ABSTRACT

PREDICTING FLOSSING BEHAVIORS WITH THE THEORY OF PLANNED

BEHAVIOR AND MESSAGE INTERVENTIONS

Gayle Susanne Wachowiak, M. A.

Department of Communication

Northern Illinois University, 2010

Mary Lynn Henningsen, Director

The theory of planned behavior was used to predict flossing intentions and

behavior. Participants who did not floss were exposed to a flossing advocacy that

activated the attitudinal, normative, or behavioral control component of the TPB.

In the first wave of the survey, college students were exposed to message

interventions and completed a survey that measured attitudes toward behavior,

subjective norms, perceived behavioral control, and behavioral intention. In the

second wave of data collection, participants reported how often they flossed in a

two-week period.

Consistent with the theory of planned behavior, attitudes and subjective

norms predicted behavioral intention. Behavioral intention was found to be a

statistically significant predictor of flossing behavior. Contrary to expectations,

perceived behavioral control did not predict behavioral intention or behavior. The

message interventions did not increase flossing behavior. The discussion focuses

on the relationship between message interventions and the theory of planned

behavior.

NORTHERN ILLINOIS UNIVERSITY

DE KALB, ILLINOIS

JULY 2010

PREDICTING FLOSSING BEHAVIORS WITH THE THEORY OF PLANNED

BEHAVIOR AND MESSAGE INTERVENTIONS

BY

GAYLE SUSANNE WACHOWIAK

2010 Gayle S. Wachowiak

A THESIS SUBMITTED TO THE GRADUATE SCHOOL

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE

MASTER OF ARTS

DEPARTMENT OF COMMUNICATION

Thesis Director:

Mary Lynn Henningsen

ACKNOWLEDGEMENTS

The author wishes to express sincere appreciation to Professors Mary Lynn

Henningsen, Kathryn Cady, and Joseph Scudder for their assistance in the

preparation of this document.

TABLE OF CONTENTS

Page

LIST OF TABLES ………………………………………………………….. v

LIST OF FIGURES …………………………………………………………. vi

LIST OF APPENDICES …………………………………………………….. vii

Chapter

1. REVIEW OF RELEVANT LITERATURE ………………………... 1

Health Behaviors ……………………………………………. 1

Dental Health Behaviors ……………………………………. 3

Theory of Planned Behavior ………………………………… 5

Message Interventions ………………………………………. 10

2. METHOD …………………………………………………………… 12

Participants ………………………………………………….. 12

Procedure …………………………………………………… 12

Message Intervention Design ………………………………... 13

Survey Measures …………………………………………….. 14

First-Wave Survey ………………………………….... 14

Second-Wave Survey ……………………………….... 17

iv

Chapter Page

3. RESULTS …………………………………………………………… 18

Manipulation Check Analysis ………………………………. 18

Hypotheses 1 and 2 …………………………………………. 20

Research Question 1 ………………………………………… 22

Research Question 2 ………………………………………… 24

4. DISCUSSION ………………………………………………………. 31

Practical Implications of Messages ………………………… 31

Theoretical Implications ……………………………………. 32

Limitations and Directions for Future Research ……………. 34

Conclusion ………………………………………………….. 35

REFERENCES ……………………………………………………………… 38

APPENDICES ……………………………………………………………… 43

LIST OF TABLES

Table Page

1. Correlations Between Theory Components and Message Types …... 24

2. P Values Between Message Types Across AB-BI Theory

Component …………………………………………………………. 26

3. P Values Between Message Types Across SN-BI Theory

Component …………………………………………………………. 27

4. P Values Between Message Types Across PBC-BI Theory

Component …………………………………………………………. 28

5. P Values Between Message Types Across BI-B Theory

Component …………………………………………………………. 29

6. P Values Between Message Types Across PBC-B Theory

Component …………………………………………………………. 30

LIST OF FIGURES

Figure Page

1. The Theory of Planned Behavior as Hypothesized ………………… 8

2. Initial Model Fit ……………………………………………………. 21

3. Revised Model Fit ………………………………………………… 22

LIST OF APPENDICES

Appendix Page

A. MESSAGE ONE (ATTITUDE-RELATED) ………………………. 44

B. MESSAGE TWO (SUBJECTIVE NORM-RELATED) …………… 46

C. MESSAGE THREE (PERCEIVED BEHAVIORAL

CONTROL-RELATED) …………………………………………… 48

D. MESSAGE FOUR (CONTROL MESSAGE) ……………………… 50

CHAPTER 1

REVIEW OF RELEVANT LITERATURE

Health Behaviors

Social scientists have researched various health behaviors to identify which

determinants of behavior generate desired outcomes (e.g., Ajzen & Timko, 1986;

Åstrøm, 2008; Bish, Sutton, & Golombok, 2000; Brenes, Strube, & Storandt, 1998;

Finlay, Trafimow, & Villarreal, 2002). Ajzen and Timko (1986) argued “the

readiness to perform health-related behavior is a function of such general

orientations as health concerns, willingness to seek medical help, perceived

vulnerability to illness, faith in doctors and medicine and feelings of control over the

disease” (p. 259). It is important, then, to investigate these predispositions in order

to formulate messages for specific behavioral outcomes and to help narrow any gap

between the intention to perform the behavior and the behavior itself. One such

framework, the theory of planned behavior (TPB; Ajzen, 1991), has been utilized in

the prediction of health behaviors such as smoking cessation (e.g., Lee, Ebesu

Hubbard, Kulp O’Riordan, & Kim, 2006), exercising (e.g., Brenes et al.,1998;

Finlay et al., 2002), condom use (e.g., Sanchez-Garcia & Batista-Foguet, 2008) and

self-health examinations (e.g., Luszczynska & Schwarzer, 2003; McCaul, Sangren,

O’Neill, & Hinsz, 1993; McClenahan, Shevlin, Adamson, Bennett, & O’Neill,

2

2007). General results supported Ajzen’s (2009) recommendation stating message

interventions can be formatted to address personal attitudes about the behavior, what

others may think about the behavior, or the amount of personal control perceived

over the situation.

