A Randomized Longitudinal Intervention Study to Assess the Efficacy and Feasibility of Telehealth-based Strategies to Increase Oral Chemotherapeutic Agent Medication Adherence and Health Literacy Among Cancer Patients.
Phase: NA
Conditions: Medication Adherence
Sponsor: East Carolina University

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Title: A randomized longitudinal intervention study to assess the efficacy and feasibility of 
telehealth-based strategies to increase oral chemotherapeutic agent medication adherence and 
health literacy among cancer patients in rural Eastern North Carolina. 
 
 
NCT Number: 53517 
 
Date: updated 5-17-2017 

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Requirements for Submitting a Full Proposal 
 
 
Section #1 - MISP Protocol Identification 
 
Study Title: 
A randomized longitudinal intervention study to assess the efficacy and 
feasibility of telehealth-based strategies to increase oral chemotherapeutic agent 
medication adherence and health literacy among cancer patients in rural Eastern 
North Carolina. 
Request Date: 
 
May 18, 2015 
 
Institution Name 
East Carolina University 
 
Investigator 
Contact 
Information: 
- Full address  
- Phone No. 
- Fax  No. 
- e-mail address 
 
PI: Alice Richman, PhD     PI: Essie Torres, PhD 
 
East Carolina University 
College of Health and Human Performance 
Department of Health Education and Promotion 
2209 / 3202 Carol Belk Building 
Greenville, NC 27858 
 
Phone: (252) 328-6431/ (252) 328-1818   Fax: (252) 328-1818 
 
Email: richmana@ecu.edu / torrese@ecu.edu   
 
 
 
 
 
 

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Section #2- Core Protocol 
 
2.1 Objectives & 
Hypotheses  
 
 
 
 
Objectives 
Objective 1: To assess the barriers to, and facilitators of, adherence to oral 
chemotherapeutic agents among cancer patients who are at high-risk of non-adherence.  
 
Objective 2: To test the effectiveness of two telehealth adherence motivation strategies 
among cancer patients on oral chemotherapeutic agents who are at high-risk of non-
adherence. 
 
Hypothesis: 
H1: Intervention groups will have increased medication adherence rates compared to 
control group 
H2: Intervention groups will have increased health literacy and self-efficacy rates 
compared to control group 
 
2.2 Background & 
Rationale, 
Significance of 
Selected Topic & 
Preliminary Data  
 
The World Health Organization has estimated that globally, only 50% of patients take 
their medications as prescribed1 and in the United States, 3 out of 4 Americans report 
not taking their medications as directed.2 Although lack of medication adherence 
affects all people, those with long-term chronic illnesses, such as cancer patients, have 
lower medication adherence rates as compared to patients with acute conditions.3-4 Oral 
chemotherapeutic agents (OCAs), including targeted therapies, are often prescribed to 
cancer patients during treatment to reduce tumor size, burden of disease, and increase 
overall survival.5 Although OCAs are increasingly being used and are commonly 
preferred by patients,5-8 adherence varies with compliance rates as low as 16% and as 
high as 100%.9-10 Additionally, adherence to OCAs is lower than adherence to 
intravenous chemotherapy.11  There are many reasons for non-adherence including 
side-effects, treatment costs, confusion of treatment instructions, inadequate social 
support, problems remembering, poor clinician/patient communication, low health 
literacy, and other psycho-social issues of patients.5,12-19 Cancer patients who adhere to 
their OCA regimens have a greater chance of cancer eradication, non-recurrence, long-
term quality of life1, as well as reduced hospital utilization and decreased health care 
costs.8,20 Thus, it is critical to develop and test interventions that effectively improve 
adherence to OCAs. Literature in this area is limited and has been criticized for not 
demonstrating significant effects on adherence behavior and for having low 
methodological quality.21-25 Furthermore, a recent systematic review found that a 
quantitative measure of adherence to OCAs was only reported in 4% of published 
clinical trials.26 This study will address some of these issues by conducting a 
theoretically driven randomized controlled trial using multi-method adherence 
strategies and quantitative adherence measurements across multiple points in 
time. 
Although the OCA medication adherence literature is limited and has methodological 
issues, some components of interventions in other medication adherence literature has 
shown promising results. Electronic monitored adherence feedback and cognitive-

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educational components were the only intervention approaches that had a significant 
effect on increased medication adherence per a systematic review and meta-analysis of 
medication adherence literature among drug dosing studies.27 Studies have also 
demonstrated that a strong patient-provider relationship that includes trust, consistency, 
and continued interaction, is a critical factor in a patient’s adherence behavior.28-29 
Furthermore, nurse-based interventions, including nurse-coach approaches, have 
significantly impacted adherence.30-33 Although these approaches have shown promise 
in increasing adherence, they are not always sustainable unless made cost-effective and 
translated into health care practices. Technology-based strategies in health care or 
telehealth have also started to play an important role as healthcare systems move away 
from the traditional fee for service system and towards new models of care. Thus, 
telehealth can potentially transition these evidence-based approaches into sustainable 
solutions. These technologies are becoming less expensive and more widely available 
and consequently can be adopted easier than ever before. The use of technologies for 
chronic disease care management has been associated with increased medication 
adherence, cost reductions, improvement in some physiologic measures, and high rates 
of satisfaction.47 We propose to unify components of these effective approaches in a 
novel way. We hypothesize that using technology-based strategies coupled with a 
tailored nurse coach approach, that includes a cognitive education intervention 
with a strong patient-provider communication component, will effectively 
increase medication adherence for our patient population. Evidence-based 
strategies for leveraging these technologies to improve health outcomes and behavior 
such as medication adherence will be extremely important in this changing healthcare 
environment. Given the critical role that effective patient-provider communication and 
patient-centered strategies play, technology should not be seen as a barrier, but rather a 
facilitator that provides a platform for sustainable and cost-effective evidence-based 
approaches for increased medication adherence.  
 
