Negative priming effects on cognitive dissonance

Running head: PRIMING AND COGNITIVE DISSONANCE 1
Priming effects on cognitive dissonance
Rachel Wallace
Wingate University

PRIMING AND COGNITIVE DISSONANCE 2
Abstract
Priming can be defined as any stimulus that elicits a conscious or unconscious behavior (Ihrke,
Behrendt, Schrobsdorff, Visser, and Hasselhorn, 2013). Priming in general is used to “evaluate
how degrees of “preparedness” for a given stimulus affect the reaction time” (Ihrke et. al, 2013,
pg 12). Negative priming is most often defined as the affect an ignored stimulus has on a behavior,
once the ignored stimulus is attended to (Ihrke et. al, 2013). Cognitive dissonance is most readily
defined as two opposing cognitions that cause a state of psychological unrest until either an action
or belief is modified (Viosin, Stone, and Becker, 2013). The current study had multiple
experimental groups, assessing three differing levels of negative priming; extreme, moderate, and
none. It was hypothesized that the more extreme the statistics, the more cognitive dissonance one
would experience, also that beliefs on alcohol would change after exposure to a prime. Results
indicate exposure to statistics elicits changes in beliefs on alcohol, but not changes in self-report.
Keywords: cognitive dissonance; priming; alcohol; extra-curricular activities

Priming effects on cognitive dissonance.
Priming as a general topic can be defined as the ability of a stimulus to affect the reactions
of an individual (Dennis & Perfect, 2013; Ihrke et. al, 2013). Although most researchers agree that
individuals can be primed to react to a probe, there are differing views on priming effects and
causes (Dennis & Perfect, 2013; Ihrke, Behrendt, Schrobsdorff, Visser, & Hasselhorn, 2013;
Skowronski, Sedikides, Heider, Wood, & Scherer, 2010; Yap, Balota, & Tan, 2013).
Horner and Henson’s research stated that there are three levels of response coding within
priming: classification, decision, and action. Using this definition, the classification level was
described as the period in which an individual responded to the initial size of the stimuli. The
decision level was described as the period in which the individual coded the stimuli, or when the
person decided on the impact. The action level was described as when the individual actually
responded to the stimuli (Horner & Henson, 2009). Dennis and Perfect (2013), along with Horner
and Henson (2009) worked under the definition of priming as responding to a stimulus, invoking
a response that then becomes associated with the original stimuli, so when the stimulus is re-
experienced, the response is as well.
As the field of psychology has progressed, priming has been studied in more detail,
with emphasis on differing ideas of the topic. Semantic priming, one of the more widely known
branches, receives a relatively large amount of focus. As stated by Yap, Balota, and Tan (2013),
“the semantic priming effect is the well-known finding that words preceded by related primes are
recognized faster than those preceded by unrelated primes” (pg 140). Although the current study’s
focus is not semantic priming, it is important to understand the implications of the effects on the

participants. The fact that this effect is present in written words is important in the foundation of
the survey to be used to measure this study. As a researcher, one would not want to skew the data
by accidental priming.
The current study plans to focus on negative priming, which allows researchers to study
how ignored information is processed (Ihrke, et al., 2013). Negative priming is often referred to as
a form of priming in which subtle primes are used to induce a behavior or action (Skowronski,
Sedikides, Heider, et al., 2010). In studies previously conducted that have contained negative
priming, behaviors and attitudes have been altered due to a previous prime (Skowronski,
Sedikides, Heider, et al., 2010). The current study hopes to see if this in conjunction with cognitive
dissonance can cause college students to unconsciously falsify self-reports of behavior.
Cognitive dissonance can be defined as shifting one’s beliefs or actions to match the
conflicting belief or action to reduce feelings of unease (Jarcho, Nerkman, & Lieberman, 2011).
This states that if a behavior or action does not match the belief of the individual, either the
behavior or belief will be changed to reduce the feelings that something is not right (Allahyani,
2012). An example to better explain cognitive dissonance is smoking. A person can have the belief
that smoking is wrong, but if they start smoking they are likely to rationalize the behavior with life
examples of people who have smoked and not experienced the side effects. There have been many
studies over the years focusing on cognitive dissonance, all of which have worked to find the
balance between what causes humans to need consistency and why they constantly change beliefs
or behaviors (Allahyani, 2012; Hoshino-Browne, 2012; Jarcho, Berkman, & Lieberman, 2011;
Voisin, Stone, & Becker, 2013).

