the effectiveness of advertisements using the social norms

The Effectiveness of Advertisements using the Social Norms Theory versus Guilt Appeals to

Motivate College Students

Erin Caruso

Joe Dreyer

Caroline Jacobs

Ashley Porcuna

Tori Ward

Louisiana State University

1

In today’s society, many people associate college as a time of unhealthy choices that

involve binge drinking, tobacco use and unprotected sex. These behaviors have negative

consequences that affect students, communities and families. For example, excessive binge

drinking can lead to a number of problems: car accidents, academic problems, depression, health

issues and even death (NIAAA, n.d.). Statistics show that 50 percent of college students, who

drink, also consume alcohol through binge drinking (NIAAA, n.d.). Tobacco can also lead to a

long line of health issues, including addiction, cancer, increased risk of many diseases and

infertility (CDC, 2013). In 2011, 18.9 percent of adults aged 18-24 were smokers (CDC, 2013).

Many universities and other organizations aim to reduce these unhealthy behaviors by creating

advertising campaigns to encourage prevention and healthy habits.

In order for prevention campaigns to resonate with college students, organizations need

to understand how to effectively communicate with their intended audience. While trying to

understand how to communicate adequately to the specific audience many questions arose. How

can you communicate a message to college students regarding the concerns of drinking and

smoking in ways that will promote action and change? What is the most effective way to

communicate the concerns of drinking and smoking to college students that will generate

positive results in awareness and action? Questions such as these will be instrumental in creating

an effective questionnaire to gauge college students’ perceptions and understand effective ways

to communicate with the audience.

Two strategies of communication will be discussed and analyzed in this experiment:

social norms theory and the use of guilt appeals. Both approaches are derived from different

views on how behaviors are influenced. It is important to understand why college students

participate in these unhealthy behaviors in order to create prevention strategies and promote

http://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption/moderate-binge-drinking

2

healthy habits. This topic is important in trying to discover which theory is more effective in

changing attitudes and behaviors about college alcohol consumption and tobacco use.

Our main objective for this experiment is to analyze and measure the amount of

motivation students have to process each advertisement. We hope that the results will help us

determine which technique LSU students feel more motivated by. We believe that LSU students

will process the advertisements that use a guilt appeal more than the social norms theory

advertisements. Support for this expectation comes from the previous use of guilt appeals in

advertisements. This method appeals to emotions and stimulates feelings of remorse (Dillard &

Pfau, 2002). We believe that a stronger reaction will be achieved by appealing to emotions

rather than by providing objective information on the actual norm.

Literature Review

Social Norms Theory

Social norms theory states that human behaviors are influenced by misperceptions of

peers’ attitudes and actions. This theory is mostly used to promote health related messages

regarding college student’s behaviors; this includes, but is not limited to, alcohol consumption,

sex, tobacco use and driving habits (Boston University, 2013). In recent years, many campaigns

have been used to change what students perceive as the social norm for different issues. This

theory aims to understand peer influences on individuals in order to correct their perception of an

issue and, ultimately, change their behaviors (Boston University, 2013). These influences create

two societal norms: the perceived norm and the actual norm. The perceived norm is what we

think it is that others do or believe. The actual norm is what they actually do and what they truly

3

believe. The gap between what is perceived and actual is a misperception, and this forms the

foundation for the social norms approach (Boston University, 2013).

Alan D. Berkowitz and H. Wesley Perkins, the first two researchers to propose this

theory, developed the social norms theory from an analysis they did on student alcohol use

patterns in 1986. The study showed that students on average overestimated the amount of their

peers who participated in unhealthy drinking habits (1986). They also concluded that this

misperception correlated with individuals’ drinking habits. The social norms theory tries to

correct the common misconceptions people place on certain matters by giving factual

information. The correction of this perception is hypothesized to lessen peer influences and in

effect change behaviors (1986).

Reactions to Social Norming Theory

A reaction is defined as the way someone acts or feels in response to something that

happens, is said, etc. (Gerrig & Zimbardo, 2002). Students have reacted to the social norms

approach in several different ways. While audiences have received and responded to some social

norms campaigns, other campaigns were doubted and ineffective. Often, due to misperceptions,

audiences are resistant to accept the information that is presented as being accurate (Berkowitz,

2004). This causes the campaign to be ineffective in correcting the misperceptions and,

furthermore, achieving any change in attitude or behavior.

