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Influence of Message Framing, Involvement, and Nicotine Dependence on Effectiveness of Anti-Smoking Public Service Announcements

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Title:
Influence of Message Framing, Involvement, and Nicotine Dependence on Effectiveness of Anti-Smoking Public Service Announcements
Creator:
Jung, Wan
Place of Publication:
[Gainesville, Fla.]
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University of Florida
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english
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Thesis/Dissertation Information

Degree:
Master's ( M.Adv.)
Degree Grantor:
University of Florida
Degree Disciplines:
Advertising
Journalism and Communications
Committee Chair:
Villegas, Jorge
Committee Members:
Kim, Hyojin
Cho, Chang-Hoan
Graduation Date:
8/9/2008

Subjects

Subjects / Keywords:
Addiction ( jstor )
Cigarettes ( jstor )
Consumer research ( jstor )
Framing effects ( jstor )
Mathematical dependent variables ( jstor )
Motivation ( jstor )
Persuasion ( jstor )
Psychological attitudes ( jstor )
Statistical models ( jstor )
Tobacco use disorder ( jstor )
Journalism and Communications -- Dissertations, Academic -- UF
addiction, framing, involvement, psa, smoking
City of Gainesville ( local )
Genre:
Electronic Thesis or Dissertation
born-digital ( sobekcm )
Advertising thesis, M.Adv.

Notes

Abstract:
Studies examining message framing effects have yielded conflicting findings. Some studies find that positively framed messages are more persuasive than negatively framed messages. Other studies report reverse outcomes. This study tried to find the reasons for the conflicting results in message framing research, and found that the effects of message framing was varied depending on the involvement level and smoking addiction level. The study suggests that subjects who are more involved with smoking issue prefer negative messages, while subjects who are less involved with smoking issue prefer positive messages. The second finding is that the more dependent on cigarette smoking subjects are, the more favorable attitude toward negatively framed PSAs they tend to have. The contrary is true when anti-smoking PSAs are framed positively. ( en )
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In the series University of Florida Digital Collections.
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Includes vita.
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Includes bibliographical references.
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This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
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Thesis (M.Adv.)--University of Florida, 2008.
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Adviser: Villegas, Jorge.
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RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31
Statement of Responsibility:
by Wan Jung.

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LIST OF FIGURES

FiMr page

3-1. Positively Framed PSA............... ...............42..

3-2. Negatively Framed PSA ................ ...............43................









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Advertising

INFLUENCE OF MESSAGE FRAMING, INVOLVEMENT, AND NICOTINE
DEPENDENCE ON EFFECTIVENESS OF ANTI-SMOKING PUBLIC SERVICE
ANNOUNCEMENT S

By

Wan Seop Jung

August 2008

Chair: Jorge Villegas
Major: Advertising

Studies examining message framing effects have yielded conflicting findings. Some

studies find that positively framed messages are more persuasive than negatively framed

messages. Other studies report reverse outcomes. This study tried to Eind the reasons for the

conflicting results in message framing research, and found that the effects of message framing

was varied depending on the involvement level and smoking addiction level. The study suggests

that subj ects who are more involved with smoking issue prefer negative messages, while

subjects who are less involved with smoking issue prefer positive messages. The second Einding

is that the more dependent on cigarette smoking subj ects are, the more favorable attitude toward

negatively framed PSAs they tend to have. The contrary is true when anti-smoking PSAs are

framed positively. Other findings and implications are discussed.









attempting to find other devices to abate the prevalence of smoking instead of restriction of

tobacco advertising. Therefore, researchers began to study anti-smoking PSAs.

A substantial number of studies have supported the efficacy of anti-smoking PSAs

empirically and practically. Goldman and Glantz (1998) found that anti-smoking PSAs had an

influence on decline in cigarette consumption in California, Massachusetts, and Arizona.

Popham and Potter (1993) did a research to test whether state- or government-sponsored PSAs

were effective by using the California Department of Health Service sponsored anti-smoking

PSAs, conducted from 1990 to 1991. They concluded that the government-sponsored PSAs

helped smokers to quit significantly.

In recent years, researchers tried to test anti-smoking PSAs using different target groups

(e.g., youth, adolescent, and adult) instead of general population. For instance, Seigel and Biener

(2000) reported that anti-smoking PSAs played a role in decrease of cigarette consumption

among youth in Massachusetts. Other studies found that anti-smoking PSAs were persuasive to

reduce tobacco consumption both for adults and for youth in California (Hu, Sung, & Keeler,

1995; Pierce et al., 1998). Bauer et al. (2000) suggested that anti-smoking PSAs have reduced

and prevented youth cigarette smoking. A result showed that anti-smoking PSAs could have an

effect both on adolescents and on young adults in Florida (Sly, Trapido, & Ray, 2002).

There has been an attempt to understand the persuasion processes that occur when

smokers are exposed to anti-smoking PSAs. For example, a Florida baseline research revealed

that anti-smoking PSAs were effective to change attitude and beliefs toward cigarette smoking

and smoking behavior among youth, and helped reduce the prevalence of smoking among youth

(Sly, Heald, & Ray, 2001). The study was the evidence that anti-smoking PSAs had an influence

on not only changing attitude and belief toward smoking behavior but smoking cessation.









As for the relationship between motivation and message framing, the causality that

individuals' motivation to process information affects the effectiveness of message framing was

supported (Kanouse, 1984; Maheswaran & Meyers-Levy, 1990; Weinberger, Allen, & Dillon,

1981). The more motivated individuals are, the more favorable attitude toward negatively framed

PSAs formed, while the less motivated individuals are, the more favorable attitude toward

positively framed PSAs. Therefore, nicotine dependence has an impact on perceived risk,

perceived risk relates to motivation. In addition, the motivation would moderate message

framing effects. Finally, such relationships affect attitude toward anti-smoking PSAs.

H2: The relationship between message framing effects and attitude toward anti-smoking
PSAs is moderated by nicotine dependence.

H2.1: For smokers who are highly dependent on smoking, an anti-smoking PSA is more
persuasive when it is framed negatively.

H12.2: For smokers who are less dependent on smoking, an anti-smoking PSA is more
persuasive when it is framed positively.










Table 4-11i. Regression of H2
Source B SE P t Sig.
(Constant) 4.85 0.52 9.36 0.000
Addiction* 0.02 0.14 0.03 0.14 0.892
Framing** -0.16 0.71 -0.05 -0.23 0.820
Interaction -0.38 0.19 -0.55 -2.04 0.048
*Nicotine Addiction: 1 (low) to 10 (high)
**Message Framing: 0 (negatively framed message), 1 (positively framed message)

Table 4-12. Follow-up Analyses for Interaction in H2
Message Framing IV B SE P t Sig.
Negative Nicotine Dependence .019 .146 .028 .133 .895
R= .028, R2 =.001, R2Ad = -.045
Positive Nicotine Dependence -.358 .115 -.570 -3.104 .006
R= .570, R2 =.325, R2Ad = .291











Hu, T., Sung, J., & Keeler, T. E. (1995). Reducing cigarette consumption in California: tobacco
taxes vs. an anti-smoking media campaign. American Journal of Public Health, 85(9),
1218-1222.

John, U., Meyer, C., Rumpf, H. J., & Hapke, U. (2003). Relation among stage of change,
demographic characteristics, smoking history, and nicotine dependence in an adult German
population, Preventive M~edicine, 37, 368-374.

Kanouse, D. E. (1984). Explaining negativity biases in evaluation and choice behavior: Theory
and research. Advances in Consumer Research, 11(1), 703-708.

Kardes, F. R. (1988). Spontaneous inference processes in advertising: The effects of conclusion
omission and involvement persuasion. Journal of Consumer Research, 15(September), 225-
233.

Kithberger, A. (1998). The influence of framing on risky decisions: a meta-analysis.
Organizational Behavior and Human Decision Processes, 75(1), 23-55.

Lau, R. R. (1985). Two explanations for negativity effects in political behavior. American
Journal of Political Science, 29(1), 119-138.

Levin, I. P. (1987) Associative effects of information framing. Bulletin of the Psychonomic
Society, 25, 85-86.

Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All framed are not created equal: a critical
review of differences in valence framing effects. Organizational Behavior and Human
Decision Processes, 76, 149-188.

MacKenzie, S. B., Lutz, R. J., & Belch, G. (1986). The role of attitude toward ad as a mediator
of advertising effectiveness: a test of comparing explanations. Journal of2arketing
Research. 23(May), 130-143.

MacInnis, D. J., Moorman, C., & Jaworski, B. J. (1991). Enhancing and measuring consumers'
motivation, opportunity, and ability to process brand information from ads. Journal of
Marketing, 55(4), 32-53.

Maheswaran, D., & Meyers-Levy, J. (1990). The influence of message framing and issue
involvement. Journal of2arketing Research, 27(3), 361-367.

Manfredi, C., Lacey, L., Warnercke, R., & Buis, M. (1992). Smoking-related behavior, beliefs,
and social environment of young black women in subsidized public housing in Chicago.
American Journal of Public Health, 82(2), 267-272.

MayoClinic. (2006, October 26). Nicotine dependence. Retrieved March 20, 2008, from
http ://www.mayoclinic.com/health/nicotine-depedne/S007.









CHAPTER 5
DISCUSSION AND CONCLUSION

Discussion

This study was designed to resolve the conflicting findings of message framing effects

and identify the variables that have an impact on the effectiveness of message framing. Overall,

the results are compatible with this study's grand assumption that involvement level and cigarette

addiction level moderate message framing effects.

In the H1, the contention of this study is that involvement level moderates the

effectiveness of either positively or negatively framed anti-smoking PSAs. This contention is

based on Petty and Cacioppo's model and previous research about overweighting of negative and

positive messages (Kanouse, 1984; Petty & Cacioppo, 1986; Weinberger, Allen, & Dillon, 1981;

Wright, 1981). Consistent with the H1, the involvement level indicates favorability of either a

positively framed PSA or a negatively framed one. These results are consistent with previous

research dealing with involvement and message framing (Maheswaran & Meyers-Levy, 1990)

that proposed the moderating role of involvement.

However, after conducting separate analyses by selecting cases whether subj ects were

exposed to either negatively or positively framed message, H1 was partially supported.

Specifically, in the H1.1, the following was predicted: Under high involvement conditions, an

anti-smoking PSA is more persuasive when it is framed negatively. Although an intended

direction was found, it was not statistically significant. Therefore, H1.1 was not supported. In the

H1.2, the following was predicted: Under low involvement conditions, an anti-smoking PSA is

more persuasive when it is framed negatively. Intended significant results were found. Thus,

H1.2 was supported.











LIST OF TABLES


Table page

4-1 Manipulation Check of Positively Framed Message for Item 1 in H1 Testing ........._.........3 5

4-2 Manipulation Check of Negatively Framed Message for Item 2 in H1 Testing. ........._.......3 5

4-3 Descriptive Statistics of H 1 .............. ...............35....

4-4 M odel Statistics of H 1 .............. ...............35....

4-5 Regression of H1............... ...............35..

4-6 Follow-up Analyses for Interaction in H1 .............. ...............36....

4-7 Manipulation Check of Positively Framed Message for Item 1 in H12 Testing ................... .36

4-8 Manipulation Check of Negatively Framed Message for Item 2 in H12 Testing. ................. .36

4-9 Descriptive Statistics of H2 .............. ...............36....

4-10 M odel Statistics of H2 .............. ...............36....

4-11 Regression of H2............... ...............37..

4-12 Follow-up Analyses for Interaction in H12 .............. ...............37....









CHAPTER 1
INTTRODUCTION

Cigarette smoking has great societal and clinical importance (American Cancer Society,

2001). According to the American Cancer Society (2008), smoking was responsible for

approximately 559,3 12 U.S. premature deaths in 2005. Moreover, a number of non-smokers

suffered from second-hand smoking. A sizable percentage of youth (20%-30%) begin smoking

as early as middle school (Centers for Disease Control [CDC], 1998). A large number of

smokers initiate cigarette smoking during youth-88% by age 18 (U. S. Department of Health and

Human Service [USDHHS], 1994), with approximately fifty percent becoming addicted (CDC,

1991). Smoking behavior in middle school has a tendency to last for a long time due to the

smoking addiction (Oei, 1987). Anti-smoking PSAs are useful due to its preventive effects

(USDHHS, 1994). In addition to the health-related damages, other economical and

environmental damages are caused by smoking. The following are examples of the damages:

productivity decrease due to cigarette breaks, dirtiness from cigarette butts, and budgetary

allocations for anti-smoking. Therefore, much research of anti-smoking Public Service

Announcements (PSAs) tried to abate the prevalence of smoking.

Schneider et al. (1981) estimated the effects of the Faimness Doctrine, which was a

Federal Communications Commission (FCC) regulation regarding broadcasting license

acquisition. Tobacco companies were subj ected to restriction on inserting their advertisements in

radio or TV because of the Fairness Doctrine. After the Faimness Doctrine, cigarette consumption

decreased from 1967 to 1970. Researchers have experienced that the restriction of tobacco

advertisements had an influence on decrease of cigarette consumption. However, in 1984, the

Supreme Court recommended the FCC to abolish the Faimness Doctrine because it harmed the

public interest and violated the First Amendment. Then, there had been an emerging interest in












LIST OF REFERENCES


American Cancer Society. (2008, February 20). Cancer facts and figures 1996: Tobacco use.
Retrived March 13, 2008, from http ://www.cancer.org/statistics/96cff/tobaccohm

American Psychiatric Association. ( 1994). Diagnostic and statistical manual of mental disorders,
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Badura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological
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Bauer, R. A. (1960). Consumer behavior as risk taking. In Hancock R. (Ed.), Dynamic
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Bauer, U. E., Johnson, T. M., Hopkins, R. S., & Brooks, R. G. (2000). Changes in youth
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Braun, K. A., Gaeth, G. J., & Levin, I. P. (1997). Framing effects with differential impact: the
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Beaudoin, C. E. (2002). Exploring antismoking ads: appeals, themes, and consequences. Journal
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Buto, C. P. (1987). The framing of buying decisions. Journal of Consumer Research, 14(3), 301-
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Block, L. G., & Keller, P. A. (1995). When to accentuate the negative: the effects of perceived
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Bock, B. C., Becker, B., Niaura, R., & Partridge, R. (2000). Smoking among emergency chest
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Cacioppo, J. T., & Petty R. E. (1979). Effects of message repetition and position on cognitive
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Connection of Nicotine Dependence Level with Message Framing

Bauer (1960) presented the construct of perceived risk. And it was introduced to the

marketing literature. Perceived risk is conceptualized as the perspective that "the amount that

would be lost if the consequences of an act were not favorable, and the individual's subjective

feeling of certainty that the consequences will be unfavorable" (Cunningham, 1967, p.37).

Similarly, Stone and Winter (1987) considered risk as an expectation of loss. In connection with

this study, perceived risk regarding smoking can be re-conceptualized as the perspective how

well individuals understand the risk of smoking.

