A Pilot Feasibility Trial of a Tailored Intervention to Improve Adherence in Adolescents and Young Adults With Cancer
Phase: NA
Conditions: Cancer, Adherence, Medication
Sponsor: Children's Hospital Medical Center, Cincinnati

Cover Page 
 
Official Title of Study: A Pilot Feasibility Trial of a Tailored Intervention to Improve Adherence in Adolescents 
and Young Adults with Cancer 
 
NCT Number: NCT05706610 
 
Date of Document: January 18, 2023 
Note. The “Date” on the protocol document face page and in the footer of “December 2022” reflect the date 
this document was most recently updated. This document was approved by the IRB on January 18, 2023.  
 
 

 
 
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Version 2.0 (December 2022) 
 
 
 
Protocol Title:  
A tailored intervention to improve adherence in adolescents and young adults 
with cancer 
 
Protocol Number: 
 
2020-0904 
 
Version: 
 
 
2.0 
 
Date:  
 
 
December 2022 
 
Principal Investigator: 
Meghan E. McGrady, Ph.D. 
 
 
 
 
Division of Behavioral Medicine and Clinical Psychology 
 
 
 
 
Patient and Family Wellness Center 
Cancer and Blood Diseases Institute 
Cincinnati Children’s Hospital Medical Center 
Phone: 513.803.8044 
Email: Meghan.McGrady@cchmc.org  
 
Primary Site:  
 
Cincinnati Children’s Hospital Medical Center 
 
Collaborating Sites:  
Seattle Children’s Hospital  
 
 
 
 
St. Jude Children’s Hospital 
 
 
 
 
 
Funding: 
National Cancer Institute of the NIH - R21CA268945 
 
 
Revision History 
# 
Date 
Summary of Changes 
Consent 
Change? 
1 
December 
2022 
Updates to measures (resulted in updates to 
consent), study timeline, and patient-facing 
materials and clarifications to study procedures 
(i.e., risk protection procedures updated to be 
relevant to multi-site study) following the 
receipt of the award in December 2022.  
Yes 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
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Confidentiality Statement:   Information contained within this document is not to be disclosed in any way 
without prior permission of the Principal Investigator. 
Table of Contents 
1.0 
STUDY SUMMARY ....................................................................................................................................................... 4 
2.0 
OBJECTIVES ................................................................................................................................................................. 4 
3.0 
BACKGROUND AND SIGNIFICANCE ............................................................................................................................. 5 
4.0 
STUDY ENDPOINTS ...................................................................................................................................................... 7 
5.0 
STUDY INTERVENTION/INVESTIGATIONAL AGENT ..................................................................................................... 7 
6.0 
PROCEDURES INVOLVED ............................................................................................................................................. 9 
7.0 
DATA AND SPECIMEN BANKING ............................................................................................................................... 11 
8.0 
SHARING OF RESULTS WITH SUBJECTS ..................................................................................................................... 11 
9.0 
STUDY TIMELINE ....................................................................................................................................................... 11 
10.0 
INCLUSION AND EXCLUSION CRITERIA ..................................................................................................................... 12 
11.0 
VULNERABLE POPULATIONS ..................................................................................................................................... 12 
12.0 
LOCAL NUMBER OF SUBJECTS .................................................................................................................................. 13 
13.0 
RECRUITMENT METHODS ......................................................................................................................................... 13 
14.0 
WITHDRAWAL OF SUBJECTS ..................................................................................................................................... 14 
15.0 
RISKS TO SUBJECTS .................................................................................................................................................... 14 
16.0 
POTENTIAL BENEFIT TO SUBJECTS ............................................................................................................................ 15 
17.0 
DATA MANAGEMENT AND CONFIDENTIALITY .......................................................................................................... 15 
18.0 
PROVISIONS TO MONITOR THE DATA TO ENSURE THE SAFETY OF SUBJECTS ......................................................... 18 
19.0 
PROVISIONS TO PROTECT THE PRIVACY INTERESTS OF SUBJECTS ........................................................................... 19 
20.0 
COMPENSATION FOR RESEARCH-RELATED INJURY .................................................................................................. 19 
21.0 
ECONOMIC BURDEN TO SUBJECTS ........................................................................................................................... 19 
22.0 
CONSENT PROCESS ................................................................................................................................................... 19 
23.0 
PROCESS TO DOCUMENT CONSENT IN WRITING ..................................................................................................... 20 
24.0 
SETTING ..................................................................................................................................................................... 20 
25.0 
RESOURCES AVAILABLE ............................................................................................................................................. 20 
26.0 
MULTI-SITE RESEARCH .............................................................................................................................................. 21 
 
 
 

 
 
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1.0 
STUDY SUMMARY 
 
Study Title 
A tailored intervention to improve adherence in 
adolescents and young adults with cancer 
Study Design 
Randomized feasibility pilot trial 
Primary Objective 
To conduct a feasibility pilot RCT of a tailored 
adherence-promotion intervention as compared 
to uniform standard of care including 40 AYAs 
with cancer (n = 20 per arm). 
Secondary Objective(s) 
To explore group differences in improvements in 
electronically-monitored medication adherence to 
inform the next phases of intervention 
development and testing.   
Research Intervention(s)/ 
Investigational Agent(s)  
Tailored adherence-promotion intervention 
IND/IDE #  
Not Applicable 
Study Population 
Adolescents and Young Adults with Cancer 
Sample Size 
40 
Study Duration for individual 
participants 
Approximately 17 weeks 
Study Specific Abbreviations/ 
Definitions  
AYA (Adolescent and Young Adult) 
 
2.0 
OBJECTIVES 
 
The purpose of this study is to conduct a pilot feasibility trial of a tailored adherence-promotion intervention as 
compared to uniform standard of care. This goal will be achieved via the following aims: 
 
Aim 1: Conduct a feasibility pilot RCT of a tailored adherence-promotion intervention as compared to 
uniform standard of care including 40 AYAs with cancer (n = 20 per arm).   
Hypothesis 1a: The intervention will meet enrollment, retention, fidelity, and data completion feasibility criteria.  
Hypothesis 1b: AYAs will rate the intervention as easy to use and acceptable.  
 
Exploratory Aim 2: To explore group differences in improvements in electronically-monitored 
medication adherence to inform the next phases of intervention development and testing. 
 
 

 
 
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3.0 
BACKGROUND AND SIGNIFICANCE 
 
3.1 
Prior Experience and Gaps in Current Knowledge 
Clinical care and treatment advances in the last 40 years have increased survival rates by more than 30% for 
children under 15 with cancer.1 Progress for adolescents and young adults (AYAs) with the same diagnoses, 
however, has been far slower, and 5-year survival rates for 20 of the 34 most common AYA cancers have not 
improved since the 1990s.2 Even in diseases where survival rates have improved (e.g., acute lymphoblastic 
leukemia), AYAs demonstrate particularly poor outcomes and have mortality rates well above those of children 
< 15 years.3 As a result, cancer remains the leading cause of disease-related death among AYAs ages 15-24 
years in high income countries4 and accounts for 5% of the AYA lives lost in the United States each year.5 
 
A likely contributor to the poor outcomes faced by AYAs with cancer is non-adherence to the oral 
chemotherapy and/or prophylactic (e.g., antibiotic) medications included in cancer treatment protocols. For 
patients with leukemia prescribed oral chemotherapy, non-adherence, or medication-taking behavior that 
deviates from the prescribed treatment protocol,6 is associated with a 2.5x greater likelihood of relapse7 and a 
1.6x greater likelihood of death.8 In addition, AYAs with cancer who are non-adherent to antibiotics are 4.6x 
more likely to die9 than adherent AYAs. Our recent systematic review indicated that 21-60% of AYAs with 
cancer are non-adherent to protocol medications.10 This means that thousands of AYAs with cancer are 
currently at risk for devastating consequences which could be prevented.11 In response, professional 
organizations have endorsed adherence promotion as a standard of pediatric12 and AYA4,13 cancer care.  
 
The factors that may lead AYAs to miss medication doses and thus should 
be targeted in adherence-promotion efforts can be conceptualized as 
barriers to adherence. According to the Theoretical Domains Framework, 
barriers are driven by an individual’s capabilities, opportunities, and 
motivation.14,15 Capabilities, opportunities, and motivations change 
throughout the lifespan and when these domains change, so do our 
barriers. For example, neurodevelopmental changes beginning at age 15 
and stabilizing after age 24 coupled with the developmental transitions of 
this period (i.e., independent living) mean that AYAs ages 15-24 years 
display a distinct pattern of capabilities,16-18  opportunities,19 and 
motivation16,20,21 and as a result, different barriers to adherence than 
younger children22,23 or older adults.24 Because barriers change with age, 
improving adherence is likely to require a developmentally-specific 
approach. While the National Cancer Institute defines the AYA period as 
15-39 years,25 a more conservative definition of 15-24 years represents an 
ideal target population due to the similarities in barriers experienced by 
AYAs 15-24 years.24  
 
Data from 3 studies26 and 1 systematic review10 led by Dr. McGrady (PI), 
suggest that the capabilities, opportunities, and motivations of AYAs ages 
15-24 years with cancer result in 18 primary barriers (Fig 1). One of the 
challenges to improving adherence is that overcoming each of these 
barriers requires a distinct set of strategies, or behavior change techniques  
(BCTs).27,28,29 For example, improving adherence in an AYA who forgets 
her medication (barrier) may require prompts or cues (BCT).30 Alternatively, 
an AYA who feels his regimen gets in the way of other activities (barrier) 
may benefit from problem-solving (BCT).31 Guided by this theory, we propose that improving adherence 
requires that each AYA receives BCTs matched to their top barriers.  
 