Social psychologists and communication scholars have attempted such

message interventions within the theory of planned behavior framework to promote

healthy behaviors (e.g., Beale & Manstead, 2006; Fishbein et al., 2001; Jemmott,

Jemmott, Fong, & McCaffree, 1999; Maddock, Silbanuz, & Reger-Nash, 2008).

Interventions such as educational messages (Beale & Manstead, 2006; Fishbein et

al., 2001), counseling sessions (e.g., Fishbein et al., 2001), videos and games (e.g.,

Jemmott et al., 1999), and television and mall advertisements (e.g., Maddock et al.,

2008) have been formulated to address either the behavioral beliefs of attitudes,

normative beliefs of subjective norms, or the control beliefs of perceived behavioral

control to influence positive behavioral changes.

In addition to general health behaviors, dental health behaviors have also

been studied by persuasion scholars. Specifically, dental hygiene behaviors (i.e.,

brushing and flossing) have been given special attention in social scientific literature

(e.g., Åstrøm, 2008; Hoogstraten, DeHaan, & Klecan, 1985; Lavin & Groarke,

2005; McCaul, O’Neill, & Glasgow, 1988; McCaul et al., 1993; Schüz, Sniehotta, &

Schwarzer, 2007; Schwarzer et al., 2007; Sniehotta, Soares, & Dombrowski, 2007;

Tedesco, Keffer, & Fleck-Kandath, 1991).

3

Dental Health Behaviors

Without proper brushing and flossing behaviors, the American Dental

Association asserts bad breath, decay, gum disease, and tooth loss can occur (ADA,

2005). Daily brushing will remove plaque from the teeth, but is ineffective at

removing plaque that has accumulated interproximally. According to the Academy

of General Dentistry (AGD; 2008), flossing is the most effective way of removing

plaque from between the teeth. Although nearly all Americans believe taking care

of their mouth, teeth, and gums is very important, only 49% of people floss daily

and 10% do not floss at all (ADA, 2008). Flossing, however, is greatly beneficial to

dental health (AGD, 2008).

Dental professionals are at a loss when oral hygiene instruction fails to

develop the skills or maintenance behaviors needed to continue good oral hygiene

between visits (e.g., Ashkenazi, Cohen, & Levin, 2007; Little et al., 1997). Despite

receiving education and instruction regarding proper brushing and flossing

techniques, the National Institute of Dental and Craniofacial Research

(NIDCR; 2010) estimates over 80% of all Americans have some form of gum

disease. In order to gain patient flossing compliance, past studies on dental

behaviors included supplementing the education and instruction received from

dental professionals in the form of implementation intentions or action planning

interventions (e.g., Åstrøm, 2008; Lavin & Groarke, 2005; Schwarzer et al., 2007;

Sniehotta et al., 2007). During the experiments, participants were asked to form a

4

concrete plan of where, when, and how to floss. Results indicated planning

interventions significantly affected flossing behaviors (Sniehotta et al., 2007),

mediated between intention and behavior (Schwarzer et al., 2007), and planning

interventions were an independent predictor of future flossing behavior (Åstrøm,

2008).

In contrast, Lavin and Groarke’s (2005) study found no significant

differences between those participants who made implementation intentions to floss

and those who did not, indicating implementation intentions were not an effective

way to increase flossing behavior. Therefore, Lavin and Groarke suggested future

studies on flossing behaviors should focus on message interventions of the

antecedents of intention (i.e., attitudes, subjective norms, perceived behavioral

control) to increase dental flossing intentions and behaviors.

In order to strategically form dental health behavioral messages to the target

audience, a well-replicated theory which identifies the attitudes about the behavior,

what others may think about the behavior, and the amount of personal control over

the situation should be employed. In this thesis, the TPB (Ajzen, 1991) will be

utilized to measure which constructs predict intention and desired flossing behavior.

Theoretically, intervention messages should influence one or more of the

antecedents of intention (i.e., attitude, subjective norm, or perceived behavior

control) which in turn should affect intention and behavior (Ajzen & Fishbein,

5

2005). Therefore, the aim of this thesis is to replicate the TPB in regards to

previous flossing studies, and to identify which intervention messages will

strengthen the intention-behavior relationship to promote the desired dental health

behavior of daily flossing.

Theory of Planned Behavior

The theory of planned behavior (Ajzen, 1991) proposes three determinants

of intention to perform a behavior: attitude, subjective norm, and perceived

behavioral control. The attitude and subjective norm conceptualizations were

adopted from Fishbein and Ajzen’s (1975) theory of reasoned action. The third

conceptualization of perceived behavioral control was introduced by Ajzen (1991)

to form the theory of planned behavior.

The theory of reasoned action (TRA; Fishbein & Ajzen, 1975) specifies

attitudes toward performing a behavior and subjective norms predict the intention to

perform the desired behavior. In the TRA, attitudes are defined as evaluations of

the behavior which are strongly influenced by behavioral beliefs. Subjective norms

are defined as the “perceived social pressure to perform or not perform the

behavior” (Ajzen & Madden, 1986, p. 454) and are influenced strongly by

normative beliefs. According to the TRA, behavioral intention is considered to be

the only determinant of the desired behavior, and performing the behavior or not

6

performing it is entirely volitional (i.e., under the person’s control; Ajzen &

Madden, 1986). Theoretically, attitude and subjective norm determine the strength

of the behavioral intention, which in turn determines whether or not the behavior is

performed (Ajzen & Madden, 1986).

The TRA (Fishbein & Ajzen, 1975) has enjoyed support in health behavioral

studies (e.g., Airhihenbuwa & Obregon, 2000; Bresnahan, Guan, Wang, & Mou,

2008; McCaul et al., 1993; Randolph et al., 2009) and in dental health behavioral

research (e.g., Hoogstraten et al., 1985; McCaul et al., 1988; McCaul et al., 1993;

Tedesco et al., 1991). Hoogstraten et al. (1985) found attitudes toward going to the

dentist were positively related to intentions, and those intentions were a predictor of

seeking dental treatment.

In another study of the TRA (Fishbein & Ajzen, 1975) and dental health,

McCaul et al. (1988) studied brushing and flossing behaviors of young adults.