The second hypothesis focuses on the nicotine dependence level as a moderator of

message framing effects by using a sample of smokers. In Wong and McMurray (2002) study,

the nicotine dependence level was related to one's perceived health risk level. In addition,

Rindfleisch and Crockett (1999) tested the relationship between nicotine dependence and

perceived risk by using a college student sample. Specifically, the less dependent on cigarette

smoking subj ects are, the lower level of perceived risk they tend to have. Conversely the more

dependent on cigarette smoking subj ects are, the higher level of perceived risk they tend to have.

A number studies proposed that a perceived health risk level be strongly related to one's

motivation to process health-related information (Block & Keller, 1995; Rothman & Salovey,

1997; Umphrey, 2003). In addition, Bock et al. (2000) revealed the relationship between risk

perception and motivation. They found that subj ects who had higher risk perceptions were more

motivated to process smoking cessation information and consult doctors to discuss smoking

issues than those who had lower risk perceptions. The sum of the relationship among nicotine

dependence, perceived risk and motivation is that highly addicted subj ects are more motivated to

process information than less addicted subj ects, while less addicted subj ects are less motivated to

process information than highly addicted subj ects.









In the H2, the contention of this study is that smoker's nicotine dependence level

moderates the effectiveness of either positively or negatively framed anti-smoking PSAs. This

contention is based on the relationship among nicotine dependence, perceived risk, motivation,

and message framing. The causalities are that nicotine dependence has an impact on perceived

risk (Rindfleisch & Crockett, 1999; Wong & McMurray, 2002), perceived risk relates to

motivation (Block & Keller, 1995; Rothman & Salovey, 1997; Bock et al., 2000; Umphrey,

2003). In addition, the motivation would moderate message framing effects (Kanouse, 1984;

Weinberger, Allen, and Dillon, 1981). Consistent with the H2, the nicotine dependence level

indicates favorability of either a positively framed PSA or a negatively framed one.

However, after conducting separate analyses by selecting cases whether subj ects were

exposed to either negatively or positively framed message, H2 was partially supported.

Specifically, in the H2. 1, the following was predicted: Under high nicotine dependence

conditions, an anti-smoking PSA is more persuasive when it is framed negatively. Although an

intended direction was found, it was not statistically significant. Therefore, H2.1 was not

supported. In the H2.2, the following was predicted: Under low nicotine dependence conditions,

an anti-smoking PSA is more persuasive when it is framed negatively. Intended significant

results were found. Thus, H2.2 was supported.

Implications

This study improves our understanding how individuals process and respond differently to

dissimilar but obj ectively equivalent messages. In the practice, anti-smoking clinic consultants

might be advised to use either negatively or positively framed message depending on clients'

nicotine dependence level. For example, the consultants can measure their clients' nicotine

dependence level. When they consult with clients with low nicotine dependence, positive

message will be more effective in terms of lowering cigarette consumption or smoking cessation.











Popham, W. J., & Potter, L. D. (1993). Do anti-smoking media campaigns help smokers quit?
Public Health Reports, 108(4), 510-513.

Ratneshwar, S., & Chaiken, S. (1991). Comprehension's role in persuasion: the case of its
moderating effect on the persuasive impact of source cues. Journal of Consumer Research,
18(1), 52-62.

Rindfleisch, A, & Crockett, D. X. (1999). Cigarette smoking and perceived risk: a
multidimensional investigation. Journal of Public Policy & Marketing, 18(2), 159-171.

Rothman, A. J., & Salovey, P. (1997). Shaping perception to motivate healthy behavior: the role
of message framing. Psychological Bulletin, 121(1), 3-19.

Rothschild, M. L. (1979). Advertising strategies for high and low involvement situations. In J.
Maloney, & B. Silverman (Eds.), Attitude Research Plays for High Stakes (pp. 74-93).
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Schneider, L., Klein, B., & Murphy, K. M. (1981). Governmental regulation of cigarette health
information. Journal ofLaw & Economics, 24(3), 575-612.

Shimp, T. A. (1981). Attitude toward ad as a mediator of consumer brand choice. Journal of
Advertising, 10(2), 9-15.

Shiv, B., Edell, J. A., & Payne, J. W. (1997). Factors affecting the impact of negatively and
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Siegel, M. (2002). Antismoking advertising: figuring out what works. Journal of Health
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Siegel, M., & Biener, L. (2000). The impact of an antismoking media campaign on progression
to established smoking: results of a longitudinal youth study. American Journal of Public
Health, 90(3), 380-386.

Sly, D. F., Heald, G. R., & Ray, S. (2001). The Florida "truth" anti-tobacco media evaluation:
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Sly, D. F., Trapido, E., & Ray, S. (2002). Evidence of the dose effects of an antitobacco
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Smith, G. E. (1996). Framing in advertising and the moderating impact of consumer education.
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Manipulation Check

Before testing H12, manipulation check was conducted. As expected, the message that "You

are saving $1,000 every year by being a non-smoker, You can buy 2 iPhones with $1,000" was

perceived as the positive anti-smoking message, whereas the message that "You are burning

$1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000" was perceived as

the negative message. Participants reported on a two-item, seven point (1 = strongly agree, 7 =

strongly disagree) Likert scale how much they agreed with the following two statements: "The

ad is focusing on the positive effect of smoking cessation," and "The ad is focusing on the

negative effect of smoking." As shown Table 7, difference between observed value for positively

framed message and test value (= 4) was significant on item one, t = -5.89, p < .001,

.f I = 2.05, SD = 1.56. As shown Table 8, difference between observed value for

negatively framed message and test value (=4) was significant on item two, t = -3.09, p < .01,

if = 2.92, SD = 1.72. Subjects felt that the anti-smoking PSA was more negative

when it was negatively framed rather than positively framed, and they felt that the anti-smoking

PSA was more positive when it was positively framed rather than negatively framed. Therefore,

these manipulation check measures suggest that the intended factors were manipulated

successfully.

Nicotine Dependence

In the H12 testing, the study was conducted to investigate how nicotine dependence

moderates the message framing effects. And the message framing was manipulated. Nicotine

dependence was measured as a continuous variable on the basis upon Heatherton et al. (1991).









In recent years there have been numerous attempts to apply message framing effects

(effects of negatively framing message versus effects of positively framed message) to anti-

smoking PSAs. This is because a substantial amount of health-related studies have tested the

effectiveness of message framing, and yielded inconsistent results. Some studies reported

positively framed messages to be more effective than negatively framed messages. Reverse

results have been obtained in other studies. Anti-smoking researchers also tried to test the

relative effectiveness between differently framed messages how the effects of message framing

differ from other health-related research. Anti-smoking studies that have studied message

framing effects have produced conflicting finding as well. The purpose of this study is to Eind the

reason of the conflicting results in message framing research, and to explore how message

recipients react to two types of anti-smoking messages. Specifically, it will be tested how the

involvement and nicotine dependence level moderate the relative effectiveness of two different

messages. The next chapters will cover previous literatures about message framing, involvement,

and nicotine dependence and methodology used to test hypotheses. The findings of this study

will be helpful to create effective PSAs in terms of lowering smoking rate or smoking cessation.










Zhang, Y., & Neelankavil, J. P. (1997). The influence of culture on advertising effectiveness in
China and the USA. European Journal of2arketing, 31(1/2), 134-149.










"the persuasion processes involved when elaboration is relatively low" (O'Keefe, 2002, p. 139).

Elaboration is meant "engaging in issue-relevant thinking" (O'Keefe, 2002, p. 138). Since the

education level plays a key part in cognitive ability to process information, he concluded that

positively framed messages are more effective for the more-educated persons than for the less-

educated. The contrary is true when messages are framed negatively.

Zhang and Buda (1999) reported that there is the moderating effect of one' s need for

cognition (NFC) on the processing of framed advertising messages. Since NFC is an indicator

for the motivation of information processing, it plays an important moderating role in message

framing effects. When individuals' NFC level is high, they devote more attention to advertising

messages. On the other hand, when individuals' NFC level is low, they tend to avoid paying

attention to advertising messages. As a result, positively framed messages were more effective

when one' s NFC was high. The contrary was true when one' s NFC was low.

A number of studies suggested that people's involvement level can influence how they

react to and process information (Greenwald & Leavitt, 1984; Kardes, 1988). This study begins

by exploring role of involvement and nicotine dependence, and relevant theory.

Involvement

Since Krugman (1965) presented the construct of involvement as personal relevance,

this topic has played a vital role in the understanding of persuasion. There is general agreement

that involvement plays a key role in explaining consumer behavior and information processing

procedure. However, the effect of involvement is debatable due to different ideas for

conceptualization and operationalization. The following two issues are barriers for obtaining

general agreement about involvement: type of involvement and intensity of involvement. Those

two are in the midst of involvement issue. The type of involvement is the first issue for the

disagreement. Some researchers proposed two types of involvement to explain the construct
































O 2008 Wan Seop Jung












LIST OF ABBREVIATIONS

CDC Centers for Disease Control

FCC Federal Communications Commission

PSA Public Service Announcement

USDHHS U. S. Department of Health and Human Service



































To my wife and parents









in without any efforts". Similarly, the negatively framed PSA "You are burning $1,000 every

year by smoking cigarettes" may be interpreted as "Smoking costs a lot." If so, positively framed

PSAs should be more effective under low involvement conditions.

Under conditions of high message processing motivation, individuals are more inclined

to process all information in the ad to arrive at a decision. Thus, they process messages in detail

with prior knowledge to judge the validity of messages (Maheswaran & Meyers-Levy, 1990),

and integrate relevant thoughts and beliefs to form an overall attitude (Petty, Cacioppo, &

Schumann, 1983). Wright (1981) suggested that negative messages received more considerable

weight and influence than positive messages when individuals integrate message-relevant

information. That is because overweightingg may only occur when an audience member is

sufficiently concerned over the message content to bother generating reactions and integrating

those into an overall impression, and to worry about making errors in this" (Wright, 1981, p.

279-280). A variety of studies have supported the overweighting to high involvement conditions

(Kanouse, 1984; Weinberger, Allen, & Dillon, 1981). The implication of those studies is that

messages should be processed thoroughly and negative messages should be more persuasive

under high involvement conditions. Based on the previous theoretical background, following

hypotheses can be predicted:

H1: The relationship between message framing effects and attitude toward anti-smoking
PSAs is moderated by involvement.

H1.1: For those who are highly involved in smoking, an anti-smoking PSA is more
persuasive when it is framed negatively.

H1.2: For those who are less involved in smoking, an anti-smoking PSA is more
persuasive when it is framed positively.












Table 4-1. Manipulation Check of Positively Framed Message for Item 1 in H1 Testing
N Mean SD t df Sig. Mean Difference

Poitvey raed97 3.06 1.86 -4.96 96 .000 -.94
Message (Item 1)
Test value = 4

Table 4-2. Manipulation Check of Negatively Framed Message for Item 2 in H1 Testing
N Mean SD t df Sig. Mean Difference
Negatively Framed
91 2.88 1.76 -6.07 90 .000 -1.12
Message (Item 2)
Test value = 4

Table 4-3. Descriptive Statistics of H1
M SD
Attitude toward Ad 4.31 1.33
Involvement 2.67 1.62
Message Framing .52 .50

Table 4-4. Model Statistics of H1
Model Source SS df MS F Sig. R R Square R4d
Involvement Regression 6.55 2 3.27
Model 1 Framing Residual 325.93 185 1.76 1.86 .159 .14 .02 .01
Total 332.48 187
Involvement Regression 37.32 3 12.44
Model 2 Framing Residual 295.17 184 1.60 7.75 .000 .34 .11 .10
Interaction Total 332.48 187

Table 4-5. Regression of H1
Source B SE fl t Sig.
(Constant) 3.96 .25 15.68 .000
Involvement* .13 .08 .16 1.65 .100
Framing** 1.32 .36 .50 3.71 .000
Interaction -.50 .11 -.66 -4.38 .000
*Involvement: 1 (low) to 7 (high)
**Message Framing: 0 (negatively framed message), 1 (positively framed message)










participants (48.4%) were assigned into Group 1 and shown the negatively framed PSA. Ninety

seven participants (51.6%) were assigned into Group 2 and shown the positively framed PSA. In

the H12 testing, twenty four participants (52.2%) were assigned into Group 1 and shown the

negatively framed PSA. Twenty two participants (47.7%) were assigned into Group 2 and shown

the positively framed PSA. After reading the anti-smoking PSA, they completed the scales

designed to check manipulation, involvement, and measure of dependent variable. For the

duration of each session, the experimenter ensured that participants completed the instrument

independently and did not turn back to the pages they had already read. Upon completion of the

instrument, subj ects were thanked and debriefed. Each session took about ten minutes.

Independent Variables

Message framing (positive vs. negative). Message framing was employed as an

independent variable to test both hypotheses. The positively-framed PSA illustrated the positive

effect of quitting smoking by stating "You are saving $1,000 every year by being a non-smoker.

You can buy 2 iPhones with $1,000," while the negatively framed PSA emphasized the adverse

effects of smoking by stating "You are burning $1,000 every year by smoking cigarettes. You can

buy 2 iPhones with $1,000." The participants reported on a two-item, seven-point (1 = strongly

disagree, 7 = strongly agree) Likert scale how much they agreed with the following two

statements: "The ad is focusing on the positive effect of smoking cessation," and "The ad is

focusing on the negative effect of smoking."

Involvement. Involvement was used as a measured variable in the H1. Participants were

asked to answer smoking involvement items. Five seven-point semantic differential items were

used to measure involvement level (1 = important, irrelevant, valuable, useful, and interesting, 7











Meyerowitz, B. E., & Chaiken, S. (1987). The effect of message framing on breast self-
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Nicotine Dependence

In the first hypothesis, it is suggested that involvement moderates the effectiveness of

message framing by using general subj ects including both smokers and non-smokers. This is

because the message framing effects depend on the motivation of message recipients to process

information. The second hypothesis is inspired by the Petty and Cacioppo's model (1983) as well.

In their model, motivation influences the way to process information by using either peripheral

route or central one. In the second hypothesis, it is suggested that the nicotine dependence level

moderates the effectiveness of message framing by using smoker samples instead of general

subj ects. A number of anti-smoking researchers revealed the relationship between nicotine

dependence and motivation. Reflecting the relationship among nicotine dependence, motivation

and the way of information processes, the second hypothesis examines how the cigarette

addiction level affect attitudes toward anti-smoking PSAs differently depending on the message

framing.

Dependence is conceptualized as compulsive physiological need for a habit-forming

substance. The Diagnostic and Statistical Manual of Mental disorders (APA, 1994) provides

several criteria for dependence which are (1) tolerance; (2) withdrawal; (3) using larger amounts

or longer than intended; (4) unsuccessful efforts to cut down; (5) much time spent to obtain

substance; (6) negative social and/or occupational consequences; (7) persistent physical and/or

psychological problems. The manual recommends that an individual must meet at least three

criteria to be diagnosed with dependence. Nicotine dependence refers to the physical

vulnerability of our body to the chemical nicotine, which is possibly addicting when carried by

various cigarette products (MayoClinic.com, 2006).









APPENDIX B
QUESTIONNAIRE

Instructions: Please review the following advertisement and then answer the questions that
correspond with a particular advertisement.

