Behavioral Economics for Activity Motivation in Adolescents and Young Adults With Prediabetes and Type 2 Diabetes
Phase: NA
Conditions: Type 2 Diabetes, PreDiabetes, Insulin Resistance, Polycystic Ovary Syndrome
Sponsor: University of Pittsburgh

 
 
  
Title: 
Behavioral Economics for Activity Motivation in Adolescents 
and Young Adults with Prediabetes and Type 2 Diabetes  
Short Title 
BEAM Trial 
Drug or Device 
Name(s): 
N/A 
FDA IND 
N/A 
Regulatory Sponsor: 
NIH 
eIRB Number :  
STUDY21040122 
Protocol Date:                   July 2, 2021 
Amendment 1 Date: February 22, 2022 [added option to recruit from Adolescent Medicine in 
addition to Endocrinology] 
  
 
Sponsor: National Institutes of Health 
National Institute of Diabetes and Digestive and Kidney Disorders 
K23DK125719-02 (PI: Mary Ellen Vajravelu, MD MSHP) 
 
Study Principal Investigator: Mary Ellen Vajravelu, MD MSHP  
Children’s Hospital of Pittsburgh 
Division of Pediatric Endocrinology, Diabetes, and Metabolism 
University of Pittsburgh School of Medicine 
email: MaryEllen.Vajravelu@pitt.edu 
 

  
 
 
 
 
 
 
 
ii 
TABLE OF CONTENTS 
Table of Contents .......................................................................................................... ii 
Abbreviations and Definitions of Terms ...................................................................... v 
Abstract ........................................................................................................................ vi 
Protocol Synopsis ........................................................................................................ vii 
Table 1: Schedule of Study Procedures ........................................................................ xi 
Figure 1: Study Diagram ............................................................................................. xii 
1 
BACKGROUND INFORMATION AND RATIONALE .................................................................... 1 
1.1 
INTRODUCTION ......................................................................................................................................1 
1.2 
NAME AND DESCRIPTION OF INTERVENTION .........................................................................................1 
1.3 
RELEVANT LITERATURE AND DATA .......................................................................................................1 
1.4 
COMPLIANCE STATEMENT .....................................................................................................................3 
2 
STUDY OBJECTIVES ....................................................................................................................... 4 
2.1 
PRIMARY OBJECTIVE .............................................................................................................................4 
2.2 
SECONDARY OBJECTIVES .......................................................................................................................4 
3 
INVESTIGATIONAL PLAN ............................................................................................................. 5 
3.1 
GENERAL SCHEMA OF STUDY DESIGN ....................................................................................................5 
3.1.1 
Screening Phase ...............................................................................................................................5 
3.1.2 
Baseline Study Visit (Visit 1) ..........................................................................................................5 
3.1.3 
Run-In ..............................................................................................................................................5 
3.1.4 
Intervention .....................................................................................................................................6 
3.1.5 
Follow Up Study Visit (Visit 5) ......................................................................................................6 
3.2 
ALLOCATION TO TREATMENT GROUPS AND BLINDING ..........................................................................6 
3.3 
ALLOCATION TO TREATMENT GROUPS ..................................................................................................6 
3.4 
STUDY DURATION, ENROLLMENT AND NUMBER OF SITES .....................................................................6 
3.4.1 
Duration of Subject Study Participation ........................................................................................6 
3.4.2 
Total Number of Study Sites/Total Number of Subjects Projected ..............................................6 
3.5 
STUDY POPULATION ..............................................................................................................................6 
3.5.1 
Inclusion Criteria ............................................................................................................................7 
3.5.2 
Exclusion Criteria ............................................................................................................................7 
4 
STUDY PROCEDURES ..................................................................................................................... 7 
4.1 
PHONE SCREENING .................................................................................................................................7 
4.2 
VISIT 1 ...................................................................................................................................................8 
4.3 
RUN-IN AND RANDOMIZATION .............................................................................................................8 
4.3.1 
2-Week Run-In ...............................................................................................................................8 
4.3.2 
Visit 2 (Phone) .................................................................................................................................8 
4.4 
12-WEEK INTERVENTION ......................................................................................................................9 
4.4.1 
Dietary recalls (phone) ....................................................................................................................9 
4.4.2 
Visit 3 (phone), Intervention Week 2 ............................................................................................9 
4.4.3 
Visit 4 (phone), Intervention Week 6 ............................................................................................9 
4.5 
STUDY COMPLETION ............................................................................................................................10 
4.5.1 
Visit 5, within 2 weeks of Intervention completion ...................................................................10 
4.6 
SUBJECT COMPLETION/WITHDRAWAL ................................................................................................10 

 
 
 
 
 
 
 
 
iii 
4.6.1 
Early Termination Study Visit ......................................................................................................10 
5 
STUDY EVALUATIONS AND MEASUREMENTS ........................................................................ 11 
5.1 
SCREENING AND MONITORING EVALUATIONS AND MEASUREMENTS ..................................................11 
5.1.1 
Medical Record Review ................................................................................................................11 
5.1.2 
Physical Examination ....................................................................................................................11 
5.1.3 
Vital Signs ......................................................................................................................................12 
5.1.4 
Laboratory Evaluations .................................................................................................................12 
5.1.5 
Medical History and Family History Questionnaire ...................................................................12 
5.1.6 
Dietary Recalls ...............................................................................................................................12 
5.1.7 
Questionnaire Assessment ............................................................................................................13 
5.1.8 
Exit Interview ................................................................................................................................14 
5.1.9 
Personal smartphone activity tracker data ..................................................................................14 
5.2 
EFFICACY EVALUATIONS .....................................................................................................................14 
5.3 
SAFETY EVALUATIONS .........................................................................................................................15 
6 
STATISTICAL CONSIDERATIONS ............................................................................................... 16 
6.1 
PRIMARY ENDPOINT ............................................................................................................................16 
6.2 
SECONDARY ENDPOINTS ......................................................................................................................16 
6.3 
EXPLORATORY MEASURES ...................................................................................................................16 
6.4 
CONTROL OF BIAS AND CONFOUNDING ...............................................................................................16 
6.5 
STATISTICAL METHODS .......................................................................................................................17 
6.5.1 
Analysis of Primary and Secondary Outcomes of Interest .........................................................17 
6.5.2 
Qualitative analysis .......................................................................................................................18 
6.5.3 
Exploratory analyses .....................................................................................................................18 
6.5.4 
Missing Data ..................................................................................................................................20 
6.6 
SAMPLE SIZE AND POWER ...................................................................................................................20 
7 
SAFETY MANAGEMENT .............................................................................................................. 22 
7.1 
CLINICAL ADVERSE EVENTS .................................................................................................................22 
7.2 
ADVERSE EVENT REPORTING ...............................................................................................................22 
7.3 
IRB/IEC NOTIFICATION OF SAES AND OTHER UNANTICIPATED PROBLEMS .......................................22 
7.3.1 
Follow-up report ...........................................................................................................................22 
7.4 
INVESTIGATOR REPORTING OF A SERIOUS ADVERSE EVENT TO SPONSOR ............................................22 
7.5 
MEDICAL EMERGENCIES ......................................................................................................................23 
8 
STUDY ADMINISTRATION .......................................................................................................... 24 
8.1 
TREATMENT ASSIGNMENT METHODS ..................................................................................................24 
8.1.1 
Randomization ..............................................................................................................................24 
8.1.2 
Blinding .........................................................................................................................................24 
8.2 
DATA COLLECTION AND MANAGEMENT ..............................................................................................24 
8.3 
CONFIDENTIALITY ...............................................................................................................................27 
8.4 
REGULATORY AND ETHICAL CONSIDERATIONS ...................................................................................28 
8.4.1 
Data and Safety Monitoring Plan .................................................................................................28 
8.4.2 
Risk Assessment ............................................................................................................................28 
8.4.3 
Potential Benefits of Trial Participation ......................................................................................30 
8.4.4 
Risk-Benefit Assessment ...............................................................................................................30 
8.5 
RECRUITMENT STRATEGY ....................................................................................................................30 
8.6 
INFORMED CONSENT/ASSENT AND HIPAA AUTHORIZATION .............................................................31 

  
 
 
 
 
 
 
 
iv 
8.6.1 
Screening .......................................................................................................................................31 
8.6.2 
Main Study ....................................................................................................................................31 
8.6.3 
Re-Consent Plan for Subjects Who Reach Age of Majority .......................................................31 
8.7 
PAYMENT TO SUBJECTS/FAMILIES ........................................................................................................31 
8.7.1 
Reimbursement for travel, parking and meals ............................................................................32 
8.7.2 
Payment Schema ...........................................................................................................................32 
9 
PUBLICATION ............................................................................................................................... 32 
10 
REFERENCES ................................................................................................................................. 33 
Appendix ..................................................................................................................... 38 
  

  
 
 
 
 
 
 
 
v 
ABBREVIATIONS AND DEFINITIONS OF TERMS 
 
 
 
 
 
 
AE 
AYA 
BEAM 
BMI 
BREQ-3 
mHealth 
MCQ 
MVPA 
PCTRC 
PHI 
RAI 
SAE 
T2D 
W2H 
 
Adverse event 
Adolescent and Young Adult 
Behavioral Economics for Activity Motivation trial 
Body mass index 
Behavioral Regulation in Exercise Questionnaire-3 
Mobile Health 
Monetary Choice Questionnaire 
Moderate to vigorous physical activity 
Pediatric Clinical and Translational Research Center 
Protected Health Information 
Relative Autonomy Index 
Serious adverse event 
Type 2 Diabetes 
Way to Health 
 

  
 
 
 
 
 
 
 
vi 
ABSTRACT 
Context: There is an urgent need to engineer targeted physical activity interventions that are 
effective and scalable for obese adolescents and young adults (AYA) with type 2 diabetes 
(T2D), who often have very low levels of physical activity. The BEAM Trial is a proposed 
mobile health (mHealth) intervention that uses behavioral economic-informed financial 
incentives and text messaging to promote physical activity in AYA with T2D and 
prediabetes. 
Objectives: The primary objective is to determine the main and interactive effects of four 
intervention components (“factors”) on time spent in moderate to vigorous physical activity 
(MVPA). Secondary objectives include to determine the main and interactive effects of the 
four intervention components on steps per day, body mass index Z-score; hemoglobin A1c; 
fasting insulin, glucose, triglycerides, LDL, and HDL; and liver enzymes (AST, ALT).  
Study Design: 24 full factorial trial; participants randomized to one of 16 experimental 
conditions (combination of 4 factors with 2 levels each: 1) text messages sent (a) once daily, 
or (b) twice daily; 2) financial incentives that are (a) loss- or (b) gain-framed; 3) step count 
goals set as (a) weekly or (b) daily; and 4) step count goal set as (a) ramped or (b) fixed) 
Setting/Participants: 13-22 year-old AYA who are overweight or obese (BMI≥85th 
percentile for age/sex, or ≥25 kg/m2 if ≥18 years old), have prediabetes or type 2 diabetes, 
and attend the Endocrinology or Adolescent Medicine outpatient clinic at the Children’s 
Hospital of Pittsburgh; 75 participants will be recruited. 
Study Interventions and Measures: Vitals, body size measurement, pubertal status, medical 
history, nutrition, physical activity questionnaires, behavioral questionnaires, and laboratory 
assessments will be assessed at two in-person study visits; labs (insulin, glucose, 
hemoglobin A1c, lipids, liver enzymes) will be collected after overnight fast. The primary 
outcome of MVPA and secondary outcome of step count will be measured using Fitbit 
physical activity trackers worn daily during a 12-week intervention, which will take place 
after a 2-week run-in.  
 
