Running head: IMPROVING HPV VACCINATION RATES

Improving Adolescent Human Papillomavirus Vaccination Rates Through Provider Education
Tierra Schulz
Arizona State University

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Abstract

Human papillomavirus (HPV) is a prevalent sexually transmitted infection that affects many
adolescents and adults worldwide. The consequences of contracting HPV have proven to be
devastating, potentially leading to a variety of life-threatening genitourinary and oral cancers. As
such, prevention via vaccination is critical. HPV vaccination is recommended for all adolescents
beginning at 11 years of age. Although the immunization has proven to be safe and effective,
HPV vaccination rates are substantially below target goals worldwide. A literature review of
evidence from the last five years was conducted to examine barriers and facilitators to HPV
vaccine uptake. The most commonly cited barriers to vaccination included lack of knowledge
about the vaccine and inadequate provider recommendation. Current evidence regarding
interventions to increase HPV vaccine uptake reveal that best practices are multi-factorial and
should include a combination of provider education and recommendation training. These
findings led to the proposal of an evidence-based intervention aimed to increase adolescent HPV
vaccination rates. A one-hour educational program was conducted at a local pediatric primary
care facility. Five healthcare providers participated in the program, which consisted of a
PowerPoint presentation outlining the benefits of HPV vaccination and use of an interactive
application from the CDC. The app taught participants how to offer a strong recommendation for
the vaccine through active participation. Pre and posttests were administered to determine the
providers’ intent to vaccinate and vaccination rates were monitored. Analysis of the data
collected revealed a statistically significant rise in vaccination rates. These results reveal that
provider education can improve recommendation techniques and therefore increase vaccine
coverage. Further research is needed to see if one-time education is sustainable.
Keywords: Adolescents, HPV, human papillomavirus, provider education, vaccination

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Improving Adolescent HPV Vaccination Rates
Vaccination against human papillomavirus (HPV) is currently recommended by the
Centers for Disease Control and Prevention (CDC) and the Advisory Committee on
Immunization Practices (ACIP) for both males and females aged 11-26 years (CDC, 2018).
Despite numerous clinical trials that led the Food and Drug Administration and CDC to deem the
vaccine both safe and effective at preventing genitourinary cancers, HPV vaccination rates are
still remarkably lower than all other required adolescent vaccinations. Failing to immunize
against HPV as an adolescent can potentially lead to lifelong consequences. A joint statement
released by 69 of the National Cancer Institute (NCI) centers refers to low HPV vaccination rates
as a serious public health threat (National Institute of Health, 2016).
Background and Significance
Human papillomavirus refers to more than 200 different strains of related viruses that can
be spread through sexual contact. It is the most common sexually transmitted infection, affecting
more than 79 million Americans (CDC, 2018). While low risk strains of HPV can lead to genital
warts, high risk HPV can lead to cervical, anal, oral, penile, or vulvar cancers (NIH, 2018). The
HPV vaccine protects against nine different strains, seven of which can potentially lead to cancer
(CDC, 2018). There are 33,000 new cases of cervical cancer diagnosed in the United States
annually, leading to 4,000 deaths each year. Vaccinating against HPV can prevent 90% of these
cases (CDC, 2018).
The HPV vaccine is currently recommended by the CDC and ACIP for all adolescents
beginning at 11 years of age, yet in 2017 only 66% of adolescents initiated the vaccine and 49%
were up to date, falling significantly short of the Healthy People 2020 goal of 80% (CDC, 2018).
After introduction of the HPV vaccine, HPV related cancers and genital warts decreased by 71%

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in adolescents (CDC, 2018). Despite the proven efficacy, only 29.5% of girls and 24.9% of boys
complete the series by age 13 (Vollrath, Thul, & Holcombe, 2018).
Internal Evidence
The Director of Professional Practice and the Chief Clinical Services at a local pediatric
primary care facility report an office HPV vaccination rate of 13-18%, significantly below state
and national levels. A poll of the providers at this location indicates that many do not routinely
recommend the vaccine and often offer delayed dosing.
Purpose and Rationale
In 2017, 44% of parents made the decision to not vaccinate their child against HPV
(CDC, 2018). This decision may lead to deleterious consequences for them as they grow into
adulthood. The purpose of this evidence-based project is to improve provider knowledge
regarding the HPV vaccine and intent to vaccinate. These practice changes are anticipated to
increase HPV vaccine uptake in adolescents between ages 11-18 years. The inquiry into this
clinical problem leads to the PICO question: In pediatric healthcare providers, does an
educational class on the HPV vaccine and recommendation techniques versus no educational
offering affect overall HPV knowledge and vaccination rates?
Evidence Synthesis
Search Strategy
An extensive review of current literature was performed to answer the PICO question.
The databases searched included PubMed, Cumulative Index of Nursing and Allied Health
Literature (CINAHL), and Cochrane Library. The databases were searched using a combination
of the following terms: adolescents, teenagers, caregivers, parents, health care providers, HPV
vaccination, HPV rates, human papillomavirus, education, and recommendation. Boolean and