Social Norm Theory: Attitudes and Opinions

An attitude is a tendency to respond to people, concepts, and events in an evaluative way

(Gerrig & Zimbardo, 2002). Similarly, an opinion is a view, judgment, or appraisal formed in the

mind about a particular matter (Gerrig & Zimbardo, 2002). Social norms theory describes three

4

common types of misperceptions that may have an affect on people’s attitudes and opinions.

Pluralistic ignorance is the most common misperception. Pluralistic ignorance occurs when the

majority of individuals falsely presume that most of their peers behave or think differently from

them when in actuality their attitudes and/or behavior are similar (Berkowitz, 2004). The second

misperception, false consensus, occurs when the minority of people with unhealthy attitudes

and/or behaviors incorrectly thinks that they are in the majority (Berkowitz, 2004). Finally, false

uniqueness occurs when individuals who are in the minority assume that their behavior is more

unique than it actually is (Berkowitz, 2004). These misperceptions can significantly influence a

person’s attitudes and opinions, which, in turn, affect a person’s behavior.

Social Norm Theory: Behaviors

A behavior is defined as one’s actions or the manner of conducting oneself (Gerrig &

Zimbardo, 2002). Social norms theory aims to understand influences that change people’s

behaviors. The theory states that behavior is influenced by perceptions of how other members of

social groups think or act. Social norms theory views peer influence as the primary source that

affects how people behave. (Berkowitz, 2004). This theory implies that due to pluralistic

ignorance, most college students drink moderately or not at all. They incorrectly assume that

other college students drink more than themselves and also more than they do in reality. This

causes individuals to stifle healthy attitudes and behaviors and encourages them to engage in the

unhealthy behaviors that are seen incorrectly as normative (Berkowitz, 2004).

Guilt Appeals

Guilt appeals influence a person’s beliefs or actions based on a feeling of remorse for a

particular behavior that the person has taken part in. Guilt appeals have been a method of

5

persuasion used for quite some time by organizations or advocates wishing to promote a cause or

a call to action for their message (Dillard & Pfau, 2002). The purpose of the guilt appeal is to

evoke emotions from a person, causing them to feel remorseful and in return change their

behavior or attitude and take action. Examples of this can be seen in advertisements that ask for

charitable donations. Some use video or pictures to display sickly individuals who are suffering

from starvation and offering a message that refers to the amount of food the viewer eats per day

compared to how much the people in the advertisement eat. Another example would be an

advertisement that advocates against cigarettes by targeting smokers and the effects second hand

smoke has on the population of non-smokers around them. The goal of guilt appeal is to trigger

an emotional response from persons generating a feeling of regret. In turn, the response would

ideally cause an individual to rethink his or her actions and react inversely to past actions (Block,

2006).

Reactions to Guilt Appeals

Guilt is an ideal emotion to manipulate in order to influence social behaviors. People

typically react to guilt by feeling remorseful, feeling responsible for the wrongdoing and wishing

they could take back their actions (Dillard & Pfau, 2002). There are two different ways that

people react when trying to eliminate the unwanted feeling of guilt. They will either try to reduce

the guilt or avoid the guilt. When an individual attempts to reduce the guilt they are more likely

to be persuaded than an individual who seeks to avoid the guilt. This is because higher levels of

perceived guilt facilitate persuasion in guilt reduction, where higher levels of perceived guilt

undermine persuasion in guilt avoidance (Block, 2006).

Guilt Appeals: Attitudes and Opinions

6

A person’s attitude about a certain value can affect how they respond to guilt appeals. If

an individual does not accept the norm or value that their behavior went against, then they may

accept responsibility for the action without experiencing guilt. When an action is inconsistent

with an individual’s typical standards, they are more likely to feel guilt and motivation to make

amends for the wrongdoing (Dillard & Pfau, 2002).

Guilt Appeals: Behaviors

Anticipated emotions have the ability to influence an individual’s intentions and actions.

Since the anticipation of guilt has the power to affect behavior, there is a possibility for

persuasion. A persuader can use guilt appeals to target the anticipated feeling in the audience in

order to sway their behaviors (Block, 2006). An individual’s behavior is ultimately what enables

the guilt appeal to work. When a person’s actions violate their standards, they feel guilty which

motivates them to change their behaviors. Guilt has a distinctive action-motivating aspect,

making it ideal for persuasion in advertisements (Dillard & Pfau, 2002).