 
 

 
 
 
 
 
 
 
 
 
 
vii 
PROTOCOL SYNOPSIS 
Study Title 
Behavioral Economics for Activity Motivation in Adolescents and 
Young Adults with Prediabetes and Type 2 Diabetes Trial 
Funder 
National Institutes of Health 
Study Rationale 
Early intervention to reduce risks associated with youth-onset type 2 
diabetes (T2D) is critical due to high rates of cardiovascular 
comorbidities early in the disease and a 15-year reduction in life 
expectancy. Due to the difficulty of treating T2D in younger people 
and the more rapid progression of disease, efforts to prevent disease 
progression in young people with prediabetes, and new and better 
ways to treat and prevent T2D in youth are needed. The proposed 
study uses a highly efficient experimental design to investigate 
multiple potential intervention components, such as text messages 
and behavioral economic-based financial incentives, aimed at 
creating an engaging, effective intervention.  
Study Objective(s) 
Primary: to determine the impact of each intervention component 
on time spent in moderate to vigorous physical activity (MVPA).  
Secondary: to determine the impact of each intervention component 
on daily step count; body mass index Z-score; hemoglobin A1c; 
fasting insulin, glucose, triglycerides, LDL, HDL; liver enzymes. 
Test Article 
 
Each participant will be randomized to 1 combination of 4 
intervention components, each with two levels. The four 
intervention components are: 1) text messages sent (a) once daily or 
(b) twice daily; 2) financial incentives framed as (a) losses or (b) 
gains; 3) step count goals set as (a) weekly or (b) daily goals; and 4) 
step count goals: (a) ramped up gradually or (b) set at a fixed goal 
throughout the intervention.  
Study Design 
 
Factorial trial 
Subject Population 
key criteria for 
Inclusion and 
Exclusion: 
Inclusion Criteria 
1. Males or females age 13 to 22 years 
2. Overweight or obese (BMI ≥85th percentile for age/sex, or 
≥25 kg/m2 for participants ≥18 years) 
3. Diagnosis with a condition associated with insulin 
resistance, including prediabetes or type 2 diabetes 
4. Consent (adult subjects), parental/guardian permission (if 
applicable), assent (if applicable) 
5. Willingness to wear Fitbit during waking hours daily for 
duration of run-in and intervention 
6. Possession of a smartphone with data plan. 

 
 
 
 
 
 
 
 
 
 
viii 
 
Exclusion Criteria 
7. Potential subject unable to speak or read in English  
8.   Severe cognitive impairment 
9.   Permanent or temporary physical disability that impairs 
ambulation or precludes engagement in MVPA 
10. Current pregnancy 
11. Previously-diagnosed or current restrictive or purging eating 
disorder 
12. MVPA>30 minutes per day or Fitbit wear < 4 days during 
second week of 2-week run-in period 
Number Of Subjects  
75 total, all at Children’s Hospital of Pittsburgh 
Study Duration 
Each participant will attend 2 in-person study visits that will last 2-3 
hours each. The duration from study entry to completion will be no 
longer than 17 weeks.  
Study Phases 
  
Screening and recruitment: Potential subjects will be identified 
via review of Endocrinology clinic schedules weekly and by using 
the CAYAH RESEARCH INTEREST FORM distributed by 
Adolescent medicine. After potential subjects are identified, they 
will be contacted along with their parents/guardians (as applicable), 
to screen for eligibility.Subjects will be consented and will be 
scheduled for a morning study visit at the Pediatric Clinical and 
Translational Research Center (PCTRC). They will be instructed to 
complete an overnight 12 hour fast at home prior to the study visit. 
Visit 1 (in-person): Participants will undergo fasting laboratory 
evaluations, vitals, anthropometry, pubertal status, medical history, 
and physical activity and behavioral questionnaires. Participants 
will be given Fitbit physical activity trackers to wear for the 
duration of the study during waking hours and will be instructed on 
use.  
Run-In: Participants will wear the Fitbit daily during waking hours 
for 14 consecutive days. They will receive daily reminder text 
messages to wear the Fitbit. At the end of 14 days, mean daily 
MVPA and number of days Fitbit was worn during days 8-14 will 
be determined. Participants will be excluded if their MVPA was >30 
minutes/day or Fitbit wear was <4 days. Eligible participants will be 
randomized to 1 of 16 experimental conditions (4 factors, 2 levels 
each = 42=16) and step count goals assigned. 
Visit 2: Randomized participants will be called to review step goal; 
ineligible participants will be called to inform of study completion 
and will be asked to return the Fitbit via prepaid envelope. 
Intervention: Participants will wear Fitbits daily for 12 weeks. 
Three nutrition recalls will be conducted via phone (weeks 1-2). A 

  
 
 
 
 
 
 
 
ix 
safety check phone call (Visit 3) will take place during week 2 and 
another safety check and step count goal review phone call will take 
place during week 6 (Visit 4) .  
Visit 5 (in-person): After a 12-hour overnight fast at home, 
participants will attend the final study visit to undergo fasting 
laboratory evaluations, vitals, anthropometry, and exit interviews. 
Participants will return the Fitbit physical activity trackers.  
Efficacy Evaluations 
Change in minutes spent in MVPA (primary) and daily step count 
(secondary) from baseline to intervention week 12 
Safety Evaluations 
Adverse events are not anticipated. Any AEs and SAEs will be 
reported to IRB within the allotted timeframe. 
Statistical And 
Analytic Plan 
Demographic and clinical characteristics of subjects will be 
described using summary statistics, including means, standard 
deviations, medians, and ranges for continuous variables, and 
frequencies and percentages of participants for categorical variables. 
Data will be assessed for outliers. Scatter plots and box plots will be 
used to examine the relationship between independent (e.g. 
individual characteristics or component level, such as gain versus 
loss-framed incentives) and dependent variables. Longitudinal data 
will be summarized by factor level (e.g. loss-framed versus gain-
framed incentives). Statistical analyses will be conducted using 
Stata 17 or R: A language and environment for statistical 
computing. The significance level for two-sided hypothesis testing 
will be set at 0.05.  
Effect coding will be used to represent each factor level (e.g. -1 for 
loss-framed and +1 for gain-framed financial incentives). ANOVA 
will be used to evaluate main and interactive effects of intervention 
components and component levels on the primary outcome of 
change in MVPA from baseline to 12 weeks, as well as secondary 
outcomes of change in BMI Z-score, fasting insulin, triglycerides, 
LDL and HDL from Visits 1 to 5. Main and interactive effects that 
demonstrate an increase in MVPA of ≥15 minutes per day from 
baseline to week 12 will be considered effective. The main and 
interactive effects of intervention components on change in MVPA 
from baseline to 6 weeks (mid-point) will also be explored using 
ANOVA.   
DATA AND SAFETY 
MONITORING PLAN 
The study team will be responsible for data management and 
collection and are responsible for the accuracy and completeness. 
Only investigators and study team members that have completed 
appropriate IRB training/approval are eligible to collect and work 
on information collected from this study. Data will be entered 
directly into REDCap by the study team or by participants when 
responding to surveys. In order to guard against disclosure of PHI, 
each study participant will be assigned a unique identification code. 

  
 
 
 
 
 
 
 
x 
The code will be kept in a password-protected file on the PI’s 
University-managed secure server.   

 
xi  
 
 
 
 
 
 
 
TABLE 1: SCHEDULE OF STUDY PROCEDURES  
Study Phase 
Screening 
(Phone) 
Baseline 
(PCTRC) 
Run-In 
(Home) 
Assign Goal 
(Phone) 
Intervention 
(Home) 
Interim Visits 
 (Phone) 
Follow-up  
(PCTRC) 
 
 
Visit Number 
 
1 
 
2  
 
3, 4 
5  
Study Days 
 
 
2-weeks 
Within 1 
week of run-
in  
12-week 
intervention 
Weeks 2 and 6 
of Intervention 
Up to 2 weeks 
after 
Intervention  
Verbal Consent/Assent 
X 
 
 
 
 
 
 
Review Inclusion/Exclusion 
Criteria 
X 
X 
 
X 
 
 
 
Written Documentation of 
Consent/Assent 
 
X 
 
 
 
 
 
Demographics/Medical History 
 
X 
 
 
 
 
 
Physical Examination 
 
X 
 
 
 
 
X 
Vital Signs: BP, HR, RR 
 
X 
 
 
 
 
X 
Anthropometry 
 
X 
 
 
 
 
X 
Urine Pregnancy Test 
 
X 
 
 
 
 
 
Prior/Concomitant Medications 
 
X 
 
 
 
 
X 
Clinical Laboratory Evaluation  
 
X 
 
 
 
 
X 
Individual interview, surveys 
 
X 
 
 
 
 
X 
Dietary recall 
 
 
 
 
X 
 
 
Randomization  
 
 
 
X 
 
 
 
Provide/Collect Fitbit 
 
X 
 
 
 
 
X 
Fitbit compliance, goal review 
 
 
X 
X 
 
X 
 
Assess baseline physical activity  
 
 
X 
X 
 
 
 
Adverse Event Assessment 
 
 
 
X 
 
X 
X 
Daily Fitbit use 
 
 
X 
 
X 
 
 

 
page xii 
  
 
 
 
FIGURE 1: STUDY DIAGRAM 
 
 
 
 
 
Visits 3,4 
Interim phone 
visits 
Visit 5 
Final study visit 

 
  
 
 
 
1 
1 
BACKGROUND INFORMATION AND RATIONALE 
1.1 Introduction 
Obese adolescents and young adults with type 2 diabetes are significantly less active than 
non-diabetic peers, despite the many cardiovascular and diabetes-related benefits of physical 
activity. Mobile health (mHealth) strategies offer benefits over in-person physical activity 
interventions including convenience, but convenience alone is unlikely to significantly alter 
behavior. The BEAM Trial (Behavioral Economics for Activity Motivation in Adolescents 
and Young Adults with Prediabetes and Type 2 Diabetes) seeks to be the first to use 
behavioral economic principals, combined with traditional health behavior change theory, in 
an mHealth intervention to effectively motivate obese adolescents and young adults with 
prediabetes and type 2 diabetes to increase moderate to vigorous physical activity (MVPA). 
This work is supported by a funded NIH K23 Career Development Award. The trial will use 
Way to Health (W2H), a web-based platform that allows two-way text messaging, delivery 
of behavioral economic-informed financial incentives, and integration with the physical 
activity tracker Fitbit.  
1.2 Name and Description of Intervention 
This trial will evaluate four intervention components (“factors”), each with two levels: once- 
or twice-daily behavior change theory-informed text messages, loss- versus gain-framed 
financial incentives, weekly versus daily step count goals, and ramped versus fixed 
stepcount goals.  
1.3 Relevant Literature and Data 
Youth-onset T2D is rising in incidence and associated with severe comorbidities, but 
effective methods of delaying or preventing disease progression are lacking. The 
incidence of youth-onset T2D is rising, with the greatest rate of increase among racial and 
ethnic minorities.(Mayer-Davis, Lawrence et al. 2017) Youth-onset, as compared to adult-
onset T2D is especially worrisome due to faster decline in pancreatic beta-cell 
function,(Nadeau, Anderson et al. 2016) as well as high rates of diabetes-related 
complications soon after diagnosis, including elevated blood pressure (14%), 
microalbuminuria (13%), low HDL cholesterol levels (80%), and high triglycerides 
(10%).(Copeland, Zeitler et al. 2011) Individuals with youth-onset T2D also face a striking 
15-year reduction in life expectancy.(Rhodes, Prosser et al. 2012) Unfortunately, effective 
medications to preserve beta-cell function in youth are lacking,(Consortium 2018) leaving 
only lifestyle interventions to reduce obesity-related risks. 
Physical inactivity is an important modifiable risk factor for individuals with T2D and 
prediabetes. Physical activity in youth is associated with decreased fasting insulin, 
increased insulin sensitivity(Ho, Garnett et al. 2013, Lee, Deldin et al. 2013, Fedewa, Gist et 
al. 2014) and improved body composition,(Lee, Deldin et al. 2013)  and youth with T2D are 
recommended to engage in at least 60 minutes of MVPA daily, the same as for healthy 
youth.(Copeland, Silverstein et al. 2013, Colberg, Sigal et al. 2016) However, youth with 
T2D are significantly less active than obese youth without T2D, ranging from 8 minutes per 
day of MVPA in 15-18 year-old girls to 35 minutes per day in 10-14 year-old boys.(Kriska, 