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MeSH terms were added to broaden the search. Initial searches yielded 116 results in PubMed,
84 in CINAHL, and 55 in Cochrane Library. Filters were then applied to include only English
language, peer reviewed articles published between 2013 and 2019 with an age limit of 18 years
old. This final search yielded 60 results in PubMed, 52 in CINAHL, and 46 in Cochrane Library.
The abstracts of each article were reviewed for quality and relevance. Inclusion criterion
included educational interventions aimed at increasing HPV vaccination rates in adolescents.
Exclusion criterion included participants older than 18 years old receiving the vaccine and
articles published prior to 2013. After critical appraisal of each article, 14 have been chosen
based on merit and relevance to the PICO question to be included in the literature review.
Critical Appraisal
Fourteen studies were chosen to be included in the literature review based on quality,
relevance and merit determined by Melnyk and Fineout-Overholt’s (2005) rapid critical
appraisal. Of the 14 studies selected, 10 were randomized controlled trials, which are considered
to be a high-level of evidence. The remaining four studies used surveys and levels of evidence
ranged from III to VI (Appendix A). Funding was disclosed for all but two of the studies, with
only two being funded by a pharmaceutical company, which could lead to a potential
sponsorship bias. Each of the 14 studies took place in an outpatient, primary care setting within
the United States and had adequate samples of adolescents aged 9-18 years old. Heterogeneity
was observed in the demographics of the sample, with an equal volume of males and females and
a wide variety of ethnicities represented (Appendix B).
Intervention methods varied widely amongst each of the studies. Single component and
multi-component methods were evaluated, including provider communication classes, web-based
videos for parents, and printed fact sheets. Due to the variability, it was difficult to assess which

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of these methods would be most beneficial. Despite heterogeneity of the interventions, there was
a commonality amongst all. Each of the studies provided education to parents or providers
regarding the risks of HPV, the benefits of HPV vaccination, and why it is important to vaccinate
at a young age.
While secondary outcomes such as provider comfort level and parent perception were
measured in three studies, the main outcome assessed in all but two of the studies was a change
in HPV vaccination rates. The measurement tools were homogeneous amongst studies due to the
fact that there are limited methods to track HPV vaccination rates. Methods included an online
registry, electronic medical records, and self-report through surveys (Appendix A).
Foundation of Evidence
After an exhaustive review of the literature was performed, parental hesitancy was
identified in numerous studies as a barrier to HPV vaccination. The greatest report of parental
hesitancy (17%) stems from the lack of a recommendation from a medical provider (Holman et
al., 2014). Eleven of the fourteen studies examined in this review cite the lack of a strong
provider recommendation as the leading cause for parents not accepting the HPV vaccine.
Parents frequently reported that their child’s medical provider did not recommend the vaccine,
with only 58.8% of girls receiving a recommendation and 14.2% of boys (Rahman, Laz,
McGrath, & Berenson, 2014). Overall, the HPV vaccine was only strongly recommended by a
provider 39% of the time compared to other adolescent vaccines, which were strongly
recommended 59% of the time. Receiving a strong recommendation from a provider makes an
adolescent five to seven times more likely to receive the vaccine than if receiving no
recommendation (Dempsey & O’Leary, 2018; Dempsey et al., 2015; Ylitalo, Lee, & Mehta,
2013). Findings indicate that provider recommendation increases uptake of the HPV vaccine by

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creating a positive parental perception of the immunization. That positive attitude is diminished,
however, if the vaccine is presented as optional (Dempsey et al., 2015; Underwood et al., 2016).
In a recent survey conducted by Warner et al. (2017), pediatricians had the lowest
proportion of knowledge (26.7%) regarding the HPV vaccine out of all specialty providers.
Providers are less likely to recommend the HPV immunization if they have little knowledge
about the vaccine (Holman et al., 2014). Provider based interventions should aim to increase
knowledge and therefore the strength of the recommendation to patients. After one hour of
provider education, which entails general HPV knowledge and the correct structure of a strong
recommendation, providers are significantly more likely to recommend the HPV vaccine and
administer it at minimum dosing intervals (Volrath, Thul, & Holcombe, 2018). A study by
Dempsey and O’Leary (2018) found that a strong recommendation results in 89% HPV vaccine
acceptance rate, whereas a weak recommendation results in a 71% acceptance rate. Learning to
frame a strong recommendation is a mainstay of provider education.
This literature review demonstrates that educational interventions aimed at providers or
parents could lead to an increase in overall HPV vaccination rates. The most common
intervention analyzed was an HPV education and communication course for providers, which
attempted to nullify each of the top parent and provider barriers to vaccination. Findings from
this literature review report that provider trainings not only increase HPV vaccination rates, but
also significantly improve both parent and provider perceptions of the vaccine.
Conceptual Framework and EBP Model
The conceptual framework used to guide this project was the Health Belief Model
(HBM), which attempts to predict an individual’s health behaviors by focusing on their attitudes
and beliefs towards an illness (Donadiki et al., 2014). In this model, an individual will take a

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health related action, such as vaccination, only if they feel as though the illness is a personal
threat to them and whether the suggested health behavior is safe, beneficial and effective
(Appendix C). Studies indicate that HPV vaccination rates are low due to both provider beliefs
that there is a low risk of adolescents contracting HPV and doubts regarding the safety of the
vaccine. If providers have doubts or concerns regarding the vaccine, they are less likely to
recommend it to their patients. An intervention designed to educate providers about the severity
of contracting HPV, the benefits of the vaccine to society, and the safety profile should foster
positive attitudes and beliefs towards the vaccine, leading to a strong recommendation. Findings
from several studies indicate that provider recommendation increases uptake of the HPV vaccine
by creating a positive parental perception of the immunization (Dempsey et al., 2015). That
positive parental perception, according to the HBM, will then lead to them taking the health
related action of vaccination.
In addition to the HBM, Rosswurm and Larrabee’s (1999) model was chosen to guide
individuals systematically through the process of developing and implementing an evidencebased practice change (Appendix D). The process begins with assessing the need for change.
State and national averages for HPV vaccination rates are markedly below target goals,
indicating improvements need to be made in the HPV vaccination process. Next, potential
interventions must be identified and recent evidence synthesized to support the intervention
based on feasibility, benefits, and risk. Provider education and communication training has been
supported by recent evidence to be a potential low cost intervention that significantly improves
vaccination rates. Once the intervention is identified, the practice change can then be designed,
where outcomes and resources are identified and the practice change is implemented and