Current research for both methods identifies responses and opinions from subjects that

have been exposed to each approach individually. In our study, we will examine the social norms

theory and the guilt appeal approach and their overall effectiveness in communicating messages

to the LSU student body. Our research will focus on the motivation LSU students have to

process each advertisement.

We speculate that aid guilt appeal approach will resonate with LSU students better.

Though we think both techniques will prove to be effective to a certain extent, we believe that

LSU students will feel more motivated to process guilt appeals. We hypothesize that correcting a

misperception about a social norm is not an appropriate method to connect with the students.

7

Approaching prevention campaigns with a guilt appeal will inspire and advocate changes in

unhealthy behaviors, particularly binge drinking and tobacco use.

Methods

Experiments are useful to demonstrate that something is true, to examine the validity of a

hypothesis, to discover new information, but most importantly to find out whether a cause and

effect relationship exists between variables. If an experiment is successfully performed, the

researcher will find an effect on the independent variable (Moore-Copple, 2013).

Design

This experiment is a one-shot case study. In a one-shot case study, there is no control.

The experiment is only performed once to find if the independent variable had an effect on the

dependent variable. The one-shot case study allows us to see why each participant chose the

pictures they did. Examples of prior research show that this method allows the researcher to see

if there is an effect on the independent variables. For example, one study wanted to see the

effects on if praising primary school children would help them do better in mathematics. To test

this, the researcher chose two pupils, praised them with a motivational class and then gave them

a math test. The results showed that praising the primary school children raised their math scores

(StatPac, 2004). The one-shot case study is the best type of experiment that will help researchers

find the best results and prove their hypothesis correct (Moore-Copple, 2013).

A questionnaire was used in this experiment. The questionnaire allowed us to show each

advertisement followed by scale questions. The questionnaire also allows us to control what

order the participant’s see the advertisements in.

8

Participants

The participants in this study were meant to be LSU students ages 18-24. We used this

sample because there is research that adults in this age group are more prone to regularly using

tobacco products and drinking excessively (Lee & Ferguson, 2002; Rigotti, 2000). This age

group was also chosen because the advertisements made by the LSU Student Health Center were

designed for members of the LSU student body. There were 70 participants who completed the

questionnaire. A frequency distribution was created for all discrete variables to show the

distribution of participants’ demographics in different categories. The test showed that females

(58, 81.7%) were more frequent than males (12, 16.9%). Caucasians (60, 84.5%) showed a

higher frequency than African Americans/Africans (3, 4.2%), Asian/Asian America/Pacific

Islander (3, 4.2%), Hispanic/Latino (2, 2.8%) or other ethnicities (2, 2.8%). Full-time students

proved to be the most frequent (60, 84.5%), as well as sophomores (19, 6.8%) and seniors (19,

26.8%). Mass communication majors were the most frequent (31, 43.7%) followed by

humanities and social sciences majors (15, 21.1%) and business majors (6, 8.5%).

Setting and Apparatus

We posted the questionnaire on our personal social media sites and under LSU’s Media

Effects Lab database. The survey was posted on the Qualtrics website on Nov. 14, 2013 and

reached 70 participants by Nov. 22, 2013. The data was then exported out of Qualtrics and was

entered into the student version of Statistical Software SPSS version 21.

Independent Variables

In this experiment, the independent variables were the two different types of

advertisements we manipulated. We wanted to determine whether social norms theory, the

exaggerated beliefs about the normal frequency and consumption habits of other students, or the

9

guilt appeal, making students feel guilty about their current consumption habits, motivated

participants to change their habits (Boston University School of Public Health, 2013). There was

no control group or manipulation checks in this experiment because the entire sample saw both

advertisements.

Dependent Variables

Our dependent variable that was measured was motivation to process each advertisement.

Testing this variable is important because it provides better understanding to which

advertisement is more effective in relating to college students. Determining if college students

are willing to process each different type of advertisement is important because processing the

advertisement is necessary for attitudes and behaviors to eventually be changed. In order to

measure this variable, we used a preexisting scale.