We propose to assess the efficacy and feasibility of two combined telehealth-based 
strategies (electronic medication-event monitoring and tailored nurse coach) in an 
effort increase OCA adherence and health literacy among cancer patients in rural 
Eastern North Carolina (ENC). With strong support from our collaborators at Vidant 
Medical Center and Leo W. Jenkins Cancer Center, study participants will include 
cancer patients that are within their first two cycles of a new oral chemotherapy 
regimen at Vidant Medical Center/Leo W. Jenkins Cancer Center, which serves 
individuals throughout the 29 counties in rural ENC. Patients at Leo W. Jenkins Cancer 
Center/ Vidant Medical Center are susceptible to barriers such as low literacy, 
transportation barriers, lack of social support, financial barriers, and many other factors 
that can affect their cancer care experience. These factors alone make this population at 
high-risk for non-adherence to their OCAs regimen. Vidant Health is the largest health 
care system in North Carolina, serving 1.4 million people. The Administrator of Cancer 
Services for Vidant Health, Phyllis DeAntonio and the Coordinator of the VHCNP, 
Judy Koutlas, are Co-Investigators on this study and have provided assurances 
concerning patient access, recruitment, and retention. This innovative and exploratory 
study can have a transformative impact on patient-centered cancer care and ultimately 
can improve the overall survival and quality of life of cancer patients.  

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2.3 Study Design 
 
 
Objective 1. To assess the barriers to, and facilitators of, adherence to oral 
chemotherapeutic agents among cancer patients who are at high-risk of non-
adherence.  
Leo W. Jenkins Cancer Center/ Vidant Medical Center serves cancer patients 
throughout the 29 counties of ENC. Using the three-stage process of elicitation, 
intervention, and evaluation, we will assess factors that influence non-adherence 
among this population. This formative qualitative assessment will be accomplished by 
conducting interviews/focus groups with English speaking cancer patients (n=25-30) 
and through key informant interviews with clinicians (n=17). Interviews/focus groups 
will include a cognitive interviewing component where we will ask patients to explain 
their OCA treatment plan in their own words, including their understanding of side 
effects/drug interactions. Comparative content analysis will be conducted using a 
written version of their treatment plan. We will also conduct key-informant interviews 
with all cancer care navigators (n=12), a sample of oncologists (n=4), and the oncology 
pharmacist at Leo W. Jenkins Cancer Center’s Outpatient Pharmacy. Specific aim 1 
will act as a baseline assessment to identify the unique factors that contribute to non-
adherence and will directly inform the development of tailored medication adherence 
strategies outlined in specific aim 2.  
 
Objective 2. To test the effectiveness of two telehealth adherence motivation 
strategies among cancer patients on oral chemotherapeutic agents who are at 
high-risk of non-adherence.  
We are proposing a randomized multi-arm intervention study of 150 subjects with two 
intervention arms and a control arm (50 subjects per arm). Subjects will be stratified by 
cancer and then randomized into each of the three groups. The Information-Motivation-
Behavioral Skills Model of Adherence and the results of specific aim 1 will guide this 
aim. Intervention Arm 1 will receive a Medication Event Monitoring System (MEMS) 
with feedback. Intervention Arm 2 will receive the MEMS plus a tailored nurse 
coaching component. Controls will receive standard-of-care from the Cancer Center. 
Specifically, we want to test whether a tailored nurse coaching intervention component 
will significantly improve medication adherence at higher rates as compared to the 
MEMS alone. The MEMS is a cap that is equipped with a microchip that registers the 
date and time of each cap opening (dosing history). MEMS caps will be given to 
patients in intervention Arms 1 and 2 either in clinic or it will be mailed to them. 
MEMS caps will only be provided to those who are taking a medication that comes in a 
bottle. Patients who receive their medication in blister packs will not be given a MEMS 
cap (as we do not think it’s a good idea for patients to transfer medication from blister 
packs to bottles). If medications patients are taking come in a bottle, Leo Jenkins 
pharmacy has agreed to fill Arm 1 and 2 oral chemotherapy prescriptions into a bottle 
that fits the MEMS cap. If patients in Arms 1 and 2 have two or more oral 
chemotherapy agents they are taking, they will be instructed to use the MEMS cap with 
the medication they take most frequently. Currently, there is no gold standard for 
measure of medication adherence but the MEMS device has been demonstrated to be a 
valid and objective method to assess medication adherence.14-15 The nurse coach 
intervention component will involve an individualized barriers/facilitators screening 
tool and regular contact with cancer patients via telephone calls across a six-month 

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period. We hypothesize that although both telehealth strategies will be effective at 
increasing medication adherence, Arm 2 will have a significantly greater effect on 
adherence. This hypothesis is supported by existing medication adherence literature 
that suggests a tailored intervention using multiple adherence strategies can potentially 
have a significant impact on increasing medication adherence.16    
Together, these two fundamentally linked aims will test innovative approaches that will 
help us understand what type of intervention may deliver the biggest impact in 
medication adherence to OCAs for cancer patients.  Most importantly, developing and 
implementing evidence-based strategies for medication adherence can ultimately 
improve the overall survival and life expectancy of cancer patients. 
  
