PREDICTORS OF PREVENTIVE DENTAL BEHAVIOR AMONG CHINESE COLLEGE

STUDENTS BASED ON THE HEALTH BELIEF MODEL

Thesis

Submitted to

The College of Arts and Sciences of the

UNIVERSITY OF DAYTON

In Partial Fulfillment of the Requirements for

The Degree of

Master of Arts in Communication

By

Peijun Hou

Dayton, Ohio

December 2018

PREDICTORS OF PREVENTIVE DENTAL BEHAVIOR AMONG CHINESE COLLEGE

STUDENTS BASED ON THE HEALTH BELIEF MODEL

Name: Hou, Peijun

APPROVED BY:

Angeline L. Sangalang, Ph.D. Faculty Advisor and Committee Chair Assistant Professor of Communication

James D. Robinson, Ph.D. Committee Member Professor of Communication

Teresa Thompson, Ph.D. Committee Member Professor of Communication

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© Copyright by

Peijun Hou

All rights reserved

2018

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ABSTRACT

PREDICTORS OF PREVENTIVE DENTAL BEHAVIOR AMONG CHINESE COLLEGE

STUDENTS BASED ON THE HEALTH BELIEF MODEL

Name: Hou, Peijun University of Dayton

Advisor: Dr. Angeline L. Sangalang

This study examined the potential for concepts within the Health Belief Model to predict

Chinese college students’ daily brushing, daily flossing, and annual dental check-up behavior.

Additionally, dental-related information seeking and scanning were explored. The survey was completed by 150 Chinese college students and found that some components of HBM significantly predict brushing behavior, flossing behavior, and dental check-up behavior. Self- efficacy was the best predictor of brushing and dental check-up behavior, while barriers and dental-related knowledge were the best predictors of flossing behavior. Participants prefer to seeking from social media and with his or her dentist and scan information from social media and mass media. Information seeking and scanning only significantly predicted flossing behavior.

Knowledge, seeking and scanning information from a dentist were the best predictor of dental check-up behavior. Future studies could examine more about self-efficacy and dental health behavior in the Chinese cultural context.

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ACKNOWLEDGMENTS

I spend a whole year to finish this thesis, in the process, I have encountered countless difficulties and obstacles. There are so many people I want to thank. I want to thank my advisor,

Dr. Angeline L. Sangalang, for directing this thesis, giving me a lot of feedbacks to help me improve.

I would also like to express my appreciation to everyone who has helping me with this work. This includes Teresa Thompson, who offered guidance and help with patience. James D.

Robinson, who gave advice concerning the self-efficacy. Irina Enevska, who always support me and encourage me. Joanna Abdallah, who helped me a lot to graduate. Xin Zhang, who made my life no lonely anymore. Last but not the least, I would like to thank my parents and my boyfriend, even though we are not in same country, they always support me, help me to overcome many difficulties. I cannot finish my thesis without them. Thank you.

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TABLE OF CONTENTS

ABSTRACT……………………………………………………………………………….………iv

ACKNOWLEDGMENTS…………………………………………………………...………..…...v

LIST OF TABLES.…..…………………………………………..…………………………...…..vii

CHAPTER 1 INTRODUCTION……………………………………………………...... ………1

CHAPTER 2 LITERATURE REVIEW………………………………………………………...…3

CHAPTER 3 METHOD……………………………………………………………………....….13

CHAPTER 4 RESULTS…………………………………………………...…………………...... 20

CHAPTER 5 DISCUSSION………………………………………………….…….…………….29

REFERENCES. ……………………………………………………………………………….…35

APPENDIX A Dental Health Belief Questionnaire…………………………………………...…42

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LIST OF TABLES

Table 4.1 Descriptive statistics of information seeking………...……………….………………..22

Table 4.2 Information seeking from social media………………...……………….……………..23

Table 4.3 Information seeking from mass media………….……...……………….….…………..23

Table 4.4 Information seeking from school……..………………...……………….…….……….23

Table 4.5 Information seeking from dentist……. ………………...……………….….………….24

Table 4.6 Descriptive statistics of information scanning……...……………….……………..…..24

Table 4.7 Information scanning from social media………………...……………….……...…….25

Table 4.8 Information scanning from mass media………………...……………….……....…...... 25

Table 4.9 Information scanning from school………………...……………….……...... …….25

Table 4.10 Information scanning from dentist………………...………….……..……….....….....26

Table 4.11 Dental related knowledge………………………………………………………...... 28

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CHAPTER 1

INTRODUCTION

Dental health is a really important component of physical health. Dental health is not

only related to teeth and gums, but also related to other diseases (Li, Kolltveit, Tronstad, & Olsen,

2000). Li and colleagues (2000) noted that periodontal diseases might have connection with

cardiovascular disease (Kinane, 1998), bacterial pneumonia (Scannapieco & Mylotte,

1996),diabetes (Grossi & Genco, 1998), and low birth weight (Dasanayake, 1998) may be caused by poor dental health. As a result, promoting dental health behaviors such as brushing and flossing are crucial.

Dental health is a bigger challenge for developing countries compared to developed countries due to reasons like economic, social and policy (Watt, 2005). For example, researchers

Chinese dental students reported higher rate of bleeding from gingiva and higher rate of belief

that wearing dentures in old age was inevitable than British students (Komabayashi, Kwan, Hu,

Kajiwara, Sasahara, & Kawamura, 2005). Additionally, more than half of Chinese participants

seek dental care only when symptoms arise, but only 13% of British participants reported so

(Komabayashi et al., 2005). There little research exploring how to improve people's awareness of dental health behavior in China and only a few researches target at Chinese immigrants in developed countries (e.g., Kwan & Holmes, 1999). More research focused on Chinese people is needed. According to the Fourth National Oral Health Epidemiology Survey, Chinese people face very serious dental problems right now (Gong, 2017). The prevalence rate of dental cavities among 12-years-old children was 34.5%, compared to ten years ago, the rate increased by 7.8%

(Gong, 2017). For 35-44 years old Chinese residents, bleeding rate was 87.4%, compared to ten

1 years ago, the rate increased by 10.1% (Gong, 2017). Despite these disturbing increases in poor dental health, there is a lack of research and health promotion activities target at Chinese people.

Therefore, more research is needed to identify how to promote Chinese dental health behaviors.

This investigation focused on dental health promotion among Chinese college students and employed the health belief model (HBM) (Rosenstock, 1990) to identify which component will be effective in persuading Chinese college students to engage in dental health behaviors. The present study also investigated cultural influences such as power distance, individualism versus collectivism and uncertainty avoidance. The HBM is often tested in individualistic cultures such as the United States, but China is a collectivist culture, therefore, this investigation also explored whether one of the HBM components, self-efficacy (Oettingen, 1995), might function differently among Chinese people.

As the availability of health information grows rapidly, especially through the Internet, it is necessary for researchers to investigate the routes of dental health related information acquisition through communication channels. For example, people might collect health information through both information seeking and scanning behavior (Niederdeppe et al., 2007).

Several previous studies (e.g., Hornik et al., 2013; Niederdeppe et al., 2007) have identified that information seeking and scanning are related to health prevention behaviors. Therefore, this investigation also investigated the relationship between information seeking and scanning and dental health promotion behaviors, and identified potential channels for a dental health promotion campaign among Chinese college students. Some areas of the investigation included identifying how Chinese college students acquire and use dental health related information and the impact of such information on dental health behaviors and health outcomes. The results from this study have theoretical implications for the HBM and the context of Chinese college student dental health, as well as practical implications for how to best promote dental prevention to this population.