The scale used was the Involvement (Ad Message) original to Baker and Lutz in their

2000 research, “An Empirical Test of an Updated Relevance-Accessibility Model of Advertising

Effectiveness.” The scale is composed of seven different items to measure a person’s level of

motivation to understand the advertisement. Their scale was 1-7 but we adjusted it to a 1-5 scale.

We also took the existing scale and altered it to “strongly agree” and “strongly disagree” rather

than different the original anchors for each question. We removed one of the scale items, this

was the “I explicitly compared the content of the three advertisements as I listened to them.” The

alpha of Baker and Lutz’s scale was .90.

Procedure

This questionnaire was placed on Qualtrics and was accessible for eight days. A

convenient sample was gathered through word of mouth, personal social media platforms and the

Media Effects Lab database. When participants reached the first page they were presented a

10

consent form that was provided by Jensen Moore-Copple. It outlined the purpose of the

questionnaire and who was conducting it. It also informed the participants that there was no risk

in taking it and that all answers would be confidential. All participants in the sample are being

exposed to both the social norms theory advertisements and the guilt appeal advertisements.

The directions informed the participant that the survey would take approximately 15

minutes and asked each participant to fill out the questionnaire in its entirety. Advertisements

were shown in a specific order. The social norms advertisement about smoking was shown first

(Appendix A), the guilt appeal and smoking advertisement second (Appendix B), the social

norms advertisement about drinking was third (Appendix C), and the guilt appeal and drinking

advertisement was last (Appendix D). After each advertisement, the exact same six scale

questions were asked. The last section included questions about participant’s demographics.

Each set of questions will be placed on different pages of the survey and will include instructions

directing the participant to complete the survey to the best of their knowledge.

Results

This experiment was guided by the overall question of which advertisement approach, the

social norms theory or guilt appeal, will be more effective in motivating the participants to

process each advertisement. The hypothesis that was being tested in this experiment was that

guilt appeal advertisements would have a greater effect on motivating participants than the social

norms theory advertisements. In terms of analyzing data for the research question and

hypothesis, the statistical methods employed were a factor analysis, a reliability analysis and a

paired samples t-test.

11

Following recoding, a factor analysis was conducted to provide evidence of construct

validity and to confirm that some variables "hang together" statistically in order to create a new

scale. The factor analysis was conducted on six continuous variables using the principle

components method with Varimax rotation. The factor analysis produced two factors with

qualifying eigenvalues (over 1.0). Factor loadings were considered significant at .50 (p<.05).

Items that either did not load or loaded similarly on two or more factors were dropped.

A reliability analysis was run on the first factor (i.e., “Motivation”), which accounted for

38.95 percent of variance and included four items: intense, message matters, effective and

disregarded (Cronbach’s Alpha = -.033). A measure is considered reliable with an Alpha over

.70. The reliability analysis shows that the scale is not considered reliable, which is due to the

scale measuring for four separate independent variables. The scale would not be considered any

more reliable if any of the items were deleted.

A paired samples t-test is used when every participant is exposed to all levels of the

independent variable. In this case, all participants were exposed to two different types of

advertisements, which were the independent variables of the experiment. A paired samples t-test

was used to examine the differences in the dependent variable of motivation between the social

norms advertisements and the guilt advertisements. Results indicated that there is a significant

difference between the two sets of advertisements, t (70) = -4.63, p < .05. The guilt

advertisements showed higher motivation among the participants (M = 27.32, SD = 2.98) as

compared to the social norms advertisements (M = 22.69, SD = 3.22). All tables and charts can

be seen in Appendix F.

12

Based on the findings from the paired-samples t-test, our hypothesis that guilt appeal

advertisements would have a greater effect on motivating participants than social norms theory

advertisements was supported. From this experiment, it can be generalized that college students

respond more strongly to advertisements that embrace guilt appeals with intense images and

wording than social norming advertisements that use primarily statistics and logic. This is

possibly due to the idea that college students are more likely to respond to emotion rather than

logic. In the future, we hope to find if guilt appeals work when used in advertisements that

contain messages other than smoking and drinking warnings. Also, we would like to see if an

emotional appeal, such as a guilt appeal, would be as effective on an older audience.