Results indicated attitudes, subjective norms, and intentions were positively related

to brushing and flossing behaviors (McCaul et al., 1988).

The TRA (Fishbein & Ajzen, 1975) has proven its utility of predicting

volitional behaviors. After criticisms (e.g., Ajzen & Madden, 1986; McCaul et al.,

1993) that some behaviors are out of one’s control and therefore not as accurately

predictable, Ajzen (1991; Ajzen & Madden, 1986) suggested an extension of the

TRA: the TPB.

7

The TPB (Ajzen, 1991), as presented in Figure 1, shares the two

motivational determinants of intention specified in the TRA: attitude and subjective

norm. To address the volitional control issue, a third determinant, perceived

behavioral control, was added to the TPB to help predict intention and behavior

when a person has limited control (Ajzen & Madden, 1986). Ajzen and Madden

(1986) defined perceived behavioral control as a “person’s belief as to how easy or

difficult the performance of the behavior is likely to be” (p. 457) by measuring the

available resources and opportunities at the time of intention to perform the actual

behavior. In other words, individuals are more apt to perform the behavior when

they feel the behavior is less difficult and have more opportunity and fewer

obstacles to overcome. Ajzen and Madden (1986) proposed perceived behavioral

control may influence behavior either indirectly through intention or directly as a

measure of actual control.

In an indirect test of the TPB (Ajzen, 1991), McCaul et al. (1988) tested

Bandura’s (1977) concept of self-efficacy (i.e., perceived ability, control) in the

TRA (Fishbein & Ajzen, 1975) framework. Results indicated self-efficacy was a

strong predictor of intention, and explained more of the variance in intention than

attitude and subjective norms. McCaul et al. concluded adding the concept of self-

efficacy to the TRA “would make a valuable contribution to the model” (p. 126).

8

Figure 1. The Theory of Planned Behavior as Hypothesized

McCaul et al. (1993) also directly tested the TPB (Ajzen, 1991) to “consider

whether self-efficacy and perceived behavioral control should be added to the

theory of reasoned action” (p. 232) to address volitional control issues. In a study of

health and dental behaviors, attitudes, subjective norms, and perceived behavioral

control were found to predict intention (McCaul et al., 1993). In addition, McCaul

et al. reported both perceived behavioral control and intention predicted brushing

and flossing behaviors. Due to this finding, McCaul et al. supported the predictive

value of perceived behavioral control in the TPB.

Other researchers have explored the utility of the TPB (Ajzen, 1991) to

predict flossing behaviors (e.g., Åstrøm, 2008; Lavin & Groarke, 2005; Schwarzer

et al., 2007; Sniehotta et al., 2007). Lavin and Groarke (2005) found attitudes,

subjective norms, and perceived behavioral control predicted intention, which was

Attitude

Subjective

Norms

Perceived

Behavioral

Control

Behavioral

Intention Behavior

9

found to be the only predictor of flossing behavior (Lavin & Groarke, 2005).

Sniehotta et al. (2007) researched flossing behaviors and also found attitudes,

subjective norms, and perceived behavioral control significantly predicted intention

to floss, while both intention and perceived behavioral control significantly

predicted flossing behavior.

To review, the TPB (Ajzen, 1991) proposes three determinants of intention

to perform a behavior: attitude, subjective norm, and perceived behavioral control.

Theoretically, these determinants influence the strength of the behavioral intention

to perform the desired behavior. Behavior is proposed to be influenced by either

intention or perceived behavioral control directly (Ajzen, 1991; Ajzen & Madden,

1986). The theory has proved its utility in promoting healthy behaviors such as

smoking cessation (e.g., Lee et al., 2006), exercising (e.g., Brenes et al., 1998;

Finlay et al., 2002), condom use (e.g., Sanchez-Garcia & Batista-Foguet, 2008) and

self-health examinations (e.g., Luszczynska & Schwarzer, 2003; McCaul et al.,

1993; McClenahan et al., 2007). In addition, dental behaviors such as flossing

have also been predicted by the TPB (e.g., Åstrøm, 2008; Lavin & Groarke, 2005;

Schwarzer et al., 2007; Sniehotta et al., 2007). To promote healthy dental

behaviors, message interventions should target one or more of the antecedents of

intention (i.e., attitude, subjective norm, or perceived behavioral control) which in

turn should elicit flossing behaviors (Ajzen & Fishbein, 2005).

10

Message Interventions

Ajzen and Fishbein (2005) argue that to effectively change intentions and

behaviors, messages should be directed at one or more of the antecedents of

intention (i.e., attitude, subjective norm, or perceived behavior control).

Specifically, “interventions target the behavioral, normative and control beliefs in an

effort to produce positive intentions” (Fishbein & Ajzen, 2005, p. 3). Unless these

underlying beliefs are affected, intention and behavior are not likely to change

(Ajzen & Manstead, 2007). For example, Hoogstraten et al. (1985) applied message

interventions within the TRA (Fishbein & Ajzen, 1975) framework to change

beliefs about seeking dental treatment. Messages were formatted to include positive

and negative consequences of seeking dental treatment. After exposure to

persuasive appeals (i.e., the messages) to sign up for dental treatment, results

indicated a strong relationship between behavioral beliefs, attitude, and intention

(Hoogstraten et al., 1985). The message targeting behavioral beliefs was the most

effective in eliciting the intention and behavior of seeking dental treatment

(Hoogstraten et al., 1985).

In another study involving message interventions, McCaul et al. (1993)

researched the relationship between dental behaviors and the TPB (Ajzen, 1991).

Experimental groups were exposed to a treatment program involving educational

messages, skills training, self monitoring, and goal-setting to encourage flossing

behavior. Although McCaul et al. did not form the message interventions from

11

specific beliefs (i.e., behavioral, normative, control), results indicated exposure to

the treatment program did increase flossing behavior.

The TPB (Ajzen, 1991) has proven its utility in predicting flossing behaviors

(e.g., Åstrøm, 2008; Lavin & Groarke, 2005; McCaul et al., 1993; Schwarzer et al.,

2007; Sniehotta et al., 2007); therefore it would be logical to extend this body of

research by investigating the role of message interventions on the strength of

relationships in the model.

