Designing and Evaluating a Health Belief Model Based Intervention to Increase Intent of HPV Vaccination Among College Men: Use of Qualitative and Quantitative Methodology

Designing and evaluating a health belief model based intervention to increase intent of HPV

vaccination among college men: Use of qualitative and quantitative methodology

A dissertation submitted to the Graduate School of the University of Cincinnati

In partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY In the School of Human Services of the College of Education, Criminal Justice, and Human Services 2012

by Purvi Mehta MS, University of Cincinnati Committee Chair: Manoj Sharma, M.B.; B.S., MCHES, Ph.D

Abstract

Humanpapilloma virus (HPV) is a common sexually transmitted disease/infection (STD/STI), leading to cervical and anal cancers. Annually, 6.2 million people are newly diagnosed with HPV and 20 million currently are diagnosed. According to the Centers for Disease Control and Prevention, 51.1% of men carry multiple strains of HPV. Recently, HPV vaccine was approved for use in boys and young men to help reduce the number of HPV cases. Currently limited research is available on HPV and HPV vaccination in men. The purpose of the study was to determine predictors of HPV vaccine acceptability among college men through the qualitative approach of focus groups and to develop an intervention to increase intent to seek vaccination in the target population

The study took place in two phases. During Phase I, six focus groups were conducted with 50 participants. In Phase II using a randomized controlled trial a HBM based intervention was compared with a traditional knowledge based intervention in 90 college men. In Phase I lack of perceived susceptibility, perceived severity of HPV and barriers towards taking the HPV vaccine were major themes identified from the focus groups. Participants for this phase and phase II were primarily single, heterosexual, about 20 years old, Caucasian males attending the University of Cincinnati. Phase II analysis was done for pretest/posttest and for pretest/posttest/follow-up. This was done due to a 17.8% retention rate at follow-up.

Repeated measures of ANOVA indicated significant positive changes in the intervention group.

Scores for knowledge and HBM constructs, perceived severity, perceived susceptibility, perceived benefits, perceived barriers, self-efficacy, and cues to action improved over time while no significant findings were made for the control group. Regression analysis was done for change scores at pretest/posttest, follow-up/pretest, and follow-up/posttest. No significant model was found for follow- up/posttest. Results from the pretest/posttest regression analysis indicated self-efficacy for taking the vaccine (p=0.000), perceived barriers (p=0.007), and perceived severity (p=0.004) were significant

positive predictors of vaccine acceptability. The model had an adjusted R2 of 0.351which indicated that these three predictors accounted for 35.1% variance. HBM is a robust model to predict HPV vaccine acceptability in college men. Results from follow-up/pretest found perceived benefits (p=.004) held a significant positive relationship towards intent to vaccinate. The model had an adjusted R2 of 0.453, which indicated this predictor accounted for 45.3% variance regarding whether participants would take the vaccine.

Overall, the intervention proved to be effective in creating positive change towards HPV vaccine acceptability. Some limitations had occurred, such as a low retention rate at follow-up, and differences between groups at baseline. Despite these issues, change in the intervention still occurred. This study indicates that more theory-based interventions are needed to increase HPV vaccination in college men.

Acknowledgements

This dissertation could not have been possible without the help of many faculty, family members, and close friends. First of all, I would like to thank my dissertation advisor, Dr. Manoj

Sharma, for his help in securing a grant with Merck Pharmaceutical and his guidance in my career development as a researcher. I would also like to thank my academic advisor, Dr. Liliana

Guyler, for her constant support, encouragement, and academic advice in this process. I would also like to thank my committee members, Dr. Wilson and Dr. Lee for their help in this endeavor.

Most of all, I would like to thank my parents, especially my mother, for all the love, support and encouragement to get me where I am today. They stood by all the decisions leading up to the culmination of my degree, and pushed me when I thought I could not go any further. For all that they have taught me and done for me, I will never be able to show them the amount of gratitude I have for them. I would also like to thank my sister, Shruti Mehta, for making light of situations and reminding me to take it easy when things got stressful. I would also like to thank Chirag

Mehta, Parag Mehta and Nyesia Mehta, for their support, laughter, and reminding me that there is light at the end of the tunnel.

Outside of my family, I could not have made it without the support of my close friends. They have been there from the beginning and have helped me get through the thick and thin of things.

It would not have been easy without them. Finally, I would like to thank, A.J.A., for his support, encouragement, and most of all, his reminder to have fun through it all. He, along with the rest, kept me sane in moments of insanity, and for that I am ever so grateful.

Table of Contents List of Tables ……………………………………………………………………………….i List of Figures……………………………………………………………………………….v Chapter One: The Purpose…………………………………………………………………..1 Statement of the Problem…………………………………...... 13 Research Questions and Hypothesis………………………………………………...14 Operational Definitions……………………………………………………………...23 Delimitations………………………………………………………………………...24 Limitations…………………………………………………………………………...25 Assumptions………………………………………………………………………....25 Summary……………………………………………………………………………..25 Chapter Two: Review of Literature………………………………………………………....26 Human Papilloma Virus…………………………………………………………...... 26 Prevalence and Incidence……………………………………..……………………..27 Transmission and Duration ……………………………………………………….....28 HPV in Men ………………………………...……………………………………….30 Genital Warts….……………………………………………………………………...31 Cervical Intraepithelial Neoplasia……………………………………………………32 Cervical Cancer………………………………………………………………………33 Vaccines ……………………………….………………………………………….....37 HPV Vaccine…………………….…………………………………………………...41 HPV Vaccines in Men………………………………………………………………..44 Health Belief Model .………………………………………………………………...47 Applications of the Health Belief Model……………………………………………..49 Quantitative Designs………………………………………………………………….53 Quantitative Designs and the Health Belief Model…………………………………..54

Qualitative Designs………………………………………………………………...…57 Qualitative Designs and the Health Belief Model…………………………………….59 Summary………………………………………………………………………………61 Chapter Three: Methods………………………………………………………………………63 Design…………………………………………………………………………………63 Population and Sample……………………………………………………….…...... 69 Setting…………………………………………………………………………..…….71 Instrumentation…………………………………………………………………….....75 Confirmatory Factor Analysis…………………………………………………….….78 Researcher’s Role………………………………………………………………….....80 Data Collection…………………………………………………………………...... 80 Data Analysis………………………………………………………………………....82 Summary……………………………………………………………………………83

Chapter Four: Results………………………………………………………………………...84

Phase 1………………………………………………………………………………..84

Phase II……………………………………………………………………………….89

Assumption Testing…………………………………………………………………..95

Results for Repeated Measures ANOVA…………………………………………… 98 Regression Analysis…………………………………………………………………118 Summary……………………………………………………………………………..120 Chapter 5: Conclusions……………………………………………………………………..122 Phase I……………………………………………………………………………….122 Phase II………………………………………………………………………………124 Limitations…………………………………………………………………………...129 Implications for Practice……………………………………………………………..131 Future Recommendations……………………………………………………………...132 Summary……………………………………………………………………………….134

References…………………………………………………………………………………….135 Appendices Appendix A. List of panel of experts…………………………………………………..140 Appendix B. Survey………………………………………………………………….....141 Appendix C. Control Group Intervention…………………………………………...... 145 Appendix D. Experimental Group Intervention………………………………………..154 Appendix E. Informed Consent………………………………………………………...161

List of Tables Table 3.1 Reliability Coefficients (Cronbach’s alpha) for Perceived Susceptibility, Perceived Severity, Perceived Benefits, Perceived Barriers, Cues to Action, Self Efficacy, and Knowledge…………………………………………………………………………………….75 Table 3.2 Test-retest Reliability Coefficients for Perceived Susceptibility, Perceived Severity, Perceived Benefits, Perceived Barriers, Cues to Action, Self Efficacy, and Knowledge……..76

Table 4.1 A comparison of demographic and study variables between participants in the control (n=45) and experimental (n=45) groups at pre-test using an omnibus multivariate test………………………90

Table 4.2 A comparison of demographic and study variables between participants in the control (n=45) and experimental (n=45) groups at pre-test using separate univariate tests…………………………...90

Table 4.3 A comparison of demographic and study variables between participants in the control (n=45) and experimental (n=45) groups at pre-test using an omnibus multivariate test………………………91

Table 4.4 Distribution of Means and Standard Deviations for Health Belief Model Constructs, Knowledge, and Intent to Vaccinate for Control and Experimental Groups at Pre-test, Post-test, and Follow-up………………………………………………………………………………………………93

Table 4.5 A summary of evaluating the normality using the Kolmogrov-Smirnov (K-S) Test……….95

Table 4.6 A summary of evaluating homoscedascity using Levene’s Test……………………………95

Table 4.7 A summary of evaluating sphericity using Mauchly’s Test………………………………...96

Table 4.8 Summary of Repeated Measures Analysis of Variance for Perceived Susceptibility Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow- up...…………………………………………………………………………………………….97

Table 4.9 Summary of Repeated Measures Analysis of Variance for Perceived Susceptibility Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post- Test……………………………………………………………………………………………..98

Table 4.10 Summary of Repeated Measures Analysis of Variance for Perceived Severity Between Experimental (n=10)and Control Groups(n=6) and Between Pre-Test, Post-Test, and Follow-up …………………………………………………………………………………….100

Table 4.11 Summary of Repeated Measures Analysis of Variance for Perceived Severity Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post- Test……………………………………………………………………………………………100

Table 4.12 Summary of Friedman Test Results for Perceived Severity……………………...101

Table 4.13 Summary of Repeated Measures Analysis of Variance for Perceived Benefits Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow- up…………………………………………………………………………………………….102

Table 4.14 Summary of Friedman’s Test for Perceived Benefits at Pretest, Posttest, and Follow- up Test ………………………………………………………………………………………102

Table 4.15 Summary of Repeated Measures Analysis of Variance for Perceived Benefits Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post- Test…………………………………………………………………………………………..103

Table 4.16 Friedman’s Test for Perceived Benefits at Pretest and Posttest………………...104

Table 4.17 Summary of Repeated Measures Analysis of Variance for Perceived Barriers Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test, Post-Test, and Follow- up……………………………………………………………………………………………105

Table 4.18 Summary of Repeated Measures Analysis of Variance for Perceived Barriers Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test ………………………………………………………………………………………….…...106

Table 4.19 Summary of Repeated Measures Analysis of Variance for Self-Efficacy Between Experimental (n=10)and Control Groups(n=6) and Between Pre-Test, Post-Test, and Follow- up...... 107 Table 4.20 Summary of Repeated Measures Analysis of Variance for Self-Efficacy Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test……108

Table 4.21 Summary of Repeated Measures Analysis of Variance for Cues to Action Between Experimental (n=10)and Control Groups(n=6) and Between Pre-Test, Post-Test, and Follow- up…………………………………………………………………………………………...109

Table 4.22 Summary of Repeated Measures Analysis of Variance for Cues to Action Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test……111

Table 4.23 Summary of Repeated Measures Analysis of Variance for Knowledge Between Experimental (n=10), Control Groups(n=6) at Pre-Test, Post-Test and Follow-up………..112

Table 4.24 A Summary of Friedman’s Test for Knowledge……………………………….112

Table 4.25 Summary of Repeated Measures Analysis of Variance for Knowledge Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test……114

Table 4.26 Summary of Friedman’s Test for Knowledge at pretest and posttest………….114

Table 4.27 Summary of Repeated Measures Analysis of Variance for Intent to Vaccinate Between Experimental and Control Groupsand Between Pre-Test, Post-Test, and Follow- up…………………………………………………………………………………………...115

Table 4.28 Summary of Repeated Measures Analysis of Variance for Intent to Vaccinate Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test …………………………………………………………………………………………..….116

Table 4.29 Distribution of Means and Standard Deviations for Change in Health Belief Model Constructs, Knowledge, and Intent to Vaccinate……………………………………………………………………………………117

Table 4.30 Parameter Estimates from the Final Regression Model for change in Intent to Vaccinate at Pre-test, and follow-up test using Follow-up and Pre-test change scores in Health Belief model (HBM) constructs (R2 = 0.453)…………………………………………….118

Table 4.31 Parameter Estimates from the Final Regression Model for change in Intent to Vaccinate at Pre-test and posttest using change scores in Health Belief Model (HBM) predictors (R2 = 0.593)……………………………………………………………………………….119

iii

List of Figures

Figure 3.1 Flow Diagram of Phase I Research……………………………………………67 Figure 3.2 Flow Diagram of Phase II Research…………………………………………..68 Figure 3.3 Logic Model of the Health Belief Model Based Intervention………………...69 Figure 3.4 Confirmatory Factor Analysis- Final Model………………………………….81

Supported in part by a research grant from Investigator-Initiated Studies Program of Merck

Sharp & Dohme Corp.. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck Sharp &Dohme Corp

Purpose 1

Chapter One

The Purpose

Humanpapilloma virus (HPV) is a common sexually transmitted disease/infection

(STD/STI). The virus attacks the skin and mucous membranes of humans and spreads from human to human due to sexual contact (Centers for Disease Control and Prevention [CDC],

2009). Due to this form of transmission HPV affects the vulva, vagina, cervix, scrotum, rectum, anal, and penis areas. There are hundreds of different strains, but only forty are known to cause disease through sexual contact. Of these forty, there are four strains in particular that are of prime interest. These are HPV 6, 11, 16 and 18, which can cause genital warts, intraepithelial neoplasia or lead to cervical cancer. Due to these outcomes, these strains are differentiated into low and high risk categories. Genital warts are primarily due to HPV 6, 11 and HPV, 16, 18 are associated with cervical cancer. The infection often times goes unnoticed as symptoms are not always apparent (CDC, 2009). At the same time, HPV can be dormant for a long time before it appears. Therefore, an HPV infection can be from current sexual involvement or from months or years ago.

According to the Centers for Disease Control and Prevention (2009), approximately 50% of men and women that are sexually active will have contracted an HPV infection in their lifetime. Annually, 6.2 million people are newly diagnosed with HPV and 20 million currently are diagnosed. It has been shown that 40-50% of cases are found in women between 14 to 24 years old. Within sexually active women, prevalence of HPV declined past the age of 25. In addition, multiple strand infections of HPV had a 5- 33% occurrence in women. It has been estimated that eighty percent of women will have had an HPV infection by the time they reach

50 years old.

Purpose 2

Overall, limited data is available regarding incidence and prevalence rates of HPV (Velicer et al.,

2009). Its asymptomatic nature makes it hard to detect and infections can be cleared up spontaneously. At the same time, HPV infections are not periodically reported to health departments. Only cervical cancer cases are reported, which allows individuals to obtain some information regarding prevalence of HPV. Limited information regarding the duration of HPV is available. Studies have shown traces of the infection to be obsolete within a year or two (Trottier et al., 2008). Approximately 70% is cleared in a year and about 90% is cleared in two. The average extent of HPV is roughly eight months. It was also found that high risk HPV is more persistent than low risk. This is attributed to low risk strains capable of quicker spontaneous clearance than high risk strains. In addition, HPV 16 has been found to be more persistent than other strains but clears out within two years.

HPV in Men

A majority of concerns dealing with HPV are related to women, due to its association with cervical cancer. Additionally, HPV holds similar frequency levels in males. About 50% of men that are sexually active acquire HPV in their lifetime (Dunne, Nielson, Stone, Markowitz, &

Giuliano, 2006). Data indicates that gay and bisexual men are more likely to be diagnosed with

HPV. These groups along with those that have HIV/AIDS were found to be 17 times more likely to develop anal cancer. The latter group tends to obtain severe cases of genital warts than other men.

Purpose 3 to test for HPV. There are possibilities of developing anal PAP tests for men, to test for abnormal cell growth in the anus. The abnormal growth can lead to anal cancer through high risk HPV strains 16, 18. Low risk HPV strains can cause genital warts. Of all the strains of HPV, 16 was found to be common in men as well. It was also found that 51.1% of men tended to carry multiple strains of HPV. In regards to duration, it was found that men had a shorter duration of infection than women.

Prevalence of genital warts was found to be in one percent of sexually active men (Dunne et al., 2006). Penile cancer and anal cancer prevalence in men is fairly uncommon.

Approximately 1 in 100,000 men are affected by it. Severe effects of HPV are not seen in men with healthy immune systems, since spontaneous clearance occurs with this virus. Due to these low risks, testing for men is non-existent. Risk factors for HPV were similar to those found in women. A few studies have looked at the relationship between circumcision and risk for HPV infection. Results indicated a significantly lowered risk for HPV infection in men that were circumcised. It was also found that high risk HPV was less likely in these men.

Vaccines

Vaccines have become wide spread in health care and known to be a valuable tool in controlling infectious disease (Stern & Markel, 2005). While vaccine campaigns have been around since the 1950’s, their existence dates back to ancient times in India and China.

Variolation, infecting healthy individuals with the strain through skin or nose contact, was used in those times to decrease severity of smallpox. This process reduced mortality from Small pox to one or two percent. This practice was then seen in Great Britain in 1718 through Lady Mary

Montague. She used variolation against smallpox with her six year old son, and shortly gained

Purpose 4 popularity as a strategy in dealing with the 1721 smallpox epidemic. In the same century, it was found that milkmaids who had gone through localized pockmarks from cowpox very rarely came down with smallpox.

Edward Jenner used this information and inoculated an eight year old James Phipps with infected hands from cowpox (Riedel, 2005; Stern & Markel, 2005). James was then inoculated with smallpox six weeks later and was not taken ill with the disease. This has been noted to be the first documentation of vaccinations. Due to this process, an eradication of smallpox eventually occurred in 1979.

It was Pasteur’s expansion of inoculation to other agents that provides us with the current day definition of a vaccine (Riedel, 2005; Stern & Markel, 2005). For instance, vaccines for anthrax and cholera were also developed. By definition, a vaccine is a “suspension of live

(usually attenuated) or inactivated microorganisms (e.g., bacteria or viruses) or fractions thereof administered to induce immunity and prevent infectious disease or its sequelae” (Stern &

Markel, 2005). While common man uses vaccine and immunization interchangeably, differences between the two exist. Immunization is when an individual is injected with an immunologic agent for the development of immunity against the specified bacteria/virus. Various forms of vaccines are available: killed-virus, whole-cell, bacterial, or live-attenuated.

A second phase of vaccine evolution was seen during the world war II era (1930-1950)

(Riedel, 2005; Stern & Markel, 2005). This was spun off by a demonstration conducted by Good

Pasture in 1931 on the viral growth of embryonated eggs from hens, which led to Theiler’s yellow fever vaccine development for tropical regions. Application was done through minced chick tissue. Hens’ eggs that were embryonated were later used to grow typhus Rickettsiae for a

Purpose 5 mass rapid production of typhus vaccinations at the Squibb Virus Lab. The same lab also produced Wendell Stanley’s flu vaccine through purification from continuous flow centrifugation. This method established a paradigm for viral vaccines.

Advancements in influenza vaccines were taken at the Walter Reed Army Institute where antigenic specificity of the virus, drift and shift, were established (Lombard, Pastoret, & Moulin,

2007). Approximately 40 million doses were administered in Fall of 1957, after learning of the flu pandemic in Hong Kong. While predictions of the spread of the flu were to occur with the commencement of schools, it did not strike till the Thanksgiving holidays. Due to widespread administration of the flu vaccine, a rapid peak and decline with the viral strain was seen.

Continuation of vaccine development and testing through clinical trials occurred between

1950 and 1985 (Hilleman 2000; Riedel, 2005; Stern & Markel, 2005). It was not till post-1985 that a rapid decrease in the pioneering of new vaccines took place. Two of the main divisions in modern day vaccinations are with bacterial and viral types. Bacteria related infections were initially treated with antibiotics or sulfonamides but did not prevent death. Dr. Robert Austrian made persistent efforts towards the development of pneumoccal vaccines in the early 1970’s, which led to the 14 and 23 valent vaccines. Meningococcus vaccines (monovalent, bivalent, and quadrivalent groups A, C, W135, and Y) stemmed from military request after the resurgence of meningitis in recruits.

Individuals viewed this process with much pride and with time, vaccines became an integral part of public health (Hilleman, 2000; Riedel, 2005; Stern & Markel, 2005).

Globalization of vaccines occurred with the establishment of the World Health Organization

(WHO) in 1974 and the United Nations Children’s Fund (UNICEF). The Expanded Programme

Purpose 6 on Immunization (EPI) was formed by WHO to increase vaccinations in developing countries.

With great effort, eradication of some diseases has occurred. While this is positive news, the negative impact is seen with a growing population taking vaccinations for granted, loss of interest among public funding agencies, and the controversy of causing autism. Skepticism regarding vaccinations comes from scenarios such as death due to the contamination of a vaccine during production. For instance in 1955, 200 children contracted Polio from the vaccine which had an active wild-type polio virus.

HPV Vaccine

Significance has been placed on HPV due to its pre-requisite nature for cervical cancer.

As a method for prevention towards this, vaccination was developed and released for usage in

2006 (Saslow et al., 2007). The vaccine does not contain DNA or a live virus. Gardasil was the first vaccine, initially approved for girls and women from the ages of nine to 25. It serves as prevention for HPV 6, 11, 16 and 18 only, meaning it is still possibly to be infected with other versions. Although, these are the prime four leading to genital warts and more importantly, cervical cancer. Three shots over a period of six months are given. Women over the age of 25 can still be vaccinated but approval is done on individual basis. This is due to high prevalence of

HPV among 14 to 24 year old versus the older age groups.

Involvement in sexual activity puts an individual at risk for attaining some form of an

HPV infection. If an individual has had an infection, the vaccine is no longer effective (Gillison,

Purpose 7 the message of prevention towards HPV. To combat the topic, emphasis towards cervical cancer is given. Individuals are reminded that HPV infections can still occur.

In 2009, the Food and Drug Administration (FDA) approved Gardasil for boys and men nine to 26 years old (Grever, 2009). Clinical trials have shown the vaccine to be 90% effective towards genital lesions in this gender. External lesions were reduced among homosexual men in the trial. While anal cancer is not common in males, it has been on the rise. The vaccine would help cease the increase; an advantage noted for women and homosexual men (Gillison et al.,

2008). Vaccination would alleviate infections in men, which would in turn help with the reduction of infections in females. In addition, vaccinating both genders removes the stigma involved with taking the vaccine or being diagnosed with the disease. There have only been two randomized controlled studies for this matter and more research is needed to comprehend the role of the vaccine in this gender.

On the same day, the FDA also approved a second vaccine, Cervarix, for only girls and women. Unlike Gardasil, Cervarix offers prevention from HPV strains 16 and 18. There are three shots given. The first one is given at the first month and the following two are given at the sixth month. A primary clinical study showed a 93% effectiveness rate for individuals that were HPV naïve. For those that were positive for an HPV infection, the effectiveness rate was 53% in preventing dysplasia. Duration of prevention from the vaccine is currently known to last for 6.4 years. Similar to Gardasil, more information is needed with regard to duration of effectiveness.

HPV Vaccines in Men

Currently, Gardasil is an approved vaccine that helps guard against 90% of genital warts in males (Gever, 2009). Gardasil is given in three shots over the course of three months. Males

Purpose 8 between the ages of nine and 26 are approved to take the vaccination. It has been noted that men who have not had sex and young men who have sex with men benefit the most from the vaccine.

Men who have had sex with a female do not benefit has much, as the likelihood of an HPV infection is higher.

In a recent review, 74%-78% acceptability of the vaccine among college males was found

(Liddon, Hood, Wynn, & Markowitz, 2010). Several studies within the review found a relationship between vaccine acceptability and males that believed sexual partners, parents or physicians would encourage taking the vaccine, having a firm belief in the general importance of the vaccine, knowledge and awareness of HPV, perception of being at high risk, and belief in vaccinations. Very limited literature exists on the role of health belief model constructs with men but some is available with regards to women (Brewer & Fazekas, 2007). Adult women and adolescents indicated high likelihood of HPV exposure and cervical cancer, which was associated to higher acceptability of the vaccine (Mays et al., 2000). Perceived severity was only found with regards to cervical cancer, but no relationship with acceptability of the vaccine. No significant values were found for perceived effectiveness. Due to limited literature, correlates of vaccine acceptability among a high risk group need to be examined for future preventative purposes.