Directions: The following questionnaire asks you to indicate your opinion about the anti-
smoking, ad. The scales in some of the questions are meant to measure your opinions on each of
the ad. There is no right or wrong answers.












B QUESTIONNAIRE ............ ..... .__ ...............45...

LIST OF REFERENCES ............ ..... .__ ...............49...


BIOGRAPHICAL SKETCH .............. ...............56....










Demographics
1) What is your gender? Female _Male
2) How old are you? years old
3) What is your ethnic background?
White, not Hispanic Hispanic, of any race
African American, not Hispanic _Asian or Pacific Islander
Native American Other
4) Please check your smoking experience.
Never smoked I used to smoke, do not smoke currently
I smoke currently


Thank you for your participation.





















Debriefing Statement
The messages in the ads were fictional. Although those ads were created for this study, the
messages in the ads were based on facts.










with attitude toward anti-smoking PSA among subj ects who were exposed to the negative

message (F (1, 22) = .02, a = .03, t = .13, p > .05), whereas nicotine dependence was negatively

associated with attitude toward anti-smoking PSA among subj ects who were exposed to positive

message (F (1, 20) =9.63, a = -.57, t = -3.10, p < .01). The results of interaction tests are

presented in Table 12.

Thus, the more dependent on cigarette smoking, the more favorable attitude toward

negatively framed PSAs individuals tend to have, while the less dependent on cigarette smoking,

the more favorable attitude toward positively framed PSAs individuals tend to have. These

results support overall assumption of H1. However, when regression analyses were conducted

separately by selecting cases (e.g., subjects who were exposed to the negatively framed PSA vs.

subjects who were exposed to the positively framed PSA), H1 was partially supported. That is,

H1.1 was supported whereas H1.2 was not supported. The main effect of the addiction level was

b = .02, t = .14, p > .05. The main effect of message framing was b = -. 16, t = -.23, p > .05. Thus,

both main effects were not statistically significant.









better, namely, enduring involvement and situational involvement (Houston & Rothschild, 1978;

Rothschild, 1979). The categorization of involvement helped researchers begin to propose the

reasons for the disagreement. The second issue for the disagreement is the intensity of

involvement, namely, high involvement and low involvement (Gainer, 1993). Involvement is

also debatable due to the measuring the involvement construct (Celsi and Olson, 1988). While

researchers have defined the construct of involvement differently (Gainer, 1993), the general

agreement of involvement is the person' s perceived relevance of a product or situation on the

basis of personal goals, values, and interests (Zaichkowsky, 1985).

Enduring involvement can be defined as "enduring personally relevant knowledge

structures" or ongoing concern (Martin & Marchall, 1999, p. 208). The structures are stored in

the relatively long-term memory and obtained from prior experiences. Situational involvement

can be defined as "situation-specific, involving the cues and stimuli that consumers perceive as

personally relevant" (Martin & Marchall, 1999, p. 208). Situational involvement occurs only in

specific situations. The analogy of situations being labeled as "being interested in cars" or

"purchasing a car" is an example of two involvement types. The level of enduring involvement is

concluded by how well the issue is pertained to personally relevant value, whereas the level of

situational involvement is concluded by how well the situation arouses personal goals and values.

The level of situational involvement is dramatically dropped when the personal goals and values

are fulfilled. Since situational involvement rather relates to characteristics of the decision

situation, it is inapposite to the purpose of this study which tries to explain how enduring or long-

term involvement moderates the effectiveness of the message framing. Therefore, this study

employed enduring involvement as a moderator of message framing effects.










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positively versus negatively framed advertising message. Journal ofAdvertising, 28(2), pl-
15.









CHAPTER 4
RESULTS

Hypothesis 1

Multiple regressions were conducted to test H1, with two independent variables,

involvement and message framing, and one dependent variable, attitude toward ad. A sample of

smokers and non-smokers was used to test how involvement moderates message framing effects.

Manipulation Check

Before testing H1, a manipulation check was conducted. As expected, the message that

"You are saving $1,000 every year by being a non-smoker, You can buy 2 iPhones with $1,000"

was perceived as the positive anti-smoking message, whereas the message that "You are burning

$1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000" was perceived as

the negative message. Participants reported on a two-item, seven point (1 = strongly agree, 7 =

strongly disagree) Likert scale how much they agreed with the following two statements: "The

ad is focusing on the positive effect of smoking cessation," and "The ad is focusing on the

negative effect of smoking." As shown Table 1, difference between observed value for positively

framed message and test value (= 4) was significant on item one, t = -4.96, p < .001,

f.1 I = 3.06, SD = 1.86. As shown Table 2, difference between observed value for

negatively framed message and test value (=4) was significant on item two, t = -6.07, p < .001,

if = 2.88, SD = 1.76. Subj ects felt that the anti-smoking PSA was more negative

when it was negatively framed rather than positively framed, and they felt that the anti-smoking

PSA was more positive when it was positively framed rather than negatively framed. Therefore,

these manipulation check measures suggest that the intended factors were manipulated

successfully.










31 or more cigarette per day, smokes more cigarette during the first hour after waking, and

smokes even when he or she is ill enough to be in bed most of the day, the nicotine dependence

level indicates 10. The nicotine dependence level was measured being continuous. The range of

the nicotine dependence level is from 0 (low) to 10 (high). Heatherton et al. (1991) suggested

that a score of 5 or more indicates a significant smoking dependence, while a score of 4 or less

shows a low to moderate dependence.

Dependent variable.

Attitude toward Ad. One dependent variable was measured to test both hypotheses:

Attitudes toward Ad. The dependent variable was measured using a four-item, seven-point

semantic differential scale (1 = unpleasant, unlikable, not irritating, and not interesting, 7 =

pleasant, likable, irritating, and interesting) (Olney, Holbrook, and Batra, 1991). The third item

for measuring involvement level (i.e., not irritating vs. irritating) was reverse coded. The scale

was internally consistent (a = .85), and the responses were averaged to represent the construct for

the H1 (M~= 4.32, SD = 1.34). For the H2, the scale was internally consistent (a = .93), and the

responses were averaged to represent the construct (M~= 4.26, SD = 1.63).









ACKNOWLEDGMENTS

This work is an accomplishment of all who helped me directly and indirectly. It is

especially dedicated to my beloved wife, Soo, who has encouraged and supported me. It is also

dedicated to my parents, Dong Kun Jung and Bok Sook Seo; without their helping hands, it

would have been impossible to complete this thesis.

I extend my sincere gratitude to my advisor and chair, Dr. Jorge Villegas, who has guided,

encouraged, and supported me with the warmest heart and has given me tremendous guidance

and support. I also want to express my thanks to my wonderful committee members, Dr. Chang-

Hoan Cho and Dr. Hyojin Kim, for their invaluable advice and encouragement. I appreciate all

the time and efforts they put into helping me with my thesis, and challenging me to learn more.

Although I first assumed that graduate schools are not fun, my adorable friends at UF

proved my assumption to be wrong. I express my thanks to my classmates. I will never forget

those wonderful moments spent with them. I especially appreciate Korean gators, Jay, Hyung

Seok, Jun Seong, Jun, Sang Won, Chang Dea, Mihyun, Yeuseung, Hyunji, Minji, Hyunmin,

Seonmi, Sooyeon and all other sisters and brothers, for helping me to go through all of those

hard tasks.









The interaction term was again explored by re-computing the regression analyses

separately for groups of subj ects exposed to negative message or positive message in terms of

message framing. Results from follow-up analyses revealed that involvement was positively

associated with attitude toward anti-smoking PSA among subj ects who were exposed to the

negative message (F (1, 89) = 2.34, a = .16, t = 1.53, p > .05), whereas involvement was

negatively associated with attitude toward anti-smoking PSA among subj ects who were exposed

to positive message (F (1, 95) = 24.40, a = -.45, t = -4.94, p < .001). Results of the interaction

tests are presented in Table 6.

Thus, the more involved in smoking, the more favorable attitude toward negatively framed

PSAs individuals tend to have, while the less involved in smoking, the more favorable attitude

toward positively framed PSAs individuals tend to have. These results support overall

assumption of H1. However, when regression analyses were conducted separately by selecting

cases (e.g., subj ects who were exposed to the negatively framed PSA vs. subj ects who were

exposed to the positively framed PSA), H1 was partially supported. That is, H1.1 was supported

whereas H1.2 was not supported. The main effect of the involvement level was b = .13, t = 1.65,

p > .05. The main effect of message framing was b = 1.32, t = 3.71, p < .001. Since this result is

irrelevant to this study, no interpretations are provided for main effects.

Hypothesis 2

Multiple regressions were conducted to test H1, with two independent variables, nicotine

dependence and message framing, and one dependent variable, attitude toward ad. A sample of

smokers among collected data was used to test how nicotine dependence moderates message

framing effects.










future research should employ other dependent variables, and test whether attitude toward ad can

predict future intentions in anti-smoking PSA research.

In the message framing studies, different messages should contain a factually equal

value. The two versions of stimuli used in this study should be equal across experimental groups

except message framing (e.g., saving money vs. burning money). Except for the framing,

causalities of messages are different. For example, in the positively framed message, the message

posits that non-smoking can save $1,000 every year, whereas, in the negatively framed message,

the message posits that smoking can burn $1,000 every year. The different causalities in the

messages may have produced unintended results. Future message framing studies should create

same messages across experimental groups.

In addition to the message framing valence, involvement scales employed in this study

may have produced unexpected results. The Zaichkowsky's scale (1985) measures an issue

involvement. The stimuli in this study focused on cessation of smoking. Even though this study

intended to measure an issue involvement, participants might think of smoking cessation issue

rather than smoking issue. Future studies should use an appropriate scale to measure involvement

level .





































Figure 3-2. Negatively Framed PSA









CHAPTER 3
METHODOLOGY

The purpose of this study is to investigate how involvement and nicotine dependence

moderate the message framing effects. The experiment was conducted to test two hypotheses

from March 3rd to March 11th. at the same period. In the H1, the study was conducted to test the

moderating effects of involvement on message framing with general samples, including both

smokers and non-smokers. In the H2, the study was conducted to test the moderating effects of

nicotine dependence on message framing with only smoker samples among collected data.



Study design. To test H1, two independent variables were involvement and message

framing with attitudes toward anti-smoking PSAs as a dependent variable. The involvement level

as one of independent variables was continuous (from 0: low to 7: high), and message framing

was categorical variable manipulated (positive versus negative). The dependent variable,

attitudes toward anti-smoking PSAs, was measured from 1 (unfavorable) to 7 (favorable). To test

H2, two independent variables were nicotine dependence and message framing with attitudes

toward anti-smoking PSAs as a dependent variable. The nicotine dependence level as one of

independent variables was continuous (from 0: low to 10: high), and message framing was

categorical variable manipulated (positive versus negative). The dependent variable, attitudes

toward anti-smoking PSAs, was measured from 1 (unfavorable) to 7 (favorable).

Participants. In the H1 testing, the total number of participants was one hundred and

eighty eight. They were recruited from undergraduate-level classes and a street on the campus in

the area of a southeastern American university. Due to relatively small number of participants

who currently smoke, more subjects were additionally recruited from a street on the campus. The

courses where students were recruited did not include smoking topics that might have sensitized









= unimportant, relevant, invaluable, useless, and not interesting). The scales were adapted from

Zaichkowsky (1985). The scale was internally consistent (a = .89).

Nicotine dependence. The nicotine dependence level was measured using the

Fagerstroim Nicotine Dependence Scale (Heatherton, 1991) in the H2. Smokers were asked to

answer the following questions:

1. How soon after you wake up do you smoke your first cigarette?
a. Within 5 minutes (3 points)
b. Within 6-30 minutes (2 points)
c. Within 31-60 minutes (1 point)
d. After 60 minutes (0 points)

2. Do you find it difficult to refrain from smoking in places where it is forbidden (e.g.,
in church, at the library, in cinema, etc)?
a. Yes (1 point)
b. No (0 points)

3. Which cigarette would you hate most to give up?
a. The first one in the morning (1 point)
b. Any other (0 points)

4. How many cigarettes per day do you smoke?
a. 10 or less (0 points)
b. 10-20 (1 point)
c. 21-30 (2 points)
d. 31 or more (3 points)

5. Do you smoke more during the first hours after waking than during the rest of the
day?
a. Yes (1 point)
b. No (0 points)

6. Do you smoke even when you are ill enough to be in bed most of the day?"
a. Yes (1 point)
b. No (0 points)

All points were added up on the basis of subj ects' responses and the assigned points. For

example, if someone smokes his or her first cigarette after waking up within 5 minutes, finds it

difficult to refrain from smoking-free places, hates to give up the first morning cigarette, smokes





































Figure 3-1. Positively Framed PSA












TABLE OF CONTENTS


page

ACKNOWLEDGMENT S ............ _...... ._ ...............4....


LIST OF TABLES ............_...... ._ ...............7....


LI ST OF FIGURE S .............. ...............8.....


LIST OF ABBREVIATIONS ............. ...... ._ ...............9....


AB S TRAC T ............._. .......... ..............._ 10...


CHAPTER


1 INTRODUCTION ................. ...............11.......... ......


2 LITERATURE REVIEW ................. ...............15................


Message Framing ................. ...............15.................
Involvem ent ............... .... ......... .. ...............17....
Connection of Involvement with Message Framing. ................ ............. ........ .......19
Nicotine Dependence ................ ... .......... ... ......... .. ..........2
Connection of Nicotine Dependence Level with Message Framing .............. ....................22


3 METHODOLOGY .............. ...............24....


4 RE SULT S .............. ...............29....


Hypothesis 1 .............. ...............29....
Manipulation Check ................. ...............29.................
Involvem ent ................. ...............3.. 0..............
Test of Hypothesis 1 .............. ...............30....
Hypothesis 2 .............. ...............3 1....
Manipulation Check. .........._..._. ...............32........ ......
Nicotine Dependence .........._....__......._. ...............32.....
Test of Hypothesis 2 ..........._.._. ...............33...._._. .....


5 DISCUSSION AND CONCLUSION .............. ...............38....


Discussion............... ...............3

Implications .............. ... ....... .............3
Limitations and Future Research ................. ...............40....._.. .....


APPENDIX


A INFORMED CONSENT FORM............... ...............44..









There has been a substantial amount of research about message framing and involvement,

respectively. However, the research about how involvement interacts with message framing has

considerably been neglected. Since both involvement and framing have been considered as

important factors to predict advertising effectiveness, this disregard is amazing. In this study, it

will be investigated how message framing effects will be moderated by intensity of involvement.

Connection of Involvement with Message Framing

Petty and Cacioppo's elaboration likelihood model (ELM) (1986) is helpful to

understand how involvement affects message framing effects. The model is composed of a

central route and a peripheral route. When individuals are more involved with an issue or a

product, they use the central route to process messages, whereas they use the peripheral route to

process messages when they are less involved with an issue or a product. The model also

suggests that those who are more involved with an issue or product are more motivated to

process relevant messages thoroughly, whereas those who are less involved with an issue or a

product are less motivated to process messages. Motivation in the model is defined as inner

arousal for goal achievement. The level of message processing motivation has an effect on how

much individuals pay more attention to and devote to process information (Celsi & Olson, 1988).