Hoshino-Browne (2012), worked to examine cognitive dissonance in a cultural context. He
focused on the area in which an individual resided and how it affected his or her personal
dissonance levels. For instance he noted that in North America, individuals are more likely to
experience dissonance if their behaviors do not match their beliefs because the society is highly
individualistic and values personal beliefs as a virtue (Hishino-Browne, 2012). For example,
because North America is an individualistic society being individual and standing out is valued
higher than blending. This leads to greater shifts in behavior when dissonance in experienced.
However, it was also noted that in East Asia the opposite was true. In a collectivist society the
norm was to adjust to society’s standards rather than one’s own. This would lead to a greater shift
in attitude than in behavior, so as to escape social exclusion from non-conformity. This is important
to remember when assessing the data to be collected in this current study, as the location is in an
individualistic society. The results could be different if the current study were to be conducted in
a collectivist society.
Researchers have studied ways to use cognitive dissonance to break habits for long periods
of time. In an article by Glock, Muller, and Krolak-Schwerdt (2013), it was found that simply
believing healthy behaviors would compensate for unhealthy habits would not reduce cognitive
dissonance. This is a very important finding because from it one can see that cognitive dissonance
has a strong grip on the mind. Although cognitive dissonance can be reduced for short periods of
time through beliefs, ultimately one must change their actions (Glock, Muller, & Krolak-Schwerdt,
2013).
Although both cognitive dissonance and priming have been studied in length, neither
phenomenon has been studied in conjunction with the other. Cognitive dissonance causes unrest

in the mind (Allahyani, 2012; Hoshino-Browne, 2012; Jarcho, Berkman, & Lieberman, 2011;
Voisin, Stone, & Becker, 2013), while priming causes unconscious responses (Dennis & Perfect,
2013; Ihrke, Behrendt, Schrobsdorff, Visser, & Hasselhorn, 2013; Skowronski, Sedikides, Heider,
Wood, & Scherer, 2010; Yap, Balota, & Tan, 2013). It was the goal of the current study to see
how the two affected each other in a study that assessed the negative priming of alcohol statistics.
It was my prediction that college students who were exposed to extreme levels of alcohol statistics
would experience higher levels of cognitive dissonance that would in turn cause students to be
dishonest on self-reports of alcohol use. It was also predicted that beliefs on alcohol use would
change after exposure to varying levels of the prime.
Methods
Participants
There were 25 participants (n=25) with ages ranging from 18-22, with the average age
being 18. Of the participants, there were eight males, sixteen females, and one who did not disclose
demographic information. Participants were recruited from a pool of students in Introduction to
Psychology courses, as well as other students enrolled in the college institution. To gain
participation, the study was advertised on a website to the Introduction to Psychology students,
and posted on social media sites to encourage participation by older members of the college
community.
Instrumentation
Extra-Curricular Activity Questionnaire. This study used a Likert-type scale survey
created by the researcher. It consists of 15 questions asking the participant about the activities they

engage in outside of the classroom. This questionnaire was designed to measure whether or not
priming had an effect on self-report. In order to do so without arousing suspicion, the items
designed to measure the intended effect were been mixed in with a variety of distractor items. An
example distractor item is, “How often do you attend sporting events?” An example measure item
is, “How often does alcohol impact your confidence?” The intent is to find that the responses on
the measure items vary significantly within the experimental groups. (See Appendix A)
Alcohol Opinion Survey. This measure is an opinion survey on the participants’ beliefs
on alcohol use. The survey used consisted of five questions asking the participant how he or she
views alcohol use. This survey was administered twice, before exposure manipulation and after,
to measure possible changes in beliefs about alcohol. The intent was to see whether or not seeing
the statistics caused cognitive dissonance to the extent that the participants change their response
to the survey unconsciously. (See Appendix B)
Statistic Posters. The alcohol statistics that were used in the present study range from
accurate to exaggerated. In order to obtain the intended result, alcohol statistics have been falsified
for one of the experimental groups. As the study focused on the effects of priming on survey
responses and cognitive dissonance, it was important to have a variable that was manipulated
enough to elicit an effect. For this reason, alcohol statistics that began in astounding numbers, for
instance: 51.5% of adults 18 and over are currently alcohol drinkers (www.cdc.gov); became:
75.9% of adults 18 and over are currently alcohol drinkers. The exaggerated numbers were
completely random, the only exception being a limit on the amount of exaggeration. For example,
one would not change a statistic from 50% to 500%, it needed to be reasonable believable. (See
Appendix C)