2.4 Study Flowchart 
 
See attached project timeline and recruitment timeline in Appendix A & B, 
respectively 
2.5 Study 
Procedures 
The Information-Motivation-Behavioral Skills Model of Adherence (IMB model) will 
guide the proposed study.  This model posits that adherence information, adherence 
motivation, and adherence behavioral skills are empirically linked to adherence 
behavior which ultimately impacts health outcomes. One important aspect of the IMB 
model is that it takes into account external moderating factors that can influence the 
relationship between IMB model constructs and adherence behavior.42 The IMB model 
of adherence is based on a validated generalized IMB approach to understanding and 
promoting health behavior and has been used extensively in research concerning HIV-
related behaviors (i.e. prevention and adherence), diabetes self-care, and condom use 
among high-risk populations.42-45  At its core, the IMB model theorizes that adherence-
related information, motivation, and behavioral skills are fundamental determinants of 
adherence. Therefore, if individuals are well informed, motivated to act, and acquire 
needed adherence behavioral skills, they can effectively increase their adherence 
behavior.43-44 The intervention in this study will use two evidence-based telehealth 
strategies for improving adherence, while examining mediating and moderating factors 
that may influence adherence to OCAs in an effort to understand the underlining 
mechanism/s for an effective intervention. Mediating factors include Adherence 
Information, Adherence Motivation, and Adherence Behavioral Skills (see Table 1 in 
Appendix). Moderating factors include access to medical care and insurance status, 
stigma of cancer, psychological health (i.e. depression), rurality-related and quality of 
life factors.  
Using the three-stage process of elicitation, intervention, and evaluation, this study will 
consist of a formative research phase in which an assessment of the population of 
interest’ initial levels of adherence will be conducted, comprehension of treatment 
plan, and an assessment of facilitators and barriers to medication adherence relevant to 
both mediating and moderating factors. This formative research phase will inform a 
tailored adaptation of the IMB model for the population of interest to remediate 
identified adherence-related information, motivation, and behavioral skills deficits and 
moderators that can be modified to influence adherence behavior. Finally, we will 
evaluate the tailored adherence strategies guided by the IMB model using multi-model 
outcome data (Table 2) expected to be influenced by improved adherence behavior.      
Objective 1. To assess the barriers to and facilitators of adherence to oral 
chemotherapeutic agents among cancer patients who are at high-risk of non-

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adherence.  
Overview: Poor medication adherence encompasses more than patients not taking their 
medicines as directed.47 The National Council on Patient Education provided a 
comprehensive overview of factors that contribute to poor adherence, which include 
medication-, patient-, prescriber-, pharmacy-related factors. Compounding these issues 
is low health literacy and transportation barriers that affect timely access to follow-up 
care which are prominent issues among rural populations. This study will conduct a 
baseline qualitative assessment to identify and understand the unique factors that 
contribute to non-adherence, which will inform a tailored approach of adherence 
strategies that specifically address the needs of our population of interest. 
Population of Interest: ENC serves a large geographic area of NC that includes 29 of 
the 100 counties in NC. The NC Department of Commerce annually ranks counties 
based on economic well-being and assigns each a tier designation (Tier 1, most 
economically distressed through Tier 3, least economically distressed). Overall, ENC 
counties comprise approximately 38% of all Tier 1 counties, the most economically 
distressed counties in the state. Vidant Health is the largest health care system in NC 
serving the ENC region, and has been accredited by the American College of Surgeons 
Commission on Cancer since 1991, as well as a designated as an Academic 
Comprehensive Cancer Program.  
Recruitment Strategy: Participants for this aim will be recruited from Leo W. Jenkins 
Cancer Center.  Maximum variation sampling will be used to select participants to 
provide a representative sample for conducting needed preliminary assessments. 
Navigators will identify, contact, and refer cancer patients for this formative research 
phase. Qualitative assessments (i.e. interviews focus groups) will be conducted with 
25-30 English speaking cancer patients who are currently undergoing or have recently 
completed (within 3 months) an OCA regimen to understand their barriers to and 
facilitators of adherence. In addition to the patient’s themselves, key-informant 
interviews will be conducted with all cancer care navigators (n=12), a sample of 
oncologists (n=4), and the oncology pharmacist. Co-investigators, Koutlas and 
DeAntonio, will assist in recruitment and coordination of interviews.  
Research Design: First, qualitative assessments (i.e. interviews/focus groups) will last 
approximately one hour and will be held at Leo Jenkins Cancer Center or Vidant 
Medical Center during the cancer patient’s scheduled follow up appointments with 
their oncology team. Participants will provide written informed consent prior to the 
interview/focus group discussions. Participants will receive a small monetary incentive 
for their participation ($50 gas card). A panel of experts (including faculty from health 
education and public health, oncologists, cancer nurse navigators, and cancer care 
team) will inform the topical guide used in these assessments. Topical guide questions 
will include questions regarding illness experiences (symptoms/side effects, 
complexity of regimen), interactions with others, caregiver availability, informational 
resources, cognitive processes, and mood state. Data gathered from these discussions 
will help identify the origins of non-adherence and will inform the intervention 
components of specific aim 2. Both surface and deep structure adaptation will take 
place in an effort to make instruments and interventions culturally and linguistically 
relevant as well as understanding our population’s core cultural values, preferences, 
and medically related needs.49  

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Second, we will conduct in-person cognitive interviews with cancer patients by asking 
patients to explain their OCA treatment plan in their own words, including their 
understanding of side effects/drug interactions.50 The purpose is to investigate how 
patients interpreted their respective treatment plans and to document the nature of 
misunderstandings that may contribute to non-adherence. From a health literacy 
perspective, we hypothesize that misunderstanding may be the result of patient literacy 
limitations, complexity of treatment plans, and the lack of information provided 
regarding potential side-effects, drug interactions, adherence expectations, and how to 
address missed or delayed doses. Comparative content analysis will be conducted using 
a written version of the patient’s prescribed treatment plan provided by their 
oncologist.  
Last, we will conduct key-informant interviews with all cancer care navigators from 
Leo W. Jenkins Cancer Center (n=12), a sample of oncologists who treat patients at 
Leo W. Jenkins Cancer Center (n=4), and the oncology pharmacist at Leo W. Jenkins 
Cancer Center’s Outpatient Pharmacy. These qualitative interviews will provide an in-
depth understanding, from the provider’s perspective, regarding the unique challenges 
in working with patients who are at high-risk for non-adherence and will identify the 
structural factors that might influence sub-optimal adherence among this population. 
Additionally, it will provide a preliminary understanding of the functional definition of 
adherence for cancer patients at the Cancer Centers and acceptable levels of medication 
adherence among health care providers. This data will inform the development of 
tailored adherence strategies for increased medication adherence, guided by the IMB 
model, outlined in specific aim 2. As part of specific aim 1, we will assess health 
literacy. Low literacy has been associated with a lack of knowledge about a disease 
process and poor self-management skills in patients with chronic disease.50 
Furthermore, marginal functional literacy has been associated with poor physical 
health, psychological health, and higher health care costs.50 The implication for 
medication adherence is the inability to read, understand, and act on health information 
and medication use. We will assess baseline health literacy using the Rapid Estimate of 
Adult Literacy in Medicine Short Form50 to inform the development of a linguistically 
appropriate tailored adherence intervention.  
Data Analysis: All qualitative assessments will be audio-recorded, transcribed 
verbatim and analyzed using qualitative analysis techniques. Open, axial, and selective 
coding will allow for data reduction and categorization of data into themes. Analytic 
memos will be written and kept throughout the coding process. In order to check for 
coding consistency, trustworthy or consistency checks will be employed. The coding 
process will be an iterative one and will be conducted by a team of two qualitative 
researchers. 
Feasibility: The study’s co-investigators are active partners in the study and will be 
facilitating access to the identified populations of interest for specific aim 1. The 
collaborative nature of this proposal will provide outcomes that can potentially 
improve the efficacy of services provided via the Leo W. Jenkins Cancer Center/ 
Vidant Medical Center and medical adherence among cancer patients. There is a strong 
commitment from Vidant Medical Center in the development, implementation, and 
evaluation of this proposed study. Drs. Richman and Torres have extensive qualitative 
research experience. Specifically, they have worked with hard-to-reach and medically 
underserved populations, in both rural and urban settings, and have experience in 