 
  
 
 
 
2 
Delahanty et al. 2013) Overweight youth in Philadelphia are similarly failing to meet 
activity recommendations: only 31% reported being physically active for ≥5 hours per 
week, while 30% reported being active for ≤2 hours per week.(Deatrick, Klusaritz et al. 
2019)  
Example activities that constitute MVPA in youth include walking > 4.0 miles/hour, team 
sports, jogging, biking, and housework including sweeping and vacuuming.(Butte, Watson 
et al. 2018) Longer average time spent in MVPA daily is negatively associated with body 
mass index Z-score in youth. Increased physical activity can reverse impaired glucose 
tolerance, impaired fasting glucose, and elevated hemoglobin A1c in youth(Weiss, Taksali 
et al. 2005, Savoye, Caprio et al. 2014, Love-Osborne, Sheeder et al. 2017) and 
adults(Knowler, Barrett-Connor et al. 2002) with prediabetes, although evidence for 
improvement in glycemic control is mixed for youth with T2D,(Group, Zeitler et al. 2012, 
Herbst, Kapellen et al. 2015) likely reflecting differences in intervention design. In addition 
to a potential impact on glycemic control, greater PA has been associated with improved 
perception of physical abilities among youth with T2D,(O'Neill, Liese et al. 2012) as well as 
improvement in depression,(Brown, Pearson et al. 2013, McGavock, Dart et al. 2015) 
psychological well-being, executive functioning, and school performance(Pivovarov, Taplin 
et al. 2015) among children and adolescents without diabetes. Even time spent in low-
intensity physical activity has been associated with improved diastolic blood pressure and 
higher HDL in adolescents(Carson, Ridgers et al. 2013) as well as lower prevalence of 
hyperglycemia(Manders, Van Dijk et al. 2010) and greater insulin sensitivity(Newsom, 
Everett et al. 2013) in adults with T2D. Due to the potential benefits of increased physical 
activity for AYA with prediabetes and T2D, methods to successfully promote engagement in 
PA interventions are needed. 
Mobile health (mHealth) interventions are a promising way to promote health 
behavior change in youth. In-person lifestyle interventions(Elvsaas, Giske et al. 2017) face 
challenges with scalability due to the need for dedicated space and multidisciplinary staff, 
and in-person interventions have high attrition rates, particularly among economically 
disadvantaged and minority youth.(Zeller, Kirk et al. 2004) mHealth strategies have been 
used successfully for a wide variety of health behavior change interventions in youth(Fedele, 
Cushing et al. 2017) and allow interventions to be more scalable, especially given the near-
ubiquity of smartphone use among adolescents.(Pew Research Center)  
The effectiveness of mHealth-based interventions can be improved through the use of 
behavior change theories as well as strategies to promote user 
engagement.(Vandelanotte, Muller et al. 2016) Use of health behavior change theories 
can allow for systematic identification of targets for behavior change interventions.(Glanz, 
Rimer et al. 2015) The Theory of Planned Behavior (TPB),(Azjen 1991) a commonly used 
model for adolescent and adult health behavior change interventions,(Muzaffar, Chapman-
Novakofski et al. 2014) suggests that intention to engage in a behavior is the proximal 
determinant of that behavior. Intention, in turn, is predicted by the 3 main constructs of the 
TPB: attitude (belief about consequences of behavior combined with evaluation of 
consequence), subjective norm (belief about what others want one to do and motivation to 
comply), and perceived behavioral control (belief about amount of control one has to 
successfully perform the behavior).  

 
  
 
 
 
3 
Although the TPB posits that behavior follows intention, the field of behavioral economics 
(BE) emphasizes that humans do not always act in their best interest and applies 
psychological insights to explain behaviors that are in apparent opposition to health behavior 
goals. BE-informed interventions have been used in numerous studies of adults to promote 
health behavior change.(Volpp, John et al. 2008, Patel, Asch et al. 2016, Patel, Benjamin et 
al. 2017, Patel, Volpp et al. 2018, Glanz, Shaw et al. 2019) One BE insight is that framing, 
or the presentation of the same information in ways that highlight different informational 
cues, can significantly impact decision-making.(Thaler 1999, Dhami 2016) As losses tend to 
be felt more acutely than gains (loss aversion),(Kahneman and Tversky 1979, Patel, Asch et 
al. 2016, Wong, Miller et al. 2017) presenting information in a “loss-framed” manner tends 
to be a convincing strategy. In addition, the concept of delay discounting describes the 
tendency to prefer smaller rewards sooner over larger rewards later.(Laibson 1997) Higher 
rates of delay discounting have been associated with worse glycemic control and lower 
physical activity among adults with prediabetes and type 2 diabetes.(Epstein, Paluch et al. 
2020) Although use of traditional behavior change theories is common among mHealth-
based interventions, application of BE principals to the design of behavior change 
interventions has been understudied. 
Motivation to perform health behaviors such as physical activity can be intrinsic or 
extrinsic, which may have implications for success and persistence of behavior 
change.(Ryan and Deci 2000) According to the Self-Determination Theory, intrinsic and 
extrinsic motivation (divided into external, introjected, identified, and integrated regulation) 
fall on opposite ends of a continuum.(Ryan and Deci 2000) Intrinsic regulation represents a 
desire to engage in an activity for its own sake, while extrinsic regulation represents 
engagement in activity only to achieve outcomes or to satisfy a requirement (such as 
meeting a step count goal to obtain a financial incentive). Introjected regulation refers to 
motivation to perform an activity in order to avoid negative feelings; identified regulation 
represents a willingness to perform an activity that is not enjoyable in order to remain 
consistent with personal values; and integrated regulation falls between identified regulation 
and intrinsic regulation and represents performance of an activity because it is consistent 
with one’s values and needs. Amotivation refers to a lack of intention to engage in an 
activity. Previous studies have found that more autonomous/less extrinsic motivation is 
associated with greater physical activity in children and adolescents.(Owen, Smith et al. 
2014, Navarro, Escobar et al. 2020) Measuring and understanding whether the degree of 
intrinsic or autonomous motivation changes when extrinsic rewards are offered will add 
depth to the findings of our proposed intervention.   
1.4 Compliance Statement 
This study will be conducted in full accordance all applicable Children’s Hospital of 
Pittsburgh and University of Pittsburgh Research Policies and Procedures and all applicable 
Federal and state laws and regulations including 45 CFR 46. All episodes of noncompliance 
will be documented. 
The investigators will perform the study in accordance with this protocol, will obtain 
consent and assent, and will report unanticipated problems involving risks to subjects or 
others in accordance with institutional Policies and Procedures and all federal requirements. 

 
  
 
 
 
4 
Collection, recording, and reporting of data will be accurate and will ensure the privacy, 
health, and welfare of research subjects during and after the study.  
2 
STUDY OBJECTIVES 
The purpose of the study is to determine the efficacy of multiple components of an mHealth 
intervention aimed at promoting increased physical activity in adolescents with prediabetes 
or T2D.   
2.1 Primary Objective  
The primary objective is to determine the main and interactive effects of four experimental 
factors (once- versus twice-daily behavior change theory-informed text messages, loss- 
versus gain-framed financial incentives, daily versus weekly step count goals, and ramped 
versus fixed step count goals) on time spent in moderate to vigorous physical activity.  
 
2.2 Secondary Objectives  
The secondary objectives are to: 
• Determine the main and interactive effects of the four intervention components on: 
• Daily step count 
• body mass index Z-score 
• hemoglobin A1c 
• fasting insulin 
• fasting plasma glucose 
• fasting triglycerides, LDL, and HDL 
• AST, ALT 
• Explore participant-reported intervention acceptability, including constructs of burden, 
perceived effectiveness, and impact on self-efficacy  
• Assess baseline and intervention-related changes in intrinsic versus extrinsic motivation 
to pursue physical activity 
• Assess the association between baseline delay discounting tendency and baseline and 
change in MVPA and step count 
• Assess the correlation between Fitbit-measured physical activity and smartphone-
measured physical activity 
 

 
  
 
 
 
5 
3 
INVESTIGATIONAL PLAN 
3.1 General Schema of Study Design 
This factorial trial will include screening by phone, completion of two in-person and two 
phone study visits, completion of dietary recalls by phone at home, and daily wearing of 
Fitbit physical activity tracker during waking hours for a 14-day run-in period and 12-week 
intervention.  
3.1.1 Screening Phase 
Potential subjects will be identified through weekly review of Pediatric Endocrinology and 
Diabetes clinic schedules. In addition, a list of potentially eligible patients will be generated 
via review of a list of patients with diagnosis of prediabetes or type 2 diabetes provided by 
Pitt+ME. Medical records of potential subjects will be screened by the study team using the 
protocol inclusion and exclusion criteria. The CAYAH RESEARCH INTEREST FORM 
will also be used for recruitment purposes. This is a REDCap form with a survey link that 
will contain questions for adolescents to answer self-screen questions which are non-
sensitive. Center for Adolescent and Young Adult Health (CAYAH) clinical staff will 
manage and distribute this survey. CAYAH clinical research staff will advertise the study to 
the teen. If the teen (age 13 or older) indicates interest in the study by viewing the study 
advertisement within the CAYAH RESEARCH INTEREST FORM, they will provide their 
contact information to the CAYAH clinical research staff who will then share it with the 
study team.  Those who appear to meet the criteria will be approached by a member of the 
study team by phone and asked if they would like to hear about the study. Subjects and/or 
their parent/guardian will provide demographic, social, and medical information about 
themselves, their child, or family (as applicable) to confirm eligibility. Subjects will 
complete an overnight fast at home prior to the baseline study visit. 
3.1.2 Baseline Study Visit (Visit 1) 
After a 12-hour overnight fast at home, participants will attend Visit 1 at PCTRC to obtain 
baseline physical and biochemical data, as well as to complete individual interviews and 
surveys. At that visit, participants will be given a Fitbit to use during the study and 
instructed on its use. Participants will download the Fitbit app on their smartphone for use 
during the study. Participants will also work with a study team member to form an 
individualized implementation intention statement, which will include specific details about 
what, when, and where the subject will participate in a physical activity of choice, as well as 
contingency plans to help promote completion of planned activities. 
3.1.3 Run-In 
To determine baseline physical activity (MVPA), participants will be asked to wear the 
provided Fitbit for 14 consecutive days during waking hours and to sync the Fitbit daily with 
the app on their smartphone. They will also receive reminder text messages twice daily. 
Participants with mean daily MVPA >30 minutes or with < 4 days of Fitbit wear during the 
second week of run-in will be withdrawn from the study and will not continue on with the 
intervention. All participants will be called by phone (Visit 2) to review whether they will 
proceed to the intervention or not. Withdrawn participants will be asked to return the Fitbit 
using a prepaid envelop. 