Experimental Conditions
Accurate Statistics. Participants were informed they would be completing a survey on
their extra-curricular activities. Once they had arrived in the initial location, after ensuring all
distractors were removed, the Alcohol Opinion Survey was administered. Once the Alcohol
Opinion Survey was completed, the researcher asked for all the participants with the number “2”
on their Consent Form to follow her. They were then led to the appropriate experimental condition
room. Once the participants had settled in their desks, and all it was ensured all distractors were
removed, the researcher left the room to go check on other experimental group. The group was
informed that the researcher would be back shortly, and not to leave the room unless absolutely
necessary.
When the researcher returned, the Extra-Curricular Activity Questionnaire was
administered. The researcher then left the room again to check on the other conditions, informing
the group she would return. As participants finished the Questionnaire, they were handed the
second Alcohol Opinion Survey, and asked to wait until the others finished. Once everyone had
completed the tasks, the group was debriefed and dismissed.
Exaggerated Statistics. Participants were informed they would be completing a survey on
their extra-curricular activities. Once they had arrived in the initial location, after ensuring all
distractors were removed, the Alcohol Opinion Survey was administered. Once the Alcohol
Opinion Survey was completed, the researcher asked for all the participants with the number “3”
on their Consent Form to follow her. They were then led to the appropriate experimental condition
room. Once the participants had settled in their desks, and all it was ensured all distractors were
removed, the researcher left the room to go administer the surveys to the first experimental group.

The group was informed that the researcher would be back shortly, and not to leave the room
unless absolutely necessary.
When the researcher returned, the Extra-Curricular Activity Questionnaire was
administered. The researcher left the room during the completion of the second survey, informing
the participants she would return shortly. As participants finished the Questionnaire, they were
handed the second Alcohol Opinion Survey, and asked to wait until the others finished. Once
everyone had completed the tasks, the group was debriefed. Within the debriefing, it was made
sure that the participants were made aware that the statistics they were presented with were false
and that they were given the accurate ones. Once it was made clear there was no confusion, they
were dismissed.
Control condition. Participants were informed they would be completing a survey on their
extra-curricular activities. Once they had arrived in the initial location, after ensuring all distractors
were removed, the Alcohol Opinion Survey was administered. Once the Alcohol Opinion Survey
was completed, the researcher asked for all the participants with the number “1” on their Consent
Form to fill out the Extra-Curricular Activity Questionnaire while she directed groups “2” and “3”
to their designated rooms.
When the researcher returned, the Alcohol Opinion Survey was re-administered and
participants were asked to remain until all participants had completed the survey. Once everyone
had completed the tasks, the group was debriefed and dismissed.
Procedure

Participants were given a consent form to read over and sign. Each consent form had a
number between one and three written as a page number in the top right hand corner of the page
and they were shuffled to assure randomness. Each number corresponded to an experimental
condition: “1” was the control, “2” was the Accurate Statistic condition, and “3” was the
Exaggerated Statistic condition. Once consent forms were collected, so were phones and other
distractors to ensure that the statistics were viewed.
The control group did not have alcohol statistics. The researcher did not change the
environment other than the initial taking of cellular devices. After each group had completed the
questionnaire they were asked to complete the alcohol opinion survey again, debriefed and made
aware the true purpose of the study. Experimental Group 3 was also made aware that their statistics
were false and given information containing the correct statistics so that they did not believe false
information.
Results
Analyses on the three conditions, Control (n = 8), Accurate Statistics (n = 8), and
Exaggerated Statistics (n = 9), were conducted in multiple ways. To test the hypothesis that college
students who were exposed to extreme levels of alcohol statistics would experience higher levels
of cognitive dissonance that would in turn cause students to be dishonest on self-reports of alcohol
use a one-way between-subjects ANOVA was conducted. To test the second hypothesis that
beliefs on alcohol would change after exposure to varying levels of the prime a Repeated Measures
ANOVA was needed, however access to software to conduct the test was unavailable. In lieu of
this, three Paired Samples t tests were run in conjunction with a Bonferroni correction to account
for Type I errors. Within analyses, higher scores indicate more negative views on or higher use of