To assist in formulating messages to address flossing behaviors, the TPB

(Fishbein & Ajzen, 1975) will be utilized to identify the motivational factors behind

these behaviors. Therefore, the following hypotheses and research questions are

provided.

H1: Attitude, subjective norm, and perceived behavioral control

will predict intention to floss.

H2: Perceived behavioral control and behavioral intent will predict desired

flossing behavior.

RQ1: Do message interventions increase flossing behavior?

RQ2: Do message interventions (i.e., attitude, subjective norm, or

perceived behavioral control-related) strengthen the

associations among the variables in the TPB?

CHAPTER 2

METHOD

Participants

A total of 125 (65 male, 81 female) undergraduate students from a large

Midwestern university participated in this study. Students enrolled in a large

communication course were recruited if they did not floss their teeth. Research

credit was offered for those students who participated in the study. Those students

who actively floss their teeth were also offered research credit by recruiting a non-

flossing subject to participate on their behalf. Students who did not fit the criteria

were offered alternative research opportunities for credit.

The participants’ ages ranged from 19 to 44, M = 21.54, SD = 2.44. The

ethnicity of participants included Caucasian (71.9%), African-American (11.6%),

Hispanic (6.2%), Middle-Eastern (0.7%) and Other (4.1%).

Procedure

This study involved two waves of data collection. A total of 146 subjects

completed the first wave of the study through an online survey. Participants were

randomly assigned to one of three message interventions (e.g., attitude-related,

subjective norm-related, or perceived behavioral control-related) or a control

13

message (see Appendices A-D). All messages reflected positive flossing behaviors.

Participants then answered survey questions regarding attitudes, subjective norms,

and perceived behavioral control and behavioral intentions. Manipulation check

items were included to verify the retention of a particular message. Participants

provided a valid e-mail address during the first wave of data collection. After two

weeks, 125 participants completed the second wave of the study. During the online

survey, participants were asked to answer survey questions regarding current

flossing behaviors since the first-wave survey (two weeks prior). Only data from

participants who provided a valid e-mail address for both waves of collection were

used in this study.

Message Intervention Design

Following Fishbein and Ajzen’s (2005) recommendations, three messages

were designed to target the behavior-specific beliefs of attitudes, subjective norms,

and perceived behavioral control. Formative research to identify accessible beliefs

was not conducted prior to formulation of the messages due to limitations of the

participant sample.

The attitude-related message emphasized the importance and benefits of

flossing and the consequences of poor oral hygiene (see Appendix A). The

subjective norm-related message stressed the value of flossing and how it is

important to your dentist, your family and friends, and you (see Appendix B). The

14

perceived behavioral control message provided instruction and moral support for the

proper technique of how to floss one’s teeth (see Appendix C).

All three messages were of similar length, layout, and format. A fourth,

shortened, control message provided general information regarding intentions to

floss (see Appendix D).

Survey Measures

Background questions of age, sex, ethnicity, and measures of prior flossing

behavior were measured in the first wave of data collection. Also measured were

the participants’ attitudes, subjective norms, perceived behavioral control, and

intentions to floss. Actual flossing behaviors after the two-week period were

measured in the second wave of data collection.

First-Wave Survey

The first-wave contained measures of attitude, subjective norm, perceived

behavioral control, and intention as suggested by Ajzen (2002). Scales were

constructed using Likert-type and semantic differential items. All items were

constructed using a 5-point response scale. Items were scored so that higher values

indicated greater endorsement of the variable.

Components of the theory of planned behavior (e.g., attitude, subjective

norm, perceived behavioral control, and intention; Ajzen, 1991) were measured in

15

the first wave after participants were exposed to the message interventions. Attitude

towards flossing behavior was measured by 14 items (i.e., both Likert-type and

semantic differential items). An example of a Likert item is “It would be good for

me to floss my teeth once a day for the next two weeks” (strongly disagree/strongly

agree). An example of a semantic differential item is “For me, to floss my teeth

once a day in the next two weeks is…” (harmful/extremely beneficial). The attitude

toward flossing scale was reliable, α = .93, M = 3.89, SD = 0.61.

Subjective norm was measured by four items using Likert-type items.

Examples include “Most people who are important to me floss once a day” and

“Most of my peers floss once a day.” The subjective norm scale was reliable, α =

.72, M = 2.75, SD = 0.71.

Perceived behavioral control was measured by eight items using Likert-type

items and semantic differential items. An example of a Likert item is “If I wanted

to, I could floss once a day in the forthcoming month” (strongly disagree/strongly

agree). An example of a semantic differential item is “How much control do you

believe you have over flossing once a day in the next two weeks?” (no control-

complete control). The perceived behavioral control scale was reliable, α = .83, M =

4.42, SD = 0.52.

Behavioral intention was measured by seven items using Likert-type items

and semantic differential items. An example of a Likert item is “I plan to floss my

teeth once a day in the next two weeks” (strongly disagree/strongly agree). An

16

example of a semantic differential item is “My intention to floss my teeth once a

day in the next two weeks is…” (very weak/very strong). The behavioral intention

scale was reliable, α = .96, M = 3.10, SD = 1.07.

Participants were exposed to one of four message conditions: an attitude-

related message, subjective norm-related message, perceived behavioral control-

related message, and a control message (see Appendices A-D). In all conditions,

participants were asked to complete the first wave of the survey after they received

the appropriate message about flossing. Manipulation checks were used to assess

message recall. Manipulation checks for message interventions were measured by

two items each. An example of a manipulation check for the attitude-related

message is “80% of Americans have some form of gum disease.” The attitude-

related manipulation check was reliable, α = .79, M = 2.31, SD = 1.44. An example

of a manipulation check for the subjective norm-related message is “No one wants

the embarrassment of having bad breath in front of their friends.” The subjective

norm-related manipulation check was not very reliable, α = .46, M = 3.32, SD =

1.24. Because there were four sets of manipulation check items, the measure was

retained. An example of a manipulation check for the perceived behavioral control-

related message is “Keep floss (string, picks, etc.) in three to four different areas so

it is readily available for use.” The perceived behavioral control-related

manipulation check was reliable, α = .77, M = 2.59, SD = 1.44. An example of a

manipulation check for behavioral intentions-related message is “Please take a

17

moment to think about what time of day you could floss.” The behavioral

intentions-related manipulation check was reliable, α = .72, M = 2.91, SD = 1.33.