A
D
H
E
R
E
N
C
E 
Barriers to Adherence 
Knowledge of how/when to take it 
Forget to take it 
Don’t realize when I run out 
Hard to time with meals 
Not home when doses due 
Don’t like taking in front of others 
Don’t like the taste 
Hard to swallow 
Don’t like the side effects 
Hard to get refills 
Can’t afford it 
Don’t get enough help 
Too many pills to take 
Tired of taking medication 
Don’t feel like taking it 
It’s inconvenient 
Gets in the way of activities 
Doesn’t matter if I take it 
Fig 1. Theoretical Model 
OPPORTUNITIES 
(Environment, Experience, 
Resources, & Support) 
MOTIVATION 
(Motivation & Health Beliefs) 
CAPABILITIES 
(Knowledge, Memory, & Skills) 

 
 
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Ensuring AYAs with cancer receive BCTs matched to their barriers is not as simple as creating another “one-
size-fits-all” intervention. This is because, in our preliminary studies, 81% of AYAs with cancer endorsed 
different barriers than any other AYA. The vast majority of AYAs, thus, likely need a unique set of BCTs to 
overcome their barriers and improve their adherence. Guided by these data and theory,14,28,31,32 we 
hypothesize that we can improve on the effects of interventions to date by testing a rigorous tailored 
adherence-promotion intervention in which each AYA receives BCTs matched to their top barriers. The 
scientific premise of this approach is supported by an RCT of an adherence-promotion intervention with 4,078 
adults with diabetes, hyperlipidemia, and hypertension. Adults who received BCTs tailored to their top barriers 
exhibited greater improvements in adherence than adults in the control group.33 Post-hoc analyses of data 
from the mobile app trial suggest this approach also holds promise for AYA oncology as the 3 of 23 AYAs 
whose adherence did improve were more likely than their peers to endorse forgetting as a barrier.24 The AYAs 
who improved, thus, happened to receive BCTs (reminders & tracking) targeting their specific barrier. 
 
3.2 
Preliminary Data Informing the Proposed Study Design 
With support of her NCI K07, Dr. McGrady is conducting a longitudinal observational study to identify 
predictors of medication adherence among AYAs (15-24 years) with cancer. Defining adherence as ≥ 95% of 
prescribed doses taken, the threshold associated with a lower risk of relapse in acute lymphoblastic leukemia,7 
our preliminary data indicate that 71% of AYAs are non-adherent per electronic monitoring data. This rate of 
non-adherence may be due to barriers faced by AYAs. At baseline, 90% of AYAs reported ≥ 1 barrier and a 
greater number of barriers was associated with lower electronically monitored (r = -.49, p = .01) and self-
reported (r = -.41, p = .01) adherence. These data suggest that targeting barriers has the potential to improve 
adherence. Doing so, however, is complicated by the individual variability inherent in barriers. Of the 54 AYAs 
reporting barriers, only 10 reported the same barriers. The other 81% reported a different set of barriers than 
any of their peers. In addition, only 26% endorsed forgetting and/or lack of knowledge, the barriers targeted by 
previous interventions.24,34,35 Because most AYAs have unique barriers, it is not surprising that “one-size-fits-
all” interventions targeting barriers endorsed by only some AYAs demonstrate limited efficacy.24,34,35 Instead, 
our data suggest that delivering BCTs tailored to an AYA’s top barriers may improve adherence. 
 
Additionally, with support of her NCI K07, Dr. McGrady conducted qualitative interviews with 15 AYAs with 
cancer to understand their intervention preferences. AYAs were enthusiastic about a tailored intervention, with 
one noting “there are just so many different reasons that somebody might not be receiving their medication.” 
AYAs, even those living with their parents, reported taking primary responsibility for adherence and wanted a 
say in if/how their parents or other support person were involved in the intervention. To align with these 
preferences, the intervention is patient-focused (versus family-based) and AYAs will be invited to engage a 
parent or other support person to implement BCTs as appropriate (e.g., asking fiancé to remind them to 
implement the BCT “prompts/cues”). We also matched the tailored adherence-promotion intervention with AYA 
preferences for “convenient” “every other week” sessions over “a few months” by designing an 8 week 
intervention that includes 4 bi-weekly videoconferencing sessions, with 4 text check-ins occurring on 
alternating weeks. 
 
3.3 
Scientific and Clinical Significance of the Proposed Study 
If feasible and efficacious, this intervention has the potential to transform AYA oncology clinical care across the 
country. Creating an intervention with standardized modules and a standardized tailoring algorithm means that 
hospitals could adapt the delivery to fit their institutional resources without compromising “active” components. 
For example, Hospital A may decide that psychologists are best-suited to deliver all modules of BCTs while 
Hospital B may have psychologists deliver modules of BCTs for some barriers but engage their social work 
team to deliver modules of BCTs for others (e.g., cost). The flexibility inherent in this design can facilitate 
implementation without negatively impacting rigor and allows for adaption to other AYA populations.36 
 
 

 
 
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4.0 
STUDY ENDPOINTS 
 
4.1 
Primary and Secondary Study Endpoints 
Hypothesis 1A: The primary endpoint for this study is the enrollment rate. Secondary outcomes for 
Hypothesis 1A include retention rate, assessment completion, and intervention fidelity as detailed in Table 1.  
 
Table 1. Hypothesis 1A Measures 
Domain 
Measure 
Outcome 
Criteria 
Feasibility 
(Hyp 1a) 
Enrollment Rate  
Percentage of eligible approached AYAs who enroll 
≥ 70% 
Retention Rate 
Percentage of AYAs completing all study procedures 
≥ 80%36 
Assessment Completion  Percentage of AYAs with complete data  
≥ 80%36 
Intervention Fidelity: 
Contact37 
Percentage of AYAs who received 4 intervention sessions (planned number 
of sessions) 
≥ 80%38 
Intervention Fidelity: 
Length37 
Percentage of AYAs whose average session length was between 30 and 45 
minutes (planned session duration) 
≥ 80%38 
Intervention Fidelity: 
Duration37 
Percentage of AYAs who completed the intervention sessions within an 8-10 
week timeframe (8 weeks = planned duration; 10 weeks = upper limit set to 
include a 2 week buffer to provide flexibility for patients who may be 
hospitalized and/or experience major complications during the intervention 
period) 
≥ 80%38 
Intervention Fidelity: 
Content37 
Percentage of AYAs receiving the BCTs matched to their barriers per protocol 
(assessed via listening to audio recordings of sessions and coding delivered 
BCTs using a fidelity rating checklist) 
≥ 80%38 
 
Hypothesis 1B: Outcomes for Hypothesis 1B include usability and acceptability as detailed in Table 2. Open-
ended questions regarding usability and acceptability will also be asked to inform potential refinements. 
 
Table 2. Hypothesis 1B Measures 
Domain 
Measure 
Outcome 
Criteria 
Usability 
(Hyp 1b) 
System Usability Scale (SUS)39  
Mean score of AYAs randomized to treatment group 
M ≥ 6839 
System Usability Scale Adjective Rating40  Mean score of AYAs randomized to treatment group 
M ≥ 440 
Acceptability 
(Hyp 1b) 
Acceptability &Adherence Scale41  
Mean score of AYAs randomized to treatment group 
M ≥ 2842 
Refinements 
3 Open-Ended Questions (1. What did you like best about the program?; 2. What could we change to 
make the program better?; 3. Anything else we should think about as we work to make this program 
better?) 
N/A 
 
Exploratory Aim 2: The outcome for Exploratory Aim 2 is electronically-monitored medication adherence. 
 
4.2 
Primary and Secondary Safety Endpoints 
No safety endpoints are included.    
 
5.0 
STUDY INTERVENTION/INVESTIGATIONAL AGENT 
 
5.1 
Description 
The intervention being tested is a tailored adherence-promotion intervention.  
 
Intervention Dose and Duration: AYAs in the intervention group will participate in 4 bi-weekly intervention 
sessions (1 every other week over 8 weeks). These sessions are estimated to last 30-45 minutes each. On 
alternating weeks, AYAs will receive a text message check-in from the interventionist. An 8 week duration was 
selected to mirror the amount of time over which adherence naturally declines, is short enough to be 
completed during the prescribed oral medication regimen of most AYAs with cancer, and is consistent with the 
“couple of months” duration preferred by AYAs in our preliminary studies. 
 

 
 
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Intervention Session Content: During the intervention sessions, each AYA will receive modules of behavior 
change techniques (BCTs) tailored to their individual barriers. Intervention content (BCTs) will be tailored to 
each AYA’s barriers via a 4-step tailoring process. First, AYAs randomized to the intervention condition will 
complete a barriers tool. Second, the barriers tool will generate a list of the AYA’s top 3 barriers, which will be 
sent to the interventionist. Third, in the first session, the interventionist will review the list and engage in shared 
decision-making with the AYA to determine which of the 3 barriers the AYA would like to target. Fourth, 
following a standardized tailoring algorithm (see Fig 2), the interventionist will select and deliver the module of 
BCTs matched to this barrier during Sessions 1 and 2. As barriers are likely to change over time, the AYA will 
complete the barriers tool a second time prior to Session 3 and the AYA and interventionist will again engage 
in shared decision-making to choose the barrier to be targeted in Sessions 3 and 4.  
Figure 2 summarizes the tailoring algorithm and content. When the barrier in column 1 is selected as the 
intervention target, the interventionist will deliver the BCT(s) in column 2. Each BCT represents a component of 
a health behavior change intervention that has been standardized via expert consensus and over 10 years of 
empirical research as published in the Theory and Techniques Tool 
(https://theoryandtechniquetool.humanbehaviourchange.org/tool). The study protocol will include the full 
definition of each BCT per the Theory and Techniques Tool and include examples relevant to AYA cancer to 
help guide the interventionist (e.g., “Prompts/cues” = “Introduce or define environmental or social stimulus with 
the purpose of prompting or cueing behavior. The prompt or cue would normally occur at the time or place of 
performance. Examples: Help the AYA to set an alarm for when their doses are due”).  
 