Discussion

Our overall research question for this experiment was a simple comparison: Which

advertisement approach, the social norms theory or guilt appeals, will be more effective in

motivating the participants to process each advertisement? The results show that the social norms

approach and emotional appeals both independently appear to have been successful in changing

attitudes on average. We hypothesized that the emotional appeal, more specifically a guilt

appeal, would have more of an influence on college students.

In this experiment, we saw that guilt appeal advertisements generated higher motivation

among college students than social norms theory advertisements. This may be because people are

typically more likely to be persuaded by emotional appeals rather than logical appeals (Dillard &

Pfau, 2002). The use of images and captions that embraced the idea of parental disappointment

could have also played a part in the guilt advertisements having higher motivation. Many college

students seek to make their parents proud, and if their actions are inconsistent with their parents’

standards, then they may experience guilt and react by being motivated to alter their behaviors

13

(Dillard & Pfau, 2002). Another possible reason that guilt appeals were more effective in

motivating college students is that the guilt appeal advertisements used strong, attention-

grabbing images, whereas the social norms advertisements had no strong visuals. Due to the lack

of existing information on guilt appeals, we found no previous research that addressed the

effectiveness of guilt appeals versus social norms theory. However, our experiment results were

consistent with our research that guilt appeals have a distinct action- motivating aspect (Dillard

& Pfau, 2002).

Our experimental methods had many strengths. The first is that it was easy and

convenient to distribute the questionnaire and gain a larger sample. Our questionnaire was also

simple and easy to understand. The strength of our results is supported by the results of the

paired samples t-test. Results indicated that there is a significant difference between the two sets

of advertisements, t (70) = -4.63, p < .05. The guilt advertisements showed higher motivation

among the participants (M = 27.32, SD = 2.98) as compared to the social norms advertisements

(M = 22.69, SD = 3.22). The significant difference between the motivation to process the two

sets of advertisements could potentially have theoretical implications regarding which type of

advertisement would be more effective in changing attitudes and behaviors.

Our findings are important because many universities and other organizations aim to

reduce unhealthy behaviors, like smoking and binge drinking, by creating advertising campaigns

to encourage prevention and healthy habits. In order for prevention campaigns to resonate with

college students, organizations need to understand how to effectively communicate with their

intended audience. Our research shows in this particular instance that LSU students better

processed the guilt appeal advertisements. This knowledge will allow the LSU Student Health

Center to create better advertisements that will effectively communicate their message to their

14

intended audience.

The design of our study is a within subjects design involving a one-shot case study.

Limitations that arose with this type of study include the inability to measure a comparison since

there is only one group. Since there is only one group, there is no basis for comparison of those

exposed and those not exposed to the stimuli (Connaway & Powell, 2010). We were unable to

determine if one stimulus was favored over another based on exposure or perceived notions

toward an appeal prior to exposure. Limitations for collecting data in this study were restricted to

each participant’s interpretation of the questions asked. While participants were able to identify

whether he or she agrees/disagrees more or less with a motivation, we did not determine the

reasons why each participant agreed or disagreed with each stimulus as we were unable to obtain

qualitative dat. Potential biases are difficult to eliminate in this experiment due to the fact that

the researchers performing the experiment are similar to the sample being tested. Since the

researchers are a part of the population being tested, we are able to tailor a message that we

believe is more appealing to our population. While it does not ensure a biased favor for the

researchers’ ads, it does present the potential possibility. Limitations for generalizing our

findings cannot extend outside the LSU community, as all participants involved in the

experiment are students of LSU.

If this experiment were to continue extended findings, one may suggest using focus

groups. Focus groups can help you discover the real issues that concern people, and they

normally provide researchers with open-ended, free responses (Paine, 2011). Additionally, focus

groups would allow us to explain the message we are trying to convey rather than a survey where

the participants may not understand what point we are trying to get across. All four ads would be

shown for the participants to see, along with a series of questions. There would be a discussion

15

among the students to determine which ad affected the students more and which ads they

preferred, either the guilt appeal or the social norms theory. Due to the fact that the participants

took the questionnaire online, there was no control of the participants’ environment, which could

have been a distraction from the experiment.

A way to improve the study is to get more participants for the experiment. Another

improvement would be to have a more diverse sample. This would give us the ability to have

more accurate results. This would allow us to generalize the results on a broader spectrum. Also,

working on the experiment for a longer amount of time would have given us the ability to “pilot”

or pretest our questionnaire before exposing it to the experimental sample.