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topical guide development, study recruitment, conducting the proposed qualitative 
assessment, transcription, and analysis.  
Expected Outcomes: Specific Aim 1: Given our rural ENC population, we hypothesize 
that low health literacy, confusion of treatment regimen and potential side-effects, 
timely access to prescribed treatment, poor patient-provider communication, misguided 
perceptions of adherence, and not remembering may be barriers to adherence. 
Facilitators may include adherence education, self-efficacy, affect support, and 
reminder systems.  
Objective 2. To test the effectiveness of two telehealth adherence motivation 
strategies among cancer patients on oral chemotherapeutic therapy agents who 
are at high-risk of non-adherence.  
Overview: We are proposing a randomized multi-arm intervention study (n=150) with 
two intervention arms and a control arm. The IMB model and the results of specific 
aim 1 will guide this aim. Intervention Arm 1 will receive a Medication Event 
Monitoring System (MEMS) with feedback. Intervention Arm 2 will receive the 
MEMS plus a tailored nurse coach component. Controls will receive standard-of-care 
from their Cancer Center. Specifically, we want to test whether a tailored nurse 
coaching intervention component will significantly improve medication adherence at 
higher rates as compared to MEMS alone. The MEMS is a medication bottle with a cap 
that is equipped with a microchip that registers the date and time of each cap opening 
(dosing history). Currently, there is no gold standard for measure of medication 
adherence but the MEMS device has been demonstrated to be a valid and objective 
method to assess medication adherence.51-52 The nurse coach intervention component 
will involve an individualized barriers/facilitators screening tool and regular contact 
with cancer patients via telephone calls across a six-month period. We hypothesize that 
although both telehealth strategies will be effective at increasing medication adherence, 
Arm 2 will have a significantly greater effect on adherence. This hypothesis is 
supported by existing medication adherence literature that suggests a tailored 
intervention using multiple adherence strategies can potentially have a significant 
impact on increasing medication adherence.47  
Population of Interest: Participants for specific aim 2 will be recruited from Vidant 
Medical Center/Leo W. Jenkins Cancer Center. Eligibility criteria includes patients 
who are starting a new cycle of OCAs (recruitment will happen within their first two 
cycles), ambulatory, age 18 years or older, able to consent for self, able to understand 
and speak English, and have a cellphone or landline. In addition, since this intervention 
uses telehealth approaches, participants must be able to understand and willing to use 
the MEMS devices. Exclusion criteria includes life expectancy <3 months as 
determined by oncologist, current participation in a similar study or in investigational 
drug trials where adverse effects have not been fully elucidated, patients who are on 
simultaneous oral and IV chemotherapeutic regimens, and presence of significant 
psychiatric or cognitive impairments as determined by oncologists and study team.      
Recruitment Procedures:  On a daily basis, the study team (i.e. LJCC clinical trial 
nurses) will discuss with the nurses and oncologists from Leo W. Jenkins Cancer 
Center (LJCC) about potential cancer patients who started a new cycle of OCAs and 
who are potentially eligible for participation in this study. The nurse coach or research 
assistants will provide a recruitment flyer about the study to potential participants when 
the patient is in the clinic or hospital. If the patient provides consent, a member from 