Health Belief Model

Development of the Health Belief Model occurred in the early 1950’s by social psychologists working with the U.S. Public Health Service. Rationale behind the development was “the widespread failure of people to accept disease preventives or screening tests for the early detection of asymptomatic disease” (Rosenstock, 1990; Rosenstock, 2000). While the

Purpose 9

Health Belief Model stems from a mixture of psychological and behavioral theories, it stands on two basic principles: the needs to avoid getting ill/get better if ill and a particular behavior will prevent an illness or aid in getting better (i.e likelihood of a behavior to achieve a desired outcome). It has also been stated that receiving some form of a health behavior recommendation that is at an acceptable cost is another factor leading the individual in adopting healthy behaviors.

This model is not a theory but serves as a powerful tool in understand and influencing health behaviors (Rosenstock & Stretcher, 1988). While being a model, it is known to be part of the value expectancy theories. According to this classification, adopting the given behavior(s) will have some value.

Perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action and self-efficacy are constructs that comprise the Health Belief Model (Becker, 1978;

Sharma & Romas, 2008). Perceived susceptibility refers to an individual’s belief that they are at risk for obtaining a health issue. Perceived severity is the belief in the potential serious consequences of the health issue. Perceived benefits are the beliefs in the advantages of adopting suggested prevention methods for the given health issue. Perceived barriers are things such as costs and side effects that would prevent individuals from adopting a behavior. Cues to action are factors that will motivate individuals to take on the given health behavior and self-efficacy is the confidence that a person has in his or her ability to carry out the behavior.

The Health Belief Model is particularly important in the program planning stages of health education, as they account for the beliefs seen in the constructs of the model (Becker,

1978; Sharma & Romas, 2008). Taking these factors into account allow for researchers/program planners to strengthen educational intervention sessions. Outside of strengthening the program, usage of the constructs allow for addressing the needs of community or the target group. This

Purpose 10 then leads to a tailored program yielding a higher level of effectiveness. Additionally, the Health

Belief Model accounts for the role of demographic factors in perceived barriers, perceived benefits, and perceived severity, which other theories do not mention. Of most importance in the utility of this model, is the concept of self-efficacy. While this construct was not initially a construct in the model, it has been fathered in overtime. Self-efficacy, in addition to the other health beliefs, increases confidence levels in the specified health behavior while serving as an explanatory variable.

Applications of the Health Belief Model

Significance in preventative health behavior was seen in the utility of the Health Belief

Model (Becker et al., 1977; Janz & Becker, 1984). Using the Health Belief Model in learning about immunizations is efficient due to the specificity in threat and a simple action response.

Being that the Health Belief Model is considered to be a value expectancy theory, in the realms of vaccines, taking the vaccine as a preventative method is hypothetically placed at a high value.

Thus, individuals would be more likely to enact the behavior. Initially, the Health Belief Model was used in swine flu vaccinations thrice, and once with influenza. Aho in 1979 examined Swine

Flu vaccination intention along with the constructs of the Health Belief Model in 122 elderly individuals. Results indicated susceptibility, efficacy, and safety were significant predictors in taking the vaccine. Additionally, severity was not properly assessed due to its interpretation.

In another Swine Flu study, random digit dialing was done prior to the launch of the vaccine campaign to determine inoculation –seeking behavior in adults (18 years and older)

(Cummings, Jette, Brock, 1979). Follow-up surveys were done a month and two months post- campaign launch. Results from the study showed major Health Belief Model constructs to be

Purpose 11 statistically significant in determining intent to vaccinate. The influence of the model shown in the intent to vaccinate was important in carrying out the action of vaccination.

Rundall and Wheeler (1979) also examined the Health Belief Model in Swine Flu vaccinations with the elderly n New York. Significant positive correlations were seen among constructs of the model and vaccination status. The only construct not significant was severity, which was similar to the findings of Aho. Studies with Swine Flu indicated the importance of the

Health Belief Model in researchers’ understanding of an individuals’ likelihood of undergoing preventive care behaviors. Cummings et al’s results indicated significant relationships between the constructs and intent to vaccinate. Social influences and previous experience with flu shots were also found to be significant in determining an individual’s self-efficacy towards vaccinating against swine flu.

Larson, Olsen, Cole et al. (1979) examined the Health Belief Model with the influenza vaccine in high risk individuals. A survey was handed post-flu epidemic, which looked at vaccination status and constructs of the model. Significant positive correlations were seen between being vaccinated and the model. Additionally, the researchers sent a reminder postcard about the vaccine but no significant differences between participants’ health beliefs and vaccination were seen. It was concluded that the reminder cards served as a cue to action.

Chor et al. (2009) measured intent to vaccinate against the pre-pandemic flu among healthcare workers in Hong Kong. Two surveys were distributed; one between January and

March 2009 and the second during May 2009. Perceived barriers and susceptibility were significant constructs associated with the intent to vaccinate. The overall intent to vaccinate was very low and insignificant, which was surprising due to the past history of SARS in the area and

Purpose 12 the nature of the individuals’ occupation. The Health Belief Model served to be important due to the findings and allowing researchers to build programs targeting these beliefs in order to increase the intent to vaccinate.

Chen, Fox, Cantrell, Stockdale, and Kagawa-Singer (2007) examined racial/ethnic influences on flu vaccinations through the Health Belief Model. Perceived susceptibility and perceived severity were of the main interest, and perceived barriers were further examined only if participants had reported not getting the vaccination. Results indicated African American and

Latinos significantly were less likely to get vaccinated than Whites and Asians, but Filipino

Americans were also significantly less likely to take the vaccine. Perceived susceptibility was the most significant predictor in vaccination. Those that did not obtain the vaccine reported a significantly low perceived severity which resulted in their decision. Barriers in not getting vaccinated were household income along with low perceived severity. African Americans noted serious side effects and lack of trust among health care workers as barriers, while Latinos reported lack of insurance/transportation/clinics. Findings from the study were important in recognizing racial/ethnic barriers and facilitators in vaccinating against the flu. Once again the importance of the Health Belief Model was signified through this study.

Butraporn and colleagues (2004) looked at the Health Belief Model in the potential use of a vaccine for Shigellosis in Thailand. It is important to note that a vaccine for Shigellosis had not occurred. Interviews were done to determine interest in the vaccine; questions were based of the constructs of the model. Results from the respondents indicated cost as a burden towards to taking the vaccine outweighed the benefits. Recommendations on taking the vaccine from health clinic staff and volunteers were deemed as significant influencers (cues to action) in intent to vaccinate. Perceived susceptibility did not show up but severity was seen as a significant theme

Purpose 13 in the interviews. This is unlike the previous studies, in which severity was not of significant concern. While the study was a qualitative design, it offered information pertinent for government officials and health policy makers in their understanding of possible vaccine acceptance if available, and ways to implement vaccine programs.

The Health Belief Model has been used in predicting HPV vaccine acceptability in both women and men. A review by Brewer and Fazekas (2007) examined constructs of the model in

HPV vaccine acceptability among women. For perceived susceptibility, 21%-46% of adolescent and young adult women believed that had a chance of getting HPV, while adult women had a higher perception of themselves being diagnosed with cervical cancer. A higher percentage of susceptibility led to a strong positive correlation in vaccine acceptability. Perceived severity had no correlation towards vaccine acceptability despite the belief in cervical cancer holding severe consequences. Interestingly, perceived severity was a strong factor in parents’ decision to vaccinate their daughters. With regard to perceived barriers, a few sub-factors emerged in the decision to vaccinate: costs, promotion of sexual activity among adolescents, vaccine safety/side effects of taking the vaccine. Finally, recommendations from physicians and school requirements were influential in intent to vaccinate.

Statement of the Problem

Purpose 14 with parents and physicians regarding HPV vaccination with girls, and a few regarding women’s awareness and acceptability (Brewer & Fazekas, 2007; Gillison et al., 2008; Saslow et al., 2007;

Mays et al., 2000). Results indicated increasing awareness of HPV, informing costs and benefits associated with the vaccine, and perceived susceptibility. Based on this information, it is crucial to obtain a further understanding of knowledge, awareness, and predictors related to HPV and its vaccination in men. Information obtained can be utilized in developing an intervention to increase intentions of taking the HPV vaccine. Refining results will lead to a standardization of an intervention that can be implemented across college campuses.

Research questions:

Phase 1

Explored through focus groups were the following questions:

1. Do you see HPV as a threat to you? If so, how?

2. Do you believe HPV can lead to serious illnesses?

3. If not, do you believe HPV can have any negative consequences on your health? In your personal life? In your professional life?

4. How likely do you think you can get an HPV related infection?

5. Do you believe passing HPV to a sexual partner can cause harm to their health? How would that impact you as an individual? Your relationship? Your future relationships?

6. What are some barriers you might face in taking the vaccine? Costs? Not sure of the availability? Made fun of by friends?

Purpose 15

Phase II

1. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in the intent to take the HPV vaccine between experimental

and comparison groups?

2. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in actually taking the HPV vaccine between experimental and

comparison groups?

3. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in Health Belief Model constructs between experimental and

comparison groups?

4. If there are significant changes over time, what is the relationship between changes in

significant Health Belief Model constructs and vaccine acceptability among college men?

5. If there are significant changes over time, what is the ability of the change in significant

Health Belief Model constructs to account for variance in change in vaccine acceptability

among college men?

Sub-research Questions

1. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in perceived susceptibility in the intent to take the HPV

vaccine between experimental and comparison groups?

2. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in perceived severity in the intent to take the HPV vaccine

between experimental and comparison groups?

Purpose 16

3. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in perceived benefits in the intent to take the HPV vaccine

between experimental and comparison groups?

4. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in perceived barriers in the intent to take the HPV vaccine

between experimental and comparison groups?

5. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in cues to action in the intent to take the HPV vaccine between

experimental and comparison groups?

6. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in self-efficacy in the intent to take the HPV vaccine between

experimental and comparison groups?

7. Is there a statistically significant difference in change (from pre and post intervention,

and one month follow up) in knowledge in the intent to take the HPV vaccine between

experimental and comparison groups?

8. Is there a statistically significant difference in change (from pre, and post intervention) in

perceived susceptibility in actually taking the HPV vaccine between experimental and

comparison groups?

9. Is there a statistically significant difference in change (from pre and post intervention) in

perceived severity in actually taking the HPV vaccine between experimental and

comparison groups?

Purpose 17

10. Is there a statistically significant difference in change (from pre and post intervention) in

perceived benefits in actually taking the HPV vaccine between experimental and

comparison groups?

11. Is there a statistically significant difference in change (from pre and post intervention) in

perceived barriers in actually taking the HPV vaccine between experimental and

comparison groups?

12. Is there a statistically significant difference in change (from pre and post intervention) in

cues to action in actually taking the HPV vaccine between experimental and comparison

groups?

13. Is there a statistically significant difference in change (from pre and post intervention) in

self-efficacy in actually taking the HPV vaccine between experimental and comparison

groups?

14. Is there a statistically significant difference in change (from pre and post intervention) in

knowledge in actually taking the HPV vaccine between experimental and comparison

groups?

Hypotheses:

1. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow up) in perceived susceptibility in the intent to take the

HPV vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

susceptibility with intent to vaccinate than the comparison group.

Purpose 18

HA: The experimental group will have a statistically significant lower level of perceived

susceptibility in the intent to take the HPV vaccine than the comparison group.

2. H0: There will be no statistically significant difference in change (from pre and post

intervention) in perceived susceptibility in the intent to take the HPV vaccine between

experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

susceptibility with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of perceived

susceptibility in the intent to take the HPV vaccine than the comparison group.

3. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow-up) in perceived severity in the intent to take the

HPV vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

severity with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of perceived

severity in the intent to take the HPV vaccine than the comparison group.

4. H0: There will be no statistically significant difference in change (from pre and post

intervention) in perceived severity in the intent to take the HPV vaccine between

experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

severity with intent to vaccinate than the comparison group.

Purpose 19

HA: The experimental group will have a statistically significant lower level of perceived

severity in the intent to take the HPV vaccine than the comparison group.

5. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow-up) in perceived benefits in the intent to take the

HPV vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

benefits with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of perceived

benefits in the intent to take the HPV vaccine than the comparison group.

6. H0: There will be no statistically significant difference in change (from pre and post

intervention) in perceived benefits in the intent to take the HPV vaccine between

experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

benefits with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of perceived

benefits in the intent to take the HPV vaccine than the comparison group.

7. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow-up) in perceived barriers in the intent to take the HPV

vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

barriers with intent to vaccinate than the comparison group.

Purpose 20

HA: The experimental group will have a statistically significant lower level of perceived

barriers in the intent to take the HPV vaccine than the comparison group.

8. H0: There will be no statistically significant difference in change (from pre and post

intervention) in perceived barriers in the intent to take the HPV vaccine between

experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of perceived

barriers with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of perceived

barriers in the intent to take the HPV vaccine than the comparison group.

9. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow-up) in self-efficacy in the intent to take the HPV

vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of self-

efficacy with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of self-

efficacy in the intent to take the HPV vaccine than the comparison group.

10. H0: There will be no statistically significant difference in change (from pre and post

intervention) in self-efficacy in the intent to take the HPV vaccine between experimental

and comparison groups

H1: The experimental group will have a statistically significant higher level of self-

efficacy with intent to vaccinate than the comparison group.

Purpose 21

HA: The experimental group will have a statistically significant lower level of self-

efficacy in the intent to take the HPV vaccine than the comparison group.

11. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow-up) in cues to action in the intent to take the HPV

vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of cues to

action with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of cues to

action in the intent to take the HPV vaccine than the comparison group.

12. H0: There will be no statistically significant difference in change (from pre and post

intervention) in cues to action in the intent to take the HPV vaccine between experimental

and comparison groups

H1: The experimental group will have a statistically significant higher level of cues to

action with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of cues to

action in the intent to take the HPV vaccine than the comparison group.

13. H0: There will be no statistically significant difference in change (from pre and post

intervention, and one month follow-up) in knowledge in the intent to take the HPV

vaccine between experimental and comparison groups

H1: The experimental group will have a statistically significant higher level of knowledge

with intent to vaccinate than the comparison group.

Purpose 22

HA: The experimental group will have a statistically significant lower level of knowledge

in the intent to take the HPV vaccine than the comparison group.

14. H0: There will be no statistically significant difference in change (from pre and post

intervention) in knowledge in the intent to take the HPV vaccine between experimental

and comparison groups

H1: The experimental group will have a statistically significant higher level of knowledge

with intent to vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of knowledge

in the intent to take the HPV vaccine than the comparison group.

15. H0: There will be no statistically significant difference between experimental and

comparison groups in intent to vaccinate (from pre and post intervention, and one month

follow-up).

H1: The experimental group will have a statistically significant higher level of intent to

vaccinate than the comparison group.

HA: The experimental group will have a statistically significant lower level of intent to

vaccinate than the comparison group.

16. H0: There will be no statistically significant difference between experimental and

comparison groups in intent to vaccinate (from pre and post intervention).

H1: The experimental group will have a statistically significant higher level of intent to

vaccinate than the comparison group.

Purpose 23

HA: The experimental group will have a statistically significant lower level of intent to

vaccinate than the comparison group.

Operational Definitions:

Perceived susceptibility of HPV: A Health Belief Model construct. Measures the belief the person may acquire HPV. Perceived susceptibility was measured in questions 9, 10, and 11, on a five point Likert scale, with the total possible score range from zero (all strongly disagree) to 12

(all strongly agree).

Perceived severity of HPV: A Health Belief Model construct. HPV is a serious disease with negative consequences Questions 12, 13, and 14 measured perceived severity, on a five point

Likert scale, with a total possible range of scores were zero (all strongly disagree) to 12 (all strongly agree).

Perceived barriers of HPV vaccine: A Health Belief Model construct. Costs and side effects that would prevent college males from taking the vaccine. Questions 15, 16, and 17 measured perceived barriers, on a five point Likert scale, with a total possible range of scores were zero

(all strongly disagree) to 12 (all strongly agree).

Cues to action in taking the HPV vaccine: A Health Belief Model construct. Factors that will motivate individuals to take the vaccine Questions 18, 19, 20, 21, and 22 measured cues to action, on a five point Likert scale, with a total possible range of scores were zero (all strongly disagree) to 20 (all strongly agree).

Perceived benefits of HPV vaccine: A Health Belief Model construct. Belief in the advantages of suggested prevention methods namely HPV vaccine Questions 23, 24, and 25 measured

Purpose 24 perceived benefits, on a five point Likert scale, with a total possible range of scores were zero

(all strongly disagree) to 12 (all strongly agree).

Self-efficacy of taking the HPV vaccine: A Health Belief Model construct. The confidence that a person has in her or her ability to take the HPV vaccine Questions 26, 27, and 28 measured self- efficacy, on a five point Likert scale, with a total possible range of scores were zero (all strongly disagree) to 12 (all strongly agree).

College males: between the ages of 18-25 years of age, attending the University of Cincinnati.

Intent to vaccinate: College males willingness to take the vaccine measured in question 29 as a yes, no, or maybe response.

Actual vaccination: College males that have taken the vaccine at the one month follow up.

Delimitations:

Phase I

1. Geographical location: students were recruited from a large Midwestern University in the

United States.

2. Convenience sample was utilized and does not allow for the generalization of results.

3. Focus group method is not representative of the general college male population.

4. Data was collected at the University of Cincinnati.

Phase II

1. A randomized intervention was conducted with a total of 90 participants at the University

of Cincinnati.

Purpose 25

Limitations:

1. The honesty and accuracy of the men responding to focus group questions, and

completing the questionnaire.

2. Possible social bias from participants.

3. Responses were based on self-reports, therefore limiting accuracy.

Assumptions:

An assumption of the study was that participants answered all questions honestly and accurately. It was also assumed that participants read and understood the questionnaire at pre and post intervention, as well as at a one month follow up.

Summary

In this chapter the link between the HPV and its risk in males was established. Reasoning for this study was provided along with the variables being explored. Research questions, hypothesis, operational definitions, delimitations, limitations and assumptions were also stated.

The next chapter investigates HPV and vaccinations in relation to men.

Review of Literature 26

Review of Literature

Chapter Two

The purpose of the study was to determine predictors of HPV vaccine acceptability among college men through the qualitative approach of focus groups and to develop an intervention to increase intent to seek vaccination in the target population. Up to this date, there is a lack of qualitative research on vaccine acceptability among men and theory-based interventions that promote HPV vaccination among men. A few studies have been conducted with parents and physicians regarding HPV vaccination with girls, and a few regarding women’s awareness and acceptability. Results indicated increasing awareness of HPV, informing costs and benefits associated with the vaccine, and perceived susceptibility. Based on this information, it is crucial to obtain a further understanding of knowledge, awareness, and predictors related to

HPV and its vaccination in men. Information obtained can be utilized in developing an intervention to increase intentions of taking the HPV vaccine. Refining results will lead to a standardization of an intervention that can be implemented across college campuses.

Humanpapilloma Virus

Humanpapilloma virus (HPV) is a common sexually transmitted disease/infection. The virus attacks the skin and mucous membranes of humans and spreads from human to human due to sexual contact (Centers for Disease Control and Prevention [CDC], 2009). Due to this form of transmission HPV affects the vulva, vagina, cervix, scrotum, rectum, anal, and penis areas.

Detection is done through PCR analysis, which detects DNA as this virus is part of DNA viruses.

There are hundreds of different strains, but only forty are known to cause disease through sexual contact. Of these forty, there are four strains in particular that are of prime interest. These are

Review of Literature 27

HPV 6, 11, 16 and 18, which can cause genital warts, intraepithelial neoplasia or lead to cervical cancer. Due to these outcomes, these strains are differentiated into low and high risk categories.

Genital warts are primarily due to HPV 6, 11 and HPV, 16, 18 are associated with cervical cancer.

The infection often times goes unnoticed as symptoms are not always apparent (CDC,

2009). At the same time, HPV can be dormant for a long time before it appears. Therefore, an

HPV infection can be from current sexual involvement or from months or years ago. Detection and diagnosis of the disease occurs through the cervical Papanicolaou test (PAP test). This test is only approved for women but is integral in finding precancerous lesions which can lead to cervical cancer. While HPV is common, it gains ground due to its linkage to cervical cancer.

High risk HPV 16, 18 are known to be necessary components causing cervical cancer.

Prevalence and Incidence

50 years old.

In 2008, 11,070 women were diagnosed with cervical cancer and at any one point in time, one percent of sexually active adults had genital warts (Velicer, Zhu, Vuocolo, Liaw, & Saah,

Review of Literature 28

2009). Data on genital warts indicate that 100 per 100,000 individuals will develop genital warts.

In regards to cervical cancer, incidence rates were found to be 8.3 per 100,000 women. Under rare circumstances, HPV can be passed on to the baby during delivery leading to respiratory papillomatosis (RPP). About 04 to 1.1 per 100,000 children are diagnosed with RPP.

Overall, limited data is available regarding incidence and prevalence rates of HPV

(Velicer et al., 2009). Its asymptomatic nature makes it hard to detect and infections can be cleared up spontaneously. At the same time, HPV infections are not periodically reported to health departments. On the other hand, cervical cancer cases are reported, which allows individuals to obtain some information regarding prevalence of HPV.

Transmission and Duration

Genital contact, regardless of penetration or non-penetration, between humans is the primary pathway for transmission of HPV (Steben & Duarte-Franco, 2007). Therefore, risk factors such as the number of sex partners, knowledge of the partner’s history, and age play vital roles. At the same time, a vulnerable immune system is also a known risk factor, as they are readily susceptible to disease. Age is looked at in regards to onset of sexual activity. Engagement in sexual activity at a younger age is typically associated with more sexual partners in their lifetime and there is also a possibility of being more biologically vulnerable to contracting the disease.

Studies have found direct relationships between number of sex partners and likelihood of having an HPV infection (Steben et al., 2007). It was also found that sex with a partner that has not been known for at least eight months also increases susceptibility towards an infection. This is attributed to the lack of knowledge of the partner’s sexual history. A partner that has or has

Review of Literature 29 had multiple sex partners increases risk for contracting HPV. To reduce transmission, monogamy is the best method since studies have found only 20% of women with one lifetime sex partner, have HPV (Burchell, Winer, de Sanjose, & Franco, 2006; Steben et al., 2007).

While transmission is predominantly due to genital to genital contact, oral to genital or hands to genital contact are also possible. The latter two are rare and controversial but possible pathways of spreading HPV. Some research indicated women to men transmission was higher than the opposite. In this process, the primary source of transmission was the penis shaft for men and the cervix and anus for women in heterosexual partners. Findings also suggested female or male hands contacting infected male genitalia as another source of transmission. Therefore, the scrotum and hands were speculated to be a reservoir for the HPV infection.

Efficiency of transmission can be reduced through the use of latex condoms during sexual activity (Burchell et al., 2006; Steben et al., 2007). Evidence for this reduction is limited, but is known to offer some form of protection due to its impermeable barrier for HPV particle sizes. A randomized study looking at use and non-use of condoms in regards to HPV clearance found significant high clearance rates of HPV infection and cervical cell changes in couples that used condoms.

It is also important to note that male and female condoms are available. Female condoms cover a wider surface area and offer more protection than the male condom. If the latter is only used, infection from the scrotum, groin, base of the penis and anus can still be transmitted as they are not covered.

In women, incident infections occurred at a 10.5% rate, while persistent infections occurred about 5% of the time in a period of 30 months. As there are numerous HPV strains,

Review of Literature 30 research suggests that almost all women, 24 to 45 years old, are naïve to at least one and 77% are naïve to two or more. In regards to HPV 16,18 as our prime interest in this gender, a prevalence rate of 4.5% to 6.8% were found for these strains. This is due to its carcinogenic nature. Despite having a negative HPV DNA test, women have been exposed to some form of HPV in their lifetime. It was also found that an infection of Gonorrhea or Chlamydia served as a risk factor for contracting HPV.

