once BAL was equal to 0.00, participants were thanked, paid, and released from the lab. Validation of self-evaluations of attractiveness by independent judges To obtain an objective measure of how attractive speakers were, an independent group also evaluated the filmed messages. Judges were 22 university students (36% males; Mage = 20, SD = 3). Each judge evaluated the filmed messages from all 86 participants. The judges were blind to any information about the alcohol consumption/expectancy status of the participant. They used the same rating dimensions and rating scales as participants did. Judges rated whether the person in the filmed performance was attractive, bright, original, and funny (1 = not at all to 7 = extremely; Cronbach’s � = .95). 230 Laurent B�egue et al. Results and Discussion
  • 16. Self-evaluations Data were analysed using a 2 (given alcohol vs. given no alcohol) × 2 (expected alcohol vs. expected no alcohol) ANOVA. Results showed that participants who thought they had consumed alcohol expressed more positive self-evaluations than did those who thought they had not consumed alcohol, Ms = 3.91 and 3.42, respectively, F(1,85) = 4.03, p = .04, d = 0.44. The main effect of alcohol content was non- significant, and the interaction between alcohol content and alcohol expectancy, were both non- significant, F(1,82) = 2.46, p = .12, and F(1,82) = 1.38, p = .24, respectively. A Levene’s test showed that alcohol and non-alcohol group variances did not differ (p = .55), which suggested that no polarization effect of alcohol of self-perceived attractiveness was observed. Descriptive statistics are in Table 1. These results suggest that alcohol related expectancies, but not actual alcohol content, influenced self-evaluations of attractiveness. Validation of self-evaluations by independent judges Judges’ ratings of speeches were analysed using a 2 (given alcohol vs. given no alcohol) × 2 (expected alcohol vs. expected no alcohol) ANOVA. No significant effects were found. These findings indicate that the boost in self-perceived attractiveness experienced by people who thought they were drunk was unrelated to the way they were perceived by independent raters. Judges blind to beverage condition gave similar attractiveness ratings to people who thought they were drunk and to people
  • 17. who thought they were sober, Ms = 3.51 and 3.45, respectively, F(1,85) = 0.09, p > .80, d = 0.065. Descriptive statistics are in Table 2. Table 1. Self-perceived attractiveness as a function of alcohol consumption and alcohol expectancy Expected Alcohol No alcohol M SD M SD Alcohol 3.96 1.33 3.42 1.12 No alcohol 3.86 1.00 3.09 1.11 Table 2. Judges evaluations of attractiveness as a function of target’s alcohol consumption and alcohol expected Expected Alcohol No alcohol M SD M SD Alcohol 3.61 1.13 3.55 0.87 No alcohol 3.40 0.78 3.35 0.73 Alcohol and perceived attractiveness 231 GENERAL DISCUSSION Our results showed that when people drink alcohol, they
  • 18. evaluate themselves as more attractive (or at least, less unattractive), but this self- perception appears to be an illusion. When independent judges evaluate attractiveness, the ratings are not influenced by expected or actual alcohol consumption. Our use of the balanced placebo design in Study 2 showed that the boost in self- perceived attractiveness can be interpreted as a consequence of the activation of mental representations implicitly related to alcohol in long-term memory. These findings are consistent with dual-process alcohol models that propose that the mind may still become ‘intoxi- cated’ if people expect to consume alcohol, even if they do not consume a single drop (Moss & Albery, 2009). These results are consistent with the hypothesis that alcohol stimuli operate on implicit expectancies, which, in turn, influence explicit self-perception. Our findings also indicate that alcohol-related expectancies lead to a general increase of perceived attractiveness. There was no evidence that alcohol-related expectancies decreased perceived attractiveness in unattractive individuals. Indeed, almost everyone thinks they are more attractive after they think they have con- sumed alcohol. Moreover, our analysis showed that alcohol and non-alcohol group variances did not differ, which suggested that no polarization effect of alcohol of self-perceived attractiveness was observed. In order to find such
  • 19. a polarization, we maybe should have introduced salient cues referring to body self-esteem. According to the alcohol myopia theory (Steele & Josephs, 1990), in such a case, attractive people could have perceived themselves as even more attractive, whereas the re- verse may have occurred with less attractive people. Future research is needed to clarify the interesting issue of polarization under the physiological influence of alcohol. Our study has also indicated that the quantity of alcohol ingested was not related to self-perceived attractiveness. We may hypothesize that pre- experimental individuals’ alcohol use and chronic self-representations should be further investigated to understand such a result. A within-subjects experiment could provide useful information regarding this issue. Previous studies have shown that alcohol consumption increases the attractiveness of members of the opposite sex (Jones, Jones, Thomas, & Piper, 2003). Our studies provide complementary results showing that the mere belief that one has consumed alcohol increases self-perceived attractiveness. This is an important topic to deal with because self-perceived attractiveness has been shown to significantly influence intimate interactions. For example, in one diary study it was observed that people who thought they were attractive had more intimate interactions of all types
