System ImplementationGantt Chart0Going Live (Software Installation.docx

System ImplementationGantt Chart0Going Live (Software
Installation)Freight Shipping Company LimitedToday's
Date:11/5/14Wednesday(vertical red line)Project Lead:[42]Start
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4/21/154/22/154/23/154/24/154/25/154/26/15WBS

Jon: Work Breakdown Structure
Level 1: 1, 2, 3, ...
Level 2: 1.1, 1.2, 1.3, ...
Level 3: 1.1.1, 1.1.2, 1.1.3, …
The WBS is automatically entered, but the formulas are
different for different levels.TasksSoftware SelectionStart
Jon: Start Date
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Duration (Days)
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minus the Start Date plus 1 day, so that a task starting and
ending on the same day has a duration of 1 day.% Complete
Jon: Percent Complete
Update the status of this task by entering the percent complete
(between 0% and 100%).Working Days
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planning work based upon the number of working days, adjust

the Duration until the desired # of working days is reached.Days
Complete
Jon: Calendar Days Complete
This column is calculated by multiplying the Duration by the
%Complete and rounding down to the nearest integer.Days
Remaining
Jon: Calendar Days Remaining
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from the Duration.
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Jon: Work Breakdown Structure
Level 1: 1, 2, 3, ...
Level 2: 1.1, 1.2, 1.3, ...
Level 3: 1.1.1, 1.1.2, 1.1.3, …
The WBS is automatically entered, but the formulas are
different for different levels.
Jon: Start Date
Enter the starting date for this task. To associate the start date
with the end of another task, enter a formula in the start date
that refers to the end date of that task.
Jon: End Date
The ending date is calculated by adding the Duration (calendar
days) to the Start date minus 1 day, because the task duration is
from the beginning of the Start day to the end of the End day.
Jon: Duration (Calendar Days)
Enter the number of calendar days for the given task. Refer to

the Working Days column or use a calendar to determine the
corresponding working days. The duration is from the beginning
of the Start date to the ending of the End Date.
When the duration is calculated, it is calculated as End Date
minus the Start Date plus 1 day, so that a task starting and
ending on the same day has a duration of 1 day.
Jon: Percent Complete
Update the status of this task by entering the percent complete
(between 0% and 100%).
Jon: Working Days
Counts the number of working days using the
NETWORKDAYS() formula, which excludes weekends. When
planning work based upon the number of working days, adjust
the Duration until the desired # of working days is reached.01 -
Sep - 1408 - Sep - 1415 - Sep - 1422 - Sep - 1429 - Sep - 1406 -
Oct - 1413 - Oct - 1420 - Oct - 1427 - Oct - 1403 - Nov - 1410 -
Nov - 1417 - Nov - 1424 - Nov - 1401 - Dec - 1408 - Dec - 1415
- Dec - 1422 - Dec - 1429 - Dec - 1405 - Jan - 1512 - Jan - 1519
- Jan - 1526 - Jan - 1502 - Feb - 1509 - Feb - 1516 - Feb - 1523
- Feb - 1502 - Mar - 1509 - Mar - 1516 - Mar - 1523 - Mar -
1530 - Mar - 1506 - Apr - 1513 - Apr - 1520 - Apr - 151Task
Category 1Consultation on the needs of the organization with
regard to software1/Sep/149/Sep/145100%332Days remaining
are Sundays which are not working daysThe reasons for
implementing a new software stipulated.Various softwares
identifiedVarious softwares identifiedVarious softwares
identifiedPresentationSystem selected and contact made with
the supplierSigning of contractSearch for software that meets
those needs9/Sep/1425/Sep/1417100%15150Needs for the new
system - tracking,shipping,receiving and inventory
management25th September 2014 - software selected0.1Sub
Task level 2Shortlisting of software
selected25/Sep/1429/Sep/145100%441This would then form the

expectations for the new software.0.2Sub Task level
2Presentation to
Management30/Sep/1430/Sep/141100%1100.2.1Sub Task level
3Selection of One system1/Oct/145/Oct/145100%4410.2.2Sub
Task level 3Contact with supplier
6/Oct/1410/Oct/145100%5500.3Sub Task level
2Negotiations11/Oct/1415/Oct/145100%4410.4Sub Task level
2Agreement and signing of
contract16/Oct/1420/Oct/145100%441Task Category 2Software
Implementation4/Nov/1428/Nov/142525%196190.1Sub Task
level 2Identifying the tasks for project
implementation4/Nov/148/Nov/14525%514This is the backbone
of the project and it needs to be conducted with great caution as
it will determine the success or failure of the software
implementationThe project lead will work closely with the
information technology and operations manger to assess the
needs and also formulate the tasks that shall be required to be
executed0.2Sub Task level 2Assessing the needs for the
software implementation10/Nov/1414/Nov/14525%514Fifteen
computers will be required for the project0.3Sub Task level
2Selecting members to carry out tests on the
software17/Nov/1421/Nov/14525%514Two members per
department must be selected of facilitate implementation0.4Sub
Task level 2Informing the Executive team on the
selection24/Nov/1428/Nov/14525%514Agreement on the
members of the team to spearhead testing and
relocation.Managers of each team will be informed on trhe
selection of members. Mangers will then agree or disagree with
the selection made and solutions on the same sought.1Task
Category 3Relocation and
Testing29/Nov/1422/Dec/14240%160241.1Sub Task level
2Relocation of the selected team
members29/Nov/144/Dec/1460%406Relocation of the selected
team members1.2Sub Task level 2Test scripts analyzed for
testing5/Dec/1410/Dec/1460%406Test scripts assessed and
procedures identified on how the testing will be carried out.

Which team will start and which one will finish or end the
testing process1.3Sub Task level 2Commencement of
tests11/Dec/1416/Dec/1460%406Testing begins each carried out
as per the test scripts1.4Sub Task level 2Collection and
interpretation of data after
testing17/Dec/1422/Dec/1460%406Each test done is well
documented with data being accurately registered and the same
analyzed to assess if it meets the needs of the
organization2Task Category 4Analysis and
Implementation23/Nov/1427/Jan/15640%470642.1Sub Task
level 2Bottlenecks
Identified23/Dec/1427/Dec/1450%405Identify the areas that
need to be changed and what needs to be done. This will be tied
to the expectations of the organization pertaining to the new
software2.2Sub Task level 2Changes that need to be made
highlighted28/Dec/141/Jan/1550%405Changes made to the
system with authorization and consultation with management on
the same. The supplier will be part of the consultation process
too.2.3Sub Task level 2System
modified2/Jan/156/Jan/1550%305Further modifications done to
the system if need be.2.4Sub Task level 2Final implementation
carried out6/Jan/1510/Jan/1550%405System is tested with the
new modifications in place and the final implementation takes
place. Computers are returned to the headquarters. The staff
also relocate back to the organization.
Copyright © The British Psychological Society
Reproduction in any form (including the internet) is prohibited
without prior permission from the Society
Effects of alcohol on the processing of social
threat-related stimuli in socially phobic women
Alexander L. Gerlach1*, Anke Schiller2,3, Cornelia Wild1

and Fred Rist1
1
University of Münster, Germany
2
Christoph Dornier Clinic, Germany
3
Christoph Dornier Foundation, Germany
Background. Social phobics are at a higher risk of developing
alcohol problems.
The mechanism promoting this association is not clear.
According to Sayette (1993b),
alcohol attenuates anxiety responses by disrupting initial
appraisal of threatening
stimuli. We used the emotional Stroop test and an implicit
memory test to investigate
whether alcohol hinders appraisal of social threat words in
patients diagnosed with
social phobia.
Procedure. Thirty-two women with social phobia (DSM-IV) and
32 female controls
performed an emotional Stroop test either after drinking alcohol
resulting in a blood
alcohol levels (BAL) of 0.6‰ or after drinking a non-alcoholic
beverage. The emotional
Stroop test contained social anxiety-related and neutral stimuli.
Implicit memory for
the words presented was tested with a word-stem completion
test.
Results. Without alcohol, both controls and socially-phobic

participants took longer
to name the colour of socially-threatening stimuli than of
neutral stimuli. Alcohol
levelled response latencies to the two stimulus categories only
in controls. Socially-
phobic participants responded more slowly to social anxiety-
related stimuli than to
neutral stimuli, irrespective of their BAL. In contrast to
controls, social phobics showed
an implicit memory bias for social threat words. This bias was
attenuated by alcohol.
Discussion. Alcohol disrupts appraisal of social anxiety-related
stimuli in controls
but not in social phobics; in these it hinders the consolidation of
memory. This also
suggests that social phobics experience similar anxiety with and
without alcohol, but
remember this experienced anxiety less precisely. This effect
might act as a reinforcer
for the use of alcohol for the purpose of self-medication in
future situations.
Epidemiological studies show that socially anxious people are
at a higher risk of abusing
alcohol or developing alcohol dependence (Schneier, Martin,
Liebowitz, Gorman, & Fyer,
1989; Allan, 1995; Holle, Heimberg, Sweet, & Holt, 1995;
Himle & Hill, 1991;
* Correspondence should be addressed to Alexander L. Gerlach,
WWU Münster, Department of Clinical Psychology, Fliednerstr.
21, 48149 Münster, Germany (e-mail: [email protected]).
The