Limited information regarding the duration of HPV is available. This is due to its asymptomatic nature and the immune system’s ability to clear the infection. Studies have shown traces of the infection to be obsolete within a year or two (Trottier et al., 2008). Approximately

70% is cleared in a year and about 90% is cleared in two. The average extent of HPV is roughly eight months. It was also found that high risk HPV is more persistent than low risk. This is attributed to low risk strains capable of quicker spontaneous clearance than high risk strains. In addition, HPV 16 has been found to be more persistent than other strains but clears out within two years.

HPV in Men

A majority of concerns dealing with HPV are related to women, due to its association with cervical cancer. At the same time, HPV holds similar frequency levels in males. About 50% of men that are sexually active acquire HPV in their lifetime (Dunne, Nielson, Stone, Markowitz,

& Giuliano, 2006). Data indicates that gay and bisexual men are more likely to be diagnosed with HPV. These groups along with those that have HIV/AIDS were found to be 17 times more likely to develop anal cancer. The latter group tends to obtain severe cases of genital warts than other men.

Review of Literature 31

Transmission of HPV in men is also from genital to genital contact. Some studies have shown transmission of hands to genital contact (Partridge et al., 2007). Data revealed detection of HPV DNA under fingernail tips to be common in men. Unlike women, there are no methods to test for HPV. There are possibilities of developing anal PAP tests for men, to test for abnormal cell growth in the anus. The abnormal growth can lead to anal cancer through high risk HPV strains 16, 18. Low risk HPV strains can cause genital warts. Of all the strains of HPV, 16 was found to be common in men as well. It was also found that 51.1% of men tended to carry multiple strains of HPV. In regards to duration, it was found that men had a shorter duration of infection than women.

Prevalence of genital warts was found to be one percent of sexually active men (Dunne et al., 2006). Penile cancer and anal cancer prevalence in men is fairly uncommon. Approximately

1 in 100,000 men are affected by it. Severe effects of HPV are not seen in men with healthy immune systems, since spontaneous clearance occurs with this virus. Due to these low risks, testing for men is non-existent. Risk factors for HPV were similar to those found in women. A few studies have looked at the relationship between circumcision and risk for HPV infection.

Results indicated a significantly lowered risk for HPV infection in men that were circumcised. It was also found that high risk HPV was less likely in these men.

Genital Warts

Genital warts are due to low risk HPV strains 6 and 11. This is typically seen in men and women between the ages of 17 and 33. Approximately one percent of the population will be infected with genital warts (CDC, 2009). Data from the National Health and Nutrition

Examination Survey (NHANES) 1990-2004 indicated that 5.6% of individuals between 18 and

Review of Literature 32

59 years old, that were sexually active, reported being diagnosed with genital warts (Mays et al.,

2000). It was also found that diagnosis for this increased between the ages of 35 to 44 and then decreased. They are growths found in the anogenital area and are either flesh colored or grey.

The infection can go unnoticed, as they are not always apparent to the naked eye but are highly contagious. Once contracted, the latency period can go from a matter of months to years. Studies have shown that 66% of individuals that were in sexual contact with someone who had genital warts will show growth within three months.

Transmission is from genital contact. In pregnant women, a genital wart infection can be passed to the baby during delivery. This can cause respiratory papillomatosis (RPP) to develop in the child. Prevalence of RPP is rare as only four per 100,000 between the United States and

Europe were found. Vaccination for HPV has shown reduction in cases of genital warts but lacks enough data.

Cervical Intraepithelial Neoplasia

Cervical intraepithelial (CIN), are lesions in the genital area and is also known as cervical dysplasia, which is the abnormal growth of squamous cells located on the surface of the cervix

(Denny, 2009). The growth can be removed through the body’s natural immune response but some have the potential of leading to cervical cancer. This typically occurs from persistent HPV infections from strains 16 or 18 but other strains can also cause dysplasia to occur. Abnormal growth is detected through an initial screening via a Pap smear, and a confirmed diagnosis is done with a colposcopy or a biopsy of the area.

Dysplasia is defined according to stages, which range from one to three. It has the possibility of progressing to the next stage or regressing to a lower stage (Denny, 2009). The first

Review of Literature 33 grade is a low grade lesion and gets cleared up through the immune system. Stage two and three are high grade lesions which can be moderate or severe, respectively. These stages are observed closely as they can lead to Stage three can involve the full thickness of the cervix and can be referred to as carcinoma in situ. Lesions can be found in any stage, and does not necessarily progress in a linear manner. Progression towards cervical cancer take anywhere from three to 40 years, so there is no exact time frame that can be given.

Cases of CIN are normally seen in women between the ages of 25 and 35 (CDC, 2009;

Denny, 2009). Approximately 250,000 to a million women in the United Sates are diagnosed annually. It was also noted that women can be diagnosed with CIN at any age and it is possible for lesions to come back. Although, the recurrence rate was found to be 20%, which is fairly low.

Of those diagnosed with CIN2, 50% will have a regression within two years. Treatment for CIN

2/3 is given once a woman is diagnosed. This is done through removal of the abnormal cells via a LEEP procedure.

Cervical Cancer

Cervical cancer is the second most common cancer found in women (Schiffman, Castle,

Jeronimo, Rodriguez, & Wacholder, 2007). Humanpapilloma virus strains 16, 18, which are high risk strains and known to be carcinogenic, are associated with this is disease. By definition, cervical cancer is due to abnormal cell growth in the cervix. There are two forms, squamous cell carcinomas and adenocarcinomas. They occur on the bottom or the top of the cervix, respectively. Squamous cell carcinomas account for 80 to 90% of cervical cancers, while the latter only occurs about 10 to 20% of the time and strongly linked with the HPV 18 strain.

Regardless of the type of cervical cancer, a carcinogenic HPV strain is necessary for the disease

Review of Literature 34 to occur. Of the two high risk strains, HPV 16 was found in 40% of adenocarcinomas and HPV

18 was found in 30% of squamous cell carcinomas.

In 2002, there were 500,000 incident cases and 275,000 deaths attributed to cervical cancer (Schiffman et al., 2007). It is also known that persistent HPV infections can lead to cervical cancer. Detection is done through a PAP test, which is annually required for women. In the United States, an estimated 500,000 precancerous lesions are annually diagnosed. Higher prevalence and mortality are seen in developing countries due to their poor health systems. A majority of women in developing countries do not go through PAP smears, which test for abnormal cell growth in the cervix. In these areas, squamous cell carcinomas are predominantly diagnosed. On the other hand, data suggest a 15 to 20% increase of adenocarcinomas diagnosis in regions with proper screening programs.

Due to cervical cancer screenings, a reduction in the incidence and mortality of this disease has been noticed in the United States. Despite proper screening programs in the United

States, statistics indicate that half of those diagnosed with cervical cancer never went through a screening process. To add to the issue, another 10% of women diagnosed failed to be screened within five years of diagnosis. In regards to race and ethnicity in the country, Black women have a 60% higher incidence than white women and have the highest mortality rate from this cancer.

Hispanic women near the border of Mexico, non-Hispanic women from Appalachia/rural New

York/Northern New England and Vietnamese women showed higher incidence and mortality rates.

HPV transmission, viral persistence, progression of a clone of persistently infected cells to precancer and invasion must occur for cervical cancer to develop. More information on these

Review of Literature 35 steps are not known, except for HPV transmission. Similar to men, women were also found to have multiple HPV strain infections. In respect to duration, the 10% of HPV infections that last for two years have a stronger link towards precancer. The precancer goes undetected during screenings due to its small particle size in the initial stages. Detection of these particles are typically seen around the ages of 25 to 30. Research indicates a 10 year period from initial sexual contact for the detection of precancer to occur.

Persistence of any HPV infection, increases the risk of cervical cancer. This occurs because spontaneous clearance decreases with a persistent infection. At the same time, there is no concise definition of persistence that is clinically significant, which gives room for controversy in regards to risk. Screening studies have shown that an infection that lasts for more than a year or two is definitely putting the individual at a greater risk of this disease. Issues of latency from the first infection to the second in HPV infections are also being speculated towards posing higher risks for cervical cancer.

Outside of the risks associated with contracting an HPV infection, there are other factors that can double or possibly triple the risks of obtaining cervical cancer. These are smoking, multiparity, and long term use of oral contraceptives and are paired with a HPV infection due to strains 16 or 18 (Brown et al., 2005). Some studies with heterosexual couples have also found that sexual behaviors of the partner were more important predictors of cervical cancer than the woman’s.

With respect to birth control pills, studies have pointed towards contraceptive use and cervical cancer (Moreno et al., 2002). It is important to note that the connection has no relationship to HPV infections. Data indicated pills taken for at least five years had an elevated

Review of Literature 36 risk of more than 50%. Mortality from this cancer was also increased with a minimum of five year usage. Continued use of the pill for 10 or more years caused almost a double increase in cervical cancer risk than those that did not use oral contraceptives. It was also indicated that at 10 years of usage, the cumulative incidence increased from 2.8 to 4.5 per 1,000 women in developed countries and 7.3 to 8.3 per 1,000 women in developing ones. The International

Agency for Research on Cancer (IARC) found usage of the pill prior to the age of 20 attributed to the increased risk of cervical cancer (Moreno et al., 2002). Although a link was established between the two, the exact cause was not determined. Another study found that persistence of a high risk towards cervical cancer continued ten years after a woman ceased usage of oral contraceptives.

Another predictor of cervical cancer was smoking. Women who smoke were twice more likely to be diagnosed with this cancer than non-smokers (Giuliano et al., 2004). This is due to tobacco by-products flowing through the bloodstream and seen in the cervical mucus. These by- products have a hand in altering cervix cells which contributes to this disease, as they are carcinogenic. At the same time, smoking has been found to weaken the immune system. This become imperative, as HPV infections are spontaneously cleared through this system. A weak immune system, leads to a reduced clearance rate of an HPV infection and allows for the persistence of the infection to occur. Damaged cervical cells from tobacco by-product, along with HPV, permits precancer to develop and possibly lead to cervical cancer (Giuliano et al.,

2004). The HPV blocks genes that fight cancer, allowing for precancer development. Greater risk for squamous cell carcinomas was found with this association.

In order to determine if the abnormal growth is in fact cervical cancer, the first line of detection is a PAP test, as stated above (Mays et al., 2000). If abnormal results are revealed,

Review of Literature 37 further procedures, such as a biopsy or colposcopy are conducted. The first test, removes a piece of cervical tissue for further investigation while the latter is simply a magnified view of the same. It is important to note that cervical cancers in its early stages are asymptomatic. As it progresses, symptoms such as abnormal vaginal bleeding between menstruation, post menopause, or after intercourse/pelvic exam. An increase in vaginal discharge, pain during intercourse and pain in the pelvic area are other symptoms. Once diagnosed, surgery, radiation or chemotherapy serve as treatment options. Hence, proper screening is vital to reduce mortality from cervical cancer.

Vaccines

Montague. She used variolation against smallpox with her six year old son, and shortly gained popularity as a strategy in dealing with the 1721 smallpox epidemic. In the same century, it was found that milkmaids who had gone through localized pockmarks from cowpox very rarely came down with smallpox.

Review of Literature 38 the first documentation of vaccinations. Due to this process, an eradication of smallpox eventually occurred in 1979.

(usually attenuated) or inactivated microorganisms (e.g., bacteria or viruses) or fractions thereof administered to induce immunity and prevent infectious disease or its sequelae” (MMWR, 2002).

While common man uses vaccine and immunization interchangeably, differences between the two exist. Immunization is when an individual is injected with an immunologic agent for the development of immunity against the specified bacteria/virus. Various forms of vaccines are available: killed-virus, whole-cell, bacterial, or live-attenuated.

Outside of Pasteur, Robert Koch was gaining fame in Berlin (Riedel, 2005; Stern &

Markel, 2005). He discovered the cholera and tubercle bacilli culture, formulated Koch’s postulates, and clinical hypersensitivity. Koch’s postulates were useful in determining specific etiology of diseases. Emill Von Behring, was the third giant in the field through his discovery of passive immunotherapy. This came about through the adoption of diphtheria and tetanus bacilli soluble toxins in detoxification for the use of immunization. It was Paul Ehrlich that enhanced

Behring’s work by using the principles of selectivity to develop medication for the treatment of syphilis (Lombard, Pastoret, & Moulin, 2007). As part of the process, antibodies were given a specified quantification which built on passive immunity. Additionally, specific receptor-ligand binding was formulated in the drug making process, which served as the harbinger in immunologic specificity, cellular chemistry, and therapeusis via drugs. By the end of world war

Review of Literature 39

I, evolution of vaccines had occurred to either a live or killed format and were developed for typhoid fever, Shigellosis, tuberculosis, plague, diphtheria, and tetanus.

A second phase of vaccine evolution was seen during the world war II era (1930-1950)

(Lombard et al., 2007). This was spun off by a demonstration conducted by Goodpasture in 1931 on the viral growth of embryonated eggs from hens, which led to Theiler’s yellow fever vaccine development for tropical regions. Application was done through minced chick tissue. Hens’ eggs that were embryonated were later used to grow typhus Rickettsiae for a mass rapid production of typhus vaccinations at the Squibb Virus Lab. The same lab also produced Wendell Stanley’s flu vaccine through purification from continuous flow centrifugation. This method established a paradigm for viral vaccines.

Advancements in influenza vaccines were taken at the Walter Reed Army Institute where antigenic specificity of the virus, drift and shift, were established (Lombard et al., 2007).

Approximately 40 million doses were administered in Fall of 1957, after learning of the flu pandemic in Hong Kong. While predictions of the spread of the flu were to occur with the commencement of schools, it did not strike till the Thanksgiving holidays. Due to widespread administration of the flu vaccine, a rapid peak and decline with the viral strain was seen.

Continuation of vaccine development and testing through clinical trials occurred between

Review of Literature 40 which led to the 14 and 23 valent vaccines. Meningococcus vaccines (monovalent, bivalent, and quadrivalent groups A, C, W135, and Y) stemmed from military request after the resurgence of meningitis in recruits.

Polio vaccines were then seen with Enders through propagation of polio virus in cell cultures of non-neural tissue (Hilleman 2000; Riedel, 2005; Stern & Markel, 2005).

Unfortunately the vaccine was ineffective due to live SV40 virus, which was resolved but discontinued for commercial reasons. Later, Sabin developed a live oral-fed vaccine based on the work of Enders. This has been the vaccine leading to the eradication of Polio. Live vaccines were further used in pediatric disease such as the mumps, measles, rubella, and varicella. For these vaccines to become commercially available, acceptable levels of toxicity and potency had to be defined through clinical trials. A two placebo-controlled protective efficacy trial was conducted with tests administered to 10 to 20,000 susceptible participants (i.e children and their contacts).

Hepatitis A and B vaccine development led to larger scaled field studies and lab testing

(Hilleman 2000; Riedel, 2005; Stern & Markel, 2005). These vaccines were of the killed virus type and controlled studies were conducted for safety and efficacy purposes. Initial development of the vaccines occurred in 1979 but was not licensed for commercial use till 1994.

Individuals viewed this process with much pride and with time, vaccines became an integral part of public health (Payette & Davis, 2001). Globalization of vaccines occurred with the establishment of the World Health Organization (WHO) in 1974 and the United Nation’s

Children’s Fund (UNICEF). The Expanded Programme on Immunization (EPI) was formed by

WHO to increase vaccinations in developing countries. With great effort, eradication of some diseases has occurred. While this is positive news, the negative impact is seen with a growing

Review of Literature 41 population taking vaccinations for granted, loss of interest among public funding agencies, and the controversy of causing autism. Skepticism regarding vaccinations comes from scenarios such as death due to the contamination of a vaccine during production. For instance in 1955, 200 children contracted Polio from the vaccine which had an active wild-type polio virus.

HPV Vaccine

Significance has been placed on HPV due to its pre-requisite nature for cervical cancer.

As a method for prevention towards this, vaccination was developed and released for usage in

2006 (Saslow et al., 2007). The vaccine does not contain DNA or a live virus. Gardasil was the first vaccine, initially approved for girls and women from the ages of nine to 25. It serves as prevention for HPV strains 6, 11, 16 and 18 only, meaning it is still possibly to be infected with other versions. Although, these are the prime four leading to genital warts and more importantly, cervical cancer. Three shots over a period of six months are given. Women over the age of 25 can still be vaccinated but approval is done on individual basis. This is due to high prevalence of

HPV among 14 to 24 year old versus the older age groups.

Involvement in sexual activity puts an individual at risk for attaining some form of an

HPV infection. If an individual has had an infection, the vaccine is no longer effective (Gillison,

Chaturvedi, & Lowy, 2008). For this reason, vaccination is recommended for 11 and 12 year olds and is even being suggested for nine years olds. This would allow for early on prevention for cervical cancer. This also places the vaccine at a controversy with parents, as it can give off the message of prevention towards HPV. To combat the topic, emphasis towards cervical cancer is given. Individuals are reminded that HPV infections can still occur.

Review of Literature 42

When determining the importance of a vaccine, the efficacy and effectiveness should be looked at. Efficacy for Gardasil, refers to how well the vaccine works in an ideal situation. Its effectiveness, refers to how well the vaccine works in the real world/ in practical life. Studies have been conducted for both conditions.

A study by Sawaya and Smith-McCune (2007) indicated a moderate efficacy for the vaccine. They noted that there were 15 oncogenic HPV strains and Gardasil serves as prevention for only two. A plateau with HPV 16 and 18 were found but the incidence of disease to steadily increase. This led to a possibility of the other 13 oncogenic strains to come to the forefronts, as

HPV 16 and 18 are being combated against. Outside of this information, the uncertainty of previous HPV 6, 11, 16, 18 infections counteracts the role of the vaccine. Gardasil is a fairly new vaccine and long term data is unavailable to determine the vaccine’s true efficacy towards preventing cervical cancer.

Another study found the vaccine to have long term effectiveness with new and persistent infections related to HPV 16 and 18 (Harper et al., 2006). A sustained immune response and persistent long term efficacy was seen at 12 months and at the follow up during four to five years. Due to this finding, it can be assumed that risks for cervical cancer from lesions and precancer are reduced. Studies from the American Cancer Society show similar findings as well.

These findings are based on women who had no evidence of past or current infection.

Effectiveness of the vaccine is indicated to last for about five years. Whether a booster will be necessary at the point or not is yet to be determined. Studies have shown an 89% decrease in incidence of persistent infections associated with HPV 6, 11, 16, 18 in a follow up that occurred over 35 months. Participants in that study had at least one of the three doses of the

Review of Literature 43 vaccine. During the vaccination period, efficacy for Gardasil was found to be 90% and efficacy for clinical disease was 100%. It was also suggested that vaccinating 10 to 13 year olds would provide the most effectiveness. Sexual activity with this age group would most likely not have begun, making them an HPV naïve group. This leads to a shift from cervical cancer mortality rates to management of precancerous lesions.

Economic concerns are also a salient consideration when looking at vaccinations. A majority of the burden with cervical cancer falls among the underserved communities and those in developing countries (Kim & Goldie, 2008). Cost effectiveness analysis was conducted for 12 year old girls, which indicated $43,600 per quality adjusted life year (QALY). As the age was increased to 21, the QALY rose to $120,400 and at the age of 26, the QALY went up to

$152,700. These numbers signify vaccination at the age of 12 is ideal. At the same time, when other health concerns due to HPV, outside of cervical cancer are addressed, a benefit was seen.

These health concerns were genital warts and non-cervical cancers. One of the limitations in analyzing cost-benefits for a vaccine is its recent introduction to society. It is still uncertain whether boosters will be needed to upkeep vaccine efficacy. In addition, there is no information available in terms of infection/re-infection at an older age, where the likelihood of cervical cancer might be higher.

In another study that looked at the cost-benefit analysis of the HPV vaccine had similar findings (Kim & Goldie, 2008). It was also mentioned that if boosters were needed for the vaccine ten years from now, the vaccine would not be cost effective. At that point, screening programs would be more cost effective than providing boosters. Currently, they assume booster will not be needed and the vaccine does not interfere with the immune system’s capability of

Review of Literature 44 fighting off HPV infections. More studies and time will determine the cost effectiveness of the vaccine.

On the same day, the FDA also approved a second vaccine, Cervarix, for only girls and women (Grever, 2009). Unlike Gardasil, Cervarix offers prevention from HPV strains 16 and 18.

There are three shots given. The first one is given at the first month and the following two are given at the sixth month. A primary clinical study showed a 93% effectiveness rate for individuals that were HPV naïve. For those that were positive for an HPV infection, the effectiveness rate was 53% in preventing dysplasia. Duration of prevention from the vaccine is currently known to last for 6.4 years. Similar to Gardasil, more information is needed with regard to duration of effectiveness.

HPV Vaccines in Men

Review of Literature 45

Currently, Gardasil is an approved vaccine that helps guard against 90% of genital warts in males (Gever, 2009). Gardasil is given in three shots over the course of three months. Males between the ages of nine and 26 are approved to take the vaccination. It has been noted that men who have not had sex and young men who have sex with men benefit the most from the vaccine.

Men who have had sex with a female do not benefit has much, as the likelihood of an HPV infection is higher.

In a recent review, 74%-78% acceptability of the vaccine among college males was found

(Liddon, Hood, Wynn & Markowitz, 2010). Several studies within the review found a relationship between vaccine acceptability and males that believed sexual partners, parents or physicians would encourage taking the vaccine, having a firm belief in the general importance of the vaccine, knowledge and awareness of HPV, perception of being at high risk, and belief in vaccinations. Very limited literature exists on the role of health belief model constructs with men but some is available with regards to women (Brewer & Fazekas, 2007). Adult women and adolescents indicated high likelihood of HPV exposure and cervical cancer, which was associated to higher acceptability of the vaccine (Mays, Zimet, Winston, Kee, Dickes & Su,

2000). Perceived severity was only found with regards to cervical cancer, but no relationship with acceptability of the vaccine. No significant values were found for perceived effectiveness.

Due to limited literature, correlates of vaccine acceptability among a high risk group need to be examined for future preventative purposes.

A few studies utilizing a quantitative approach have explored correlates of HPV vaccination in men. Reiter, Brewer, McRee, Gilbert & Smith (2010) examined acceptability of the vaccine among a national sample of gay and bisexual men. Acceptability was high among this target population. In particular, 73% were aware of the vaccine, 74% willing to take it.

Review of Literature 46

Recommendations from the doctor, five or more sexual partners, perceived greater severity of

HPV-related diseases, and perceived higher levels of effectiveness were all factors in acceptance of the vaccine.

Gerend and Barley (2009) conducted a random assigned self-protection versus self- protection and partner protection about HPV and the vaccine among heterosexual college males.

Results indicated a moderate level of interest in taking the vaccine, regardless of the group they were assigned to. Factors related to taking the vaccine were: sexual activity, perceived susceptibility, perceived benefits, perceived costs, self-efficacy, and perceived norms. These correlates are analogous to those identified in women; thus suggesting predictors of vaccine acceptability tend to be similar regardless of gender.

Another study by Ferris, Waller, Miller, Patel, Price, Jackson, and Wilson (2009) examined correlates of HPV vaccine among college men. In this study, participants were given a one page HPV and HPV vaccine information sheet, followed by a 29 item questionnaire. Unlike the previous study, this one focused on demographic, sexual and vaccine-related variables.

Results showed higher education, Hispanic ethnicity, wearing a seat belt most of the time, regular tobacco use, sexual inactivity, more than 10 sexual partners, importance of getting oral sex, familiarity with HPV, and extreme importance of receiving the vaccine. This indicated that males with high-risk health behaviors, higher education, and awareness of HPV were more likely to take the vaccine.

Review of Literature 47 were of major concern for men 18-26 years old, but were more likely to get vaccinated than other age groups. Of the 18-26 year olds, men having sex with men had a higher intention of vaccination versus heterosexual men. Based on the study, costs and sexual history are crucial determinants in intentions towards vaccination.