2 CHAPTER 2

LITERATURE REVIEW

Health Belief Model

The health belief model (HBM) was developed by social psychologists at the U.S. Public

Health Service (Rosenstock, 1990). It is usually utilized to predict why people will take action to prevent, to screen for, or to control illness conditions. The HBM contains six constructs: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy, which are briefly reviewed below.

Perceived susceptibility refers to the assessment of risk of developing the health problem

(Glanz, Rimer, & Viswanath, 2008). In other words, this construct refers to one's opinion of his or her chances of acquiring the health risk. In this study, perceived susceptibility referred to participants’ assessment of their personal likelihood to develop cavities and other dental problems. Perceived severity refers to the assessment of severity of the health problem, such as whether the problem is life-threatening or may cause extensive disability or pain. In this study, perceived severity referred to participants’ assessment of the consequences of poor dental health

(e.g., development of dental cavities and other dental issues). Sometimes perceived susceptibility and severity are combined to identify threat (Glanz, Rimer, & Viswanath, 2008).

Perceived benefits refer to the advantages people can gain if they engage in a health- promoting behavior to decrease risk of disease. Perceived benefits in this study referred to the positive consequences that can occur if people engage in preventive dental health behaviors (i.e., brushing, flossing, dental checkup). Perceived barriers refer to the assessment of the obstacles they might face if they engage in a health-promoting behavior to decrease risk of disease (Jones,

3 Smith, & Llewellyn, 2014). This could include lack of knowledge, lack of time, and fear of

visiting the dentist. Cues to action refer to the cue to prompt participants’ engagement in these

behaviors (Rosenstock, 1990). In this study, for example, cues to action included reminder cards, dental knowledge lectures, and dental check-up discounts. Finally, self-efficacy refers to assessment of participants’ competence to successfully perform these health behaviors. For example, participants assessed whether they have confidence in their ability to brush their teeth daily. These six constructs and modifying factors (knowledge and demographic factors) can affect people’s perceptions, the combination of beliefs leads to behavior (Jones et al., 2015).

Cultural dimensions

This study explored dental health behaviors among Chinese college students, a

population with much different characteristics than populations in previous studies that have

tested both the HBM and dental behaviors. Several theoretical models explain why intercultural

differences produce different behavioral patterns, and then produce different health outcomes. It is pertinent to understand how health functions differently in these distinct contexts. Much

research has investigated different health outcomes under different cultural background. For

example, after measuring health related quality of life of Dutch and Chinese traumatic brain injury patients, researchers found conceptual differences in the social functioning, domains

vitality and mental health (Cnossen et al., 2017). They inferred cultural differences play a role.

Researchers also investigated depression of Chinese and Euro-Canadian outpatients (Ryder et al.,

2008). The report showed that Chinese participants reported more somatic symptoms (such as

headaches, insomnia, dizziness, and various pains), however, Euro-Canadians reported more

psychological symptoms. This section reviews why Chinese culture is distinct from Western

cultures, and why that might impact dental behavior (or health behavior more broadly defined) in

this context. Individualism versus collectivism, power distance and uncertainty avoidance are

discussed to explore how cultural similarities and differences in different countries affect

4 decision-making. Each of the dimensions are reviewed and examples related to Chinese culture and potential relationships to dental health behaviors are explored.

Individualism versus collectivism. Individualism versus collectivism refers to the

relationship between individuals with both society and other people (Hofstede Insights, 2018). In

individualistic cultures, individuals are more likely to have independent relationships with other

people, and their goals are more important than group’s goals. In contrast, in collectivistic

cultures, individuals prefer to have interdependent relationships to other people, and group

interests are more important than individual interests and aspirations (Triandis, Bontempo,

Villareal, Asai, & Lucca, 1998). In collectivist cultures, if group interests conflict with individual

interests, group interests have priority.

China is guided by collectivistic culture because of the influence of Confucianism.

Confucianism was developed by philosopher Confucius (551–479 BCE) and includes moral,

social, political, and religious. Confucianism influences how Chinese people how to live, get

along with others, and even how to govern the country (Confucius, Brooks, & Brooks, 1998).

Confucianism emphasized the harmony of family and social, people are supposed to uphold his or

her country’s interest with his or her life — and that he or she should not do things just to pursue

his or her personal interests. He or she should be more care about the whole group rather than him

or herself.

For dental health behaviors such as brushing, flossing and dental checkups, some

individuals in an individualist culture might think these behaviors are individual health behaviors

and a related health campaign is an effort to interfere with their right to privacy for these personal

behaviors (Pentecostes, 1999). However, for individuals in a collectivistic culture, if they

consider dental health as collective health, such as a behavior that impacts other people, they

would be more likely to accept the health campaign. For example, if health care practitioners

want to design an advertisement to promote dental health behaviors, advertisement emphasizing

individualistic benefits (such as the prevention of dental cavities or that teeth will be clean) would

5 be more persuasive for individualist cultures, while advertisement emphasizing family or ingroup benefits (such as their breath will be presentable to others) would be more appropriate for

collectivistic cultures such as China.

Power distance. Power distance refers to the situation of unequal social status between

people and how people accept it (Hofstede, 2001). A culture with high power distance is always

autocratic and paternalistic, the power is concentrated in the hands of the minority, and people

view the power and hierarchy as natural, there is nothing wrong with inequality (Triandis, 1982).

In societies with high power distance, individuals tend to accept a request from or agree with authority demands and the opinions of people in authority (Jung & Kellaris, 2006). Alternatively, the low power distance cultures are egalitarianism, which means the distribution of power among people is relatively low inequality (Triandis, 1982). Low power distant individuals would be less likely to accept a request from or agree with authority demands compared to high power distant individuals, and the opinions of people in authority would be less persuasive (Jung & Kellaris,

2006).

China is a culture with high power distance, because Confucianism continues to have far- reaching influence in China. Confucianism emphasizes altruism and the obligations of the ruled to the ruler, the ruled should be loyal to the ruler (Confucius, Brooks, & Brooks, 1998). Chinese people are supposed to give priority to the opinions of people in authority. A study explored the effect of cultural differences on persuasion, they found individuals in high power distance culture are less likely to question the validity of a claimed expert, whereas individuals in low power distance culture are more likely to question the authority, and more focus on the evidence itself

(e.g., Pornpitakpan & Francis, 2000; Hornikx & Hoeken, 2007). Therefore, for a dental health campaign in China, if the information is from the authority, it would be more persuasive for

Chinese people, and they would be more likely to accept it compared people in low power

distance culture.

6 Uncertainty avoidance. Uncertainty avoidance refers to individual’s tolerance for ambiguity and uncertainty (Hofstede Insights, 2018). For people, unknown future will bring anxiety, this dimension is about how people in different culture deal with such anxiety. People in

cultures with high uncertainty avoidance always try to avoid risks and maintain rigid codes of

belief and behavior, therefore, they tend to be distrustful of new ideas or behaviors (Dawar,

Parker, & Price, 1996). Weak uncertainty avoidance index countries have a greater tolerance for uncertainty, have a great tendency to a relaxed lifestyle and a tendency to encourage adventure.

(Hofstede, 1980).

In Hofstede’s (2010) cultural dimensions, dimensions’ scores range from 0 to 120, 0 means low, 120 means high. For uncertainty avoidance, China’s score is 30, which means

Chinese culture is a low uncertainty avoidance culture. In Chinese culture, people might have a greater tolerance for uncertainty. Therefore, for dental health, Chinese people might be more likely to try new ideas or behaviors.