Second-Wave Survey

The purpose of the second wave of the study was to measure flossing

behaviors from a two-week period after the first wave of data collection. Flossing

behavior was measured by six Likert-type items and two open-ended items. An

example of a Likert item is “I have flossed my teeth everyday in the last two weeks”

(strongly disagree/strongly agree). The Likert-type behavioral scale was reliable, α

= .97, M = 1.72, SD = 1.20. An example of an open-ended scale is “How many

days in the last two weeks have you flossed your teeth?” The open-ended

behavioral scale was reliable, α = .87, M = 3.77, SD = 3.89.

CHAPTER 3

RESULTS

Manipulation Check Analysis

The goal of the manipulation checks was to verify how much information

participants recalled from exposure to the intervention message. One-way

ANOVAs with the message type (e.g., attitude-related, subjective norm-related,

perceived behavioral control-related, or control message) as the independent

variable and the manipulation check measures as the dependent variable were

conducted to verify the recall validity of the information in the messages.

The manipulation check for the attitude-related message was successful,

F(3,139) = 56.73, p < .001; partial = .55. The mean for recollection of

information that was in the attitude-related message was much higher (M = 4.07, SD

= 1.03) for participants who read the attitude-related message than for any of the

other groups (subjective norm, M = 1.55, SD = 0.86; perceived behavioral control,

M = 1.71, SD = 0.96; control, M = 1.91, SD = 1.18).

The manipulation check for the subjective norm-related message was also

successful, F(3,139) = 29.55, p < .001; partial = .39. The mean for recollection of

information that was in the subjective norm-related message was much higher (M =

4.35, SD = 0.97) for participants who read the subjective norm-related message than

19

for any of the other groups (attitude, M = 2.91, SD = 1.00; perceived behavioral

control, M = 2.91, SD = 0.70; control, M = 2.25, SD = 1.41).

The manipulation check for the perceived behavioral control-related

message was successful, F(3,139) = 45.61, p < .001; partial = .50. The mean for

recollection of information that was in the perceived behavioral control-related

message was much higher (M = 4.26, SD = 0.89) for participants who read the

perceived behavioral control-related message than for any of the other groups

perceived behavioral control-related message (attitude, M = 1.91, SD = 1.03;

subjective norm, M = 1.96, SD = 1.05; control, M = 2.22,

SD = 1.25).

The manipulation check for the control message was successful, F(3,136) =

28.65, p < .001; partial = .39. The control message mean and standard deviation

were reported as M = 4.69, SD = 0.62. The other message conditions related to

lower recall of the information in the control message (i.e., attitude, M = 2.11, SD =

0.99; subjective norm, M = 2.55, SD = 1.11; perceived behavioral control, M = 3.34,

SD = 1.17).

Generally speaking, the manipulation checks demonstrated that participants

recalled information correctly from the message they read.

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Hypotheses 1 and 2

H1 and H2 investigated the relationship between attitudes, subjective norms,

perceived behavioral control, and intentions. Specifically, H1 stated attitude,

subjective norm, and perceived behavioral control will predict intention to floss. H2

stated perceived behavioral control and behavioral intent will predict desired

flossing behavior. These predictions are described in Figure 1. Specifically,

attitude toward flossing should be a statistically significant, positive predictor of

intentions to floss. Subjective norms should be a statistically significant, positive

predictor of intentions to floss. Perceived behavioral control should be a

statistically significant, positive predictor of intentions to floss. Perceived

behavioral control and intentions to floss should predict flossing behavior over a

two-week period of time.

The hypothesized structural equation model was tested using the AMOS

16.0 computer program to perform maximum likelihood estimation. At the

recommendation of Byrne (2010), several indicators of the goodness of fit of the

model were assessed. Overall indicators of fit, baseline comparison indicators and

the RMSEA were evaluated. First, a fit model had to have a non-significant (i.e.,

p < .05) Chi-square. Second, the model needed a CFI (i.e., Comparative Fit Index)

of .95 or higher. Third, the model had to have a TLI (i.e., Tucker-Lewis Index) of

.95 or higher. Fourth, the model needed a RMSEA (i.e., Root Mean Square Error of

21

Approximation) of .05 or lower. After initial fit, post hoc modification was used to

remove direct paths that were not statistically significant.

The hypothesized model did not fit the data, χ2 (5) = 62.43, p < .001, CFI = .70,

TLI = .39, RMSEA = .28. Figure 2 presents the path statistics for the initial model.

It was clear from evaluating the initial model that perceived behavioral control was

not a strong contributor to the model. The revised model shows that clearly. The

model presented in Figure 3 is an excellent fit to the data, χ2 (3) = 4.44, p = .22,

CFI = .99, TLI = .98, RMSEA = .05. All standardized path coefficients that

remained in the model were statistically significant p < .05. No other model that

was tested provided a better fit.

Figure 2. Initial Model Fit

Attitude

toward

Behavior

Subjective

Norms

Perceived

Behavioral

Control

Behavioral

Intention Behavior

e1 e1 e2 .64

.27

-.07

.02

.49

22

Figure 3. Revised Model Fit

Research Question 1

RQ1 asked if message interventions would increase flossing behavior. A

one-way ANOVA with the message type (i.e., attitude-related, subjective norm-

related, perceived behavioral control-related, or control message) as the independent

variable and reported behavior after two weeks as the dependent variable was

conducted to determine if exposure to a specific message increased flossing

behavior. Message type did not affect “days flossed,” F(3, 117) = 0.80, p > .05. In

the “days flossed” measure, groups were similar in their flossing behaviors: attitude-

related message, M = 3.08, SD = 3.51; subjective norm-related message, M = 4.11,

SD = 3.69; perceived behavioral control-related message, M = 4.33, SD = 4.53;

Attitude

toward

Behavior

Subjective

Norms

Behavioral

Intention Behavior

e1 e1 e2

.61

.28

.49

23

control message, M = 3.17, SD = 3.74. In the behavioral measure, there were no

differences among groups, F(3, 120) = 0.08, p > .05. In the behavioral measure, the

groups were similar in their flossing behaviors; attitude-related message, M = 1.66,

SD = 1.09; subjective norm-related message, M = 1.72, SD = 1.21; perceived

behavioral control-related message, M = 1.73, SD = 1.22; control message, M =

1.85, SD = 1.47.