16

Appendix

Appendix A

17

Appendix B

18

Appendix C

19

Appendix D

20

Appendix E

Instructions for Questionnaire

Students from MC 3020 are conducting the following questionnaire. This questionnaire will take

10-15 minutes to complete.

You will be shown four individual advertisements. Please view each advertisement carefully,

examining all elements, and then respond to the following questions as quickly and accurately as

possible. Be sure to fill these questions out completely.

There will be a section of demographic questions at the end of the questionnaire. Please fill out

all questions of this section.

Questionnaire

1. This ad affected my opinion of the topic.

Strongly agree Strongly disagree

1 2 3 4 5

1. This ad motivates me to stop participating in the activity.

Strongly disagree Strongly agree

1 2 3 4 5

2. The message in this ad was intense.

Strongly agree Strongly disagree

1 2 3 4 5

3. The message of this advertisement mattered to me.


1 2 3 4 5

4. I think this advertisement is effective.

Strongly agree Strongly Disagree

1 2 3 4 5

5. I disregarded this advertisement.


1 2 3 4 5

21

Demographics:

Gender:

1. Male

2. Female

Ethnicity:

1. African American/African

2. Asian/Asian American/Pacific Islander

3. Caucasian

4. Hispanic/Latino

5. Middle Eastern/Indian/Arabian

6. Native American/Alaskan Indian

7. Other

LSU affiliation:

8. Part-time student

9. Full-time student

10. Alumni

11. Other

College/Major (if applicable):

1. Agriculture

2. Art and Design

3. Business

4. Coast and Environment

5. Engineering

6. Human Sciences and Education

7. Humanities and Social Sciences

8. Mass communication

9. Music and Dramatic Arts

10. Science

Classification (if applicable):

1. Freshman

2. Sophomore

3. Junior

4. Senior

22

Thank you for completing this survey. Two of the advertisements you saw were produced by the

LSU Student Health Center and the other two guilt appeal advertisements were produced by the

student’s of a public relations research class. Your participation will aid in determining which

types of advertisements are more effective.