In summary, China is a collectivistic, high power distance and low uncertainty avoidance culture. If health care practitioners want to conduct a dental health campaign in China, a suitable way is using restrictive strategies (active measures, such as enforcement, as well as education and engineering), emphasizing family or ingroup benefits and the information is from the authority,

encourage people to try new dental health behaviors such as flossing.

Dental Health Prevention

Several previous studies have used different theories to explore dental health issues,

which included the theory of planned behavior (TPB) and the theory of reasoned action (TRA), in

addition to the HBM (Buglar, White, & Robinson, 2010; Dumitrescu, Wagle, Dogaru, &

Manolescu, 2011; Lavin & Groarke, 2005; Syrjälä, Niskanen, & Knuuttila, 2002). For example,

Dumitrescu, Wagle, Dogaru, & Manolescu (2011) used TPB to conduct a survey and measured

attitudes, subjective norms, perceived behavior control, oral hygiene intentions and behaviors related to oral health. Lavin & Groarke (2005) also used TPB to predict dental floss intentions

7 and behavior. Researchers also used TRA explored the relationship among brushing attitude, subjective norm of brushing, brushing intention, brushing behavior and diabetes (Syrjälä,

Niskanen, & Knuuttila, 2002).

Some previous studies have examined dental health behaviors based on the HBM in international contexts outside of the United States. For example, researchers designed an educational intervention targeted at pregnant women based on the HBM in Iran, the result showed that the intervention was effective to promote preventive behaviors of tooth decay (Ghaffari,

Rakhshanderou, Safari, & Torabi, 2018). The HBM concepts were all significant predictors.

Additionally, Buglar (2010) utilized the HBM in Australia to examine the relationships among

HBM beliefs and brushing, and flossing behaviors. The results showed self-confidence of brush and floss and perceived barriers significantly predicted oral behaviors, rather than perceived severity and perceived benefits. Finally, Tiwari, Mulvahill, Wilson, Rai, and Albino (2018) explored at Latino populations’ to assess parental dental knowledge, attitudes, behavior and psychosocial measures, then tried to found the relationships between these aspects and dental health behaviors of children. They found the results were different for Spanish-speaking mothers and English-speaking mothers. These studies provided evidence that the HBM not only can be used on Western cultures like the United States, but also can be used in different cultural contexts. In addition, above studies showed that in different cultural contexts, different components of HBM best predict the health behavior. In summary, the applicability in different cultural contexts indicates the HBM is likely a good model for Chinese college students, and it is clear research should uncover the strongest predictors of dental health in this context specifically.

Therefore, the following hypothesis is proposed:

H1: The components of HBM will predict daily brushing (H1A), daily flossing (H1B) and annual check-up behavior (H1C) among Chinese college students.

Self-efficacy has a wide range of applications in communication. Studies have established that self-efficacy can predict various types of health behaviors, for example, quit

8 smoking (Pinsker et al., 2017), cope with the challenges of chronic disease (Cameron et al.,

2018), healthy eating (Strachan & Brawley, 2009), among others. Many studies measured self-

efficacy in a diversity of ways across different contexts. For example, Guan & So (2016)

measured self-efficacy by reporting the extent they describe themselves as being confident on

specific concepts. The result showed that for participants in a social group which advocate health-

related behavior, if they had stronger social identity, they would perceive greater social support

from the group, then they would have higher self-efficacy of performing the specific behavior,

and it caused greater behavioral intention. In another study, in order to assess optimistic self-

beliefs of German, Spanish, and Chinese individuals, Schwarzer, Bäßler, Kwiatek, Schröder, &

Zhang (1997) used a ten-item scale to measure general self-efficacy. General self-efficacy refers

to a broad and stable personal competence to handle a wide range of stressful situations

effectively. They found all three languages scales were reliable. Specifically, Chinese participants

showed low mean levels of perceived self-efficacy due to Chinese were less individualistic than

Westerners. The result showed that the general measure of self-efficacy is equivalent across

cultures.

There were several studies that explored the relationship between self efficacy and dental

health. Ghorbani, Shahnazi, and Hassanzadeh (2018) conducted a randomized controlled trial to

assess the impact of dental health educational intervention on female junior high school students’

perceived susceptibility and self efficacy. Self-efficacy was measured by eight questions that

assessed specific self-efficacy, such as “I can learn the correct way to use dental floss”. Stewart,

Strack, & Graves (1999) studied the relationships among dental self-efficacy, outcome

expectations, dental health value and dental health behavior and dental plaque. The dental self-

efficacy scales included self-efficacy items for brushing, flossing and dental visits specifically.

Therefore, these past studies that have investigated self-efficacy of dental behaviors have

measured it in terms of its specific context, rather than general self-efficacy. Therefore, the

9 present study measured self-efficacy by assessing participants’ confidence on specific dental

health behaviors such as brushing, flossing and dental checkups rather than general self-efficacy.

Indeed, some studies have explored the relationship between the HBM and dental health behavior (Jeihooni, Jamshidi, Kashfi, Avand, & Khiyali, 2017)), but none of these studies have

examined Chinese populations. Most of the work has been conducted in Western cultures, and

usually in the United States. Even though many studies have shown that self-efficacy is a strong

predictor of under Western context (e.g., Stewart, Strack, & Graves,1999), few studies examined

how self-efficacy beliefs operate with non-Western context. So the impact of self-efficacy on

health (and specifically dental health) still unclear. Therefore, the research questions are

proposed:

RQ1: Does self-efficacy predict daily brushing (RQ1A), daily flossing (RQ1B), and

annual check-up (RQ1C) among Chinese college students?

RQ2: Which component of the HBM is the best predictor of daily brushing (RQ2A),

daily flossing (RQ2B), and annual check-up (RQ2C) among Chinese college students?

As a developing country, health communication in China is still an underexplored

cultural context, especially for dental health. Another goal of the present research is to explore

how Chinese college students retrieve health information through seeking and scanning.

Information seeking was defined by Johnson (1997) as “the purposive acquisition of information

from selected information carriers” (p. 4). Alternatively, “information scanning represents

information acquisition that occurs within routine patterns of exposure to mediated and

interpersonal sources that can be recalled with a minimal prompt”. (Niederdeppe et al., 2007, p.

2). Information scanning is very common, in contrast, information seeking is relatively rarer

(Niederdeppe et al., 2007). Study showed that participants used more sources for information

scanning, but information received through seeking influenced their decisions more than

information received through scanning (Niederdeppe et al., 2007). Hovick & Bigsby (2016)

conducted a survey to explore the links among information seeking and scanning and disease-

10 related beliefs, attitudes and health outcomes. The result suggested that less purposeful information acquisition had a stronger impact on disease-related beliefs, attitudes and health outcomes. Another research investigated mammogram-related media information seeking and scanning (Lee, Zhao, & Pena-y-Lillo, 2016) and they found that information seeking and scanning behaviors were positively linked to the intention to get a mammogram. Above studies indicate that information seeking or scanning are consequential to subsequent preventive health behaviors. Therefore, identifying seeking and scanning behaviors will provide a greater understanding of information that could influence subsequent preventive health behaviors.