According to the model, the level of message processing motivation determines whether

message claims predominate in persuasion because individuals employ either a central route or a

peripheral route in persuasion process. That is, the motivation level determines the use of one of

processing routes. Under conditions of low message processing motivation, individuals are more

likely to form an attitude by relying on peripheral cues, such as message tone, wording, and

message attractiveness instead of scrutinizing message claims thoroughly and integrating

relevant thoughts and beliefs to form an overall attitude. Hence, the positively framed PSA "You

are saving $1,000 every year by being a non-smoker" may be interpreted as "Non-smokers cash









Involvement

In the H1 testing, the study was conducted to investigate how involvement moderates the

message framing effects. And the message framing was manipulated. Involvement was measured

as a continuous variable on the basis upon Zaichkowsky (1985). The scale measuring

involvement level was internally consistent (a = .89).

Test of Hypothesis 1

Influence of Involvement and Message Framing

This study investigated how involvement moderates the effectiveness of message

framing. Specifically, Subj ects who are more involved with smoking issue would have more

favorable attitude toward negatively framed PSAs, while subj ects who are less involved with

smoking issue would have more favorable attitude toward positively framed PSA.

A multiple regression was conducted to test H1, with attitude toward the ad as a

dependent variable, with the involvement level and message framing as independent variables.

The descriptive statistics are presented in Table 3. The mean of involvement was 2.67 (SD =

1.62), .52 (SD = .50) for message framing, and 4.31 (SD = 1.33) for attitude toward ad,

respectively.

The model with two independent variables, the involvement level and the message

framing, and the j oint effect of these two variables was statistically significant, F (3, 184) = 7.75,

p < .001. Message framing was employed as a dummy variable where a negatively framed PSA

was 0, and a positively framed PSA was 1. The results are presented in Table 4 and 5. Initially, a

multiple regression was conducted with only two independent variables, involvement and

message framing. Its F-value was 1.86. Adding the interaction, then, contributed to 9.3% of the

model with only two independent variables. F-value change was 19. 18. The effect of the

interaction between the addiction level and message framing was b = -.50, t = -4.3 8, p < .001.










Test of Hypothesis 2

Influence of Nicotine dependence and Message Framing

This study investigated how addiction level affects attitude toward anti-smoking PSA

when it is framed either positively or negatively. Specifically, Subj ects who are more addicted to

smoking would have more favorable attitude toward negatively framed PSAs, while subjects

who are less addicted to smoking would have more favorable attitude toward positively framed

PSA.

A multiple regression was conducted to test H12, with attitude toward the ad as the

dependent variable, and with the addiction level and message framing as independent variables.

The descriptive statistics were presented in Table 9. The mean of smoking addiction was 3.11

(SD = 2.27), .48 (SD = .51) for message framing, and 4.26 (SD = 1.63) for attitude toward ad,

respectively.

The model with two independent variables, the addiction level and the message framing,

and the j oint effect of these two variables was statistically significant, F (3, 42) = 6.72, p < .001.

Message framing was employed as a dummy variable where a negatively framed PSA was 0, and

a positively framed PSA was 1. The results are presented in Table 10 and 11. Initially, a multiple

regression was conducted with only two independent variables, nicotine dependence and

message framing. Its F-value was 7.46. Adding the interaction, then, contributed to 6.7% of the

model with only two independent variables. F-value change was 4. 15. The effect of the

interaction between the nicotine dependence level and message framing was b = -.38, t = -2.04, p

< .05.

Interaction was again explored by re-computing the regression analyses separately for

groups of subj ects exposed to negative message or positive message in terms of message framing.

Results from follow-up analyses revealed that nicotine dependence was positively associated









In other words, negative message will be more effective when they consult with clients with high

nicotine dependence. Anti-smoking PSA executioners might be advised to employ either

negatively or positively framed message depending on message recipients' involvement level.

Moreover, it is also helpful to choose appropriate place and time for implementing anti-smoking

PSAs. For instance, when PSA executioners place anti-smoking PSAs in magazines, the message

framing will depend on magazine types. More specifically, when a positively framed PSA is

placed in a teen magazine, we can predict better effects because teens' involvement level might

be low. Therefore, anti-smoking consultants and PSA executioners can create either negative or

positive message by categorizing target groups into either smoker or non-smoker group.

Limitations and Future Research

There are a few limitations in the study. This proj ect is based the use of student

participants as a sample. Although the use of student participants is more acceptable in

experimental studies than in survey, homogeneity of the sample may have produced results that

are not typically found in the population. Findings of this proj ect need to be replicated using

more a heterogeneous, adult sample to achieve external validity.

This study tested anti-smoking PSAs' impact on attitude toward messages, not intention

to quit smoking or attitude toward smoking behavior. Attitude toward ad has been posited to be a

mediator of advertising effectiveness which includes brand attitudes and future intentions

(Mitchell & Olson, 1981; Shimp, 1981). This study measured one dependent variable: attitude

toward ad. This study found significant interaction effects by measuring attitude toward ad as a

dependent variable in both experiments. However, it might have different results if different

dependent variables such as attitude toward smoking behavior or intention to quit were employed.

This is because the maj ority of smokers do not have an intention to give up smoking in the near

future (Hennrikus, Jeffery & Lando, 1995; John, Meyer, Rumpf, & Hapke, 2003). Therefore,









APPENDIX A
INFORMED CONSENT FORM

Protocol Title: College Students' Ideas About Smoking
Please read this consent statement carefully before you decide to participate in this study
Purpose of the research study: The purpose of this research is to study college students' ideas
about smoking. The participants will be asked questions about their beliefs and personal
experiences about smoking.
What you will be asked to do in this study: You will be invited to a laboratory. After the
investigator' s instruction, print your name and student ID on the attached name sheet, sign the
consent form, and complete the questionnaire adequately apart from others. When your instructor
requests the survey, detach the name sheet and this consent form from the main survey. Then
submit the consent form, name sheet, and the envelope separately.
Time required: About 15 minutes
Risks and Benefits: We do not anticipate there will be any risks or direct benefits to you as a
consequence of your decision to complete the survey.
Confidentiality: Your name or student ID will not appear on the questionnaire itself. Your
identity will be kept confidential to the extent provided by law. Your instructor will need your
student ID to give you extra credit, but will not receive your name before the final exam. Your
responses are completely confidential and no reference will be made in any oral or written report
that would link you individually to the study. Further, the principal investigator works
independently of your instructor.
Voluntary participation: Your participation in this study is completely voluntary.
Right to withdraw from the study: You have the full right to withdraw from the study at
anytime without consequence.
Whom to contact if you have questions about the study: Wan Seop Jung, Master' s student,
College of Communications, University of Florida, address: 2018 Weimer Hall, University of
Florida, Gainesville, FL, 32611-8400. phone: 352.870.2077 email: wanseop9@ufl.edu. Jorge
Villegas, Assistant Professor, College of Communications, University of Florida, address: 2084
Weimer Hall, University of Florida, Gainesville, FL, 32611-8400. phone: 352.392.5059. email:
jvillegas@j ou.ufl.edu
Whom to contact about your right as a research participant in this study:
UFIRB, Box 112250, University of Florida, Gainesville, FL 32611-2250; ph 392-0433
Agreement: I have read the procedure described above. I voluntarily agree to participate in the
procedure and I have received a copy of this description.

Participant: Date:

Principal Investigator: Date:










Centers for Disease Control (CDC). (1991). Selected tobacco-use behaviors and dietary patterns
among high school students-United States, 1991. M~orbidity an2dMortality Weekly Report,
41(24), 417-421.

Chandy, R. K., Tellis, G. J., Macinnis, D. J., & Thaivanich, P. (2001). What to say when:
advertising appeals in evolving markets. Journal of2arketing Research, 3 8(4), 3 99-414.

Cunningham, S. M. (1967). The maj or dimensions of perceived risk. In Cox, D.F.(Ed.), Risk
takitt~~~~tttt~~~~ng and information handling in consumer behavior (pp. 82-108). Boston, MA: Harvard
University Press.

Edwards, K. (1990). The interplay of affect and cognition in attitude formation and change.
Journal ofPersonality and Social Psychology, 59(2), 202-216.

Gainer, B. (1993). An empirical investigation of the role of involvement with a gendered product.
Psychology & Marketing, 10(4), 265-283.

Ganzach, Y., & Karsahi, N. (1995). Message framing and buying behavior: A field experiment.
Journal of Business Research, 32, 11-17.

Goldman, L. K., & Glantz, S. A. (1998). Evaluation of antismoking advertising campaigns.
Journal of the American M~edical Association, 279(10), 772-777.

Grandpre, J., Alvaro, E. M., Burgoon, M., Miller, C. H., & Hall, J. R. (2003). Adolescent
reactance and anti-smoking campaigns: a theoretical approach. Health Conanunication,
15(3), 349-366.

Greenwald, A., & Leavitt, C. (1984). Audience involvement in advertising: Four levels. Journal
of Consumer Research, 1 1(June), 58 1 -592.

Hale, J. L., & Dillard, J. P. (1995). Fear appeals in health promotion campaigns: Too much, too
little, or just right? Designing health messages. Thousand Oaks, CA: Sage Publications.

Hamilton, J. L. (1972). The demand for cigarettes: advertising, the health scare, and the cigarette
advertising ban. Review of Econontics & Statistics, 54(4), 401-411.

Hennrikus, D. J., Jeffery, R. W., & Lando, H. A. (1995). The smoking cessation process:
longitudinal observation in a working population. Preventive M~edicine, 24, 235-244.

Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., & Fagerstriim, K. O. (1991). The Fagerstriim
Test for Nicotine Dependence: A revision of the Fagerstriim Tolerance Questionnaire.
British Journal of Addiction, 86, 1 119-1 127.

Houston, M. J. & Rothschild, M. L. (1978). Conceptual and methodological perspectives on
involvement. In S. C. Jain (Ed.), 1978 Educator 's Proceedings (pp. 184-187). Chicago:
American Marketing Assoication.










Meyerowitz and Chaiken (1987) found opposing results about message framing effect. In the

Meyerowitz and Chaiken's study (1987), a negatively framed breast self-examination (BSE)

message was more effective than positively framed one when women were exposed to both

negatively and positively framed BSE messages. They have observed that the negatively framed

message attracts more attention than the positively framed one. Since people are more responsive

and emotional towards negative messages, the researchers have supported the effect of negative

framing (Pratto and John, 1991).

Recent message framing studies tried to find reasons for the conflicting findings. The

studies found that the effectiveness of message framing would differ depending on various

factors. For instance, Ganzach and Karsahi (1995) reported that a study setting can moderate the

effectiveness of the message framing on buying behavior in terms of credit card uses.

Specifically, when the experiment was conducted in the laboratory, a positive message was more

persuasive in terms of increase of card use, whereas a negative one was more effective when the

experiment was conducted in the natural market environment. They found that individuals'

perceived importance level varied in situations, i.e., laboratory setting versus natural market

environment setting. That is because message recipients regarded the issue as more important so

they are motivated to process the ad information in the natural market environment than

laboratory setting.

Smith (1996) revealed that a consumer education level has a moderating effect on the

message framing effects. The study assumed that the education level is highly related to

information processing ability which determines the dominant information processing route

(central vs. peripheral). The central route to persuasion refers to "the persuasion processes

involved with elaboration is relatively high," whereas the peripheral route to persuasion refers to









INFLUENCE OF MESSAGE FRAMING, INVOLVEMENT, AND NICOTINE
DEPENDENCE ON EFFECTIVENESS OF ANTI-SMOKING PUBLIC SERVICE
ANNOUNCEMENT S
















By

WAN SEOP JUNG


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF ADVERTISING

UNIVERSITY OF FLORIDA

2008









Please read each set of adj ectives carefully, and decide where your opinion would be the most
accurately reflected on the continuum. Then, mark on the square that most closely reflects your
opinion. You may refuse to answer any questions. Remember, there are no right or wrong
answers.

1) Do you age httea sfcsn npstive effect of smoking cessation?
Strongly 1 2 3 4 5 6 7 Strongly
agree 0 0 0 0 0 0 0 disagee

2) Do you agree that the ad is focusing on negative effect of smoking?
Strongly 1 2 3 4 5 6 7 Strongly
agre 0 0 0 0 0 0 disagee

Please check the scale that best reflects your agreement with each of the following items.
3) In general, smoking is.
1 2 3 4 5 6 7
Important Unimportant
0 0 0 0 0 0 0 O

1 2 3 4 5 6 7
Irrelevant Relevant
0 0 0 0 0 0 0 O

1 2 3 4 5 6 7
Valuable Invaluable
0 0 0 0 0 0 0 O

1 2 3 4 5 6 7
Useful Useless
0 0 0 0 0 0 0 O

1 23 45 6 7Not
Interesting
O O O O O O O interesting










Table 4-6. Follow-up Analyses for Interaction in H1
Message Framing IV B SE fl t Sig.
Negative Involvement .133 .087 .160 1.529 .130
R= .160, R2 = .026, R2Adl = .015
Positive Involvement -.367 .074 -.452 -4.939 .000
R= .452, R2 = .204, R2Adl = .196

Table 4-7. Manipulation Check of Positively Framed Message for Item 1 in H2 Testing
N Mean SD t df Sig. Mean Difference
Positively Framed
22 2.05 1.56 -5.89 21 .000 -1.96
Message (Item 1)
Test value = 4

Table 4-8. Manipulation Check of Negatively Framed Message for Item 2 in H2 Testing
N Mean SD t df Sig. Mean Difference

Neatvey raed24 2.92 1.72 -3.09 23 .005 -1.08
Message (Item 1)
Test value = 4

Table 4-9. Descriptive Statistics of H2
M SD
Attitude toward Ad 4.26 1.63
Addiction Level 3.11 2.27
Message Framing 0.48 0.51

Table 4-10. Model Statistics of H2
Model Source SS df MS F Sig. R R Square RAdl
Addiction Regression 30.90 2 15.45
Model 1 Framing Residual 89.03 43 2.07 7.46 0.002 0.51 0.26 0.22
Total 119.94 45
Addiction Regression 38.91 3 12.97
Model 2 Framing Residual 81.02 42 1.93 6.72 0.001 0.57 0.32 0.28
Interaction Total 119.94 45









4) Do you Eind the advertisement is (EAUATION OF THE ADVERTISEMEN:
1 2 3 4 5 6 7
Unpleasant Pleasant
0 0 0 0 0 0 0 O

1 2 3 4 5 6 7
Unlikable Likable
0 0 0 0 0 0 0 O

1 2 3 4 5 6 7
Not irritating Irritating
0 0 0 0 0 0 0 O

Not 12 34 56 7
Interesting
interesting O O O O O O O

5) Please check your smoking behavior on the square.
(If you are not a smoker, g~o to the next page)
1. How soon after you wake up do you smoke your first cigarette?
O 0-5 min 0 6-30 min 0 31-60 min 0 After 60 min

2. Do you Eind it difficult to refrain from smoking in places where
it is forbidden (e.g., church library, cinema)?
O Yes O No

3. Which cigarette would you be the most unwilling to give up?
O First in the morning 0 Any of the others

4. How many cigarettes per day do you smoke?
O 10 or less O 11 to 20 0 21 to 30 0 31 or more

5. Do you smoke more frequently during the first hours after waking than during
the rest of the day?
O Yes O No

6. Do you smoke if you are so ill that you are in bed most of the day?
O Yes O No









CHAPTER 2
LITERATURE REVIEW

In this study, it will be investigated how to create more effective anti-smoking PSAs by

identifying the role of involvement and nicotine dependence in message framing effects.