Text Check-Ins: On alternating weeks, the interventionist will check-in with the AYA via a text message 
including the AYA’s target barrier, BCTs, and adherence calendar. The AYA may respond to obtain additional 
support on how to implement the BCTs if desired.  
 
 
 
Instruction on how to perform behavior 
Knowledge of how/when to take it 
Prompts/cues; Problem-solving; Associative learning (e.g., pairing w activity) 
Forget to take it 
Problem-solving; Prompts/cues; Conserving mental resources (e.g. auto refills) 
Don’t realize when I run out 
Instruction on how to perform behavior; Problem-solving 
Hard to time with meals 
Problem-solving; Restructure environment; Prompts/cues 
Not home when doses due 
Restructure social environment; Info about others’ approval 
Don’t like taking in front of others 
Adding objects to environment (e.g., gel capsule, food to mask taste) 
Don’t like the taste 
Graded tasks; Behavioral practice/rehearsal; Verbal persuasion 
Hard to swallow 
Instruction on how to perform behavior (discuss with team) 
Don’t like the side effects 
Prompts/cues; Practical social support; Restructure environment 
Hard to get refills 
Practical social support (e.g., consult with social worker) 
Can’t afford it 
Practical social support; Social reward 
Don’t get enough help 
Problem-solving 
Too many pills to take 
Pros and cons; Goal setting; Incentives/rewards 
Tired of taking medication 
Pros and cons; Goal setting; Incentives/rewards 
Don’t feel like taking it 
Focus on past successes; Problem-solving 
It’s inconvenient 
Focus on past successes; Problem-solving 
Gets in the way of activities 
Information about consequences; Pros and cons; Incentives/rewards 
Doesn’t matter if I take it 
Fig 2. Barriers and Behavior Change Techniques (BCTs)  
Capabilities 
Opportunities 
Motivation 
Barriers 
BCTs 

 
 
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6.0 
PROCEDURES INVOLVED 
6.1 
Study Design 
This is a multisite feasibility pilot RCT that includes 4 sets of study procedures: 
1) electronic monitoring of medication adherence; 2) intervention or control 
group participation; 3) self-report measure completion; and 4) an electronic 
medical record review (Fig. 3). Reminders (and thank you messages) for 
completing study procedures may be provided via text, email, and/or phone as 
preferred by the AYA.  
 
6.2 
Study Procedures 
6.2.a. Electronic Monitoring of Medication Adherence. In this study, 
medication adherence will be monitored using an electronic pill bottle. The 
electronic pill bottle includes a computer chip in the cap that records a date- 
and time-stamp of each time the bottle is opened, our proxy for medication-
taking behavior.  
 
To be eligible for the study, AYAs must demonstrate < 95% adherence and use 
the electronic monitor without difficulty. A 4-week run-in period is included to assess these eligibility criteria. 
After an AYA is enrolled, they will receive an electronic monitoring device and be asked to store their eligible 
oral medication in this device for the duration of their participation in the study. AYAs who demonstrate ≥ 95% 
adherence during the 4-week run-in period and/or who have difficulty using the electronic monitoring device will 
be informed that they do not meet the eligibility criteria and their study participation will be ended at that point. 
AYAs with < 95% run-in adherence will continue with study procedures per Fig. 3 and be asked to continue to 
use the electronic adherence monitoring device until the end of the 4-week post-intervention period (for 17 total 
weeks).  
 
Electronic Monitoring Device Distribution: AYAs will either be provided an electronic monitoring device at 
their recruitment visit or mailed an electronic monitoring device and provided instructions by a member of the 
CCHMC research team.  
 
For participants currently enrolled in an ongoing clinical initiative including electronic adherence monitoring, 
adherence data will be downloaded from the clinic-provided device. Doing so will ensure that participants are 
only provided with one electronic monitor.  
 
Electronic Monitoring Device Return: Participants will be asked to return their adherence electronic 
monitoring device at the conclusion of their participation in the study. In instances where participants are 
unable to bring their adherence electronic monitoring device to a study visit, a pre-paid addressed envelope 
will be provided so participants can mail their devices to the study team.  
 
Cellular Phones: AYAs will be asked to download a mobile application to their personal cellular phone that 
they will use to upload data from their electronic monitoring device to a secure Cloud-based application 
(CertiScan® Cloud). If AYAs would not be able to participate in the study because they do not have access to 
an appropriate mobile phone (phone with NFC capabilities) and/or a data package, they will be given a 
CCHMC-provided cellular phone to use for the duration of the study.  
 
6.2.b. Intervention or Control Group Participation. AYAs randomized to the intervention group (tailored 
adherence-promotion intervention, termed “Tailored Program”) will participate in 4 bi-weekly sessions with an 
interventionist and receive text check-ins on alternating weeks (see Section 5). AYAs randomized to the control 
group (uniform standard of care condition, termed “Feedback Program”) will receive a weekly text message 
Feedback
Tailored 
Cal + Con 
Session 1 
1
    4-Week Post-Intervention  
  Post-Treatment Assessment 
Fig 3. RCT Procedures 
Cal + Con = Adherence calendar + 
contact information for medical team 
4-Week Run-In 
  Pre-Treatment Assessment 
Randomization 
Cal + Con 
Check-In 
2
Cal + Con 
Session 2 
3
Cal + Con 
Check-In 
4
Cal + Con 
Session 3 
5
Cal + Con 
Check-In 
6
Cal + Con 
Session 4 
7
Cal + Con 
Check-In 
8
         Electronic Adherence Monitoring 

 
 
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from the interventionist including a calendar depicting their adherence and a medical team contact should they 
desire support (Fig 3).  
 
Intervention sessions will be delivered via a HIPAA-compliant videoconferencing system (Zoom for Healthcare) 
or phone should technical difficulties arise with Zoom. All intervention sessions will be recorded. 
 
6.2.c. Self-Report 
Measure Completion. 
AYAs will complete pre- 
and post-treatment 
assessments remotely via 
REDCap, a secure, HIPAA-
compliant web-based 
platform. Prior to use, the 
PI will test the online 
measures. The consent 
forms signed by all 
participants will detail the 
use of online measures. 
The self-report measures 
are summarized in Table 3. 
Published and validated 
versions of all measures 
will be used unless noted in 
Table 3. 
 
6.2.d. Chart Review. Medical diagnoses, date of cancer diagnosis, current medical regimen, cancer status 
(e.g., relapse), cancer-related complications, and health care utilization will be obtained via medical chart 
review. Trained study staff will conduct chart reviews. 
 
6.3 
Blinding. Participants will be blinded to the study hypotheses in that they will not be told that we expect 
the “Tailored Program” (intervention condition) to result in greater improvements in adherence (Exploratory Aim 
2) than the “Feedback Program” (control condition). Dr. McGrady (PI) will not be blinded as she will be 
providing clinical supervision to the study interventionist.  
 
6.4 
Procedures Conducted by Collaborating Site Staff. Study staff at collaborating sites will have 3 
main responsibilities: 1) recruiting patients per the procedures described in Section 13; 2) conducting weekly 
medical record reviews to provide updates to the patient’s medical regimen (to allow for adherence data to be 
adjusted according to medication holds, etc.); and 3) assisting with a medical record review at the end of the 
study to obtain the information detailed in 6.2.d. Once a participant is recruited, their information will be 
securely transferred to CCHMC (as per 13.1) and CCHMC staff will oversee all other procedures as detailed in 
6.5.  
 
6.5 
Procedures Conducted by CCHMC Staff. CCHMC staff will be responsible for enrolling CCHMC 
patients. CCHMC staff will also be responsible for: 1) assigning participants to the intervention or control 
condition; 2) delivering the intervention or control condition (i.e., distributing electronic adherence monitoring 
devices and cellular phones as necessary); 3) providing supervision to the coach delivering the intervention or 
control condition; 4) tracking participants’ progress; 5) overseeing adherence data collection and synthesis with 
data from weekly electronic medical record reviews; 6) administering and overseeing pre- and post-treatment 
Table 3. Self-Report Measures 
Domain 
Measures Completed by AYAs, Psychometrics 
 
Pre- Post- 
Usability 
System Usability Scale (SUS)39  
10-item rating of usability, α=.9139  
 
 
X 
System Usability Scale Adjective Rating40 
1-item rating of user-friendliness, r=.82 w SUS40 
 
X 
Acceptability 
Acceptability &Adherence Scale41 
7-item rating of psychological treatment acceptability (adapted 
from the Treatment Acceptability & Adherence Scale,α=.8841,42) 
 
X 
Refinements 
3 Open-Ended Questions regarding potential refinements 
(see Table 2) 
 
X 
Consultation and Relational Empathy (CARE) Measure 
10-item rating of rapport and empathy, α=.9350 
 
X 
Preliminary 
Efficacy 
Barriers Measure 
18-item measure of barriers to adherence  
 
X 
X 
Medical Adherence Measure43 
2-item report of N missed and late doses, r=.4 with monitor44 
 
X 
X 
Control 
Covariates 
Demographics – Self-reported Demographics  
X 
 
Parental Involvement – Allocation of Treatment Responsibility, α=.8545 
X 
 
Emotional Distress – Pediatric (ages 15-17) or Adult (ages 18-24) 
PROMIS Depression and PROMIS Anxiety Short Forms, α=.84-86.46,47  
X 
 

 
 
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assessment visits; 7) managing all study data; 8) managing participant compensation; and 9) conducting data 
analyses. Each of these tasks will be detailed in our Standard Operating Procedures. 
 