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evaluated. If positive outcomes are achieved, the practice change can be integrated and
maintained in practice (Appendix D) (Rosswurm & Larrabee, 1999).
Methods
Ethical Considerations
University Institutional Review Board (IRB) approval was obtained prior to project
implementation. Physical data (surveys) were de-identified by assigning unique coded numbers
to individuals and were stored in a locked file cabinet. Electronic data was also de-identified and
stored on an encrypted, password-protected computer. All information will be deleted at the
completion of the project.
Population and Setting
Five healthcare providers (nurse practitioners and physicians) were eligible to participate
in this evidence-based project. Inclusion criteria included being a healthcare provider employed
by the project site and having an interaction with adolescents who were eligible for the HPV
vaccine. Participants were excluded if they did not provide direct care to patients or if they did
not attend the staff meeting where the intervention was presented. The project was conducted in
a pediatric primary care facility located in Mesa, Arizona. The clinic provides services such as
well child exams, sick visits, and immunization encounters for children from birth to age 18
years.
Procedure
The Director of Professional Practice for the organization was contacted regarding
potential participation in the project. Upon agreement of participation, the project director
contacted the clinic manager to arrange a date and time for the intervention that was convenient
for potential participants. In July of 2019, the project site champion identified eligible

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participants. The project director distributed a recruitment letter to the potential participants prior
to the start of the intervention. The recruitment letter described the evidence-based project and
also served as the consent form. By choosing to stay and take part in the intervention, individuals
consented to be an active participant in the project. An eight-point questionnaire along with a
demographic data form was then distributed to eligible participants. Each participant had 10
minutes to complete the questionnaire. After all questionnaires were completed, a one-hour
educational course regarding HPV and the HPV vaccine commenced. Led by the project
director, 30 minutes were dedicated to providing a PowerPoint presentation regarding the risks of
HPV, the benefits of the vaccine, and tips for providing a strong, assumptive recommendation.
During the final 30 minutes, an interactive video from the CDC and American Academy of
Pediatrics was shown. The web-based app (Same Day, Same Way) is an interactive video about
how to give a strong recommendation for the HPV vaccine. The app simulated typical parentprovider interactions that take place during adolescent visits and allowed the providers to choose
how they would recommend the vaccine and answer frequently asked questions. Based on their
responses, the virtual patient and parent would make a decision to either accept or decline the
vaccine. Feedback was then given to participants about how to better frame their
recommendations. Immediately following the hour-long educational intervention, a post-survey
was distributed for participants to complete. A final post-survey was hand-delivered to the
participants three months post intervention.
Data Collection and Outcome Measures
The primary outcome measured was overall HPV vaccination rates, while secondary
outcomes included provider knowledge and intent to vaccinate. The Clinical Services Director
pulled vaccination rates monthly from the electronic medical record. Administration rates were

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pulled both collectively for the clinic and individually by provider. Intent to vaccinate was
measured using a modified Determinants of Intent to Vaccinate (DIVA) survey. This 56-item
questionnaire is intended to assess provider commitment to vaccination and knowledge regarding
the vaccine. The questions are grouped into six different domains: (a) ‘properties of the vaccine’,
(b) ‘disease characteristics/benefits’, (c) ‘information about the vaccine’, (d) ‘practical aspects’,
(e) ‘adaptation’, and (f)‘primary care provider’s experience’ (Martinez et al., 2016). Prescribing
providers are asked questions within each of these domains and must choose from four possible
responses on a scale between 1= “totally disagree”, 2= “somewhat disagree”, 3= “somewhat
agree” and 4= “totally agree”. Of the 56 questions in the original questionnaire, eight were
chosen for the modified version due to time constraints of the participants. The DIVA tool was
found to be a valid and reliable instrument to assess provider intent to vaccinate, with a
Cronbach’s alpha of 0.85. A Delphi panel also concluded that the DIVA questionnaire could be
utilized as a stand-alone tool in assessing provider commitment to vaccinate against HPV,
finding good internal consistency and reliability (Martinez et al., 2016).
Budget and Funding
The intervention for this project was cost-effective with minimal out-of-pocket expenses.
The majority of the budget plan (Appendix E) was allocated to printed copies of the pre and post
surveys, which are not necessary for project implementation. There was also the potential for the
associated cost of paying the providers’ salary or loss of patient revenue if the education was
provided at any time other than the lunch hour. This project was implemented during the lunch
hour, so while there was no loss of revenue, a meal was provided. There were no grants awarded
for this project. The student provided all funding.
Results

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Five providers returned completed surveys to the project director (N=5). Answers
provided were converted to a Likert scale and given a score. A Wilcoxon Signed Rank Test was
conducted to compare the average scores for provider intent to vaccinate pre-intervention versus
post-intervention. Scores could not be analyzed due to constant variables, indicating there was no
difference in provider intent to vaccinate pre-intervention compared to post-intervention.
Vaccination rates for the clinic, and per provider, were pulled for five months prior to
intervention and five months post intervention. A repeated measures of analysis of variance
(ANOVA) was conducted to determine if there were any significant differences in individual
provider vaccination rates between the months before the intervention and the months after. The
results were examined based on an alpha of 0.05. The main effect for the within-subjects factor
was not significant (F(4, 16) =1.96, p = .200), indicating that vaccination rates pre-intervention
and post-intervention were similar. A two proportions z-test was also conducted to determine
whether there was a significant difference between the proportion of total eligible adolescents
(N=2,096) who accepted the vaccine pre-intervention and the proportion of total eligible
adolescents (N=2,428) who accepted the vaccine post-intervention. The result of the two
proportions z-test was statistically significant based on an alpha of 0.05 (z = -5.12, p = <.001)
indicating that the proportion of children accepting the vaccine pre-intervention was significantly
lower than children accepting the vaccine post-intervention. These results are consistent with the
literature in that increasing provider knowledge and the strength of their recommendation leads
to increased vaccine uptake.
Potential Impact
Implementing a provider-based educational training on HPV will lead to practitioners
having increased knowledge regarding the benefits of the vaccine and will increase their comfort