23

Appendix F

Frequencies

27.32

22.69

0

5

10

15

20

25

30

Guilt Ads Social Norms Ads

Motivation

Motivation

Notes

Output Created 23-NOV-2013 23:31:48

Comments

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24

Statistics

Gender Ethnicity LSUaffiliation Major Classification

N Valid 70 70 70 68 65

Missing 1 1 1 3 6

Mean 1.83 3.01 2.17 6.96 2.66

Median 2.00 3.00 2.00 8.00 3.00

Mode 2 3 2 8 2a

Std. Deviation .380 .843 .613 1.988 1.079

Skewness -1.782 2.517 2.220 -1.275 -.125

Std. Error of Skewness .287 .287 .287 .291 .297

Kurtosis 1.209 14.405 4.900 1.577 -1.266

Std. Error of Kurtosis .566 .566 .566 .574 .586

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Frequency Table

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Gender


Percent

Valid

male 12 16.9 17.1 17.1

female 58 81.7 82.9 100.0

Total 70 98.6 100.0

Missing System 1 1.4

Total 71 100.0

25

Valid

African American/African 3 4.2 4.3 4.3

Asian/Asian

American/Pacific Islander

3 4.2 4.3 8.6

Caucasian 60 84.5 85.7 94.3

Hispanic/Latino 2 2.8 2.9 97.1

other 2 2.8 2.9 100.0

Total 70 98.6 100.0


Total 71 100.0

LSUaffiliation


Percent

Valid

Part-time student 2 2.8 2.9 2.9

Full-time student 60 84.5 85.7 88.6

Alumni 2 2.8 2.9 91.4

other 6 8.5 8.6 100.0

Total 70 98.6 100.0


Total 71 100.0

Major


Percent

Valid

Agriculture 2 2.8 2.9 2.9

Business 6 8.5 8.8 11.8

Engineering 4 5.6 5.9 17.6

Human Sciences and

Education

5 7.0 7.4 25.0

Humanities and Social

Sciences

15 21.1 22.1 47.1

Mass communication 31 43.7 45.6 92.6

Science 5 7.0 7.4 100.0

Total 68 95.8 100.0

26


Total 71 100.0

Classification


Percent

Valid

Freshman 11 15.5 16.9 16.9

Sophomore 19 26.8 29.2 46.2

Junior 16 22.5 24.6 70.8

Senior 19 26.8 29.2 100.0

Total 65 91.5 100.0


Total 71 100.0

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Factor Analysis

Notes

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Communalities

28

Total Variance Explained

Compone

nt

Initial Eigenvalues Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Tota

l

% of

Varianc

e

Cumulativ

e %

Tota

l

% of

Varianc

e

Cumulativ

e %

Tota

l

% of

Varianc

e

Cumulativ

e %

1 2.74

1

45.682 45.682 2.74

1

45.682 45.682 2.33

7

38.952 38.952

2 1.09

6

18.274 63.956 1.09

6

18.274 63.956 1.50

0

25.004 63.956

3 .704 11.740 75.696

4 .642 10.695 86.391

5 .483 8.056 94.448

6 .333 5.552 100.000

Extraction Method: Principal Component Analysis.

Initial Extraction

LSUsmokeChangedOpini

on

1.000 .740

LSUsmokeParticipating 1.000 .872

LSUsmokeIntense1 1.000 .543

LSUsmokeMessageMatter

s

1.000 .588

LSUSmokeEffective1 1.000 .524

LSUsmokeDisregarded 1.000 .571

Extraction Method: Principal Component

Analysis.

Component Matrixa

Component

1 2


on

.765 .394

LSUsmokeParticipating .446 .820

LSUsmokeIntense1 .657 -.334


s

.704 -.305

LSUSmokeEffective1 .718 -.087

LSUsmokeDisregarded -.717 .237

29

Rotated Component Matrixa

Component

1 2


on

.469 .721

LSUsmokeParticipating -.019 .933

LSUsmokeIntense1 .736 .035


s

.762 .083

LSUSmokeEffective1 .667 .280

LSUsmokeDisregarded -.741 -.150


Analysis.

Rotation Method: Varimax with Kaiser

Normalization.

a. Rotation converged in 3 iterations.

GET

FILE='C:\Users\Owner\Documents\SOPH-Semester

1\PR\Experiment\AdComparisonResults.sav'.

DATASET NAME DataSet1 WINDOW=FRONT.

RELIABILITY

/VARIABLES=LSUsmokeIntense1 LSUsmokeMessageMatters LSUSmokeEffective1

LSUsmokeDisregarded

/SCALE('Motivation') ALL

/MODEL=ALPHA

/SUMMARY=TOTAL.

Reliability


Analysis.

a. 2 components extracted.

Component Transformation

Matrix

Component 1 2

1 .869 .496

2 -.496 .869

Extraction Method: Principal

Component Analysis.

Rotation Method: Varimax with

Kaiser Normalization.

30

[DataSet1] C:\Users\Owner\Documents\SOPH-Semester

1\PR\Experiment\AdComparisonResults.sav

Scale: Motivation

Reliability Statistics

Cronbach's Alphaa N of Items

-.033 4

Notes

Output Created 03-DEC-2013 16:09:08

Comments

Input

Data


Semester



Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 71

Matrix Input


Definition of Missing User-defined missing values are treated as

missing.

Cases Used Statistics are based on all cases with valid

data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=LSUsmokeIntense1


LSUSmokeEffective1

LSUsmokeDisregarded

/SCALE('Motivation') ALL

/MODEL=ALPHA

/SUMMARY=TOTAL.



Case Processing Summary

N %

Cases

Valid 71 100.0

Excludeda 0 .0

Total 71 100.0

a. Listwise deletion based on all variables in the

procedure.

31

a. The value is negative due to a

negative average covariance

among items. This violates

reliability model assumptions. You

may want to check item codings.

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's Alpha

if Item Deleted

LSUsmokeIntense1 9.39 1.785 .381 -1.035a

LSUsmokeMessageMatters 8.75 2.478 .194 -.440a

LSUSmokeEffective1 8.99 2.557 .215 -.449a

LSUsmokeDisregarded 9.25 5.706 -.534 .662

a. The value is negative due to a negative average covariance among items. This violates reliability model

assumptions. You may want to check item codings.