Finally, a study looking at predictors of vaccine acceptability among college men was conducted at the University of Cincinnati by the researchers (Mehta & Sharma, 2012). Results indicated self-efficacy (p=0.000), cues to action (p=0.000), and perceived susceptibility

(p=0.005) held a significant positive relationship towards vaccine acceptability. The model had an adjusted R2 of 0.480, which indicated that HBM constructs could account for 48% variance in participants ability to take the vaccine. At that time, a majority of the participants were neutral about taking the vaccine. Talking to college men about their perceived susceptibility, cues to action, and increasing their self-efficacy would lead them to take the vaccination. These findings were parallel to those in the previous studies. There still exist a limited number of studies exploring reasons towards the intention to vaccinate.

Up to this date, there is a lack of qualitative research on vaccine acceptability among men and theory-based interventions that promote HPV vaccination among men. A few studies have been conducted with parents and physicians regarding HPV vaccination with girls, and a few regarding women’s awareness and acceptability. Results indicated increasing awareness of HPV, informing costs and benefits associated with the vaccine, and perceived susceptibility. Based on this information, it is crucial to obtain a further understanding of knowledge, awareness, and predictors related to HPV and its vaccination in men.

Health Belief Model

Review of Literature 48

Perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action and self-efficacy are constructs that comprise the Health Belief Model (Becker, 1978;

Review of Literature 49

The Health Belief Model is particularly important in the program planning stages of health education, as they account for the beliefs seen in the constructs of the model (Becker,

1978; Sharma & Rojas, 2008). Taking these factors into account allow for researchers/program planners to strengthen educational intervention sessions. Outside of strengthening the program, usage of the constructs allow for addressing the needs of community or the target group. This then leads to a tailored program yielding a higher level of effectiveness. Additionally, the Health

Belief Model accounts for the role of demographic factors in perceived barriers, perceived benefits, and perceived severity, which other theories do not mention. Of most important in the utility of this model, is the concept of self-efficacy. While this construct was not initially a construct in the model, it has been fathered in overtime. Self-efficacy, in addition to the other health beliefs, increases confidence levels in the specified health behavior while serving as an explanatory variable.

On the downside of the model, insight on health beliefs related to diabetic struggles during middle age years, risky sexual behaviors among college students, cigarette use by teenagers, and obesity (Zak-Place & Stern, 2004). Alternatively, use of the model in a qualitative design allows for the comprehension of serving the needs of diverse groups in risky health behaviors.

Applications of the Health Belief Model

The model was useful in screening behaviors for programs. Becker and colleagues (1977) explored the Health Belief Model in determining participants for a Tay-Sachs Disease program.

A Jewish population in the DC area was part of a Tay-Sachs Disease educational campaign program seven weeks prior to the program. Individuals were given a survey based on the Health

Review of Literature 50

Belief Model as part of the screening process. Results indicated that there were significantly more participants than non-participants that felt susceptible to being carriers of the gene and a significant negative relationship between participants and severity. At the same time, beliefs on susceptibility and severity between spouses were also found to be a significant predictor in screening participants.

Hallal (1982) examined the Health Belief Model in the practice of breast self- examinations among women in non-health care settings. The constructs of susceptibility and benefits were given a higher emphasis. Significant positive relationships were seen between those that practiced breast self-examinations and the constructs of the model, especially susceptibility and benefits.

Significance in preventative health behavior was seen in the utility of the Health Belief

Model (Janz & Becker, 1984). Using the Health Belief Model in learning about immunizations is efficient due to the specificity in threat and a simple action response. Being that the Health Belief

Model is considered to be a value expectancy theory, in the realms of vaccines, taking the vaccine as a preventative method is hypothetically placed at a high value. Thus, individuals would be more likely to enact the behavior. Initially, the Health Belief Model was used in swine flu vaccinations thrice, and once with influenza. Aho in 1979 examined Swine Flu vaccination intention along with the constructs of the Health Belief Model in 122 elderly individuals. Results indicated susceptibility, efficacy, and safety were significant predictors in taking the vaccine.

Additionally, severity was not properly assessed due to its interpretation.

In another Swine Flu study, random digit dialing was done prior to the launch of the vaccine campaign to determine inoculation –seeking behavior in adults (18 years and older)

Review of Literature 51

(Cummings, Jette & Brock, 1979). Follow-up surveys were done a month and two months post- campaign launch. Results from the study showed major Health Belief Model constructs to be statistically significant in determining intent to vaccinate. The influence of the model shown in the intent to vaccinate was important in carrying out the action of vaccination.

Larson et al (1979) examined the Health Belief Model with the influenza vaccine in high risk individuals. A survey was handed post-flu epidemic, which looked at vaccination status and constructs of the model. Significant positive correlations were seen between being vaccinated and the model. Additionally, the researchers sent a reminder postcard about the vaccine but no significant differences between participants’ health beliefs and vaccination were seen. It was concluded that the reminder cards served as a cue to action.

Chor et al (2009) measured intent to vaccinate against the pre-pandemic flu among healthcare workers in Hong Kong. Two surveys were distributed; one between January and

March 2009 and the second during May 2009. Perceived barriers and susceptibility were

Review of Literature 52 significant constructs associated with the intent to vaccinate. The overall intent to vaccinate was very low and insignificant, which was surprising due to the past history of SARS in the area and the nature of the individuals’ occupation. The Health Belief Model served to be important due to the findings and allowing researchers to build programs targeting these beliefs in order to increase the intent to vaccinate.

Latinos significantly were less likely to get vaccinated than Whites and Asians, but Filipino

Americans were also significantly less likely to take the vaccine. Perceived susceptibility was the most significant predictor in vaccination. Those that did not obtain the vaccine, reported a significantly low perceived severity which resulted in their decision. Barriers in not getting vaccinated were household income along with low perceived severity. African Americans noted serious side effects and lack of trust among health care workers as barriers, while Latinos reported lack of insurance/transportation/clinics. Findings from the study were important in recognizing racial/ethnic barriers and facilitators in vaccinating against the flu. Once again the importance of the Health Belief Model was signified through this study.

Butraporn et al (2004) looked at the Health Belief Model in the potential use of a vaccine for Shigellosis in Thailand. It is important to note that a vaccine for Shigellosis had not occurred.

Interviews were done to determine interest in the vaccine; questions were based of the constructs of the model. Results from the respondents indicated cost as a burden towards to taking the vaccine outweighed the benefits. Recommendations on taking the vaccine from health clinic staff

Review of Literature 53 and volunteers were deemed as significant influencers (cues to action) in intent to vaccinate.

Perceived susceptibility did not show up but severity was seen as a significant theme in the interviews. This is unlike the previous studies, in which severity was not of significant concern.

While the study was a qualitative design, it offered information pertinent for government officials and health policy makers in their understanding of possible vaccine acceptance if available, and ways to implement vaccine programs.

The Health Belief Model has been used in predicting HPV vaccine acceptability in both women and men. A review by Brewer and Fazekas (2007) examined constructs of the model in

Woodhall et al. (2007) found perceived susceptibility, more sexual partners, low cost of the vaccine and its safety to be predictors in accepting the HPV vaccine. In a study among women in the UK revealed that 90% would take the HPV vaccine once it is available (Marlow,

Waller, & Wardle, 2009). Predictors in its acceptance were all of the constructs of the Health

Belief Model, minus perceived severity. This finding is similar to the review of studies by

Review of Literature 54

Brewer and Fazekas. Rationale behind the insignificance of perceived severity was the confusion on the impacts of the HPV virus. This is due to the fact that an HPV infection is not serious and clears up on its own, but can lead to cervical cancer which is a severe consequence of HPV.

Quantitative Designs

Quantitative designs are a form of research methods that are objective in nature and use deductive reasoning (Reswell, 2003). Data collected in a quantitative design are all numerical and generalisable. Its primary intent is to test theory, unlike its qualitative counterpart. This design also aimed to show relationships between two things (independent variable and the dependent variable) within a population. This research design segments into two dynamics: descriptive and experimental. Descriptive studies are conducted once and establish associations between variables, while the latter is conducted more than once and forms causality. With experimental designs, a quasi-experimental type also exists. It examined cause and effect but varied from an experimental design in its lack of randomized controlled trials.

Descriptive quantitative designs provide characteristic of the population being examined

(Reswell, 2003). They aided in the development of theories, identifications of issues in the situation being tested, or serve as justification for an action. Means, standard deviations, and the sorts are provided to paint a numerical picture. Quasi-experimental designs allow for the researcher to examine causality when experimental controls are not conducive. Random assignment is not seen in this set of design. The experimental design is controlled and has random assignment. Causality is also determined but in closer manner than the quasi- experimental design. The most often used in experimental design is a pre-test, post-test version.

Review of Literature 55

Both groups are randomized and controlled by the researcher. A comparison between the pre-test and the post-test is done to determine if change occurred.

Quantitative Designs and the Health Belief Model

Gottval, Tyden, Hogland, and Larsson (2010) conducted an education intervention among high school students on the knowledge of HPV. The Health Belief Model was used as their theoretical backdrop for the educational intervention. A questionnaire at baseline and at a two month follow-up was given to participants. The average age of students were 16 and of

Swedish descent. A significant increase in knowledge was seen with the intervention group

(p<.001). Attitudes towards use of condoms, HPV vaccinations, and Pap smear screening were not affected. Approximately 15% of girls had been vaccinated between baseline and follow- up. Although it is important to note that a direct-to consumer campaign was ongoing throughout the study. Discussions based on the health belief model in the intervention group were useful in the increase of knowledge and had a hand in improving knowledge scores from baseline to follow-up.

Dempsey, Zimet, Davis, and Koutsky (2006) examined factors related parental acceptance of the HPV vaccine through a randomized intervention using written information.

The Health Belief Model and the Theory of Reasoned Action were used in the development of the survey and intervention materials. The normative beliefs construct from the latter theory was the only construct being used, while perceived susceptibility, perceived severity, perceived benefits, and perceived barriers from the former model were assessed. Results indicated similarity of low knowledge and awareness between both groups at baseline. Perceived benefits

(p<.001) was the largest factor impacting vaccine acceptability, along with normative belief

Review of Literature 56

(p=.004), perceived susceptibility (p<.001), while perceived barriers (p<.001) was a significant factor deterring parents. While the information sheet had an impact on increasing HPV/HPV vaccine knowledge (p<.001) it did not significantly alter their attitudes towards vaccine acceptability. It was concluded that parental beliefs and attitudes had a higher impact on acceptability but the intervention was successful in enhancing knowledge.

Juraskova, Bari, O’Brien, and McCaffery (2011) conducted a randomized controlled trial intervention with women based on joint reference to cervical cancer and genital warts. The

Health Belief Model was used as the theoretical backdrop for pre and post measurements.

Groups were either given an information sheet for cervical cancer or cervical cancer with genital warts. Results indicated that 55% of participants had low awareness of HPV at baseline no differences between groups (p> .05). Differences between groups were seen with perceived benefit and severity scores (p<.01), with the scores for both constructs being higher for the cervical cancer with genital warts group (p<.01). Health belief model constructs predicting HPV vaccine intentions found perceived susceptibility and benefits to be significant predictors

(p=.002). Framing the HPV vaccine as cervical cancer only or cervical cancer with genital warts had not impact on the intent to vaccinate (p>.05). Findings from the study were able to provide recommendations for emphasizing campaigns on the HPV vaccine and formulating tailored messages.

O”brien, Hughes Halbert, Bixby, Pimentel, and Shea (2010) used randomized controlled trials using community health workers in decreasing cervical cancer disparities among

Hispanic women. Self-efficacy, acculturation, and knowledge were assessed before and after the intervention. The intervention consisted two three hour workshops with the promotoras.

Review of Literature 57

Discussions on female genitalia, information on cervical cancer, screening procedures, and epidemiology of cervical cancer among Hispanic women was done. Low levels of acculturation were found among participants. Significant increases in knowledge and self-efficacy were seen at a six month follow up (p<.001) with the intervention group. Rates of pap smear screening in the intervention group was also up at the six month follow up (p=.02). Differences between groups were found for pap smear rates (p=.004) and knowledge and self-efficacy scores

(p<.001); the intervention group doing better than the control group.

Qualitative Designs

Qualitative research designs are unlike quantitative research methods, in their inductive reasoning (Patton, 2002). This form of research is popularly referred to as interpretive research and utilized to depict an account of events/experiences, new subjective perspective on a phenomena, or perceptions of a process. Data is collected through several means: participant observation, nonparticipant observation, interviews, focus groups, collection of documents and artifacts. Analysis of the data collected can be done through: standardized observational protocols, analytic induction, or constant comparison. The goal in the analysis is to determine relationships, themes, perspectives, context and its influences. Based on the information obtained, it is explained in terms of philosophical perspectives, sociocultural/psychological/economic/political constraints, or ideological interpretations.

While this form of design remains to be subjective and not as robust as its counterpart, many benefits can be reaped (Patton, 2002). Using a qualitative method gives the researcher thick descriptive accounts of the situation at hand, which cannot be seen through a quantitative measure. This means that more discovery can also be oriented. While a vast amount of

Review of Literature 58 individuals are not used in the sample, a smaller sample size allows for the researcher to study them more intensely. Qualitative measure also allow for naturalistic behavioral observations versus more reactive ones. While the researcher is the instrument in a qualitative study, the data obtained facilitates triangulation to occur for a more grounded understanding of the phenomena at hand.

Of particular interest in qualitative research methods are focus groups (Patton, 2002). A focus group is comprised of a group, typically eight to 10 individuals and ideal in learning perspectives about the topic of discussion at hand. In this setting, the researcher is able to get insight on how individuals view the issue and the influence of others. Outside of the focus group members, are the facilitator and a moderator. The facilitator leads the group, while the moderator takes noted and ensures that everyone has had a chance to voice their opinion. In essence, the goal of the focus group is to draw on attitudes, beliefs, feelings, experiences, and reactions which can not be done through interviews or surveys. In a short time period, the researcher is able to gain a vast amount of information from more than one person. These are especially significant when deviances exist between the target population and the decision-makers. Data from the focus groups bridges the gap and enables for future communication and services to be more user appropriate.

Downfalls to the focus group method exist (Yach 1992). While the focus group serves to empower is participants in their ability to openly converse, it may not occur for all. Some individuals may find the interaction to be intimidating. Ways to overcome this barrier is by building the trust and going through round table discussions, in which every individuals’ voices at least one opinion on the question being asked. Another limitation is the assumption that participants are sharing their own perspective, when that may not be the case. The views being

Review of Literature 59 share are in a specified context and can change when asked on an individual basis. Additionally, setting up groups can be difficult and may not represent the target population. It is important to note that focus groups are not anonymous, as they it is a group in which information is being shared. Confidentiality can be preserved in the note taking process and analysis portion through code names.

Qualitative Methods and the Health Belief Model

Studies have used both a qualitative and quantitative approach along with the Health

Belief Model in better understanding health issues. In the past, integrative approaches to research were fairly common. Focus groups was the popular technique in qualitative research that was applied (Yach 1992).

Yarbrough (2008) used the Health Belief Model in explaining or predicting breast cancer screening behaviors. In the review, 16 qualitative studies were found. Results from the review did not indicate consistent results based on the Health Belief Model. While there was a linear relationship between the constructs and screening behavior, other factors were also at play.

These factors were socioeconomics status, age, and education, which kept the results from being consistent. Perceived susceptibility, severity, and benefits were positive correlated of breast screening while barriers were negatively correlated.

Mazor, Velten, Andrade and Yood (2010) conducted in-depth interviews to better understand older women’s perception of prescription osteoporosis medication. Themes of perceived need, safety and effectiveness emerged from the transcription of 50 women. While smaller themes existed, these were the major ones that drove women towards medication adherence. Through a qualitative design, the researchers were able to conclude improvements in

Review of Literature 60 patient-provider communication were in strong need, in order for women to take osteoporosis prescriptions. In addition, providing for more quantitative based research on the topic.

Gaylord Vanslyke, Baum, Plaza, Otero, Wheeler, and Helitzer (2008) used focus groups to determine knowledge, beliefs and attitudes on HPV and Cervical Cancer testing among

Hispanic women. There were seven focus groups with five to 11 women in each. Overall results found that women viewed the diagnosis as an extremely negative event affecting their social, emotional, and physical well-being. While they lacked knowledge about the cancer, they were able to associate sexual activity with cervical cancer. Women expressed a desire to learn more about HPV, and also indicated an importance on prevention and the role of men in transmission.

The Health Belief Model was noted as a theoretical backdrop to help in the decision making for preventative methods.

Wong (2008) also use the focus group technique in determining attitudes towards the

HPV vaccine in multiethnic women. There were seven focus groups (six to eight women per group), and separated into Malay, Chinese, or Indian ethnic groups for comparison purposes.

Results indicated the following themes that emerged from the group: lack of knowledge of

HPV/HPV vaccine, low perceived risk, adverse effects, promote promiscuity, social stigma, parental barrier, halal, cost, physician recommendation, and mandatory vaccination. Knowledge of HPV and its vaccine were low regardless of socioeconomic status or ethnic backgrounds.

Physicians were deemed as the key factor in getting the vaccine but issues of costs, halal, social stigma of being permiscuous, and acceptability by parents/guardians had to be present to take the

HPV vaccine. While the sample is small, it provided information that would foster higher vaccine acceptability.

Review of Literature 61

Katz, Reiter, Heaner, Ruffin, Post, and Paskett (2009) examined HPV vaccine acceptability among women, parents, community leaders, and healthcare providers in Ohio

Appalachia using focus groups. Questions in the focus group were specified to the areas of knowledge, barriers, beliefs, and attitudes about the HPV vaccine at an individual and community level. A total of 23 focus groups were conducted: six for healthcare providers, six for community leaders, six for parents, and five for women. A total of 112 participants were in the study. The following themes emerged from the groups: barriers, knowledge, attitudes and beliefs, and suggestions for educational materials and programs. Several sub-themes for each category were also found. Concerns across the board were: general lack of knowledge of

HPV/HPV vaccine, limited access to healthcare, costs, side-effects (short and long term), promotion of promiscuity, cervical cancer due to genes/environment, lack of trust with the medical community and those from outside the community/pharmaceutical companies. A strong need for materials pertaining to the Appalachian population in Ohio but also ones that were appropriate for each group of individuals (i.e healthcare providers, young women, parents, etc.) was noted. An overall acceptance for the vaccine was found.

Summary

HPV is a sexually transmitted disease affecting many men and women. Genital warts and cervical cancer are the most known diseases caused by HPV. While HPV has been popularly known for cervical cancer among women, little has been acknowledged about its impacts on males. Genital warts are primarily seen in men but testicular, anal, head, and neck cancers are also associated with having an HPV infection. To combat the effects of HPV, Merck has developed the Gardasil vaccination available for both genders. Based on the review of studies, limited knowledge about effects of HPV and the HPV vaccine are available for men.

Review of Literature 62

The Health Belief Model was the theoretical background used to explore acceptability of the vaccination among men. Perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy are constructs within the Health Belief Model that were utilized. Few studies that have explored HPV vaccine acceptability in men have indicated moderate levels of acceptability, with perceived susceptibility, self-efficacy, and cues to action to be significant predictors of intent to vaccinate. The lack of literature in men indicates a further need to examine correlates of intent to vaccinate by using the Health Belief Model and increase willingness to take the vaccine. The next chapter defines the methodology for the study.

Methods 63

Chapter Three

Methods

Design

Phase I

The study went through two phases. The first phase took the qualitative approach and used focus group discussions to gain in-depth knowledge regarding barriers, facilitators, and motivators in their intent to seek vaccination. Each focus group discussion consisted of eight to

10 participants and was conducted at the University of Cincinnati. Focus group discussions were performed until a point of saturation was reached. It was anticipated that five focus group discussions would be needed to reach this saturation point. Eligibility requirements for

Methods 64 participation were: English speaking males, 18 years or older, attending the University of

Cincinnati. The upper age limit for participation was 25 years. Both undergraduate and graduate students were eligible for recruitment.

The Health Belief Model was used as the guiding theoretical model in developing questions for the focus group. Questions were based on the following constructs: perceived benefits of taking the HPV vaccine, perceived barriers in taking the HPV vaccine, perceived severity for HPV, perceived susceptibility for acquiring HPV, cues to action for taking the HPV vaccine, and self-efficacy for taking the HPV vaccine. Through these questions, the researchers aimed to identify barriers, facilitators, and influencers in the intent of college males to get the

HPV vaccine. This combined with the results obtained from the survey aided in the development of an intervention aimed at increasing levels of intent to seek vaccination. In addition, this information was useful for healthcare providers, parents, and Merck in increasing HPV vaccinations for males.

Questions for focus group discussions:

1. Do you see HPV as a threat to you? If so, how?

2. Do you believe HPV can lead to serious illnesses?

3. If not, do you believe HPV can have any negative consequences on your health? In your

personal life? In your professional life?

4. How likely do you think you can get an HPV related infection?

5. Do you believe passing HPV to a sexual partner can cause harm to their health? How

would that impact you as an individual? Your relationship? You future relationships?

Methods 65

6. What are some barriers you might face in taking the vaccine? Costs? Not sure of the

availability? Made fun of by friends?

7. Would taking the HPV vaccine help you? If so, how?

8. Under what circumstances would you be willing to take the HPV vaccine?

9. Under what circumstances would you not be willing to take the HPV vaccine?

10. What or who would make you feel confident in taking the vaccine now?

11. How confident do you feel in taking the HPV vaccine now?

Phase II

Phase II of the study was a randomized-controlled educational trial aimed to test the intent of vaccination and actual vaccination between two approaches: HBM based educational approach and knowledge-based educational approach. This was a quantitative experimental design and content for both groups was developed by the researcher. The control group received a knowledge-based intervention, regarding HPV and its vaccine, while the experimental group was based on health belief model and its constructs as derived from the triangulation of the literature review, phase 1, and the quantitative study already completed. The experimental intervention utilized all the constructs of health belief model found to be significant predictors of taking the vaccine, based on a prior self-report study and qualitative study results in Phase 1. Discussions based on perceived susceptibility and cues to action, and role plays to increase self-efficacy in taking the HPV vaccine will comprise the intervention. Adjustments to the content were made after analyzing results from phase I. Duration of the intervention was one session for a minimum of two hours but no more than four. A pre-test and post-test were administered to determine efficacy of the intervention. This instrument has already been developed and validated in the earlier quantitative study.

Methods 66

Eligibility requirements for participation were: English speaking males, 18 years or older, attending the University of Cincinnati, who have not yet taken the vaccine. The upper age limit for participation will be 25 years. Both undergraduate and graduate students were eligible for recruitment. Figure 3.1 and Figure 3.2 displays a flow diagram of the study, while Figure 3.3 depicts a logic model of the Health Belief Model based intervention.

Figure 3.1 Flow Diagram of the Phase I Research Design

Flow Diagram of Phase I research (Total duration =7 months)

Phase I: Focus Groups w/IRB approval (completion time: 7 months)

Participant Recruitment n=50 (1 month)

Data Collection (1 month)

Focus group 2 Focus group 3 Focus group 4 Focus group 1 Focus group 5 n=10 n=10 n=10 n=10 n=10 Time=1-2hours Time=1-2hours Time=1-2hours Time=1-2hours Time=1-2hours

Data Analysis N-Vivo software (2 months)

Adjustments to intervention/ phase I manuscript development and submission/Phase II IRB submission ( 3 months)

Methods 67

Figure 3.2 Flow Diagram of the Phase II Research Design

Flow Diagram of Phase II research (Total duration = 5 months)

Phase II: intervention (Completion time: 5 months)

Participant Recruitment n=52 (1month)

Data Collection: Random assignment (1 month)

Control Intervention n=26 n=26 1 session 1 session 2-3 hours 2-3 hours

Data Analysis Repeated measures ANOVA PASW 18.0 (1 month)

Phase II manuscript development and submission (2 months)

Methods 68

Figure 3.3 Logic Model for Increasing HPV Vaccination through a Health Belief Model Based Intervention

Logic Model for Increasing HPV vaccination through a Health Belief Model Based Intervention

Educational Health Belief Model Behavioral outcome Methods Constructs

Discussion Perceived Susceptibility

Lecture Perceived Severity HPV vaccination

Perceived Benefits

Brainstorming

Perceived Barriers

Discussion Cues to Action

Role play Self-Efficacy

Methods 69

Population and Sample

Population

The target population consisted of males attending the University of Cincinnati between the ages of 18 and 25. Situated in an urban setting, students were typically from the greater

Cincinnati area and some from other parts of the state of Ohio. Current enrollment of students at the University of Cincinnati is 41,357, with 8.9% African Americans, 3.0% Asian, and 2.0%

Hispanic. Of these students, 3,861 resided on campus and the average age is 25.2 (University of

Cincinnati, 2012). There are 18,695 males between 18-25 years of age, which is our target population.