Information seeking and scanning related studies are limited in the Chinese context. One study investigated adults’ health information seeking behaviors in Hong Kong (Wang, Viswanath, Lam,

Wang, & Chan, 2013). They found most of participants sought health information monthly from newspapers/magazines, television, radio or Internet. Moreover, male with lower education background, lower income, ever-smoking and physical inactivity were less likely to seek health information. Deng, Liu, & Hinz (2015) explored the how Chinese consumers seek health information through mobile phones, and measured their usage behavior intention. The result suggested that information quality, perceived value, and influenced the intention to seek, and thus the intention to use the information. Only few studies measured the ways Chinese people used to gain dental health information (Yin, Peng, Chen, & Zhong, 2005). The results showed that participants gained most of their dental health related information from the dentists, mass media, and dental health publicity and education from government are subsidiary channels. Once study explored media use and preferences of Chinese college students, researchers can select a channel that people prefer to improve a potential dental health campaign’s potential exposure and effectiveness. Therefore, the following research questions are proposed:

RQ3: What source(s) do Chinese college students prefer when they seek dental health- related knowledge?

11 RQ4: From what source(s) do Chinese college students come across dental health-related knowledge?

RQ5: Does seeking or scanning best predict daily brushing behavior (RQ5A), daily

flossing behavior (RQ5B), and annual dental check up (RQ5C)?

In summary, this study examined the predictors of dental health prevention behavior

(specifically teeth brushing, flossing, and regular check-up) and information seeking and

scanning behaviors among Chinese college students. Moreover, this research also examined the

intercultural differences in the Chinese context. Results from this study have implications for effective ways to teach and encourage dental health promotion in China and improve Chinese dental health awareness.

12 CHAPTER 3

METHOD

Participants

Chinese college students currently completing their undergraduate degrees were recruited to participate in the study. A convenience sample of 150 participants was recruited via social media (on the platforms of QQ and Wechat). Eighty-two participants (54.7%) indicated gender identification as female, fifty-two (34.7%) indicated gender identification as male, seven (4.7%) indicated they preferred not to respond, and nine (6%) did not respond. The participants were

between the ages of 18-25 (M = 21.42, SD = 1.74). Only participants that responded to all of the demographic items were included in the present data analysis. Participants received a link to complete the questionnaire online from their personal computers or personal smart phones. They were told that they would participate in a study on student’s health beliefs. They were asked to respond to a questionnaire, which took approximately 10-15 minutes. Finally, respondents were thanked for their assistance in the research. The study was approved by the institutional review board at the University of Dayton prior to the administration of the survey

Procedure

The survey was hosted on Fanqier. Fanqier is an online form creation and data collection tool. Recruitment information was posted on college student group and chat with college students from the group online to invite them to complete the survey (on the platforms of QQ and

Wechat). After participants agreed to participate the survey, they were asked to respond to a series of items related to dental prevention behavior such as daily tooth brushing and flossing, as well as regular dental visits. The questionnaire took approximately 10-15 minutes to complete.

13 Because the population recruited is in China, the questionnaire was translated from English to

Chinese to accommodate the students’ native language. Data collection took place in May and

June of 2018.

Measures

Components of the Health Belief Model. Items measuring the components of the

Health Belief Model (susceptibility, severity, benefits, barriers, cues to action, and self-efficacy) were developed for this study. The wording of several items was adapted from Buglar, White, &

Robinson (2010) from their study on brushing behaviors. The items have been adjusted to address three dental prevention behaviors: daily brushing, daily flossing, and annual dental check-up. All items were rated on five point Likert scales, anchored by 1 (Strongly Disagree) to 5 (Strongly

Agree). Examples of the items within the specific construct are illustrated below.

HBM: Threat. Susceptibility was measured by six items assessing perceived risk of

developing dental cavities. This included items such as: “It is likely that I will develop dental

cavities”, “It is more likely that I will develop dental cavities if I do not brush regularly”. The

susceptibility scale was reliable (M = 3.43, SD = .91, α = .87). Severity was measured by seven

items assessing perceived consequences of developing dental cavities. This included items such

as: “If I get dental cavities, it will be very serious”, “If I get dental cavities, it will influence my

day to day life”. The severity scale was reliable (M = 4.07, SD = .79, α = .89).

HBM: Benefits. Benefits of three behaviors were measured: daily brushing, flossing, and

dental check-up. Benefits of daily brushing was measured by five items assessing perceived

advantages of daily brushing. This included items such as: “Brushing my teeth daily will make

my teeth healthy” and “Brushing my teeth daily will make me more confident”. Benefits of daily

brushing was reliable (M = 4.61, SD = .51, α = .84). Benefits of daily flossing was measured by

four items accessing perceived advantages of daily flossing. This included items such as:

“Flossing my teeth once a day will make my teeth healthy” and “Flossing my teeth once a day

will prevent dental cavities”. Benefits of daily flossing was reliable (M = 3.15, SD = 1.17, α

14 = .95). Benefits of annual dental check-up was measured by four items assessing perceived

advantages of annual dentist visits. This included items such as: “Go to dentist annually will

inform my teeth condition”, “Go to dentist annually will make me know how to protect teeth”.

The benefits of annual dental check-up were reliable (M = 4.32, SD = .90, α = .92).

HBM: Barriers. Barriers of three behaviors were measured: daily brushing, flossing, and

dental check-up Barriers of daily brushing was measured by four items assessing perceived

obstacle of daily brushing. This included items such as: “I am too lazy to brush my teeth daily”

and “I have very busy schedule, so I don’t have time to brush my teeth daily”. Barriers of daily

brushing was reliable (M = 1.85, SD = 1.19, α = .91). Barriers of daily flossing was measured by

six items accessing perceived obstacle of daily flossing. This included items such as: “I don’t

know about flossing” and “I am too lazy to floss my teeth daily”. Barriers of daily flossing was

reliable (M = 3.79, SD = .99, α = .84). Barriers of dental check-up was measured by six items

assessing perceived obstacles to dental check-up. This included items such as: “Going to the dentist annually spend much money” and “I am too lazy to go to dentist annually”. The barriers to

annual dental check-up were reliable (M = 2.87, SD = .92, α = .80).

HBM: Cues to Action. Cues to action of three behaviors were measured: daily brushing,

flossing, and dental check-up. Cues to action of daily brushing were measured by six items

accessing cue to prompt engagement in daily brushing. This included items such as: “I will brush

my teeth daily if I already have the habit” and “I will brush my teeth daily because of intimate

contact such as a kiss”. Cues to action of daily brushing was not reliable (M = 4.30, SD = .67, α

= .71). Cues to action of daily flossing was measured by five items accessing cue to prompt

engagement in daily flossing. This included items such as: “I will floss my teeth once a day if I

know information about flossing” and “I will floss my teeth once a day if my friends or families

recommend it”. Cues to action of daily flossing was reliable (M = 2.96, SD = 1.04, α = .87). Cues

to action of dental check-up was measured by six items assessing cue to prompt engagement in

dental check-up. This included items such as: “I will go to dentist annually if my teeth are really

15 bad” and “I will go to dentist annually if there is group check-up”. Cues to action of annual dental check-up was reliable (M = 3.95, SD = .81, α = .83).