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the study team can initiate the enrollment visit concurrently or can contact patients by 
phone to set up an initial enrollment visit within two weeks. At enrollment, written 
informed consent will be obtained and baseline assessments will be administered to all 
participants. Randomization to Arm 1, Arm 2, or Control Arm will also occur at 
enrollment. All study materials and procedures will be approved by the East Carolina 
University and Medical Center Institutional Review Board.  
Intervention Design:  
Control Group (Standard-of-Care). Subjects assigned to the control arm will receive 
standard-of-care at Vidant Medical Center and Leo W. Jenkins Cancer Center, which 
includes education on treatment plan provided by a medical oncologist, clinical 
pharmacist, and/or nurse, follow-up by a nurse navigator, and patient education 
information packets included in the product information from the drug manufacturer. 
Lite Group (Arm 1: MEMS). Subjects randomized to the lite group will receive a 
Medication Event Monitoring System (MEMS) device with feedback. Subjects will be 
advised to only open their pill bottles when they take their medications. Patients will 
also be given a MEMS diary to record unscheduled cap openings, such as those to refill 
the bottle, so that those unscheduled events unrelated to adherence can be removed 
from analysis. Currently, there is no gold standard measure of medication adherence, 
but the MEMs has been used extensively in medication adherence studies.54-55 
Furthermore, it has been shown that drug package opening times is a strong indicator 
of the actual time a person takes a dose of medication.38-40 Participants will meet with 
the nurse coach during their regularly scheduled monthly oncology visits where the 
MEMS data will be collected. During this monthly meeting, participants in the lite 
group will receive feedback of their medication-taking behavior via a MEMS report. 
The nurse coach will explain to the participant how to interpret the feedback report. 
The purpose of this feedback is to give participants insight into their own medication-
taking behavior, and assess if this type of feedback alone can increase their self-
efficacy and improve medication adherence and health outcomes.    
Enhanced Group (Arm 2: MEMS + Nurse Coach). Subjects randomized to the 
enhanced group will receive the MEMS outlined in Arm 1, plus a tailored nurse coach 
component. Before beginning their OCA regimen, patients in Arm 2 will be 
administered a barriers/facilitators screening tool (adapted from Schneider et al5., and 
informed by IMB model/specific aim 1) that will help the nurse coach identify specific 
adherence strategies (i.e. cognitive education, knowledge skills, and affective support) 
tailored to the participant’s needs. Once a tailored intervention plan is developed, 
participants will receive a 60-minute session conducted by the nurse coach. The 
educational component will include: information about the patient’s cancer treatment, 
why it was selected, and expected outcomes; clear instructions about medication 
dosing schedule; what to do if a dose is missed or delayed; medication side effects 
and/or potential drug interactions; addressing adherence-related heuristics; and a self-
developed glossary of terms associated with the OCA regimen (translating difficult 
medical terminology into meaningful “patient-language”). The behavioral skills and 
affective support strategies include coping strategies for side effects, skills for fitting 
medication regimen into daily routine (i.e. cues and medication plan), identifying a 
support network, communication skills for interacting with providers, and facilitating a 
positive perception of a positive self-management experience. Patients will receive 
weekly phone calls from the nurse coach during the first month of the intervention, and 

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then bi-monthly follow-up calls for the remainder of treatment or 6-month follow-up 
period (whichever occurs first).  During these calls, lasting 15-20 minutes, the nurse 
coach will assess adherence strategies, evaluate for effectiveness, and modify or 
reinforce as needed. During monthly face-to-face meetings, participants in the 
enhanced group will also receive feedback of their medication-taking behavior from 
the MEMS. MEMS feedback will be used to show patients their own medication-
taking behavior via the MEMS Report, to correct any misperceptions of actual 
adherence and to identify problem areas. The nurse coach will modify the intervention 
plan to address identified barriers to adherence at this time.  
2.6 Study Duration 
2 years;  Start: September 1, 2015 End: August 31, 2017 
2.7 Statistical 
Analysis and 
Sample Size 
Justification  
 
Table 2. Outcome 
Measures 
Data Collection Instrument 
Expected Outcomes 
Primary Outcome Measures 
Self-report medication 
adherence 
Ask-20 
H1: Arm 1 and Arm 2 will have increased self-
report adherence rates compared to control 
group 
H2: Arm 2 will have significantly higher rates of 
self-report medical adherence compared to 
Arm 1 and Control group 
Non-self-report 
measures of adherence 
1. 
Dosing History 
2. 
Pill count 
3. 
Pharmacy refill 
rates 
4. 
Missed Medical 
Appointments  
1. EM-feedback: MEMS Data 
2. Pill count: This will be conducted 
in-person by nurse coach 
3. Pharmacy refill rates: Secondary 
Data from Electronic Medical 
Record 
4. Secondary Data from Electronic 
Medical Record 
H1:Arm 1 and Arm 2 will have increased non-
self-report adherence rates compared to control 
group 
H2: Arm 2 will have significantly higher rates of 
medical adherence compared to Arm 1 and 
Control group 
 
Self-Efficacy 
Self-Efficacy for Appropriate 
Medication Use Scale(SEAMS) 
(pre/post) 
H1: Arm 2 will have significantly higher rates of 
self-efficacy compared to Arm 1 and Control 
group 
Health Literacy 
CHLT-30 
REALM-R 
H1: Arm 2 will have significantly higher health 
literacy level compared to Arm 1 and Control 
group 
Secondary Outcome Measures 
Usability and 
Satisfaction  
1. 
Satisfaction with nurse coach 
components 
2. 
Usability of MEMs for 
medication adherence 
H1: Arm 2 will have significantly higher 
satisfaction level compared to Arm 1 and 
Control group 
Hospital Utilization (i.e. 
ER visits, 
hospitalizations, and 
length of stay) 
Secondary Data from Electronic 
Medical Record 
H1: Arm 1 and Arm 2 will report lower hospital 
utilization rates compared to control group 
 
We will also assess health outcomes/treatment response via results from routine 
diagnostic testing (e.g. CT, MRI, PET, bone scan, bone marrow aspiration and biopsy, 
tumor marker), as per oncologist for participants enrolled in this study. Co-
investigators have agreed to assist with the interpretation of diagnostic test results. We 
expect diagnostic results to be affected by adherence behavior. 
   
Description of Assessments Tools: 
Ask-20 Tool: This is a validated tool that may be a useful brief measure of adherence 
behavior and barriers to treatment adherence (Matza et al., 2009). 
Cancer Health Literacy along a Continuum  (CHLT-30): The CHLT-30 is designed 
to measure cancer health literacy along a continuum. Accurate measurements of 
theoretical constructs such as cancer health literacy allow researchers to estimate 

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treatment effect in intervention studies, assess change over time, and establish 
relationships with theoretically relevant factors and clinically important outcomes (e.g., 
morbidity, mortality). The instrument has a broad content coverage, very high 
reliability, and is strongly linked to self-confidence about engaging in health decisions. 
The CHLT-30 is easy to administer and takes approximately 10–15 minutes. The test 
score is obtained by the total number of correct responses and ranges from 0 to 30. 
Self-Efficacy for Appropriate Medication Use Scale(SEAMS): This is a validated 
13-item self-report scale measuring patient confidence in the ability to take 
medications properly. The measure has high internal consistency and strong criterion-
related validity.19 This survey will be administered in-person by nurse coach at 
enrollment visit, and and final in-person meeting. 
REALM-R: This is a shortened version of the REALM, which is used to help identify 
literacy levels of adult patients. It consists of 8 items, and is used to measure how well 
individuals can read words they will encounter in a medical setting.59 This will be used 
as initial assessment of the level of health literacy during the formative research phase. 
 