In addition, a t-test was also performed to address RQ1. All three messages

(e.g., attitude-related, subjective norm-related, perceived behavioral control-related)

were compared to the control message. In the “days flossed” behavioral measure,

there was no difference between message and control, t(119) = -0.69, p > .05. The

“days flossed” for participants with a message (M = 3.86, SD = 3.92) were similar to

the “days flossed” for those in the control message condition (M = 3.17, SD = 3.74).

In the behavioral measure, there also were no differences between groups t(122) =

0.15, p > .05. Participants who received a content message (M = 1.70, SD = 1.17)

were similar to those in the control message condition (M = 1.85, SD = 1.47). These

results indicate message interventions did not increase flossing behavior.

For RQ1, the ANOVA and follow-up t-tests indicated that the messages did

not directly increase flossing behaviors.

24

Research Question 2

RQ2 asked if message interventions would strengthen the associations

among the variables in the TPB (Ajzen, 1991). Correlations were calculated to

assess the strength of association of the components of the TPB across each

message type (see Table 1). The correlations were then compared using a Fisher’s z

score to assess the probability that the correlations differ from each other.

Table 1. Correlations Between Theory Components and Message Types

Theory

component

Attitude-

related

Message 1

Subjective

norm-related

Message 2

Perceived

behavioral

control-

related

Message 3

Control

Message 4

AB-BI r = .63, N = 33 r = .64, N = 48 r = .81, N = 37 r = .51, N = 16

SN-BI r = .42, N = 37 r = .40, N = 47 r = .31, N = 38 r = .38, N = 17

PBC-BI r = .30, N = 35 r = .29, N = 49 r = .40, N = 38 r = .33, N = 17

BI- B r = .64, N = 31 r = .49, N = 39 r = .62, N = 33 r = .37, N = 17

PBC-B r = .14, N = 31 r = .27, N = 40 r = .27, N = 33 r = -.10, N = 15

25

Exact p values for the attitude-behavioral intent component are reported in

Table 2. For the attitude-behavioral intent component, the differences between

correlations of the attitude-related message and the subjective norm-related

message, (z = -0.07, p > .05), perceived behavioral control-related message (z = -

1.54, p > .05), and the control message (z = 0.54, p > .05) were not statistically

significant. The difference between the correlation of the subjective norm-related

message and the perceived behavioral control-related message was statistically

significant (z = -1.63, p = .05). The difference between the subjective norm-related

message and the control message was not statistically significant (z = 0.62, p > .05).

Lastly, the difference between the perceived behavioral control-related message and

the control message was statistically significant (z = -1.73, p < .05). Therefore, the

attitude-behavioral intent component strength of relationship was stronger for the

perceived behavioral control message group than for the subjective norm-related or

control message groups.

26

Table 2. P Values Between Message Types Across AB-BI Theory Component

Theory Component

AB-BI

Subjective norm-

related

Message 2

Perceived behavioral

control-related

Message 3

Control

Message 4

Attitude-related

Message 1

p = .47

p = .06

p = .29

Subjective norm-

related

Message 2

p = .05

p = .27

Perceived

behavioral

control-related

Message 3

p = .04

Exact p values for the subjective norm-behavioral intent component are

reported in Table 3. For the subjective norm-behavioral intent component, the

differences between correlations of the attitude-related message and the subjective

norm-related message (z = 0.11, p > .05), perceived behavioral control-related

message (z = 0.53, p > .05), and the control message (z = 0.15, p > .05) were not

statistically significant. The differences between the correlations of the subjective

norm-related message and the perceived behavioral control-related message (z =

0.46, p > .05) and the control message (z = 0.08, p > .05) were not statistically

significant. Lastly, the difference between the perceived behavioral control-related

message and the control message was not statistically significant (z = -0.25, p > .05).

27

Table 3. P Values Between Message Types Across SN-BI Theory Component

Theory Component

SN-BI

Subjective

norm-related

Message 2

Perceived

behavioral

control-related

Message 3

Control

Message 4

Attitude-related

Message 1

p = .46

p = .30

p = .44

Subjective norm-related

Message 2

p = .32

p = .47

Perceived behavioral

control-related

Message 3

p = .40

Exact p values for the perceived behavioral control-behavioral intent

component are reported in Table 4. For the perceived behavioral control-behavioral

intent component, the differences between correlations of the attitude-related

message and the subjective norm-related message (z = 0.05, p > .05), perceived

behavioral control-related message (z = -0.47, p > .05), and the control message (z =

-0.10, p > .05) were not statistically significant. The differences between the

correlations of the subjective norm-related message and the perceived behavioral

control-related message (z = -0.56, p > .05) and the control message (z = 0.14, p >

.05) were not statistically significant. Lastly, the difference between the perceived

behavioral control-related message and the control message was not statistically

significant (z = 0.26, p > .05).

28

Table 4 P Values Between Message Types Across PBC-BI Theory Component

Theory

Component

PBC-BI

Subjective norm-

related Message 2

Perceived

behavioral

control-related

Message 3

Control

Message 4

Attitude-related

Message 1

p = .48

p = .32

p = .46

Subjective norm-

related

Message 2

p = .29

p = .44

Perceived

behavioral

control-related

Message 3

p = .40

Exact p values for the behavioral intent-behavior component are reported in

Table 5. For the behavioral intent-behavior component, the differences between

correlations of the attitude-related message and the subjective norm-related message

(z = 0.88, p > .05), perceived behavioral control-related message (z = 0.13, p > .05),

and the control message (z = 1.13, p > .05) were not statistically significant. The

differences between the correlations of the subjective norm-related message and the

perceived behavioral control-related message (z = -0.77, p > .05) and the control

message (z = 0.47, p > .05) were not statistically significant. Lastly, the difference

between the perceived behavioral control-related message and the control message

was not statistically significant (z = 0.99, p > .05).