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and confidence in delivering a stronger and more timely recommendation to parents. This
recommendation will in turn empower parents with knowledge of the importance of vaccinating,
leading to increased vaccine uptake. Significantly improving HPV vaccination rates will
ultimately lead to a decreased incidence of HPV related genitourinary cancers, thus creating
better health outcomes for our population.
Project Sustainability
The one-hour educational course provided during this evidence-based project can be
easily replicated at other pediatric primary care facilities throughout the organization. The
materials used were electronic and tailored to train any type of pediatric provider. As such, the
course could be effortlessly sent to and implemented at other pediatric facilities. The site would
need an individual who is trained in using the course materials to facilitate the class as well as
time allotted to provide the education. There would be no additional cost to the organization.
Discussion
Summary and Conclusions
Low HPV vaccination rates in Arizona and the United States indicate the need for an
evidence-based intervention aimed at increasing immunization uptake. This project demonstrates
that provider education intended to strengthen recommendation techniques can successfully
improve overall vaccination rates. While survey results of this project indicate that provider
intent to vaccinate did not improve, this is likely due to the fact that individual intent was already
at peak potential pre-intervention. This conclusion was reached as providers had high preintervention scores with no room for improvement post-intervention. This suggests that providers
were already intending to vaccinate all adolescents, yet their current practice was not sufficient

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to promote vaccination. By implementing a provider education course, techniques were given on
how to improve vaccine recommendations and therefore uptake.
Vaccination rates did improve post-intervention for each individual provider. Though this
is clinically significant, given the small sample size of five providers, rates were not statistically
significant. Additional data was also analyzed, using a larger sample size of total adolescents
eligible for the vaccine. The proportion of eligible adolescents that accepted the vaccine postintervention was significantly higher than the proportion of eligible adolescents that accepted the
vaccine prior to the intervention. These results are consistent with suggestions from the literature
in that increasing provider knowledge and the strength of their recommendation leads to
increased vaccine uptake.
Limitations and Barriers
There were several limitations and barriers noted throughout this project. The barriers
that were encountered included reluctance from two providers to participate and time constraints.
There were significant challenges in pulling vaccination rates for the office without including the
rates for the non-participating providers. This initially led to the possibility of skewed data and
falsely low vaccination rates. However, upon further evaluation, an alternative method for
extracting vaccination rates was developed to alleviate that potential issue. The participating
providers also voiced concern that they had limited time to properly discuss the HPV vaccine
given their short ten-minute appointment windows. Furthermore, an additional limitation of the
project was the inability of the electronic medical record to separate administration of the first
dose versus subsequent doses of the HPV vaccine. Separating this data would have allowed for
the opportunity to determine if series initiation or series completion was of greater concern for
the facility.

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Recommendations
Office vaccination rates began to decline two months after the education was provided.
This would seemingly indicate that continuing education is needed to reinforce recommendation
techniques and the importance of HPV vaccination. It is recommended that similar education be
provided to all medical staff in direct contact with adolescent patients on a quarterly basis to
continually improve vaccine uptake.
The educational course provided during this project was implemented just prior to the
start of school, which is typically when a large influx of patients are seen by their primary care
provider for back-to-school needs. Given the decline of vaccination rates over time postintervention, and the timing of the delivery of the intervention, future studies are needed to
determine if provider education courses about HPV vaccination are equally successful in
improving vaccination rates at different time periods throughout the year.
Conclusion
Human papillomavirus vaccination rates in adolescents are significantly below target
goals, creating missed opportunities for reducing cancer cases. The lack of a recommendation
from a medical provider is a driving factor that limits vaccination. Attempting to improve HPV
vaccination rates amongst adolescents is a daunting task, especially considering it is a worldwide
issue. Utilizing knowledge gained from the literature, an evidence-based intervention was
developed in an effort to improve vaccine uptake. Through implementation of a provider
education course in which techniques were given on how to provide a strong recommendation,
HPV vaccination rates improved significantly. These findings indicate that educational
interventions, system changes, and improved provider recommendation could lead to an increase
in overall HPV vaccination rates and therefore a decrease in HPV related cancer deaths.

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of audio recordings. Journal of Adolescent Health, 61(2), 246–251. Doi:
10.1016/j.jadohealth.2017.02.006
Underwood, N. L., Gargano, L. M., Jacobs, S., Seib, K., Morfaw, C., Murray, D., … Sales, J. M.
(2016). Influence of sources of information and parental attitudes on human

IMPROVING HPV VACCINATION RATES

20

papillomavirus vaccine uptake among adolescents. Journal of Pediatric and Adolescent
Gynecology, 29(6), 617–622. Doi: 10.1016/j.jpag.2016.05.003
Vollrath, K., Thul, S., & Holcombe, J. (2018). Meaningful methods for increasing human
papillomavirus vaccination rates: An integrative literature review. Journal of Pediatric
Health Care, 32(2), 119–132. Doi: 10.1016/j.pedhc.2017.07.005
Walling, E. B., Benzoni, N., Dornfeld, J., Bhandari, R., Sisk, B. A., Garbutt, J., & Colditz, G.
(2016). Interventions to improve HPV vaccine uptake: A systematic review. Pediatrics,
138(1), e20153863. Doi: 10.1542/peds.2015-3863
Warner, E., Ding, Q., Pappas, L., Bodson, J., Fowler, B., Mooney, R.,…Kepka, D. (2017).
Health care providers’ knowledge of HPV vaccination, barriers, and strategies in a state
with low HPV vaccine receipt: Mixed-methods study. JMIR Cancer, 3(2). Doi:
10.2196/cancer.7345
Ylitalo, K. R., Lee, H., & Mehta, N. K. (2013). Health care provider recommendation, human
papillomavirus vaccination, and race/ethnicity in the US national immunization survey.
American Journal of Public Health, 103(1), 164–169. Doi: 10.2105/AJPH.2011.300600