British
Psychological
Society
279
British Journal of Clinical Psychology (2006), 45, 279–295
q 2006 The British Psychological Society
www.bpsjournals.co.uk
DOI:10.1348/014466505X49862
Page & Andrews, 1996; Nardi & Versiani, 1997; Clark &
Sayette, 1993; Stockwell &
Bolderston, 1987). A prospective study found a 2.3-fold
increased risk for alcohol abuse
and dependence in subclinical social phobia (Crum & Pratt,
2001). However, there are
also reports that people with a diagnosis of social phobia
consume less alcohol than
controls (Holle et al., 1995). This result cannot simply be
explained as a social desirability
effect, since social desirability and reported alcohol

consumption werenot correlated in a
different sample of patients with social phobia (Cox, Swinson,
Direnfeld, & Bourdeau,
1994). Thus, different processes may be at work as different
intensities of social anxiety
lead to the overlap of social phobia, alcohol abuse and
dependence.
A number of models attempt to explain the connection between
anxiety or stress
and alcohol use. Conger (1956) suggested that alcohol reduces
tension (or anxiety) and
that people consume alcohol to this effect. In line with this
suggestion, social phobia
patients consume more alcohol in a socially stressful situation
(public speaking), and
they report more attenuation of anxiety by drinking alcohol than
controls, especially if
they expected that alcohol would have such an effect (Abrams,
Kushner, Medina, &
Voight, 2001; Abrams, Kushner, Medina, & Voight, 2002).
These findings support a self-
medication theory of alcohol abuse. In this model, alcohol
serves as a readily-available
means to cope with anxiety, inadvertently leading to abuse and
dependence. In contrast

to this model, however, direct anxiety-reducing effects of
alcohol in socially anxious
people have not been found consistently. For example, a direct
effect of alcohol on
anxiety was lacking when social phobics were to give a speech
under the influence of
alcohol (Himle et al., 1999; Naftolowitz, Vaughn, Ranc, &
Tancer, 1994).
The tension-reduction theory as stated by Conger (1956) has not
remained
undisputed. According to Sayette’s (1993b) appraisal-disruption
model, ‘SRD
[stress-response dampening] occurs to the degree that alcohol
acts pharmacologically
to interfere with a person’s appraisal of stressful information’
(p. 463). Sayette suggests
that alcohol has this effect because it reduces the propensity of
relevant stimuli to
activate stressor-associated memories. In the context of social
phobia, these
considerations imply that biased processing of social phobia-
related stimuli is reduced
after the consumption of alcohol, since phobia-related memories
are not activated.
However, Sayette also proposed that in case of stressors which
are most readily or

automatically apprised, alcohol is much less likely to hinder
appraisal. This proposition
is based on the conviction that highly automatic cognitive
processes cannot easily be
disrupted. Accordingly, alcohol may not affect processing of
threat-related stimuli in
clinically-phobic subjects. Whereas this notion seems
reasonable, it has not yet been
tested directly in an information-processing paradigm.
Alternatively, Josephs and Steele (1990) Steele and Josephs
(1988) suggested that
alcohol will narrow the attention of an individual to immediate
and salient cues,
hindering the processing of more remote or less salient cues
(alcohol myopia theory):
only if a cue is present that is more salient or more easily
processed than the anxiety-
related cues, will alcohol alleviate anxiety by hindering the
processing of the anxiety-
related cue.
The processing of social phobia-related stimuli can be assessed
by various procedures.
The paradigm that is probably most often used in social phobia
and anxiety disorders is

the emotional Stroop test. Colour-naming latency to social
phobia-related words as
compared with neutral words was longer in a number of studies
in social phobia patients
(Amir, Freshman, & Foa, 2002; Amir et al., 1996; Becker,
Rinck, Margraf, & Roth, 2001;
Holle, Neely, & Heimberg, 1997; Lundh & Öst, 1996; Mattia,
Heimberg, & Hope, 1993;
McNeil et al., 1995; Orsillo, Lilienfeld, & Heimberg, 1994).
How can this slowed
Alexander L. Gerlach et al.280
processing be accounted for? The emotional Stroop effect can at
least partially be
attributed to increased activation of negative emotion-related
identity nodes, which
spreads automatically to related nodes ‘in some sort of semantic
recognition’ (White,
1996; p. 206). Sayette (1993b) argues that ‘alcohol disrupts
initial appraisal of stressful
information by constraining the spread of activation of

associated information previously
established in long-term memory’ ( p. 247). Thus, alcohol can
be expected to alter
performance in the emotional Stroop test.
The alcohol myopia theory states that alcohol influences
behaviour when
conflicting cues simultaneously influence behaviour ( Josephs &
Steele, 1990; Steele &
Josephs, 1988). Stroop interference is the result of a response
conflict (e.g. MacLeod,
1991). Thus, according to alcohol myopia theory, ingestion of
alcohol will increase the
emotional Stroop effect. Colour naming is the process that is
less automatic and less
salient compared with word reading. Since alcohol reduces
cognitive control, word
reading that interferes with colour naming should be processed
with priority and
consequently an increased interference should occur. Indeed,
Curtin and Fairchild
(2003) found an increase in error rate and a tendency for longer
reaction times after
ingestion of alcohol (0.08 per mille) in incongruent trials in the
colour word version of

the Stroop test.
Alcohol, in addition to potentially preventing appraisal of
information, also possesses
powerful amnesic effects (Weissenborn & Duka, 2000).
Generally, it is assumed that
alcohol impairs the encoding and storage of new information
(Sayette, 1993b).
However, with respect to acute alcohol effects on implicit
memory there is very little
and contradictory information. Hashtroudi et al. (1984) found
increased performance
on an implicit memory test after consumption of alcohol. Duka
et al. (2001) and Lister et
al. (1991) found that alcohol had a profound negative impact on
explicit memory but
left implicit memory intact.
During the emotional Stroop test, perceptual priming takes
place, resulting in
enhanced implicit memory for emotional stimuli of negative
valence ( Rajaram, Srinivas,
and Travers, 2001). Although information-processing models of
emotional disorders
suggest that anxious people (e.g. social phobics) have a memory

bias for threat-related
stimuli (e.g. Williams & Scott, 1988), empirical support for
such a memory bias is weak.
Specifically for social phobia, there is only limited evidence for
either an explicit or an
implicit memory bias for social threat stimuli (Coles &
Heimberg, 2002). Amir et al.
(2003) argued that methodological issues may have prevented
the detection of memory
biases for social threat material in social phobics in previous
studies. For example, Rapee
et al. (1994) failed to find an implicit memory bias for social
threat words in social
phobics. However, participants were tested not before 15–35
minutes after first
exposure to the stimulus material. In the Lundh and Öst study
(1997) that found an
implicit memory bias in non-generalized social phobics,
memory performance was
tested only 5 minutes after the first exposure. Graf and Mandler
(1984) argued
convincingly that the duration between acquisition and testing
is critical if implicit
memory is measured by word-stem completion. In two newer

studies using tests for
implicit memory other than word-stem completion, Amir and
colleagues demonstrated
implicit memory biases for social threat stimuli in social
phobics (Amir et al., 2003; Amir,
Foa, & Coles, 2000). Consequently, we additionally planned to
explore whether implicit
memory measured by word-stem completion for social phobia-
related words used in our
emotional Stroop test would be enhanced in social phobics and
whether this bias would
be affected by alcohol.
Effects of alcohol on processing social threat words 281
Based on these considerations we investigated whether
consumption of alcohol
attenuated the effect of social phobia-related words on colour-
naming latencies and also
reduced a possible implicit memory bias for such words in
social phobics. Since alcohol