  • 20. than did those who thought they were less attractive (Nezlek, 1999). In summary, the present research shows that alcohol-related expectancies can significantly boost self-perceived attractiveness. However, the perceived attractiveness lies in the eyes of the ‘beer holder’ and is not shared by anyone else. Acknowledgement We would like to thank the editor and three anonymous reviewers for their insightful comments and their very useful suggestions. 232 Laurent B�egue et al. References Bandura, A. (1965). Influence of models’ reinforcement contingencies on the acquisition of imitative responses. Journal of Abnormal and Social Psychology, 66 , 575–582. Bargh, J. A., & Erin, W. (2006). The automaticity of social life. Current Directions in Psychological Science, 15, 1–4. Bargh, J. A., & Ferguson, M. J. (2000). Beyond behaviorism: On the automaticity of higher mental processes. Psychological Bulletin, 6 , 925–945. Bègue, L., Subra, B., Arvers, P., Muller, D., Bricout, V., & Zorman, M. (2009). The message, not the
  • 21. bottle: Extrapharmacological effects of alcohol on aggression. Journal of Experimental Social Psychology, 45, 137–142. Beresford, T. P., Blow, F. C., Hill, E., Singer, K., & Lucey, M. R. (1990). Comparison of CAGE questionnaire and computer-assisted laboratory profiles in screening for covert alcoholism. Lancet, 336 , 482–485. Collins, A. M., & Loftus, E. F. (1975). Spreading activation theory of semantic processing. Psychological Review, 82, 407–428. Collins, A. M., & Quillian, M. R. (1969). Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Behavior, 8, 240–247. Crowe, L., & George, W. (1989). Alcohol and human sexuality: Review and integration. Psycho- logical Bulletin, 105, 374–386. Ferguson, M. J., & Bargh, J. A. (2004). How social perception can automatically influence behavior. Trends in Cognitive Sciences, 8, 33–39. Friedman, R. S., McCarty, D. M., Forster, J., & Denzler, M. (2005). Automatic effects of alcohol cues on sexual attraction. Addiction, 100, 672–681. Giancola, P. R., & Corman, M. D. (2007). Alcohol and aggression: A test of the attention- allocation model. Psychological Science, 18, 649–655. Hull, J. G., & Bond, C. F. (1986). The social and behavioral consequences of alcohol consumption
  • 22. and expectancy: A meta-analysis. Psychological Bulletin, 99, 347–360. Hull, J. G., Levenson, R. W., Young, R. D., & Sher, K. J. (1983). The self-awareness reducing effects of alcohol consumption. Journal of Personality and Social Psychology, 44, 461–473. Jones, B. T., Jones, B. C., Thomas, A. P., & Piper, J. (2003). Alcohol consumption increases attractiveness ratings of opposite sex faces: A possible third route to risky sex. Addiction, 98, 1069–1075. Knight, L. J., Barbaree, H. E., & Boland, F. J. (1986). Alcohol and the balanced-placebo design: The role of experimenter demands in expectancy. Journal of Abnormal Psychology, 95, 335–340. Lange, J. E. (2002). Alcohol’s effect on aggression identification: A two-channel theory. Psychology of Addictive Behaviors, 16 , 47–55. Lyvers, M., Cholakians, E., Puorro, M., & Sundram, S. (2011). Beer goggles: Blood alcohol con- centration in relation to attractiveness ratings for unfamiliar opposite sex faces in naturalistic settings. Journal of Social Psychology, 151, 105–112. Marlatt, G. A., & Rohsenow, D. J. (1980). Cognitive processes in alcohol use: Expectancy and the balanced placebo design. In N. Mello (Ed.), Advances in substance abuse (Vol. 1, pp. 159–199). Greenwich, CT: JAI Press. Martin, C., & Sayette, M. (1993). Experimental design in
  • 23. alcohol administration research: Limitations and alternatives in the manipulation of dosage-set. Journal of Studies on Alcohol, 54, 750–761. McIntosh, D. (1999). Nondrinkers in films from 1940 to 1989. Journal of Applied Social Psychology, 29(6), 1191–1199 Millar, K., Hammersley, R. H., & Finnigan, F. (1992). Reduction of alcohol-induced performance impairment by prior ingestion of food. British Journal of Psychology, 83, 261–278. Moss, A., & Albery, I. (2009). A dual-process model of the alcohol-behavior link for social drinking. Psychological Bulletin, 125, 516–530. Alcohol and perceived attractiveness 233 Moss, A. C., & Albery, I. P. (2010). Are alcohol expectancies associations, propositions, or elephants? A Reply to Wiers and Stacy. Psychological Bulletin, 136 , 17–20. Neave, N., Tsang, C., & Heather, N. (2008). Effects of alcohol and alcohol expectancy on perceptions of opposite-sex facial attractiveness in university students. Addiction Research & Theory, 16 , 359–368. Nezlek, J. B. (1999). Body image and day-to-day social interaction. Journal of Personality, 67, 793–817.