 
  
 
 
 
6 
3.1.4 Intervention 
The 12-week intervention will consist of text messages sent to the participant and financial 
incentives that are dependent on compliance with step count goals. Eligible participants will 
be randomized and individualized step count goals for the intervention will be reviewed. 
The participant will be instructed that the intervention will begin on the following Monday 
and will last for 12 weeks.  
During week 2 of the intervention, study staff will call the participant by phone to review 
adverse events or other safety concerns (Visit 3). During week 6 of the intervention, study 
staff will call the participant by phone (Visit 4) to obtain feedback from the participant on 
the intervention and to troubleshoot any issues with the Fitbit.  
Dietary recalls (3) will be conducted by phone during the first two weeks of the 12-week 
intervention. 
3.1.5 Follow Up Study Visit (Visit 5) 
Within 2 weeks of completing the 12-week intervention, participants will be requested to 
return to PCTRC for Visit 5 to obtain follow-up physical and biochemical data, as well as 
exit interview. Participants will be asked to fast for a minimum of 12 hours before the visit, 
and will be asked to return the Fitbit at study visit 5. 
3.2 Allocation to Treatment Groups and Blinding 
3.3 Allocation to Treatment Groups 
Participants will be randomized via Way to Health to 1 of 16 experimental conditions (4 
factors, with 2 levels each; e.g., twice-daily text messages + loss-framed incentive + weekly 
goals + ramped goals = one experimental condition). 
 
3.4 Study Duration, Enrollment and Number of Sites 
3.4.1 Duration of Subject Study Participation 
Each in-person study visit is expected to take approximately 1-1.5 hours. Screening, phone 
study visits, and dietary recalls are expected to take approximately 30 minutes each. The 
entire study duration per subject is planned to last a maximum of 17-weeks (2-week run-in, 
up to 1 week between run-in and intervention, 12-week intervention, ending with study visit 
up to 2 weeks after completion of intervention). However, the time window between 
completion of the intervention and Visit 5 could be adjusted due to public health 
recommendations, and/or local, state, federal, and/or institutional guidelines.  
3.4.2 Total Number of Study Sites/Total Number of Subjects Projected 
This study will be conducted at the Children’s Hospital of Pittsburgh. A maximum of 75 
subjects will be included. 
3.5 Study Population 
We will not restrict enrollment based on gender or age within the eligible age group.  

 
  
 
 
 
7 
We plan to enroll only English-speaking patients. 
3.5.1 Inclusion Criteria  
1) Males or females age 13 to 22 years.   
2) Overweight or obese (BMI ≥85th percentile for age/sex, or ≥25 kg/m2 for participants 
≥18 years) 
3) Diagnosis with a condition associated with insulin resistance, including prediabetes or 
type 2 diabetes. 
4) Consent (subjects 18 and older), Parental/guardian permission (subjects 13-17), assent 
(subjects 13-17) 
5) Willingness to wear Fitbit during waking hours daily for duration of run-in and 
intervention. 
6) Possession of a smartphone with data plan. 
3.5.2 Exclusion Criteria 
1) Potential subject unable to speak or read in English 
2) Severe cognitive impairment 
3) Permanent or temporary physical disability that impairs ambulation or precludes 
engagement in MVPA 
4) Current pregnancy 
5) Previously-diagnosed or current restrictive or purging eating disorder 
 
6) MVPA>30 minutes per day or Fitbit wear < 4 days during second week of 2-week run-in 
period 
Subjects that do not meet all of the enrollment criteria may not be enrolled. Any violations of 
these criteria must be reported in accordance with IRB Policies and Procedures.  
4 
STUDY PROCEDURES 
4.1 Phone screening 
• Medical Record Review 
• Brief study overview: 5 minutes 
• Consent/HIPAA Authorization: 5-10 minutes/as long as needed for full 
comprehension of study involvement 
• Screening questionnaire: 15 minutes 

 
  
 
 
 
8 
• Overview of 12-hour overnight fast and upcoming screening visit: 5 minutes 
4.2 Visit 1 
• Vital signs (heart rate, blood pressure): 5 minutes 
• Urine pregnancy test (all females): 3 minutes 
• Height, weight, waist and hip circumference: 5 minutes 
• Focused physical exam, including pubertal status: 5 minutes 
• Fasting blood draw: 10 minutes 
• Baseline questionnaires: 30 minutes 
• Coach participant to form implementation intention statement about physical 
activity: 10 minutes 
• Provide Fitbit, help participant download app, and instruct on use: 5 minutes 
4.3 Run-In and Randomization 
4.3.1 2-Week Run-In  
• Participant wears Fitbit daily during waking hours and syncs daily with smartphone 
• Daily text message reminder sent to participant  
• On day 15, study team will evaluate MVPA during days 8-14 
o Exclude from intervention if mean > 30 minutes/day or if < 4 days with 
evaluable Fitbit data 
• Calculate mean daily step count during days 8-14, to provide to participant for 
reference 
4.3.2 Visit 2 (Phone)  
• Randomize to 1 of 16 experimental conditions 

 
  
 
 
 
9 
 
Figure 2. 24 = 16 experimental conditions 
• Call participant to:  
o Review assigned step count goal  
o Explain financial incentive structure  
o Troubleshoot concerns related to Fitbit or text messages 
o If not eligible based on run-in: inform participant of study completion and 
request return of Fitbit via prepaid envelope 
4.4 12-Week Intervention 
4.4.1 Dietary recalls (phone) 
• 2 weekday, 1 weekend recall during weeks 1-2 of intervention: 3 x 30 minutes each 
4.4.2 Visit 3 (phone), Intervention Week 2 
• Assess possible adverse events  
4.4.3 Visit 4 (phone), Intervention Week 6 
• Assess possible adverse events  
Text 

 
  
 
 
 
10 
• Medical Record Review 
• Troubleshoot any concerns related to Fitbit or text messages 
4.5 Study Completion 
4.5.1 Visit 5, within 2 weeks of Intervention completion  
• Medical Record Review 
• Assess possible adverse events: 5 minutes  
• Current medications: 3 minutes 
• Vital signs (heart rate, blood pressure): 5 minutes 
• Height, weight, waist and hip circumference: 10 minutes 
• Fasting blood draw: 10 minutes 
• Individual exit interview: 30 minutes 
• Collect Fitbit 
.  
4.6 Subject Completion/Withdrawal 
Subjects may withdraw from the study at any time without prejudice to their care. They may 
also be discontinued from the study at the discretion of the Investigator for lack of adherence 
to study treatment or visit schedules, AEs, or due to adherence to study treatment or visit 
schedules. The Investigator may also withdraw subjects who violate the study plan, or to 
protect the subject for reasons of safety or for administrative reasons.  It will be documented 
whether or not each subject completes the clinical study. If the Investigator becomes aware 
of any serious, related adverse events after the subject completes or withdraws from the 
study, they will be recorded in the source documents and on the case report form (CRF) on 
REDCap. 
Fitbit, questionnaire, interview, and clinical data obtained prior to subject withdrawal will be 
retained. 
4.6.1 Early Termination Study Visit 
Subjects who withdraw from the study will have all procedures enumerated for Visit 5 as the 
early termination visit if at least 4 weeks have elapsed since the start of the 12-week 
intervention.  
 
 

 
  
 
 
 
11 
5 
STUDY EVALUATIONS AND MEASUREMENTS 
5.1 Screening and Monitoring Evaluations and Measurements 
5.1.1 Medical Record Review 
Participants will be interviewed regarding their medical history. To ensure that no major 
items are missed and to clarify interview answers, the study team will review participant 
electronic medical records prior to and after the participant interview to confirm the 
following: 
• Date of birth 
• Birth history (gestational age, birth weight, complications during pregnancy) 
• Anthropometrics (weight, height, BMI) 
• Medications 
• List of medical problems, especially as they relate to inclusion and exclusion criteria 
• Demographic data including race, ethnicity, gender, and insurance type 
• Endocrine-related diagnoses, including: insulin resistance, prediabetes, impaired 
glucose tolerance, impaired fasting glucose, elevated hemoglobin A1c, diabetes 
mellitus, and polycystic ovary syndrome  
• History of attendance at an obesity clinic  
• History of bariatric surgery 
• Diabetes-related labs, including: plasma and point-of-care glucose, hemoglobin A1c, 
and insulin 
• History of non-alcoholic fatty liver disease, non-alcoholic steatohepatitis, elevated 
ALT or AST, or other known liver disease 
5.1.2 Physical Examination 
A study physician (pediatric endocrinologist) will review with the parent and child the 
child’s current and past medical history, a review of systems, and family history (with 
particular attention to cardiovascular disease and diabetes). A focused physical examination 
will be conducted, including measurement of height, weight, waist circumference, hip 
circumference, pubertal staging, and pertinent physical findings associated with insulin 
resistance, including the presence of acanthosis nigricans, which will be recorded on a 
standardized form.  Investigators will verify that the patient has been fasting for a minimum 
of 12 hours.  
 

 
  
 
 
 
12 
5.1.3 Vital Signs 
• Blood pressure (BP) will be recorded while the subject is sitting down by the nursing 
staff. BP will be measured by auscultation three times, after a five minute rest in a 
quiet area with the subject in a seated position; the average of the 2nd and 3rd 
measurements will be used. 
• Pulse and respiratory rate will be measured by nursing staff 
5.1.4 Laboratory Evaluations  
5.1.4.1 Table: Clinical Laboratory Tests  
Category 
Tests 
Biomarkers of glucose 
metabolism 
Hemoglobin A1c, plasma glucose, insulin 
Liver function tests 
SGOT/AST, SGPT/ALT 
Lipids 
Triglycerides, LDL, HDL 
 
5.1.4.2 Pregnancy Testing 
A urine pregnancy test will be performed for all female subjects at baseline. A positive 
pregnancy result will be disclosed to the participant only. Pregnancy results will be 
disclosed to the parent/guardian if the subject gives the investigators permission. Subjects 
found to be pregnant during the visit will not be able to enroll in this study. The 
investigators will counsel the subject and guide them to seek the appropriate care. 
5.1.5 Medical History and Family History Questionnaire  
Will include past medical history, 1st and 2nd degree family history of diabetes, dyslipidemia, 
cardiovascular disease, and socioeconomic status questions. 
5.1.6 Dietary Recalls 
During weeks 1-2 of the intervention, three 24-hour (2 weekday, 1 weekend) dietary recall 
interviews of participants will be conducted by a Children’s Hospital of Pittsburgh 
registered dietitian via phone or in-person. Reported intake will be entered into a nutrition 
application (e.g. CalorieKing), without any patient-identifying information, in order to 
determine nutrition information including calories, protein, saturated fat, fatty acids, added 
sugar, and sodium. These data will be used to calculate the Healthy Eating Index score, 
(Krebs-Smith, Pannucci et al. 2018) using the scoring standards listed in Figure 3.  

 
  
 
 
 
13 
 
Figure 3. Healthy Eating Index-2015 Components and Score Standards; 
https://www.fns.usda.gov/how-hei-scored. 
5.1.7 Questionnaire Assessment 
PACE+ adolescent physical activity questionnaire will be administered by the study 
coordinator or appropriate member of the investigative team. PACE+ is a validated, two 
question measure of physical activity.(Prochaska 2000)  
Monetary Choice Questionnaire (MCQ) is a set of 27 questions developed by Kirby et 
al(Kirby, Petry et al. 1999) that is used to measure temporal discounting, or the tendency to 
prerfer smaller, sooner rewards over larger, delayed rewards. It is a self-administered 
questionnaire that has been used in numerous studies of adults and adolescents. Ten ranges 
of discount rates are used, with delays ranging from 7-186 days. To evaluate the degree of 
delay discounting, a hyperbolic function is fit to bivariate data on indifference points 
between delayed rewards (small, medium, and large rewards) and delay. A parameter (k) 
resulting from the model may be used to compare discount tendencies across individuals or 
over time. 
Behavioral Regulation in Exercise Questionnaire-3 (BREQ-3) is a 24-item questionnaire 
drawing from Self-Determination Theory(Ryan and Deci 2000) that asks respondants to rate 
statements about physical activity behaviors as “Not true for me,” “Sometimes true for me,” 
or “Very true for me.”(Mullan, Markland et al. 1997, Wilson, Rodgers et al. 2006) It is used 
to assess motivation on the spectrum of intrinsic to extrinsic to amotivation and has been 

 
  
 
 
 
14 
used to assess motivation to perform physical activity in adolescents.(Navarro, Escobar et al. 
2020)   
5.1.8 Exit Interview 
Semi-structured individual interviews will be conducted by study staff in a private setting at 
visit 5 to evaluate intervention acceptability, including constructs of burden, perceived 
effectiveness, and impact on physical activity-related self-efficacy. Interviews will be 
audiorecorded and then transcribed by a University of Pittsburgh-approved vendor. 
5.1.9 Personal smartphone activity tracker data 
Once weekly during the 12-week intervention, participants will be asked (via text message) 
to send in a screenshot of their smartphone’s activity tracker’s step count measurement for 
the week. Step counts will be abstracted via study staff and entered into a secure REDCap. 
 