HBM: Self-Efficacy. Self-efficacy to perform the three behaviors (daily brushing, flossing, and dental check-up) was measured as well. Self-efficacy of daily brushing was measured by three items assessing participants’ competence to successfully perform daily brushing. This included items “Brushing my teeth is hard to do”, “I am confident I can brush my teeth daily” and “I am not sure if I can brush my teeth daily”. Self-efficacy of daily brushing did not develop a reliable scale (α = .69), so items were entered into analyses separately rather than as a combined scale. Self-efficacy of daily flossing was measured by three items assessing participants’ competence to successfully perform daily flossing. This included items “Flossing my teeth is hard to do”, “I am confident I can floss my teeth once a day” and “I am not sure if I can floss my teeth once a day”. Self-efficacy of daily flossing was not reliable (α = .23), so items were entered into analyses separately rather than as a combined scale. Self-efficacy of dental check-up was measured by three items assessing participants’ competence to successfully perform dental check-up. This included items “Going to dentist is hard to do”, “I am confident I can go to dentist annually” and “I am not sure if I can got to dentist annually”. Self-efficacy of annual dental check-up was not reliable (α = .40), so items were entered into analyses separately rather than as a combined scale.

Information scanning and seeking. The survey included two questions about dental health related information scanning and seeking. Information scanning was measured with the item: “Through what sources do you come across information about health-related knowledge?”

[never (1), occasionally (2), some days (3), every day (4)]. The resources included social media, mass media (newspaper, TV, radio), school, dentist, and other. Information scanning was not reliable (α = .61), so each item was entered as a separate predictor rather than a combined scale.

Information seeking was measured with the item: “Through what sources do you search information about health-related knowledge?” [never (1), occasionally (2), some days (3), every

16 day (4)]. The resources also included social media, mass media (newspaper, TV, radio), school,

dentist, and other. Information seeking was not reliable (α = .76), so each item was entered as a

separate predictor rather than a combined scale. Respondents were asked to indicate the number

[never (1), occasionally (2), some days (3), every day (4)] for each source that best reflects how

often they see health-related information.

Self-reported dental behavior. The survey measured three current dental behaviors: daily

brushing, daily flossing and annual check-up. These items were adopted from self-report behavior measures developed by Buglar, White, and Robinson (2010). Brushing behavior was measured with the item: ‘‘During the last week, how often did you brush your teeth?’’ [not at all (1), once a

week (2), every second day (3), once a day (4), twice a day (5)]. Flossing behavior was measured

with the item: ‘‘During the last week, how often did you floss your teeth?’’ [not at all (1), once a

week (2), every second day (3), once a day (4), twice a day (5)]. Annual check-up behavior was

measured with the item: “During the last year, did you ever do dental health check-up?” [yes (1),

no (0)].

Self-reported demographic items. Participants also responded to three demographic

items. The respondents reported gender: “What is your gender?” (male, female, prefer not to

respond). Additionally, they self-reported age with the item, “what is your age?”. Finally, the

participants assessed self-rated knowledge of dental health, “How will you rate your dental

health-related knowledge” on a 5-point Likert-type scale, anchored by Very deficient (1) to Very

sufficient (5).

Statistical Analysis

Hierarchical multiple regression analysis was used to assess demographic variables and

the HBM factors in predicting twice daily brushing and daily flossing. Each behavior was

analyzed separately in three different models. In all models, the demographic variables of gender,

age and knowledge were entered as control variables in Step 1, similar to the procedure of the

dental health study Buglar et al (2010) conducted. The five HBM components (perceived

17 susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action) were entered in Step 2. Self-efficacy was entered in Step 3 to predict daily brushing behavior (Model 1; to assess H1A, RQ1A, RQ2A) and daily flossing behavior (Model 2; to assess H1B, RQ1B,

RQ2B). For the control variables, age was used to confirm the participants are college students; gender was used to examine whether there was gender difference; knowledge was used to examine the influence of dental related knowledge on dental behaviors.

Logistic regressing analysis was used to assess demographic variables and the HBM factors in predicting annual check-ups. The demographic variables of gender, age and knowledge were entered as control variables in Step 1, similar to the procedure of the dental health study

Buglar et al (2010) conducted. The five HBM components (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action) were entered in Step 2. Self- efficacy was entered in Step 3 to predict annual check-ups behavior (Model 3; to assess H1C,

RQ1C, RQ2C).

To examine RQ5, hierarchical multiple regression analysis and logistic regression using either information scanning or seeking as independent variables, using dental health promotion behaviors as dependent variables, in order to examine the multivariate relationships between independent variables and dependent variables. More specifically, in order to determine whether information scanning or seeking is associated with health behavior, this survey used hierarchical multiple regression analysis for continuous dependent variables of daily brushing behavior

(RQ5A) and daily flossing behavior (RQ5B) and logistic regression for dichotomous dependent variables of annual dental check-up behavior (RQ5C).

Data Cleaning

All the HBM components (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy), information seeking and scanning, three behaviors (brushing, flossing, and check-up) and dental-related knowledge were checked for normality. All these variable skewed significantly according to the Shapiro-Wilk test. For

18 behaviors variables, if the data are non-normal, they must be transformed. Researcher tried

transformation approaches for daily brushing behavior, daily flossing behavior and annual dental check-up behavior. Because these variables were positively skew, a log transformation, square root transformation, reciprocal transformation, were formed (Field, 2013), but still failed to provide normally distributed data. As a result, bootstrapping was used (Field, 2013).

19 CHAPTER 4

RESULTS

HBM and Brushing Behavior

In this survey, one hundred and seven (71.3%) participants reported brushing twice a day

during last week, thirty-two (24.7%) participants indicated brushing once a day, six (4%)

participants reported brushing every second day, and no participant indicated brushing once a

week or not at all.

Multiple regression analysis was conducted to test whether the HBM constructs

significantly predicted the brushing behavior. In this multiple regression, the first model included

gender, age and knowledge, the second model included the five HBM components scales

(perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to

action) for brushing behavior, the third model included the three items of self-efficacy for

brushing behavior. The components of HBM significantly predict brushing behavior (adjusted R2

of model 3 = .15; R2 change between model 2 and model 3 = .12, p < .01, model 3: F (11,107) =

2.90, p < .01). Thus, H1A was supported. For RQ1A, self-efficacy significantly improves the

model (as evidenced by R2 change between model 2 and 3). For RQ2A, self-efficacy was the best predictor of brushing behavior, especially item #2 (I am confident I can brush my teeth daily) (β

= .38, t = 3.62, p < .01).

HBM and Flossing Behavior

In this survey, one hundred and thirty-four (89.3%) participants did not floss at all during

the last week, seven (4.7%) participants flossed once a week, four (2.7%) participants flossed

20 every second day, three (2%) participants flossed once day, and two (1.3%) participants reported

flossing twice a day.

Multiple regression analysis was conducted to test whether the HBM constructs

significantly predicted the flossing behavior. In this multiple regression, the first model included

gender, age and knowledge, the second model included the five HBM components scales

(perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action) for flossing behavior, the third model included the three items of self-efficacy for flossing

behavior. The components of HBM significantly predicted flossing behavior (adjusted R2 of model 3 = .14; R2 change between model 2 and model 3 = .01, p = .76; model 3: F (11,107) =

2.74, p < .01), H1B was supported. For RQ1B, model 3 did not improve model 2, self-efficacy

does not improve flossing behavioral prediction. For RQ2B, barriers and dental-related

knowledge were the best predictor of flossing behavior, such that reducing barriers improved

flossing behavior (β = -.30, t = -2.85, p < .01), and increasing knowledge improved flossing behavior (β = .23, t = 2.59, p = .01).

HBM and Dental Check-up Behavior

In this survey, one hundred and three (68.7%) participants did not do dental check-up during last year, forty-seven (31.3%) participants did dental check-up.