  • 24. Rohsenow, D. J., & Marlatt, G. A. (1981). The balanced placebo design: Methodological consider- ations. Addictive Behaviors, 6 , 107–122. Steele, C. M., & Josephs, R. A. (1990). Alcohol myopia: Its prized and dangerous effects. American Psychologist, 45, 921–933. Streufert, S., Pogash, R. M., & Gingrich, D. (1993). Alcohol and complex functioning. Journal of Applied Social Psychology, 23, 847–866. Wiers, R. W., & Stacy, A. W. (2010). Are alcohol expectancies associations? Comment on Moss & Albery (2009). Psychological Bulletin, 136(1), 12–16. Received 20 September 2011; revised version received 23 March 2012 234 Laurent B�egue et al. Copyright of British Journal of Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
  • 25. YO16XLCH05GRADERPS1HW_- _University_Call_Center_13_Instructions.docx Office 2016 – myitlab:grader – Instructions Excel Project YO16_XL_CH05_GRADER_PS1_HW - University Call Center 1.3 Project Description: The University’s call center needs a workbook developed that will use data to analyze the performance of the call center. The call center contacted your professor and she recommended you for the task. The workbook will set up a variety of tools that will help assess the efficiency of the center and its staff. Your will develop a workbook for the call center manager that will help with the center's data analysis. Instructions: For the purpose of grading the project you are required to perform the following tasks: Step Instructions Points Possible 1 Start Excel. Open the downloaded Excel file named e03ch05_grader_h1_CallCenter.xlsx. Save the file with the name e03_grader_h1_CallCenter_LastFirst, using your last and first name. 0.000 2 On the Lists worksheet, create the following named ranges to use within formulas: A2:A6 as Department A14:B18 as GradeScale B9:H9 as DayofWeek Select the range E1:I5, and create named ranges using the top row as the range values. 4.000 3 Select the CallData worksheet. In cell A9, format the data as an Excel table with headers using the current data set. Apply White, Table Style Light 1. In cell H9, type Issue as the field label. In cell I9, type Grade as the field label.