Message Framing

Message framing effects can be conceptualized as the perspective that individuals

process and respond differently to dissimilar but obj ectively equivalent messages (Kuihberger,

1998). The analogy of gambling being labeled as "80% of probability of losing money" or "20%

of probability of earning money" is an example of message framing. As stated by Kithberger

(1998), same message tone, manner, and value should be applied to different messages. That is,

different messages should contain a factually equal value. Message framing can be

operationalized either by stressing on benefits gained, namely positively framed message, or by

stressing on benefit lost, namely negatively framed message. Inspired by the message framing

effects, a substantial stream of literature has investigated the effect of message framing on

individual' decisions (Puto, 1987). Puto's study revealed that people tend to be risk averse when

they process a positively framed message, but they tend to be risk seeking when they receive a

negatively framed message.

There has been little research addressing how and why people response differently to

different messages (Levin, Schneider & Gaeth, 1998; Meyerowitz & Chaiken, 1987;

Maheswaran & Meyers-Levy, 1990; Stuart & Blanton, 2002; Umphrey, 2003). Moreover, those

studies failed to yield consistent results. For instances, in Levin and Gaeth's research (1988;

Levin, 1987), people have more favorable attitude toward positively framed messages than

negatively framed ones when they are exposed to messages, stressing either percentage of lean in

total meat or percentage of fat (e.g. containing 75% of lean vs. containing 25% of fat). However,









BIOGRAPHICAL SKETCH

Wan Seop Jung was born in Busan, Korea. He earned his Bachelor of Advertising and

Public Relations from Chung-Ang University in Seoul, Korea. He came to the University of

Florida in August 2006 to pursue a Master of Advertising. He is received his Master of

Advertising degree in August of 2008. He continues with his doctoral studies at the University of

Florida.










subj ects to the purpose of the study. Female participants made up 5 1. 1% of the sample, and

18. 1% were smokers. The dominant percentage of ethnicity was Caucasians (54.9%), and

followed by Hispanics (20.7%), Asian-Americans (19.0%), and African-Americans (3.8%). In

the H2 testing, a sample of smokers among collect data was used. Out of original participant,

forty six were smokers. Female participants made up 42.2% of the sample, and all experiment

participants were smokers. The dominant percentage of ethnicity was Caucasians (55.6%), and

followed by Hispanics (15.6%), Asian-Americans (26.7%), and African-Americans (2.2%).

Stimuli. Two versions of a print anti-smoking public service announcements were

created to test both hypotheses. As shown Figure 1 and 2, visuals and layout were equal across

experimental groups. Two advertisements contained either a positively framed message or a

negatively framed message. Both advertisements presented the argument that stopping or

continuing with cigarette consumption can lead to a financial gain or loss equivalent to two

iPhones which is one of the most appealing and familiar products among college students. Thus,

experiment participants can recognize the value of financial gain or loss easily that is caused by

stopping or continuing with cigarette consumption. The manipulation of message framing

occurred in the body copy. For the negatively framed message, the following message was used:

"You are burning $1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000."

For the positively framed message, the following message was used: "You are saving $1,000

every year by being a non-smoker. You can buy 2 iPhones with $1,000."

Procedure. Sessions were conducted in small classroom settings and on a street on the

campus. Participants were instructed that the purpose of the study was to understand consumers'

ideas about smoking message. After the informed consent was secured, participants were

randomly assigned into one of the two experimental conditions. In the H1 testing, ninety one









A large amount of studies have supported the positive effect of anti-smoking PSAs in

terms of decrease of cigarette consumption or smoking cessation. Many researchers, however,

suggested different results. For instance, O'Keefe (1971) reported that PSAs produced an effect

on smoking behavior in a limited way. He found that the effectiveness of PSAs depended on

recipients' inclination to give up smoking. In other words, anti-smoking PSAs were effective

only for the smokers who were determined to give up smoking. Wallack and Corbett (1987)

tested how a variety of PSAs such as anti-drug, anti-drinking, and anti-smoking diminished the

rate of smoking, drinking, and drug-taking. The study showed that the contribution of PSAs was

minor in the context of lowering of the rates of smoking, drinking, and drug-taking because

addictive behaviors were unwilling to be changed. Wallack (1981) reported the minor effects of

PSAs on smoking cessation as well.

Traditional anti-smoking PSA research rather related to the efficacy of anti-smoking

PSA in terms of whether persuasion occurs. Recently, researchers have expanded research topics

of anti-smoking PSAs to understand how and why the effect of PSAs varied; further, they tried

to optimize the effectiveness of PSAs. For example, Goldman and Glantz (1998) have examined

a variety of message themes of anti-smoking PSAs such as industry manipulation, addiction,

health issue and second-hand smoke to find the relative effectiveness of each message theme,

and revealed that the industry deception theme was the most effective. A number of studies have

tested the relative effectiveness of ad appeal types among fear, humor, dirtiness (e.g., bad breath

and odor), sports, and sociability because those were frequently used ad appeals in anti-smoking

PSAs (Blum, 1980; Millstein. 1986; Hale & Dillard, 1995; Witte, 1995). The studies found that

fear and humor were the most effective appeals in their appeal type research, and other appeal

types failed to reduce the prevalence of smoking.




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INFLUENCE OF MESSAGE FRAMING, INVOLVEMENT, AND NICOTINE DEPENDENCE ON EFFECTIVENESS OF ANTI-SMOKING PUBLIC SERVICE ANNOUNCEMENTS By WAN SEOP JUNG A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ADVERTISING UNIVERSITY OF FLORIDA 2008 1

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2008 Wan Seop Jung 2

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To my wife and parents 3

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ACKNOWLEDGMENTS This work is an accomplishment of all who he lped me directly and indirectly. It is especially dedicated to my beloved wife, Soo, w ho has encouraged and supported me. It is also dedicated to my parents, Dong Kun Jung and Bok Sook Seo; without their helping hands, it would have been impossible to complete this thesis. I extend my sincere gratitude to my advisor and chair, Dr. Jorge Villegas, who has guided, encouraged, and supported me with the warmes t heart and has given me tremendous guidance and support. I also want to express my thanks to my wonderful committee members, Dr. ChangHoan Cho and Dr. Hyojin Kim, for their invaluable advice and encouragement. I appreciate all the time and efforts they put into helping me w ith my thesis, and challenging me to learn more. Although I first assumed that graduate schools are not fun, my adorable friends at UF proved my assumption to be wrong. I express my thanks to my classmates. I will never forget those wonderful moments spent with them. I es pecially appreciate Korean gators, Jay, Hyung Seok, Jun Seong, Jun, Sang Won, Chang Dea, Mihyun, Yeuseung, Hyunji, Minji, Hyunmin, Seonmi, Sooyeon and all other sist ers and brothers, for helping me to go through all of those hard tasks. 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................7 LIST OF FIGURES .........................................................................................................................8 LIST OF ABBREVIATIONS ..........................................................................................................9 ABSTRACT ...................................................................................................................................10 CHAPTER 1 INTRODUCTION................................................................................................................. .11 2 LITERATURE REVIEW.......................................................................................................15 Message Framing ....................................................................................................................15 Involvement ............................................................................................................................17 Connection of Involvement with Message Framing ...............................................................19 Nicotine Dependence ..............................................................................................................21 Connection of Nicotine Dependenc e Level with Message Framing ......................................22 3 METHODOLOGY.................................................................................................................2 4 4 RESULTS...................................................................................................................... .........29 Hypothesis 1 ...........................................................................................................................29 Manipulation Check ................................................................................................................29 Involvement ............................................................................................................................30 Test of Hypothesis 1 ...............................................................................................................30 Hypothesis 2 ...........................................................................................................................31 Manipulation Check ................................................................................................................32 Nicotine Dependence ..............................................................................................................32 Test of Hypothesis 2 ...............................................................................................................33 5 DISCUSSION AND CONCLUSION....................................................................................38 Discussion ...............................................................................................................................38 Implications ............................................................................................................................39 Limitations and Future Research ............................................................................................40 APPENDIX A INFORMED CONSENT FORM............................................................................................44 5

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B QUESTIONNAIRE................................................................................................................ 45 LIST OF REFERENCES ...............................................................................................................49 BIOGRAPHICAL SKETCH .........................................................................................................56 6

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LIST OF TABLES Table page 4-1 Manipulation Check of Positively Framed Message for Item 1 in H1 Testing ....................35 4-2 Manipulation Check of Negatively Framed Message for Item 2 in H1 Testing...................35 4-3 Descriptive Statistics of H1............................................................................................... ...35 4-4 Model Statistics of H1..........................................................................................................35 4-5 Regression of H1........................................................................................................... ........35 4-6 Follow-up Analyses for Interaction in H1............................................................................36 4-7 Manipulation Check of Positively Framed Message for Item 1 in H2 Testing....................36 4-8 Manipulation Check of Negatively Framed Message for Item 2 in H2 Testing...................36 4-9 Descriptive Statistics of H2............................................................................................... ...36 4-10 Model Statistics of H2..........................................................................................................36 4-11 Regression of H2.......................................................................................................... .........37 4-12 Follow-up Analyses for Interaction in H2............................................................................37 7

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LIST OF FIGURES Figure page 3-1. Positively Framed PSA ...........................................................................................................42 3-2. Negatively Framed PSA .........................................................................................................43 8

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LIST OF ABBREVIATIONS CDC Centers for Disease Control FCC Federal Communications Commission PSA Public Service Announcement USDHHS U.S. Department of Health and Human Service 9

PAGE 10

Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Advertising INFLUENCE OF MESSAGE FRAMING, INVOLVEMENT, AND NICOTINE DEPENDENCE ON EFFECTIVENESS OF ANTI-SMOKING PUBLIC SERVICE ANNOUNCEMENTS By Wan Seop Jung August 2008 Chair: Jorge Villegas Major: Advertising Studies examining message fr aming effects have yielde d conflicting findings. Some studies find that positively framed messages ar e more persuasive than negatively framed messages. Other studies report reverse outcomes. This study tried to find the reasons for the conflicting results in message framing researc h, and found that the eff ects of message framing was varied depending on the involvement level and smoking addiction leve l. The study suggests that subjects who are more involved with smoking issue prefer negative messages, while subjects who are less involved with smoking issu e prefer positive messages. The second finding is that the more dependent on cigarette smoking s ubjects are, the more favorable attitude toward negatively framed PSAs they tend to have. The c ontrary is true when anti-smoking PSAs are framed positively. Other findings an d implications are discussed. 10

PAGE 11

CHAPTER 1 INTRODUCTION Cigarette smoking has great societal and clin ical importance (American Cancer Society, 2001). According to the American Cancer Society (2008), smoking was responsible for approximately 559,312 U.S. premature deaths in 2005. Moreover, a number of non-smokers suffered from second-hand smoking. A sizable percentage of youth (20%-30%) begin smoking as early as middle school (Centers for Dis ease Control [CDC], 1998). A large number of smokers initiate cigarette smoking during youth-88% by age 18 (U.S. Department of Health and Human Service [USDHHS], 1994), w ith approximately fifty per cent becoming addicted (CDC, 1991). Smoking behavior in middle school has a tendency to last for a long time due to the smoking addiction (Oei, 1987). Anti-smoking PSAs are useful due to its preventive effects (USDHHS, 1994). In addition to the health-related damages, other economical and environmental damages are caused by smoking. Th e following are examples of the damages: productivity decrease due to ci garette breaks, dirtiness from cigarette butts, and budgetary allocations for anti-smoking. Therefore, much research of anti-smoking Public Service Announcements (PSAs) tried to ab ate the prevalence of smoking. Schneider et al. (1981) estimated the effect s of the Fairness Doctrine, which was a Federal Communications Commission (FCC) re gulation regarding broadcasting license acquisition. Tobacco companies were subjected to re striction on inserting th eir advertisements in radio or TV because of the Fairness Doctrine. After the Fairness Doctrine, cigarette consumption decreased from 1967 to 1970. Researchers have experienced that the rest riction of tobacco advertisements had an influen ce on decrease of cigarette cons umption. However, in 1984, the Supreme Court recommended the FCC to abolish the Fairness Doctrine because it harmed the public interest and violated the First Amendment. Then, there had been an emerging interest in 11

PAGE 12

attempting to find other devices to abate the pr evalence of smoking instead of restriction of tobacco advertising. Therefore, researchers began to study anti-smoking PSAs. A substantial number of studies have supported the efficacy of anti-smoking PSAs empirically and practically. Goldman and Glantz (1998) found that anti-smoking PSAs had an influence on decline in ciga rette consumption in Californi a, Massachusetts, and Arizona. Popham and Potter (1993) did a research to te st whether stateor government-sponsored PSAs were effective by using the California Departme nt of Health Service sponsored anti-smoking PSAs, conducted from 1990 to 1991. They conc luded that the government-sponsored PSAs helped smokers to quit significantly. In recent years, researchers tried to test anti-smoking PSAs using different target groups (e.g., youth, adolescent, and adult) instead of general population. For instance, Seigel and Biener (2000) reported that anti-smoking PSAs played a role in decrease of cigarette consumption among youth in Massachusetts. Other studies found th at anti-smoking PSAs were persuasive to reduce tobacco consumption both for adults and for youth in California (Hu, Sung, & Keeler, 1995; Pierce et al., 1998). Bauer et al. (2000) suggested that anti-smoking PSAs have reduced and prevented youth cigarette smoking. A result showed that anti-smoking PSAs could have an effect both on adolescents and on young adults in Florida (Sly, Trapido, & Ray, 2002). There has been an attempt to understand th e persuasion processes that occur when smokers are exposed to anti-smoking PSAs. For ex ample, a Florida baseline research revealed that anti-smoking PSAs were effective to change attitude and beliefs toward cigarette smoking and smoking behavior among youth, and helped reduce the prevalence of smoking among youth (Sly, Heald, & Ray, 2001). The study was the evid ence that anti-smoking PSAs had an influence on not only changing attitude and belief towa rd smoking behavior but smoking cessation. 12