IMPROVING HPV VACCINATION RATES

21
Appendix A

Table 1
Evaluation Table
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Brewer et al.
(2017).
Announcements
versus
conversations to
improve HPV
vaccination
coverage: A
randomized
trial.

Inferred
Theory of
Planned
Behavior

RCT (3 & 6 month
FU)

N= 30 (clinics)
n= 10 (CG)
n=10 (IV1)
n=10 (IV2)

Country: USA
Funding:
Pfizer &
National Cancer
Institute
Bias:
Sponsorship
Bias

Purpose: To
determine if
announcement or
conversation
training lead to
larger increases in
HPV vax coverage

Major
Variables and
Definitions
IV1- 1 hr
provider
announcement
training

Measurement

Data Analysis

Study Findings

Decision for Use

Online vax
registry

Power analysis

IV13 month:
IG difference from
CG- 5.1%
p=.003

LOE: II

ITT
Fisher’s exact

Pt type: Vax
prescribing
providers
A:
11-12- 31%
13-17- 69%
Setting: Primary
care clinic
serving 1112yo’s
Exclusions:
prior QI to
increase HPV
vax rates w/i last

IV2- 1 hr
provider
conversation
training
DV- Change in
HPV vax
initiation
between baseline
& 6 months post
Definitionannouncement1) due for 3 vax
2) HPV middle
of vax stated
3)state you will
vax

ANOVA
Poisson regression

6 month:
IG difference from
CG- 5.4%
p=.02
IV23 month:
IG difference from
CG- 2%
p=.10
6 month:
IG difference from
CG- 2%
p=.24

Strengths:
randomized,
standardized
intervention, low
attrition, large sample
Weaknesses:
unknown providers
adherence to
intervention
Conclusions: Brief
provider
announcement
training increases
HPV vax rates,
conversation training
does not
Feasibility: Low
cost and resources

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
6 months, <100
11-12 yo patients
Attrition: 3%
(clinic closed)

Citation

Conceptual
Framework

Design/Method

Sample/Setting

Dempsey et al.
(2019). Effect
of a health care
professional
communication
training
intervention on
adolescent
Human
Papillomavirus
vaccination.

Precautionadoption
process
model

RCT
CSS

N= 43,132
n=21,892 (CG)
n= 21,240 (IG)

Country: USA
Funding: Not
disclosed
Bias: None

Purpose: To
determine if
multimodal
provider
intervention would
increase HPV vax
rates

Pt type:
Adolescents 9yo
or older
presenting for
care
A:
Median-12.6yo
S:
f- 50.3%
m-49.7%
R:
c-54.9%
b-4.5%
his- 12.4%
o-7.9%

22

Conversation1) introduce 3
vax needed
2)place HPV in
middle of list
3)discuss health
benefits, ask if
questions
Major
Variables and
Definitions
IV: 5
componentHPV fact sheet,
parent ed
website, images
of HPV
diseases,
decision aid for
HPV vax, 2.5 hr
provider
communication
training
DV1: Change
over time
between IG and
CG in initiating
HPV series

Measurement

Data Analysis

Study Findings

Decision for Use

EMR

ITT

Online vax
registry

Generalized linear
mixed model

DV1:
CG: 1.8%
IV: 11.3%
p<.001
OR= 1.46

Surveys

Intercept-only
model

LOE: II
Strengths:
heterogeneity of
treatment effects
analysis, randomized,
large sample size

Descriptive
statistics

DV2:
CG: -5.5%
IG: -0.9%
OR=1.56
DV3: 72-90%
used
communication
techniques (most
frequently used).
91% likely to
continue to use.

Weaknesses: small
geographic area not
generalizable, long
term FU not assessed
Conclusion:
Substantial and
sustained increase in
HPV vax initiation
after multicomponent
provider intervention.
Provider
communication ed
used most frequently

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
Setting:
PCO w/ at least
400 active
adolescent
patients
Exclusions: Less
than 9 yo, not
eligible for HPV
vax

Citation

Dempsey et al.
(2019). Parent
report of
provider HPV
vaccine
communication
strategies used
during a
randomized,
controlled trial
of provider
communication
intervention.
Country: USA
Funding: CDC

Conceptual
Framework
Inferred
Theory of
Planned
Behavior

Design/Method

RCT
CSS
Purpose: To assess
secondary, parent
reported outcomes
of a provider
communication
intervention aimed
at improving
adolescent HPV
vax

Attrition: None
(electronic
monitoring)
Sample/Setting

N= 342
n= 162 (CG)
n= 180 (IG)
Pt type: Parents
of young
adolescents seen
at participating
PCO
A:
<13=59%
13-14=41%
S:
f=50%
m=50%
R:

23
and reported easiest
to use

DV2:
Completion of
HPV vax series

Feasibility:
Multicomponent
utilizes more
resources that
individual
interventions, may be
difficult to sustain
over long period of
time

DV3:
intervention
sustainability

Major
Variables and
Definitions
IV: 2.5 hour
provider
communication
training teaching
strong,
presumptive
techniques
DV1: Parents
report of
provider rec
style
DV2: Parents
HPV vax
perception

Measurement

Data Analysis

Study Findings

Decision for Use

Surveys

Chi-square

DV1:
CG=36%
IG=68%

LOE: II

Fishers Exact
Descriptive
Statistics

P<.001
DV2:
CG=28%
IG=55%
P<.001
DV3:
CG=45%
IG=63%
P=.003

Strengths:
randomized, noninvasive, validated
data analysis tools
Weaknesses: selfreport, potential
recall bias, unvaried
demographic
population, poor
attrition rate
Conclusion: Giving a
strong, presumptive
rec improves parent

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
Bias: Recall
(d/t attrition
rate)

C=77%
B=4%
O=19%
Setting: PCO in
Denver, CO.