Figure 4. Example of smartphone activity tracker data summary 
 
5.2 Efficacy Evaluations  
MVPA (>100 steps per minute)  is the primary endpoint to evaluate efficacy and will be 
obtained via Fitbit and W2H. Fitbit data collected through W2H will include step count, 
heart rate, manually logged activities, and sleep data, if available due to participant choosing 
to wear the Fitbit at night. MVPA will be calculated by W2H.  

 
  
 
 
 
15 
5.3 Safety Evaluations  
Participants will be fasting for a minimum of 12 hours prior to on site  study visits. This may 
cause hunger pangs, upset stomach, headache, or light-headedness. If the participant shows 
any signs of clinical instability or definitively decides to discontinue participation, the study 
visit will be ended. 
The patient will be notified of any clinically relevant abnormal test result(s) performed, by 
mail and or by phone. It will be recommended that results, especially abnormal results, be 
discussed by the guardian with the participant’s primary care physician.  

 
  
 
 
 
16 
6 
STATISTICAL CONSIDERATIONS 
6.1 Primary Endpoint 
We will determine the main and interactive effects of intervention components on mean 
daily MVPA during week 12 of the intervention.  
6.2 Secondary Endpoints 
Secondary endpoints include main and interactive effects of intervention components on 
mean steps per day during week 12 of the intervention, and change from visit 1 to visit 5 in: 
• body mass index Z-score,  
• hemoglobin A1c, 
• fasting insulin, 
• fasting glucose, 
• fasting triglycerides, LDL, HDL, and 
• liver enzymes (AST, ALT) 
6.3 Exploratory Measures 
Self-reported behavioral and motivational measures will be collected to use as covariates in 
multivariable analysis, as well as for exploratory correlational analyses. These include: 
• Delay discounting tendency (k) 
• Relative autonomy index  
• Healthy eating inventory 
• Smartphone-collected step count 
6.4 Control of Bias and Confounding 
Potentially eligible subjects will be stratified by sex and age (13-18, 19-22), and an equal 
number of participants will be contacted per group until recruitment goals are reached or all 
potentially eligible subjects in a category are enrolled or decline to participate. 
Multivariable models will adjust for covariates including age, sex, race, ethnicity, disease 
type (prediabetes versus diabetes), baseline laboratory values, anthropometrics (e.g. BMI-Z), 
and baseline activity level. The distribution of measured motivation characteristics and delay 
discounting tendencies will be assessed across intervention components (e.g., proportion 
with high measures of intrinsic motivation among those randomized to loss-framed versus 
those randomized gain-framed incentives) will be assessed. If imbalanced across 
components, these measures will be included in multivariable models.  
 

 
  
 
 
 
17 
6.5 Statistical Methods 
6.5.1 Analysis of Primary and Secondary Outcomes of Interest 
Descriptive and visual statistics: Demographic and clinical characteristics of subjects will be 
described using summary statistics, including means, standard deviations, medians, and 
ranges for continuous variables, and frequencies and percentages of participants for 
categorical variables. Data will be assessed for outliers. Scatter plots and box plots will be 
used to examine the relationship between independent (e.g. individual characteristics such as 
age, prediabetes versus T2D, race/ethnicity; as well as component level, such as gain versus 
loss-framed incentives) and dependent variables. Line plots will be generated for the primary 
outcome of daily MVPA, with one line per subject and an overall trend line. Longitudinal data 
will be summarized by factor level (e.g. loss-framed versus gain-framed incentives). 
Statistical analyses will be conducted using Stata 17 (StataCorp, College Station, TX) or R: 
A language and environment for statistical computing (R Corp Team, Vienna, Austria). The 
significance level for two-sided hypothesis testing will be set at 0.05. 
Main Effects and Interactions: The trial is a 24 full factorial design (4 factors with 2 levels 
each), resulting in 16 experimental conditions. Importantly, this is not a 16-arm randomized 
control trial: in factorial designs, subjects are “recycled,” allowing for the N per level (e.g. 
subjects randomized to loss-framing) to be the relevant value rather than the n per 
experimental condition.(Collins 2018) Effect coding will be used to represent each factor level 
(e.g. -1 for loss-framed and +1 for gain-framed).(Collins, Dziak et al. 2014) Effect coding 
allows effect estimates to be uncorrelated when the factorial study is balanced, which allows 
hypothesis tests to be independent.(Collins 2018) With effect coding, beta coefficient standard 
errors are equal, so in a balanced design, the power to detect each coefficient is the same. 
ANOVA will be used to evaluate main and interactive effects(Collins, Dziak et al. 2014) of 
intervention components and component levels on the primary outcome of change in weekly 
mean minutes in MVPA per day from baseline to 12 weeks, as well as secondary outcomes of 
change in BMI Z-score,(Centers for Disease Control and Prevention 2009) fasting insulin, 
triglycerides, LDL, and HDL from Visit 1 to Visit 5. For example, the main effect (ME) of 
ramped (versus no ramping) of step count goal on MVPA would be the mean change in daily 
MVPA of conditions 1-8 minus that of conditions 8-16: 𝑴𝑬𝑹𝒂𝒎𝒑𝒆𝒅= (𝝁(.(.. −𝝁(.)..), where 
“+/-” represent levels of each factor (i.e. ramped (+) versus no ramp (-)) and “.” represents 
all levels combined. Two-way and three-way interactions will also be assessed. A two-way 
interaction is calculated by halving the difference in the effect of a factor across the level of a 
second factor, averaging over all other factors.(Montgomery 2009) For example, the 
interaction between twice-daily text messages and ramped goals would be half the difference 
in main effect of twice-daily messages for ramped conditions (mean of conditions 1-4 minus 
mean of conditions 5-8) and main effect of twice-daily messages for un-ramped conditions 
(mean of conditions 8-12 minus mean of conditions 9-12): 𝑰𝑵𝑻𝑹𝒂𝒎𝒑𝒆𝒅×𝑻𝒘𝒊𝒄𝒆𝑻𝒆𝒙𝒕=
(𝝁3!!..)𝝁3#!..))(𝝁3!#..)𝝁3##..)
𝟐
. A 3-way interaction between ramped goals, tailored text messages, 
and 
incentive 
framing 
(loss 
versus 
gain) 
would 
be 
calculated 
as: 
𝑰𝑵𝑻𝑹𝒂𝒎𝒑𝒆𝒅×𝑻𝒘𝒊𝒄𝒆𝑻𝒆𝒙𝒕×𝑰𝒏𝒄𝒆𝒏𝒕𝒊𝒗𝒆=
(𝝁3!!!.)𝝁3#!!.))(𝝁3!#!.)𝝁3##!.))(𝝁3!!#.)𝝁3#!#.))(𝝁3!##.)𝝁3###.)
𝟒
. 
This will allow us to investigate the impact of intervention component settings individually 
and in combination, in order to determine which component settings are most effective at 
increasing MVPA and should be included in an optimized intervention. Main and interactive 

 
  
 
 
 
18 
effects that demonstrate an increase in MVPA of ≥15 minutes per day from baseline to week 
12 will be considered effective. The main and interactive effects of intervention components 
on change in MVPA from baseline to 6 weeks (mid-point) will also be explored using 
ANOVA.   
In addition to ANOVA to evaluate effects of the intervention on MVPA at fixed time points 
(0 versus 12 weeks, 0 versus 6 weeks, Visit 1 versus Visit 5), mixed effects linear regression 
models will be created, including interactions found to be significant in ANOVA. These 
models are implemented via maximum likelihood and account for within- and between-
subject variability.(Hedeker and Gibbons 2006) Random intercepts will be used to allow for 
variation between subjects. Sensitivity of the primary analysis to choice of variance model 
will be examined. 
Table 1 summarizes the analyses planned by outcome measure. 
6.5.2 Qualitative analysis 
After the completion of exit interviews, recordings will be transcribed. Transcripts will be 
analyzed in NVivo software, using directed content analysis techniques(Merriam and Tisdell 
2016) to identify and organize relevant themes. Codes and coding rules for a codebook will 
be established by the PI and study staff based on the interview guide and transcripts. When 
the codebook is established, at least two study staff will independently code transcripts to 
identify themes and sub-themes, resolving disagreements in coding through discussion. 
Themes will be summarized and compared across demographic groups (e.g. sex, age, 
race/ethnicity), component-level (e.g., loss- versus gain-framed financial incentives), and 
diagnosis of prediabetes versus T2D, as well as by intervention effect on MVPA (e.g., more-
successful versus less-successful goal achievement by study completion).  
6.5.3 Exploratory analyses 
Demographic characteristics of participants who were excluded after the run-in period (due 
to MVPA>30 minutes/day or Fitbit wear < 4 days in week 2) will be compared (mean/t-test 
or median/ranksum for continuous variables, or Fisher’s exact test for categorical variables) 
to participants who were randomized and began the intervention. Adherence to Fitbit wear 
and syncing will be assessed as number of days with Fitbit data available during the 
intervention; adherence will be compared across baseline participant characteristics, 
including demographics, body size measurements, disease (prediabetes or T2D), relative 
autonomy index, and delay discounting measure.  
 
 

 
  
 
 
 
19 
Table 1. Analysis plan 
Outcome 
Analysis/statistical test 
MVPA min/day: baseline vs 6 and 12 weeks 
(primary outcome) 
Mean/SD or median/IQR, ANOVA/ANCOVA 
MVPA min/day:  baseline vs 6 and 12 weeks 
% of days with ≥60 min/day, Fisher’s exact test 
MVPA  min/day: average per week of 
intervention 
% of days with ≥60 min/day, Fisher’s exact test 
Steps/day: baseline (2nd-week of run-in) versus 
6 weeks and 12 weeks  
Mean/SD or median/IQR,  ANOVA/ANCOVA 
Steps/day: baseline (2nd-week of run-in) versus 
6 weeks and 12 weeks 
% of days with ≥10,000 steps/day, Fisher’s 
exact test 
Steps/day: average per week of intervention 
% of days with ≥10,000 steps/day, Fisher’s 
exact test 
Body mass index Z-score 
Mean/SD or median/IQR,  ANOVA/ANCOVA 
Hemoglobin A1c, insulin, glucose, triglycerides, 
LDL, HDL, AST, ALT 
Mean/SD or median/IQR,  ANOVA/ANCOVA 
Hemoglobin A1c 
% <5.7%, 5.7-6.4%, ≥6.5%, Fisher’s exact test 
Healthy Eating Index 
Mean/SD or median/IQR,  ANCOVA 
covariate, Pearson/Spearman correlation with 
demographic variables 
Measure of delay discounting, k, derived from 
MCQ 
Mean/SD or median/IQR,  ANCOVA covariate 
(visit 1 measure), Pearson/Spearman 
correlation with demographic variables, paired 
t-test or Wilcoxon signed rank test to assess 
whether baseline and follow-up measures differ 
Relative Autonomy Index (RAI) from BREQ-3 
Mean/SD or median/IQR,  ANCOVA covariate 
(visit 1 measure), Pearson/Spearman 
correlation with demographic variables, 
ANOVA/ANCOVA to assess change from 
visit 1 to 5 by experimental factor 
PACE+: number of days with at least 60 
minutes of activity per day in (a) past 7 days 
and (b) typical week 
Mean/SD or median/IQR,  Pearson/Spearman 
correlation with demographic variables and 
with number of days with MVPA ≥60 minutes 
at baseline and week 12  
Steps/week on smartphone activity tracker 
Pearson/Spearman correlation with Fitbit-
measured steps/week 