29

Table 5. P Values Between Message Types Across BI-B Theory Component

Theory Component

BI-B

Subjective norm-

related Message 2

Perceived

behavioral

control-related

Message 3

Control

Message 4

Attitude-related

Message 1

p = .19

p = .45

p = .13

Subjective norm-related

Message 2

p = .22

p = .32

Perceived behavioral

control-related

Message 3

p = .16

Exact p values for the behavioral intent-behavior component are reported in

Table 6. For the perceived behavioral control-behavior component, the differences

between correlations of the attitude-related message and the subjective norm-related

message (z = -0.54, p > .05), perceived behavioral control-related message (z = -

0.52, p > .05), and the control message (z = 0.70, p > .05) were not statistically

significant. The differences between the correlations of the subjective norm-related

message and the perceived behavioral control-related message (z = 0.50, p > .05)

and the control message (z = 1.14, p > .05) were not statistically significant. Lastly,

the difference between the perceived behavioral control-related message and the

control message was not statistically significant (z = 1.10, p > .05).

30

Table 6. P Values Between Message Types Across PBC-B Theory Component

Theory Component

PBC-B

Subjective norm-

related

Message 2

Perceived

behavioral

control-related

Message 3

Control

Message 4

Attitude-related

Message 1

p = .29

p = .30

p = .24

Subjective norm-

related

Message 2

p = .50

p = .13

Perceived behavioral

control-related

Message 3

p = .14

Overall, the results indicated that the perceived behavioral control message

group showed the strongest relationship of any message group in the attitude-

behavioral intent component of the TPB (Ajzen, 1991). For RQ2, the messages did

not strengthen the associations in the model.

CHAPTER 4

DISCUSSION

Practical Implications of Messages

RQ1 asked if message interventions would increase flossing behavior.

Ideally, exposure to a belief message should have increased flossing behavior. The

results indicated that exposure to messages did not influence flossing behavior. To

check for a general effect of messages on behavior, message condition means were

grouped and compared to the control message mean. No statistically significant

differences were found. Although the manipulation checks indicated that the

participants retained what they read in each respective message, the messages

themselves were not effective at changing flossing behavior. It is possible that the

underlying behavioral, normative, and control beliefs were not sufficiently activated

in the messages to encourage flossing behavior.

RQ2 asked if message interventions (i.e., attitude-related, subjective norm-

related, or perceived behavioral control-related) would strengthen the associations

among the variables in the TPB (Ajzen, 1991). Surprisingly, only two statistically

significant differences in effectiveness were found across message conditions. In

the attitude-behavioral component of the model, the perceived behavioral control-

32

related message group had a stronger association than the subjective norm-related

message group and the control group. Even though manipulation checks were

performed on the messages (i.e., attitude-related, subjective norm-related, perceived

behavioral control-related, and control), only the perceived behavioral control-

related message was found to strengthen the attitude-intention association.

These results imply that additional research is needed to explore why the

perceived behavioral control-related message affected attitude toward intention

while the other messages (i.e., attitude- and subjective norm-related) did not.

Theoretical Implications

Results indicated partial support for H1. Following the TPB model (Ajzen,

1991), H1 stated attitude, subjective norm, and perceived behavioral control would

predict intention to floss. After SEM analysis, the revised fit of the model revealed

attitude toward flossing and subjective norms predicted intention to floss, and

behavioral intent was found to predict flossing behaviors. Perceived behavioral

control was not found to significantly predict intention to floss.

Results also indicated partial support for H2. Following the TPB model

(Ajzen, 1991), H2 stated perceived behavioral control and behavioral intent would

predict desired flossing behavior. The results indicated intention, but not perceived

behavioral control, predicted flossing behavior.

33

This study showed an ability to replicate previous research (e.g.,

Hoogstraten et al., 1985; McCaul et al., 1988; McCaul et al., 1993; Tedesco et al.,

1991) on flossing behaviors with respect to the TRA (Fishbein & Ajzen, 1975). The

current study supported the TRA in that attitudes and subjective norms predicted

behavioral intentions, and behavioral intentions predicted flossing behavior.

Interestingly, the present study does not support previous research that has

found perceived behavioral control to be a statistically significant predictor of

intention and behavior (e.g., McCaul et al., 1988; McCaul et al., 1993). In McCaul

et al.’s (1988) study of the TRA (Fishbein & Ajzen, 1975), self-efficacy was found

to predict intention to floss. A possible reason for this finding is participants in the

study were given assessments of their dental health and hygiene skills by dental

professionals and experimenters before measurement of dental behaviors. This

personalized assessment may have influenced participants’ feelings of self-efficacy

in the form of encouragement from the assessor more so than reading similar

information in written form.

In another study of the TPB (Ajzen, 1991), McCaul et al. (1993) found

perceived behavioral control to be a stronger predictor of flossing intention than

self-efficacy. In the McCaul et al. study, participants were invited to attend a dental

health treatment program that involved teaching self-care skills to help prevent gum

disease. Again, the exposure to a treatment program may have

34

influenced perceived behavioral control over flossing intentions more than exposure

to written message of the same nature.

The current study has replicated previous research of the TRA (Fishbein &

Ajzen, 1975), but not the TPB (Ajzen, 1991). Perceived behavioral control was not

found to predict intent or behavior to floss as it was in previous research (e.g.,

McCaul et al., 1988; McCaul et al., 1993). Perhaps the method of the intervention

(e.g., face-to-face) in previous research was partially responsible for perceived

behavioral control to appear as a predictor in the revised TPB model.

Limitations and Directions for Future Research

Small sample sizes per treatment condition were a limitation in this study.

Although exposure to a specific message (i.e., perceived behavioral control-related

messages in the attitude-behavioral intent component) was found to strengthen the

association between TPB variables (Ajzen, 1991), a better test of message effects

could have been performed had SEM analysis on each message group been possible.