24
attitude and
acceptance of HPV
vax

DV3:
Adolescent HPV
vax receipt

Feasibility:
Recommended d/t
low cost, time
effective approach

Exclusions:
ineligible to
receive HPV
vax, not between
the ages of 11-17
years

Citation

Dixon et al.
(2019). An
educational
intervention to
improve HPV
vaccination: A
cluster
randomized
trial.
Country: USA
Funding:
Merck-

Conceptual
Framework
Theory of
Planned
Behavior

Design/Method

RCT- cluster
Purpose: Test the
effect of digital
HPV vax
educational
intervention
delivered during a
clinic visit

Attrition: 53%
d/t invalid
addresses or no
response
Sample/Setting

N=1596
n=1059 (CG)
n= 537 (IG)
Pt type: Parents
of adolescents 11
to 17 yo who
were
unvaccinated or
partially
vaccinated.
A:
11-12 -57.4%
13-14 -25.6%

Major
Variables &
Definitions
IV: HPV digital
educational
video
DV: HPV vax
uptake

Measurement

Data Analysis

CHICA

Chi squared test

Theo

t-tests
ITT
GEEs

Definitions:
Vax uptake:
change in vax
status as a result
of a clinic visit

Study Findings

DV:
IG:78%
CG:52.8%
OR=3.07 with
95% CI
p=.003

Decision for Use

LOE: II
Strengths: noninvasive, low attrition
rate, randomization
Weaknesses:
unblinded, clustering
in single urban health
system, dichotomous
variable
Conclusion: Video
presented to parents

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
Regenstrief
Program.
Bias:
Sponsorship
Bias

25

15-17-17%
S:
F-45.3%
M-54.7%
R:
B- 54.5%
C-8.8%
O-36.7%

on risks and benefits
of HPV triples the
odds of HPV vax
uptake
Feasibility:
Recommended due to
ease of
administration,
potential lack of
resource (tablets)

Setting:
Eskenazi
pediatric health
clinics
Exclusions:
parents of
children who
were fully
vaccinated, not
able to read
English language

Citation

Conceptual
Framework

Design/Method

Attrition: None
(able to track vax
status in state
registry)
Sample/Setting

Krantz et al.
(2017).
Increasing HPV
vaccination
coverage

Inferred
Health
Belief
Model

QI

N=105

Purpose: To
increase rate of
HPV series

Pt type: Medical
providers serving
adolescents

Major
Variables and
Definitions
IV: 15 minute
provider
education w/
HPV facts &
framing of rec

Measurement

Data Analysis

Study Findings

Decision for Use

Online vax
registry

Fisher’s exact

DV:
Preintervention50.9%
Post-intervention61.7%

LOE: V

Clopper-Pearson
exact method

Strengths: validated
analysis tools,
completion of series

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
through
provider-based
interventions.

competition after
provider education

Country: USA
Funding: None
Bias: None

S:
f- 41%
m- 59%
R:
B- 74%
His- 1%
O-25%
Setting: PCO w/
predominantly
low income
patients

26

DV: HPV vax
series
competition
rates

p<.05

Weaknesses: no
control group,
minimal variability in
demographics

Definition:
Series
completionreceive all
recommended
doses

Conclusions:
Provider based
interventions increase
HPV series
completion rates
Feasibility: Low
cost, limited
resources

Exclusion: Not
between the ages
of 13-17, not an
active patient in
vax registry

Citation

Conceptual
Framework

Design/Method

Kumar et al.
(2019). A brief
provider
training video
improves
comfort with
recommending

Inferred
Health
Belief
Model

Descriptivequestionnaire
Purpose: Assess
efficacy &
feasibility of
provider training

Attrition: None
(electronic
monitoring)
Sample/Setting

N=96
Pt type:
pediatric
providers
Physicians-52%

Major
Variables and
Definitions
IV: Video w/
didactic teaching
outline HPV
disease & vax
DV: Provider
comfort w/

rather than single
dose

Measurement

Data Analysis

Study Findings

Decision for Use

Questionnaire
(baseline & posttest)

Likert-scale

Unacceptable to
delay:
Baseline- 50%
Post- 71%
p<.01

LOE: VI

McNemar test

Strengths:
inexpensive,
validated IV &
questionnaire

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
the human
papillomavirus
vaccine.

video about HPV
vax

Residents- 6.3%
NP/PA-23.9%

27
counseling on
HPV

Setting: 4
Pediatric PCOs

Country: USA
Funding:
American
Academy of
Pediatrics
Bias: None

Exclusions:
Not a peds
provider
Attrition: 11%

Citation

Malo et al.
(2018). Why is
announcement
training more
effective than
conversation
training for
introducing
HPV
vaccination? A
theory based
investigation.

Conceptual
Framework

Design/Method

Sample/Setting

Theory of
Planned
Behavior

RCT
CSS

N=83
n=47 (CG)
n=36 (IG)

Purpose: To assess
the impact of
announcement and
conversation
communication
training on HPV
vax coverage.