PAGE 13

A large amount of studies have supported the positive effect of anti-smoking PSAs in terms of decrease of cigarette consumption or smoking cessation. Many researchers, however, suggested different results. For instance, OKeef e (1971) reported that PSAs produced an effect on smoking behavior in a limited way. He found that the effectiveness of PSAs depended on recipients inclination to give up smoking. In other words, anti-smoking PSAs were effective only for the smokers who were determined to give up smoking. Wallack and Corbett (1987) tested how a variety of PSAs such as anti-dr ug, anti-drinking, and anti-s moking diminished the rate of smoking, drinking, and drug-taking. The study showed that the contribution of PSAs was minor in the context of lowering of the ra tes of smoking, drinking, and drug-taking because addictive behaviors were unwilling to be change d. Wallack (1981) reported the minor effects of PSAs on smoking cessation as well Traditional anti-smoking PSA research rath er related to the efficacy of anti-smoking PSA in terms of whether persuasion occurs. Recen tly, researchers have ex panded research topics of anti-smoking PSAs to understand how and why the effect of PSAs varied; further, they tried to optimize the effectiveness of PSAs. For example, Goldman and Glantz (1998) have examined a variety of message themes of anti-smoking PS As such as industry manipulation, addiction, health issue and second-hand smoke to find the re lative effectiveness of each message theme, and revealed that the industry deception theme wa s the most effective. A number of studies have tested the relative effectiveness of ad appeal types among fear, humor, di rtiness (e.g., bad breath and odor), sports, and sociability because those we re frequently used ad appeals in anti-smoking PSAs (Blum, 1980; Millstein. 1986; Hale & Dilla rd, 1995; Witte, 1995). The studies found that fear and humor were the most effective appeals in their appeal type res earch, and other appeal types failed to reduce the prevalence of smoking. 13

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In recent years there have been numerous attempts to apply message framing effects (effects of negatively framing message versus e ffects of positively framed message) to antismoking PSAs. This is because a substantial amount of health-related studies have tested the effectiveness of message framing, and yielded inconsistent results. Some studies reported positively framed messages to be more effective than negatively framed messages. Reverse results have been obtained in other studies. An ti-smoking researchers al so tried to test the relative effectiveness between di fferently framed messages how the effects of message framing differ from other health-relat ed research. Anti-smoking studie s that have studied message framing effects have produced c onflicting finding as well. The pur pose of this study is to find the reason of the conflicting results in message framing research, and to explore how message recipients react to two types of anti-smoking messages. Specifically, it will be tested how the involvement and nicotine dependence level moderate the relative effectiveness of two different messages. The next chapters will cover previous literatures about message framing, involvement, and nicotine dependence and me thodology used to test hypotheses. The findings of this study will be helpful to create effective PSAs in terms of lowering smoking rate or smoking cessation. 14

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CHAPTER 2 LITERATURE REVIEW In this study, it will be investigated how to create more effectiv e anti-smoking PSAs by identifying the role of involvement and nico tine dependence in message framing effects. Message Framing Message framing effects can be conceptualized as the perspective that individuals process and respond differently to dissimilar but objectively equivalent messages (Khberger, 1998). The analogy of gambling being labeled as % of probability of losing money or % of probability of earning money is an exampl e of message framing. As stated by Khberger (1998), same message tone, manner, and value should be applied to different messages. That is, different messages should contain a factua lly equal value. Message framing can be operationalized either by stressing on benefits gained, namely positively framed message, or by stressing on benefit lost, name ly negatively framed message. Inspired by the message framing effects, a substantial stream of literature has investigated the effect of message framing on individual decisions (Puto, 1987). Pu tos study revealed that people tend to be risk averse when they process a positively framed message, but they tend to be risk seeki ng when they receive a negatively framed message. There has been little research addressing how and why people response differently to different messages (Levin, Schneider & Gaeth, 1998; Meyerowitz & Chaiken, 1987; Maheswaran & Meyers-Levy, 1990; Stuart & Blanton, 2002; Um phrey, 2003). Moreover, those studies failed to yield consistent results. For instances, in Levin and Gaeths research (1988; Levin, 1987), people have more favorable attitude toward positively framed messages than negatively framed ones when they are exposed to messa ges, stressing either pe rcentage of lean in total meat or percentage of fat (e.g. containing 75 % of lean vs. containing 25% of fat). However, 15

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Meyerowitz and Chaiken (1987) found opposing results about messa ge framing effect. In the Meyerowitz and Chaikens study (1987), a negatively framed breast self-examination (BSE) message was more effective than positively framed one when women were exposed to both negatively and positively framed BSE messages. They have observed that the negatively framed message attracts more attention than the positivel y framed one. Since people are more responsive and emotional towards negative messages, the res earchers have supported th e effect of negative framing (Pratto and John, 1991). Recent message framing studies tried to fi nd reasons for the conflicting findings. The studies found that the effectiveness of me ssage framing would differ depending on various factors. For instance, Ganzach and Karsahi (1995 ) reported that a study setting can moderate the effectiveness of the message framing on buying behavior in terms of credit card uses. Specifically, when the experiment was conducted in the laboratory, a positive message was more persuasive in terms of increase of card use, whereas a negative one was more effective when the experiment was conducted in the natural market environment. They f ound that individuals perceived importance level varied in situations, i.e., laboratory setting versus natural market environment setting. That is because message recipi ents regarded the issue as more important so they are motivated to process the ad informa tion in the natural market environment than laboratory setting. Smith (1996) revealed that a consumer e ducation level has a moderating effect on the message framing effects. The study assumed that the education level is highly related to information processing ability which determines the dominant information processing route (central vs. peripheral). The cen tral route to persuasion refers to the persuasion processes involved with elaboration is relatively high, wher eas the peripheral route to persuasion refers to 16

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the persuasion processes involved when elabor ation is relatively low (OKeefe, 2002, p. 139). Elaboration is meant engaging in issue-rele vant thinking (OKeefe, 2002, p. 138). Since the education level plays a key part in cognitive abil ity to process information, he concluded that positively framed messages are more effective for the more-educated persons than for the lesseducated. The contrary is true when messages are framed negatively. Zhang and Buda (1999) reported that there is the moderating effect of ones need for cognition (NFC) on the processing of framed adve rtising messages. Since NFC is an indicator for the motivation of information processing, it pl ays an important moderating role in message framing effects. When individuals NFC level is high, they devote more attention to advertising messages. On the other hand, when individuals NFC level is low, they tend to avoid paying attention to advertising messages. As a result, positively framed messages were more effective when ones NFC was high. The contrary was true when ones NFC was low. A number of studies suggeste d that peoples involvement le vel can influence how they react to and process information (Greenwald & Leavitt, 1984; Kardes, 1988). This study begins by exploring role of involvement and nico tine dependence, and relevant theory. Involvement Since Krugman (1965) presented the construct of involvement as personal relevance, this topic has played a vital ro le in the understanding of persua sion. There is general agreement that involvement plays a key role in explaining consumer beha vior and information processing procedure. However, the effect of involveme nt is debatable due to different ideas for conceptualization and operationalization. The fo llowing two issues are barriers for obtaining general agreement about involvement: type of i nvolvement and intensity of involvement. Those two are in the midst of involvement issue. The type of involvement is the first issue for the disagreement. Some researchers proposed two ty pes of involvement to explain the construct 17

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better, namely, enduring involvement and situational involvement (Houston & Rothschild, 1978; Rothschild, 1979). The categorizatio n of involvement helped rese archers begin to propose the reasons for the disagreement. The second issue for the disagreement is the intensity of involvement, namely, high involvement and low involvement (Gainer, 1993). Involvement is also debatable due to the measuring the invol vement construct (Celsi and Olson, 1988). While researchers have defined the construct of invol vement differently (Gainer, 1993), the general agreement of involvement is the persons percei ved relevance of a product or situation on the basis of personal goals, values, and interests (Zaichkowsky, 1985). Enduring involvement can be defined as enduring personally relevant knowledge structures or ongoing concern (Martin & Marchall, 1999, p. 208). The struct ures are stored in the relatively long-term memory and obtained fr om prior experiences. Situational involvement can be defined as situation-spec ific, involving the cues and stimuli that consumers perceive as personally relevant (Martin & Marchall, 1999, p. 208). Situational involvement occurs only in specific situations. The analogy of situations being labele d as being interested in cars or purchasing a car is an exam ple of two involvement types The level of enduring involvement is concluded by how well the issue is pertained to personally relevant value, whereas the level of situational involvement is concluded by how well the situation arouses pe rsonal goals and values. The level of situational involvement is dramatically dropped when the personal goals and values are fulfilled. Since situational involvement rath er relates to characteristics of the decision situation, it is inapposite to the purpose of this study which tries to explain how enduring or longterm involvement moderates the effectiveness of the message framing. Therefore, this study employed enduring involvement as a moderator of message framing effects. 18

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There has been a substantial amount of res earch about message fr aming and involvement, respectively. However, the research about how involvement interacts with message framing has considerably been neglected. Since both involve ment and framing have been considered as important factors to predict advertising effectiveness, this disr egard is amazing. In this study, it will be investigated how message framing effects will be moderated by intensity of involvement. Connection of Involvement with Message Framing Petty and Cacioppos elaboration likelihood model (ELM) (1986) is helpful to understand how involvement affect s message framing effects. The model is composed of a central route and a peripheral r oute. When individuals are more involved with an issue or a product, they use the central route to process messa ges, whereas they use th e peripheral route to process messages when they are less involved w ith an issue or a product. The model also suggests that those who are more involved with an issue or product are more motivated to process relevant messages thoroughly, whereas t hose who are less involved with an issue or a product are less motivated to process messages. Motivation in the model is defined as inner arousal for goal achievement. The level of messa ge processing motivation has an effect on how much individuals pay more attention to and devo te to process information (Celsi & Olson, 1988). According to the model, the level of message processing motivation determines whether message claims predominate in persuasion because individuals employ either a central route or a peripheral route in persua sion process. That is, the motivation level determines the use of one of processing routes. Under conditions of low message processing mo tivation, individuals are more likely to form an attitude by relying on periphe ral cues, such as message tone, wording, and message attractiveness instead of scrutinizi ng message claims thoroughly and integrating relevant thoughts and beliefs to form an overall attitude. Hence, the pos itively framed PSA You are saving $1,000 every year by being a non-smoker may be interpreted as Non-smokers cash 19

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in without any efforts. Similarly, the negati vely framed PSA You are burning $1,000 every year by smoking cigarettes may be interpreted as Smoking costs a lot. If so, positively framed PSAs should be more effective under low involvement conditions. Under conditions of high messa ge processing motivation, indi viduals are more inclined to process all information in the ad to arrive at a decision. Thus, they process messages in detail with prior knowledge to judge the validity of messages (M aheswaran & Meyers-Levy, 1990), and integrate relevant thoughts and beliefs to form an overall attit ude (Petty, Cacioppo, & Schumann, 1983). Wright (1981) sugge sted that negative messages r eceived more considerable weight and influence than positive messages wh en individuals integrate message-relevant information. That is because overweighting ma y only occur when an audience member is sufficiently concerned over the message content to bother generating reactions and integrating those into an overall impression, and to worry about making errors in this (Wright, 1981, p. 279-280). A variety of studies have supported th e overweighting to high involvement conditions (Kanouse, 1984; Weinberger, Allen, & Dillon, 1981). The implication of those studies is that messages should be processed thoroughly and ne gative messages should be more persuasive under high involvement conditions. Based on th e previous theoretical background, following hypotheses can be predicted: H1 : The relationship between message framing effects and attitude toward anti-smoking PSAs is moderated by involvement. H1.1: For those who are highl y involved in smoking, an anti-smoking PSA is more persuasive when it is framed negatively. H1.2: For those who are le ss involved in smoking, an anti-smoking PSA is more persuasive when it is framed positively. 20

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Nicotine Dependence In the first hypothesis, it is suggested that involvement moderates the effectiveness of message framing by using general subjects including both smokers and non-smokers. This is because the message framing effects depend on the motivation of message recipients to process information. The second hypothesis is inspired by the Petty and Cacioppos model (1983) as well. In their model, motivation influences the way to process information by using either peripheral route or central one. In the sec ond hypothesis, it is suggested that the nicotine dependence level moderates the effectiveness of message frami ng by using smoker samples instead of general subjects. A number of anti-smoking researcher s revealed the relationship between nicotine dependence and motivation. Reflecting the relati onship among nicotine dependence, motivation and the way of information processes, the second hypothesis examines how the cigarette addiction level affect attitudes toward anti -smoking PSAs differently depending on the message framing. Dependence is conceptualized as compulsive physiological need for a habit-forming substance. The Diagnostic and Statistical Ma nual of Mental disorders (APA, 1994) provides several criteria for dependence wh ich are (1) tolerance; (2) wit hdrawal; (3) using larger amounts or longer than intended; (4) unsuccessful efforts to cut down; (5) much time spent to obtain substance; (6) negative social and/or occupational consequences; (7) persistent physical and/or psychological problems. The manual recommends th at an individual must meet at least three criteria to be diagnosed with dependence. Nicotine dependence refers to the physical vulnerability of our body to the chemical nicotine, which is possibly addicting when carried by various cigarette products (MayoClinic.com, 2006). 21

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Connection of Nicotine Dependence Level with Message Framing Bauer (1960) presented the c onstruct of perceived risk. And it was introduced to the marketing literature. Perceived risk is conceptualized as the pers pective that the amount that would be lost if the consequences of an act were not favorable, and th e individuals subjective feeling of certainty that the consequences will be unfavorable (Cunningham, 1967, p.37). Similarly, Stone and Winter (1987) considered risk as an expecta tion of loss. In connection with this study, perceived risk regard ing smoking can be re-conceptual ized as the perspective how well individuals understand the risk of smoking. The second hypothesis focuses on the nicotine dependence level as a moderator of message framing effects by using a sample of smokers. In Wong and McMurray (2002) study, the nicotine dependence level was related to ones perceived hea lth risk level. In addition, Rindfleisch and Crockett (1999) tested the relationship be tween nicotine dependence and perceived risk by using a college student samp le. Specifically, the less dependent on cigarette smoking subjects are, the lower level of perceive d risk they tend to have. Conversely the more dependent on cigarette smoking subj ects are, the higher level of per ceived risk they tend to have. A number studies proposed that a perceived health risk level be strongly related to ones motivation to process health-related informa tion (Block & Keller, 1995; Rothman & Salovey, 1997; Umphrey, 2003). In addition, Bock et al. (2000) revealed th e relationship between risk perception and motivation. They found that subjec ts who had higher risk perceptions were more motivated to process smoking cessation informa tion and consult doctors to discuss smoking issues than those who had lowe r risk perceptions. The sum of the relationship among nicotine dependence, perceived risk and motivation is that highly addicted subjects are more motivated to process information than less addicted subjects, while less addicted subject s are less motivated to process information than highly addicted subjects. 22

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As for the relationship between motivation and message framing, the causality that individuals motivation to process information af fects the effectiveness of message framing was supported (Kanouse, 1984; Maheswaran & Meyers-Levy, 1990; Weinberger, Allen, & Dillon, 1981). The more motivated individuals are, the more favorable attitude toward negatively framed PSAs formed, while the less motivated individuals are, the more favorable attitude toward positively framed PSAs. Therefore, nicotine de pendence has an impact on perceived risk, perceived risk relates to motivation. In a ddition, the motivation would moderate message framing effects. Finally, such relationships affect attitude toward anti-smoking PSAs. H2 : The relationship between message framing effects and attitude toward anti-smoking PSAs is moderated by nicotine dependence. H2.1: For smokers who are highly dependent on smoking, an anti-smoking PSA is more persuasive when it is framed negatively. H2.2: For smokers who are less dependent on smoking, an anti-smoking PSA is more persuasive when it is framed positively. 23

