Optimization of a mHealth Behavioral Weight Loss Intervention for Young Adults
Phase: NA
Conditions: Obesity
Sponsor: University of North Carolina, Chapel Hill

Complete Title: Optimization of a mHealth Behavioral Weight Loss Intervention for Young Adults 
 
Sponsor: University of North Carolina at Chapel Hill 
NCT number: NCT04922216 
Final Protocol Date: 20 February 2023 
 
 
University of North Carolina at Chapel Hill 
 
Study Principal Investigator: Deborah Tate, PhD. 
CB#7440 Chapel Hill, NC 27599 
919-966-7546 
email: dtate@unc.edu 
 
PROTOCOL TITLE: Optimization of a mHealth Behavioral Weight Loss Intervention for Young Adults 
Protocol Version: 1.0  
Version Date: 02/20/2023 
 
I confirm that I have read this protocol and understand it.    
 
 
 
 
 
 
Principal Investigator Signature: 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Table of Contents 
 
ABBREVIATIONS AND DEFINITIONS OF TERMS .......................................................................................... 3 
PROTOCOL SYNOPSIS .................................................................................................................................. 4 
BACKGROUND AND RATIONALE ................................................................................................................. 7 
1. STUDY OBJECTIVES .................................................................................................................................. 8 
2. INVESTIGATIONAL PLAN .......................................................................................................................... 9 
3. STUDY PROCEDURES ............................................................................................................................. 13 
4. STATISTICAL CONSIDERATIONS ............................................................................................................. 15 
5. SAFETY MANAGEMENT ......................................................................................................................... 16 
6. DATA COLLECTION AND MANAGEMENT ............................................................................................... 20 
7. RECRUITMENT, CONSENT, AND RETENTION STRATEGY ........................................................................ 20 
8. PLANS FOR PUBLICATION ...................................................................................................................... 22 
9. REFERENCES .......................................................................................................................................... 22 
APPENDIX .................................................................................................................................................. 27 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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ABBREVIATIONS AND DEFINITIONS OF TERMS 
 
Abbreviation 
Definition 
ACM 
Adopt Core Measure 
ADOPT 
Accumulating Data to Optimally Predict obesity Treatment Core Measures 
AGILE 
Adaptive Goals and Interventions for Lifestyle Enhancement 
API 
Application Program Interface  
BCT 
Behavior Change Technique 
BMI 
Body Mass Index 
CES-D 
Center for Epidemiological Studies Depression Scale  
DSMB 
Data Safety Monitoring Board  
DSM-IV-TR 
Diagnostic and Statistical Manual of Mental Disorders 
EARLY 
Early Adult Reduction of weight through LifestYle intervention  
ELM 
Elaboration Likelihood Model  
IMPACT 
IMproving Physical Activity after Cancer Treatment 
IRB 
Institutional Review Board 
JITAI 
Just-in-Time Adaptive Intervention 
JIT 
Just-in-Time 
MOST 
Multiphase Optimization Strategy 
MVPA 
Moderate to Vigorous Physical Activity 
NCI 
National Cancer Institute 
NIDDK 
National Institute of Diabetes and Digestive and Kidney Diseases  
NIH 
National Institutes of Health 
OCT 
Office of Clinical Trials  
PAR-Q 
Physical Activity Readiness Questionnaire  
PAQ 
Paffenbarger Physical Activity Questionnaire  
REDCap 
Research Electronic Data Capture  
RCT 
Randomized Clinical Trial 
RF 
Red Food 
SDT 
Self-Determination Theory  
SNAP 
Studies of Novel Approaches to Prevention 
TraCS 
North Carolina Translational and Clinical Sciences  
YA 
Young Adult 
 
 
 
 
 
 
 
 