7.0 
DATA AND SPECIMEN BANKING 
 
7.1 
Location of Data Storage. Data will be retained from this pilot feasibility study to inform the 
development and refinement of future versions of the adherence intervention. The Excel database containing 
identifiable information, connecting participants to their study ID number (see Section 17.3), will be deleted at 
the closure of the study. Databases including de-identified adherence (from CertiScan® cloud) and 
questionnaire (from REDCap) data will be stored in a password-protected electronic file on the CCHMC hard 
drive for 10 years after the study has been closed. Data from this study will be used to inform an R01 or U-
series multi-site trial of an adherence promotion intervention. A 10 year period was selected to ensure that data 
informing the larger study (data from this study) are available to inform modifications throughout the potential 
R01 or U-award period. After the study has been closed, only the PI will have access to the data.  
 
7.2 
Procedures to Release Data. 
De-identified data may be shared with other individuals according to procedures outlined in the Data Sharing 
Agreement linked to this protocol.  
8.0 
SHARING OF RESULTS WITH SUBJECTS 
AYAs will receive feedback on their adherence as part of this study. If a provider suspects non-adherence and 
believes that reviewing adherence data in our study could help to inform their clinical care, we will share the 
relevant data with the participant’s provider. Participants will consent to this data sharing during the consent 
process. The AYA may also share these data with their care providers if they choose. No other individual 
subject results will be shared with participants or others not involved in the conduct of this study.  
 
A summary of study results will be provided to study participants via a newsletter.  
 
9.0 
STUDY TIMELINE  
 
9.1 
Subject Participation Duration 
Adolescents and young adults enrolled in this study will participate in a 4-week run-in period, 1 week pre-
treatment assessment, 8-week intervention or control group, and 4 week post-treatment period. In all, the 
estimated duration of subject participation is 17 weeks.  
 
Given the demanding nature of cancer treatment, all study procedures can be completed +/- 2 weeks of the 
planned completion date and still be considered completed “on time.” 
 
9.2 
Enrollment Duration 
Based on the number of eligible AYAs receiving care at the 3 participating institutions, it is estimated that 
participant enrollment will be completed in 12 months.  
 
9.3 
Study Timeline  
 The Notice of Award was issued on December 12, 2022. The proposed study timeline is detailed in Table 4.  
 
Table 4. Study Timeline 
Dates 
Tasks 
December 2022 to February 2023 
Prepare study materials and train study staff 
February 2023 to November 2024 
Participant enrollment 
January 2023 to March 2025 
Data collection  
July 2023 to December 2026 
Data analysis, cleaning, and publication 

 
 
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10.0 INCLUSION AND EXCLUSION CRITERIA 
 
10.1 
Eligibility Screening and Criteria 
This study includes a 4 week run-in period during which eligibility will be determined. First, AYAs deemed 
eligible per inclusion and exclusion criteria 1-7 (Table 5) will be identified by a member of the study team via 
electronic medical record review. A waiver of HIPAA authorization is requested for preparatory research to 
identify potential participants based on inclusion/exclusion criteria. AYAs deemed eligible per criteria 1-7 and 
interested in participating will then complete the consent process as per Sections 13 and 22.    
 
Prescribed Oral Medication Regimen Eligibility Criteria: An AYA’s oral medication regimen can be modified 
based on their treatment response and thus it is possible that some enrolled AYAs will discontinue their 
medication prior to the end of the 17 week study. To minimize the likelihood of enrolling these patients, we will 
consult with an oncologist prior to enrolling each patient and only enroll patients who the medical team believes 
(at the time of enrollment) will be prescribed an oral prophylactic or chemotherapy medication for the 17 week 
study duration. 
 
Run-In Period to Confirm Eligibility: After an AYA is enrolled, they will receive an electronic monitoring 
device and be asked to store their eligible oral medication in this device for the duration of their participation in 
the study. These criteria will be confirmed during the 4-week run-in period as detailed in Section 6.2.a. 
 
10.2 
Inclusion of Vulnerable Populations 
Teenagers ages 15-17 years of age are eligible to participate in this study.   
 
As our population includes women of child-bearing age, pregnant women may be eligible to participate.  
 
Adults unable to consent and prisoners are not eligible to participate.   
 
11.0 VULNERABLE POPULATIONS 
The cohort will consist of patients between the ages of 15 and 24 years at baseline. This is a minimal risk 
study, including risks no greater than those encountered in routine behavioral assessment and clinical care. 
The steps taken to minimize coercion or undue influence during the process of obtaining informed consent will 
be followed in accordance with all applicable regulatory requirements. A patient and their family will not be 
approached if they 1) do not meet the proposed study criteria; and/or 2) are under distress. Additional 
procedures for obtaining consent are listed below.  
 
This is a minimal risk study with no risk to the fetus.  
Table 5. Inclusion and Exclusion Criteria and Rationale  
Inclusion Criteria (Rationale) 
1. Patient between 15 and 24 years of age at consent visit (unique biological characteristics and behavioral transitions)  
2. Patient diagnosis of cancer (intervention designed to address medical components of oncology treatment) 
3. Patient prescribed oral prophylaxis or chemotherapy (non-adherence to these medications is linked to relapse & death) 
Exclusion Criteria (Rationale) 
4. Patient is not fluent in English (piloting an intervention to be delivered in multiple languages is beyond the scope of this study) 
5. Patient evidences significant cognitive deficits per medical team (may interfere with intervention comprehension and/or participation) 
6. Patient’s medical status/condition precludes participation per medical team, patient, or caregiver (ensuring ethical recruitment) 
7. Patient enrolled on a medical trial requiring medication storage in a trial-provided container (adherence measured via electronic 
monitor) 
8. Patient demonstrates ≥ 95% adherence9 during run-in (maximize accuracy of evaluation of preliminary efficacy)*  
9. Patient declines to use or has difficulty using the electronic monitoring device (minimize missing data)* 
*determined during run-in period  

 
 
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12.0 LOCAL NUMBER OF SUBJECTS 
 
12.1 
Total Number of Subjects to be Accrued Locally 
Recruitment will be ended when 40 AYAs are randomized. It is estimated that approximately 15 AYAs will be 
recruited locally with the remainder recruited at collaborating sites.  
12.2 
Total Numbers Completing Each Phase of Study 
There are likely to be AYAs who are deemed eligible per inclusion and exclusion criteria 1-7 but are deemed 
ineligible due to criteria 8-9 following the 4 week run-in period. It is also possible that some participants will not 
complete initial study procedures (i.e., no-show for pre-treatment assessment visit). As a result, additional 
AYAs (estimated n = 10-20 AYAs) will be enrolled until a total of 40 AYAs are randomized.  
 
13.0 RECRUITMENT METHODS 
Participants will be recruited from the Cancer and Blood Diseases Institute (CBDI) at CCHMC and 
collaborating sites (see title page). Participants deemed eligible per inclusion and exclusion criteria 1-7 will be 
identified via electronic medical record review. A member of the study team will review the electronic medical 
records of these patients and to determine AYA eligibility. 
 
Eligible participants can be recruited either in-person or remotely.  
 
13.1 
In-Person Recruitment Procedures  
Eligible participants may be approached by study personnel during a clinic appointment or inpatient admission 
to extend an invitation to participate in the study and verify inclusion/exclusion criteria. A recruitment script will 
be followed. A study flyer may be provided to interested participants.  
 
Primary Site (CCHMC) Procedures. If the AYA is willing to participate, the study staff will obtain appropriate 
informed consent/assent and a signed HIPAA authorization form. No further attempts will be made to contact 
disinterested AYAs. This recruitment strategy has been successful for the PI’s previous studies (79-94% 
enrollment).  
 
Collaborating Site Procedures. For AYAs receiving care at collaborating sites, study staff at the collaborating 
site will be responsible for screening and approaching eligible patients. If the patient is interested in 
participating in the study, study staff at that site will obtain informed consent/assent, signed HIPAA 
authorization form, and contact information. This information will be securely emailed to CCHMC via a 
password-protected Excel sheet. The password-protected Excel sheet will be saved on a secure drive on 
CCHMC’s network. Only study staff will have access to the Excel sheet. Of note, all staff at these sites will be 
trained in informed consent procedures by CCHMC study staff. No further attempts will be made to contact 
disinterested AYAs. This recruitment strategy has been successful for the PI’s previous multi-site studies (91-
95% enrollment). 
 
13.2 
Remote Recruitment Procedures 
Patients may also be recruited remotely. Specifically, eligible participants may be mailed a letter and flyer 
describing the study procedures. The letter will include instructions regarding opt-out procedures (participants 
call or email a designated phone number/email address). Eligible participants who do not opt-out will be 
contacted by a member of the study team within approximately two weeks and consent procedures will be 
completed. This recruitment strategy has been previously used by the PI on multi-site studies of young adult 
cancer survivors (IRB # 2018-1885) and AYAs with cancer (IRB # 2019-0623).  
 

 
 
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13.3 
Participant Payment 
Participants will be compensated for the time 
required for assessment completion. 
Compensation for survey completion (est. 
completion time: 30-45 minutes) was set at $20. 
Participants will be compensated an additional 
$5 weekly, for 17 weeks, for using and 
downloading data from their electronic 
adherence monitoring device. If a participant 
completes all Feedback Group or Tailored Group procedures, they will be compensated a $15 bonus. 
Participants will also be compensated an additional $10 upon return of the study-provided electronic 
adherence monitoring device at the conclusion of the study (either at study completion or at drop-out – 
whenever the electronic monitoring device is returned).  
 