A logistic regression analysis was conducted to test whether the HBM constructs significantly predicted the dental check-up behavior. In this logistic regression, the first model included gender, age and knowledge, the second model included the five HBM components scales (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action) for dental check-up behavior, the third model included the three items of self- efficacy for dental check-up behavior. The components of HBM significantly predicted dental checkup behavior (model 2: χ 2 (8, N = 119) = 30.47, p < .01). The model explained 31.6%

(Nagelkerke R2) of the variance in annual dental check-up behavior and correctly classified

73.1% of cases. H1C was supported. For RQ1B, model 3 improved model 2 (model 3: χ 2 (11, N

21 = 119) = 40.51, p < .01), this model explained 40.4% (Nagelkerke R2) of the variance in annual dental check-up behavior and correctly classified 75.6% of cases, self-efficacy improved check- up behavioral prediction. For RQ2B, knowledge (Wald = 16.25, df = 1, p < .01) and the second item of self-efficacy (Wald = 8.18, df = 1, p < .01) were the best predictors of dental check-up behavior. Chinese college students with more dental-related knowledge were 6.25 times more likely to do annual dental check-up. Chinese college students with higher confidence about going to dentist annually were 2.05 times more likely to do annual dental check-up.

Information Seeking and Scanning

For RQ3, this study explored the sources Chinese college students prefer to seek dental health-related knowledge. The results indicated that participants prefer to seek from social media

(M =1.99, SD = .77) and from the dentist (M = 1.87, SD = .82) for dental health-related

knowledge. The descriptive statistics of information seeking as following.

Table 4.1: Descriptive statistics of information seeking

Std. N Minimum Maximum Mean Deviation

Seek from social media 130 1 4 1.99 .773

Seek from mass media 129 1 4 1.83 .811

Seek from school 126 1 4 1.62 .768

Seek from dentist 123 1 4 1.87 .819

The distribution of responses is reported in the following tables. Table 4.2 indicates

results for social media, Table 4.3 for mass media, Table 4.4 for school, and Table 4.5 for dentist.

22 Table 4.2: Information seeking from social media

Frequency of behavior N Percentage(%)

Never 37 24.7

Occasionally 59 39.3

Some days 32 21.3

Every day 2 1.3

Total 130 86.7

Table 4.3: Information seeking from mass media

Frequency of behavior N Percentage(%)

Never 52 34.7

Occasionally 50 33.3

Some days 24 16.0

Every day 3 2.0

Total 129 86.0

Table 4.4: Information seeking from school

Frequency of behavior N Percentage(%)

Never 68 45.3

Occasionally 40 26.7

Some days 16 10.7

Every day 2 1.3

Total 126 84.0

23 Table 4.5: Information seeking from dentist

Frequency of behavior N Percentage(%)

Never 48 32.0

Occasionally 45 30.0

Some days 28 18.7

Every day 2 1.3

Total 123 82.0

For RQ4, this study explored the sources Chinese college students prefer to scan dental health-related knowledge. Participants prefer to scanning from social media (M = 2.25, SD = .72) and mass media media (M = 2.25, SD = .71) for dental health-related knowledge. The descriptive statistics of information scanning as following.

Table 4.6: Descriptive statistics of information scanning

Std. N Minimum Maximum Mean Deviation

Scan from social media 143 1 4 2,25 .717

Scan from mass media 138 1 4 2.25 .713

Scan from school 135 1 4 2.70 .792

Scan from dentist 139 1 4 1.85 .774

The distribution of responses is reported in the following tables. Table 4.7 is social media, Table 4.8 is mass media, Table 4.9 is school, Table 4.10 is dentist.

24 Table 4.7: Information scanning from social media

Frequency of behavior N Percentage(%)

Never 16 10.7

Occasionally 82 54.7

Some days 38 25.3

Every day 7 4.7

Total 143 95.3

Table 4.8: Information scanning from mass media

Frequency of behavior N Percentage(%)

Never 18 12.0

Occasionally 72 48.0

Some days 44 29.3

Every day 4 2.7

Total 138 92.0

Table 4.9: Information scanning from school

Frequency of behavior N Percentage(%)

Never 64 42.7

Occasionally 51 34.0

Some days 16 10.7

Every day 4 2.7

Total 135 90.0

25 Table 4.10 Information scanning from dentist

Frequency of behavior N Percentage(%)

Never 45 30.0

Occasionally 56 37.3

Some days 38 25.3

Every day 0 0.0

Total 139 92.7

Brushing. Multiple regression analysis was conducted to test whether information

seeking significantly predicted brushing behavior. In this multiple regression, the first model

included gender, age and knowledge, the second model included seeking from social media, seeking from mass media, seeking from school and seeking from dentist. For RQ5A, information

seeking did not significantly predict brushing behavior (adjusted R2 of model 2 = .03; R2 change

between model 1 and model 2 = .00, p = .99, model 2: F (7, 90) = 1.47, p = .23).

Multiple regression analysis was conducted to test whether information scanning

significantly predicted brushing behavior. In this multiple regression, the first model included

gender and age, the second model included scanning from social media, scanning from mass

media, scanning from school and scanning from dentist. For RQ5A, information scanning did not

significantly predict brushing behavior (adjusted R2 of model 2 = .02; R2 change between model 1

and model 2 = .03, p = .59, model 2: F (7, 94) = 1.35, p = .24).

Flossing. Multiple regression analysis was conducted to test whether information seeking significantly predicted flossing behavior. In this multiple regression, the first model included gender, age and knowledge, the second model included seeking from social media, seeking from mass media, seeking from school and seeking from dentist. For RQ5B, information seeking not

26 significantly predict flossing behavior (adjusted R2 of model 2 = .06; R2 change between model 1 and model 2 = .02, p = .69, model 2: F (7, 90) = 1.81, p = .10).

Multiple regression analysis was conducted to test whether information scanning significantly predicted flossing behavior. In this multiple regression, the first model included gender, age and knowledge, the second model included scanning from social media, scanning from mass media, scanning from school and scanning from dentist. For RQ5B, information scanning not significantly predict flossing behavior (adjusted R2 of model 2 = .07; R2 change between model 1 and model 2 = .09, p = .02, model 2: F (7, 94) = 2.05, p = .06).

Dental check-up. Logistic regression analysis was conducted to test whether information seeking significantly predicted dental check-up. In this regression, the first model included gender, age and knowledge, the second model included seeking from social media, seeking from mass media, seeking from school and seeking from dentist. For RQ5C, information seeking significantly predicted brushing behavior (model 2: χ 2 (7, N = 98) = 37.21, p < .01). The model explained 44.9% (Nagelkerke R2) of the variance in annual dental check-up behavior and

correctly classified 78.6% of the cases. Particularly, knowledge (Wald = 12.65, df = 1, p < .01) and seeking from dentist (Wald = 7.04, df = 1, p < .01) were the best predictors of check-up behavior. Chinese college students with more dental-related knowledge were 5.67 times more likely to do annual dental check-up. Chinese college students who sought dental-related information from the dentist more frequently were 2.90 times more likely to do annual dental check-up.

Logistic regression analysis was conducted to test whether information scanning significantly predicted the dental check-up. In this regression, the first model included gender, age and knowledge, the second model included scanning from social media, scanning from mass

media, scanning from school and scanning from dentist. For RQ5C, information scanning significantly predicted annual check-up (model 2: χ 2 (7, N = 102) = 35.34, p < .01). The model explained 42.4% (Nagelkerke R2) of the variance in annual dental check-up behavior and

27 correctly classified 78.6% of the cases. Specifically, knowledge (Wald = 8.98, df = 1, p < .01) and scanning from dentist (Wald = 6.52, df = 1, p = .01) were the best predictors of checkup behavior.