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PROTOCOL SYNOPSIS 
 
Study Title 
Optimization of a mHealth Behavioral Weight Loss Intervention for Young Adults 
Funder 
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 
Clinical Phase 
NA 
Study Rationale 
Young adults (YAs) are underrepresented in behavioral health and weight loss 
interventions and express interest in flexible, highly tailored programs. Mobile 
interventions are a lower-burden, scalable approach to providing behavioral support. Just-
in-time-adaptive interventions (JITAI) promise to deliver the “right” support at the “right” 
time using real-time data from smartphones and sensors. JITAIs hold promise for 
promoting behavior changes needed for weight loss (eating, activity, and self-weighing); 
however, there is limited evidence for selecting treatment components and levels of 
adaptation that are needed for success. Results of this trial will be used to create an 
optimized JITAI for weight loss in young adults. 
Study Objective(s) 
Primary  
• 
To build an optimized JITAI consisting of the set of intervention components that yield 
the greatest improvement in weight change among young adults at 6 months 
Secondary 
• 
To conduct mediation analyses to test the relationships between the intervention 
components and hypothesized proximal mediators (self-regulation, competence, 
relatedness, relevance, autonomy) and more distal behavioral mediators (dietary 
intake, physical activity, and daily self-weighting) 
• 
To conduct exploratory analyses of program engagement 
Test Article(s) 
(If Applicable) 
All participants will receive a core 6-month weight loss intervention that includes evidence-
based lessons, behavioral skills training, and daily weighing. 
Study Design 
 
The AGILE (Adaptive Goals and Interventions for Lifestyle Enhancement) trial utilizes the 
Multiphase Optimization Strategy (MOST) framework and a 25 full factorial experimental 
trial to test the efficacy of 5 intervention components, each with two levels, on weight loss 
among 608 YAs recruited from around the United States. All participants will receive a core 
6-month weight loss intervention that includes evidence-based lessons, behavioral skills 
training, and daily weighing. With the goal of determining if greater adaptation leads to 
greater weight loss, we will test standard versus adaptive options of 5 additional 
intervention components: 1) diet monitoring approach (standard vs. simplified), 2) 
adaptive physical activity goals (weekly vs. daily), 3) decision points for message timing 
(fixed vs. adaptive), 4) decision rules for message content (standard vs. adaptive), and 5) 
message choice (no vs. yes). Assessments will occur at baseline, 3 months, and 6 months.   
Subject Population 
 
Inclusion Criteria 
1. Age 18-39 
2. Body mass index (BMI) of 25-45 kg/m2 
3. English speaking and writing 

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4. Own a smartphone with a data and text messaging plan 
5. Willing to be randomized to any levels of the factors 
Exclusion Criteria 
1. Type 1 diabetes or currently receiving medical treatment for Type 2 diabetes.  
2. Other health problems which may influence the ability to walk for physical activity 
or be associated with unintentional weight change, including cancer treatment 
within the past 5 years or tuberculosis.  
3. Report a heart condition, chest pain during periods of activity or rest, or loss of 
consciousness on the Physical Activity Readiness Questionnaire (PAR-Q; items 1-4).  
4. Lost 10 or more pounds (and kept it off) in the last 6 months. 
5. Currently taking weight loss medications.  
6. Report a past diagnosis of or receiving treatment for a DSM-IV-TR eating disorder 
(anorexia nervosa or bulimia nervosa). 
7. Currently pregnant, pregnant within the past 6 months, or planning to become 
pregnant within the next 6 months. 
8. Hospitalization for depression or other psychiatric disorder within the past 12 
months. History of psychotic disorder or bipolar disorder.  
9. Another member of the household is a participant or staff member on this trial. 
10. Currently participating in a weight loss, nutrition or physical activity study or 
program or other study that would interfere with this study. 
Number Of Subjects  
 
608 
Study Duration 
Each subject’s participation will last 6 months. 
The entire study is expected to last five years. 
Study Phases 
Screening 
Study Treatment 
Follow-Up   
(1) Screening: screening for eligibility and obtaining consent and (2) Baseline assessment 
(3) Intervention: study intervention/experimental treatment. (4) Follow-up assessment will 
occur at 3 and 6 months. 
Efficacy Evaluations 
Results of the optimization experiment will be used to determine which combination of 
components and component levels contribute most significantly to mean weight loss 
(primary) and achievement of 5% weight loss (secondary) at 6 months. 
Pharmacokinetic 
Evaluations 
NA 
Safety Evaluations 
All medical events and safety data will be assessed at assessment points or when interim 
events are reported by participants using a standard form used in our ongoing NIH funded 
trials. 
Statistical And Analytic 
Plan 
The primary outcome analysis will use mixed effects models to test for differences in 
weight by intervention components across time (baseline, 3, and 6 months).24 Effects will 
be modeled as component x time interactions with the 6-month outcome as the primary 
endpoint. All higher-order interactions between components will be modeled. Additional 
models will evaluate the likelihood of reaching 5% weight loss at 6 months. 
DATA AND SAFETY 
MONITORING PLAN 
Data safety management in this trial is intended to achieve 4 objectives: 1) to minimize the 
occurrence of adverse effects, especially those related to intervention; 2) to effectively 