 
  
 
 
 
20 
 
6.5.4 Missing Data 
Step count and MVPA data may be missing for any day if the Fitbit is not used or not 
synced. To prevent potential downward bias from very low minutes per day, we will ignore 
days in which fewer than 1000 steps are recorded, as this likely represents a failure to 
capture actual activity.(Rowe, Mahar et al. 2004, Patel, Benjamin et al. 2017) We will use 
multiple imputation for missing data or days with fewer than 1000 steps recorded, and 
results will be combined using standard rules.(Rubin 1987, Allison 2002) Predictors will 
include baseline daily minutes in MVPA, experimental condition, week in study after 
baseline (1-12), calendar month, and an indicator variable for weekday or weekend.(Patel, 
Benjamin et al. 2017) We will perform sensitivity analyses using all collected data without 
multiple imputation, including or excluding days with fewer than 1000 steps. Of note, mixed 
effects models allow for handling of incomplete and unbalanced data, making possible an 
intention-to-treat approach using the missing at random assumption. To minimize 
confounding for secondary outcomes, in a sensitivity analysis, subjects who start a new 
medication that may alter weight (including metformin, insulin, or glucagon-like peptide-1 
receptor agonists) after visit 1 will have visit 5 weight, waist circumference, and laboratory 
measurements censored.  
As an exploratory analysis, for days with missing Fitbit data, we will use participant-
reported step count data recorded by their smartphones (sent via screenshot once weekly via 
text message to Way to Health).  
 
6.6 
Sample Size and Power 
To determine sample size, the MOST R package (FactorialPowerPlan) was used.(Collins, 
Huang et al. 2017) Using a sample size of 64, 4 factors (n=16/factor, n=4/experimental 
condition), and two-sided alpha = 0.05, we will have at least 80% power to detect a 15-
minute change in MVPA assuming a standard deviation of 20 minutes(Kriska, Delahanty et 
al. 2013) (Table 2). To allow for 64 evaluable subjects, we will recruit 75 AYA (anticipated 
dropout rate of 15%). In 2020, the Children’s Hospital of Pittsburgh Division of Pediatric 
Endocrinology, Metabolism, and Diabetes followed approximately 2200 patients, 
approximately 10% (~220) of whom have type 2 diabetes. The vast majority of youth with 
type 2 diabetes are in the adolescent age range that will be targeted in this intervention. In 
addition, a variable number of youth with prediabetes are seen by the Division. Based on 
this, a total sample size of 75 is feasible to enroll over the planned study period. For 
secondary outcomes including BMI Z-score, labs, and Healthy Eating Index, using a sample 
size of 64, 4 factors, and two-sided alpha = 0.05, we will have at least 80% power to detect a 
standardized regression coefficient of 0.36. 
Table 2. Effect size and power estimates (N=64) 
∆ 
SD 
Effect size 
𝜶 
Power 
15 
20 
0.38 
0.05 
0.84 
15 
20 
0.38 
0.1 
0.91 

 
  
 
 
 
21 
 
 
- 
- 
0.36 
0.05 
0.80 
- 
- 
0.32 
0.1 
0.80 

 
  
 
 
 
22 
7 
SAFETY MANAGEMENT 
7.1 Clinical Adverse Events 
Clinical adverse events (AEs) will be monitored throughout the study.  
7.2 Adverse Event Reporting 
Since the study procedures are not greater than minimal risk, serious adverse events (SAEs) 
are not expected. If any unanticipated problems related to the research involving risks to 
subjects or others happen during the course of this study (including SAEs) they will be 
reported to the IRB in accordance with institutional guidelines. AEs that are not serious but 
that are notable and could involve risks to subjects will be summarized in narrative or other 
format and submitted to the IRB at the time of continuing review. 
The relationship of each SAE to the study intervention will be characterized using one of the 
following terms in accordance with IRB Guidelines: definitely, probably, possibly, unlikely 
or unrelated.  
7.3 IRB/IEC Notification of SAEs and Other Unanticipated Problems 
The Investigator will promptly notify the IRB of all on-site unanticipated, serious Adverse 
Events that are related to the research activity. Other unanticipated problems related to the 
research involving risk to subjects or others will also be reported promptly. Written reports 
will be filed using the electronic IRB system and in accordance with the timeline below. 
External SAEs that are both unexpected and related to the study intervention will be 
reported promptly after the investigator receives the report.   
Type of Unanticipated Problem 
Initial 
Notification  
(Phone, 
Email, Fax) 
Written Report 
Internal (on-site) SAEs 
Death or Life Threatening  
24 hours 
Within 2 calendar days 
Internal (on-site) SAEs 
All other SAEs 
7 days 
Within 7 business days 
Unanticipated Problems Related to Research 
7 days  
Within 7 business days 
All other AEs 
N/A 
Brief Summary of important AEs may 
be reported at time of continuing review 
7.3.1 Follow-up report 
If an SAE has not resolved at the time of the initial report and new information arises that 
changes the investigator’s assessment of the event, a follow-up report including all relevant 
new or reassessed information (e.g., concomitant medication, medical history) will be 
submitted to the IRB. The investigator will be responsible for ensuring that all SAE are 
followed until either resolved or stable.  
7.4 Investigator Reporting of a Serious Adverse Event to Sponsor 
Reporting will be consistent with National Institutes of Health requirements. 

 
  
 
 
 
23 
7.5 Medical Emergencies 
Medical emergencies that might develop during the course of the study at PCTRC will be 
referred to the CHP emergency room. Medical emergencies that might develop during the 
course of the study during the at-home intervention will be referred to local emergency 
medical services.  
 

 
  
 
 
 
24 
8 
STUDY ADMINISTRATION 
8.1 Treatment Assignment Methods 
8.1.1 Randomization 
The Way to Health platform will be used to generate random sequences to assign eligible 
participants to one of sixteen experimental conditions.  We will use a block randomization 
approach so that we will have 3-5 participants randomized to each study condition. 
Demographic and clinical characteristics will be assessed at baseline. If there are differences 
with respect to key covariates (e.g., age, sex, baseline activity level) across component 
levels at baseline we will consider including those variables as covariates in our statistical 
models. 
 
8.1.2 Blinding 
It will not be feasible to blind participants to the intervention components, and in fact would 
be undesirable to do so, as the intent of the behavior change intervention is to leverage 
behavioral economic insights to promote behavior change. Study staff will not be blinded, in 
order to ensure financial incentives are provided as intended and that assigned step count 
goals are communicated correctly to participants. During data analysis, each intervention 
component (factor) will be assigned a de-identified categorical value (A, B, C, D) with two 
de-identified levels (1, 2). Thus, the main and interactive effects of each intervention 
component can be evaluated in a blinded fashion.  
8.2 Data Collection and Management 
Case report forms (CRF) in a REDCap database will be created by the study team for data 
capture. REDCap is a secure web-based data management software designed by Vanderbilt 
University investigators. Study data will be entered through intelligent REDCap forms that 
adapt to data content, and include built-in eror checks to trap out-of-range or inconsistent 
entries into the central database.   
 
The PI is responsible for the accuracy and completeness of data collection and management. 
The PI may designate qualified individual(s) to collect data and manage data. Only 
investigators and research staff that have completed appropriate IRB training and approval 
and are listed on the IRB approved protocol are eligible to collect and work on information 
from the study. Future studies that may use patients or data collected from this study must 
have separate approved IRB protocols and consent forms, if applicable. Data will be 
recorded onto the screening questionnaire after consent is documented. Original data will be 
recorded directly into CRFs by the study coordinator or a study investigator. Copies of 
laboratory, physical exam, anthropometric, and questionnaire responses will be received 
through the electronic medical record or through secured email. This information also will 
be recorded into CRFs in REDCap. The password to log into REDCap will be unique to 
each member of the study team.  
Fitbit Data: Following enrollment and completion of the participant’s Way to Health profile, 
study staff will help connect the participant’s mobile device to the participant’s Fitbit 
account and authorize W2H to access their data using OAuth. Participants will be asked to 

 
  
 
 
 
25 
download the free Fitbit app onto their smartphone to allow the Fitbit to sync at least once 
daily. Once the participant’s account is authenticated to W2H, an hourly background job 
will query the vendor API for activity since the last data point that was downloaded. The 
daily Fitbit data will then be available to the study team on the secure, password-protected 
W2H platform and will be downloaded as a CSV file directly to the PI’s institutional shared 
drive. 
 
Survey Data: Participants will either complete surveys by hand or directly into REDCap. 
Study IDs will be used to link responses to participants. If used, responses on paper forms 
will be transferred via study staff to REDCap. Original paper forms will be stored in a 
secure file cabinet in the PI’s office. 
 
Exit Interview Data: Written data collected during the interview will be stored in a secure 
file cabinet in the PI’s office. Only the research team will have access to interview notes, 
which will be destroyed after a minimum of 7 years after completion of the study. 
Interviews will also be audio-recorded. Audio recordings will be kept as digital files and 
kept on the PI’s password-protected institutional shared drive. Recordings will be destroyed 
after the recordings are transcribed and qualitative analysis is complete. 
 
Way to Health Platform:  
Way to Health (W2H) is the vendor that will be used to collect Fitbit data and text message 
responses (screenshot of step count on smartphone). It is a software platform developed by 
the Penn Center for Health Incentives and Behavioral Economics (CHIBE) at the University 
of Pennsylvania (UPENN) and is currently operated through a partnership between CHIBE 
and the Penn Medicine Center for Health Care Innovation. W2H is an integrated, cloud-
based platform that blends behavioral science with scalable digital technology to improve 
clinical outcomes. W2H automates many research functions necessary for conducting 
randomized controlled trials of healthy behavior interventions. UPENN is not considered to 
be engaged in the research, as the W2H platform does not directly administer research 
interventions but instead facilitates research-related activities such as online and mobile 
participant enrollment; survey administration; integrated biomedical device data 
transmissions; automated randomization in a variety of schemes; automated communication 
with participants/patients via voice, text and email; delivery of financial and social 
incentives; utilization of gamification strategies and more. Furthermore, the W2H services 
do not merit professional recognition, and services are used at Upenn for both research and 
non-research purposes. More details are available at https://waytohealth.org. 
W2H is a HIPAA compliant platform and collects subjects’ names, dates of birth, and phone 
numbers. To assure that participant confidentiality is preserved, individual identifiers are 
stored in a single password protected folder on a shared drive that is accessible only to study 
research, analysis and IT staff. An investigator or statistician who logs in will be able to 
access only coded data. The W2H administrative group is able to view participant names 
and contact information, but will not participate in any research activities.  
 