Phase I

A snowball sampling technique was used to recruit participants for focus groups. This form of sampling enabled recruitment of participants through recommendations of others.

Recruitment was conducted through e-mail messages sent by instructors, flyers around campus, and through word of mouth. Those interested in participating e-mailed the researchers, as directed in the e-mail messages and flyers. This inhibited any forms of coercion or conflict of interest with participants. After a minimum of 50 college males signed up, focus groups began.

Approximately two months were allotted for recruitment and conduct of focus groups.

Phase II

Once again a snowball sampling technique was used to recruit participants for the interventions. This form of sampling enabled recruitment of participants through recommendations of others. Recruitment was conducted through e-mails sent from instructors

Methods 70 that agreed to send out information regarding the study, flyers around campus, and through word of mouth. Those interested in participating e-mailed the researcher, as directed in the e-mail messages and flyers. This inhibited any forms of coercion or conflict of interest with participants.

A sample size of 90 men total (Erdfleder, Faul, & Buchner, 1996) were needed for the intervention. This was calculated by G*Power based on: alpha= 0.05, power=.80, groups=2, measurements=2, effect size=.20, correlations among repeated measures-0.5, nonsphericity correction ε=1, giving us total sample of 90. Random assignment was done through the use of software available online, known as the Research Randomizer (Urbianiak & Plous, 2008).

Through this generator, all 90 participants were assigned to either of the two groups.

Participants were asked to sign informed consent forms prior to both phases of the study.

(Appendix E). These forms explained participation was voluntary and participants may withdraw from the study at any time. This measure was taken for the protection of human subjects. All forms were kept by the primary investigator in a locked file cabinet.

Setting

Phase I

Focus groups were conducted on campus at Teachers College room 435. This was a neutral setting and easily accessible for students. The doctoral student served as the facilitator of the discussion, while the faculty mentor served as the facilitator of group process (i.e observe and take notes of the discussion). Each focus group ran for a minimum of an hour and no more than two hours and were audio recorded. Time varied based on the discussion being held in the group. Approximately two months were allotted for Phase I data collection.

Phase II

Methods 71

Intervention was conducted on campus at Teachers College room 435. This was a neutral setting and easily accessible for students. The doctoral student served as the facilitator of the intervention, while the faculty mentor oversaw the process (i.e. observe and take notes of the discussion). Each group ran for a minimum of two hours but no more than three hours. Time will varied based on the conversations held in the group. Approximately two months were allotted for data collection.

Once participants were recruited, they were entered into SPSS with their initials and randomized using an randomization software online. The experimental group was listed as “0” and the control group was listed as “1”. Group labels were assigned in the next column based on the results of the randomizer. This was done to minimize any differences that may occur between groups.

Content for the experimental group was based on the triangulation of data from the literature review, results of phase I, and the survey conducted prior to this study. The health belief model constructs were addressed in this presentation. Along with a powerpoint presentation, role plays, brain storming session, and discussions were conducted (Appendix D).

These techniques were used to not only supply knowledge and awareness of HPV and the HPV vaccine but help change attitudes and beliefs towards HPV vaccinations. The behavioral and learning objectives for this presentation were:

1- ….increase their perceived susceptibility level of obtaining a HPV related infection as measured

by the perceived susceptibility questionnaire

Learning Objectives:

At the end of the session on perceived susceptibility at least 80% of the participants will be able

to:

Methods 72

- Define STDs and give examples of STDs

- Identify likelihood of obtaining an HPV related infection in the lifetime

- Name modes of transmission of HPV

- Identify what the HPV vaccine is

2- …increase their level of perceived severity (knowledge and beliefs) of HPV related infections as

measured by the perceived severity questionnaire

Learning Objectives:

At the end of the session on perceived severity at least 80% of the participants will be able to:

- Define HPV

- Explain the immediate effects of HPV on their health

- Explain long-term consequences of HPV on human body

- Describe family and societal implications of HPV infection

3- …decrease their perceived barriers and increase the perceived benefits in taking the HPV vaccine

as measured by the perceived barriers and benefits questionnaires

Learning Objectives:

At the end of the session on perceived barriers and benefits at least 80% of the participants will be

able to:

- Identify benefits of taking the vaccine

- Narrate barriers of taking HPV vaccine

- List methods of counteracting barriers

- Describe how to overcome barriers of taking the vaccine in their personal lives

4- …increase their self-efficacy in taking the HPV vaccine as measured by the self-efficacy

questionnaire

Learning Objectives:

At the end of the session on self-efficacy at least 80% of the participants will be able to:

- List HPV vaccination process

Methods 73

- Identify role models who have taken HPV vaccine

- Identify stressors associated with taking the vaccine

- Describe ways of overcoming stress associated with taking the vaccine

5- ….increase their cues to action in taking the HPV vaccine as measured by the cues to action

questionnaire

Learning Objectives:

At the end of the session on cues to action at least 80% of the participants will be able to:

- Identify support systems in taking the vaccine

- Name at least three methods they can use to remind themselves of getting the vaccine

6- …increase their acceptability of the HPV vaccination as measured by the question in the post-test

Learning Objectives:

At the end of the session on acceptability at least 80% of the participants will be able to:

- Publicly commit to taking the HPV vaccine

- Narrate three benefits of taking the vaccine

- Name three ways of overcoming barriers in taking the HPV vaccine

Content for the control group was based on information regarding sexually transmitted diseases and the history of vaccines (Appendix C). This was done to avoid any tampering of information that may occur, since the researcher was conducting all sessions. The presentation for this group involved a powerpoint, discussion, and videos only. A theoretical backdrop was not used for the preparation of the presentation. Information was simply provided to the participants. The behavioral and learning objects for this presentation were:

1- ….increase their perceived susceptibility level of obtaining a HPV related infection as

measured by the perceived susceptibility questionnaire (2

Learning Objectives:

Methods 74

At the end of the session on perceived susceptibility at least 80% of the participants will

be able to:

- Define STDs and give examples of STDs

- Identify likelihood of obtaining an HPV related infection in the lifetime

- Name modes of transmission of HPV

- Identify what the HPV vaccine is

2- …increase their level of perceived severity (knowledge and beliefs) of HPV related

infections as measured by the perceived severity questionnaire

Learning Objectives:

At the end of the session on perceived severity at least 80% of the participants will be

able to:

- Define HPV

- Explain the immediate effects of HPV on their health

- Explain long-term consequences of HPV on human body

- Describe family and societal implications of HPV infection

3- …decrease their perceived barriers and increase the perceived benefits in taking the HPV

vaccine as measured by the perceived barriers and benefits questionnaires

Learning Objectives:

At the end of the session on perceived barriers and benefits at least 80% of the

participants will be able to:

- Identify benefits of taking the vaccine

- Narrate barriers of taking HPV vaccine

- List methods of counteracting barriers

Methods 75

- Describe how to overcome barriers of taking the vaccine in their personal

lives

4- …increase their self-efficacy in taking the HPV vaccine as measured by the self-efficacy

questionnaire

Learning Objectives:

At the end of the session on self-efficacy at least 80% of the participants will be able to:

- List HPV vaccination process

- Identify role models who have taken HPV vaccine

- Identify stressors associated with taking the vaccine

- Describe ways of overcoming stress associated with taking the vaccine

5- ….increase their cues to action in taking the HPV vaccine as measured by the cues to

action questionnaire

Learning Objectives:

At the end of the session on cues to action at least 80% of the participants will be able to:

- Identify support systems in taking the vaccine

- Name at least three methods they can use to remind themselves of getting the

vaccine

6- …increase their acceptability of the HPV vaccination as measured by the question in the

post-test

Learning Objectives:

At the end of the session on acceptability at least 80% of the participants will be able to:

- Publicly commit to taking the HPV vaccine

- Narrate three benefits of taking the vaccine

Methods 76

- Name three ways of overcoming barriers in taking the HPV vaccine

Instrumentation

A valid and reliable survey based on the health belief model (HBM) was developed by the doctoral student and the faculty mentor. Face and content validity were established by a panel of six experts (two HBM experts, two target population experts, and two HPV vaccine experts) in two rounds (See appendix A for list of panel of experts). Internal consistency of subscales was established by Cronbach’s alpha; values between 0.70 and 0.90 were obtained.

These are summarized in Table 3.1. Reliability of the survey was determined through a test-retest procedure. Test retest reliability coefficients were computed in a sample of 30 participants; r values between 0.6-0.8 were obtained. These are summarized in Table 3.2.

Table 3.1. Reliability Coefficients (Cronbach’s alpha) for Perceived Susceptibility, Perceived Severity, Perceived Benefits, Perceived Barriers, Cues to Action , Self Efficacy and Knowledge

______

Constructs Alpha levels ______Perceived Susceptibility 0.900

Perceived Severity 0.753

Perceived Benefits 0.585

Perceived Barriers 0.920

Cues to Action 0.706

Self Efficacy 0.761

Knowledge 0.705

Table 3.2. Test-retest Reliability Coefficients for Perceived Susceptibility, Perceived Severity, Perceived Benefits, Perceived Barriers, Cues to Action, Self Efficacy and Knowledge

Methods 77

______

Construct r p-value

______

Perceived Susceptibility .819 .003

Perceived Severity .603 .006

Perceived Barriers .853 .000

Perceived Benefits .652 .050

Cues to Action .571 .009

Self Efficacy .647 .002

Knowledge .624 .003

The instrument has been provided in Appendix B. The first two questions assessed if participants had heard of HPV and the HPV vaccine. Responses were true, false, and do not know. Knowledge was measured in the next six questions with answer options of true or false.

Items such as: HPV is a common virus that can be passed on through sexual contact, and HPV can cause health problems, such as genital warts were asked. Perceived susceptibility was measured in the next three questions on a five point Likert scale, with the total possible score range from zero (all strongly disagree) to 12 (all strongly agree). Due to my sexual behaviors I am at higher risks for HPV infections or cancers, and I have had more than 1 sexual partner, placing me at risk for getting an HPV infection, were examples of items asked for this construct.

The next three questions asked about perceived severity with items such as: HPV can cause health problems such as genital warts, HPV can cause serious diseases. A total possible range of scores were zero (all strongly disagree) to 12 (all strongly agree). Perceived barriers were

Methods 78 addressed in the following three questions with items such as: I cannot afford the HPV vaccine

($375), and I do not have access to getting the 3 shot series of the HPV vaccine. A total possible range of scores between zero (strongly disagree) to 12 (strongly agree). Cues to action were measured by five questions with items such as: I have been advised by friends about the benefits of taking the vaccine, my friends have gotten the vaccine, and I plan on getting it as well, and I would like to take the HPV vaccine to take better care of my sexual health. A total possible range of scores between zero (all strongly disagree) to 20 (all strongly agree). Perceived benefits were the following questions. A total possible range of scores between zero (all strongly disagree) to

12 (all strongly agree). Self-efficacy was measured in the following three items with items such as: I am confident I can take the HPV vaccine, or I am confident I can complete all 3 doses of the

HPV vaccine. A total possible range of scores between zero (all strongly disagree) to 12 (all strongly agree). This was then followed by a question asking whether participants would take the vaccine or not, with a possible score rage of 0 (strongly disagree) to four (strongly agree).

Demographic questions were asked regarding age, sexual orientation, year in school, marital status, and participation in sexual intercourse. No information regarding HPV and its vaccination were stated on the survey. Participants were asked to answer questions to their best ability.

Confirmatory Factor Analysis

A confirmatory factor analysis was conducted after 222 samples were collected. The dependent variable (whether they would take the vaccine or not) was coded as a categorical variable; no =0, maybe = 1, yes= 2. Missing variable issues were taken care of by coding for them in the model with “missing is .” Perceived susceptibility of HPV, perceived severity of

HPV, perceived benefits of HPV, perceived barriers of HPV, cues to action to take the HPV

Methods 79 vaccine and self-efficacy in taking the vaccine were coded f1-f6, respectively. The output was standardized and a modification index at a 3.84 level was also obtained to help refine the model.

The initial model obtained was not a good fit due to a chi-square value of (df=40, p=.000)= 135, RMSEA = 0.106, and a CFI=0.631. Regression results deemed F1, F4, and F5 to be significant predictors of vaccine acceptability. The significant predictors were: perceived susceptibility, cues to action, and self-efficacy. Correlations between factors were significant but remained in the low to moderate (-.023 to 0.24); f1 with f4,f5; f2 with f3,f4; f3 with f5, f6; f4 with f5; f5 with f6, were the respective correlations. Proportion of variance accounted for were moderate to high (42%-80%) except for a few indicators with low levels (1%-32%).

Modification indices gave suggestions for improvement in the model. Based on these suggestions, q15 and q20 were eliminated from the survey. In addition q19 was correlated with q18 and q23.

Results from the model adjustments gave us a good fit model, with a chi-square value of

(df=37, p=.087)= 49.17, CFI=0.952, and a RMSEA=.039. These are all good indicators of good fit model. Parameter estimates for loadings slightly increased compared to the initial model.

Loadings (standardized) on each factor vary from moderate to high: range of 0.114 to 0.99.

Modifications to the initial model raised the factor loadings. An ideal loading varies from 0.6 to

0.9, indicating a few weak indicators are present: q11, q14, q25. This may pose a problem with questions being similar in nature. Correlations with factors were significant at an alpha level of

.05 for the following: f1 with f4,f5; f2 with f3,f4; f3 with f5, f6; f4 with f5; f5 with f6. These correlations were similar to those found in the initial model, Q14 still remained a low factor loading and insignificant at an alpha level of .05. Regression results remained the same as the

Methods 80 initial model. Proportion of variance (r-squared) values increased from the initial model, with a majority of variance ranging from 42%-99%.

Based on the results of the confirmatory factor analysis, the final model properly addressed constructs. The only issue at hand was with q14 due to its low factor loading and non- significant value in the model. This item was kept on the survey as it was deemed necessary when conducting reliability and validity measurements before its administration to the 222 samples. Re-wording of the item would change this outcome. The final instrument is presented in Appendix B.

Figure 3.4. Confirmatory Factor Analysis- Final Model

Methods 81

Researcher’s Role

The doctoral student, faculty mentor and qualitative researcher served as the primary investigators of the study. Participant recruitment, data collection, data analysis, confidentiality of forms and data were the responsibility of this team. All of them have taken classes in qualitative research methods and experimental designs prior to the study. Prior experience conducting focus groups, as well as partaking in them has been done by all of them.

Data Collection

Phase I

The study commenced after IRB approval. At the beginning of each session, participants were introduced to both facilitators and their role will be explained. The co-facilitator was taking notes on a flip chart. Each session was audio-taped and transcribed. Thereafter, participants were informed that the discussion would be kept confidential, encouraged everyone to speak, and respect each others’ opinions. A set of eleven questions were addressed at each session. At the end of each focus group, participants were thanked for their time, and an incentive was provided for their time. This incentive was a $25 gift card to Kroger.

Phase II

The study commenced after IRB approval. Participants were listed in an excel sheet and randomized using a randomizer software through the internet. Based on the randomization sequence provided, participants were given a code of “0” for intervention group and “1” for control group in SPSS. Initials of participants were used to coordinate randomization numbers

Methods 82 and groups. Thereafter, participants were contacted to attend sessions, accordingly. Changes in time were made based on participants’ availability.

At the beginning of the session, participants were provided a baseline survey and requested to provide initials only at the top of the page. Fifteen minutes were allotted to survey completion. Thereafter, administration of the program commenced. Participants in the experimental group were given an intervention based on triangulation of information from the literature review, phase I results, and a prior survey that was conducted in 2011. A powerpoint slide addressing the constructs, role plays, discussions, and brain storming sessions were components of the program. Participants that were randomly assigned to the control group also received a powerpoint presentation. Unlike the experimental group, the content in the presentation dealt with the history of sexually transmitted diseases and vaccinations. Role plays and brainstorming sessions were not included in this group. Discussions were conducted for this group as well.

At the end of both sessions, participants were given a posttest and told to write their initials at the top of the page. This enabled the researcher to pair baseline surveys with the posttest. Prior to participants leaving, the researcher made an announcement regarding a follow- up survey to be administered in one month. The researcher stressed the importance of their follow-up responses, thanked them for their participation, and distributed the $25 Kroger incentive.

Data Analysis

Phase 1

Methods 83

After all participants have left, a debriefing session will immediately occur with the co- facilitator. Notes from the discussion group, and a debriefing session will be saved on the laptop as a secured file. This is to ensure files are not hacked into and confidentiality of the focus groups is not breached. Participant names will be replaced with subject/interviewer coded names for confidentiality purposes.

Data analysis involved a constant comparative analysis approach. Themes were pre- established based on the constructs of the Health Belief Model. Comparative analysis of focus groups enabled the researcher to search for sub-themes within themes. Based on these findings, phase II of the study was established. The primary goal of the intervention was to increase knowledge, and attitude of HPV and the intent to vaccinate. Due to the ongoing comparative nature of the analysis, a three to four month time frame was allotted for this portion of the study.

Phase II

A repeated measures analysis of variance (ANOVA) were conducted for the randomized- controlled trial. Mauchly’s sphericity test was used to validate the repeated measures factor for the ANOVA. This test allowed the researchers to determine whether equality of variances existed between levels for the repeated measures, and is an assumption when conducting an

ANOVA. If the significance level of this test was below 0.05, sphericity cannot be assumed. If the assumption was violated, a Greenhouse-Geisser value was used for correction purposes. The

Greenhouse-Geisser test has been known to be a good rule of thumb when sphericity violation occurs. This was followed by a regression for the immediate and one month follow up post-tests.

For the analysis, IBM-SPSS 18.0 was the statistical software used for conducting the analysis.

Summary

Methods 84

This chapter explored the target population, instrumentation, procedures and data analysis for the study. Information regarding the content of phase I and phase II of the study were described as well as step by step procedures. In the next chapter outcomes from both phases are addressed followed by their interpretation in chapter 5.

Results 85

Results

Chapter Four

The purpose of the study was to determine predictors of HPV vaccine acceptability among college men through the qualitative approach of focus groups and to develop an intervention to increase intent to seek vaccination in the target population. Up to this date, there was a lack of qualitative research on vaccine acceptability among men and theory-based interventions that promote HPV vaccination among men. A few studies have been conducted with parents and physicians regarding HPV vaccination with girls, and a few regarding women’s awareness and acceptability. Results indicated increasing awareness of HPV, informing costs and benefits associated with the vaccine, and perceived susceptibility. Based on this information, it is crucial to obtain a further understanding of knowledge, awareness, and predictors related to

This chapter will discuss the results found from phase I and phase II of the study. Phase I was qualitative and provided information obtained from focus groups. Phase II was an intervention based on the literature review and results of phase I. Quantitative results from phase

II are provided and determination of hypothesis acceptance and rejection are noted.

Phase I

Results 86

Phase I of the study consisted of focus groups held at 425 Teachers College, University of Cincinnati. Groups were composed based on availability of participants, which led to varying number of participants per group. The questions, based on the Health Belief Model, were posed at each session and recorded. Participants were college males with ages ranging from 18-25 years and mainly Caucasian. After all sessions were completed, the audio was transcribed and sub-themes were pooled under the major themes of the Health Belief Model.

Review of the audio transcriptions indicated an overarching theme of lack of awareness of HPV and the HPVA vaccine in relation to men. In-depth analysis of responses could not be conducted due to the general lack of knowledge and awareness of the topic at hand.

The first question posed at each session was under the main theme of knowledge. A majority of the participants were unaware of HPV in men or the HPV vaccine availability for them. This becomes problematic, as knowledge would influence perceived susceptibility, perceived severity, self-efficacy, and sexual behaviors. In exploring this area, the researcher was able to find sub-themes on areas the subjects had no awareness in by thematic analysis. Thematic analysis was done by a thorough review with the advisor. Comments and phrases of similar nature were grouped together to form sub-themes and then confirmed with both reviews.

Questions developed for the focus groups were based on the Health Belief Model, with each question corresponding to a construct. A question on knowledge was also assessed. The researcher manually went through responses and highlighted repeated comments or phrases throughout the focus groups which formulated sub-themes. These sub-themes were: lack of knowledge about HPV in men/HPV vaccine, lack of awareness, and barriers in taking the vaccine.

Results 87

Perceived susceptibility, a construct within the Health Belief Model, was then assessed.

This examined the individual’s assessment of their risk in getting HPV. The main response given to the research was “ I don’t know”. After further exploration, participants began responding with “ I guess you’re more susceptible of it in college, with everyone sleeping with everyone”.

Responses started became based on general assumptions of obtaining a sexually transmitted disease. “ I concur with the others I feel it is fairly to be fairly simple to contract HPV if you are sexually active” and “ I am sure it is just as easy to contract as an STD” were other similar responses heard in the group.

The next question dealt with the theme of perceived severity, which examined the individual’s assessment of the seriousness of the condition and its potential consequences. Due to the lack of knowledge of HPV as seen with the first question, not many responses were given.

Some answers fell into assumption statements such as , “it seems like it could be serious” or “it sounds serious, or else we wouldn’t be talking about it right now”. Another individual responded with “Uhm I think that um you know if you don’t know you have it or something and you don’t try to get it check out then yea it can lead to something serious but uh other than that uh I don’t really know much but yea I think it will I think it can uh lead to something very serious”.

Self-efficacy, their confidence in taking the HPV vaccine, was also discussed. There was a consensus of being confident in taking the vaccine but participants brought up some hesitations that would hinder them from doing so. Indications of intrinsic motivation in taking the vaccine were also made. External influence from friends and family was not seen to have higher value in building self-efficacy or persuasion towards taking the vaccine. For instance some stated, “ I am abstinent, why should I get it?” or “if it’s going to help, I’ll take it regardless of what people think” or “I don’t believe in pharmaceutical companies, nothing could convince me”. Other

Results 88 comments such as “vaccines are not safe, why should I harm myself” were also made, which led towards the conversation on perceived barriers.

The question regarding barriers, allowed for a few sub-themes to emerge; these were: unawareness of vaccine availability, costs, pain, side effects, social stigma, and previous testing of the HPV vaccine. Participants indicated their lack of knowledge of the HPV vaccine, saying “

I thought it was just for girls” or “I didn’t know we could take it”. This further led to others commenting on the unawareness of where the vaccine would be available. Locations and the type of physicians offering the vaccine was an important source of information needed in their decision making process. Simultaneously information on costs and insurance coverage were of rising concern. These themes once again, fall under the over-arching theme of lack of knowledge and awareness. Increased marketing efforts and promotion towards availability and financial aid may help increase the number of men obtaining the vaccine.

The most popular were those related to pain and side effects of the vaccine. Some participants indicated they were afraid of needles or just making visits to the physician’s office.

Others mentioned stories they heard in relation to taking the vaccine such as, “the girl took the vaccine and she was mentally retarded” or “you can die from getting a vaccine”. The possibility of a vaccine damaging their day to day lifestyles served as a huge impediment in taking the vaccine. With access to endless information on the internet, participants were curious on previous testing that has been done with the vaccine to ensure safety. Participants stressed the importance of getting this information as part of their decision making process. The lack of it served as a road block in HPV prophylaxis.