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manage adverse events as they relate to the study; 3) to identify when the interventions 
should be suspended because of concerns for participant safety; and 4) to determine when 
interventions may be resumed after having been suspended. The Principal Investigator 
(Tate) will have primary responsibility for the safety of participants as it relates to the study 
protocol, which must be approved by the UNC IRB prior to study initiation. In addition, the 
North Carolina Translational and Clinical Sciences (TraCS) Institute Data Safety Monitoring 
Board (DSMB) is responsible for reviewing data from clinical trials approved by the UNC 
Biomedical IRB. Because the risks to subjects participating in this phase of this study are 
expected to be low, we do not anticipate the need for a formal Data Safety Monitoring 
Board.  The research team will provide continuous monitoring of participant safety and 
periodic reporting to the IRB as required, including any Unanticipated Problems/Severe 
Adverse Events that may have occurred during the study. If risk or complexity is significant, 
the UNC Office of Human Research Ethics may require additional reporting or alternative 
data and safety monitoring. Data safety and monitoring activities continue until all 
participants have completed treatment and until all participants have been followed to the 
point at which study related adverse events would likely no longer be encountered. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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BACKGROUND AND RATIONALE  
 
1.1 
Introduction 
Obesity has reached epidemic proportions in the United States and is recognized as a major cause of morbidity 
and mortality. There is an increased risk of weight gain during young adulthood, 1,2 and 40% of young adults 
(YAs) aged 20-39 years are living with obesity.3 Obesity in this age group is associated with increased risk of 
hypertension, hyperlipidemia, diabetes, and cancer.2,4 Despite these risks, YAs are underrepresented in 
behavioral weight loss programs 5–7 and few evidence-based programs have been designed specifically for YAs.7–
10  
1.2 
Name and Description of Investigational Intervention  
The AGILE (Adaptive Goals and Interventions for Lifestyle Enhancement) trial is a 25 full factorial experimental 
trial testing the efficacy of 5 intervention components (factors), each with two levels, to identify component 
levels that contribute to greater weight loss among YAs. To do so, we will randomize 608 YAs with overweight or 
obesity to receive one level of each of the 5 intervention components, in addition to a core mobile-delivered 
behavioral weight loss program.  
 
1.3 
Relevant Literature and Data 
Almost all young adults in the United States own a smartphone (97%) and mobile phone ownership in this age 
group is widespread across all racial/ethnic, education, income, and residential groups.11 Our formative work 
with YAs (n=137) with overweight or obesity indicates that at least 60% are interested in technology-delivered 
programs, and that YAs would like programs that are individualized, lower intensity, flexible, and minimize time 
burden.12 Commonly cited barriers to weight management among YAs include not having enough motivation or 
time and not getting enough exercise.12 Exclusively mobile treatments have produced weight losses of 1-6 kgs 
over 6 months,9,13–15 demonstrating that mobile-delivered programs have the potential to increase the access, 
reach, and impact of weight management.  
To date, the most effective digital obesity interventions have relied on predetermined, fixed schedules of 
treatment contact, typically providing email counselor feedback once per week and/or text messages delivered 
on a pre-specified schedule to all participants.16 With the widespread use of smartphones and connected health 
devices that seamlessly collect daily participant health data, mobile programs are able to provide more tailored 
intervention messages, such as varying message content based on current or recent behavioral data (e.g., 
activity minutes so far that day at time of message; number of days a goal was met in the past week).17–19 The 
availability of participants’ real-time digital health data allows for highly individualized intervention and real-
time support while minimizing burden to the participant. Rather than relying on largely pre-determined 
messaging schedules that evaluate a limited number of variables, emerging research has focused on improving 
the ability to send the “right message” at the “right time.” These interventions, called “just-in-time adaptive 
interventions,” (JITAIs) have the potential to improve upon outcomes by offering highly adaptive, personalized 
feedback on behavior when needed.20 Examples of JITAIs have included providing just-in-time skills support for 
reducing alcohol intake,21 in-the-moment messaging to disrupt sedentary behavior,22 and using data to predict 
dietary lapses and provide supportive interventions before they occur.23 Despite widespread availability of 
digital health devices and the emerging use of JITAIs, most JITAIs to date have been short in duration (12 weeks 
or less) and have targeted single behaviors versus multiple. In turn, there remains limited theoretical, empirical, 
and practical evidence to inform interventions.20   