has different effects on men and women (Eckardt et al., 1998),
only female participants
were tested. In a number of information-processing studies,
anxiety induction was
employed in order to activate social threat-relevant schemata. In
his 1993 paper, Sayette
argued that SRD is unlikely to occur when a stressor is
sufficiently threatening to
override appraisal deficits. Consequently, we decided not to use
an anxiety-inducing
procedure in order to test the appraisal disruption hypothesis
explicitly under
conditions of low threat. It is still likely that social phobics will
experience more
evaluation anxiety during the stress test than non-anxious
controls.
Method
Recruitment
Women who responded to newspaper advertisements seeking
women either with or
without fear of social situations and who successfully
completed a brief telephone
screening were invited to attend a diagnostic session for
approximately 2-hours.
This session included completion of several questionnaires and

the German Version of
the Structured Clinical Interview for the Diagnostic and
Statistical Manual of Mental
Disorders (SCID; Wittchen). Interviews were conducted by
clinicians with several years
of experience in treating social phobia patients and who were
trained in using the SCID.
Control participants received 60 or 40 German marks (DM),
depending on whether they
received alcohol or not. Socially-phobic participants were
offered the choice of the same
amount of money or participation in a 6-hour workshop dealing
with social phobia.
Exclusion criteria for participation in the study were current or
past drug or alcohol
abuse or dependence, complete abstinence from alcohol, colour-
blindness, use of
psychoactive medication, liver damage, and current or past
psychotic episodes.
Participants
Forty-two socially phobic patients and 36 control participants
took part in the
experiment. Due to equipment failure (malfunction of the throat
microphone), data for
only 32 socially phobic and 32 control participants were

available. We did not control
the phase of the menstrual cycle of our participants at the time
of testing. Table 1 shows
significant differences in the expected direction of social
phobia-related measures.
These were the German versions of the Fear of negative
evaluation scale (Vormbrock &
Neuser, 1983), the Social phobia scale (Stangier, Heidenreich,
Berardi, Golbs, & Hoyer,
1999), the Social interaction and anxiety scale (Stangier et al.,
1999), Drinking due to
social anxiety scale (‘Trinken wegen sozialer Angst’,
Heidenreich, Wagner, & Stangier,
2003), and the Blushing propensity scale (Leary & Meadows,
1991), the Beck
Depression Inventory (Hautzinger, Bailer, Worall, & Keller,
1994), and an Alcohol
Expectancy Questionnaire (Demmel & Hagen, 2002a). On the
Alcohol Expectancy
Questionnaire socially-phobic participants reported that they
expected more tension-
reduction and regulation of negative mood and more enhanced
socio-emotional
functioning due to alcohol than the control group. Finally, all
participants filled out

the German version of the Short Michigan Alcoholism
Screening Test for father and
mother (Demmel & Hagen, 2002b). Based on the cut-off score
of 6 as suggested by
Demmel and Hagen (2002b), the percentage of participants with
at least one parent
with alcohol problems was calculated.
All participants gave written informed consent after learning
about the experiment,
but prior to randomization. They were then randomized to either
the alcohol or the
orange juice condition. Thus, all participants agreed to
participate irrespective of
whether they would receive alcohol or not. The randomization
procedure resulted in
18 controls and 17 social phobics receiving alcohol, and 14
controls and 15 social
phobics receiving orange juice. Neither the two resulting social
phobic groups nor the

two control groups differed on any of the baseline variables.
Thus, the randomization
procedure was successful in creating equivalent groups.
Procedure
Once randomized, all participants were asked to eat a ‘light
meal’, specified in a
hand-out, approximately 3.5 hours before the start of the
experiment. They were also
asked to refrain from drinking anything containing caffeine
(coffee, tea, soft drinks)
during the 4 hours prior to the experiment, and not to drink
alcohol for 24 hours prior
to the experiment.
All participants were informed whether they would receive
alcohol or not before
coming to the laboratory. No attempt was made to deceive
participants about the nature
Table 1. Comparison of the social phobic and healthy
participants
Social phobics (N ¼ 32) Normal controls (N ¼ 32)
Age 32.5 (1.6) a 31.0 (1.6) a
% Single 75.0 a 84.4.a
Education (% $ high school graduation) 78.1 a 87.5.a
% Smokers 59.4 a 35.5 b

Beginning of social drinking (age) 17.2 (1.3) a 17.0 (1.2) a
Alcohol consumption (grams) during the
past week
56.9 (35.9) a 49.0 (30.2) a
Comorbid diagnosis (%) 10 (31.2) 0 (0)
G-FNE 63.8 (1.5) a 28.3 (1.5) b
BPS 49.1 (2.0) a 29.4 (2.0).b
BDI 19.9 (1.1) a 2.5 (1.1) b
ASI 33.5 (1.4) a 11.7 (1.4) b
SPS 36.6 (2.3) a 3.3 (2.3) b
SIAS 39.9 (1.6) a 12.1 (1.6) b
TWSA 17.4 (2.4) a 4.0 (2.4) b
Parental alcohol problems (%) 18.7 a 12.5 a
AEQ_KO 12.6 (0.5) a 14.2 (0.5) b
AEQ_SP 12.7 (0.4) a 14.0 (0.4) b
Note. Values enclosed in parentheses represent standard errors
where not otherwise noted.
G-FNE ¼ German version of the fear of negative evaluation
scale; BPS ¼ Blushing propensity scale;
BDI ¼ Beck Depression Inventory; ASI ¼ Anxiety Sensitivity
Index; SPS ¼ Social phobia scale;
SIAS ¼ Social avoidance and distress scale; TWSA ¼
‘Fragebogen Trinken wegen sozialer Angst’
[Drinking due to social anxiety scale]; AEQ_KO ¼ Alcohol
Expectancy Questionnaire, subscale
‘tension-reduction and regulation of negative mood’; AEQ_SP
¼ Alcohol Expectancy Questionnaire,
subscale ‘enhanced socio-emotional functioning’. Parental
alcohol problems were defined as a score
greater than 3 on the German version of the Short Michigan
Alcoholism Screening Test. Means for
specific questionnaires that do not share a common superscript
differ significantly in Mann–Whitney

U tests p , :001. Fisher exact tests were used for comparison of
percentages.
of the beverage they were about to get. Sayette (1993a) argues
convincingly that
appraisal disruption will only take place if a person is
pharmacologically sufficiently
intoxicated. Unfortunately, a full balanced placebo design
cannot be achieved
successfully if behaviourally-relevant alcohol doses are used. In
a thorough study by
Lyvers and Maltzman (1991), 90% of the participants that were
lead to believe that they
drank a non-alcoholic beverage but received alcohol (.0.5‰)
were able to sense the
intoxication resulting from drinking the alcohol. In a study by
Sayette et al. (1994) using
alcohol levels of 0.6‰, 94% of their subjects receiving alcohol
in the placebo condition
were not deceived.

When the participants receiving alcohol arrived on the test day,
a urine sample was
collected for pregnancy testing ( Hilary, Dolorgiet). None of the
participants tested
positive. Subsequently, their height and weight was measured.
Breath alcohol
concentrations were measured using a standard breathalyzer
with an accuracy of
^0.03 mg / L ( Dräger, Alkotester 7410). Test results for all
participants upon arrival
were 0.00‰. For participants receiving alcohol, the necessary
amount of alcohol based
on their weight and height was estimated following a version of
the Widmark formula
( Widmark, 1932), modified by Fisher et al. (1987), Kapur,
(1991) and Breslin et al.
(1997). We aimed for a blood alcohol concentration of 0.06%
based on findings that
people are able to perform the Stroop test without significant
performance deficits with
similar blood alcohol levels (BAL; Gustafson & Källmén,
1990a, 1990b).
The alcoholic beverage was one part vodka and two parts orange
juice, the non-
alcoholic beverage was juice only in comparable amounts.