alcohol. For the Alcohol Opinion Survey the range ran from 5-18. For the Extra Curricular Activity
Questionnaire there was a possible range of 4-26 but participants scored within a range or 4-20.
Descriptive Statistics
Analysis on the Extra Curricular Activities Survey indicated differences in the means for
the three conditions. The Accurate Statistic condition showed more use of alcohol (M = 12.50, SD
= 5.16) than both the Control (M = 8.75, SD = 4.40), and the Exaggerated Statistic conditions (M
= 9.67, SD = 5.32).
Analysis on the Alcohol Opinion Surveys revealed differences in participant opinions of
alcohol from the pre-test to the post-test in all three conditions. The Control condition had a greater
change in means from the pre-test (M = 10.25, SD = 1.04) to the post-test (M = 11.13, SD = 0.99)
than either of the other two conditions. The Accurate Statistic condition had the second greatest
change in means from the pre-test (M = 10.00, SD = 0.76) to the post-test (M = 10.63, SD = 0.92).
The Exaggerated Statistic Condition had the smallest change in means from pre-test (M = 10.89,
SD = 2.15) to post-test (M = 11.00, SD = 1.50).
Dishonest self-report of alcohol behavior
Statistical significance was not found with the analysis of the Extra Curricular Activity
survey, F(2, 22) = 1.24, p > .05. This refutes the hypothesis that the alcohol statistics would cause
cognitive dissonance and change the honesty of participants’ self-report on alcohol use. A Tukey
Post hoc was preformed to ensure no errors. The Tukey also found no statistical significance
between conditions, p > .05, and the greatest insignificance being between the Control and
Exaggerated Statistic conditions. However, there was a large effect size, n2 = 0.10.

Changes in Opinion of Alcohol
The hypothesis that exposure to varying levels of the prime would change beliefs on
alcohol was partially confirmed based on the statistical analysis. Statistical significance was found
in the Control, t(7) = -7.0, p < .05, d = -0.87, and the Accurate Statistic, t(7) = -3.42, p < .05, d = -
0.75, conditions with the analysis of the Alcohol Opinion Survey. However, significance was not
found with the Exaggerated Statistic condition, t(8) = -0.244, p > .05, d = -0.06. Because multiple
t-tests had to be run to analyze the results, a Bonferroni Correction had to be performed as well.
Even after the Correction, significance was maintained in the two conditions: Control, p < .016;
Accurate, p <.016.
Discussion
The purpose of this study was to determine an interaction between cognitive dissonance
and priming. More specifically, to see how introducing a college student with a prime of alcohol
statistics would influence their beliefs on alcohol, and the way they report their actions on alcohol.
Previous research has shown that individuals are likely to change either actions or beliefs when
experiencing cognitive dissonance (Allahyani, 2012; Hoshino-Browne, 2012; Jarcho, Berkman, &
Lieberman, 2011; Voisin, Stone, & Becker, 2013). It has also shown that primes can lead people
to unconsciously act towards a certain behavior or belief (Ihrke, Behrendt, Schrobsdorff, Visser,
and Hasselhorn, 2013). It was the hope of the current study to find support for a causal relationship
between the theories found in previous research.
Results of this study found no statistical significance with the measure used to test priming
on cognitive dissonance, the Extra Curricular Activities Survey, refuting the hypothesis that the

primes causes cognitive dissonance enough to change self-report on alcohol behavior. However
there was a large effect size present in the analysis, suggesting that an effect was in fact taking
place. It would be interesting to find a way to assess what effect was happening, and to see if there
was a better way to measure changes in behavior after exposure to the prime.
Results did, however, indicate some significance in regards to priming affecting cognitive
dissonance changes in beliefs. The hypothesis of this study was partially confirmed in this regard
because significance was found in the Control and Accurate Statistic conditions but not in the
Exaggerated Statistic condition. This partial confirmation was actually counterintuitive to the
researcher because it was thought that significance would be found in the Exaggerated Statistic
condition due to the greater perceived threat. However, it was found to have a small effect size.
Thus meaning, the effect was actually smaller than thought and a larger sample would have been
needed to possibly find anything.
Significance being found in the Accurate Statistic condition is beneficial to the real world,
and a real world application due to the fact that one sees accurate alcohol statistics when
researching, and not exaggerated and falsified statistics. The results that a person changes their
beliefs from a positive view on alcohol to a more negative view after exposure to the statistic prime
can be useful in aiding alcoholics in the recovery process or aiding other individuals with other
similar afflictions. It can also be interpreted to mean that the presence of a prime well known in
society to be negative to a relative degree can lead individuals to change their beliefs. Because
there was no accurate measure of change in behavior, it is possible that this change in belief after
the presence of statistics lead to a change in behavior. It would be interesting to investigate further
the complete effects of these statistics on this age group.