Pt type: Vax
prescribing
clinicians
serving
adolescents age
11-17 years.
S:

Major
Variables and
Definitions
IV: 1 hr
provider
education course
teaching the
EASE approach
for HPV rec
DV1: provider’s
HPV vax
attitudes

Counseling for
rationale:
Baseline- 49%
Post- 79%
p<.01

Weaknesses:
convenience
sampling, self-report,
did not assess vax
rates

Making a strong
rec:
Baseline- 68%
Post- 84%
p<.01

Conclusion: training
video significantly
improves provider
comfort in counseling
on vax & strong rec.
Feasibility:
Recommended d/t
low cost, minimal
resources & selfreported
improvement in
counseling
Decision for Use

Measurement

Data Analysis

Study Findings

Validated pre
and post training
surveys

Paired t-tests

DV1:
CG: M=4.4
IV: M= 4.7

Independent
sample t-tests
ANOVA

p < .001
d = .62
DV2:
CG:3.5
IV:4.1
p<.001

LOE: II
Strengths: no
attrition,
randomization,
validated
measurement tools
Weaknesses: short
follow-up, selfreport, possible social
desirability

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
f= 69%
m=31%

Country: USA
Funding:
Grants from
Pfizer &
National Cancer
Institute
Bias: None

Years of
practice:
>10 yrs: 66%
Setting:
pediatric PCO
providing HPV
vax to
adolescents

28
DV2: subjective
norms about
HPV vax

d=.90
DV3:
CG:4.1
IG: 44.6

DV3: selfefficacy to rec
HPV vax

p<.001
d=.89

DV4: time spent
discussing vax

DV4:
CG:3.8 min
IG:3.2 min
p=.01

Exclusions:
<100 11-12 yo
patients, no
pediatric
provider to order
HPV vax

Citation

Conceptual
Framework

Design/Method

Attrition= 0%
Sample/Setting

McLean et al.
(2017).
Improving
human
papillomavirus
vaccine use in
an integrated
health system:
Impact of a
provider and

Inferred
Theory of
Planned
Behavior

Pre- & post-test
(1yr post)
Quasi-experimental

N=24, 658
n=16,041 (IG)
n=8,617 (CG)

Purpose: To
evaluate the
effectiveness of a
multicomponent
provider
intervention in

Pt type: Medical
provider for
adolescents 1117 yo
A:

Conclusion: After a
1 hr HPV rec training
course, providers
report delivering rec
that is stronger,
timelier, more urgent
and more consistent
than pre-training.
Feasibility:
Recommended due to
low cost and minimal
time commitment

d=.28

Major
Variables and
Definitions
IV: Multicomponentprovider
training,
quarterly
feedback of vax
rates, patient
reminder

Measurement

Data Analysis

Study Findings

Decision for Use

EMR vax
registry

GEE

DV:

LOE: III

11-12 yo:
CG pre IV: 31.9%
CG post IV:
44.5%

Strengths: No
attrition, long FU
period

IG pre IV: 40.6%
IG post IV: 59.3%

Weaknesses: multicomponent so
increases cannot be
attributed to one item,

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
staff
intervention.

changing HPV vax
coverage

Country: USA
Funding: CDC
Bias: None

11-12- 28%
13-15-44%
16-17-28%
S:
F- 49%

29
DV: Change in
HPV vax
coverage

p=.002
13-17yo:
CG pre IV: 48.4%
CG post IV:
55.4%

Setting: Medical
offices that serve
a large number
of adolescents in
regional health
care system in
WI

IG pre IV: 53%
IG post IV: 61.7%
p=.001

Exclusions: Not
between the ages
of 11-18yo

Citation

Conceptual
Framework

Design/Method

Perkins et al.
(2015).
Effectiveness of
a provider
focused
intervention to
improve HPV
vaccination
rates in boys
and girls.

Inferred
Theory of
Planned
Behavior

RCT
Purpose: Evaluate
the effectiveness of
multi-component
provider-based
intervention in
increasing HPV
vax

Attrition- 0%
(electronically
followed)
Sample/Setting

N=13,118
n= 9025 (CG)
n=4093
Pt type:
Physicians, NPs,
PAs of
adolescents,
adolescents 1121yr

Major
Variables and
Definitions
IV: repeated
contact, focused
education on
HPV vax,
individualized
feedback on vax
rates, incentives
DV: HPV vax
rates

pediatric providers
higher in IV group
Conclusion: multifaceted approach
targeting providers
and parents increases
HPV vax rates
Feasibility:
Components such as
provider training low
cost and few
resources, however
patient recall is not
cost effective and
utilizes many
resources

Measurement

Data Analysis

Study Findings

Decision for Use

EMR
(pre IV, active, 6
month FU)

LR

Active phase:
DV:
f:
OR- 1.6
95% CI
m:
OR- 11
95% CI

LOE: II
Strengths: low
attrition rate,
randomized, diverse
demographics
Weaknesses: state
funded vax for boys,

6 month post:

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES

Country: USA
Funding:
American
Cancer Society
Bias: None

A:
<15 yr=54%
>15yr=46%
S:
f= 44%
m= 56%
R:
C= 8%
B= 47%
O= 45%

30
f:
OR-1.6
95% CI
m:
OR-8.5
95% CI

Definitions:
repeated contact:
HPV education
at staff meeting
every 6-8 weeks

p<.05

limited number of
practices
Conclusions: multicomponent provider
intervention increases
HPV vax in boys &
girls
Feasibility: Repeated
contact time
consuming, many
resources needed for
multicomponent IV

Setting:
Pediatric PCO &
community
health center
Exclusion: HPV
vax completion,
pregnancy