Chinese college students with more dental-related knowledge were 4.86 times more likely to do annual dental check-up. Chinese college students who scanned dental-related information from the dentist more frequently were 2.90 times more likely to do annual dental check-up.

Knowledge

In this study, most (52.0%) participants thought their dental-related knowledge is moderate. The frequencies of dental related knowledge are presented in Table 4.11.

Table 4.11: Dental related knowledge

Frequency of knowledge N Percentage(%)

Very sufficient 1 0.7

Sufficient 8 5.3

Moderate 78 52.0

Deficient 46 30.7

Very deficient 17 11.3

Total 150 100.0

28 CHAPTER 5

DISCUSSION

In this study, the Health Belief Model has been confirmed to be an effective model to predict health behavior among Chinese population. The HBM was developed as a Western

culture based model, but it also has been validated as useful in several international contexts: with

Chinese cultural background, Iran cultural background (Rahmati-Najarkolaei, Rahnama, Gholami

Fesharaki, & Behnood, 2016), Australian cultural background (Buglar, White, & Robinson,

2010). However, the HBM might have different results in different cultural backgrounds -- not all concepts will be good predictors. In this study, self-efficacy and barriers were significantly predictors of dental health behaviors. In Buglar’s (2010) study, self-efficacy and barriers also predicted oral hygiene behaviors. Even though Buglar’s results were the same as the present

study, the questions that were used to measure barriers were different. In this study, barriers for

flossing were lack of knowledge, lack of flossing, laziness, do not have flossing habits,

complexity of flossing, and lack of need to floss. In Buglar’s research, barriers for flossing were

pain, teeth will break, gums will bleed, forgetting to brush and so on. In an Iran study (Rahmati-

Najarkolaei, Rahnama, Gholami Fesharaki, & Behnood, 2016), perceived susceptibility, severity, and barriers were predictors of oral health behaviors. Present study had same predictor with this

study -- barriers, but the biggest barrier in this study was the fear of injections and dentist visits,

which was not measured in the present study.

The health belief model significantly predicted daily brushing behavior among Chinese

college students. This finding is in accordance with earlier findings (Buglar, White, & Robinson,

2010; Hosseini et al., 2014; Rahmati-Najarkolaei, Rahnama, Gholami Fesharaki, & Behnood,

29 2016). Self-efficacy emerged as a significant predictor of this behavior, especially the second

self-efficacy item “I am confident I can brush my teeth daily”. It indicates that daily brushing

behavior is influenced by whether individuals have the confidence that the behaviors can be

performed. Other HBM constructs (susceptibility, severity, benefits, barriers, and cues to action) were less significant than self-efficacy, this difference may be due to Chinese college students

already know the threat of dental cavities -- they have basic knowledge of the benefits of daily

brushing. So, health campaigns practitioners focusing on Chinese college students daily brushing

behavior should try to improve their confidence regarding the behavior to encourage them to do

it.

The health belief model also significantly predicted daily flossing behavior among

Chinese college students. Consistent with previous research (Carpenter, 2010; Rahmati-

Najarkolaei, Rahnama, Gholami Fesharaki, & Behnood, 2016), perceived barriers was the most

important and strongest determinant of the HBM dimensions for flossing behavior. It suggests

that health campaign interventions should target barrier reduction processes. In this survey, most

of participants (89.3%) did not floss at all during the last week, with only three (2%) participants

flossing daily. Considering such a situation, interventions also should target flossing-related

knowledge. Practitioners could prepare a lecture, offer brochures, exhibit how to use dental floss,

distribute free dental floss samples, distribute flyer to Chinese college students.

The health belief model significantly predicted annual dental check-up behavior among

Chinese college students. Knowledge and self-efficacy emerged as significant predictors of this

behavior, especially the second self-efficacy item “I am confident I can go to the dentist

annually”. It indicates that health campaign interventions should focus on dental check-up related knowledge and confidence regarding dental check-up behavior. Practitioners need to educate target audience dental check-up related knowledge, and improve their confidence on the behavior to encourage them to do it.

30 Thus, the HBM significantly predicted all three dental health behaviors, daily brushing,

daily flossing, and annual dental check-ups. Self-efficacy is the best predictor of both brushing and check-ups behaviors, especially the second item. Knowledge is the best predictor of both flossing and check-up behavior. Flossing behavior has one more predictor -- perceived barriers.

Researchers usually measure general self-efficacy to find out the differences in self- efficacy beliefs among people from different cultures (Scholz, Doña, Sud, & Schwarzer, 2002;

Schwarzer, 1997; Schwarzer, Bäßler, Kwiatek, Schröder, & Zhang, 1997). Self-efficacy for specific behaviors will be more likely to predict the behaviors than general self-efficacy. So self- efficacy in this study was measured by specific behaviors rather than general ones.

In this study, information seeking and scanning only significantly predicted annual dental check-up behavior. In particular, knowledge and seeking/scanning from the dentist were the best predictors. Chinese college students with more dental-related knowledge or who scanned/sought dental-related information from the dentist more frequently were more likely to do annual dental check-ups. This suggests that health campaign interventions should target knowledge. Dentists share dental related knowledge with target audiences will be a good way to encourage them to do annual check-up.

Although the majority (68.7%) reported that they did not do dental check-ups last year,

72.0% of participants reported that they will go to the dentist annually if their teeth are really bad.

This indicates that they do not want to take action for uncertain risk. One item used to measure cues to action about dental check-up behavior is “I will go to the dentist annually if there is a group check-up”. On this item, 72.0% of participants reported they strongly agreed or agreed.

This indicates that the Chinese prefer collectivism. And participants reported that they prefer to seek dental related knowledge from the dentist. This is evidence of a high power-distance culture.

This study did not find differences based on gender. Additionally, it did not measure social norm about dental health behaviors and long term orientation related items.

31 From the survey results, most respondents (52.0%) think their oral health-related knowledge is moderate; only nine participants (6.0%) think it is sufficient or very sufficient. So, providing appropriate oral health-related knowledge is necessary. As for the channel, participants prefer to seek dental health-related knowledge on social media and from the dentist, participants prefer to scan dental health-related knowledge on social media and the mass media. This finding is accordance with the findings of Xu (2010). Health campaign practitioners can post dental health knowledge on social media such as the WeChat official account and Sina Weibo, or post dental health knowledge on mass media such as newspapers, TV, radio. Also, providing dental health related knowledge brochures in dental clinics is a good way for Chinese college students to be reached.

One of the limitation of this study was its sample. The sample in this study is a snowball sample, and included only 150 respondents. China has more than 14 billion people -- 150 college students cannot represent all Chinese college students. Most of the participants were from the

Hunan and Yunnan provinces. These places are underdeveloped compared to Beijing and

Shanghai. This limits the generalizability of the study results, so cautious interpretation is needed in generalizing these findings to other populations. Future study may consider exploring the

general Chinese population.

Another limitation of the survey was the length of the questionnaire, which can lead to

participant fatigue. Future research may consider focusing on fewer HBM concepts rather than

including all concepts. This study included three behaviors, daily brushing, daily flossing and

annual dental check-up. From the results, most of the people already have good brushing habits,

but inadequate flossing and check-up behaviors. Thus future study should focus more on flossing

and check-up behaviors. For example, practitioners may examine the relationship of several self-

efficacy items and annual dental check-up behavior, examine which barriers will prevent people

flossing daily, examine what kind of flossing related knowledge is lacking.