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To improve weight, multiple daily behavioral targets are needed, including dietary intake, physical activity, and 
self-weighing. Thus, for weight loss, automated mobile interventions must be able to provide tailored, adaptive 
messaging that considers participants’ behavioral contexts across all weight-related behaviors and sends the 
“right” message for the “right” behavior and at the “right” time. However, the level of tailoring provided in 
messaging exists along a continuum, and it is not yet known how much tailoring and adaptation is needed to be 
effective. Moreover, there are other components of automated interventions that could increase engagement 
or effectiveness, including adaptive goal setting and alternative methods of self-monitoring, but few studies 
have examined alternatives among YAs. We conducted a pilot 12-week remotely delivered JITAI that delivered 
up to 4 messages per day to young adults in a mobile behavioral weight loss program and found that 
participants viewed 68% of messages, and viewing messages was associated with increased likelihood of 
reaching daily behavioral goals.18 While this was promising, many questions remain about how adaptive and 
personalized a JITAI needs to be to be effective for weight loss in YAs.   
 
1. STUDY OBJECTIVES 
 
To address evidence gaps regarding JITAIs, the objective of this trial is to simultaneously test innovative or 
adaptive intervention components, compared to their standard counterparts, that are expected to increase 
weight loss among YAs. This is an optimization trial, conducted as part of the Multiphase Optimization Strategy 
(MOST) framework.24 Guided by Self-Determination Theory (SDT),25 the trial will test 5 components that are 
designed to promote positive changes in SDT constructs: 1) diet self-monitoring approach (standard vs. 
simplified), 2) adaptive physical activity goals (weekly vs. daily adaptive), 3) decision points for message timing 
(fixed vs. adaptive), 4) decision rules for message content (standard vs. adaptive), and 5) message choice (no vs. 
yes).     
Aim 1: Build an optimized JITAI consisting of the set of intervention components (and component levels) that 
yield the greatest improvement in weight change among young adults at 6 months. We will use a highly 
efficient experimental design, powered to detect both main effects and all two-way interactions between 
components. Results of the optimization experiment will be used to determine which combination of 
components and component levels contribute significantly to mean weight loss at 6 months. The proportion 
achieving 5% weight loss is our second-level decision-making criterion in cases of equal weight losses. 
 
Aim 2: Conduct mediation analyses to test the relationships between the intervention components and 
hypothesized mediators. Mediators to be tested include the proximal theoretical mediators of component 
effects (self-regulation, competence, relatedness, relevance, autonomy) and the more distal behavioral 
mediators (dietary intake, physical activity, and daily self-weighing).  
 
Aim 3: Conduct moderation analyses. The primary moderator to be tested is intervention engagement including 
self-monitoring engagement (weighing frequency, diet monitoring, tracker wear) and app engagement (app 
views, lessons, feedback, intervention message views). Exploratory moderators include gender, race/ethnicity, 
and initial BMI status. 
 
The active component levels determined from this study will be used to create an optimized just-in-time 
adaptive intervention that will be tested in a separate RCT to examine weight losses at 6 months with follow-up 
at 12 months. If the proposed aims are achieved, we will expand our understanding of ways to improve public 
health with just-in-time support that accounts for individual variability in lifestyle and environmental contexts. 
Our work advances the science of JITAI development–answering key questions about adaptation and tailoring–
and is guided by a conceptual model, which will further understanding of how JITAI components and mobile 
interventions may operate via key theoretical mediators. Our study will be one of the first to systematically 

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optimize a fully automated mobile JITAI. These aims are critical initial steps for overcoming the challenge of 
providing and evaluating broad-reach public health interventions that are more precisely tailored to the specific 
characteristics of individuals. 
 