Participants received their
respective beverages in three equal doses, each to be finished
within 5 minutes.
All participants were able to complete this procedure. No
participant reported nausea
or other feelings of being uncomfortable. At the end of the
experiment, participants
who had received alcohol either were given newspapers to read
until their BAL reached
less than 0.04‰ or they were fetched by their partners.
Presentation of the stimuli
ERTS software ( Beringer, 1994) was used to present the stimuli
and to measure
reaction times. Words were presented in a blocked format on a
computer screen: half
of the participants were first asked to name the colours of the
social phobia-related
words and then of the neutral words, whereas the other half of
the participants first
had to name the colours of the neutral words and then the
colours of the social
phobia-related words. Each word was presented individually.
Within blocks, word
order was randomized. Word presentation ended as soon as the
colour naming was

registered by a throat microphone. The colours were red, blue,
green, and yellow,
randomly chosen for each word presentation. After naming the
colour of a word there
was a 1-second interval before the next word was presented.
Participants were allowed
a maximum of 3 seconds to name the colour of a word, but no
participant needed that
much time.
Stimuli and measures
The emotional Stroop test was composed of 16 social phobia-
related words and 16
neutral words. Social phobia-related words and neutral words
were matched based on
word length and frequency of use in the German language.
Reaction times for colour
naming were measured with a throat microphone attached with
double-coated adhesive
electrode rings (Marquette Hellige). Estimates of mean reaction
times for each stimulus

class were calculated after elimination of values above or below
two standard deviations
(Ratcliff, 1993). Although the Stroop test is emotionally
demanding, participants rarely
make errors in naming the word colour. To check the prevalence
of errors, 11 socially
phobic and 10 control participants (13 under the influence of
alcohol) were selected
randomly and their errors were counted using a videotape of the
Stroop session. Only 31
errors were made out of the total of 2,016 trials that we
checked. There was no
difference in the number of errors between social phobics and
controls (Mann–Whitney
U tests: social phobia-related words Z ¼ 20:49, p ¼ :62; neutral
words: Z ¼ 0, p ¼ 1:0)
or between participants in the alcoholic or non-alcoholic
beverage group
(Mann–Whitney U tests: social phobia-related words Z ¼ 20:07,
p ¼ :94; neutral
words: Z ¼ 1:01, p ¼ :20).
Implicit memory was assessed with a word-stem completion
test. Participants were
asked to complete 32 three-letter word stems to the first word
that came to their mind,

without a time restriction. Of these 32 word stems, 16 word
stems could only be
completed to previously-presented social phobia-related words
and 16 word stems
could only be completed to previously-presented neutral words.
With the exception of
one neutral word (‘dringend’, English: urgent) and one social
phobia-related word
(‘peinlich’, English: embarrassing), all word stems could be
completed to more frequent
words other than the primed words. This was ensured using the
Corpus Search,
Management, and Analysis System (COSMAS; Belica,
Herberger, & al-Wadi, 1992). For the
results presented here, only words that were identical to the
ones presented during the
Stroop test were counted. However, more liberal scoring
including words that shared
the same root as the words from the emotional Stroop test did
not affect the pattern of
findings. Participants could achieve a maximum implicit
memory score of 16 for anxiety-
related and 16 for neutral stimuli.

In addition, we also assessed explicit memory for the words
employed in the Stroop
task. While the instructions for the Stroop task make it unlikely
that the participants will
remember many words explicitly, assessing explicit recollection
of the words by free-
recall will allow for the control of effects of explicit
recollection on the implicit memory
test. Presentation of the implicit and the explicit memory test
was counterbalanced.
We also measured anxiety state using 10-centimetre visual
analogue scales.
Participants were asked to rate how anxious they felt ‘right
now’ at baseline and after
completing the emotional Stroop test.
Timeline
After arrival, all participants were weighed. Participants in the
alcohol condition were
also tested for pregnancy. Then everybody was seated in the
experimenter room and the
first breath alcohol measurement (BAC 1) was taken. Then
participants were asked to
drink their respective beverages within 15 minutes (three cups
presented at 0, 5, and 10

minutes). After 5 additional minutes allowed for absorption, the
breath alcohol was
measured again (BAC 2). Then all participants performed the
Stroop test (5–6 minutes)
and the third breath alcohol measurement was taken (BAC 3)
and participants were
asked to report their amount of anxiety (SUDS 1). The two
memory tests were presented
in balanced order. Half of the participants were first asked to
perform the explicit
(5 minutes) and then the implicit memory test (5 minutes), half
of the participants were
asked to first perform the implicit and then the explicit memory
test. Finally, breath
alcohol was measured again (BAC 4) and the participants were
asked to report their
respective intensity of anxiety (SUDS 2).
Data analysis
Colour-naming reaction times were analyzed with repeated

measures ANOVAs/MANOVAs
with group (social phobics and controls) and condition (alcohol
vs. orange juice) as
between-subjects factors and category (anxiety stimuli vs.
neutral stimuli) as the repeated
measurement factor. Planned comparisons were calculated
between social phobics and
controls. An alpha level of 0.05 was used for all statistical tests.
F-statistics are misleading
when the means are correlated with variances across cells of the
design (Winer, Brown, &
Michels, 1991). Therefore, for the comparison of self-report
measures of social phobics and
controls, Mann–Whitney U tests were employed.
Results
Blood alcohol concentration and anxiety state
Figure 1 shows that the social phobic and the control
participants who had received
alcohol reached comparable levels of BAL. There was no
difference in blood alcohol
concentration between the two groups (F ¼ 1:0, p ¼ :4).
Socially-phobic participants
reported significantly more anxiety than controls, Fð1; 60Þ ¼
17:64, p , :001
(social phobics with alcohol after Stroop test: M ¼ 2:5 (SE:

0.4); after the two memory
tests: M ¼ 3:1 (SE: 0.4), social phobics without alcohol after
Stroop test: M ¼ 3:4 (SE:
0.4); after the two memory tests: M ¼ 3:0 (SE: 0.4), controls
with alcohol after the
Stroop test M ¼ 1:3 (SE: 0.4), after the two memory tests: M ¼
1:1 (SE: 0.4); controls
without alcohol after the Stroop test M ¼ 1:6 (SE: 0.4), after
the two memory tests:
Figure 1. Blood alcohol concentration in participants that
received alcohol.
Note. BAC 1 ¼ blood alcohol concentration at baseline, BAC 2
¼ blood alcohol concentration
5 minutes after last drink, BAC 3 ¼ blood alcohol concentration
after Stroop test, BAC 4 ¼ blood
alcohol concentration after memory test at the end of the
session.
M ¼ 1:3 (SE: 0.5). However, neither consuming alcohol nor
performing the emotional
Stroop test influenced self-report anxiety level. There was
neither an effect of time
(post-Stroop test vs. post-memory tests), condition (alcohol vs.

no alcohol), nor an
interaction effect of Group £ Time £ Condition, Fð1; 60Þ # 0:8.
Emotional Stroop test
The analysis of reaction times with group (social phobics vs.
controls) and condition
(alcohol vs. no alcohol) as a between-subjects factor and
category (anxiety stimuli vs.
neutral stimuli) as a within-subjects factor resulted in a
significant interaction
Group £ Condition £ Category, Fð1; 60Þ ¼ 4:02, p ¼ :049.
Also, a significant main
effect of category Fð1; 60Þ ¼ 8:57, p ¼ :005 was found, but no
main effect of group
or condition or any two-way interaction effects were (see Fig. 2
for an illustration
of the significant effects). The three-way interaction was due to
an interaction of
Condition £ Category in the control group, Fð1; 60Þ ¼ 4:92, p
¼ :030, but not in the
social phobia group Fð1; 60Þ ¼ 0:37, p ¼ :54). Accordingly,
differential effects of alcohol
on colour-naming latencies were confined to the control group
without alcohol. Controls
responded more slowly to anxiety stimuli than to neutral
stimuli, Fð1; 60Þ ¼ 5:08,
p ¼ :028, as did the social phobics. With alcohol, colour-
naming latencies to anxiety-
related words in controls were reduced to the level of colour-

naming latencies for neutral
words, Fð1; 60Þ ¼ 0:63, p ¼ :42. In contrast, the social phobia
patients took longer to
name the colour of the anxiety stimuli compared with neutral
stimuli, irrespective of the
beverage consumed, Fð1; 60Þ ¼ 8:89, p ¼ :004). Thus, social
phobics show an
attentional bias, but not more so than controls. Alcohol reduces
this bias in controls,
but not in patients.
An index for the observed interference effect was formed by
subtracting the colour-
naming latency for neutral words from the colour-naming
latency for anxiety-related
words. This index was significantly correlated (Spearman rank
correlation, p , :05)
with the SPS (r ¼ :26), the SIAS (r ¼ :27), and the TWSA (r ¼
:27). The correlation with
the German FNE was not significant (r ¼ :17). Neither during
baseline nor following the
Stroop test did interference correlate with anxiety state (r ¼
2:06 and r ¼ :01).
Finally, alcohol expectancy as measured with the AEQ-KO and
AEQ-SP was also not
Figure 2. Emotional Stroop interference depending on stimuli
and diagnostic group.