Also, it is possible the message interventions did not affect flossing

behaviors as expected due to the message format. In this study, the messages were

constructed according to theoretical components of the TPB (Ajzen, 1991) and

manipulation checks found the messages to be retained by participants. It is

possible that the underlying behavioral, normative, and control beliefs may not have

been affected enough to increase flossing behaviors. In addition, some college

35

students may not have experienced serious dental problems to be motivated by the

messages. Future research should include the use of focus groups to determine if

the beliefs of the participants will be affected by each component-specific message

intervention.

Another formatting issue may be due to the convenience sample. Because of

the college sample, written messages and a survey were used as a matter of

expediency. Future research should look to formulate messages for a college

sample in a way that is more persuasive in wording and format (e.g., face-to-face) to

elicit desired flossing behaviors in addition to the written word.

Sample age may be the reason why the perceived behavioral control

component did not stay in the revised TPB model. It is possible that college-aged

subjects may have the physical agility to maneuver floss around their teeth, as

opposed to older subjects who may encounter difficulties while attempting to do so.

Therefore, college-aged subjects may have less control and efficacy issues than

older subjects.

Conclusion

This study investigated the utility of the TPB (Ajzen, 1991) and message

interventions as predictors of flossing intention and behavior. In this thesis, one

goal was to explore the naturally occurring relationships between attitudes,

subjective norms, perceived behavioral control, intention and flossing behaviors.

36

Contrary to expectations, this study did not replicate the TPB, as perceived

behavioral control was not found to predict intention or flossing behaviors.

Consistent with the TRA (Fishbein & Ajzen, 1975), attitudes and subjective norms

were found to predict intention, and intention was found to predict flossing

behaviors. These results are consistent with TRA research of flossing behaviors

(e.g., Hoogstraten et al., 1985; McCaul et al., 1988; McCaul et al., 1993; Tedesco et

al., 1991).

Another goal of this study was to examine the effects of message

interventions on flossing behavior and the TPB (Ajzen, 1991) model components.

Although message interventions have been found to influence behavior in other

studies of the TPB (e.g., Beale & Manstead, 2006; Fishbein et al., 2001; Maddock et

al., 2008) and the TRA (e.g., Hoogstraten et al., 1985), the current study was unable

to replicate previous results. It is possible that the underlying behavioral,

normative, and control beliefs necessary to affect attitude, subjective norm, and

perceived behavioral control were not sufficiently activated in the message

interventions. Future research should include the use of focus groups to determine

which belief messages would be the most effective at changing behavior.

Also, message interventions were not found to strengthen the associations

between TPB (Ajzen, 1991) components has expected. Even though manipulation

checks were performed on the messages (i.e., attitude-related, subjective norm-

related, perceived behavioral control-related, and control), only the perceived

37

behavioral control-related message was found to strengthen the attitude-intention

association. These results imply that additional research is needed to explore the

manner in which message interventions would significantly affect the strength of

associations between TPB components.

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doi:10.1007/BF00845111

APPENDICES

APPENDIX A

MESSAGE ONE (ATTITUDE-RELATED)

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Message 1 (Attitude-related)

Unfortunately only 49% of Americans floss every day (AGD, 2008): a

statistic which has caused 80% of Americans to have gum disease (NIDCR, 2010).

The leading cause of tooth decay and gum disease is the failure to remove plaque;

therefore without proper brushing and flossing, bad breath, decay, gum disease, and

tooth loss can occur. According the Academy of General Dentistry (2008), flossing

is the most effective way of removing plaque from between the teeth. Brushing

alone is not enough to stop tooth decay and tooth loss. Flossing removes plaque

from in-between the teeth where a toothbrush cannot reach, and stimulates healthy

gum tissue around each tooth to stop potential bone loss. Good oral hygiene habits

including brushing and flossing your teeth daily and visiting the dentist every six to

twelve months are proven preventative measures that can save time, money, and

your teeth.

APPENDIX B

MESSAGE TWO (SUBJECTIVE NORM-RELATED)

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Message 2 (Subjective norm-related)

Dentists and dental hygienists know the value of flossing. At your cleaning

appointment, the dentist or hygienist will instruct you on how to floss your teeth,

and then floss your teeth for you. It is their goal to have you floss at home between

visits to help eliminate plaque which in turn eliminates the need for future dental

work. Dentists would rather see you every six months with your teeth and gums in

a healthy condition than with plaque and decay throughout your mouth.

Also, oral hygiene behaviors such as flossing once a day will lessen the bacteria

count in your mouth that leads to bad breath. Brushing alone does not reach the

plaque between the teeth that causes these bacteria. No one wants the

embarrassment of having bad breath in front of their friends.

Gum disease can not only lead to bad breath, but to infection as well.

Periodontal disease is an infection in the gums and if left untreated can spread to the

rest of the body over time. No one in your family wants you to become sick,

especially from not flossing.

APPENDIX C

MESSAGE THREE (PERCEIVED BEHAVIORAL CONTROL-RELATED)

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Message 3 (Perceived behavioral control-related)

Dental awareness has come a long way in the last thirty years. It is not

commonplace in the 21st century to think there is nothing you can do to stop your

teeth from becoming decayed and diseased. Good oral hygiene behaviors such as

brushing, flossing, limiting your sugar intake, and visiting the dentist every six

months all directly contribute to a healthy smile.

The ability to perform these behaviors lies with you. Set aside the same time

every day to brush and floss your teeth. Keep floss (string, picks, etc.) in three to

four different areas so it is readily available for use. If using string floss, wrap an

18- inch piece around your middle fingers and use your pointer fingers to guide the

floss gently between each tooth to remove debris. As you move from tooth to tooth,

unwind clean sections of floss as needed. It may take a few tries to get the hang of

it, and soon it will take only a few minutes to floss all your teeth.

Your dental health is in your control. Setting a time to floss daily and

mastering the proper techniques are two ways that will help you start flossing your

teeth on a daily basis.

APPENDIX D

MESSAGE FOUR (CONTROL MESSAGE)

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Message 4 (Control Message)

Please take a moment to think about what time of day you could floss. What

would you need to floss? How can you make it easier on yourself to floss? Please

think for a moment about the benefits of flossing.