  • 26. In cell J9, type Weekday as the field label. Note, depending upon the Office version used, the table style name may be Table Style Light 1. 9.000 4 On the CallData worksheet, select range A9:J128, and then name the entire data set, including the labels, as CallDataAll. Next, create named ranges using the top row as the range values. 6.000 5 In cell H10, enter an INDEX function that will use a nested INDIRECT reference to the Dept named range listed in column C (C10), and use the Reason field in column B (B10) as the row number to return for the department name in the referenced named range. Nest the function inside an IF function so that issues currently displaying as a 0 will display as a blank cell. Resize the column width as needed. 4.000 6 In cell I10, enter a VLOOKUP function that will convert the Satisfaction Rating to a grade found in the second column of the GradeScale named range. The formula is not looking for an exact match. 4.000 7 In cell J10, enter an INDEX function that will convert the Call Day to the actual weekday found in row 1 of the DayofWeek named range. Resize the column width as needed. 4.000 8 On the CallData worksheet: In cell C2, type Public_Affairs In cell G2, type Y Run an advanced filter on the table data set using the criteria range A1:J2. 2.000 9 On the CallCenterReport worksheet, add formulas that will summarize the issues for the department entered in cell B3. In cell B6, add an INDEX function that will use an INDIRECT function to retrieve the department issue list for the department
  • 27. listed in cell B3. Use an absolute reference to B3, and then use a relative cell reference to A6 as the row_num argument. Copy the formula down to cell B9. 4.000 10 In cell C6, add a COUNTIFS function that will count the number of departments on the CallData worksheet. Use the Dept named range as criteria_range1, and then use an absolute reference to B3 as criteria1. Use the Reason named range as criteria_range2, and then use cell A6 as criteria2. Copy the formula down to cell C9. 4.000 11 In cell D6, add a COUNTIFS function that will count the number of calls coming from the department listed in B3. Use the Dept named range as criteria_range1, and then use an absolute reference to B3 as criteria1. Use the Reason named range as criteria_range2, and then use cell A6 as criteria2. Use the On_Hold named range as criteria_range3, and then use "Y" as criteria3. Copy the formula down to cell D9. 4.000 12 In cell E6, add an IF statement with a nested AND that will enter a status notice. If the number of calls on issue in cell C6 is greater than 3 and the number of calls on hold in cell D6 is greater than 2, then "Check Hold Issue" should display. Otherwise, nothing should display. Copy the formula down to cell E9. 4.000 13 In cell B12, add an AVERAGEIF function that will find the average call length for the Dept named range and the criteria specified in cell A12. In cell C12, add a COUNTIF function that will count the number of calls for the Dept named range and the criteria specified in cell A12. 8.000 14 In cell D12, add a formula that sums two COUNTIFS formulas. The first COUNTIFS will count the number of calls associated with the Dept named range and criteria specified in cell A12 that received a grade F, and the second COUNTIFS will do the same for grade D. 4.000 15 In cell E12, add an IF statement using a nested OR
  • 28. function that will return any notes associated with the issue. If there are more than 10 issues reported with a grade below a C in cell D12, or when the number of scores less than C divided by the total calls in cell C12 is greater than 50%, then "Explore Issues" should display. Otherwise, the result will be blank. Copy the formulas in B12:E12 down through row B16:E16. 4.000 16 In cell H11, add a MAX function that will show the maximum call length minutes using the Call_Length named range. In cell H12, add an INDEX function that will use the Dept named range as the array associated with a MATCH function to determine the lookup array for the longest call referenced in H11 from the Call_Length named range with an exact match. 8.000 17 In cell H13, add an INDEX function that will pull the satisfaction rating associated with a MATCH function to determine the lookup array for the longest call referenced in H11 from the Call_Length range with an exact match. 4.000 18 On the CallCenterReport worksheet, in cell G19, type Y. In cell J19, type Friday. Name the range A18:J19 Call_Criteria. In cell B22, add a DCOUNT function for the CallDataAll database to find the count of the satisfaction rating currently listed in cell B21 using the Call_Criteria named range. 7.000 19 In B23:B26, add database functions that find the DAVERAGE (B23), DSUM (B24), DMAX (B25), and DMIN (B26) for the CallDataAll named range. Use named ranges in the formulas. Select the cell range B22:B26, and then copy the formulas to column C.16.000 20 Save the workbook, exit Excel, and then submit your file as directed by your instructor. 0.000 Total Points 100.000