In the event that a study phone is not returned, we will attempt to reach the family via phone and email and set 
up a way to retrieve the phone. Given the high costs of the phones, if, after several months it is still not 
returned, we will offer an incentive of $50 for the safe return of the working mobile device, no questions asked. 
Other BMCP faculty have had success in using this procedure to increase mobile device return rates.  
 
All compensation will be managed by the study team at CCHMC and provided via ClinCards. 
 
14.0 WITHDRAWAL OF SUBJECTS 
There are no anticipated circumstances under which subjects will be withdrawn from the research without their 
consent. 
 
If participants wish to withdraw from the study, they are asked to contact the study team in writing. Following 
withdrawal, no additional attempts will be made to contact participants and no new data will be collected. Data 
collected prior to withdrawal, however, will still be analyzed. These procedures are detailed in the consent 
document.  
 
15.0 RISKS TO SUBJECTS 
This is a minimal risk study, including risks no greater than those encountered in routine behavioral 
assessment and clinical care. There are no medical risks. Participation in all study procedures is voluntary and 
participants can withdraw at any time. 
 
Risk of Discomfort: Prior to study participation, AYAs will be reminded that they may decline to answer any 
question that makes them feel uncomfortable. In the unlikely event that the content of a study visit or 
intervention session causes emotional or psychological distress, the Principal Investigator, Meghan E. 
McGrady, PhD, a licensed clinical psychologist at CCHMC (or the licensed clinical psychologist providing back-
up coverage) will be contacted immediately to assess the situation. The licensed clinical psychologist will 
follow-up with patient’s medical team as necessary. These procedures will also be followed should concerns 
regarding abuse, self-harm, homicidal/suicidal thoughts or behaviors arise. Patients and caregivers will be 
made aware that any information obtained during their participation that suggests the potential for harm to self 
or others will be disclosed to their medical team in order to protect the patient. As study procedures are 
conducted virtually, patients and families will be instructed to go to the local ED or call 911 if there is an 
immediate safety concern.  
 
Risk of Loss of Privacy of Data: There is also the risk of possible loss of privacy of data or loss of 
confidentiality. These risks are inherent in all research studies. While HIPAA-compliant health technology 
services will be used to remotely access medication adherence data (CertiScan® cloud) and deliver 
Table 6. Incentive Schedule 
Task 
Amount 
Pre-Treatment Assessment 
$20 
Weekly eCAP downloads (4 week run-in + 1 week for 
pre-treatment assessment + 8 weeks of intervention 
+ 4 weeks post-intervention = 17 weeks) 
$5/week (total 
up to $85) 
Group completion bonus 
$15 
Post-Treatment Assessment 
$20 
eCAP return 
$10 
Max Total = $150 

 
 
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assessments and intervention sessions (Zoom for Healthcare), there is a risk of loss of privacy of data and a 
risk of loss of confidentiality associated with health technology use. A statement to this effect will be included in 
the consent documents. Every effort will be made to ensure that all participant information will be kept 
confidential and secure (as detailed in Section 17). 
 
Unanticipated problems related to the research will be reported to the IRB within 24 hours of Dr. McGrady (PI) 
becoming aware of the problem. Unanticipated problems will also be regularly reported to Dr. Sarah Beal, the 
Independent Data Safety Monitor for this study. 
 
16.0 POTENTIAL BENEFIT TO SUBJECTS 
AYAs randomized to either the treatment (Tailored Program) or control (Feedback Program) arm may benefit 
from improved medication adherence, which has the potential to improve health outcomes. The information 
gained will improve our understanding of how best to help AYAs with cancer adhere to their medication 
regimens. The minimal risks associated with study participation are deemed reasonable in relation to the 
aforementioned anticipated benefits to participants and others. 
 
17.0 DATA MANAGEMENT AND CONFIDENTIALITY 
 
17.1 
Sample Size Justification 
A medical record review was conducted to determine the number of eligible AYAs across each site. In 2019, 
an estimated 97 AYAs ages 15-24 years of age with a diagnosis of cancer prescribed an oral prophylactic or 
chemotherapy medication (anticipated duration > 17 weeks) received care at one of the three participating 
sites: Cincinnati Children’s Hospital Medical Center (CCHMC), Seattle Children’s Hospital, and St. Jude 
Children’s Research Hospital. Of these 97 AYAs, based on enrollment data from our preliminary studies, it is 
estimated that 5% (n = 5) will be excluded due to lack of English fluency, presence of significant cognitive 
deficits, poor medical status, and/or participation in a medical clinical trial. In our preliminary studies, 29% of 
AYAs took ≥ 95% of doses and 3% declined to use an electronic monitoring device (total = 32%). Based on 
these data, we conservatively estimate that an additional 35% will not meet the adherence-related criteria (< 
95% adherence during run-in; AYA uses electronic monitoring device without difficulty) and be excluded. Thus, 
in all, we estimate that 39 of the 97 AYAs will not meet inclusion criteria (97*[.05+.35] = 39), resulting in an 
estimated eligible sample of 58 AYAs (97 - 39 = 58).  
 
We have set our recruitment rate goal of 70%, well below our previous enrollment rates of 79-92% into multi-
site observational psychosocial studies including AYAs with cancer. Based on an enrollment rate of 70%, it is 
estimated that we will enroll 3-4 AYAs per month and meet our recruitment goal of N = 40 (58*.70 = 40) in 12 
months. 
 
As it is estimated that approximately 58 AYAs with cancer meeting the inclusion criteria will receive care at one 
of the 3 participating sites during the 12 month recruitment period, a target N of 40 (randomized) was set to 
test our ability to achieve a 70% recruitment rate (58*.70 = 40). Assuming 20% attrition, our estimated final N 
will be 32, a number that exceeds the recommended sample size (n = 20) for a pilot 2-arm RCT with the goal 
of informing an efficacy trial with 80% power to detect a medium effect.36  
 
17.2 
Data Analysis Plan  
 
Hypothesis 1a: The intervention will meet enrollment, retention, fidelity, and data completion feasibility 
criteria.  
Hypothesis 1a will be supported if descriptive statistics indicate the feasibility criteria in Table 7 are met. The 
percent of eligible approached AYAs who enroll will be calculated to explore the hypothesis that the 
intervention will meet the enrollment rate goal of 70%. The percentage of AYAs completing all study 
procedures and with complete data will be calculated to evaluate the hypothesis that the retention and 

 
 
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assessment completion rates will be “acceptable”37 as defined as 80% or higher. In addition, the percentage of 
AYAs who received the intervention length, contact, content, and duration as specified in the treatment 
protocol will be calculated to evaluate the hypothesis that intervention fidelity will be “high”39 as defined as 80% 
or higher. 
 
Hypothesis 1b: AYAs will rate the intervention as easy to use and acceptable.  
Participants in both the treatment and control arms will complete usability and acceptability measures (see 
Table 8) in an effort to promote blinding. Data from the treatment group will be analyzed separately to explore 
Hypothesis 1b. Mean System Usability Scale, System Usability Scale Adjective Rating, and Acceptability 
&Adherence Scale scores will be calculated for AYAs randomized to the treatment group. It is hypothesized 
that AYAs participating in the treatment group will rate the intervention as easy to use as defined by a mean 
System Usability Scale score of 68 or greater39 and a mean System Usability Scale Adjective Rating of 4 or 
higher.41 It is also hypothesized that AYAs participating in the treatment group will rate the intervention as 
acceptable as defined by a mean Acceptability &Adherence Scale score of 28 or higher.42  
 
Data from the open-ended refinement questions (see Table 2) will be coded in NVivo by two independent 
raters using theoretical thematic analysis, a method selected as it codes for themes related to specific research 
questions such as those posed in this grant (i.e., “What could we change about the intervention to make it 
more acceptable to AYAs?”).  
 
Exploratory Aim 2: To explore group differences in improvements in electronically-monitored 
medication adherence to inform the next phases of intervention development and testing.   
To explore group differences in improvements in electronically-monitored medication adherence to inform the 
next phases of intervention development and testing (Exploratory Aim 2), we will conduct longitudinal mixed 
effects models using Stata version 16.49 Longitudinal trajectories of adherence will be estimated and tested for 
treatment group differences.  
 
While this study is not designed to test for treatment-related differences in adherence by demographic or 
clinical variables, demographic (age, sex, race), clinical (side effects, diagnosis, additional adherence 
interventions), and psychosocial variables (parental involvement, emotional distress) previously associated 
with adherence10 (see Table 3) will be explored as potential covariates. Exploring the role of these variables as 
covariates will enhance the precision of our efficacy estimate. Data will also be disaggregated by sex in all 
publications to facilitate efforts to consider sex in the interpretation and generalization of findings.  
 
17.3 
Data Security and Storage  
All data will be de-identified with the use of unique assigned study identifier codes. Study identifier codes will 
be used on study measures for data entry and analysis. No other identifying data such as date of birth, 
address, phone numbers, social security number, or zip code will be entered on measures. A password-
Table 7. Hypothesis 1A Measures 
Domain 
Measure 
Outcome 
Criteria 
Feasibility 
(Hyp 1a) 
Enrollment Rate  
Percentage of eligible approached AYAs who enroll 
≥ 70% 
Retention Rate 
Percentage of AYAs completing all study procedures 
≥ 80%37 
Assessment Completion  
Percentage of AYAs with complete data  
≥ 80%37 
Intervention Fidelity38 
Percentage of AYAs receiving the intervention length, contact, 
content, and duration as specified in the protocol 
≥ 80%39 
Table 8. Hypothesis 1B Measures 
Domain 
Measure 
Outcome 
Criteria 
Usability 
(Hyp 1b) 
System Usability Scale (SUS)40  
Mean score of AYAs randomized to treatment group 
M ≥ 6840 
System Usability Scale Adjective 
Rating41  
Mean score of AYAs randomized to treatment group 
M ≥ 441 
Acceptability 
(Hyp 1b) 
Acceptability &Adherence Scale42  
Mean score of AYAs randomized to treatment group 
M ≥ 2843 

 
 
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protected Excel database will be maintained to link study identifiers to participants. This database will be 
housed on CCHMC’s network and backed up as per below. Only trained study staff involved in the research 
and under the direct supervision of Dr. McGrady (PI) will have access to this database. 
 