Sample Size Estimation. A sample size of 150 subjects, 50 in each arm (control, Arm 
1, and Arm 2) is sufficient to detect a 10-point difference in mean medication 
adherence rates (measured by MEMS) between the three groups, assuming equal 
standard deviation of 16 using a two-tailed t- test of difference between means with 
80% power and a 2-sided alpha of .05. Medication adherence rates in the literature vary 
based on the methods of measurement. The assumptions used in our sample size 
calculations are based on similar studies, especially those that used the MEMs device 
as the primary measure of medication adherence [4,6]. Participants will be followed up 
for a total of 6 months. 
 
Statistical Analysis: A variety of bivariate statistical analyses will be utilized to 
examine the data collected from this study.  Descriptive statistics and data 
visualizations will be used to assess both the overall distribution of important outcome 
variables as well as differences in distributions between treatment arms.  Differences 
between treatment groups for pre/post changes in non-count quantitative outcomes (i.e. 
Morisky Medication Adherence Scale Scores, Self-Efficacy Scale, etc.) will be 
assessed using a combination of t-tests and ANOVA methods or nonparametric tests 
(Kruskal-Wallis and/or Wilcoxon tests) as appropriate for the collected data.  Count 
based quantitative outcomes (number of ER visits, hospitalizations, days of stay) will 
be compared across groups using a mix of count regression models. In particular, 
Poisson regression will be used to compare treatment arms on standard count data 
outcomes. Alternatively, if the counts are found to be overdispersed (having higher 
than expected variance) then negative binomial regression will be utilized to compare 
treatment arms with an eye to accounting for the unexpectedly high variation in count 
outcome data.  Categorical data (i.e. adherence counts and rates) will be analyzed with 
via contingency tables analysis utilization a mixture of Chi-Square tests and Fisher’s 
exact tests as appropriate. All statistical analysis will be performed using a mixture of 
SPSS (version 21) and SAS Software (version 9.4).  
 

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2.8 Specific Drug 
Supply 
Requirements  
We are not requesting any drug supplies for this project. 
2.9 Adverse 
Experience 
Reporting 
Participants will be told that they are free to leave the study at any time and can resume 
services at their respective cancer center/clinic with no penalty. If an adverse 
experience should be reported, we are required to notify our institutional review board 
(IRB).  Then, the IRB will review the report and determine the appropriate action. 
2.10 Itemized Study 
Budget  
Our itemized study budget and justification appears in Appendix C.     
2.11 References 
1. World Health Organization. Adherence to Long-Term Therapies: Evidence for 
Action. Eur J Cardiovasc Nurs. 2003; 2: 323. 
2. Cooke C. Take As Direction: A Prescription Not Followed. National 
Community Pharmacists Association. December 15, 2006. 
3. Osterberg L, Blashcke T. Adherence to Medication. N. Engl J Med. 2005; 
353:487-497. 
4. U.S. Department of Health and Human Services. Medications and Older 
People. FDA Consumer Magazine. September-October 1997. Accessed 
February 18, 2015. 
5. Schneider S, Adams D, Goddelin T. A Tailored Nurse Coaching Intervention 
for Oral Chemotherapy Adherence. J Adv Pract Oncol. 2014; 5(3): 163-173. 
6. Weingart SN, Bach PB, Johnson SA, et la. NCCN Task Force Report: Oral 
Chemotherapy. Journal of the National Comprehensive Cancer Network. 2008; 
6(3): 1-25. 
7. Lio G, Franssen E, Fitch MI, Warner E. Patient preferences for oral versus 
intravenous palliative chemotherapy. J Clin Oncol. 1997; 15(1): 110-115. 
8. Twelves C, Gollins S, Grieve R, Samuel L. A randomized cross-over trial 
comparing patient preference for oral capecitabine and 5-
fluorouracil/leucovorin regimens in patients with advanced colorectal cancer. 
Annals of Oncology. 2006; 17(2): 239-245. 
9. Ruddy K, Mayer E, Partridge A. Patient Adherence and Persistence with Oral 
Anticancer Treatment. CA: A Cancer Journal for Clinicians. 2009; 59(1): 56-
66. 
10. Partridge AH, Avorn J, Wang PS, Winer EP. Adherence to Therapy with Oral 
Antineoplastic Agents. J Natl Cancer Inst. 2002; 94(9): 652- 661. 
11. Wood L. A review on adherence management in patients on oral cancer 
therapies. J Oncol Nurs. 2012; 16(4): 432-438. 
12. Verbrugghe M, Verhaeghe S, Lauwaert K, Beeckman D, Van Hecke A. 
Determinants and associated factors influencing medication adherence and 
persistence to oral anticancer drugs: A systematic review. Cancer Treat Rev. 
2013; 39(6): 610-621. 
13. Ngoh LN. Health literacy: A barrier to pharmacist-patient communication and 
medication adherence. J Am Pharm Assoc. 2009; 49(5):32–146. 

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14. DiIorio C, McCarty F, DePadilla L, et al. Adherence to Antiretroviral 
Medication Regimens: A Test of a Psychosocial Model. AIDS and behavior. 
2009;13(1):10-22. doi:10.1007/s10461-007-9318-4. 
 