COMPUTE SNsmoke=LSUsmokeIntense1 + LSUsmokeMessageMatters +

LSUSmokeEffective1 + LSUsmokeDisregarded.

EXECUTE.

COMPUTE GuiltSmoke=MC3020smokeIntense1 + MC3020smokeMessageMatters +

MC3020smokeEffective1 + MC3020smokeDisregarded.

EXECUTE.

COMPUTE SNdrink=LSUdrinkIntense1 + LSUdrinkMessageMatters +

LSUdrinkEffective1 + LSUdrinkDisregarded.

EXECUTE.

COMPUTE GuiltDrink=MC3020drinkIntense1 + MC3020drinkMessageMatters +

MC3020drinkEffective1 + MC3020drinkDisregarded.

EXECUTE.

COMPUTE SNads=SNsmoke + SNdrink.

EXECUTE.

COMPUTE GuiltAds=GuiltSmoke + GuiltDrink.

EXECUTE.

T-TEST PAIRS=SNads WITH GuiltAds (PAIRED)

/CRITERIA=CI(.9500)

/MISSING=ANALYSIS.

T-Test

Notes

Output Created 03-DEC-2013 16:18:39

Comments

32

[DataSet1] C:\Users\Owner\Documents\SOPH-Semester


Paired Samples Correlations

N Correlation Sig.

Pair 1 SNads & GuiltAds 71 .369 .002

Paired Samples Test

Paired Differences t df Sig. (2-

tailed) Mean Std.

Deviation

Std. Error

Mean

95% Confidence Interval

of the Difference

Lower Upper

Pair

1

SNads -

GuiltAds

-

4.63380

3.48974 .41416 -5.45981 -3.80780 -

11.189

70 .000

Input

Data


Semester



Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 71


Definition of Missing User defined missing values are treated as

missing.

Cases Used

Statistics for each analysis are based on the

cases with no missing or out-of-range data

for any variable in the analysis.

Syntax

T-TEST PAIRS=SNads WITH GuiltAds

(PAIRED)

/CRITERIA=CI(.9500)

/MISSING=ANALYSIS.



Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1 SNads 22.6901 71 3.21866 .38198

GuiltAds 27.3239 71 2.98460 .35421

33

References

Baker, W. E., & Lutz, R. (2009). An Empirical Test of an Updated Relevance-Accessibility

Model of Advertising Effectiveness. JA, 29 (1), 1-14

Berkowitz, A. (2004, August). The Social Norms Approach: Theory, Research, and

Annotated Reaction. (n.d.). Merriam-Webster.com. Retrieved from: http://www.merriam-

webster.com/dictionary/reactionBibliography. Retrieved from

http://www.alanberkowitz.com/articles/social_norms.pdf.

Block, L. G. (2005). Self-Referenced Fear and Guilt Appeals: The Moderating Role of SeIf-

Construal. Journal Of Applied Social Psychology, 35(11), 2290.

Boston University School of Public Health. (2013, January 22). Behavioral Change Models:

Social Norms Theory. Retrieved from http://sphweb.bumc.bu.edu/otlt/MPH-

Modules/SB/SB721-Models/SB721-Models7.html#socialnormstheory

Center for Disease Control and Prevention [CDC]. (2013, June 24). Smoking and Tobacco Use:

Health Effects of Cigarette Smoking. Retrieved from:

http://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/effects_cig_smokin

g/index.htm

Delahaye, P. K. (2011). Measure what matters: Online tools for understanding customers, social

media, engagement, and key relationships. Hoboken, N.J: John Wiley & Sons Inc.

Dillard, J. P., & Pfau, M. (2002). Guilt as a Mechanism of Persuasion. In M. H. Seawell

(Ed). The Persuasion Handbook: Developments in Theory and Practices (pp. 329-343).

Thousand Oaks, CA: Sage Publications, Inc.

Gerrig, R.J. & Zimbardo, P.G. (2002).Glossary. Psychology And Life, 16e. Retrieved from:

34

http://www.apa.org/research/action/glossary.aspx#b

National Institute on Alcohol Abuse and Alcoholism [NIAAA]. Overview of Alcohol

Consumption. Retrieved from

http://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption

StatPac (2004). The Experimental Method. Retrieved November 12, 2013, from

http://www.learningdomain.com/PXGS6102Experimental2.html