  • 29. Updated: 10/17/2017 1 Current_Instruction.docx li_e03ch05_grader_h1_CallCenter.xlsx CallDataCall HourReasonDeptCall LengthSatisfaction RatingCall DayOn HoldIssueGradeWeekdayCall HourReasonDeptCall LengthSatisfaction RatingCall DayOn Hold82Accounting64.54Y161Public_Affairs6.73.75Y152Accou nting5.55.91N31Public_Affairs3.79.22N211Admissions6.55.91 N153Public_Affairs8.863N221Human_Resources6.36.44N122A dmissions27.22Y193Accounting5.47.66N151Financial_Aid5.94. 25Y191Public_Affairs3.39.23N142Accounting4.95.13N124Publ ic_Affairs45.95N202Public_Affairs4.38.22N142Public_Affairs5 .36.75N112Public_Affairs5.16.85N151Admissions3.56.52Y161 Admissions5.48.46N102Public_Affairs3.66.85Y152Admissions7 .24.27Y12Public_Affairs3.39.97N93Admissions6.38.36N132Pu blic_Affairs2.66.54Y203Admissions7.26.65N172Admissions1.8 7.52N111Admissions2.58.31N142Admissions4.76.62N173Publi c_Affairs7.65.33N211Financial_Aid5.75.47Y161Public_Affairs 36.75Y21Admissions3.79.44N131Accounting1.57.81N113Publi c_Affairs3.39.31N183Admissions4.45.45Y202Accounting541Y2 32Public_Affairs3.283Y81Public_Affairs4.54.95Y82Admissions 8.14.14Y51Human_Resources6.56.24N211Public_Affairs5.78.5 6N202Admissions4.55.67N193Admissions4.892N41Admissions 5.98.24N222Admissions4.44.57Y201Public_Affairs3.29.47N203 Admissions43.83Y164Financial_Aid4.96.52N111Public_Affairs 5.76.25Y72Public_Affairs59.95N122Public_Affairs4.68.84N161 Financial_Aid3.58.31N202Public_Affairs5.77.11N144Admissio ns46.12N121Admissions3.19.65N62Admissions3.5107N172Ad missions2.78.11N212Human_Resources557Y64Admissions2.77. 73N202Public_Affairs6.16.76N201Admissions64.41Y222Public _Affairs4.78.13N31Public_Affairs5.354Y91Admissions3.48.96 N132Accounting4.96.32Y231Accounting5.57.23N242Admission s4.57.13N103Admissions7.33.86Y204Human_Resources4.56.51 N93Human_Resources5.84.92Y142Accounting4.27.63N111Hum
  • 30. an_Resources3.8105N182Public_Affairs4.58.12N202Admission s3.5102N62Accounting1.49.54N62Admissions3.8102N131Acco unting4.56.12N211Accounting4.66.83N231Admissions4.56.65Y 101Admissions2.67.34Y191Public_Affairs6.37.71N133Admissi ons1.38.84N182Human_Resources4.95.52N182Human_Resourc es4.85.46Y122Accounting3.981N192Accounting6.86.64Y111Pu blic_Affairs6.28.77N44Human_Resources56.22N243Human_Re sources2.48.16N212Accounting6.864N123Human_Resources3.1 8.36N142Human_Resources3.27.41N143Admissions7.86.91N93 Admissions5.44.82N142Public_Affairs6.65.86Y123Admissions3 .58.65Y193Human_Resources5.77.23N41Public_Affairs6.36.55 N83Admissions8.366N72Human_Resources47.26N12Human_Re sources4.87.74N111Accounting3.19.86N152Accounting54.63Y1 01Public_Affairs5.58.95N121Admissions5.257Y92Public_Affai rs4.68.91N53Admissions2.27.31Y204Accounting6.17.86N241A ccounting4.48.34N203Admissions64.75Y93Financial_Aid3.910 7N103Accounting5.27.22N142Accounting4.65.53N224Accounti ng6.58.33N153Financial_Aid7.15.11Y24Financial_Aid6.36.67N 101Admissions4.58.54N21Admissions7.46.45N183Financial_Ai d5.46.95N231Financial_Aid5.352Y &F ListsDepartmentPublic AffairsHuman ResourcesAdmissionsAccountingFinancial AidPublic Affairs1Frozen screenBlackboardBannerBlackboardInternetHuman Resources2VoicemailElectricalIntranetInternetBlackboardAdmi ssions3OtherInternetBlackboardIntranetAccounting4IntranetInte rnetFinancial AidDay of WeekSundayMondayTuesdayWednesdayThursdayFridaySaturda yFinancial AidSatisfaction RatingGrade0F4D6C8B9A+ &F CallCenterReportCall Center ReportDepartmentFinancial_Aid
  • 31. Your Office: Public_Affairs Human_Resources Admissions Accounting Financial_Aid Student_LifeIssues# Calls on Issue# On HoldStatus1234DepartmentAverage Call LengthTotal CallsBelow CNotesLongest CallPublic_AffairsDepartmentHuman_ResourcesScoreAdmissio nsAccountingFinancial_AidCall HourReasonDeptCall LengthSatisfaction RatingCall DayOn HoldIssueGradeWeekdaySatisfaction RatingCall LengthCountAverageSumMaxMin &F