15. Duong M, Piroth L, Grappin M, et al. Evaluation of the Patient Medication 
Adherence Questionnaire as a tool for self-reported adherence assessment in 
HIV-infected patients on antiretroviral regimens. HIV Clin Trials. 2001; 2:128–
135.  
16. Fongwa MN, Evangelista  LS, Hays RD, et al. Adherence treatment factors in 
hypertensive African American women. Vasc Health Risk Manag. 2008; 
4(1):157–166. 
17. George J, Munro K, McCaig DJ, Stewart DC. Prescription medications: Beliefs, 
experiences, behavior, and adherence of sheltered housing residents. Ann 
Pharmacother. 2006;40(12): 2123–2129.  
18. Odegard PS, Gray SL. Barriers to medication adherence in poorly controlled 
diabetes mellitus. Diabetes Education.  2008;34(4):692–697.  
19. Rust CF, Davis C, Moore M. Medication Adherence Skills Training for 
African-American Breast Cancer Survivors: The Effects on Health Literacy, 
Medication Adherence, and Self-Efficacy. Soc Work Health Care. 2015; 
54(1):37-41. 
20. Agboola S, Flanagan C, Searl M, Elfiky A, Kvedar J, Jethwani K. Improving 
Outcomes in Cancer Patients on Oral Anti-Cancer Medications Using a Novel 
Mobile Phone-Based Intervention: Study Design of a Randomized Controlled 
Trial. Eysenbach G, ed. JMIR Research Protocols. 2014;3(4):e79. 
doi:10.2196/resprot.4041. 
21. Mathes T, Antonine SL, Pieper D, Eikermann M. Adherence enhancing 
interventions for oral anticancer agents: a systemic review. Cancer Treatment 
Reviews. 2014; 40: 102-108. 
22. Haynes B, Yao X, Degani A, Kripalani S, Garg A, McDonald HP. Interventions 
to enhance medication adherence. Cochrane Database Syst Rev. 2005; 19(4). 
23. Haynes RB, Ackloo E, Sahota N, McDonaold HP, Yap X. Interventions for 
enhancing medication adherence. Cochrance Database Syst Rev. 2008; 16(2). 
24. McDonaold HP, Garg AX, Haynes RB. Intervention to Enhance Patient 
Adherence to Medication Prescriptions. JAMA. 2002; 288(22): 2686- 2879. 
25. Viswanathan M, Golin CE, Jones CD, et al. Interventions to Improve 
Adherence to self-administered Medications for chronic disease in the United 
States: A systematic review. Ann Intern Med. 2012; 157(11): 785-795. 
26. Bergsbaken JJ, Eickhoff JC, Buss BA, Mably MS, Kolesar JM. Assessment of 
adherence with oral anticancer agents in oncology clinical trials: A systemic 
review. J Oncol Pharm Pract. 2015; 0(0):1-9.  
27. Demonceau J, Ruppar T, Krostanto P, Hughes D, Fargher E, et al. Identification 
and assessment of adherence-enhancing interventions in studies assessing 
medication adherence through electronically complied drug dosing histories: a 
systematic literature review and meta-analysis. Drugs. 2013; 73: 545-562.  
28. Nerini E, Grip L, Camm A, Giugliano R. Atrial fibrillation and the ‘other drug 
problem’: reducing non-adherence with technology. Eur Heart J. 2013; 
34:2031-2033. 

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29. Reynolds NR. The problem of antiretroviral adherence: A self-regulatory model 
for intervention. 2003; 36(11):117-124. DOI: 10.1080/0954012021000039815 
30. Foley EC, D’Amico F, Merenstein JH. Five-year follow-up of a nurse-initiated 
intervention to improve mammography recommendation. J Am Board Fam 
Pract. 1995; 8(6):452–456. 
31. McCauley KM, Bixby MB, Naylor MD. Advanced practice nurse strategies to 
improve outcomes and reduce cost in elders with heart failure. Disease 
Management. 2006; 9(5), 302–310. http://dx.doi.org/10.1089/ dis.2006.9.302 
32. Vied RY, Caron P A, Rosenthal KL,  Weismantel, B. Monitoring patient safety 
with oral chemotherapy: A nurse-managed project. Nurs Spectr (N Engl Ed). 
2004; 8(10):10. 
33. Holistic nursing: scope and standards of practice. 2nd ed. Silver Spring, MD: 
American Holistic Nurses Association and American Nurses Association 
(AHNA/ANA); 2013. 
34. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 
2005;353(5):487–97. 
35. Kass MA, Gordon M, Meltzer DW. Can ophthalmologists correctly identify 
patients defaulting from pilocarpine therapy? Am J Ophthalmol. 
1986;101(5):524–30. 
36. Norell SE. Accuracy of patient interviews and estimates by clinical staff in 
determining medication compliance. Soc Sci Med E. 1981;15(1):57–61. 
37. Okeke CO, Quigley HA, Jampel HD, Ying GS, Plyler RJ, Jiang Y, et al. 
Adherence with topical glaucoma medication monitored electronically the 
Travatan Dosing Aid Study. Ophthalmology. 2008;116(2):191–9. 
38. Girard P, Sheiner LB, Kastrissios H, Blaschke TF. Do we need full compliance 
data for population pharmacokinetic analysis? J Pharmacokinet Biopharm. 
1996;24(3):265–82. 
39. Rubio A, Cox C, Weintraub M. Prediction of diltiazem plasma concentration 
curves from limited measurements using compliance data. Clin Pharmacokinet. 
1992;22(3):238–46. 
40. Vrijens B, Tousset E, Rode R, Bertz R, Mayer S, Urquhart J. Successful 
projection of the time course of drug concentration in plasma during a 1-year 
period from electronically compiled dosing-time data used as input to 
individually parameterized pharmacokinetic models. J Clin Pharmacol. 
2005;45(4):461–7. 
41. Checchi KD, Huybrechts KF, Avorn J, Kesselheim AS. Electronic Medication 
Packaging Devices and Medication Adherence: A Systematic 
Review. JAMA.2014;312(12):1237-1247. doi:10.1001/jama.2014.10059. 
42. Fisher JD, Fisher WA. An information-motivation-behavioral skills model of 
adherence to antiretroviral therapy. Health Psychology. 2006; 25(4): 462-473. 
43. Fisher WA, Fisher JD, Harman J. The information–motivation– behavioral 
skills model: A general social psychological approach to understanding and 
promoting health behavior. In J. Suls &K. Wallston (Eds.), Social 
psychological foundations of health and illness. 2003; 87–106. 
44. Osborn CY, Egede LE. Validation of an Information–Motivation–Behavioral 
Skills model of diabetes self-care (IMB-DSC). Patient Education Counseling. 
2010; 79(1): 46-54. 