Results 89

Finally the sub-theme of social stigma arose. Some comments were, “the main barrier of getting the HPV vaccine would be how you would be viewed by other people” or “I would be somewhat embarrassed to go in there and ask uh can I get this vaccination for this STD”. A few also stated, “mean I don’t have any personal barriers I think if it is something that serious um a shot would be well worth the risk to prevent something more serious” or “your trying to take a step forward in your life in becoming more healthy so I don’t think that’s something to be ashamed of” in response to the social stigma related phrases that were being acknowledged in the groups.

The final question being posed related to the benefits of the vaccine. “It’s something you don’t have to worry about anymore” was the consensus among all groups. Participants indicated that if in fact the vaccine were safe and helpful, that would serve as a benefit. At least a few people in each group stated the following: “- I think the benefit would be um getting healthier uh the problem that I can see with it is like some other people said not really worry about getting it again uh it could be a potential downfall because you kind of think that your invincible once you have this vaccine so you might give some people a little big head about actually getting the vaccine and could possibly lead to obtaining some other um health problems risks, so it definitely is a benefit but on the same sense it could also be a uh disadvantage to actually getting it but its obviously encouraged”. The potential downfall of taking the vaccine, serves as an important concern when building knowledge and awareness of HPV vaccinations.

The lack of knowledge and awareness of HPV in men was of prime interest in the focus group investigation for building an intervention. Additionally, concerns of barriers in taking the vaccine also lend a hand in the amount of information individuals have. While there is an

Results 90 understanding of a healthier life by taking the vaccine and the confidence in obtaining it, there are apprehensions in their actual behaviors due to a lack of existing information. Based on the information gathered in these groups, an intervention heavily based on knowledge is ideal.

HPV’s relationship to men, potential severity, and extensive knowledge on the vaccine are components necessary in building perceived severity and susceptibility while reducing barriers in

HPV vaccine acceptability.

Phase II

The second phase of the study consisted of 90 participants that met inclusion and exclusion criteria and were randomized into an experimental or control group. Participants were randomly assigned to the control group (n=45) and the experimental group (n=45). Random assignment was done through the use of software available online, known as the Research

Randomizer (Urbianiak & Plous, 2008). Through this generator, all 90 participants were assigned to either of the two groups.

Table 4.1 and 4.2 displays results for demographic and study variable as dependent variables and groups, experimental versus control, as the independent variable. Categorical variables were excluded from this list and chi-squares were conducted for the assessment as seen in Table 4.3. The omnibus test was done using a MANOVA. As see in the table, differences between the groups existed but interpretation was not difficult as a high amount of power was yielded. Thus, univariate pairwise comparisons were conducted, as seen in Table 4.2. Based on these comparisons, it was found that differences between groups were found for the study variables, perceived benefits and perceived barriers. Other study and demographic variables in

Table 4.2 were similar between groups. Table 4.3 further examines difference between groups at

Results 91 pretest for categorical variables. Based on the results obtained from a chi-square, differences between groups for race/ethnicity, marital status, sexual orientation, year in college, and whether participants had heard of HPV/HPV vaccine were significant, p < .05. Therefore, at baseline, difference between both groups existed.

Table 4.1 A comparison of demographic and study variables between participants in the control (n=45) and experimental (n=45) groups at pre-test using an omnibus multivariate test

Effect Estimate Value F-Statistic degrees of p-value Power Effect size (f) freedom (1-beta)

Group Pillai’s Trace 0.244 3.260 88 .003 0.959 0.244

Wilks’ Lambda 0.756 3.260 88 .003 0.959 0.244

Hotelling’s Trace 0.322 3.260 88 .003 0.959 0.244

Roy’s Largest Root 0.322 3.260 88 .003 0.959 0.244

Table 4.2 A comparison of demographic and study variables between participants in the control (n=45) and experimental (n=45) groups at pre-test using separate univariate tests

Variable Possible Obs. Control Group Experimental p-value Power Effect Range Group M (SD) size (f) Range M (SD) (1-beta)

Perceived 0-12 0-10 3.51 (3.00) 3.67 (2.99) 0.773 .001 .059 Susceptibility

Perceived Severity 0-12 4-12 9.06 (1.85) 9.11 (1.79) 0.697 .002 .067

Perceived Benefits 0-16 0-12 7.08 (2.05) 7.40 (2.12) 0.001* .118 .925

Perceived Barriers 0-12 2-11 5.35 (1.92) 5.49 (1.89) 0.004* .842 .093

Self-Efficacy 0-12 0-12 6.80 (2.59) 6.93 (2.51) 0.676 .070 .002

Cues to Action 0-15 0-13 4.35 (2.72) 4.27 (2.57) 0.116 .348 .028

Results 92

Knowledge 0-6 2-6 4.73 (0.72) 4.78 (0.64) 0.678 .070 .002

Intent to Vaccinate 0-4 0-4 2.28 (1.14) 2.16 (1.13) 0.578 .086 .004

Age 18-25 18-25 20.62 (2.44) 19.76 (1.05) 0.031 .581 .052

*significant values (p<.05)

Table 4.3 A comparison of demographic and study variables between participants in the control (n=45) and experimental (n=45) groups at pre-test using an omnibus multivariate test

Variable Control Group Experimental Chi-square p-value (n=45) Group (n=45) statistic

Race .000

African American 5 (11.1%0 6 (13.3%)

Caucasian 29 (64.4%) 35 (77.8%)

Asian 11 (24.4%) 4 (8.9%) 58.07

Hispanic 0 (0%) 0 (0%)

Mixed Race 0 (0%) 0(0%)

Sexual .000 Orientation Heterosexual 45 (100%) 44 (97.8%) 86.04

Homosexual 0 (0%) 1 (2.2%)

Sexual Activity .000

Yes 36 (80.0%) 34 (75.6%) 27.78

No 9 (20.0%) 11 (24.4%)

College level .000

Freshmen 25 (55.6%) 14 (31.1%)

Sophmore 1 (2.2%) 14 (31.1%)

Junior 2 (4.4%) 13 (28.9%) 32.00

Senior 6 (13.3%) 3 (6.7%)

Results 93

Graduate 11 (24.4%) 1 (2.2%)

Marital Status .000

Single 44 (97.8%) 45 (100%)

Married 1 (2.2%) 0 (0%) 86.04

Divorced 0 (0%) 0 (0%)

Widowed 0 (0%) 0 (0%)

Heard of HPV

Yes 34 (75.6%) 41 (91.1%) 101.67 .000

No 7 (15.6%) 3 (6.7%)

Don’t Know 4 (8.9%) 1 (2.2%)

Heard of HPV Vaccine Yes 25 (55.6%) 26 (57.8%) 24.87 .000

No 15 (33.3%) 11 (24.4%)

Don’t Know 5 (11.1%) 8 (17.8%)

Results 94

It is important to note that attrition occurred for follow-up test scores. Attrition at the one month follow up occurred, a total 16 out of 90 responded; 10 from the experimental and 6 from the control. This gave a 17.8% overall retention rate, 22.2% for the experimental and 13.3% for the control group. Possible reasons for attrition were: follow up occurred at the end of the school year, participants were occupied with final exams/ moving away from campus, lack of interest due to no incentives at initial follow up notice, incentives for participation was approved at a later date. Table 4.4 displays means and standard deviations of scores between experimental and control groups.

Results 95

Control Experimental

Pre-Test (n=45) Post – Test (n=45) Follow-up (n=6) Pre-Test (n=45) Post –Test (n=45) Follow-up (n=10)

Source Possible Obs. M SD Obs. M SD Obs. M SD Obs. M SD Obs. M SD Obs. M SD Range Range Range Range Range Range Range

Perceived 0-12 0-10 3.51 3.00 0-10 3.67 2.99 1-11 5.67 3.78 0-10 3.69 2.82 0-12 5.84 3.65 0-9 4.80 3.62 Susceptibility

Perceived 0-12 4-12 9.06 1.85 4-12 9.11 1.79 3-12 8.83 3.37 4-12 9.22 1.93 7-12 10.44 1.62 8-12 11.10 1.37 Severity

Perceived 0-16 0-12 7.08 2.05 0-12 7.40 2.13 4-9 5.67 1.86 3-9 5.76 1.59 6-12 9.04 1.02 5-10 7.90 1.97 Benefits

Perceived 0-12 2-10 5.35 1.92 2-10 5.49 1.89 5-10 6.50 1.98 3-11 6.58 1.95 0-8 3.53 2.04 0-8 4.30 2.98 Barriers

Self-Efficacy 0-12 0-12 6.80 2.59 0-12 6.93 2.51 4-10 6.00 2.10 2-12 6.60 1.88 4-12 8.49 2.05 5-12 8.80 1.87

Cues to 0-15 0-13 4.35 2.72 0-11 4.27 2.57 0-15 6.67 5.09 0-11 3.44 2.73 0-10 5.07 2.78 0-12 6.50 3.17 Action

Knowledge 0-6 2-6 4.73 0.72 2-5 4.78 0.64 2-5 4.33 1.21 2-6 4.67 0.80 2-6 5.20 1.36 4-5 4.90 0.32

Intent to 0-4 0-4 2.28 1.14 0-4 2.27 1.10 0-3 1.67 1.03 0-4 2.16 1.13 0-4 2.78 1.11 1-4 2.70 1.06 Vaccinate

Methods 96

Based on a lower sample size at follow up, repeated measures and regressions were done at two levels: one for pre-test and post-test and second for pre, post, and follow up tests for repeated measures of ANOVA. Results from repeated measures ANOVA determined whether hypothesis were accepted or rejected.

Prior to running the ANOVA assumption testing was conducted. Assumption testing for normality, independence of observations, sphericity, and homogeneity of variance were done.

Independence of observations was not violated. The Kolmogorov-Smirnov (K-S) test was used to determine normality of study variables. Table 4.5 displays results for the K-S test at pretest, posttest, and follow-up. Results from the K-S test found multiple violations as indicated by the asterisks. Histograms for those variables were viewed and outliers were found. Transformations using the natural log and log10 were done in attempts to normalize the variables. A K-S test was run for the transformed variables but significance still remained. Due to this violation, the

Friedman test was conducted in addition to the Repeated Measures ANOVA for those three variables. The Friedman test is a non-parametric equivalent for a Repeated Measures ANOVA and is used when assumptions for ANOVA are not met.

Homogeneity of variance was tested using Levene’s Test of Equality of Error Variances. Results are displayed on Table 4.6. A few violations were noted from these results, as indicated by the asterisk marks. Violations of Levene’s test can be fixed by transformations or using an alpha level of 0.01, as suggested by Tabachnick and Fidell (2007). Tabachnick and Fidell (2007) also stated that transformed data can yield to a limited interpretation. Therefore, a stringent alpha level of 0.01 was utilized for the variables in violation.

Methods 97

Sphericity was the final assumption tested using Mauchly’s test of sphericity. Table 4.7 displays results from the Mauchly’s test. Results indicated a violation of sphericity for most variables. To remedy the violation, the Greenhouse-Geisser correction was used.

Table 4.5 A summary of evaluating the normality using the Kolmogrov-Smirnov (K-S) Test

Variable Test Pretest (p- Posttest (p-value) Follow-up test (p- value) statistic statistic value) statistic

Perceived Kolmogorov-Smirnov 0.182 0.188 0.812 Susceptibility

Perceived Severity Kolmogorov-Smirnov 0.022* 0.050 0.300

Perceived Benefits Kolmogorov-Smirnov 0.000* 0.000* 0.266

Perceived Barriers Kolmogorov-Smirnov 0.100 0.335 0.968

Self-Efficacy Kolmogorov-Smirnov 0.082 0.173 0.528

Cues to Action Kolmogorov-Smirnov 0.081 0.110 0.904

Knowledge Kolmogorov-Smirnov 0.000* 0.000* 0.002*

Intent to Vaccinate Kolmogorov-Smirnov 0.001* 0.001* 0.381

*Violations of the K-S test. NOTE: sample size at follow-up was 16, while at pretest and posttest n=45.

Table 4.6 A summary of evaluating homoscedascity using Levene’s Test

Variable Test Pretest (p- Posttest (p-value) Follow-up test (p- value) statistic statistic value) statistic

Perceived Levene’s Test 0.360 0.131 0.965 Susceptibility

Perceived Severity Levene’s Test 0.552 0.597 0.042

Perceived Benefits Levene’s Test 0.031* 0.000* 0.432

Perceived Barriers Levene’s Test 0.746 0.699 0.112

Self-Efficacy Levene’s Test 0.041* 0.368 0.941

Cues to Action Levene’s Test 0.701 0.532 0.283

Methods 98

Knowledge Levene’s Test 0.258 0.841 0.012

Intent to Vaccinate Levene’s Test 0.464 0.931 0.894

*Violations. NOTE: sample size at follow-up was 16, while at pretest and posttest n=45.

Table 4.7 A summary of evaluating sphericity using Mauchly’s Test

Variable Test Mauchly’s p-value Mauchly’s W p-value W (pre/post) (pre/post/follow- (pre/post/follow- (pre/post) up) up)

Perceived Mauchly’s Test 1.000 .000 0.058 .000 Susceptibility

Perceived Mauchly’s Test 1.000 .000 0.816 .266 Severity

Perceived Mauchly’s Test 1.000 .000 0.596 .035 Benefits

Perceived Mauchly’s Test 1.000 .000 0.677 .079 Barriers

Self-Efficacy Mauchly’s Test 1.000 .000 0.966 .796

Cues to Action Mauchly’s Test 1.000 .000 0.399 .003

Knowledge Mauchly’s Test 1.000 .000 0.809 .253

Intent to Mauchly’s Test 0.596 .035 1.000 .000 Vaccinate

Methods 99

Results for Repeated Measures ANOVA

Hypothesis 1

H0: There will be no statistically significant difference in change (from pre, post, and one month follow up) in perceived susceptibility in the intent to take the HPV vaccine between experimental and comparison groups.

The hypothesis was not rejected. No significant interaction for time and group was found, as seen in Table 4.8.

Table 4.8 Summary of Repeated Measures Analysis of Variance for Perceived Susceptibility Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow- up*

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 871.200 871.200 57.677 0.693 0.011

Error 14 211.467 15.105

Within Subjects

Time 1 20.833 20.833 1.522 0.238 0.066

Time*Group 1 3.333 3.333 0.243 0.266 0.043

Error 14 191.667 13.690

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Methods 100

Hypothesis 2

H0: There will be no statistically significant difference in change (from pre and post-test) in perceived susceptibility in the intent to take the HPV vaccine between experimental and comparison groups

The hypothesis was rejected. Interaction between time and groups (p=.000) and over time

(p=.000) was significant. Initial mean score for the control group was 3.51+/-3.00 and at post- test, the mean score was 3.67 +/- 2.99. For the experimental group, the initial mean score was

3.69+/- 2.82 and a post-test mean score of 5.84+/-3.65. A medium effect size was seen between groups (ƒ=.308) and over time (ƒ=.373). Table 4.9 displays results from the ANOVA.

Table 4.9 Summary of Repeated Measures Analysis of Variance for Perceived Susceptibility Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post- Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 62.422 62.422 3.379 .069 .037

Error 88 1624.89 18.476

Within Subjects

Time 1 60.089 60.089 52.401 .000 .373

Time*Group 1 45.000 45.00 39.242 .000 .308

Error 88 100.911 1.147.

______

Methods 101

A significant increase in perceived susceptibility was seen with the experimental group over time.

Hypothesis 3

H0: There will be no statistically significant difference in change (from pre, post, and one month follow up) in perceived severity in the intent to take the HPV vaccine between experimental and comparison groups.

The hypothesis was rejected, as no significance was found. Table 4.10 displays results from the ANOVA.

Table 4.10 Summary of Repeated Measures Analysis of Variance for Perceived Severity Between Experimental (n=10)and Control Groups(n=6) and Between Pre-Test, Post-Test, and Follow-up

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 10.272 10.272 2.858 0.113 0.050

Error 14 50.311 3.594

Within Subjects

Time 1 2.852 2.852 0.724 0.409 0.163

Time*Group 1 12.352 12.352 3.138 0.098 0.144

Error 14 55.117 3.937

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Methods 102

Hypothesis 4

H0: There will be no statistically significant difference in change (from pre and post-test) in perceived severity in the intent to take the HPV vaccine between experimental and comparison groups.

Interaction between time and groups (p=.000) and over time (p=.000) was significant.

The hypothesis was rejected. Additionally, statistical significance was also found between groups (p=.035), as a main effect; this had a low effect size (ƒ=.05). Initial mean score for the experimental group was 9.22+/-1.93 and at post-test, the mean score was 10.444 +/- 1.62. For the control group, the initial mean score was 9.07+/- 1.85 and a post-test mean score of 9.11+/-1.79.

A low effect size was seen with the difference in time (ƒ=0.16) and with time and groups

(ƒ=0.14). Table 4.11 displays results from the ANOVA.

Table 4.11 Summary of Repeated Measures Analysis of Variance for Perceived Severity Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post- Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 24.939 24.939 4.598 .035 0.05

Error 88 477.289 5.424

Within Subjects

Time 1 18.050 18.050 17.108 .000 0.16

Time*Group 1 15.606 15.606 14.791 .000 0.14

Methods 103

Error 88 92.844 1.055

______

An increase in perceived severity over time with the experimental group was seen.

Friedman test was also conducted for this variable as normality was violated. Results from the

Friedman test were significant (p=.001) and synonymous to the results found in the repeated measures of ANOVA. Table 4.12 displays results from the Friedman test.

Table 4.12 Summary of Friedman Test Results for Perceived Severity

Variable Mean Rank Mean Rank Chi-square degrees of p-value freedom (pretest) (posttest)

Perceived 1.39 1.61 11.77 1 .001 Severity

Hypothesis 5

H0: There will be no statistically significant difference in change (from pre, post, and one

month follow up) in perceived benefits in the intent to take the HPV vaccine between

experimental and comparison groups.

The hypothesis was rejected as the interaction between time and groups (p=.011) was significant. Initial mean score for the experimental group was 5.76+/-1.60, at post test, the mean score was 9.04 +/- 1.02, and at follow up the mean score was 7.9 +/- 1.97. For the control group, the initial mean score was 7.08+/- 2.05, a post-test mean score of 7.40+/-2.12, and at follow up the mean score was 5.67 +/- 1.86. The difference in time had a medium effect size (ƒ=0.432).

Methods 104

Table 4.13 displays results from the ANOVA.

Table 4.13 Summary of Repeated Measures Analysis of Variance for Perceived Benefits Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow-up

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Groups 1 11.756 11.756 2.717 .122 .163

Error 14 60.578 4.327

Within Subjects

Time*Group 1 23.852 23.852 8.537 .011 .432

Error 14 59.867 4.276

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

The experimental group showed higher improvement than the control between pre and post-test. Friedman’s test was also conducted as the normality violation was violated by the perceived benefits variable. Table 4.14 shows results from the test which is in congruence with the ANOVA results.

Methods 105

Table 4.14 Summary of Friedman’s Test for Perceived Benefits at Pretest, Posttest, and Follow- up Test

Variable Mean Rank Mean Rank Mean Chi-square degrees of p-value Rank freedom (pretest) (posttest) (follow-up test)

Perceived 1.50 2.53 1.97 11.34 2 .003 Benefits

Hypothesis 6

H0: There will be no statistically significant difference in change (from pre and post-test) in

perceived benefits in the intent to take the HPV vaccine between experimental and

comparison groups.

As for pre and post-test an interaction between time and groups (p=.000) and over time

(p=.000) was significant. The hypothesis was rejected. At pre-test there was statistically significant difference in mean scores between experimental and control groups. Initial mean score for the experimental group was 5.76+/-1.60 and at post-test, the mean score was 9.04 +/-

1.02. For the control group, the initial mean score was 7.09+/- 2.05 and a post-test mean score of

7.40+/-2.13. A medium effect size was seen in the difference between time (ƒ=.677) and with groups and time (ƒ=.590). A large increase in mean scores was seen with the experimental groups improved over time, as seen in Table 4.15.

Methods 106

Table 4.15 Summary of Repeated Measures Analysis of Variance for Perceived Benefits Between Experimental (n=45) and Control Groups(n=45) and Between Pre-Test and Post-Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 1.089 1.089 0.202 .654 .002

Error 88 477.289 5.424

Within Subjects

Time 1 145.800 145.800 184.758 .000 .677

Time*Group 1 99.756 99.756 126.410 .000 .590

Error 88 69.444 0.789

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

The experimental group showed higher improvement at post-test. Friedman test was also conducted for this variable as normality was violated. Results from the Friedman test were significant (p=.000) and synonymous to the results found in the repeated measures of ANOVA.

These are seen in Table 4.16 below.

Table 4.16 Friedman’s Test for Perceived Benefits at Pretest and Posttest

Variable Mean Rank Mean Rank Chi-square degrees of p-value freedom (pretest) (posttest)

Perceived 1.24 1.76 46.00 1 .000 Benefits

Methods 107

Hypothesis 7

H0: There will be no statistically significant difference in change (from pre, post, and one

month follow up) in perceived barriers in the intent to take the HPV vaccine between

experimental and comparison groups.

The hypothesis was not rejected. The main effect of groups was significant (p=.039) with a medium effect size (ƒ=.269). Initial mean score for the control group was 5.36+/-3.78, at post- test, the mean score was 5.49 +/- 1.89 and at follow up the mean score was, 6.50 +/- 1.97. For the experimental group, the initial mean score was 6.58+/- 1.95 at post-test mean score of 3.53+/-

2.04, and at follow up the mean score was 4.30 +/- 2.98. Table 4.17 displays results.

4.17 Summary of Repeated Measures Analysis of Variance for Perceived Barriers Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test, Post-Test, and Follow-up

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 22.050 22.050 5.156 .039 .269

Error 14 59.867 4.276

Within Subjects

Time 1 4.800 4.800 0.838 .375 .114

Time*group 1 12.675 12.675 2.213 .159 .138

Error 14 80.200 5.729

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Methods 108

The control group showed an increase in perceived barriers over the three time periods, while the experimental group showed a reduction between pre and post-test. A slight increase in barriers occurred at follow up for the experimental group.

Hypothesis 8

H0: There will be no statistically significant difference in change (from pre and post-test) in

perceived barriers in the intent to take the HPV vaccine between experimental and

comparison groups.

For pre and post-test, an interaction between time and groups (p=.000) and over time (p=.000) was significant. Initial mean score for the experimental group was 6.58+/-1.94 and at post-test, the mean score was 3.53 +/- 2.04. For the control group, the initial mean score was 5.36+/- 1.92 and a post-test mean score of 5.49+/-1.89. Over time a reduction in barriers for the experimental group was seen. A medium effect size in the difference between time (ƒ=.368) and time and groups (ƒ=.410) was found. Results from the ANOVA are displayed in table 4.18.

Methods 109

4.18 Summary of Repeated Measures Analysis of Variance for Perceived Barriers Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 6.050 6.050 1.052 .308 .012

Error 88 506.178 5.752

Within Subjects

Time 1 95.339 95.339 51.296 .000 .368

Time*Group 1 113.606 113.606 61.125 .000 .410

Error 88 163.556 1.859

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Hypothesis 9

H0: There will be no statistically significant difference in change (from pre, post, and one

month follow up) in self-efficacy in the intent to take the HPV vaccine between experimental

and comparison groups.

This hypothesis was rejected. Interaction between time and groups (p=.031) was significant.

Initial mean score for the control group was 6.80+/-2.59 at post-test, the mean score was 6.93 +/-

2.50, and at follow-up the mean score was 6.00 +/- 2.10. For the experimental group, the initial mean score was 6.60 +/- 1.87, a post-test mean score of 8.49 +/- 2.05, and at follow up the mean score was 8.80 +/- 1.87. The experimental group showed a consistent significant increase in self-

Methods 110 efficacy at posttest and follow-up compared to the control group. A low effect size was seen with time and groups (ƒ= .178). Results are depicted in Table 4.19.