2. INVESTIGATIONAL PLAN  
 
Study Design 
Rationale for Component Selection  
We selected components to evaluate for an optimized JITAI based on empirical and theory-based support 
(Figure 1). Factors 1 and 2 test two different methods of dietary tracking and two methods of physical activity 
goal adaptation, respectively. Factors 3-5 directly affect the just-in-time (JIT) messages being delivered to 
participants, specifically the “when” and “what” of the JITAI. Guided by the JITAI framework, in which the goal is 
to intervene at the right time and with the right type of treatment, this study evaluates different methods for 
choosing decision points, decision rules, and intervention options.26 Decision points are the times at which a 
decision is made about whether and how to intervene and can occur one or several times per day or week. At 
these times, decision rules (a set of tailoring variables and their values) are evaluated to determine which 
intervention option (type of treatment or message) to deliver, if any.20,26 In this study, all intervention options 
will be brief messages delivered via smartphone application; therefore, hereafter intervention options will be 
referred to as intervention messages.   
Rationale of Factors/Intervention Components  
Dietary Self-Monitoring Approach (Standard versus Simplified). Detailed calorie tracking is the standard form of 
dietary tracking in standard behavioral weight loss interventions,27,28 but adherence to calorie tracking declines 
over time29,30 and participants who stop tracking generally do not achieve clinically significant weight losses. 
Calorie tracking can be time intensive, and adherence may decline if the perceived cost of tracking does not 
outweigh its benefit.31 Given that self-monitoring is a central feature of self-regulation,32 there is a need to test 
other methods of dietary self-monitoring that might reduce burden and improve dietary self-regulation. We 
have conducted three pilot trials that have shown that a simplified Traffic Light approach,33 in which participants 
track only their “red” (high-calorie) foods, is feasible among YAs and has similar adherence and weight losses at 
6 months to detailed calorie tracking.17,18,34 However, few, if any, fully powered trials have directly compared 
detailed calorie tracking (“Standard”) with a simplified red food tracking approach (“Simplified”).   
Adaptive Activity Goals (Weekly Adaptive versus Daily Adaptive). Adaptive intervention components, such as 
adaptive physical activity goals, may support more precise shaping of an individual’s behaviors, improve 
adherence, reduce treatment mismatch, and increase competence.35 Perceived competence, or an individual’s 
feelings about their capabilities with respect to a behavior, has been shown to be an important predictor of 
weight loss,36 and adoption and maintenance of physical activity.37 The current standard for physical activity goal 
progression, in the context of weight loss, is to gradually increase goals with a fixed progression over time, 
regardless of an individual’s previous goal achievement, which may not be optimal for promoting behavior 
change38 or supporting an individual’s competence related to physical activity. Adaptive goal setting, in which 
the goals are set based on participants’ personal activity levels, is emerging as an alternative to fixed progression 
goals,38,39 with evidence that interventions with step goals that adapted on a daily basis improved steps/day 
compared to static step goals.38–40 However, it is unclear whether this daily frequency of goal adaptation (“Daily 
Adaptive”) is necessary for a daily activity goal and whether it is more effective than adapting goals on a weekly 
basis (“Weekly Adaptive”).   

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Decision Time Points (Fixed versus Adaptive). In a JITAI framework, decision points are the times at which a 
decision is made about whether and how to intervene and can occur one or several times per day or per week. 
To date, many mobile interventions have relied on pre-specified, fixed messaging times (e.g., sending a text 
message at 5 pre-determined times per week).17,41,42 However, it is possible to collect and use behavioral and 
contextual data to determine the “right time” to deliver a message, such as JITAIs that have sent messages when 
participants are at risk of a behavioral lapse.23 This requires evaluating participant data throughout a longer time 
interval instead of pre-determining the message times. This additional level of tailoring may increase program 
and message relevance. The Elaboration Likelihood Model (ELM)43 of message processing posits that individuals 
show greater elaboration or thinking about a given circumstance when they are more motivated, find the 
content interesting and personally relevant, and when they can process it. 44 Prior intervention studies have 
shown that increased perceptions of relevance of the program and program messaging increased intervention 
effects.45,46 However, it is not known if using participant behavioral data to determine decision points 
(“Adaptive”) will increase the relevance of the messages, and in turn improve outcomes compared to 
predetermined decision points (“Fixed”).   
 