Also, significance being found in the Control condition leads one to question the accuracy
of the experiment as a whole. Although the Control was not exposed to the prime, there was a
significant change in their responses to the survey. This could be accounted for by the fact that the
surveys were administered back to back, and they were exactly the same. There may have been a
threat to the internal validity of the experiment, specifically a testing effect, due to the fact that the
same measure was given back to back. This may have caused the participants to think they were
supposed to change their answers. It may be better to have a distractor in the Control room as well,
that does not correlate with the experiment in any way.
With this study, the results are completely counterintuitive and lead to many more
questions. One such question is whether or not the way that the prime was introduced played an
effect. It would be interesting to see if introducing the prime in a different way would elicit
different results. Another question is why the exaggerated statistics did not show significance in
analysis. When debriefing many of the participants, it was noted that they were relieved to find
that the numbers were exaggerated. Curiosity leads on to wonder what effect fear actually has on
individuals.
Limitations
In addition to the possible threat to internal validity in the Control condition, there were
limitations to this study in the way that the methodology had flaws. It was noticed when the
conduction of the experiment was taking place that it was difficult to keep consistent timing with
all of the participants and the different conditions, and that it was difficult to keep the same script
on each of the four nights. It would be beneficial, if the experiment was conducted again, to find a
way to correct the flaws in the methodology. Or, to at least have more than one researcher and a

script with specific times laid out for each part. Also, finding significance in the Control condition
needs to be corrected. It is thought that it would be beneficial to have a form of statistical
information for viewing, which was not related to the tested subject. For example, if testing alcohol
statistics use a statistic that does not relate to alcohol in any way. Another limitation of the study
was that there were only 25 participants. While the small sample size found significance, it would
have been more beneficial to have a larger, more representative sample than 25 college students,
the majority being freshman.
Conclusion
Priming and cognitive dissonance are important aspects to the field of Psychology. The
relationship between how they affect each other should be more thoroughly tested, in order to be
used to aid in further research of treatments of addictions and fears. Although the current study
had flaws and is counterintuitive in nature, it created interesting results that can lead to many more
interesting studies. It would be beneficial to the field to further test if priming causes cognitive
dissonance enough to change beliefs and or behavior.

References
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in a sample of female students at the university of UMM Al Qura. Education, 132(3),
641-663.
Dennis, I., & Perfect, T.J. (2013). Do stimulus–action associations contribute to repetition
priming? Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(1),
85-95.
FASTSTATS - Alcohol Use. (n.d.). Retrieved from http://www.cdc.gov/nchs/fastats/alcohol.htm
Glock, S., Muller, B.C.N., Krolak-Schwerdt, S. (2013). Implicit associations and compensatory
health beliefs in smokers: Exploring their role for behavior and their change through
warning labels. British Journal of Health Psychology. doi: 10.1111/bjhp.12023
Horner, A.J., & Hensom, R.N. (2009). Bindings between stimuli and multiple response codes
dominate long-lag repetition priming in speeded classification tasks. Journal of
Experimental Psychology: Learning, Memory, and Cognition, 35, 757-779.
Hoshino-Browne, E. (2012). Cultural variations in motivation for cognitive consistency:
Influences of self-systems on cognitive dissonance. Social & Personality Psychology
Compass, 6(2), 126-141.
Ihrke, M., Behrendt, J., Schrobsdorff, H., Visser, I., & Hasselhorn, M. (2013). Negative priming
persists in the absence of response-retrieval. Experimental Psychology, 60(1), 12-21.