32 Also, this questionnaire only has three self-efficacy questions for each behavior. As self-

efficacy has been confirmed to be an effective predictor of daily brushing and annual dental

check-up, future research may explore more in more detail the predictive function of self-efficacy

on dental health behaviors. This study only measured the confidence of the dental health

behaviors, but self-efficacy includes many aspects, such as ability to deal with unexpected events,

ability to solve problems, past experiences, personality and so on (Scholz, Doña, Sud, &

Schwarzer, 2002). Future study could refer to self-efficacy measurement in other field (such as academics and work life), and self-efficacy under different cultural backgrounds (Western cultures and Asian cultures), to determine more specific self-efficacy items that influence dental health behavior. Health campaign practitioners may then use the results to help people improve their self-efficacy, and then influence their intention and behaviors. Moreover, this study did not explore every cultural dimensions. It only measured individualism versus collectivism, power distance, and uncertainty avoidance. It did not measure masculinity versus femininity, long term orientation versus short term orientation or indulgence versus restraint. Future study could

examine more about how dimensions of cultural variability influence dental health behaviors,

such as whether long/short term orientation, indulgence versus restraint and masculinity versus femininity will influence dental health behaviors.

In summary, this study examined the relationships among daily brushing, daily flossing, annual dental check-up and Health Belief Model items and dental related information seeking and

scanning. It found that the components of the HBM significantly predicted brushing behavior,

flossing behavior, and dental check-up behavior. Self-efficacy was the best predictor of brushing

and dental check-up behavior; barriers and dental-related knowledge were the best predictors of

flossing behavior. Participants prefer to seeking from social media and dentist, and scanning from

social media and mass media. Information seeking and scanning only significantly predict dental

check-up behavior. Knowledge, seeking from dentist, and scanning from the dentist were the best

33 predictors of check-up behavior. Future study could examine more about self-efficacy and dental health behavior within the Chinese cultural context.

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41 APPENDIX A

Dental Health Belief Questionnaire

I am a graduate student at University of Dayton studying communication. The purpose of this study is to examine college students’ beliefs of dental health. The survey should take 10-15 minutes, and your responses are completely anonymous. Thank you for your participation.

First, we will ask you about some of your beliefs about dental health. Please indicate the extent to which you agree or disagree with the following statements.

1 - Strongly disagree

2 - Disagree

3 - Neither agree nor disagree

4 – Agree

5 - Strongly agree

1. It is likely that I will develop dental cavities

My chances of developing dental cavities are high

My mouth is in bad condition

Within the next year I will develop dental cavities

It is more likely that I will develop dental cavities if I eat too much sugar

It is more likely that I will develop dental cavities if I do not brush regularly

2. If I get dental cavities, it will be very serious

42 If I get dental cavities, I will suffer from severe toothaches

If I get dental cavities, it will influence my eating

If I get dental cavities, it will cause other health problems

If I get dental cavities, it will cost me a lot of money

If I get dental cavities, it will influence my day-to-day life

If I get dental cavities, it will make me look unattractive

Next, we will ask you about your brushing behavior and beliefs. Please indicate the extent to

which you agree or disagree with the following statements.

1 - Strongly disagree

2 - Disagree

3 - Neither agree nor disagree

4 – Agree

5 - Strongly agree

3. During the last week, how often did you brush your teeth?

(1) not at all (2) once a week (3) every second day (4) once a day (5) twice a day

4. Brushing my teeth daily will make my teeth healthy

Brushing my teeth daily will prevent me from dental cavities

Brushing my teeth daily will keep my teeth clean

Brushing my teeth daily will gain fresh breath

Brushing my teeth daily will make me more confident

5. I am too lazy to brush my teeth daily

I have very busy schedule, so I don’t have time to brush my teeth daily

43 I forget to brush daily

If I am tired I don’t brush my teeth

6. I will brush my teeth daily if I already have the habit

I will brush my teeth daily for my health

I will brush my teeth daily because I know the benefits

I will brush my teeth daily because of intimate contact such as a kiss

I will brush my teeth daily if I have favorite toothpaste or toothbrush

I will brush my teeth daily if other people compliment my teeth

7. Brushing my teeth is hard to do

I am confident I can brush my teeth daily

I am not sure if I can brush my teeth daily

Next, we will ask you about your flossing behavior and beliefs. Please indicate the extent to which you agree or disagree with the following statements.

1 - Strongly disagree

2 - Disagree

3 - Neither agree nor disagree

4 – Agree

5 - Strongly agree

8. During the last week, how often did you floss your teeth?

(1) not at all (2) once a week (3) every second day (4) once a day (5) twice a day

9. Flossing my teeth once a day will make my teeth healthy

44 Flossing my teeth once a day will make my teeth more clean

Flossing my teeth once a day will prevent dental cavities

Flossing my teeth once a day will be better than toothpick

10. I don’t know about flossing

I don’t have flossing

I am too lazy to floss my teeth daily

I don’t have the habits to floss my teeth

Use flossing is too complicated

I don’t need to floss

11. I will floss my teeth once a day if I know information about flossing

I will floss my teeth once a day for cleaning my teeth deeply

I will floss my teeth once a day if my friends or families recommend it

I will floss my teeth once a day if I feel it is cool

I will floss my teeth once a day because of intimate contact such as kiss

12. Flossing my teeth is hard to do

I am confident I can floss my teeth daily

I am not sure if I can floss my teeth daily

Next, we will ask you about your dental check-up behavior and beliefs. Please indicate the extent to which you agree or disagree with the following statements.

1 - Strongly disagree

2 - Disagree

3 - Neither agree nor disagree

45 4 – Agree

5 - Strongly agree

13. During the last year, did you ever do dental health check-up?

(1) Yes (2) No

14. Going to the dentist annually will inform my teeth condition

Going to the dentist annually will be good for my health

Going to the dentist annually will prevent dental cavities

Going to the dentist annually will make me know how to protect teeth

15. Going to the dentist annually spend much money

Healthy teeth are not very important

I don’t know people need to go to dentist annually

I am too lazy to go to dentist annually

I am afraid to go to dentist annually

I don’t have time to go to dentist annually

16. I will go to dentist annually if my teeth are really bad

I will go to dentist annually if there is free check-up

I will go to dentist annually if the check-up is cheap

I will go to dentist annually if there is group check-up

I will go to dentist annually if I watch the advertisement

I will go to dentist annually if it is convenient for me

17. Going to dentist annually is hard to do

46 I am confident I can go to dentist annually

I am not sure if I can go to dentist annually

Now, we are interested in learning a bit more about where you find dental health information.

18. Through what sources do you come across information about dental health-related

knowledge?

Please indicate the number for each source that best reflects how often you see health-related

information.

(1) Never (2) Occasionally (3) Some days (4) Every day

____ Social media

____ Mass media (newspaper, TV, radio)

____ School

____ Dentist

____ Other (please specify) ______

19. Through what sources do you search information about dental health-related knowledge?

Please indicate the number for each source that best reflects how often you see health-related

information.

(1) Never (2) Occasionally (3) Some days (4) Every day

____ Social media

____ Mass media (newspaper, TV, radio)

____ School

____ Dentist

____ Other (please specify) ______

47 Finally, we would like to know a bit more about you.

20. What is your gender?

(1) Female (2) Male (3) Prefer not to respond

21. What is your age? ______

22. How will you rate your dental health-related knowledge?

(1) Very deficient (2) Deficient (3) Moderate (4) Sufficient (5) Very sufficient

48