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45. Robertson AA, Stein JA, Baird-Thomas C. Gender differences in the prediction 
of condom use among incarcerated juvenile offenders: testing the information-
motivation-behavior skills (IMB) model. Journal of Adolescent Health. 2006; 
38(1): 18-25.  
46. Anderson, ES, Wagstaff DA, Heckman TG, et al. Information-motivation-
behavioral skills (IMB) model: Testing direct and mediated treatment effects on 
condom use among women in low-income housing. Annals of Behavioral 
Medicine. 2006; 31(1): 70-79.  
47. Ellwood M, Lichtenfeld L, Parker RM, et al. Enhancing prescription medicine 
adherence : A national action plan. NCPIE. 2007; 1-38. 
48. Lea CS, May C, Miller E. Cancer Prevention in Eastern North Carolina Task 3: 
Final Report A Cancer Profile of Eastern North Carolina. 2012; 1-153. 
49. Resnicow K, Baranowski T, Ahluwalia JS, Braithwaite RL. Cultural sensitivity 
in public health: defined and demystified. PubMed.1999; 9(1):10-21. 
50. Bass P, Wilson J, Griffith C. A Shortened Instrument for Literacy Screening. J 
Gen Intern Med. 2003;18: 1336-1339. 
51. Wolf M, Davis T, Skrank W, et al. To err is human: Patient misinterpretations 
of prescription drug label instructions. Patient Educ Couns. 2007; 67: 293-300. 
52. Wu JR, Coreley D, Lennie T, Moser D. Effect of a Medication-Taking 
Behavior Feedback Theory-Based Intervention on Outcomes in Patients With 
Heart Failure. JACC Heart Fail. 2012;18(1): 1-9. 
53. Agboola S, Flanagan C, Searl M, et al. Improving Outcomes in Cancer Patients 
on Oral Anti-Cancer Medications Using a Novel Mobile Phone-Based 
Intervention: Study Design of a Randomized Controlled Trial. JMIR Res 
Protoc. 2014; 3(4). doi:10.2196/resprot.4041 
54. Clifford S, Perez-Nieves M, Skalicky AM, Reaney M, Coyne KS. A systematic 
literature review of methodologies used to assess medication adherence in 
patients with diabetes. Curr Med Res Opin. 2014 Jun;30(6):1071-1085. 
doi:10.1185/03007995.2014.884491. 
55. Simons S, Ringsdorf S, Braun M, Mey UJ, Schwindt PF, Ko YD, et al. 
Enhancing adherence to capecitabine chemotherapy by means of 
multidisciplinary pharmaceutical care. Support Care Cancer. 2011 
Jul;19(7):1009-1018 doi:10.1007/s00520-010-0927-5 
56. Moon JH, Sohn SK, Kim SN, et al. Patient counseling program to improve the 
compliance to imatinib in chronic myeloid leukemia patients. Med Oncol. 
2012;29(2):1179–85. 
57. Khandelwal N, Duncan I, Ahmed T, Rubinstein E, Pegus C. Oral chemotherapy 
program improves adherence and reduces medication wastage and hospital 
admissions. J Natl Compr Canc Netw. 2012;10(5):618–25. 
58. Morisky D.E, Ang A, Krousel-Wood M, Ward H.J. Predictive Validity of A 
Medication Adherence Measure in an Outpatient Setting. J Clin 
Hypertens(Greenwich). 2009; 1-14. 
59. Weiss B, Mays M, Martz W, et al. Quick Assessment of Literacy in Primary 
Care: The Newest Vital Sign. Ann Fam Med. 2005; 3: 514-522. 
2.12 Publication 
Plan 
Presentations at national scientific meetings: It is expected that approximately 2-4 
presentations at national meetings would be appropriate for a research study this size. 
Potential targeted scientific meetings for dissemination of results are the American 

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Association for Cancer Research, American Association for Cancer Education, 
American Society of Clinical Oncology, American Public Health Association’s annual 
meeting, Academy of Oncology Nurse & Patient Navigators annual conference, and 
Oncology Nursing Society’s annual congress. PIs and Co-investigators are members of 
these professional organizations and will be active participants in presentations at these 
scientific meetings. 
Dissemination with local oncology special interest groups: This research team is an 
active participant in local efforts that promote best practices for cancer patients 
throughout the cancer care continuum. As such, we will disseminate study results and 
share study protocols, assessment tools, and intervention components developed during 
the course of this study to advance the translational nature, from theoretical to clinical 
practice, of this study. Local groups include North Carolina Oncology Navigation 
Association (NCONA), Eastern North Carolina Cancer Support Community, and 
Eastern North Carolina Cancer Coalition. 
Dissemination via Vidant Health media outlets: In an effort to advance the 
translational implications of study results into practice, our dissemination strategy will 
include consistent communication with the cancer care practice community at Vidant 
Health. This includes Vidant Medical Center’s Cancer Committee, Vidant Medical 
Center’s Cancer Annual Report that is made publically available via Vidant Health’s 
website, and Vidant Health’s Navigation meetings. 
   
Dissemination via manuscripts: Translation of research findings into practice in the 
health promotion sciences is important and will be accomplished by publishing results 
in high impact peer-reviewed journals that target audiences addressing the science that 
underpins clinical practice and is concerned with improving health outcomes 
throughout the cancer care continuum. Additionally, manuscripts will specifically 
focus on intervention reach, adoption, implementation, and maintenance that have been 
identified as critical areas that need to be better understood in order to address the gap 
between research and practice. 
2.13 Curriculum 
Vitae 
 
The curriculum vitae’s for Dr. Richman and Dr. Torres appear in Appendix D. 
2.13 Protocol 
Submission for 
Investigator-
Initiated Studies  
U.S. protocols should be submitted by US investigators directly or through the Global Research Specialist 
at  www.merckiisp.com   
 
Non U.S. protocols should be submitted to the MSD office by the investigators.