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CHAPTER 3 METHODOLOGY The purpose of this study is to investigat e how involvement and nicotine dependence moderate the message framing effects. The e xperiment was conducted to test two hypotheses from March 3rd to March 11th. at the same period. In the H1, the study was conducted to test the moderating effects of involvement on message framing with general samples, including both smokers and non-smokers. In the H2, the study was conducted to test the moderating effects of nicotine dependence on message framing with only smoker samples among collected data. Study design. To test H1, two independent variables were involvement and message framing with attitudes toward an ti-smoking PSAs as a dependent variable. The involvement level as one of independent variables was continuous (from 0: low to 7: high), and message framing was categorical variable manipulated (positiv e versus negative). Th e dependent variable, attitudes toward anti-sm oking PSAs, was measured from 1 (unfa vorable) to 7 (favorable). To test H2, two independent variables were nicotine dependence and message framing with attitudes toward anti-smoking PSAs as a dependent variable. The nicotine depende nce level as one of independent variables was continuous (from 0: low to 10: high), and message framing was categorical variable manipulated (positive versus negative). The dependent variable, attitudes toward anti-smoking PSAs, was measured fr om 1 (unfavorable) to 7 (favorable). Participants. In the H1 testing, the total number of participants was one hundred and eighty eight. They were recruited from undergraduate-level classe s and a street on the campus in the area of a southeastern American university. Du e to relatively small number of participants who currently smoke, more subjects were additiona lly recruited from a st reet on the campus. The courses where students were recru ited did not include smoking topics that might have sensitized 24

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subjects to the purpose of the study. Female pa rticipants made up 51.1 % of the sample, and 18.1% were smokers. The dominant percentage of ethnicity was Caucasians (54.9%), and followed by Hispanics (20.7%), Asian-American s (19.0%), and African-Americans (3.8%). In the H2 testing, a sample of smokers among collect data was used. Out of original participant, forty six were smokers. Female participants ma de up 42.2% of the sample, and all experiment participants were smokers. The dominant percenta ge of ethnicity was Caucasians (55.6%), and followed by Hispanics (15.6%), Asian-Ameri cans (26.7%), and Afri can-Americans (2.2%). Stimuli. Two versions of a print anti-smoki ng public service announcements were created to test both hypotheses. As shown Figure 1 and 2, visuals and layout were equal across experimental groups. Two advertisements cont ained either a positively framed message or a negatively framed message. Both advertisements presented the argument that stopping or continuing with cigarette consumption can lead to a financial gain or loss equivalent to two iPhones which is one of the most appealing and familiar products among college students. Thus, experiment participants can recogn ize the value of financial gain or loss easily that is caused by stopping or continuing with ci garette consumption. The manipulation of message framing occurred in the body copy. For the negatively framed message, the following message was used: You are burning $1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000. For the positively framed message, the follo wing message was used: You are saving $1,000 every year by being a non-smoker. You can buy 2 iPhones with $1,000. Procedure. Sessions were conducted in small classroom settings and on a street on the campus. Participants were instructed that the purpose of the study was to understand consumers ideas about smoking message. After the informed consent was secured, participants were randomly assigned into one of the two experiment al conditions. In the H1 testing, ninety one 25

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participants (48.4%) were assigned into Group 1 a nd shown the negatively framed PSA. Ninety seven participants (51.6%) were assigned into Group 2 and shown the positively framed PSA. In the H2 testing, twenty four pa rticipants (52.2%) were assigned into Group 1 and shown the negatively framed PSA. Twenty two participants (47.7%) were assigned into Group 2 and shown the positively framed PSA. After reading the anti-smoking PSA, they completed the scales designed to check manipulation, involvement, and measure of dependent variable. For the duration of each session, the expe rimenter ensured that particip ants completed the instrument independently and did not turn back to the page s they had already read. Upon completion of the instrument, subjects were thanked and debr iefed. Each session took about ten minutes. Independent Variables Message framing (positive vs. negative). Message framing was employed as an independent variable to test both hypotheses. The positively-framed PSA illustrated the positive effect of quitting smoking by stating You are sa ving $1,000 every year by being a non-smoker. You can buy 2 iPhones with $1,000, while the ne gatively framed PSA emphasized the adverse effects of smoking by stating You are burning $1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000. The partic ipants reported on a two-item, seven-point (1 = strongly disagree, 7 = strongly agree) Likert scale how much they agreed with the following two statements: The ad is focusing on the positive effect of smoking cessation, and The ad is focusing on the negative effect of smoking. Involvement. Involvement was used as a measured va riable in the H1. Participants were asked to answer smoking involvement items. Five seven-point semantic differential items were used to measure involvement level (1 = important irrelevant, valuable, useful, and interesting, 7 26

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= unimportant, relevant, invaluable useless, and not interesting). The scales were adapted from Zaichkowsky (1985). The scale was internally consistent ( = .89). Nicotine dependence. The nicotine dependence level was measured using the Fagerstrm Nicotine Dependence Scale (Heatherton, 1991) in the H2. Smokers were asked to answer the following questions: 1. How soon after you wake up do you smoke your first cigarette? a. Within 5 minutes (3 points) b. Within 6-30 minutes (2 points) c. Within 31-60 minutes (1 point) d. After 60 minutes (0 points) 2. Do you find it difficult to refrain from sm oking in places where it is forbidden (e.g., in church, at the library, in cinema, etc)? a. Yes (1 point) b. No (0 points) 3. Which cigarette would you hate most to give up? a. The first one in the morning (1 point) b. Any other (0 points) 4. How many cigarettes per day do you smoke? a. 10 or less (0 points) b. 10-20 (1 point) c. 21-30 (2 points) d. 31 or more (3 points) 5. Do you smoke more during the first hours af ter waking than during the rest of the day? a. Yes (1 point) b. No (0 points) 6. Do you smoke even when you are ill enough to be in bed most of the day? a. Yes (1 point) b. No (0 points) All points were added up on the basis of subj ects responses and the assigned points. For example, if someone smokes his or her first ci garette after waking up within 5 minutes, finds it difficult to refrain from smoking-fr ee places, hates to give up the first morning cigarette, smokes 27

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31 or more cigarette per day, smokes more ci garette during the firs t hour after waking, and smokes even when he or she is ill enough to be in bed most of the day, the nicotine dependence level indicates 10. The nicotine dependence leve l was measured being continuous. The range of the nicotine dependence level is from 0 (low) to 10 (high). He atherton et al. (1991) suggested that a score of 5 or more indi cates a significant smoking dependen ce, while a score of 4 or less shows a low to moderate dependence. Dependent variable. Attitude toward Ad. One dependent variable was me asured to test both hypotheses: Attitudes toward Ad. The dependent variable was measured using a four-item, seven-point semantic differential scale (1 = unpleasant, un likable, not irritating, and not interesting, 7 = pleasant, likable, irritating, and interesting) (Olney, Holbrook, and Ba tra, 1991). The third item for measuring involvement level (i .e., not irritating vs. irritati ng) was reverse coded. The scale was internally consistent ( = .85), and the responses were averag ed to represent the construct for the H1 ( M = 4.32, SD = 1.34). For the H2, the scale was internally consistent ( = .93), and the responses were averaged to represent the construct ( M = 4.26, SD = 1.63). 28

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CHAPTER 4 RESULTS Hypothesis 1 Multiple regressions were conducted to test H1, with two independent variables, involvement and message framing, and one dependent variable, attitude toward ad. A sample of smokers and non-smokers was used to test how i nvolvement moderates message framing effects. Manipulation Check Before testing H1, a manipulation check was conducted. As expected, the message that You are saving $1,000 every year by being a non-smoker, You can buy 2 iPhones with $1,000 was perceived as the positive anti-smoking message, whereas the message that You are burning $1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000 was perceived as the negative message. Participants reported on a two-item, seven point (1 = strongly agree, 7 = strongly disagree) Likert scale how much they agreed with the following two statements: The ad is focusing on the positive effect of smoking cessation, and The ad is focusing on the negative effect of smoking. As shown Table 1, difference between observed value for positively framed message and test value (= 4) was significant on item one, t = -4.96, p < .001 M PositiveMessage = 3.06, SD = 1.86. As shown Table 2, difference between observed value for negatively framed message and test va lue (=4) was significant on item two, t = -6.07, p < .001 M NegativeMessage = 2.88, SD = 1.76. Subjects felt that the anti -smoking PSA was more negative when it was negatively framed rather than positiv ely framed, and they felt that the anti-smoking PSA was more positive when it was positively frame d rather than negatively framed. Therefore, these manipulation check measures suggest th at the intended factors were manipulated successfully. 29

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Involvement In the H1 testing, the study was conducted to investigate how involvement moderates the message framing effects. And the message fram ing was manipulated. Invol vement was measured as a continuous variable on the basis upon Zaichkowsky (1985). The scale measuring involvement level was internally consistent ( = .89). Test of Hypothesis 1 Influence of Involvement and Message Framing This study investigated how involvement moderates the effectiveness of message framing. Specifically, Subjects who are more i nvolved with smoking issue would have more favorable attitude toward nega tively framed PSAs, while subjec ts who are less involved with smoking issue would have more favorable attitude toward positively framed PSA. A multiple regression was conducted to test H1, with attitude toward the ad as a dependent variable, with the involvement level and message framing as independent variables. The descriptive statistics are presented in Table 3. The mean of involvement was 2.67 (SD = 1.62), .52 (SD = .50) for message framing, and 4.31 (SD = 1.33) for attitude toward ad, respectively. The model with two independent variables, the involvement level and the message framing, and the joint effect of these tw o variables was statis tically significant, F (3, 184) = 7.75, p < .001 Message framing was employed as a dummy variable where a negatively framed PSA was 0, and a positively framed PSA was 1. The results are presented in Table 4 and 5. Initially, a multiple regression was conducted with only tw o independent variables, involvement and message framing. Its F-value was 1.86. Adding the in teraction, then, contributed to 9.3% of the model with only two independent variables. F-value change was 19.18. The effect of the interaction between the addiction leve l and message framing was b = -.50, t = -4.38, p < .001 30

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The interaction term was again explored by re-computing the regression analyses separately for groups of subjects exposed to negative message or positive message in terms of message framing. Results from follow-up analyses revealed that involvement was positively associated with attitude to ward anti-smoking PSA among subjects who were exposed to the negative message (F (1, 89) = 2.34, = .16, t = 1.53, p > .05), whereas involvement was negatively associated with attitude toward an ti-smoking PSA among subjects who were exposed to positive message ( F (1, 95) = 24.40, = -.45, t = -4.94, p < .001 ). Results of the interaction tests are presented in Table 6. Thus, the more involved in smoking, the more favorable attitude to ward negatively framed PSAs individuals tend to have, while the less invo lved in smoking, the more favorable attitude toward positively framed PSAs individuals tend to have. These results support overall assumption of H1. However, when regression analyses were conducted separately by selecting cases (e.g., subjects who were exposed to the negatively framed PSA vs. subjects who were exposed to the positively framed PSA), H1 was partially supported. That is, H1.1 was supported whereas H1.2 was not supported. The main effect of the involvement level was b = .13, t = 1.65, p > .05. The main effect of message framing was b = 1.32, t = 3.71, p < .001 Since this result is irrelevant to this study, no interpretations are provided for main effects. Hypothesis 2 Multiple regressions were conducted to test H 1, with two independent variables, nicotine dependence and message framing, and one dependent variable, attitude toward ad. A sample of smokers among collected data was used to te st how nicotine dependence moderates message framing effects. 31

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Manipulation Check Before testing H2, manipulation check was c onducted. As expected, the message that You are saving $1,000 every year by being a non-sm oker, You can buy 2 iPhones with $1,000 was perceived as the positive anti-smoking message whereas the message that You are burning $1,000 every year by smoking cigarettes. You can buy 2 iPhones with $1,000 was perceived as the negative message. Participants reported on a two-item, seven point (1 = strongly agree, 7 = strongly disagree) Likert scale how much they agreed with the following two statements: The ad is focusing on the positive effect of smoking cessation, and The ad is focusing on the negative effect of smoking. As shown Table 7, difference between observed value for positively framed message and test value (= 4) was significant on item one, t = -5.89, p < .001 M PositiveMessage = 2.05, SD = 1.56. As shown Table 8, difference between observed value for negatively framed message and test va lue (=4) was significant on item two, t = -3.09, p < .01 M NegativeMessage = 2.92, SD = 1.72. Subjects felt that the anti -smoking PSA was more negative when it was negatively framed rather than positiv ely framed, and they felt that the anti-smoking PSA was more positive when it was positively frame d rather than negatively framed. Therefore, these manipulation check measures suggest th at the intended factors were manipulated successfully. Nicotine Dependence In the H2 testing, the study was conducted to investigate how nicotine dependence moderates the message framing effects. And the message framing was manipulated. Nicotine dependence was measured as a continuous vari able on the basis upon Heatherton et al. (1991). 32

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Test of Hypothesis 2 Influence of Nicotine dependence and Message Framing This study investigated how a ddiction level affects attit ude toward anti-smoking PSA when it is framed either positively or negatively. Specifically, Subjects who are more addicted to smoking would have more favorab le attitude toward negativel y framed PSAs, while subjects who are less addicted to smoking would have more favorable attitude to ward positively framed PSA. A multiple regression was conducted to test H2, with attitude toward the ad as the dependent variable, and with the addiction level and message fram ing as independent variables. The descriptive statistics were presented in Table 9. The mean of smoking addiction was 3.11 (SD = 2.27), .48 (SD = .51) for message framing, and 4.26 (SD = 1.63) for attitude toward ad, respectively. The model with two independent variables, the addiction level and the message framing, and the joint effect of these two vari ables was statistically significant, F (3, 42) = 6.72, p < .001 Message framing was employed as a dummy variab le where a negatively framed PSA was 0, and a positively framed PSA was 1. The results are pr esented in Table 10 and 11. Initially, a multiple regression was conducted with only two independent variables, nicotine dependence and message framing. Its F-value was 7.46. Adding the in teraction, then, contributed to 6.7% of the model with only two independent variables. F-value change was 4.15. The effect of the interaction between the nicotine dependen ce level and message framing was b = -.38, t = -2.04, p < .05. Interaction was again explored by re -computing the regression analyses separately for groups of subjects exposed to negative message or positive message in terms of message framing. Results from follow-up analyses revealed that nicotine dependence was positively associated 33