Medication Adherence Data: Medication adherence data will be transmitted from the AYA’s electronic 
adherence monitoring device to the CCHMC study team via the CertiScan® cloud, a HIPAA 21CFR Pt11 
compliant cloud. Specifically, after the study team has helped the AYA to download the CertiScan mobile 
application, AYAs will “tap” their electronic adherence monitoring device to their study-provided near field 
communication (NFC)-enabled smartphone. A participant’s data will then be securely transmitted to the 
CertiScan® cloud. Of note, all participant data stored in the cloud is identified with a study identifier only (and 
no identifying data such as name or date of birth). Only trained members of the CCHMC study team will have 
access to CertiScan® cloud.  
 
The adherence electronic monitoring devices are not marked with any patient identifying information. The 
adherence electronic monitoring device is assigned to a patient using a Study ID encrypted into the device. 
Accessing the data from the adherence electronic monitoring device (including the Study ID used to link the 
patient to the device) is possible only with access to the secure online portal available only to the study team. 
Thus, even in the unlikely case that the envelope is lost in transit, it would not be possible for participant data 
to be identified.  
 
REDCap Data: Data from pre-treatment and post-treatment assessments and clinical data obtained from the 
electronic medical record will be entered and stored in REDCap, a secure and HIPAA-compliant web 
application for building and managing online surveys and databases. The barriers tool used to tailor BCTs for 
AYAs assigned to the treatment condition will be completed via Sawtooth Software hosted by CCHMC. 
Security for these web-based applications is provided through a Secured Socket Layer certificate allowing for 
128-bit encryption between client and server transactions as well as the secured demilitarized zone (DZD) 
network. Participant responses will be stored on the secured SQL server database. All data will be stored and 
accessed in accordance with the HCFA’s Internet Security Policy and HIPAA.  
 
Audio or Video Files: Audio or video files from intervention sessions (collected to rate intervention fidelity) will 
be stored in a password-protected folder on the secure CCHMC hard drive. Intervention fidelity will be rated on 
a form including the participant’s Study ID and not including any identifying information. Following fidelity 
rating, all audio files will be deleted. 
 
Exported Data: Exports of adherence (from CertiScan® cloud) and questionnaire (from REDCap) data will be 
completed by the PI or another trained member of the CCHMC study team. All exported data will be stored in 
password-protected electronic files on the CCHMC hard drive. Passwords will only be known to study staff 
directly involved in the administration and oversight of data collection. All information collected as part of this 
study will be accessible only to study staff who will complete human subjects training to ensure familiarity with 
rights of research participants and protection of confidentiality.  
 
Electronic data stored on CCHMC’s network is backed up incrementally each night, fully each week, and 
monthly in offsite vaults. The server is maintained and all backups are conducted by the Division of Biomedical 
Informatics. Access to data will be limited to study team members. 
 
Intervention Sessions: Intervention sessions will be delivered via Zoom for Healthcare, a HIPAA-compliant 
videoconferencing software. It is possible that privacy can be lost when using technology. Participants will be 
advised about this potential loss of privacy and it will be detailed in the consent document.  
 

 
 
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Consent Forms: AYAs may complete informed consent forms electronically or on paper. Electronic informed 
consent documents will be maintained in REDCap and a password-protected electronic database on CCHMC 
hard drives. Dr. McGrady’s (PI’s) team has used electronic consent signing procedures (via REDCap) for 
multiple studies with AYAs with cancer with approval from the CCHMC IRB (sIRB of record for the proposed 
research). Paper informed consent documents will be maintained in locked storage cabinets. Consent forms 
will be maintained in separate databases from participant data.  
 
SSN: Finally, because this research study involves payment for participation, we are required by Internal 
Revenue Service (IRS) rules to collect and use the AYA’s social security number (SSN) or taxpayer 
identification number (TIN) for compensation tracking purposes. We will only use the AYA’s SSN or TIN to 
track compensation. SSNs and/or TINs will not be used for any other purposes.  
 
17.4 
Data Quality 
Self-report questionnaires will be completed via REDCap, a secure web-based application for measure 
administration. To maximize data integrity and minimize the likelihood of missing data, the REDCap data 
collection system only accepts values within allowable ranges and has been programmed to prompt 
participants to complete items accidentally skipped. 
 
All data entered by a member of the study team (i.e., chart review data) will be checked by a second member 
of the study team for accuracy, with discrepancies resolved via consultation with the original data source. 
 
17.5 
Concerns About Access to Adult Websites and Apps on Cell Phones 
Participants may be provided with a cellular phone for use for the duration of the study. During the consent 
process, participants will be asked to use the cell phone “as they normally would use any smartphone that has 
internet access.” We have gone to great lengths to make the cell phone provided easy to use and compelling 
in terms of incentives and features so that participants will use the cell phone provided as opposed to other cell 
phones they likely have. However, for this endeavor to be successful, participants must feel confident that their 
phone activity--how they normally use the phone--will not be met with repercussion or reprimand. 
 
We considered only installing the CertiScan® and Zoom apps and severely restricting the accessible internet 
websites on the study cell phones. However, this would create an “unnatural” cell phone use environment for 
those participants that had not previously been exposed to filtering and would cause them to not use the study 
cell phone as their main device they carry with them. Because this would minimize the likelihood that the 
participant would have the phone available for use when they needed to upload their adherence data or 
contact their coach, we have consulted closely with study teams who have had success providing cell phones 
to participants to design the following procedures for informing participants of their options while not 
compromising the integrity of the study. Cell phones will be loaded with the CCHMC-recommended security 
software program. We will explain this to the parents/guardians and AYAs. After being informed, participants 
will be provided with cell phone contracts to review and sign. These contracts will cover basic internet and 
phone safety measures and include study contact information in case the participant experiences any technical 
issues or has concerns. The study team will be able to erase all content in the event of a lost/stolen device. 
Internet access on the phone is being restricted with Safari for the web browsers. These content filters do their 
best to block websites with inappropriate content. The Internet content filter can identify, with a high degree of 
accuracy, whether a Web page is safe or not by examining various properties of the website including text and 
structure. The content filters are being managed by the security software and cannot be removed. 
 
18.0 PROVISIONS TO MONITOR THE DATA TO ENSURE THE SAFETY OF SUBJECTS 
Not Applicable. This is a minimal risk pilot feasibility study of an adherence-promotion intervention as 
compared to uniform standard of care among AYAs with cancer.  
 

 
 
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19.0 PROVISIONS TO PROTECT THE PRIVACY INTERESTS OF SUBJECTS 
 
19.1 
Procedures to Protect Privacy Interests 
All study contacts (i.e., consent visit, intervention sessions) will be conducted in a private room or via 
videoconferencing (Zoom for Healthcare) or phone. At the beginning of study participation, study staff will work 
with the participant to come up with a plan for when/where they will complete study procedures to ensure they 
can be completed in a manner that aligns with their privacy interests (e.g., completing sessions in a private 
room so that their parents cannot hear conversations).  
 
19.2 
Procedures to Make Subjects Feel at Ease 
Participants may decline answering questions that cause them to feel uncomfortable and will be reminded of 
this prior to each study contact. Participants may also withdraw from the study at any time and will be informed 
of this right during the consent process. In the unlikely event that the content of study visit causes emotional or 
psychological distress, the Principal Investigator, Meghan McGrady, PhD, a licensed clinical psychologist at 
CCHMC (or the licensed clinical psychologist providing back-up coverage) will be contacted immediately to 
assess the situation. The psychologist triaging any concerns will provide appropriate referrals and/or treatment. 
 
19.3 
Access to Participant Information 
Individual data will not be available to anyone not directly associated with the study. All study personnel have 
been trained in data safety and monitoring, privacy and confidentiality, minimizing risks related to loss of 
privacy, and confidentiality. We will closely monitor performance of our research personnel to ensure the 
strictest standards.  
 
20.0 COMPENSATION FOR RESEARCH-RELATED INJURY 
Not Applicable. This research involves no more than minimal risk.  
 
21.0 ECONOMIC BURDEN TO SUBJECTS 
No payment from participants will be required to participate in this study. All study components (i.e., electronic 
monitoring device, cellular phone and data plan) will be supplied to participants at no cost. Participants will be 
responsible for the usual costs of medical care. If a referral for psychosocial services is made as a result of this 
study, the participant is responsible for the costs of those services.  
 
22.0 CONSENT PROCESS 
Informed consent will be obtained in accordance with SOP: Informed Consent Process for Research (HRP-
090). Informed consent will be obtained by trained research staff and may be obtained in-person or remotely. 
During the consent process, all pertinent aspects of consent/assent will be covered including study purpose, 
risks/benefits, confidentiality, and right to withdraw. Patients will be informed that their care will not be affected 
by whether they choose to participate in the study.  
 