correlated with Stroop interference, neither in the social phobic
group (r ¼ :08 AEQ-
KO, r ¼ 2:1 AEQ-SP), nor in the control group (AEQ-KO: r ,
2:01, AEQSP: r ¼ 2:1).
Explicit memory test
As expected, all participants did poorly on the free-recall test.
The average number of
correctly-remembered social threat words was 1.8 (SE ¼ 1:19)
and 0.19 (SE ¼ 0:06) for
neutral words. That is, 27 participants per group (social phobics
and controls) did not
remember one single neutral word, four participants in each
group remembered one
word and one participant in each group remembered two neutral
words. Seven social
phobics and six controls remembered no social threat-related
word, 11 social phobics
and 10 controls remembered one social threat-related word, five
social phobics and six
controls remembered two social threat-related words, and nine
social phobics and 10

controls remembered three or more social threat words. Based
on these low rates no
statistical analyses were computed.
Implicit memory test
The ANOVA of the implicit memory scores with category
(anxiety stimuli vs. neutral
stimuli) as a within-subjects factor, group (social phobics vs.
controls) and condition
(alcohol vs. no alcohol) as between-subjects factors, resulted in
a significant effect
of category, Fð1; 60Þ ¼ 5:93, p , :05, and a trend for group,
Fð1; 60Þ ¼ 3:72, p ¼ :06,
which was moderated by a Group £ Category effect, Fð1; 60Þ ¼
5:43, p , :05. (see
Fig. 3 for an illustration of the significant effects). The
socially-phobic participants
remembered more socially negative words than neutral words,
Fð1; 60Þ ¼ 11:42,
p , :05. Furthermore, social phobics remembered more social
threat words than
controls, Fð1; 60Þ ¼ 7:01, p , :05. There were no differences
between social phobics
and control participants on implicit memory for neutral words,
Fð1; 60Þ ¼ 0:54, ns.
In addition, we found a tendency for an interaction of Group £
Condition £
Category, Fð1; 60Þ ¼ 3:04, p # :09. In order to evaluate the
tendency for a three-fold
interaction, we analyzed the Condition £ Category interaction in

the social phobia
group only and found a significant effect, Fð1; 60Þ ¼ 4:54, p ,
:05. Hence, social
Figure 3. Implicit memory values depending on stimuli and
diagnostic group.
phobics showed a significantly lesser implicit memory bias for
social threat words if they
were drinking alcohol. The implicit memory bias for social
threat (memory scores for
anxiety-related words minus memory score for neutral words)
was significantly
correlated (Spearman–Brown) with the SIAS, r ¼ :31, tð62Þ ¼
2:5, p , :01, and the SPS,
r ¼ :29, tð62Þ ¼ 2:1. There was also a trend for the TWSA, r ¼
:27, tð62Þ ¼ 1:8, p , :08,
and the German FNE, r ¼ :21, to be correlated with implicit
memory bias for social
threat words. Thus, a higher self-rating on measures of social
anxiety tended to be
related to better retention of social anxiety-related words.

Discussion
We used an emotional Stroop procedure with neutral and social
anxiety-related word
stimuli and an implicit memory test for these words to assess
the effect of alcohol on
cognitive processing in social phobics as compared with non-
anxious controls.
We hypothesized an information-processing bias in social
phobics, evident in longer
colour-naming latencies and a better implicit memory for social
threat words. Based on
functional analysis, considerations of the link between social
phobia and alcohol
consumption and on the core proposition of Sayette’s appraisal
disruption theory, we
further expected that alcohol would have a stronger effect on
social phobics in the sense
of reducing both the interference produced by anxiety stimuli
and their enhanced
memory effect. Alternative expectations were derived from the
alcohol myopia theory,
namely that alcohol should increase Stroop interference. In line
with these
considerations, social phobia patients did take longer to name
the colour of anxiety

words than of neutral words, and they remembered more anxiety
words than the
controls. But contrary to our expectation, alcohol attenuated the
effect of anxiety-
related word stimuli on colour-naming latencies only in non-
anxious controls, but not in
social phobics, and it did not affect memory performance.
Hence, we disconfirmed the
alcohol myopia theory and at least partially failed to confirm
the appraisal disruption
theory as applied to social phobia patients.
Anxiety stimuli provoked an interference effect in colour-
naming responses, in line
with the literature on emotional Stroop effects. But why did this
interference effect
occur in controls also, and why was the effect not greater in
social phobics than in
controls? Interference effects for social threat words in non-
anxious controls have been
repeatedly reported (Amir et al., 1996; Mattia et al., 1993).
Emotionally-salient words
generally cause more interference than neutral words (MacLeod,
1991), and it seems
reasonable to assume that social threat words also qualify as
emotionally-salient words

for non-anxious controls. Also, only the anxiety-related words
were semantically related,
whereas the neutral words were not. In a blocked presentation,
this could result in
increased interference (Waters, Sayette, & Wertz, 2003).
These considerations may explain the interference in controls in
general, but Mattia
et al. (1993), in contrast to our findings and the findings of
Amir et al. (1996), found that
the interference effect was nevertheless stronger in social
phobics than in controls.
We have no ready explanation for the lack of a similar group
difference in our colour-
naming latencies, but we will consider several possibilities
drawn from the literature on
emotional Stroop effects.
One possible explanation might be taken from Amir et al.
(2002), who suggested that
social phobics can inhibit emotional Stroop interference if they
have the opportunity to
strategically influence their reactions. When ‘opportunity’ was
operationalized as a low
or a high ratio of threat words, social phobics showed more
emotional interference with

rare than with frequent social threat words (Amir et al., 2002).
On the other hand,
blocked presentation of threat words increases interference
(Holle et al., 1997),
although one could argue with Amir et al., that in a blocked
format, patients have the
perfect opportunity to strategically influence their reactions. We
attempted to examine
these intriguing possibilities by calculating interference effects
separately for the first,
second, third, and fourth quarters of the block of threat words.
However, no interaction
of time (first, second, third, and fourth quarters) with category
(social threat vs. neutral
words) and/or with condition (alcohol vs. no alcohol) was
observed in the social phobic
groups. In other words, interference was stable throughout the
duration of the blocked
presentation, which supports neither the hypothesis of Amir et
al., nor the notion that

interference will increase with increasing confrontation
(blocked format).
We should also consider the possibility that particular aspects
of our social anxiety
challenge condition might have hindered the expected group
difference to appear.
Performance anxiety may attenuate the emotional Stroop
interference in social phobics
(Amir et al., 1996) and our socially-phobic participants did
report more anxiety than
controls. But the levels of anxiety were generally low (3 on a
scale of 0–10). Also, level of
acute anxiety was not correlated with emotional Stroop
interference. Thus, emotional
override cannot explain the lack of a higher interference effect
in social phobics.
We found that alcohol did attenuate the emotional Stroop
interference in controls
but not in social phobics. According to the core assumption of
the appraisal disruption
theory, alcohol should constrain the spread of activation of
associated information and
thus attenuate the emotional Stroop interference produced by
presenting words related

to social anxiety. Sayette, Martin, Perrott, Wertz, and Hufford
(2001) have shown this
effect of alcohol in a non-anxious control group. Specifically,
they demonstrated that
alcohol, if ingested before conducting the emotional Stroop test,
reduces the
interference for social stress words. This finding has been
replicated in our study.
But why was this not true for social phobics as well, and what
does this imply for the
functional analysis of the relation between social phobia and a
tendency to alcohol
abuse and dependence?
It can be argued that the spread of social threat-related
activation is much better
organized in social phobics than in non-anxious controls.
Sayette (1993b) argued that
alcohol is less likely to hinder spread of activation if a stressor
is ‘relatively easy to
process’ or ‘sufficiently threatening to override appraisal
deficits’ (p. 469). It seems
conceivable that, for social phobia patients, not only indicators
of acute stressors, but
also social threat words, may either be easier to process or are
associated strongly

enough with impending danger so that alcohol may no longer
effectively reduce spread
of activation. However, in this context our second, exploratory
finding is of interest.
We found a significantly better implicit memory for social
threat words in social phobics
compared with controls. Furthermore, this memory bias was
reduced by alcohol in the
expected direction.
Generally, it is assumed that two different processes are
responsible for implicit
memory biases. For the word-stem completion task it is assumed
that more data-driven
(or perceptually driven) processes are responsible. In this study,
however, it is clear that
conceptually-driven processes must be involved in order to
produce a valence-
associated (or threat-associated) bias. Indeed, at least four prior
studies have
demonstrated that conceptual/associative processing on
perceptual implicit memory
tests can be independent of explicit memory processes (e.g.
Hirshman, Passannante, &
Arndt, 2001). Note that participants had almost no traces of
explicit memory for either