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with attitude toward anti-smoking PSA among subjects who were exposed to the negative message ( F (1, 22) = .02, = .03, t = .13, p > .05), whereas nicotine dependence was negatively associated with attitude towa rd anti-smoking PSA among subjects who were exposed to positive message ( F (1, 20) =9.63, = -.57, t = -3.10, p < .01 ). The results of interaction tests are presented in Table 12. Thus, t he more dependent on cigarette smoking, the more favorable attitude toward negatively framed PSAs individuals tend to have while the less dependent on cigarette smoking, the more favorable attitude toward positively framed PSAs individuals tend to have. These results support overall assumption of H1. Howe ver, when regression analyses were conducted separately by selecting cases (e.g., subjects who were exposed to the negatively framed PSA vs. subjects who were exposed to the positively fram ed PSA), H1 was partially supported. That is, H1.1 was supported whereas H1.2 was not supported. The main effect of the addiction level was b = .02, t = .14, p > .05. The main effect of message framing was b = -.16, t = -.23, p > .05. Thus, both main effects were not statistically significant. 34

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Table 4-1. Manipulation Check of Positively Framed Message for Item 1 in H1 Testing N Mean SD t df Sig. Mean Difference Positively Framed Message (Item 1) 97 3.06 1.86 -4.96 96 .000 -.94 Test value = 4 Table 4-2. Manipulation Check of Negatively Framed Message for Item 2 in H1 Testing N Mean SD t df Sig. Mean Difference Negatively Framed Message (Item 2) 91 2.88 1.76 -6.07 90 .000 -1.12 Test value = 4 Table 4-3. Descriptive Statistics of H1 M SD Attitude toward Ad 4.31 1.33 Involvement 2.67 1.62 Message Framing .52 .50 Table 4-4. Model Statistics of H1 Model Source SS df MS F Sig. R R Square R Adj Involvement Regression 6.55 2 3.27 Framing Residual 325.93 185 1.76 Model 1 Total 332.48 187 1.86 .159 .14 .02 .01 Involvement Regression 37.32 3 12.44 Framing Residual 295.17 184 1.60 Model 2 Interaction Total 332.48 187 7.75 .000 .34 .11 .10 Table 4-5. Regression of H1 Source B SE t Sig. (Constant) 3.96 .25 15.68 .000 Involvement* .13 .08 .16 1.65 .100 Framing** 1.32 .36 .50 3.71 .000 Interaction -.50 .11 -.66 -4.38 .000 *Involvement: 1 (low) to 7 (high) **Message Framing: 0 (negatively framed me ssage), 1 (positively framed message) 35

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Table 4-6. Follow-up Analyses for Interaction in H1 Message Framing IV B SE t Sig. Negative Involvement .133 .087 .160 1.529 .130 R = .160, R 2 = .026, R 2 Adj = .015 Positive Involvement -.367 .074 -.452 -4.939 .000 R = .452, R 2 = .204, R 2 Adj = .196 Table 4-7. Manipulation Check of Positively Framed Message for Item 1 in H2 Testing N Mean SD t df Sig. Mean Difference Positively Framed Message (Item 1) 22 2.05 1.56 -5.89 21 .000 -1.96 Test value = 4 Table 4-8. Manipulation Check of Negatively Framed Message for Item 2 in H2 Testing N Mean SD t df Sig. Mean Difference Negatively Framed Message (Item 1) 24 2.92 1.72 -3.09 23 .005 -1.08 Test value = 4 Table 4-9. Descriptive Statistics of H2 M SD Attitude toward Ad 4.26 1.63 Addiction Level 3.11 2.27 Message Framing 0.48 0.51 Table 4-10. Model Statistics of H2 Model Source SS df MS F Sig. R R Square R Adj Addiction Regression 30.90 2 15.45 Framing Residual 89.03 43 2.07 Model 1 Total 119.94 45 7.46 0.002 0.51 0.26 0.22 Addiction Regression 38.91 3 12.97 Framing Residual 81.02 42 1.93 Model 2 Interaction Total 119.94 45 6.72 0.001 0.57 0.32 0.28 36

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Table 4-11. Regression of H2 Source B SE t Sig. (Constant) 4.85 0.52 9.36 0.000 Addiction* 0.02 0.14 0.03 0.14 0.892 Framing** -0.16 0.71 -0.05 -0.23 0.820 Interaction -0.38 0.19 -0.55 -2.04 0.048 *Nicotine Addiction: 1 (low) to 10 (high) **Message Framing: 0 (negatively framed me ssage), 1 (positively framed message) Table 4-12. Follow-up Analyses for Interaction in H2 Message Framing IV B SE t Sig. Negative Nicotine Dependence .019 .146 .028 .133 .895 R = .028, R 2 = .001, R 2 Adj = -.045 Positive Nicotine Dependence -.358 .115 -.570 -3.104 .006 R = .570, R 2 = .325, R 2 Adj = .291 37

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CHAPTER 5 DISCUSSION AND CONCLUSION Discussion This study was designed to resolve the conf licting findings of message framing effects and identify the variables that have an impact on the effectiveness of message framing. Overall, the results are compatible with this studys grand assumption that involvement level and cigarette addiction level moderate message framing effects. In the H1, the contention of this study is that involvement level moderates the effectiveness of either positively or negatively framed anti-smoking PSAs. This contention is based on Petty and Cacioppos model and previous research about overweighting of negative and positive messages (Kanouse, 1984; Petty & Cacioppo, 1986; Weinberger, Allen, & Dillon, 1981; Wright, 1981). Consistent with th e H1, the involvement level indi cates favorability of either a positively framed PSA or a negatively framed one. These results are consistent with previous research dealing with involvement and messa ge framing (Maheswaran & Meyers-Levy, 1990) that proposed the moderating role of involvement. However, after conducting separate analyses by selecting cases whether subjects were exposed to either negatively or positively framed message, H1 was partially supported. Specifically, in the H1.1, the following was pr edicted: Under high involvement conditions, an anti-smoking PSA is more persuasive when it is framed negatively. Although an intended direction was found, it was not statis tically significant. Therefore, H1.1 was not supported. In the H1.2, the following was predicted: Under low in volvement conditions, an anti-smoking PSA is more persuasive when it is framed negativel y. Intended significant re sults were found. Thus, H1.2 was supported. 38

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In the H2, the contention of this study is that smoker s nicotine dependence level moderates the effectiveness of either positivel y or negatively framed anti-smoking PSAs. This contention is based on the relationship among nico tine dependence, perceived risk, motivation, and message framing. The causalities are that nicotine dependence has an impact on perceived risk (Rindfleisch & Crocke tt, 1999; Wong & McMurray, 2002), perceived risk relates to motivation (Block & Keller, 1995; Rothman & Salovey, 1997; Bock et al., 2000; Umphrey, 2003). In addition, the motivation would modera te message framing effects (Kanouse, 1984; Weinberger, Allen, and Dillon, 1981). Consistent with the H2, the nicotine dependence level indicates favorability of either a positively framed PSA or a negatively framed one. However, after conducting separate analyses by selecting cases whether subjects were exposed to either negatively or positively framed message, H2 was partially supported. Specifically, in the H2.1, the following wa s predicted: Under high nicotine dependence conditions, an anti-smoking PSA is more persua sive when it is framed negatively. Although an intended direction was found, it was not statisti cally significant. Therefore, H2.1 was not supported. In the H2.2, the following was predic ted: Under low nicotine dependence conditions, an anti-smoking PSA is more persuasive when it is framed negatively. Intended significant results were found. Thus, H2.2 was supported. Implications This study improves our understanding how individuals process and respond differently to dissimilar but objectively equivalent messages. In the practice, anti-smoking clinic consultants might be advised to use either negatively or positively framed message depending on clients nicotine dependence level. For example, the c onsultants can measure their clients nicotine dependence level. When they consult with cl ients with low nicotine dependence, positive message will be more effective in terms of lowering cigarette consumption or smoking cessation. 39

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In other words, negative message will be more effective when they consult with clients with high nicotine dependence. Anti-smoking PSA executioners might be advised to employ either negatively or positively framed message depending on message recipients involvement level. Moreover, it is also helpful to choose appropriate place and time for implementing anti-smoking PSAs. For instance, when PSA executioners pla ce anti-smoking PSAs in magazines, the message framing will depend on magazine types. More specifically, when a positively framed PSA is placed in a teen magazine, we can predict better effects because teens involvement level might be low. Therefore, anti-smoking consultants a nd PSA executioners can create either negative or positive message by categorizing target groups into either smoker or non-smoker group. Limitations and Future Research There are a few limitations in the study. Th is project is based the use of student participants as a sample. Although the use of student participants is more acceptable in experimental studies than in survey, homogeneit y of the sample may have produced results that are not typically found in the popul ation. Findings of this project need to be replicated using more a heterogeneous, adult sample to achieve external validity. This study tested anti-smoking PSAs impact on attitude towa rd messages, not intention to quit smoking or attitude toward smoking behavior Attitude toward ad has been posited to be a mediator of advertising effec tiveness which includes brand atti tudes and future intentions (Mitchell & Olson, 1981; Shimp, 1981). This study measured one dependent variable: attitude toward ad. This study found significant interaction effects by measuring attitude toward ad as a dependent variable in both experiments. Howeve r, it might have different results if different dependent variables such as att itude toward smoking behavior or intention to quit were employed. This is because the majority of smokers do not ha ve an intention to give up smoking in the near future (Hennrikus, Jeffery & Lando, 1995; John, Meyer, Rumpf, & Hapke, 2003). Therefore, 40

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future research should employ othe r dependent variables, and test whether attitude toward ad can predict future intentions in anti-smoking PSA research. In the message framing studies, different messages should contain a factually equal value. The two versions of stimuli used in this study should be equal across experimental groups except message framing (e.g., saving money vs. burning money). Except for the framing, causalities of messages are different. For example, in the positively framed message, the message posits that non-smoking can save $1,000 every year, whereas, in the negatively framed message, the message posits that smoking can burn $1,000 ev ery year. The different causalities in the messages may have produced unint ended results. Future message framing studies should create same messages across experimental groups. In addition to the message framing valence, involvement scales employed in this study may have produced unexpected results. The Zaic hkowskys scale (1985) measures an issue involvement. The stimuli in this study focu sed on cessation of smoking. Even though this study intended to measure an issue involvement, partic ipants might think of smoking cessation issue rather than smoking issue. Future studies should use an appropriate scale to measure involvement level. 41

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Figure 3-1. Positively Framed PSA 42

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Figure 3-2. Negatively Framed PSA 43

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APPENDIX A INFORMED CONSENT FORM Protocol Title: College St udents Ideas About Smoking Please read this consent statement carefully be fore you decide to par ticipate in this study Purpose of the research study: The purpose of this research is to study college students ideas about smoking. The participants will be asked questions about their beliefs and personal experiences about smoking. What you will be asked to do in this study: You will be invited to a laboratory. After the investigators instruction, print your name and student ID on the attached name sheet, sign the consent form, and complete the que stionnaire adequately apart from others. When your instructor requests the survey, detach the name sheet and th is consent form from the main survey. Then submit the consent form, name sheet, and the envelope separately. Time required: About 15 minutes Risks and Benefits: We do not anticipate there will be any risks or direct benefits to you as a consequence of your decision to complete the survey. Confidentiality: Your name or student ID will not appear on the questionnaire itself. Your identity will be kept confidenti al to the extent provided by law. Your instructor will need your student ID to give you extra credit, but will not receive your name before the final exam. Your responses are completely confidential and no refere nce will be made in any oral or written report that would link you individually to the study. Fu rther, the principal investigator works independently of your instructor. Voluntary participation: Your participation in this study is completely voluntary. Right to withdraw from the study: You have the full right to w ithdraw from the study at anytime without consequence. Whom to contact if you have questions about the study: Wan Seop Jung, Masters student, College of Communications, University of Florid a, address: 2018 Weimer Hall, University of Florida, Gainesville, FL, 32611-8400. phone: 352.870.2077 email: wanseop9@ufl.edu. Jorge Villegas, Assistant Professor, College of Commu nications, University of Florida, address: 2084 Weimer Hall, University of Florid a, Gainesville, FL, 32611-8400. phone: 352.392.5059. email: jvillegas@jou.ufl.edu Whom to contact about your right as a research participant in this study: UFIRB, Box 112250, University of Florid a, Gainesville, FL 32611-2250; ph 392-0433 Agreement: I have read the procedure described above. I voluntarily agree to participate in the procedure and I have received a copy of this description. Participant: __________________________________ Date: ______________________ Principal Investigator : __________________________ Date: ______________________ 44

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APPENDIX B QUESTIONNAIRE Instructions : Please review the following advertisement and then answer the questions that correspond with a partic ular advertisement. Directions : The following questionnaire asks you to indicate your opinion about the antismoking ad The scales in some of the questions are meant to measure your opinions on each of the ad. There is no right or wrong answers. 45

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Please read each set of adjectives carefully, and decide where your opinion would be the most accurately reflected on the continuum. Then, mark on the square that most closely reflects your opinion. You may refuse to answer any questio ns. Remember, there are no right or wrong answers. 1) Do you agree that the ad is focusing on positive effect of smoking cessation? 1 2 3 4 5 6 7 Strongly agree Strongly disagree 2) Do you agree that the ad is focusing on negative effect of smoking? 1 2 3 4 5 6 7 Strongly agree Strongly disagree Please check the scale that best reflects your agreement with each of the following items. 3) In general, smoking is. 1 2 3 4 5 6 7 Important Unimportant 1 2 3 4 5 6 7 Irrelevant Relevant 1 2 3 4 5 6 7 Valuable Invaluable 1 2 3 4 5 6 7 Useful Useless 1 2 3 4 5 6 7 Interesting Not interesting 46

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4) Do you find the advertisement is (EVALUATION OF THE ADVERTISEMENT) : 1 2 3 4 5 6 7 Unpleasant Pleasant 1 2 3 4 5 6 7 Unlikable Likable 1 2 3 4 5 6 7 Not irritating Irritating 1 2 3 4 5 6 7 Not interesting Interesting 5) Please check your smoking behavior on the square. ( If you are not a smoker go to the next page ) 1. How soon after you wake up do you smoke your first cigarette? 0-5 min 6-30 min 31-60 min After 60 min 2. Do you find it difficult to refrai n from smoking in places where it is forbidden (e.g., church library, cinema)? Yes No 3. Which cigarette would you be th e most unwilling to give up? First in the morning Any of the others 4. How many cigarettes per day do you smoke? 10 or less 11 to 20 21 to 30 31 or more 5. Do you smoke more frequently during th e first hours after waking than during the rest of the day? Yes No 6. Do you smoke if you are so ill that you are in bed most of the day? Yes No 47

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Demographics 1) What is your gender? Female ____ Male ____ 2) How old are you? _______ years old 3) What is your ethnic background? White, not Hispanic ____ Hispanic, of any race ____ African American, not Hispanic ____ Asian or Pacific Islander ____ Native American ____ Other ____ 4) Please check your smoking experience. Never smoked _____ I used to smoke, do not smoke currently _____ I smoke currently _____ Thank you for your participation. Debriefing Statement The messages in the ads were fictional. Although those ads were created for this study, the messages in the ads were based on facts. 48

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BIOGRAPHICAL SKETCH Wan Seop Jung was born in Busan, Korea. He earned his Bachelor of Advertising and Public Relations from Chung-Ang University in Seoul, Korea. He came to the University of Florida in August 2006 to pursue a Master of A dvertising. He is received his Master of Advertising degree in August of 2008. He continues with his doctoral studies at the University of Florida. 56