22.1 
Consent Document Format 
Consent forms may be signed electronically using REDCap, a secure web-based interface supported by the 
CCHMC Division of Biomedical Informatics in compliance with HIPAA and designed to protect PHI in the 
electronic transfer and storage of the consent form. Should technical issues arise with the REDCap interface, 
hard copies of consent forms may also be used. If the patient/parent agrees to participate and is signing an 
electronic consent form via REDCap, they will have an opportunity to check a box stating that they agree to 
provide their consent. There will also be fields for their typed name, date, and electronic signature to document 
the informed consent process. Once the electronic form has been submitted, patients (and parents as 
appropriate) will receive a copy of the electronically signed and dated consent form via email.   
22.2 
Consent Location 

 
 
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Participants recruited in-person will complete the informed consent/parental permission document in-person 
(either via REDCap or paper forms). For participants being recruited remotely, a member of the study team will 
schedule a phone or video call and provide a link to access the consent form in REDCap via email. A hard 
copy of the consent/permission form may also be mailed if necessary. During the consent phone or video call, 
research staff will ensure all patient (and parent) questions are answered. In compliance with CCHMC SOP 
Number 41-1.6, study staff will sign and date accordingly on the signature page of each form corresponding to 
the date the forms were received, not necessarily reviewed with the family. The method used to obtain 
participant consent will also be written on the Informed Consent Process Note. 
 
22.3 
Subjects Who Are Not Yet Adults 
For participants who are under the age of 18, parental permission will be obtained from at least one parent. 
Permission will not be obtained from individuals other than parents. Assent will be obtained from all 
participants under 18 years of age and documented on the consent form. 
 
23.0 PROCESS TO DOCUMENT CONSENT IN WRITING 
Informed Consent/Parental Permission documents will be completed via REDCap or in-person. CCHMC SOP: 
Written Documentation of Consent (HRP-091) will be followed. A consent/permission document is included in 
this IRB submission. 
 
24.0 SETTING 
Participants will be recruited from Cincinnati Children’s Hospital Medical Center, Seattle Children’s Hospital, 
and St. Jude Children’s Hospital. Seattle Children’s Hospital and St. Jude Children’s Hospital are referred to as 
a “Collaborating Site” throughout the document. Our study team includes a Patient Partner serves as a 
Consultant.  
 
25.0 RESOURCES AVAILABLE 
25.1 
Access to Patient Population 
A medical record review was conducted to determine the number of eligible AYAs across each site. In 2019, 
an estimated 97 AYAs ages 15-24 years of age with a diagnosis of cancer prescribed an oral prophylactic or 
chemotherapy medication received care at one of the three participating sites: Cincinnati Children’s Hospital 
Medical Center (CCHMC), Seattle Children’s Hospital, and St. Jude Children’s Research Hospital. As detailed 
in Section 17, it is anticipated that this sample size is sufficient to enable us to achieve our recruitment goal of 
40 randomized AYAs.  
 
25.2 
Time Commitment 
This research is associated with an NIH R21 application which supports 25% of Dr. McGrady’s (PI’s) effort.  
 
25.3 
Facilities and Resources 
Dr. McGrady (PI) has access to all of the necessary resources to conduct the proposed research through a 
combination of CCHMC resources (e.g., REDCap access), Divisional support, and grant-provided resources 
(e.g., CRC support).  
 
25.4 
Communication 
A Communication Plan will be finalized prior to study initiation, but will include at a minimum, the methods 
proposed in Table 9. Dr. McGrady (PI) will be directly responsible for overseeing all communication efforts.  

 
 
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25.5 
Psychological Resources 
In the unlikely event that the content of study visit causes emotional or psychological distress, the Principal 
Investigator, Meghan McGrady, PhD, a licensed clinical psychologist at CCHMC (or the licensed clinical 
psychologist providing back-up coverage) will be contacted immediately to assess the situation. The 
psychologist triaging any concerns will provide appropriate referrals and/or treatment. All AYAs enrolled in the 
proposed research will be currently receiving care at CCHMC or one of the collaborating sites and thus have 
access to psychological services through their home institution.  
 
26.0 MULTI-SITE RESEARCH 
 
26.1 
Study-Wide Number of Subjects 
Up to 40 AYAs will be randomized to the intervention or control condition. 
 
26.2 
Study-Wide Recruitment 
Recruitment methods are described in Section 13. Consent methods are described in Section 22. Bi-weekly 
phone calls will be scheduled including the PI, Lead CRC, and Collaborating Site study staff. During these 
phone calls, Collaborating Site study staff will provide updates on recruitment.  
 
26.3 
Study-Wide Communication 
Following the approval of the protocol and the subsequent approvals of any modifications, all updated 
protocols, consent documents, and HIPAA authorization will be distributed to collaborating sites by the 
CCHMC Lead Clinical Research Coordinator. The CCHMC Lead Clinical Research Coordinator, under the 
supervision of Dr. McGrady, will ensure all required approvals have been obtained at each site prior to the 
initiation of any study procedures.  
 
Table 9. Communication Plan  
Meeting 
Frequency 
Attendees 
Topics 
Standard 
Operating 
Procedure 
Development 
Bi-Weekly 
(Study Start-Up) 
• PI (McGrady) 
• Behavioral RCT Co-I (Pai) 
• mHealth Co-I (Hommel) 
• Oncology Co-I (Norris) 
• CCHMC Research Coordinator 
(Breen) 
• Patient Partner (Burke) 
• Standard operating procedure development 
• Recruitment and retention procedure development 
• Functionality testing 
Study Team 
Training 
Single Session 
(Study Start-Up) 
• PI (McGrady) 
• Site Co-Is (Tillery, Ketterl) 
• CCHMC, Seattle, & St. Jude 
Research Coordinators 
• Interventionist (Psychology Trainee) 
• Standard operating procedure training 
• Research ethics training 
• Intervention content training 
McGrady Lab  
Weekly 
(Ongoing) 
• PI (McGrady) 
• CCHMC Research Coordinator 
(Breen) 
• Patient Partner (Burke, ~bi-monthly) 
• IRB Updates 
• Questions or concerns regarding study procedures 
Multi-Site Zoom 
Bi-Weekly 
(Ongoing) 
• PI and Site Co-Is (McGrady, Tillery, 
Ketterl) 
• CCHMC, Seattle, & St. Jude 
Research Coordinators 
• Behavioral RCT, mHealth, Oncology 
Co-Is as necessary 
• Patient Partner (Burke, ~bi-monthly) 
• Recruitment 
• Retention 
• IRB Updates 
• Questions or concerns regarding study procedures 
Supervision 
Weekly 
(Intervention Delivery) 
• PI (McGrady) 
• Interventionist (Psychology Trainee) 
• Clinical supervision 
• Review of fidelity ratings 
• Ethical/safety issues as necessary 

 
 
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REFERENCES 
 
1. Bleyer A, Choi M, Fuller CD, Thomas CR, Jr., Wang SJ. Relative lack of conditional survival 
improvement in young adults with cancer. Semin Oncol. 2009;36(5):460-467. 
doi:10.1053/j.seminoncol.2009.07.004 
2. Keegan THM, Ries LAG, Barr RD, et al. Comparison of cancer survival trends in the United States of 
adolescents and young adults with those in children and older adults. Cancer. 2016;122(7):1009-1016. 
doi:10.1002/cncr.29869 
3. Wolfson J, Sun C-L, Wyatt L, Stock W, Bhatia S. Adolescents and young adults with acute 
lymphoblastic leukemia and acute myeloid leukemia: impact of care at specialized cancer centers on 
survival outcome. Cancer Epidemiol Biomarkers Prev. 2017;26(3):312-320. doi:10.1158/1055-
9965.EPI-16-0722 
4. Barr RD, Ferrari A, Ries L, Whelan J, Bleyer WA. Cancer in adolescents and young adults: a narrative 
review of the current status and a view of the future. JAMA Pediatr. 2016;170(5):495-501. 
doi:10.1001/jamapediatrics.2015.4689 
5. National Center for Injury Prevention and Control. 10 Leading Causes of Death by Age Group, United 
States - 2017. https://www.cdc.gov/injury/images/lc-
charts/leading_causes_of_death_by_age_group_2017_1100w850h.jpg. Published 2017. Accessed 
August 11, 2020. 
6. Modi AC, Pai AL, Hommel KA, et al. Pediatric self-management: a framework for research, practice, 
and policy. Pediatrics. 2012;129(2):e473-485. doi:10.1542/peds.2011-1635 
7. Bhatia S, Landier W, Hageman L, et al. Systemic exposure to thiopurines and risk of relapse in children 
with acute lymphoblastic leukemia: a children’s oncology group study. JAMA Oncol. 2015;1(3):287-295. 
doi:10.1001/jamaoncol.2015.0245 
8. Ganesan P, Sagar TG, Dubashi B, et al. Nonadherence to imatinib adversely affects event free survival 
in chronic phase chronic myeloid leukemia. Am J Hematol. 2011;86(6):471-474. doi:10.1002/ajh.22019 
9. Kennard B, Stewart S, Olvera R, et al. Nonadherence in adolescent oncology patients: preliminary data 
on psychological risk factors and relationships to outcomes. J Clin Psychol Med Settings. 
2004;11(1):31-39. 
10. McGrady ME, Pai ALH. A systematic review of rates, outcomes, and predictors of medication non-
adherence among adolescents and young adults with cancer. J Adolesc Young Adult Oncol. 
2019;8(5)485-494. doi:10.1089/jayao.2018.0160 
11. National Comprehensive Cancer Network. NCCN Guildelines for Patients: Adolescents and Young 
Adults with Cancer. https://www.nccn.org/patients/guidelines/content/PDF/aya-patient.pdf. Published 
April 12, 2019. Accessed August 11, 2020. 
12. Pai ALH, McGrady ME. Assessing medication adherence as a standard of care in pediatric oncology. 
Pediatr Blood Cancer. 2015;62(suppl 5):S818-S828. doi:10.1002/pbc.25795 
13. Ferrari A, Thomas D, Franklin AR, et al. Starting an adolescent and young adult program: some 
success stories and some obstacles to overcome. J Clin Oncol. 2010;28(32):4850-4857. 
doi:10.1200/JCO.2009.23.8097 
14. McGrady ME, Ryan JL, Brown GA, Cushing CC. Topical review: theoretical frameworks in pediatric 
adherence-promotion interventions: research findings and methodological implications. J Pediatr 
Psychol. 2015;40(8):721-726. doi:10.1093/jpepsy/jsv025 