neutral or social threat words. Thus, it is highly unlikely that
explicit recollection of
social threat words may have contaminated performance on the
stem completion task.
Furthermore, due to our balanced design only half of the
participants were first asked to
consciously recollect the Stroop words. It is generally
acknowledged that implicit
memory processes play an important role in ‘human affairs’
(Tulving & Schacter, 1990).
These authors proposed that ‘conceptually driven priming
reflects a process of semantic
learning: the modification of, or adding of new information to,
semantic memory’
(p. 304). Consequently, our results suggest that, in clinically-
anxious social phobics, not
only is appraisal hindered by alcohol, but elaboration after
initial processing also is also
affected. If that notion is correct, a threatening situation entered

by a social phobic after
drinking alcohol may be experienced with similar anxiety with
and without alcohol, but
this anxiety is remembered less intensively, thus still
encouraging the use of alcohol as
self-medication in future situations. This may partly explain
why studies focusing on
direct effects of alcohol on anxiety in clinically socially
anxious people have repeatedly
failed to find significant anxiety-reducing effects of alcohol
(Abrams et al., 2001; Himle
et al., 1999; Naftolowitz et al., 1994).
It has been found that alcohol has a different effect on anxiety
in women compared
with men. Especially alcohol expectancy – the belief that one
has received alcohol and
that it will have specific effects – has been studied in this
respect. For example, de Boer
et al. (1993) showed that alcohol expectancy reduced social
anxiety in women but not
in men. However, paradoxical effects of alcohol expectancy
have been demonstrated in
women as well: for example, Abrams and Wilson (1979) found
that women were more

anxious during a social interaction test if they believed that they
had received alcohol.
Hence, findings regarding the effects of alcohol expectancy on
women are inconclusive
(Schippers, de Boer, van der Staak, & Cox, 1997). However, in
the only experimental
study testing the direct effects of alcohol on anxiety involving
socially-phobic
participants, alcohol expectancy reduced reported social anxiety
while giving a public
speech (Abrams et al., 2001). We did not directly test whether
the pharmacological
effects of alcohol were solely responsible for our findings or if
alcohol expectancy or
other psychological factors may have additionally led to the
reduction of the emotional
Stroop interference in controls. Our participants did know
whether they received
alcohol or orange juice. The socially-phobic women in our
sample reported that they
expected more tension-reduction and regulation of negative
mood and also more
enhanced socio-emotional functioning after drinking alcohol (as
measured with the
AEQ) than the control participants. Possibly this may have
modulated the effects of

alcohol in some way or another. We did not find any association
between our measure of
alcohol expectancy and Stroop interference. However, it may be
that alcohol
expectancies are a transient- or an affect-dependent form of
cognition and consequently
have to be measured in vivo rather than at baseline.
There are a number of other limitations of our study. Based on
ethical considerations
we recruited social drinkers without a history of abuse or
dependence. It is possible that
this may have led to recruitment of a group of participants who
are especially unlikely to
experience anxiety reduction by ingestion of alcohol. Also, we
have only indirect
information on the alcohol status of the relatives of our
participants. Paternal alcoholism
has been associated with an increased risk to develop alcohol
problems and is
also known to affect the propensity to use alcohol to dampen
stress responses
(Finn & Pihl, 1987). We cannot exclude the possibility that our
recruitment procedure
implicitly excluded a subgroup that could potentially react

differently to alcohol. Also,
we exclusively recruited women. Thus, our results are limited to
female social phobics.
Finally, whereas a full balanced placebo design may not be
suitable if BAL above 0.6‰
(Sayette et al., 1994; Lyvers & Maltzman, 1991), our design
would clearly benefit from at
least a third cell with participants receiving placebo but
believing that they receive
alcohol. Future studies consequently should include such a
group in order to further
explore the contribution of alcohol expectancies.
In summary, we were able to confirm the notion that alcohol
disrupts appraisal
of threatening information in non-anxious women. This effect
was not observable
in socially-phobic women, which supports the notion that highly
effective processing

of threatening information lessens such an effect of alcohol. In
addition, we found an
implicit memory bias for socially-threatening words in social
phobics as compared with
controls. This implicit memory bias was attenuated by alcohol.
The overlap of excessive
alcohol use and social phobia may not be the result of appraisal
disruption exclusively,
but also the result of a curtailed memory for the anxiety
experienced during social
situations.
Acknowledgements
Alexander L. Gerlach and Anke Schiller have equally
contributed to this study and are listed in
alphabetical order. We thank Ralf Demmel and Michael Sayette
for comments and
recommendations in the planning phase of this study. This
research was supported by the
Christoph Dornier Foundation and the Christoph Dornier Clinic.
Portions of this study were
presented at the XXXIII Annual Congress of the EABCT,
Prague, The Czech Republic, September
2003.

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Effect of moderate alcohol consumption on fetuin-A levels in
men and women:
post-hoc analyses of three open-label randomized crossover
trials
Diabetology & Metabolic Syndrome 2014, 6:24
doi:10.1186/1758-5996-6-24
Michel M Joosten ([email protected])
Ilse C Schrieks ([email protected])
Henk FJ Hendriks ([email protected])
ISSN 1758-5996
Article type Research
Submission date 22 October 2013
Acceptance date 14 February 2014

Publication date 18 February 2014
Article URL http://www.dmsjournal.com/content/6/1/24
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Effect of moderate alcohol consumption on fetuin-A
levels in men and women: post-hoc analyses of three
open-label randomized crossover trials
Michel M Joosten1,2,3,*
* Corresponding author
Email: [email protected]
Ilse C Schrieks1,2
Henk FJ Hendriks1
1 TNO (a Dutch acronym for Netherlands Organisation of
Applied Scientific
Research), Zeist, the Netherlands
2 Division of Human Nutrition, Wageningen University,
Wageningen, the
Netherlands
3 Department of Internal Medicine, University of Groningen,
University Medical
Center Groningen, Groningen, the Netherlands
Abstract
Background

Fetuin-A, a liver-derived glycoprotein that impairs insulin-
signalling, has emerged as a
biomarker for diabetes risk. Although moderate alcohol
consumption has been inversely
associated with fetuin-A, data from clinical trials are lacking.
Thus, we evaluated whether
moderate alcohol consumption decreases circulating levels of
fetuin-A.
Methods
We analyzed data of three separate open-label, randomized,
crossover trials: 1) 36
postmenopausal women consuming 250 ml white wine (25 g
alcohol) or white grape juice
daily for 6 weeks, 2) 24 premenopausal women consuming 660
ml beer (26 g alcohol) or
alcohol-free beer daily for 3 weeks, and 3) 24 young men
consuming 100 ml vodka (30 g
alcohol) orange juice or only orange juice daily for 4 weeks.
After each treatment period
fasting blood samples were collected.
Results
Circulating fetuin-A concentrations decreased in men after
vodka consumption (Mean ±
SEM: 441 ± 11 to 426 ± 11 µg/ml, p = 0.02), but not in women
after wine (448 ± 17 to 437 ±
17 µg/ml, p = 0.16) or beer consumption (498 ± 15 to 492 ± 15
µg/ml, p = 0.48) compared to
levels after each corresponding alcohol-free treatment. Post-hoc
power analyses indicated

that the statistical power to detect a similar effect as observed
in men was 30% among the
postmenopausal women and 31% among the premenopausal
women.
Conclusions
In these randomized crossover trials, moderate alcohol
consumption decreased fetuin-A in
men but not in women. This sex-specific effect may be
explained by the relatively short
intervention periods or the low statistical power in the trials
among women.
Trials registration
ClinicalTrials.gov ID no’s: NCT00285909, NCT00524550,
NCT00918918.
Keywords
Alcohol consumption, Fetuin-A, Insulin sensitivity, Liver
enzymes, Type 2 diabetes mellitus
Introduction
Fetuin-A (α-Heremans-Schmid glycoprotein) is an abundant
hepatokine that impairs insulin
signalling by inhibiting tyrosine kinase activity [1,2]. Several
prospective studies have
reported positive associations between circulating fetuin-A and
type 2 diabetes risk and,
concomitantly, observed inverse relations between alcohol
consumption and fetuin-A [3-5].
More importantly, a recent case-control study suggested that
fetuin-A may partially explain

the reduced risk of type 2 diabetes [6] that has consistently been
observed with moderate
alcohol consumption [7-9]. However, the cross-sectional and
observational nature of these
alcohol-fetuin-A associations may raise concern about potential
confounding. Thus, to
comprehensively investigate the effect of moderate alcohol
consumption on fetuin-A levels,
we performed post-hoc analyses of three randomized crossover
interventions with different
alcohol-containing beverages in men and women.
Materials and methods
The rationale of the three trials was to study the effect of
moderate alcohol consumption on
markers of insulin sensitivity and/or inflammation. Each trial is
registered at
ClinicalTrials.gov: NCT00285909, NCT00524550, and
NCT00918918. Independent medical
ethics committees approved the research protocols The Medical
Ethics Committee of the
University Medical Centre Utrecht; Utrecht, the Netherlands
[NCT00285909] and METOPP;
Tilburg, the Netherlands [NCT00524550, and NCT00918918])
and all participants gave
written informed consent. Eligible subjects were apparently
healthy, were habitual alcohol
consumers, refrained from smoking, and had no family history
of alcoholism. The design of
each individual intervention has been described in more detail
elsewhere [10-12]. In short,
the three studies were open-label, randomized, crossover
intervention trials and were all
conducted at TNO (a Dutch acronym for Netherlands
Organisation of Applied Scientific