4.19 Summary of Repeated Measures Analysis of Variance for Self-Efficacy Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow-up ______Source df SS MS F p-value Effect Size ______Between Subjects Group 1 26.068 26.068 4.840 .045 .027 Error 14 75.411 5.387 Within Subjects Time 1 10.208 10.208 4.375 .055 .224 Time*Group 1 13.333 13.333 5.714 .031 .178 Error 14 32.667 2.333

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Hypothesis 10

H0: There will be no statistically significant difference in change (from pre and post-test) in

self-efficacy in the intent to take the HPV vaccine between experimental and comparison

groups.

As for pre and post-test, the hypothesis was rejected. Interaction between time and groups

(p=.000) and over time (p=.000) was significant. Initial mean score for the experimental group

Methods 111 was 6.60+/-1.88 and at post test, the mean score was 8.49 +/- 2.05. For the control group, the initial mean score was 6.80+/- 2.59 and a post-test mean score of 6.93+/-2.50. The experimental group showed significantly higher improvement between pretest and posttest than the control.

Table 4.20 depicts results from the ANOVA.

4.20 Summary of Repeated Measures Analysis of Variance for Self-Efficacy Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 20.672 20.672 2.418 0.124 0.027

Error 88 752.22 8.548

Within Subjects

Time 1 46.006 46.006 25.331 0.000 0.224

Time*Group 1 34.672 34.672 19.091 0.000 0.178

Error 88 159.822 1.816

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Hypothesis 11

H0: There will be no statistically significant difference in change (from pre, post, and one

month follow up) in cues to action in the intent to take the HPV vaccine between

experimental and comparison groups.

Methods 112

The hypothesis was partly rejected. Time was found to be significant (p=.038) variable but groups (p=.776) and the interaction between time and groups (.628) was not. The mean score for the control group at pre-test was 4.356 +/- 2.723, 4.267 +/- 2.571 at post-test, and 6.67 +/- 5.086 at follow up. The experimental group’s mean score at pre-test was 3.44 +/- 2.727, 5.067 +/-

2.783 at post-test, and 6.500 +/- 3.171 at follow up. Over time, the experimental group showed a significant increase in cues to action at all three time points. The difference over time had a low effect size (ƒ=0.187). Table 4.21 displays results from the ANOVA.

4.21 Summary of Repeated Measures Analysis of Variance for Cues to Action Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow-up

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 1.422 1.422 0.084 0.776 0.006

Error 14 235.91 16.851

Within Subjects

Time 1 48.769 48.769 5.274 0.038 0.187

Time*Group 1 2.269 2.269 0.245 0.628 0.024

Error 14 129.450 9.246

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Methods 113

Hypothesis 12

H0: There will be no statistically significant difference in change (from pre and post test) in

cues to action in the intent to take the HPV vaccine between experimental and comparison

groups.

For pre and post test, the hypothesis was rejected. Interaction between time and groups and over time was significant. Initial mean score for the experimental group was 3.44+/-2.73 and at post test, the mean score was 5.01 +/- 2.78. For the control group, the initial mean score was 4.36+/-

2.72 and a post-test mean score of 4.27+/-2.57. The experimental group had an increase in cues to action over time, while the control group declined. Results from the ANOVA are displayed in table 4.22.

4.22 Summary of Repeated Measures Analysis of Variance for Cues to Action Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 .139 .139 .012 .915 0.000

Error 88 1059.91 12.044

Within Subjects

Time 1 26.450 26.450 10.340 .002 0.105

Time*Group 1 32.939 32.939 12.876 .001 0.128

Error 88 225.11 2.558

______

Figure 4. Cell Mean Graphs for Cues to Action at pre and post-test

Methods 114

Hypothesis 13

H0: There will be no statistically significant difference in change (from pre, post, and one

month follow up) in knowledge with actually taking the HPV vaccine between experimental

and comparison groups.

This hypothesis was not rejected as no significance was found. Friedman’s test was also conducted as a violation for normality was found for this variable. Results from the test are synonymous to the results from the ANOVA, as seen in table 4.23 and 4.24, respectively.

Methods 115

4.23 Summary of Repeated Measures Analysis of Variance for Knowledge Between Experimental (n=45), Control Groups(n=45) at Pre-Test, Post-Test and Follow-up

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 614.41 614.41 0.00 0 .939 0.028

Error 14 5.848 0.418

Within Subjects

Time 1 0.408 0.408 0.604 0.450 0.095

Time*Group 1 1.408 1.408 2.083 0.171 0.095

Error 14 9.467 0.676

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Table 4.24 A Summary of Friedman’s Test for Knowledge

Variable Mean Rank Mean Rank Mean Chi-square degrees of p-value Rank freedom (pretest) (posttest) (follow-up test)

Knowledge 2.03 2.16 1.81 3.26 2 .196

Figure 4. Cell Means for Knowledget at Pre, post, and follow-up

Methods 116

Hypothesis 14

H0: There will be no statistically significant difference in change (from pre and post) in

knowledge with actually taking the HPV vaccine between experimental and comparison

groups.

As for pre and post-test, the hypothesis was not rejected. The main effect of time

(p=.000) was found to be statistically significant, which suggests improvement in scores over time. The control group began with a mean of 4.73 +/- 0.72 and increased to 4.77 +/- 0.64, while the experimental group had an initial mean of 4.67 +/- 0.80 and ended with a mean of 5.2 +/-

1.36. The experimental group had a lower mean at pre-test than the control group and over time both groups improved. A Friedman’s test was also conducted due to the violation of normality found with this study variable. The difference over time had a low effect size (ƒ=.049). Results were synonymous to the ANOVA as seen in tables 4.25 and 4.26, respectively.

Methods 117

4.25 Summary of Repeated Measures Analysis of Variance for Knowledge Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 0.002 0.002 0.00 0.939 0.018

Error 88 29.495 0.335

Within Subjects

Time 1 434.838 434.838 1608.73 0.000 0.049

Time*Group 1 0.242 0.242 0.894 0.347 0.035

Error 88 73.556 0.836

______

Table 4.26 Summary of Friedman’s Test for Knowledge at pretest and posttest

Variable Mean Rank Mean Rank Chi-square degrees of p-value freedom (pretest) (posttest)

Knowledge 1.44 1.56 5.00 1 .025

Figure 4. Cell Mean Graphs for Knowledge at Pre and Post-test

Methods 118

Hypothesis 15

H0: There will be no statistically significant difference between experimental and

comparison groups in HPV vaccine acceptability.

This hypothesis was rejected. An interaction between time and groups (p=.000) and over time(p=.000) was found to be significant. The mean score for intent to vaccinate in the experimental group at pre-test was 2.156 +/- 1.127, 2.77 +/- 1.106 at post-test, and 2.700 +/-

1.059 at follow-up. For the control group, the mean score for intent to vaccinate at pre-test was

2.289 +/- 1.141, 2.267 +/- 1.095 at post-test, and 1.667 +/- 1.033 at follow up. Over time the experimental group’s intent to vaccinate at post-test increased but then dropped at follow up, while the control group’s intent decreased over post-test and follow-up. Friedman’s test was also conducted due to the violation of normality for this variable. The difference over time had a low effect size (ƒ=.072) as well as the interaction between time and groups (ƒ=.227). Results were congruent with the ANOVA, as seen in tables 4.27 and 4.28.

Methods 119

4.27 Summary of Repeated Measures Analysis of Variance for Intent to Vaccinate Between Experimental and Control Groups and Between Pre-Test, Post-Test, and Follow-up

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 0.235 0.235 0.117 0.737 0.008

Error 14 28.078 2.006

Within Subjects

Time 1 4.050 4.050 20.047 0.000 0.072

Time*Group 1 4.672 4.672 23.128 0.000 0.227

Error 14 17.778 0.202

______

* NOTE: sample size at follow-up was 16 (control group n=6, experimental group n=10), while at pretest and posttest n=45.

Figure 4. Cell Mean Graphs for Intent to Vaccinate at Pre, Post, and Follow-up

Methods 120

Hypothesis 16

At pre and post test, this hypothesis was rejected. An interaction between time and groups over time was found. The mean score for intent to vaccinate in the experimental group at pre-test was 2.156 +/- 1.127 and, 2.77 +/- 1.106 at post-test. For the control group, the mean score for intent to vaccinate at pre-test was 2.289 +/- 1.141 and, 2.267 +/- 1.095 at post-test. Over time, a significant change in intent to vaccinate was seen with the experimental group. Friedman’s test was also conducted due to the violation of normality for this variable.

4.28 Summary of Repeated Measures Analysis of Variance for Intent to Vaccinate Between Experimental (n=45)and Control Groups(n=45) and Between Pre-Test and Post-Test

Methods 121

______

Source df SS MS F p-value Effect Size

______

Between Subjects

Group 1 1.66 1.606 0.700 0.405 0.008

Error 88 201.956 2.295

Within Subjects

Time 1 4.050 4.050 20.047 0.000 0.186

Time*Group 1 4.672 4.672 23.128 0.000 0.208

Error 88 17.778 0.202

______

Figure 4. Cell Mean Graphs for Intent to Vaccinate at Pre and Post-test

4.29 Summary of Repeated Measures Analysis of Covariance for Intent to Vaccinate Between Experimental (n=45) and Control Groups(n=45) and Between Pre-Test (n=90), Post-Test (n=90), and Follow-up (n=16)

Methods 122

Source df SS MS F p-value

Between Subjects

Groups 1 0.682 0.682 1.575 .233

Prebarriers 1 0.030 0.030 0.070 .796

Prebenefits 1 0.452 0.452 1.045 .327

Error 12 5.192 0.433

Within Subjects

Time 1 .470 0.470 3.452 .089

Time*Group 1 .637 0.637 4.634 .052

Time*prebarriers 1 1.183 1.183 8.615 .012

Time*prebenefits 1 .005 0.005 .034 .856

Error 12 1.648 0.137

Regression Analysis

Regressions were also conducted using change scores to determine predictors of intent to get vaccine. Multiple regressions with change scores for all three time points as well as for pre and post-test only were conducted. A stepwise method was selected when running analysis. The apriori criteria of probability of the predictor in the model was chosen as less than or equal to

0.05 and for removing the predictor as greater than or equal to 0.10. The predictors used were knowledge, perceived susceptibility, perceived severity, perceived barriers, perceived benefits, self-efficacy, and cues to action.

Methods 123

Multiple regressions were conducted using the change variables from follow-up and pre-test and follow-up and post-test. Table 4.30 displays the means and standard deviations for the change variables.

Table 4.30 Distribution of Means and Standard Deviations for Change in Health Belief Model Constructs, Knowledge, and Intent to Vaccinate

Posttest- Pretest Followup- Pretest Followup-Posttest

Variable M SD M SD M SD

Perceived Susceptibility 1.16 1.81 1.50 5.09 0.50 5.87

Perceived Severity 0.63 1.56 0.94 2.99 0.19 2.79

Perceived Benefits 1.80 1.95 1.56 2.90 -1.13 1.78

Perceived Barriers -1.46 2.50 -1.13 3.52 0.63 2.96

Self-Efficacy 1.01 2.09 1.50 2.48 0.56 2.16

Cues to Action 0.77 2.41 2.69 4.19 -1.63 4.24

Knowledge 0.29 1.31 -0.13 1.20 -0.38 2.16

Intent to Vaccinate 0.30 0.71 0.56 1.36 0.43 1.31

The first set of regressions indicated perceived benefits (p=.004) held a significant positive relationship towards intent to vaccinate. The model had an adjusted R2 of 0.453, which indicated this predictor accounted for 45.3% variance regarding whether participants would take the vaccine. A tolerance of 1.00 and a VIF score of 1.00 were obtained for the model, indicating a linear relationship with the other HBM predictors entered in the model. These values indicate no multi-collinearity amongst study variables. The parameter estimates are summarized in table

4.31.

Table 4.31 Parameter Estimates from the Final Regression Model for change in Intent to Vaccinate at Pre-test, and follow-up test using Follow-up and Pre-test change scores in Health Belief model (HBM) constructs (R2 = 0.453)

Methods 124

______

Source Unstd. Coeff. Std. Error Std. Coefficients Beta t p-value

______

(constant) 0.067 0.299 0.244 0.828

Perceived benefits 0.317 0.093 0.673 3.407 0.004

A regression analysis for the change from follow-up and post-test scores for the Health

Belief Model variables did not find a significant model.

Another set of regression analysis were also conducted with pretest and posttest variables. Results for pre-test and post-test regression analysis indicated self-efficacy for taking the vaccine (p=0.000), perceived barriers (p=0.007), and perceived severity (p=0.004) held a significant positive relationship towards vaccine acceptability. The model had an adjusted R2 of

0.351, which indicated that these three predictors accounted for 35.1% variance regarding whether participants would take the vaccine. Tolerance for perceived severity was 0.687 with a

VIF of 1.46, for perceived barriers the tolerance was 0.725 with a VIF of 1.38, and for self- efficacy the tolerance was 0.711 with a VIF of 1.41. These values indicate no multi-col1inearity amongst study variables. The parameter estimates are summarized in the table 4.32.

Table 4.32 Parameter Estimates from the Final Regression Model for change in Intent to Vaccinate at Pre-test and posttest using change scores in Health Belief Model (HBM) predictors (R2 = 0.593)

______

Source Unstd. Coeff. Std. Error Std. Coefficients Beta t p-value

Methods 125

______

(constant) 0.095 0.073 1.298 0.198

Perceived severity -0.137 0.046 -0.301 -2.947 0.004

Perceived barriers -.081 .029 -0.284 -2.755 .007

Perceived self-efficacy .173 .036 .508 4.851 0.000

Summary

In this chapter, results from Phase I and Phase II were detailed. For phase I, over-arching themes were established from focus group discussion. Phase II involved quantitative analyses which began with a depiction of descriptive statistics for study and demographic variables at pretest. This then lead to establishing assumptions for repeated measures and regression analysis.

Results from those tests indicated a few variables that violated and remedies for those issues were applied. Due to attrition at follow-up, not much can be stated for all three time points but results from pretest and posttest indicated significant positive change in the intervention group.

The next chapter will delve into a further discussion of these results.

Methods 126

Conclusions 127

Conclusions

Chapter Five

The purpose of the study was to determine predictors of HPV vaccine acceptability among college men through the qualitative approach of focus groups and to develop an intervention to increase intent to seek vaccination in the target population. Up to this date, there was a lack of qualitative research on vaccine acceptability among men and theory-based interventions that promote HPV vaccination among men. A few studies have been conducted with parents and physicians regarding HPV vaccination with girls, and a few regarding women’s awareness and acceptability. Results indicated increasing awareness of HPV, informing costs and benefits associated with the vaccine, and perceived susceptibility. Based on this information, it is crucial to obtain a further understanding of knowledge, awareness, and predictors related to

This chapter will discuss and interpret the results found from phase I and phase II of the study, limitations of the study, implications for practice, and recommendations for future research.

Discussion

Phase I

Fifty participants were recruited for phase I of the study. A total of six groups were assembled according to availability of participants. Two of the three groups consisted of 12 participants, while the others had five to six individuals. Focus groups were audio recorded and later

Conclusions 128 transcribed. A majority of participants were single, heterosexual, Caucasian, early college

(freshmen/sophomore) level males from the University of Cincinnati.

Focus group analysis indicated an over-arching theme of lack of knowledge and awareness of

HPV and the HPV vaccine in relation to men. The researcher was not able to delve into further detail regarding their perceived severity and susceptibility, cues to action, and self-efficacy. This was primarily due to participants repeating their lack of awareness/knowledge regarding HPV and the HPV vaccine. Detailed discussions on what participants were unaware of, barriers with their existing knowledge, and potential benefits they perceived about the vaccine were established.

Results found from the focus groups had some similarities to those found by Wong (2008).

Wong (2008) also used the focus group technique in determining attitudes towards the HPV vaccine in multiethnic women. While that study was with multi-ethnic females, results indicated the following themes that emerged from the group: lack of knowledge of HPV/HPV vaccine, low perceived risk, adverse effects, promote promiscuity, social stigma, parental barrier, halal, cost, physician recommendation, and mandatory vaccination. For this study, halal (meats allowed under Islamic dietary guidelines), parental barriers, physician recommendations, and mandatory vaccination were not pertinent. The remainder of the sub-themes was similar with college males that participated in the focus groups. Despite different pool of participants, concerns and lack of awareness/knowledge are apparent between both groups.

Another study by Katz, Reiter, Heaner, Ruffin, Post, and Paskett (2009) shared similarities to the results found from the focus groups. Questions in the focus group for the Katz, Reiter, Heaner et al. (2009) study were specified to the areas of knowledge, barriers, beliefs, and attitudes about

Conclusions 129 the HPV vaccine at an individual and community level. The following themes emerged from the groups: barriers, knowledge, attitudes and beliefs, and suggestions for educational materials and programs. Concerns across the board were: general lack of knowledge of HPV/HPV vaccine, limited access to healthcare, costs, side-effects (short and long term), promotion of promiscuity, cervical cancer due to genes/environment, lack of trust with the medical community and those from outside the community/pharmaceutical companies. An overall acceptance for the vaccine was found. Issues of cervical cancer were not applicable to the participants in the focus group for this study and lack of trust with the medical community was not expressed.

Hernandez, Wilkens, Shvetsov, Goodman, Ning, and Kaopua (2010) surveyed college men between the ages of 18 and 79 on awareness, attitudes and intentions to vaccinate. Results indicated side effects, efficacy, safety, and costs as main predictors in vaccinating. Cost issues were of major concern for men 18-26 years old, but were more likely to get vaccinated than other age groups. Yet again, these findings are parallel to those found with the focus groups with college males from the University of Cincinnati.

Overall, results found from the study are comparable to the themes emerged from previous focus groups. It is important to note that previous focus groups were comprised of females but similar concerns were expressed. The lack of awareness and knowledge related to HPV and the HPV vaccine were driving forces in the development of an intervention to enhance vaccine acceptability.

Phase II

Ninety participants were recruited for phase II. They were primarily single, heterosexual,

Caucasian, early college (freshmen/sophomore) level, about 20.6 year old males from the

Conclusions 130

University of Cincinnati. Baseline testing for study and demographic variables were done to assess if any differences between groups occurred. Results from univariate tests indicated differences in groups for perceived benefits and barriers, while chi-squares indicated differences in demographic variables. While randomization was done using computer software, difference still remained between groups. This could be attributed to the fact that participants, 50, from phase I signed up for Phase II as well. About 56% of participants rolled over from phase I and randomly assigned to intervention or control groups.

Assumption testing for phase II led to some violations that had to be taken into account.

In terms of normality, transformations could not be done to meet assumption requirements. This was attributed to a few outliers found for each construct. Therefore, a Friedman’s test, nonparametric, was conducted. Mauchly’s test of sphericity was also violated. Violations were seen for all baseline measurements, but improvements were seen at post-test and follow-up.

Greenhouse-Geisser values were used for the violations in order to meet this assumption.

Homogeneity of variance was also tested and violations were also found. A stringent alpha of

0.01 was used to remedy the solution. Finally, multi-collinearity was also assessed for regressions. These scores indicated no violations.

Thirteen out of sixteen hypotheses were rejected. There was no change in perceived susceptibility between groups nor was change in knowledge between groups at pre-test, post-test and follow-up found. Results obtained from pre, post, and follow-up test analysis indicated improvements within the experimental group. While the sample size for follow up was small, those results indicated remnants of intervention knowledge were still apparent. This was seen with higher mean scores for constructs, knowledge, and intent to vaccinate for the experimental group than the control group. Repeated measures ANOVA among the Health Belief Model

Conclusions 131 constructs, and intent to vaccinate showed the experimental group had improved scores over time significantly than the control group This indicated effectiveness of the intervention provided to participants. Significance over time was seen with knowledge, as mean scores for both groups increased between pre and post-test but at follow up no significance over time was found.

Similar significance over time was also found with cues to action but over time, the experimental group showed an increase in cues to action while the control group showed some fluctuation.

The control group had a reduction in cues to action at post-test but then increased again at follow-up. Results at follow-up are contributable to attrition, which did not allow for a valid comparison of scores with baseline and posttest scores. Despite this limitation, ANOVA’s indicated maintenance of intervention information over time.

With regards to awareness of the vaccine at baseline, 97.8% heard of HPV but only 91.1% were aware of the vaccine, while 2.2% had never heard of HPV and 8.9% were unaware of the vaccine. This was higher than the levels found by Reiter, Brewer, McRee, Gilbert, Smith (2010).

Reiter et al. (2010) found 73% of participants were aware of the vaccine. Reasons for higher awareness are contributable to participants that rolled over from phase I of the study into phase

II. All fifty participants from phase I entered into phase II of the study. Another reason that may have led to higher awareness could have been due to participants looking up information prior to their arrival or having heard about HPV/HPV vaccines through friends that encouraged participation in the study,

In terms of vaccine acceptability 37.8% were in favor for intent to vaccinate and 28.9% were strongly in favor towards intent to vaccinate with the experimental group. At follow up with 10 participants, 11.1% and 4.4% agreed and strongly agreed to vaccinate, respectively. For the control group at post-test, 28.9% and 15.6% agreed or strongly agreed towards vaccine

Conclusions 132 acceptability, respectively, while only 2.2% at a follow up of six, had the intent to vaccinate.

Repeated measures of ANOVA for intent to vaccinate was significant at all three time (p=.000) and at pre and post-test (p=.000), indicating change over time and in groups. A decrease was seen in the control group, while an increase in intent to vaccinate was seen with the experimental group. These results indicate effectiveness of the information provided in the intervention, as participants’ willingness to vaccinate remained high at post and follow-up tests.

In comparison to previous studies, vaccine acceptability results were moderate. Liddon, Hood,

Wynn, Markowitz (2010) reported 74%-78% acceptability of the vaccine among college males.

Gerend and Barley (2009) conducted a random assigned self-protection versus self-protection and partner protection about HPV and the vaccine among heterosexual college males. Results indicated a moderate level of interest in taking the vaccine, regardless of the group they were assigned to. These findings are similar to acceptability among participants in the randomized intervention.

Regression analysis for pretestand follow –up tests indicated perceived benefits (p=.010) as the significant predictor in vaccine acceptability. The model had an adjusted R2 of 0.453, which indicated that perceived benefits could account for 45.3% of variance in participants’ ability to take the vaccine. For the regression analysis at pre and post-test only for Health Belief Model constructs and knowledge, self-efficacy for taking the vaccine (p=0.000), perceived barriers

(p=0.007), and perceived severity (p=0.004) held a significant positive relationship towards vaccine acceptability. The model had an adjusted R2 of 0.593, which indicated the predictors could account for 59.3% of variance in participants’ ability to take the vaccine.

Conclusions 133

For baseline and follow-upperiods, a positive relationship was seen between perceived benefits and intent to vaccinate. The higher the perceived benefits for an individual, an increase in their intent to vaccinate existed. As for the pretest and posttest periods, a positive relationship with self-efficacy was seen in predicting intent to vaccinate. A negative relationship with perceived severity and barriers was indicated with intent to vaccinate. Thus, as perceived severity and barriers decrease, the more likely the individual would want to vaccinate against HPV. Providing information to reduce barriers and increase self-efficacy would enable a higher intent to vaccinate.

In comparison to a recent study looking at predictors of vaccine acceptability among college men at the University of Cincinnati by the researchers, self-efficacy (p=0.000), cues to action

(p=0.000), and perceived susceptibility (p=0.005) held a significant positive relationship towards vaccine acceptability. The model had an adjusted R2 of 0.480, which indicated that HBM constructs could account for 48% variance in participants’ ability to take the vaccine. At that time, a majority of the participants were neutral about taking the vaccine.

Self-efficacy was the common predictor for this study and the one conducted earlier by the researcher. Cues to action and perceived susceptibility were not significant predictors after an intervention. Interestingly, reductions in barriers and severity were more likely predictors in vaccination than cues to actions or increasing susceptibility. Barriers were heavily brought up in phase I as reason not to vaccinate. Information at the intervention alleviating these concerns were brought up, which may have surged significance for this pool of participants. This in turn would affect their self-efficacy. As for reduction in severity, not making HPV and the HPV vaccine a daunting item in their minds may have contributed towards acceptability of the vaccine versus

Conclusions 134 the opposite effects. Findings from phase II share similarities with previous research, but there still exista limited number of studies exploring reasons towards the intention to vaccinate.