The W2H web development team and Project Director currently have administrative access 
to PHI. All of these personnel will have completed Human Subjects Protection and HIPAA 
privacy training. The system automatically generates logs of all data queries which can be 

 
  
 
 
 
26 
reviewed by research staff to ensure that no unauthorized persons have gained access to 
identifiable information. This system is hosted on site at The University of Pennsylvania 
(UPenn) and is protected by a secure firewall and several layers of operational security. 
Once a participant has been entered into this system, they are given a unique study 
identification number (ID). Any datasets and computer files that leave the firewall are 
stripped of all identifiers and individuals are referred to by their study ID. The study ID is 
also used on all analytical files. 
The Penn Medicine Academic Computing Services (PMACS) is the hub for the hardware 
and database infrastructure that supports the project and the W2H web portal is built on this 
infrastructure. The data collected for W2H based studies is stored in My Structured Query 
Language databases on a PMACS-operated blade server environment devoted specifically to 
W2H. The data center is housed in Information Systems and Computing at 3401 Walnut 
Street. All data are stored in a single relational database, allowing researchers to correct 
mistakes. Every Structured Query Language (SQL) transaction, including accessing and 
changing data, is logged for auditing purposes. Data are entered into the database through 
several different mechanisms. Participants enter their own personal information and respond 
to surveys through a PHP-based web interface. Researchers have a separate interface that 
allows them to manually enter data if needed. Data from biometric/monitoring devices are 
uploaded automatically, this includes data from mobile phones such as picture or text 
messaging. Datasets are blinded of all personally identifiable information when exported for 
analysis. The web application automatically removes all identifiers when a researcher 
requests an analytic dataset. Personal information and research data will be stored in 
separate SQL tables and will be linked by a computer-generated ID number. Additionally, 
any information that leaves this system to communicate with third party data sources 
(biometrics devices, survey software, etc.) is stripped of any identifiers and transmitted in 
encrypted format. The same unique study ID is used to link these outside data to the 
participants.  
 
The W2H Research Data Center staff is responsible for preventing unauthorized access to 
the trial participant tracking system database. The secure servers are located in a specially 
designed, highly secured facility at UPenn with dedicated uninterrupted power supply and 
strictly limited access. The study will utilize a client-server deployed Data Management 
System rather than a 'Store and Forward' database configuration, obviating research site 
database security concerns. Confidential participant information will be entered into the 
database. Thereafter, confidential information will be made available to authorized users 
only as specifically needed. No one can gain access to an individual SQL database table 
unless explicitly granted a user ID, password, and specific access. Even those with user 
names and passwords cannot gain access to the tables that contain the identifying participant 
information.  
 
No results will be reported in a personally identifiable manner. All tracking system data will 
be password-protected with several levels of protection. The first will allow access to the 
operating system of the computer. The second will allow access to the basic menus of the 
integrated system; within certain menu options, such as database browsing, a third password 
will be required. W2H’s team’s prior research employing similar precautions has 
demonstrated that these techniques are very successful in assuring the protection of subjects.  

 
  
 
 
 
27 
 
The W2H portal applies security and privacy requirements generated by the HIPAA 
Security Rule and subsequently the HITECH requirements. Currently, the data is encrypted 
at rest and in motion in accordance with these laws and is certified by FDA.  
 
W2H Data Transfer Description  
1) Fitbit to Way to Health platform: every day, Fitbit data will be downloaded from Fitbit to 
the W2H platform. W2H code automates this transfer of data.  
2) Way to Health to Site Server: Coded Fitbit data will be converted to a CSV file and 
downloaded to a dedicated research folder on the study PI’s shared drive. No PHI will be 
involved in this transfer, only the subject’s study ID. 
All transferred and created files will be stored in a password-protected folder available only 
to study staff in the PI’s institutional shared drive. All identifiers will be removed in 
publications. 
 
Participant Recruitment Log:  
This password-protected Microsoft Excel file, saved on the PI’s institutional shared drive 
will include patient identifying information necessary for registration, enrollment, and 
follow-up. Following enrollment, this document will be used to maintain a log of enrolled 
patients. For patients who are not enrolled, patient-identifying information will be destroyed. 
A non-identifiable list of patients that were not enrolled will be retained for the purpose of 
calculating response rate.  
 
Consent Forms:  
Electronic copies of the consent forms will be stored in a password-protected folder on the 
PI’s shared drive. Participants will be emailed their signed consent form. If a participant 
turns 18 during the study, the W2H platform will notify the study team, informing that the 
participant needs to be re-consented, which will be done electronically via REDCap. 
 
Anonymization:  
Data will be extracted from the secure W2H platform for the purpose of data analysis. Any 
datasets and computer files that leave the W2H firewall will be stripped of all identifiers and 
individuals will be referred to by their study ID. The study ID will also be used on all 
analytical files. 
 
8.3 Confidentiality 
Access to the systems used for this project, including the W2H database, will be limited to 
staff who meet all relevant training requirements and are assigned to (or support) this 
project. Security procedures will be in accordance with the National Institute of Standards 
and Technology Special Publication guidelines. All staff will have completed the Human 
Subjects Protection Training.  
Electronic adherence monitoring data associated with the mobile application will be 
maintained by W2H, Inc. W2H has designed their database to comply with HIPAA 

 
  
 
 
 
28 
regulations. The site is HIPAA compliant. The data are maintained on secure servers that are 
password-protected. Please see Section 8.2 for measures taken to assure confidentiality.  
All data and records generated during this study will be kept confidential in accordance with 
institutional policies and on HIPPA subject privacy. The investigators/study team 
members/site personnel will not use such data and records for any purpose other than for 
conducting the study. 
As a way to minimize the chance of PHI (protected health information) from being 
disclosed, a unique identification code will be used for each participant. Specific keys will 
be saved in an encrypted format on the PI’s secure institutional shared drive.   
Participants will not be identified by name/PHI on any publications that result from this 
research. 
The information collected as part of this study will be kept for 7 years after study 
completion. At that time, the information collected will be destroyed or all identifiable 
information will be removed. All keys will be destroyed at this time, as well. No identifiable 
data will be used for future studies without first obtaining IRB approval. 
8.4 Regulatory and Ethical Considerations 
8.4.1 Data and Safety Monitoring Plan 
Due to the minimal risk involved in the investigation, a Data and Safety Monitoring Board 
(DSMB) is not applicable. Study data will be carefully monitored by the PI. The PI will 
provide weekly supervision to a trained clinical research coordinator who will be involved in 
data collection. The study team will monitor and track collection of all study data. The team 
will additionally track all protocol deviations and adverse events and will report these to the 
IRB, in accordance with reporting guidelines.  
8.4.2 Risk Assessment 
Study participation poses no more than minimal risk. Expected risks by procedure are as 
follows: 
Phlebotomy: The blood volume collected will be less than 5 ml per study visit (less than 10 
ml total). The blood volume removal is much less than the maximum blood volume removal 
per 8-week period recommended by OHRP (Adults < 10.5 ml/kg or 550 ml). In children, the 
maximal blood volume removal per 6 week period is 7 ml/kg. Assuming a 13 year old with 
BMI at the 85%ile would be our smallest participant, and would weigh approximately 60 kg, 
this would be a maximum of 420 ml over 6 weeks.  
There is a risk of bruising and discomfort at the venipuncture site. Blood draw may result in 
temporary discomfort from needle stick, bruising, fainting, weakness, and rarely an infection 
at the site. 
Overnight Fast: Fasting may cause hunger pangs, upset stomach, headache, or light-
headedness. For individuals on basal insulin, prolonged fasting may increase the risk of 
hypoglycemia. However, the requested fasting period is no longer than usual for most 
individuals. To reduce the risk of unrecognized hypoglycemia, participants on basal insulin 

 
  
 
 
 
29 
will be asked to check glucose on their home glucometer upon waking, prior to the fasting 
study visit. For fasting glucose < 70 mg/dL at home, participants will be asked to eat or 
drink juice, and to reschedule the study visit.  
Anthropometric measurements and pubertal status: Exam poses minimal risks.The 
anthropometric assessment involves measurements of height, weight, and circumferences. 
The exam will be performed by staff experienced in obtaining measurements in children at 
all levels of cognitive ability. The measurements are obtained in a private room. The parent 
is permitted to stay with the child if it increases their comfort with the exam. 
 
The puberty assessment will be performed by a pediatric endocrinologist in a private 
setting. The procedure will be explained to the child in advance, and the parent is permitted 
to be present if preferred by the child. The exam is performed by highly experienced 
personnel who are familiar with minimizing distress associated with the exam. 
Blood pressure measurement by auscultation: Procedure may cause temporary 
numbness/tingling in the arm 
Engagement in moderate to vigorous physical activity (MVPA): Risks for the study 
population could include physical discomfort or injury. Participants will not be asked to be 
more active than would be advised for general good health, in line with Physical Activity for 
Americans guidelines from the US Department of Health and Human Services. Participants 
will choose their own activity, including the intensity.  
There is a very small risk of participants who use insulin becoming hypoglycemic during 
physical activity. Participants will be reminded of signs and symptoms of hypoglycemia and 
asked to check glucose using home glucometer if they are concerned for hypoglycemia. 
They will be reminded how to treat hypoglycemia with fast-acting carbohydrates, or 
glucagon if necessary. However, the physical activity encouraged by this intervention is no 
greater than that recommended in usual clinical care. In addition, patients with type 2 
diabetes have a very high degree of insulin resistance and low incidence of hypoglycemia. It 
is anticipated that only a small subset of participants will be on bolus insulin (which carriers 
a higher risk of hypoglycemia), with the remainder on no insulin or basal insulin only. 
Wearing a Fitbit physical activity tracker on wrist: Participants may experience 
discomfort related to wearing the Fitbit. Participants will be provided with alternative Fitbit 
wrist bands upon request if needed due to discomfort. 
Interview and questionnaires: Potential risks include momentary embarrassment or 
discomfort as well as breach of privacy and confidentiality. Participants may decline to 
answer any question on the questionnaires or during the interviews for any reason. Every 
precaution will be taken to secure participants' personal information to ensure 
confidentiality. 
Sharing of private health information (PHI): There is the potential risk for a breach of 
confidentiality. Private health information will be collected, accessed and stored according 
to HIPAA guidelines, including the use of multilevel password protection and enforcement 
of system user privileges on the database. To limit the risk of disclosure to the minimum 
necessary to conduct the study, all direct identifiers will be removed as soon as possible and 

 
  
 
 
 
30 
codes will be substituted for personal identifiers. Records of individuals are stored with ID 
numbers and a code with no discernible personal identifiers. Code lists and data files will be 
stored in separate, secure locations. Data will be stored on institutional secure servers hosted 
and accessed on password-protected computers. To maintain confidentiality, codes will be 
used in the database, presentations and publications. 
8.4.3 Potential Benefits of Trial Participation 
Participants may benefit directly by becoming more physically active, which is 
recommended for all individuals with prediabetes or type 2 diabetes. However, there is no 
guarantee of direct benefit. 
Participants may indirectly benefit from identification of abnormalities such as diabetes 
from the hemoglobin A1c or fasting glucose. Participants may indirectly benefit from 
identification of abnormalities such as dyslipidemia from the laboratory evaluations. If 
clinically relevant abnormalities are found, the family will be notified. With the consent 
from the family, clinically relevant tests results will be shared with the subject’s primary 
care physician. Only studies performed by CLIA certified labs will be disclosed. Participants 
found to have an impaired fasting glucose or impaired glucose tolerance who are not aleady 
under care for the condition will be referred appropriately for further management and 
treatment.  
The physical activity questionnaires and dietary recall may potentially lead the 
participants/parents/guardians into awareness about making healthy lifestyle options in diet 
and exercise.  
There is also a potential indirect benefit in helping scientists and health providers further 
develop mHealth interventions using behavioral modification strategies for adolescents with 
obesity and prediabetes or type 2 diabetes.  
8.4.4 Risk-Benefit Assessment 
As the risk is no more than minimal and there is significant potential direct and indirect 
benefits, the risk-benefit balance is favorable.  
8.5 Recruitment Strategy 
The study will be publicized via flyers placed in the CHP Pediatric Endocrinology clinics. 
Potential participants will also be identified via review of pediatric endocrinology clinic 
schedules by the PI (a pediatric endocrinologist in the clinic from which participants will be 
recruited) or study staff. Potential participants will be approached in-person at scheduled 
endocrinology clinic visits. In addition, Pitt+ME will be used to obtain a list of potentially 
eligible participants based on age and diagnosis. Potential participants may be mailed a letter 
or emailed by Dr. Vajravelu to introduce the study. This email or letter will request that the 
participant or guardian respond by email or phone with their agreement to be contacted; if 
no response is made within 1 week of emailing or 2 weeks of mailing, the potential 
participant will be contacted by the investigator or a member of the research team by phone 
or by email, using an approved recruitment script. The CAYAH RESEARCH INTEREST 
FORM will also be used for recruitment purposes. This is a REDCap form with a survey 
link which will contain questions for the adolescent to answer to self-screen which are non-