Research) in Zeist, the Netherlands. The trials consisted of 1)
36 postmenopausal women
consuming 250 ml white wine (25 g alcohol; Chardonnay; Jean
d’Alibert, Rieux, France) or
white grape juice (Albert Heijn, Zaandam, the Netherlands)
daily for 6 weeks between March
and June 2006, 2) 24 premenopausal women consuming 660 ml
beer (26 g alcohol) or
alcohol-free beer daily (both Amstel, Amsterdam, the
Netherlands) for 3 weeks between
August and November 2007, and 3) 24 young men consuming
100 ml vodka (30 g alcohol;
Smirnoff, Diageo, London, UK) and 200 ml orange juice
(Appelsientje, Riedel, Ede, The
Netherlands) or only orange juice daily for 4 weeks between
August and November 2009.
Postmenopausal women had an absence of menses for at least
two years. Premenopausal
women used phase I or II oral contraceptives. Allocation to
treatment order (alcohol-
containing vs. alcohol-free period) was randomized according to
age and body mass index
(BMI). After each treatment period, fasting blood samples were
obtained. Plasma samples
were stored at −80°C (beer and vodka trials) and serum samples
at −20°C (wine trial) until
analysis. Fetuin-A concentrations were determined by a
sandwich enzyme-linked
immunosorbent assay (ELISA) (R&D Systems, Minneapolis,
MN) with a mean intra-assay
coefficient of variation of 6.8%.
Data were analyzed using SAS statistical software (version 8.2;

SAS Institute, Cary, NC,
USA). Variables were compared between treatments with a
mixed analysis of variation
(ANOVA) model that included terms for treatment, period and
the interaction between period
and treatment (indicating possible carryover effects).
Correlation coefficients were computed
according to Spearman rank order to assess associations
between intervention-induced
changes in fetuin-A and other biochemical variables. Data are
presented as mean ± standard
error of the mean (SEM). All tests were two-sided. Statistical
significance was defined as p <
0.05.
Results
All subjects completed both arms of their intervention. No
notable adverse effects were
reported. Age and BMI were 56.5 ± 4.2 y and 25.4 ± 3.3 kg/m2
in postmenopausal women,
23.9 ± 4.3 y and 22.2 ± 1.6 kg/m2 in the premenopausal women,
and 25.5 ± 4.3 y and 22.2 ±
1.6 kg/m2 in the men, respectively. Indicators of compliance
were the increased high-density
lipoprotein (HDL)-cholesterol and adiponectin levels after each
of the three alcohol
consumption periods compared with after the alcohol-free
consumption periods (Table 1).
Table 1 Biochemical markers of 24 young men, 24
premenopausal women, and 36
postmenopausal women sampled after an overnight fast after 4,
3 and 6-week treatment
periods, respectively, of consuming alcohol-free or alcohol-
containing beverages

Young men Premenopausal women Postmenopausal women
Orange
juice
Vodka and
orange juice
p value Alcohol-free beer Beer p
value
White grape
juice
White
wine
p
value
Fetuin-A (µg/ml) 441 ± 11 426 ± 11 0.02 498 ± 15 492 ± 15
0.48 448 ± 17 437 ± 17 0.16
Adiponectin (µg/ml) 10.5 ± 1.0 11.8 ± 1.0 0.005 6.8 ± 0.4 7.2 ±
0.4 0.01 12.0 ± 0.7 13.1 ± 0.7 <0.001
Insulin (pmol/l) 59.8 ± 8.5 55.7 ± 8.6 0.53 45.7 ± 4.0 46.1 ± 4.0
0.90 46.5 ± 3.4 40.0 ± 3.4 0.90
Glucose (mmol/l) 5.3 ± 0.10 5.3 ± 0.10 0.76 4.8 ± 0.11 4.8 ±
0.11 0.36 5.4 ± 0.11 5.4 ± 0.11 0.36
HOMA-IR 1.98 ± 0.30 1.87 ± 0.30 0.61 1.41 ± 0.11 1.43 ± 0.11
0.81 1.64 ± 0.13 1.42 ± 0.13 0.02
HDL cholesterol (mmol/l) 1.12 ± 0.05 1.22 ± 0.05 0.009 1.52 ±
0.07 1.62 ± 0.07 0.008 1.57 ± 0.07 1.68 ± 0.07 <0.001
LDL cholesterol (mmol/l) 2.63 ± 0.17 2.70 ± 0.17 0.55 2.40 ±
0.07 2.37 ± 0.07 0.77 3.84 ± 0.12 3.51 ± 0.12 <0.001
Triglycerides (mmol/l) 1.23 ± 0.14 1.33 ± 0.14 0.30 1.27 ± 0.08
1.25 ± 0.08 0.61 1.18 ± 0.08 1.04 ± 0.08 <0.001

Free fatty acids (mmol/l) 0.42 ± 0.03 0.35 ± 0.03 0.07 0.34 ±
0.03 0.29 ± 0.03 0.26 0.43 ± 0.04 0.44 ± 0.04 0.67
Alanine aminotransferase (U/l) 15.2 ± 1.1 15.9 ± 1.1 0.49 10.8
± 1.8 10.0 ± 1.8 0.21 13.8 ± 2.5 17.4 ± 2.5 0.29
Alkaline phosphates (U/l) 65.1 ± 4.3 65.8 ± 4.3 0.70 56.9 ± 6.5
57.8 ± 6.5 0.68 72.7 ± 2.9 73.6 ± 2.9 0.73
Aspartate aminotransferase
(U/l)
21.0 ± 1.0 20.6 ± 1.0 0.62 17.8 ± 2.0 17.8 ± 2.0 0.95 20.9 ± 2.0
24.8 ± 2.0 0.13
γ-Glutamyltransferase (U/l) 19.8 ± 2.4 24.3 ± 2.4 0.003 16.5 ±
2.2 18.5 ± 2.2 0.01 18.4 ± 5.2 27.5 ± 5.2 0.21
Data are presented as means ± SEM. P values are obtained from
a mixed-model ANOVA. Abbreviations: HOMA-IR homeostasis
model
assessment of insulin resistance; HDL high-density lipoprotein;
LDL low-density lipoprotein.
No carry-over effects were found in fetuin-A, indicating that a
possible effect on fetuin-A
levels due to a treatment given in the first time period of the
crossover trial did not persist
into the second period and influence the effect of the second
treatment. Fetuin-A levels
decreased in men after vodka juice consumption (441 ± 11 to
426 ± 11 µg/ml, p = 0.02) but
not significantly in postmenopausal women after wine (448 ± 17
to 437 ± 17 µg/ml, p = 0.16)
or in premenopausal women after beer consumption (498 ± 15 to
492 ± 15 µg/ml, p = 0.48)
(Figure 1) as compared to levels after each corresponding