Jarcho, J.M., Berkman, E.T., & Lieberman, M.D. (2011). The neural basis of rationalization:
Cognitive dissonance reduction during decision-making. Social Cognitive & Affective
Neuroscience, 6(4), 460-467.
Skowronski, J.J., Sedikides, C., Heider, J.D., Wood, S.E., Scherer, C.R. (2010). On the road to
self-perception: Interpretation of self-behaviors can be altered by priming. Journal of
Personality, 78(1), 361-391.
Statistics and Outcomes - Addiction Info - Drug Addiction Stats | Caron Pennsylvania. (n.d.).
Retrieved from https://www.caron.org/knowledge-library/statistics-
outcomes?WT_mc_id=GrantsPPC&gclid=CPbDj9PqiboCFQto7AodohQAaA
Voisin, D., Stone, J., & Becker, M. (2013). The impact of the antitobacco norm on the selected
mode of cognitive dissonance reduction. Journal of Applied Social Psychology, 43(1),
57-67.
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Experimental Psychology: Learning, Memory, and Cognition, 39(1), 140-158.

Appendix A
Age:
Sex:
Grade Level:
Major:
Please answer all questions as honestly as possible.
How often do you attend sporting events?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
7- Every chance offered
On average, how often do you spend your time studying for upcoming tests?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
How often do you drink alcoholic beverages?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
If given the choice between staying in or going out with friends, how often do you go out?
1- Never
2- Very rarely
3- Rarely
4- Sometimes

Appendix A (Continued)
5- Often
6- Very often
How often do you watch movies?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
On a scale of 1 to 5, how intoxicated do you become when drinking alcoholic beverages?
1- Never
2- Very rarely
3- Occasionally
4- Often
5- Every instance
How often do you go home for the weekend?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
Are you involved in on organization on campus?
Yes
No
If involved in an organization on campus, how often do you devote your time to the
organization?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often

How often do others influence the amount of alcohol you consume?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
How often do you work on the weekends?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
If you work on the weekends, how often do you still find time to spend on yourself?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
How often does alcohol impact your confidence?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often
How often do you spend your time volunteering?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often

How often do you spend your time focused on anything other than school work?
1- Never
2- Very rarely
3- Rarely
4- Sometimes
5- Often
6- Very often

Appendix B
Please answer all questions honestly your answers are confidential.
1. I believedrinkingalcohol onaschool nightis:
a. Awful,andshouldneverbeendone.
b. Okaydependingonthe situation.
c. Perfectlyacceptable.
d. I don’tdrink,andI have no opinion.
2. Alcohol isthe leadingcause of failure incollege age students.
a. True
b. False
3. If I see someone drinkingirresponsibly,Iwill:
a. Notsay anything,itistheirbusinesswhattheydowiththeirlife.
b. Go findsomeone whocantake care of it.
c. Talk to themandtry to help.
d. Who am I kidding,I’mrightthere withthem
4. Alcohol is:
a. A gatewaydrug.
b. Fine inmoderation.
c. A useful waytorelax.
d. I have no opinion.
5. On average Idrink:
a. Socially.
b. Everyday to relieve stress.
c. Occasionallyorrarely.
d. I don’tdrink.

Appendix C
53 percent of adults in the United
States have reported that one or more
of their close relatives has a drinking
problem

Appendix C (Continued)
72 percent of adults in the United
States have reported that one or more
of their close relatives has a drinking
problem

23.5 million people 12 years of age and
older needed treatment for an illicit
drug or alcohol abuse problem in 2009

32.5 million people 12 years of age and
older needed treatment for an illicit
drug or alcohol abuse problem in 2009

50,000
cases of
alcohol
overdose
are
reported
each year

80,000
cases of
alcohol
overdose
are
reported
each year

2009, an estimated 30.2 million people
12 or older reported driving under the

influence of alcohol at least once in the
past year

2009, an estimated 60.2 million people
12 or older reported driving under the
influence of alcohol at least once in the
past year

Number of alcoholic liver disease
deaths: 15,990
Number of alcohol-induced deaths,
excluding accidents and homicides:
25,692

Number of alcoholic liver disease
deaths: 75,990
Number of alcohol-induced deaths,
excluding accidents and homicides:
29,862

Percent of adults 18 years of age and
over who were current regular drinkers

(at least 12 drinks in the past year):
51.5%

over who were current regular drinkers

(at least 12 drinks in the past year):
71.5%
over who were current infrequent
drinkers (1-11 drinks in the past year):
13.6%

over who were current infrequent
drinkers (1-11 drinks in the past year):
33.6%

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