 
  
 
 
 
31 
sensitive. Center for Adolescent and Young Adult Health (CAYAH) clinical staff will 
manage and distribute this survey. CAYAH clinical research staff will advertise the study to 
the teen. If the teen (age 13 or older) indicates interest in the study by viewing our study 
advertisement within the CAYAH RESEARCH INTEREST FORM, they will provide their 
contact information to the CAYAH clinical research staff who will then share it with a 
member of the study team.  
Identified subjects will be screened over the telephone or in-person by study staff. Initial 
eligibility will be determined, and with subject/parent agreement, verbal consent from the 
adult subject or parent for the minor subject to fast for the baseline visit will be obtained. 
See script on WAIVER page.  
8.6 Informed Consent/Assent and HIPAA Authorization 
8.6.1 Screening  
Information obtained via chart review will be preparatory to enrollment and will be limited 
to the minimum necessary information to determine eligibility for the main study.  
8.6.2 Main Study 
Consent/assent (as applicable) will be signed electronically via REDCap. A combined 
consent/assent-authorization document will be used, and subjects will be provided with a 
copy of the consent form. Subjects will be allowed to read the consent form and ask 
questions. Written consent/assent will be obtained from the family after all the questions and 
discussions have been completed and we are reassured that subjects comprehend the nature 
of the study, the study procedures and the risks-benefits of participation. To maximize 
subject privacy, the discussion will take place in a private location in or near PCTRC, or via 
phone. A copy of the fully signed and completed consent form will then be provided via 
email.  
To avoid coercion, we will explain that study participation is voluntary and the subject does 
not have to partake in the study in order to receive care at CHP. Decision not to participate 
or decision to withdraw after consent for study participation will not cause penalties or loss 
of any benefits otherwise entitled to the subject as a patient. In addition, the subject’s current 
and future medical care at CHP will not be affected by final decision for or against study 
participation.  
8.6.3 Re-Consent Plan for Subjects Who Reach Age of Majority 
Individuals who turn 18 while enrolled in the study will be contacted by phone and will be 
asked to provide consent/HIPAA authorization for their continued participation via 
REDCap.  
8.7 Payment to Subjects/Families 
All study procedures and expenses will not be billed to the participant but rather to the 
study’s grant. 

 
  
 
 
 
32 
8.7.1 Reimbursement for travel, parking and meals 
Reimbursement will be provided for travel/parking for study visits: $20 per study visit, 
given via Vincent. 
Incentives and compensation will be provided via Vincent as described below. 
 
 
 
8.7.2 Payment Schema  
Visit 1 Complete: Compensation: $50; Reimbursement for travel/parking: $20  
Fitbit wear during Run-In: Incentive: $1/day worn (max $14)   
Returning Fitbit for those disqualified based on MVPA or Fitbit wear: Incentive: $25 upon 
receipt of Fitbit,   
Step count goal attainment during intervention: Incentive: $1/day (max $84)   
Visit 5 Complete: Compensation: $50; Reimbursement for travel/parking: $20    
Fitbit returned: Incentive: $25   
Total: Max compensation $223 to participant; max reimbursement for travel: $40 
9 
PUBLICATION 
After completion of the study, the investigator and study team will review and analyze the 
data for reporting and publication. All published data will be de-identified. No individually 
identifiable PHI will be published. 
 
 

 
  
 
 
 
33 
 
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466-470. 
 
 
 

 
  
 
 
 
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APPENDIX 
 
 
 
 
 

 
  
 
 
 
39 
 
EXERCISE REGULATIONS QUESTIONNAIRE (BREQ-3) 
 
Age: 
_______ years 
 
 
Sex:  male 
female (please circle) 
 
WHY DO YOU ENGAGE IN EXERCISE? 
We are interested in the reasons underlying peoples’ decisions to engage or not engage in physical 
exercise. Using the scale below, please indicate to what extent each of the following items is true for 
you. Please note that there are no right or wrong answers and no trick questions. We simply want to 
know how you personally feel about exercise. Your responses will be held in confidence and only 
used for our research purposes. 
 
Not true 
Sometimes 
Very true 
 
for me 
true for me 
for me 
 
1 
It’s important to me to exercise regularly 
0 
1 
2 
3 
4 
 
  
2 
I don’t see why I should have to exercise 
0 
1 
2 
3 
4 
 
3 
I exercise because it’s fun 
0 
1 
2 
3 
4 
 
4 
I feel guilty when I don’t exercise 
0 
1 
2 
3 
4 
 
5 
I exercise because it is consistent with 
0 
1 
2 
3 
4 
 
my life goals 
 
6 
I exercise because other people say I should 
0 
1 
2 
3 
4 
 
 
7 
I value the benefits of exercise 
0 
1 
2 
3 
4 
 
 
8 
I can’t see why I should bother exercising 
0 
1 
2 
3 
4 
 
9 
I enjoy my exercise sessions 
0 
1 
2 
3 
4 
 
10 
I feel ashamed when I miss an exercise session 
0 
1 
2 
3 
4 
 
11 
I consider exercise part of my identity 
0 
1 
2 
3 
4 
 
12 
I take part in exercise because my 
0 
1 
2 
3 
4 
 
friends/family/partner say I should 
 
13 
I think it is important to make the effort to 
0 
1 
2 
3 
4 
 
exercise regularly 

 
  
 
 
 
40 
 
14 
I don’t see the point in exercising 
0 
1 
2 
3 
4 
 
 
15 
I find exercise a pleasurable activity 
0 
1 
2 
3 
4 
 
16 
I feel like a failure when I haven’t 
0 
1 
2 
3 
4 
 
exercised in a while 
  
17 
I consider exercise a fundamental part of 
0 
1 
2 
3 
4 
 
who I am 
 
18 
I exercise because others will not be  
0 
1 
2 
3 
4 
 
pleased with me if I don’t 
 
19 
I get restless if I don’t exercise regularly 
0 
1 
2 
3 
4 
 
20 
I think exercising is a waste of time 
0 
1 
2 
3 
4 
 
21 
I get pleasure and satisfaction from 
0 
1 
2 
3 
4 
 
participating in exercise 
 
22 I would feel bad about myself if I was 
0 
1 
2 
3 
4 
not making time to exercise 
 
23 I consider exercise consistent with my values 
0 
1 
2 
3 
4 
 
24 I feel under pressure from my friends/family 
0 
1 
2 
3 
4 
to exercise 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  

 
  
 
 
 
41 
 
BREQ-3 Scoring 
  
Amotivation 
2 
8 
14 
20 
  
  
  
External regulation 
6 
12 
18 
24 
  
  
  
Introjected regulation 
4 
10 
16 
22 
* 
  
  
Identified regulation 
1 
7 
13 
19 
  
  
  
Integrated regulation 
5 
11 
17 
23 
  
  
  
Intrinsic regulation 
3 
9 
15 
21 
  
 
The relative autonomy index (RAI) is a single score derived from the subscales that gives an 
index of the degree to which respondents feel self-determined. The index is obtained by 
applying a weighting to each subscale and then summing these weighted scores. In other 
words, each subscale score is multiplied by its weighting and then these weighted scores are 
summed. Higher, positive scores indicate greater relative autonomy; lower, negative scores 
indicate more controlled regulation 
For the BREQ-3 the weightings are as follows: 
  
Amotivation 
-3 
  
  
External regulation 
-2 
  
  
Introjected regulation 
-1 
  
  
Identified regulation 
+1 
  
  
Integrated regulation 
+2 
  
  
Intrinsic regulation 
+3 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Monetary Choice Questionnaire 

 
  
 
 
 
42 
 
Description: The Monetary-Choice Questionnaire is a 27-item self-administered  
questionnaire. For each item, the participant chooses between a smaller,  
immediate monetary reward and a larger, delayed monetary reward. The  
protocol is scored by calculating where the respondent’s answers place  
him/her amid reference discounting curves, where placement amid steeper  
curves indicates higher levels of impulsivity.  
Protocol: For each of the next 27 choices, please indicate which reward you would  
prefer: the smaller reward today, or the larger reward in the specified number  
of days.  
 
1. Would you prefer $54 today, or $55 in 117 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
2. Would you prefer $55 today, or $75 in 61 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
3. Would you prefer $19 today, or $25 in 53 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
4. Would you prefer $31 today, or $85 in 7 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
5. Would you prefer $14 today, or $25 in 19 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
6. Would you prefer $47 today, or $50 in 160 days?  

 
  
 
 
 
43 
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
7. Would you prefer $15 today, or $35 in 13 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
8. Would you prefer $25 today, or $60 in 14 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
9. Would you prefer $78 today, or $80 in 162 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
10. Would you prefer $40 today, or $55 in 62 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
11. Would you prefer $11 today, or $30 in 7 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
12. Would you prefer $67 today, or $75 in 119 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  

 
  
 
 
 
44 
13. Would you prefer $34 today, or $35 in 186 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
14. Would you prefer $27 today, or $50 in 21 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
15. Would you prefer $69 today, or $85 in 91 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
16. Would you prefer $49 today, or $60 in 89 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
17. Would you prefer $80 today, or $85 in 157 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
18. Would you prefer $24 today, or $35 in 29 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
19. Would you prefer $33 today, or $80 in 14 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
20. Would you prefer $28 today, or $30 in 179 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
21. Would you prefer $34 today, or $50 in 30 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  

 
  
 
 
 
45 
22. Would you prefer $25 today, or $30 in 80 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
23. Would you prefer $41 today, or $75 in 20 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
24. Would you prefer $54 today, or $60 in 111 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
25. Would you prefer $54 today, or $80 in 30 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
26. Would you prefer $22 today, or $25 in 136 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
27. Would you prefer $20 today, or $55 in 7 days?  
[ ] smaller reward today  
[ ] larger reward in the specified number of days  
 
 
 
 
 
 
 
 
 

 
  
 
 
 
46 
Scoring: A participant’s discounting curve may be calculated according to the  
following function: V = A/(1+kD)  
V is the present value of the delayed reward A at delay D, and k is the rate of  
discounting. k typically falls between 0.0 and 0.5, with smaller values  
indicating a lack of discounting and preference for delayed rewards and higher  
values indicating strong discounting and a preference for immediate rewards.  
Thus higher values of k are indicative of high levels of impulsivity.  
There are two ways of scoring the Monetary-Choice Questionnaire. The first  
involves hand scoring to get an estimate of k following the guidelines given in  
Kirby (2000). The second involves fitting a logistic regression function to  
individual responses following procedures described in Wileyto et al. (2004).  
Estimating Discounting Rate  
The following table lists the calculated k values (the degree of discounting) at  
indifference for each question (i.e., when the subjective value of the  
immediate and delayed rewards are equivalent).  
 
 

 
  
 
 
 
47 
 
An estimate of the respondent’s discounting rate can be calculated as the  
geometric mean (to avoid underweighting) of the k at indifference between the  
two questions that reflect when the respondent changes between choosing the  
delayed reward versus the immediate reward. In cases where the respondent’s  
change between preferring the delayed versus the immediate reward is not  
consistent, the two questions that are most proportional to their responses are  
chosen. If the participant always chooses the immediate reward or the delayed  
reward, the estimation of k is equal to one of the endpoints (0.25 or 0.00016).