alcohol-free beverage
consumption.
Figure 1 Individual changes of circulating fetuin-A levels at the
end of the alcohol or
alcohol-free treatment periods after an overnight fast for three
open-label randomized
crossover trials.
No correlations were observed between alcohol-induced changes
in fetuin-A and
corresponding changes in the homeostasis model assessment of
insulin resistance (HOMA-
IR) (ρ = 0.01, p = 0.95; ρ = 0.25, p = 0.26; ρ = 0.20, p = 0.24)
or changes in adiponectin (ρ =
0.22, p = 0.31; ρ = 0.17, p = 0.44; ρ = 0.25, p = 0.15) among
young men, pre- or
postmenopausal women, respectively. Changes in HOMA-IR
and adiponectin were also not
correlated among men (ρ = 0.14, p = 0.51), premenopausal
women (ρ = 0.01, p = 0.96), or
postmenopausal women (ρ = 0.27, p = 0.11). Also, no consistent
correlations were observed
between alcohol-induced changes in fetuin-A and analogous
changes in fasting blood lipids
including HDL-cholesterol and free fatty acids (FFA), or liver
function parameters across the
three trials.
Conclusions
In post-hoc analyses of three separate open-label randomized
crossover intervention studies,
we found that moderate alcohol consumption reduced fetuin-A
levels in men but not in
women. This decrease was apparent after four weeks of

moderate vodka consumption. No
consistent correlations between intervention-induced changes in
fetuin-A and other
biochemical markers were observed across the three studies.
To our knowledge, these are the first intervention studies
investigating the effect of different
alcohol-containing beverages on circulating fetuin-A. The
lowered fetuin-A levels in men
after moderate alcohol consumption partially confirm cross-
sectional observations in several
epidemiological studies [3-6,13,14] and may provide some
physiological support for the
protective effect of moderate alcohol consumption on the risk of
developing type 2 diabetes
[6,8] besides adiponectin [15]. Furthermore, these findings
extend prior evidence of short-
term clinical trials that noted favourable changes in selected
biological markers associated
with diabetes and cardiovascular risk after moderate alcohol
consumption [16].
The underlying physiological explanation how alcohol
consumption may lower fetuin-A is
not clear. Also, the sex-specific alcohol-fetuin-A effect was
unexpected, particularly since all
women were either on oral contraceptives or postmenopausal,
which limits potential
influences of hormonal fluctuations or menstrual cycles. The
null finding in our trials among
pre- and postmenopausal women do not seem to correspond with
a previous observational
study among 1331 middle-aged and older US female nurses,
where moderate alcohol
consumption was inversely associated with plasma fetuin-A
even after adjustment for several

lifestyle variables, demographic information, and medical
history [6]. Perhaps this
discrepancy can be explained by the low statistical power in the
two trials among women.
Post-hoc power analyses indicated that the power to detect a
similar effect as observed in
men was only 30% among the postmenopausal women and 31%
among the premenopausal
women.
Circulating fetuin-A was strongly and negatively associated
with the insulin-sensitizing
adipokine adiponectin in humans [17] and treatment of human
adipocytes with fetuin-A
repressed ADIPOQ mRNA levels [17]. Furthermore, given the
prior associations between
fetuin-A and insulin resistance [18] and insulin sensitivity [19],
we hypothesized that
reductions in fetuin-A may play a role in the increased
adiponectin levels or improved insulin
sensitivity after alcohol consumption [10]. Therefore, we
analyzed correlations between
intervention-induced changes in fetuin-A and adiponectin levels
and other markers of insulin
sensitivity, such as HOMA-IR. We, however, did not find such
inverse correlations despite
the fact that moderate alcohol consumption increased both
ADIPOQ expression [10] and
corresponding circulating adiponectin levels [10-12], suggesting
that fetuin-A and
adiponectin levels may be independently affected by alcohol.
Also, it is important to note that
the HOMA-IR index is a weak estimate of insulin resistance,

particularly in a small study.
The absence of a correlation between alcohol-induced changes
in fetuin-A and HOMA-IR
may partially be explained by the relatively low FFA levels of
the studied participants. In a
study among 347 healthy subjects at increased risk of type 2
diabetes, fetuin-A was only
inversely associated with insulin sensitivity among individuals
with high FFA levels (~ >
0.65 mmol/l) [20].
Strengths of the study are the randomized crossover design
(considered the ‘gold standard’
for evidence-based research), the assessment of compliance
markers (i.e. HDL-cholesterol
and adiponectin) to the study treatments, the inclusion of both
sexes, and the broad range of
biochemical variables. Some limitations warrant consideration.
The trials consisted of
alcohol-administration periods of 3 to 6 weeks and were
performed among fairly insulin-
sensitive subjects. Maybe more profound effects on fetuin-A
levels would have been
observed if the interventions lasted longer and/or were executed
in subjects with glucose
levels in the (pre)diabetic range. For example, three months of
moderate alcohol consumption
decreased fasting glucose levels among subjects with impaired
glucose metabolism [21] and
fetuin-A levels were particularly associated with an increased
diabetes risk among subjects
with higher fasting glucose [3,5]. Regardless, the duration of
the present interventions were
long enough to detect alcohol-induced changes in other
biochemical markers such as
adiponectin and HDL-cholesterol. Also, the association between

moderate alcohol
consumption and lower risk of type 2 diabetes mellitus is not
limited to subjects with
impaired glucose metabolism but also exists for subjects already
at low risk for diabetes on
the basis of multiple combined low-risk lifestyle behaviours
[22]. Nevertheless, the subjects
studied were rather lean (mean BMI values 22-26), had no fatty
liver (low liver enzyme
levels) and were rather insulin sensitive (low HOMA-IR). Also,
all premenopausal women
used oestrogen-containing oral contraceptives, which may
explain their somewhat higher
fetuin-A levels given the positive associations between
oestrogen and fetuin-A [23,24]. Thus,
the data are not representative for a typical at-risk population
for metabolic diseases. Second,
the daily amounts of alcohol consumed by women (~25 g
alcohol) were higher than what is
considered ‘moderate’ according to most guidelines (i.e. max.
~15 g alcohol). However, the
nadir of the alcohol-diabetes association for women appeared to
be at 24 g of alcohol/day in a
meta-analysis of 20 prospective studies [8] while alcohol
consumption became harmful above
50 g/day (and above 60 g/day for men). Third, post-hoc power
analyses showed that there
was low statistical power in the two trials among women to
detect a similar effect as observed
in the trial among men. Fourth, although unlikely since vodka is
basically an ethanol-water
mixture, we cannot fully exclude a potential beverage-specific
effect. Finally, the alcohol-

induced reductions in fetuin-A were comparable to associations
reported in epidemiological
studies [3,5,6], but were relatively small as compared to
alcohol’s effect on HDL-cholesterol
and adiponectin. It is possible that the findings, including the
sex differences, were due to
chance.
In conclusion, the results of these three randomized clinical
trials with different alcohol-
containing beverages demonstrated that short-term moderate
alcohol consumption decreases
fetuin-A levels in men but not in women. Further research is
needed to determine whether
long-term moderate alcohol consumption decreases fetuin-A
levels. If so, these findings may
add to the current knowledge of possible metabolic benefits of
moderate alcohol
consumption.
Abbreviations
ANOVA: Analysis of variation; BMI: body mass index; ELISA:
enzyme-linked
immunosorbent assay; FFA: free fatty acids; HDL-cholesterol:
High-density lipoprotein-
cholesterol; HOMA-IR: homeostasis model assessment of
insulin resistance; SEM: standard
error of the mean
Competing interests
The authors have no potential conflicts relevant to this article.
Authors’ contributions

M.M.J. conceived the idea of the study, designed the study,
directed the study’s
implementation, conducted the statistical analyses, interpreted
the data, and wrote the
manuscript. I.C.S. assisted in the study’s implementation,
assisted in the interpretation of the
data, and critically edited the manuscript. H.F.J.H. designed the
study, directed the study’s
implementation, assisted in the interpretation of the data,
critically edited the manuscript, and
obtained funding. All authors read and approved the final
manuscript.
Acknowledgements
This work was supported by the Dutch Ministry of Economic
Affairs, Agriculture and
Innovation and by the Dutch Foundation for Alcohol Research
(SAR) representing Dutch
producers of and traders in beer, wine and spirits and by TNO.
Their joint aim is to
independently study the health effects of moderate alcohol
consumption.
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I want a research paper and an Annotated Bibliography for each
source that is used in this research paper
The Argument research paper is about the effect of alcohol on
blood MLA format.
There are two sources in the attachment that I have to use and I
want three more sources from anywhere.
That’s what teachers want” In an opinion paper, you just state
your view and perhaps offer reasons for your opinion. It’s not
necessary to garner agreement. An argument paper, on the other
hand, not only states your view, but also offers evidence to
support your position, raises counterarguments, and refutes or
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And annotated bibliography following that:
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and what you are hoping to argue in your paper.
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3. A concise (2-3 sentences) description of each source,

including what type of publication it’s from, the credibility of
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