Citation

Conceptual
Framework

Design/Method

Attrition: 0%
(electronic
tracking)
Sample/Setting

Sanderson et al.
(2017).
Pragmatic trial
of an
intervention to
increase human
papillomavirus

Social
Ecological
Model

Clustered,
pragmatic nonRCT

N= 269
n= 167 (CG)
n= 194 (IG)

Purpose: Evaluate
the effectiveness of
provider-focused

Pt type: B or
Hisp adolescents
who had

Major
Variables and
Definitions
IV1: educational
video/flyer &
1 hr provider
training & rec

Measurement

Data Analysis

Study Findings

Decision for Use

Parent
Questionnaire
(pre & post, 12
month FU)

Chi-square

IV1:
CG:32.9%
IG: 45.4%

LOE: III

ITT
LR

RR= 1.38
95% CI

Strengths: noninvasive, pragmatic
trial

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES
vaccine in
safety-net
clinics.
Country: USA
Funding: NIH
Bias: None

and patient-focused
intervention
strategies aimed at
increasing HPV
vax rates among
AA’s and Hisp.

received no HPV
vax
A:
9-12-60%
13-15- 23%
16-18- 17%
S:
f- 50%
m- 50%
R:
AA- 90%
Hisp- 10%
Setting: PCO for
low income

31
IV2: Provider
training & rec
alone
DV: Receipt of
HPV vax

IV2:
RR: 4.08
95% CI

Weaknesses: nonrandomized, narrow
demographic range
Conclusion: Provider
recommendation had
4x increased HPV
vax rate, video/flyer
did not. Parent report
video/flyer was
helpful
Feasibility:
Recommended d/t
low cost and noninvasive

Exclusions: not
AA or Hisp, not
adolescent,
received HPV
vax
Attrition: 27%
(IG), 38% (CG)
d/t refusal

Key: A- age, ANOVA- analysis of variance, B-black, C- Caucasian, CDC- Centers for Disease Control and Prevention, CG-control group, CHICA- child health improvement
through computer automation, CI- confidence interval, CSS- cross-sectional survey, d- Cohen’s d, DV- dependent variable, DV1-dependent variable 1, DV2- dependent variable 2,
DV3- dependent variable 3, DV4- dependent variable 4 EASE- elicit, acknowledge, share, explain, ed- education, f-female, EMR- electronic medical record, FU- follow up, GEEgeneralized estimating equation, His- Hispanic, HPV- human papillomavirus, hr- hour, IG- intervention group, ITT- intention to treat, IV- independent variable, IV1- independent
variable 1, IV2-independent variable 2, LR- logistic regression, M- mean, m-male, min- minutes, N-sample (population), n-sample size (studies), NP- nurse practitioner, O- other,
OR- odds ratio, PA- physician assistant, PCO- primary care office, QI- quality improvement, R- race, RR- relative risk, RCT- randomized control trial, rec- recommendation, Sgender, vax- vaccine/vaccinated, yo- years old

IMPROVING HPV VACCINATION RATES

32
Appendix B

Table 2
Synthesis Table

Year
Design
LOE
Demographics
Age Range (yo)
Female %
Caucasian %
Setting
USA
PCO
Sample
Measurement Tools
EMR
Registry
Survey

Brewer
2017
RCT
II

Dempsey
2019
RCT/CSS
II

Dempsey
2019
RCT/CSS
II

Dixon
Krantz
2019
2017
RCT
QI
II
V
Study Characteristics

11-17

9-18
50.3
54.9

9-14
50
77

11-17
45.3
8.8

13-17
41
25

X
X
30(clinics)

X
X
43,132

X
X
342

X
X
1596

X
X
105

X

X
X
X

X

X

Kumar
2019
DS
VI

X
X
96

Malo
2018
RCT/CSS
II

McLean
2017
QE
III

Perkins
2015
RCT
II

Sanderson
2017
NRCT
III

11-17
69

11-17
49

11-21
44
8

9-18y
50
0

X
X
83

X
X
24, 658

X
X
13,118

X
X
269

X
X

X
X

X

X

X

X

Interventions
Provider Training (SIV)
Provider Training (MIV)
Parent Education
Parent & Provider Education

X

X

X

X

X

X

X
X
Outcomes

Change in HPV vax rates
Provider Perception
Parent Perception

Key: CSS= Cross Sectional Survey, DS= Descriptive Survey, EMR= Electronic Medical Record, LOE= Level of Evidence, MIV= Multicomponent Intervention,
NRRCT= Non-randomized controlled trial, PCO= Primary Care Office, QE= Quasi-experimental, QI= Quality Improvement, RCT= Randomized Controlled
Trial, SIV= Single Intervention, = significantly increased

IMPROVING HPV VACCINATION RATES
Appendix C
Figure 1
The Health Belief Model

33

IMPROVING HPV VACCINATION RATES
Appendix D
Figure 2
Rosswurm & Larrabee’s Model for EBP Change

34

IMPROVING HPV VACCINATION RATES

35

Appendix E
Table 3
Budget Plan
Phase

Activities

Educational Design and print educational
handouts (15 total x
Class
$.10/page)
Laptop to stream educational
app*
Educational app
HDMI cable to connect
laptop to television
Television to project images
larger*
Design and print pre and post
intervention surveys (30 total
x $.10/page)
Meeting room space for 1
hour*
Electricity and air
conditioning in meeting
space*
Pay 15 providers for 1 hour
of their time ($65/hr)*
Lunch for 15 people
Intellectus
Data
Collection
3 month post intervention
surveys (15x $.10 each)

Cost

subtotal

Total

$1.50

$0
$0
$10
$0
$3.00

$0
$50

$0
$200
$75
$1.50

$264.50
$75.50

$340.00