Limitations

Phase I

There were some limitations in running focus groups. The primary limitation was with the logistics. Groups were developed based on the time availability of participants. This sometimes meant that groups from one class would show up together, which could serve as an inhibitor in individuals freely talking. At the same time, participants were told no readings on the topic had to be done prior to participation but there was at least one individual that violated the rule. When going through a question, at least one or two individuals would mention some research they conducted online prior to arriving at the group. Their recall of information may have altered responses with the rest of the group members. Overall, lack of knowledge limited answers to questions and hindered the researcher from in-depth qualitative analysis. Outside of these concerns, no other limitations were found.

Participant demographics served as a limitation with the study. Only students from the

University of Cincinnati were recruited. Student from other local universities could have altered the results obtained. Most of the participants were Caucasian males. A more diverse group may have responded differently with the intervention materials. Finally, most of the men in the study were heterosexual. A higher level of homosexual males would have altered the responses.

Phase II

Conclusions 135

One of the main limitations for the second phase dealt with attrition at follow up. Initial recruitment for the study was feasible due to a monetary incentive but at that time no incentives were offered for follow ups. Participants were deeply encouraged to respond to the follow up survey, which would occur a month from initial participation. During the follow-up period, waves of e-mail reminders were sent to participants, but not many responses were received.

It is important to note that the finale of the school year was at hand during the follow up time period. This meant that students were busy preparing for finals, starting co-ops/internships, moving back home, or getting ready for a summer transition. Another reason could have also been due to a lack of interest. Some students indicated that they were abstinent and did not see the importance in taking the HPV vaccine. These confounding factors along with a lack of an incentive drove students to being negligent with follow-up responses (10 out of 90 had responded).

This led to the researcher obtaining permission from Merck to distribute incentives for follow up responses. Upon IRB and Merck approval, another batch of emails regarding the follow-up survey was sent. At this point in time, summer vacation had commenced. Students were either off-campus or on-campus but not actively checking e-mails. An additional six responses come through with this effort. A few more e-mail reminders were sent ever few days but not more responses came through. Due to low retention rates, two sets of analysis (pre/post,/follow up and pre/post) had to be conducted to determine rejection or acceptance of set hypotheses.

Participant demographics served as a limitation with the study. Only students from the

University of Cincinnati were recruited. Student from other local universities could have altered the results obtained. Most of the participants were Caucasian males. A more diverse group may

Conclusions 136 have responded differently with the intervention materials. Finally, most of the men in the study were heterosexual. A higher level of homosexual males would have altered the responses.

Additionally, baseline demographic and study variables were not similar. Differences were present between groups from the beginning of the study, which affected outcomes. This occurred despite using computer software for randomization to avoid differences in groups.

Implications for Practice

Concerns for HPV in men are important due to their potential cancerous risk. Increasing knowledge and awareness of HPV affecting men is crucial in promoting the HPV vaccine. While there is a general acceptance of the vaccine, hesitations remain in the actual behavior of taking the vaccine. This is due to barriers and lack of information regarding HPV and the vaccine, which was proven by the focus groups conducted in the study.

The intervention developed in the study brought up important concerns to address as health educators. Utilizing knowledge to help overcome barriers while building self-efficacy and benefits in HPV vaccination are behavioral enablers towards taking the vaccine. Based on results, the intervention group had significant changes, indicating techniques used for delivery were successful. Thus, it is not only important to provide the information but to also engage participants in role plays, discussions, and brainstorming sessions to help them grasp the concepts being presented.

While the duration of the intervention was a brief two hour session which covered all health belief model constructs. Individual session on each construct would allow for deeper understanding and perhaps longer retention of the information provided. Thus the one time session would be prolonged to six sessions, two hours each. This would enable for

Conclusions 137 researchers/health educators to continuously build self-efficacy while breaking down barriers that may exist. Additional sessions would also enable researchers/health educators to help develop cues to action/social support system towards this preventative behavior.

Future Recommendations

Phase I

Information obtained from focus groups was pertinent in comprehending male awareness of

HPV and the HPV vaccine available for them. When targeting marketing campaigns towards the vaccine for men, knowledge of HPV among men must be established a priori. For future focus groups, questions that are more probing towards lack of knowledge and awareness should be addressed as well as asking participants on recommendations of alleviating that issue. This would enable a participant invested interest in building a cohort related intervention towards increasing intent to vaccinate.

Additionally focus groups that involved a more diverse crowd would also benefit in building a database of information related to HPV and HPV vaccinations. Diversity in relation to sexuality, race/ethnicity, socio-economic class, standing in college curricula, athletics, Greek life, and various social organizations should be examined to get a more in-depth analysis.

Results that are obtained from this type of study were useful in establishing interventions for health educators. Building an intervention based on assessing the target population’s ideas and beliefs would allow for a higher participation and outreach pool. Conducting focus groups of this nature also enables researchers to assess the awareness and attitudes towards HPV and HPV vaccinations, which inevitably effects its marketing.

Conclusions 138

Phase II

The intervention built off of Phase I results indicated some change in attitudes and beliefs regarding HPV and HPV vaccination but more could be done. For instance, intentions towards the action of vaccinating changed but the action of obtaining the vaccine had not. More interventions linked to accessibility to an HPV vaccine may serve as a solution. Additionally some attention is also required for individuals that are not sexually active and do not see significance in taking the vaccine.

Based on regression analysis, interventions with an emphasis on reducing perceived barriers, perceived severity and increasing self-efficacy should be established. Perceived benefits should also be emphasized to increase acceptability of the HPV vaccine. External to addressing constructs, utility of role plays and discussions should also be incorporated. This enables strengthening of concepts through practice and vocal acknowledgment. Although,both qualitative and quantitative assessments need to be conducted to determine types of information necessary for interventions geared towards non-sexually active individuals.

Diversity in relation to sexuality, race/ethnicity, socio-economic class, standing in college curricula, athletics, Greek life, and various social organizations should be assessed for this phase.

Various outcomes may arise that may differ from those obtained in this study. In addition to diverse individuals, diverse university settings should also occur. Geo-political locations may bring about differing results as lifestyles vary accordingly. A comparison of these groups would be of benefit to researchers to determine which predictors are common amongst all populations and which are specific to a certain population.

Conclusions 139

Summary

In summary, this study demonstrated the need for further studies examining vaccine acceptability among college men. While follow-up issues occurred in the study, the intervention was effective in producing positive changes within the experimental group. A mixed methodology approach helped develop an intervention that catered to the needs of the college male population at the

University of Cincinnati. Further research employing similar techniques must be conducted to obtain a better understanding of vaccine acceptability. Efficacy trials must also be conducted to determine usefulness of this program. With limited research available at present, there is ample room for investigation in the future

140

References

Becker, M.H. (1974). The health belief model and personal health behavior. Health Education

Monographs, 2(4), 324-473.

Brewer, N. T., & Fazekas, K. I. (2007). Predictors of HPV vaccine acceptability: A theory-

informed, systematic review. Preventive Medicine, 45(2-3), 107-114.

Centers for Disease Control and Prevention (CDC). (2008). Genital HPV infection: Fact sheet.

Retrieved from: http://www.cdc.gov/STD/HPV/STDFact-HPV.htm.

Chen, J. Y., Fox, S. A., Cantrell, C. H., Stockdale, S. E., & Kagawa-Singer, M. (2007). Health disparities and prevention: Racial/ethnic barriers to flu vaccinations. Journal of Community Health, 32, 5- 20.

Dunne, E.F., Nielson, C.M., Stone, K.M., Markowitz, L.E., Giuliano, A.R.(2006). Prevalence of HPV infection among men: a systematic review of the literature. Journal of Infectious Disease, 194:1044--57.

Ferris, D.G., Waller, J.L., Miller, J., Patel, P., Price, G.A., Jackson, L., & Wilson, C. (2009). Variables associated with Human Papillomavirus (HPV) vaccine acceptance by men. The Journal of the American Board of Family Medicine, 22(1), 24-42.

Gerend, M.A., Jessica, B. (2009). Human Papillomavirus vaccine acceptability among young adult men. Sexually Transmitted Diseases, 36(1), 58-62.

Gever, J. (2009). FDA approves vaccine for men and boys. Medpage Today. Retrieved

November 12, 2009, from http://www.medpagetoday.com/PrimaryCare/Vaccines/16484.

Gillison, M.L., Chaturvedi, A.K., Lowy, D.R.(2008).HPV prophylactic vaccines and the potential prevention of noncervical cancers in both men and women. Cancer, 113(suppl 10):3036 –3046.

Harper, D.M., Franco, E.L., Wheeler, C.M., Moscicki, A.B., Romanowski, B., Roetlli-Martin, C.M., et al.(2006). Sustained efficacy up to 4.5 years of a bivalent L1 virus-like particle vaccine against human papillomavirus types 16 and 18, follow-up from a randomised control trial. Lancet, 367, 1247-55.

Hilleman MR. (2000). Overview of vaccinology with special reference to papillomavirus vaccines. Journal of Clinical Virology, 19(1-2), 79-90.

Katz, M.L., Reiter, P.L., Heaner, S., Rufﬁn, M.T., Post, D.M., Paskett, E.D.(2009). Acceptance of the HPV vaccine among women, parents, community leaders, and healthcare providers in Ohio Appalachia. Vaccine, 27 (30), 3945–3952.

Larson EB, Olsen E, Cole W.(1978).The relationship of health beliefs and a postcard reminder to influenza vaccination. Journal of Family Medicine,8, 1207-1222.

141

Liddon, N., Hood, J., Wynn, B.A., & Markowitz, L.E. (2010). Acceptability of Human Papillomavirus vaccine for males: A review of literature. Journal of Adolescent Health, 46(2), 113-123.

Mays, R. M., Zimet, G. D., Winston, Y., Kee, R., Dickes, J. & Su, L. (2000). Human papillomavirus, genital warts, Pap smears, and cervical cancer: knowledge and belief of adolescents and adult women. Health Care Women International, 5, 361-374.

Partride, J. M, Hughes, J. P, Feng Q, Winer, R.L., Weaver, B.A., XI L.F., et al. (2007). Genital human papilloma virus infection in men: incidence and risk factors in a cohort of university students. Journal of Infectious Disease, 196(8):1128-36.

Payette ,P.J., Davis. H.L.(2001).History of vaccines and positioning of current trends. Current Drug Targets Infectious Disorders,1(3),241-7.

Reiter, P, Brewer, N. T., & Smith, J. S. (2010). Human papillomavirus knowledge and vaccine acceptability among a national sample of heterosexual men. Sexually Transmitted Infections, 86, 241-246.

Reiter, P.L., Brewer, N., McRee, A., Gilbert, P., & Smith, J. S. (2010). Acceptability of HPV vaccine among a national sample of gay and bisexual men. Sexually Transmitted Diseases, 37(3), 197- 203.

Riedel, S. (2005). Edward Jenner and the history of smallpox and vaccination. Baylor University Medical Center Proceedings, 18, 21-25

Rosenstock, I. M. (1990). The health belief model, Explaining health behavior through expectancies. In K. Glanz, F. M.Lewis, & B. K. Rimer (Eds.), Health behavior and education, Theory, research and practice (pp. 39–62). San Francisco, Jossey-Bass.

Rosenstock, I. M. (2004). Health belief model. In A. E. Kazdin (Ed.), Encyclopedia of psychology (Vol. 4, pp. 78–80).Washington, DC, American Psychological Association.

Rosenstock, I. M. (1974). Historical origins of the health belief model. Health Education Monographs, 2, 1–8.

Saslow, D., Castle, P.E., Cox, J.T., Davey, D.D., Einstein, M.H., Ferris, D.G., et. al.(2007). American Cancer Society guideline for human papillomavirus (HPV) vaccine use to prevent cervical cancer and its precursors. CA Cancer Journal for Clinicians, 57(1),7-28.

Sawaya, G.F, Smith-McCune K.(2007). HPV vaccination--more answers, more questions. New England Journal of Medicine. 356(19),1991-3.

Sharma, M., & Romas, J. A. (2008). Theoretical foundations of health education and health promotion.

(pp. 69-90). Sudbury, Massachusetts: Jones and Bartlett Publishers.

Stern AM, Markel H. (2005). The history of vaccines and immunization: familiar patterns, new

challenges. Health Affairs, 24(3): 611-21.

Stanley MA. (2002). Human papillomavirus vaccines. Current Opinion in Molecular Therapy, 4(1), 15-22.

142

Stevens, J. (2009). Applied multivariate statistics for the social sciences (5th ed). New York,

NY, Taylor and Francis Group.

Tabachnick, B. G., Fidell, L. S. (2007). Using multivariate statistics (5th ed). Boston, MA, Pearson.

Vanslyke, J.G., Baum, J., Plaza, V., Otero, M., Wheeler, C., Helitzer, D.L.(2008). HPV and cervical cancer testing and prevention: knowledge, beliefs, and attitudes among Hispanic women. Qualitative Health Research, 18, 584-596. Wong, L.P.(2008). Young multiethnic women's attitudes toward the HPV vaccine and HPV vaccination. International Journal Gynaecologic Obstetrics, 103, 131–135.

Zak-Place, J.,& Stern, M.(2004). Health belief factors and dispositional optimism as predictors of STD and HIV preventive behavior. Journal of American college health, 52(5), 229-236.

143

Appendix A

Panel of Experts

1) Dr. Manoj Sharma Professor of Health Promotion and Education University of Cincinnati Email: [email protected] Expertise: Instrumentation

2) Dr. Liliana Guyler Professor of Health Promotion and Education University of Cincinnati Email: [email protected] Expertise: Instrumentation, sexual health, HPV, Health Belief Model

3) Allison Friedman Health Scientist CDC, NCHHSTP Division of STD Prevention Atlanta, GA Email: [email protected] Expertise: STD prevention, HPV awareness and education, health communications

4) Ann Forsythe- CDC Associate Director CDC, Division of STD Prevention Atlanta, GA Email: [email protected] Expertise: STD prevention, HPV awareness and education, health communications

5) Keith King Professor of Health Promotion and Education University of Cincinnati Email: [email protected] Expertise: Instrumentation, sexual health, HPV, Health Belief Model

6) Dr. Randall Cottrell Professor of Health Promotion and Education University of Cincinnati Email: [email protected] Expertise: Instrumentation, Health Belief Model

144

Appendix B

Survey on HPV in College Males

Directions: The following survey is about Human Papilloma Virus (HPV) and its vaccine. Participation in this survey is voluntary and anonymous. Your responses would be greatly appreciated. Please check the box that best describes your view.

1. Have you ever heard of HPV?  Yes  No  Don’t Know

2. Have you ever heard of an HPV vaccine?  Yes  No  Don’t Know

The following are True/False statements. Please check the box most appropriate to your knowledge.

3. HPV only affects women.  True  False

4. HPV can lead to serious health consequences.  True  False

5. HPV causes cervical cancer in women.  True  False

6. HPV is a common virus that can be passed on through sexual contact.  True  False

7. HPV can cause health problems, such as genital warts.  True  False

8. HPV can cause rare cancers in men, such as penile and anal cancers.  True  False

Please check how strongly you agree or disagree Strongly Strongly Disagree Neutral Agree with each statement. Disagree Agree

9. I have had more than 1 sexual partner, placing me at risk for getting an HPV infection.

10. Due to my sexual behaviors I am at higher risks for HPV infections or cancers.

11. It is very likely I will get HPV at some point in my life.

12. HPV can cause serious diseases.

13. HPV can cause health problems such as genital warts.

145

14. It would be very bad if future sex partners refused to have sex with me because I had a HPV infection

Please check how strongly you agree or Strongly Strongly Disagree Neutral Agree disagree with each statement. Disagree Agree

15. If I get the HPV vaccine, I will suffer from side effects.

16. I cannot afford the HPV vaccine ($375).

17. I do not have access to getting the 3 shot series of the HPV vaccine.

18. I have been advised by my sexual partner(s) about taking the HPV vaccine.

19. I have been advised by friends about the benefits of taking the vaccine.

20. I would like to take the HPV vaccine to take better care of my sexual health.

21. I have had many sexual partners and am possibly at high risk for HPV infection.

22. If prevention is not taken, HPV can

lead to serious negative consequences.

23. If prevention is not taken, my sexual partner and I will be at higher risks for HPV infections or cancers.

24. My chances of getting HPV are high.

25. I plan on taking the HPV vaccination.

26. My friends have gotten the vaccine, and I plan on getting it as well.

27. Someone I trust has recommended me to take the HPV vaccine.

27. I am confident I can take the HPV vaccine.

146

28. I am confident I can complete all 3 doses of the HPV vaccine.

29. I will take the HPV vaccine even if I have to travel a far distance from my home to get it.

30. Will you take the vaccine?

Demographics:

31. How old are you? ______years

32. What is your sexual orientation? ____ homosexual

____ heterosexual

____ bisexual

33. Which year of college are you in? ____ Freshman

____ Sophomore

____ Junior

____ Senior

_____ Graduate student

34. What is your marital status? ____ Single, never married

____ Married

____ Widower

____ Divorced

35. Have you ever had sexual intercourse? ____ Yes

____ No

147

36. Have you taken the vaccine? _____ Yes

_____ No

37. If yes, were there any adverse effects? Please list them below.

148

Appendix C

Control Group Intervention (Knowledge based)

After completing this session, 80% of participants will be able to

Behavior Objectives

7- will increase their susceptibility level of obtaining a HPV related infection as measured by the perceived susceptibility questionnaire (20 min) Learning Objectives: - Define STDs - Name common STD’s - Describe the characteristics of HPV virus - Identify the modes of transmission of HPV - Identify likelihood of obtaining an HPV related infection in the lifetime - Identify what the HPV vaccine is Learning Process: - Lecture - Small group discussions

8- will increase their level of knowledge and beliefs of HPV related infections as measured by the perceived severity questionnaire Learning Objectives: - Defining what HPV is - Explain the immediate effects of HPV on their health - Explain long-term consequences Learning Process: - Lecture - Video - Small group discussion

9- will decrease their barriers and increase the benefits in taking the HPV vaccine as measured by the perceived barriers and benefits questionnaire Learning Objective: - Identify benefits of taking the vaccine - List methods of counteracting barriers - Describe how to overcome barriers of taking the vaccine Learning Process - Discussion - Brainstorming session - Role plays

149

10- will increase their self-efficacy in taking the HPV vaccine as measured by the self-efficacy questionnaire Learning Objective: - - List HPV vaccination process

Learning Process:

- lecture

11- will increase their cues to action in taking the HPV vaccine as measured by the cues to action questionnaire Learning Objectives: - Identify support systems in taking the vaccine Learning Process: - Lecture

12- will increase their acceptability and knowledge of the HPV vaccination as measured by the question in the post-test Learning Objective: - Identify the HPV vaccine - Explain process and rationale for taking the HPV vaccine Learning Process: - lecture

13- will take the HPV vaccination within one month post seminar as measured by the follow up questionnaire

150

151

152

153

154

155

156

157

Appendix D

Experimental Intervention (HBM based)

After completing this session, 80% of participants will be able to

Behavior Objectives

1- will increase their susceptibility level of obtaining a HPV related infection as measured by the perceived susceptibility questionnaire (20 min) Learning Objectives: - Identify likelihood of obtaining an HPV related infection in the lifetime - Identify what the HPV vaccine is Learning Process: - Lecture - Small group discussions

2- will increase their level of perceived severity (knowledge and beliefs) of HPV related infections as measured by the perceived severity questionnaire Learning Objectives: - Defining what HPV is - Explain the immediate effects of HPV on their health - Explain long-term consequences Learning Process: - Lecture - Video - Small group discussion

3- will decrease their perceived barriers and increase the perceived benefits in taking the HPV vaccine as measured by the perceived barriers and benefits questionnaire Learning Objective: - Identify benefits of taking the vaccine - List methods of counteracting barriers - Describe how to overcome barriers of taking the vaccine Learning Process - Discussion - Brainstorming session - Role plays

4- will increase their self-efficacy in taking the HPV vaccine as measured by the self-efficacy questionnaire Learning Objective: - - List HPV vaccination process

158

Learning Process:

- group discussion

5- will increase their cues to action in taking the HPV vaccine as measured by the cues to action questionnaire Learning Objectives: - Identify support systems in taking the vaccine Learning Process: - Brainstorming - Group discussion

6- will increase their acceptability of the HPV vaccination as measured by the question in the post- test Learning Objective: - Identify the HPV vaccine Learning Process: - Group discussion

7- will take the HPV vaccination within one month post seminar as measured by the follow up questionnaire

159

160

161

162

163

164

Adult Consent Form for Research

University of Cincinnati

Department: Health Promotion and Education

Principal Investigator: Manoj Sharma

Co-Investigators: Rebecca Lee & Purvi Mehta

Title of Study: Designing and evaluating a health belief model based intervention to increase intent of HPV vaccination among college men: Use of qualitative and quantitative methodologies

Introduction:

You are being asked to take part in a research study. Please read this paper carefully and ask questions about anything that you do not understand.

Who is doing this research study?

The persons in charge of this research study are Dr. Manoj Sharma, Purvi Mehta and Dr. Rebecca Lee of the University of Cincinnati (UC) Department of Health Promotion and Education and College of Nursing.

What is the purpose of this research study?

The purpose of the study is to determine predictors of HPV vaccine acceptability among college men through a Health Belief Model designed program.

Who will be in this research study?

About 90-100 people will take part in this study. You may be in this study if you are an: English speaking male, between the ages of 18 and 25, attending the University of Cincinnati as a undergraduate or graduate student.

What will you be asked to do in this research study, and how long will it take?

165

You will be asked to listen to a powerpoint presentation, and share your opinions regarding HPV vaccinations. It will take about an two to two and a half hours. The research will take place at Teacher’s College Room 435.

Are there any risks to being in this research study?

There are almost none to minimal risks involved with participating in the study. Some statements made during focus group discussion may adversely affect some students.

Are there any benefits from being in this research study?

There are no direct benefits for participating in the study.

What will you get because of being in this research study?

You will receive a $25 gift certificate for your participation.

Do you have choices about taking part in this research study?

Participation is purely voluntary. If you do not want to take part in this research study, return the consent form blank.

How will your research information be kept confidential?

Information about you will be kept private by giving you a code name. Your information will be kept in a password secured computer file for 5 years. After that it will be destroyed by the researchers.

Agents of the University of Cincinnati may inspect study records for audit or quality assurance purposes.

What are your legal rights in this research study?

Nothing in this consent form waives any legal rights you may have. This consent form also does not release the investigator, the institution, or its agents from liability for negligence.

166

What if you have questions about this research study?

If you have any questions or concerns about this research study, you should contact Dr. Manoj Sharma at [email protected] Or (513) 556-3878; Purvi Mehta at [email protected], or Dr. Rebecca Lee at [email protected].

The UC Institutional Review Board reviews all research projects that involve human participants to be sure the rights and welfare of participants are protected.

If you have questions about your rights as a participant or complaints about the study, you may contact the UC IRB at (513) 558-5259. Or, you may call the UC Research Compliance Hotline at (800) 889-1547, or write to the IRB, 300 University Hall, ML 0567, 51 Goodman Drive, Cincinnati, OH 45221-0567, or email the IRB office at [email protected].

Do you HAVE to take part in this research study?

No one has to be in this research study. Refusing to take part will NOT cause any penalty or loss of benefits that you would otherwise have. You may start and then change your mind and stop at any time. To stop being in the study, you should inform either one of the researchers and will be excused from the remainder of the focus group session.

Agreement:

I have read this information and have received answers to any questions I asked. I give my consent to participate in this research study. I will receive a copy of this signed and dated consent form to keep.

Participant Name (please print) ______

Participant Signature ______Date ______

Signature of Person Obtaining Consent ______Date ______