 
 
Page 23 of 25 
Version 2.0 (December 2022) 
 
 
15. Cane J, O'Connor D, Michie S. Validation of the theoretical domains framework for use in behaviour 
change and implementation research. Implement Sci. 2012;7(1):37. 
16. Richards JM, Plate RC, Ernst M. Neural systems underlying motivated behavior in adolescence: 
implications for preventive medicine. Prev Med. 2012;55,(suppl 0):S7-S16. 
doi:10.1016/j.ypmed.2011.11.016 
17. Colver A, Longwell S. New understanding of adolescent brain development: relevance to transitional 
healthcare for young people with long term conditions. Arch Dis Child. 2013;98(11):902-907. 
doi:10.1136/archdischild-2013-303945 
18. Chang TT, Metcalfe AW, Padmanabhan A, Chen T, Menon V. Heterogeneous and nonlinear 
development of human posterior parietal cortex function. Neuroimage. 2016;126:184-195. 
doi:10.1016/j.neuroimage.2015.11.053 
19. National Academies of Sciences, Engineering, and Medicine. The Promise of Adolescence: Realizing 
Opportunity for All Youth. Washington, DC: The National Academies Press; 2019. 
20. Steinberg L. Risk taking in adolescence: what changes, and why? Ann N Y Acad Sci. 2004;1021:51-58. 
doi:10.1196/annals.1308.005 
21. Ernst M, Pine DS, Hardin M. Triadic model of the neurobiology of motivated behavior in adolescence. 
Psychol Med. 2006;36(3):299-312. doi:10.1017/S0033291705005891 
22. Gutierrez-Colina AM, Smith AW, Mara CA, Modi AC. Adherence barriers in pediatric epilepsy: from 
toddlers to young adults. Epilepsy Behav. 2018;80:229-234. doi:10.1016/j.yebeh.2018.01.031 
23. Mancini J, Simeoni M-C, Parola N, et al. Adherence to leukemia maintenance therapy: a comparative 
study among children, adolescents, and adults. Pediatr Hematol Oncol. 2012;29(5):428-439. 
doi:10.3109/08880018.2012.693150. 
24. Linder LA, Wu YP, Macpherson CF, et al. Oral medication adherence among adolescents and young 
adults with cancer before and following use of a smartphone-based medication reminder app. J 
Adolesc Young Adult Oncol. 2019;8(2):122-130. doi:10.1089/jayao.2018.0072 
25. National Institutes of Health: National Cancer Institute. Adolescents and Young Adults with Cancer. 
https://www.cancer.gov/types/aya. Updated September 24, 2020. Accessed August 11, 2020. 
26. McGrady ME, Brown GA, Pai AL. Medication adherence decision-making among adolescents and 
young adults with cancer. Eur J Oncol Nurs. 2015;20:207-214. 
27. Michie S, Richardson M, Johnston M, et al. The behavior change technique taxonomy (v1) of 93 
hierarchically clustered techniques: building an international consensus for the reporting of behavior 
change interventions. Ann Behav Med. 2013;46(1):81-95. doi:10.1007/s12160-013-9486-6 
28. Carey RN, Connell LE, Johnston M, et al. Behavior change techniques and their mechanisms of action: 
a synthesis of links described in published intervention literature. Ann Behav Med. 2019;53(8):693-707. 
doi:10.1093/abm/kay078 
29. Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health 
Psychol. 2008;27(3):379-387. doi:10.1037/0278-6133.27.3.379 
30. Huang CY, Nguyen PA, Clinciu DL, et al. A personalized medication management platform (PMMP) to 
improve medication adherence: a randomized control trial. Comput Methods Programs Biomed. 
2017;140:275-281. doi:10.1016/j.cmpb.2016.12.012 
31. Allemann S, Nieuwlaat R, van den Bemt B, Hersberger K, Arnet I. Matching adherence interventions to 
patient determinants using the Theoretical Domains Framework. Front Pharmacol. 2016;7(429). doi: 
10.3389/fphar.2016.00429 
32. Hugtenburg JG, Timmers L, Elders PJ, Vervloet M, van Dijk L. Definitions, variants, and causes of 
nonadherence with medication: a challenge for tailored interventions. Patient Prefer Adherence. 
2013;7:675-682. doi:10.2147/PPA.S29549 
33. Choudhry NK, Isaac T, Lauffenburger JC, et al. Effect of a remotely delivered tailored multicomponent 
approach to enhance medication taking for patients with hyperlipidemia, hypertension, and diabetes: 

 
 
Page 24 of 25 
Version 2.0 (December 2022) 
 
 
the STIC2IT cluster randomized clinical trial. JAMA Intern Med. 2018;178(9):1182-1189. 
doi:10.1001/jamainternmed.2018.3189 
34. Kato PM, Cole SW, Bradlyn AS, Pollock BH. A video game improves behavioral outcomes in 
adolescents and young adults with cancer: a randomized trial. Pediatrics. 2008;122(2):e305-317. 
doi:10.1542/peds.2007-3134 
35. Bhatia S, Hageman L, Chen Y, et al. Effect of a daily text messaging and directly supervised therapy 
intervention on oral mercaptopurine adherence in children with acute lymphoblastic leukemia: a 
randomized clinical trial. JAMA Netw Open. 2020;3(8):e2014205. 
doi:10.1001/jamanetworkopen.2020.14205 
36. Bell ML, Whitehead AL, Julious SA. Guidance for using pilot studies to inform the design of intervention 
trials with continuous outcomes. Clin Epidemiol. 2018;10:153-157. doi:10.2147/CLEP.S146397 
37. Fewtrell MS, Kennedy K, Singhal A, et al. How much loss to follow-up is acceptable in long-term 
randomised trials and prospective studies? Arch Dis Child. 2008;93(6):458-461. 
doi:10.1136/adc.2007.127316 
38. Carroll C, Patterson M, Wood S, Booth A, Rick J, Balain S. A conceptual framework for implementation 
fidelity. Implement Sci. 2007;2:40. doi:10.1186/1748-5908-2-40 
39. Borrelli B, Sepinwall D, Ernst D, et al. A new tool to assess treatment fidelity and evaluation of 
treatment fidelity across 10 years of health behavior research. J Consult Clin Psychol. 2005;73(5):852-
860. doi:10.1037/0022-006X.73.5.852 
40. Bangor A, Kortum PT, Miller JT. An empirical evaluation of the system usability scale. Int J Hum 
Comput Interact. 2008;24(6):574-594. https://doi.org/10.1080/10447310802205776 
41. Bangor A, Kortum P, Miller J. Determining what individual SUS scores mean: adding an adjective rating 
scale. J Usability Stud. 2009;4(3):114-123. 
42. Milosevic I, Levy HC, Alcolado GM, Radomsky AS. The treatment acceptability/adherence scale: 
moving beyond the assessment of treatment effectiveness. Cogn Behav Ther. 2015;44(6):456-469. 
doi:10.1080/16506073.2015.1053407 
43. Soucy JN, Hadjistavropoulos HD. Treatment acceptability and preferences for managing severe health 
anxiety: perceptions of internet-delivered cognitive behaviour therapy among primary care patients. J 
Behav Ther Exp Psychiatry. 2017;57:14-24. doi:10.1016/j.jbtep.2017.02.002 
44. Zelikovsky N, Schast AP. Eliciting accurate reports of adherence in a clinical interview: development of 
the Medical Adherence Measure. Pediatr Nurs. 2008;34(2):141-146. 
45. Landier W, Chen Y, Hageman L, et al. Comparison of self-report and electronic monitoring of 6MP 
intake in childhood ALL: a Children's Oncology Group study. Blood. 2017;129(14):1919-1926. 
doi:10.1182/blood-2016-07-726893 
46. Pai AL, Gray E, Kurivial K, Ross J, Schoborg D, Goebel J. The Allocation of Treatment Responsibility 
scale: a novel tool for assessing patient and caregiver management of pediatric medical treatment 
regimens. Pediatr Transplant. 2010;14(8):993-999. doi:10.1111/j.1399-3046.2010.01391.x 
47. Varni JW, Magnus B, Stucky BD, et al. Psychometric properties of the PROMIS ® pediatric scales: 
precision, stability, and comparison of different scoring and administration options. Qual Life Res. 
2014;23(4):1233-1243. doi:10.1007/s11136-013-0544-0 
48. Lazor T, Tigelaar L, Pole JD, De Souza C, Tomlinson D, Sung L. Instruments to measure anxiety in 
children, adolescents, and young adults with cancer: a systematic review. Support Care Cancer. 
2017;25(9):2921-2931. doi:10.1007/s00520-017-3743-3 
49. R: A language and environment for statistical computing [computer program]. Vienna, Austria: R 
Foundation for Statistical Computing; 2018. 
50. Place MA, Murphy J, Duncan EAS, Reid JM, Mercer SW. A preliminary evaluation of the visual CARE 
measure for use by allied health professionas with children and their parents. J Child Health Care. 
2016;20:55-67.