Decision Rules (Standard versus Adaptive). Decision rules are the sets of variables used to evaluate which 
intervention message a participant should receive and can include one or many tailoring variables. Delivering 
the “right message” should enhance feelings of relatedness or being respected and understood by the program, 
which is a critical aspect of autonomy support in self-determination theory (SDT).47 Human-computer interaction 
research on mobile phone identity defines relatedness as the degree to which individuals feel connected when 
considering how they relate to their mobile phone and may also reflect the extent to which an app or mobile 
intervention provides support.48 Within the context of a mobile program that delivers brief messages, the level 
of relatedness and personalization in message content is dependent upon the amount of behavioral and 
contextual data that is used to determine which message to deliver (i.e., the number of tailoring variables in a 
decision rule). It is currently not known whether increasing the complexity and adaptation of decision rules 
(“Adaptive”) will enhance the effects of JIT support compared to simpler decision rules (“Standard”).  
 
Participant Message Choice (Choice versus No Choice). SDT posits that an individual will adopt and maintain 
more autonomous and self-determined motivation in an autonomy supportive context.25,49 Autonomy 
supportive behavioral strategies include providing individuals multiple options for change, a lack of forced 
behavior, and allowing individuals to share their perspectives.50 Formative work among YAs with overweight or 
obesity emphasizes the desire for autonomy, flexibility, and choice in behavioral weight loss programs12 and 
indicate that an approach that offers choice has potential for promoting clinically meaningful weight loss.7 While 
the option to have more frequent choices and control over the types of messages or intervention support 
received has been less studied in weight management, it has shown promise with other health behaviors.51 It is 
currently not known whether providing choice in the types of messages received will enhance the effects of JIT 
support and improve weight outcomes.  
Core Intervention Overview  
All participants will receive a core intervention modified from concepts of the Diabetes Prevention Program52 
and adapted specifically for YAs.53 The intervention is based on social cognitive and control theories focused on 
improving self-regulation via self-monitoring coupled with weekly tailored feedback. Participants will receive a 
Bluetooth-enabled scale (Fitbit Aria Air) and activity tracker (Fitbit) in the mail, followed by an introductory 
videochat session with an interventionist. In this session they will receive information relevant to their 
participation in the program, including an overview of how to use the AGILE app (for both iOS and Android) and 
other required apps (Fitbit; Traffic Light Log for participants assigned to it as described below), how to self-

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monitor to achieve their daily goals (eating, activity, and self-weighing), and other information relevant to the 
conditions to which they have been randomized.   
 
Activity, weight, and dietary data are synced to study servers and available in the AGILE app on pages that 
display participants’ daily and overall progress towards their goals. The AGILE app also includes 24 behavioral 
lessons that are unlocked each week of the program. These include behavioral strategies with specific 
instruction on core cognitive and behavioral skills (i.e., goal setting, self-monitoring, problem solving, 
overcoming barriers, reaching out for social support, and cognitive restructuring). A Feedback page in the app 
displays weekly tailored feedback that summarizes participant progress based on weight change, self-monitoring 
frequency, and weekly goal achievement. Adaptive JIT intervention messages related to the components below 
are delivered 1-2 times per day.   
Overview of Intervention Components and Messaging System  
To equate frequency of message delivery across all conditions, all participants will receive 10 messages per week 
(1-2 messages per day), between 8:00AM and 9:00PM. Participants will receive a smartphone notification when 
a new message is displayed in the app. The messages are displayed on the Home page of the AGILE app and 
remain there until they expire at midnight. Participants can like or dislike messages with a thumbs up/thumbs 
down. Messages pertain to one of three behaviors (eating, activity, self-weighing) and are chosen based on 
decision rules that evaluate participant behavioral data at the time the rules are evaluated. A pre-determined 
schedule (which varies by some of the components as described below) assigns 1-2 behaviors that will be 
messaged on each program day, with unique decision rules or each behavior. Most intervention messages 
include one or two of the following message types: feedback on outcome, feedback with a data point, directive 
action, nondirective action, encouragement/motivation, and social comparison. Other intervention messages 
are short interactive action planning tools that guide the participant to develop a plan for one of their behavioral 
goals.   
Description of Intervention Components (Factors)  
Dietary Self-Monitoring Approach. Participants in this trial will be randomly assigned to a Standard or Simplified 
approach. Participants assigned to Standard tracking will receive a calorie goal ranging from 1425-2850 per day 
based on their sex and starting weight and will track their calories using the Fitbit app, which transmits to the 
study servers via the Fitbit API. The Simplified “red” food (RF) approach focuses on reducing overall caloric 
intake by tracking and reducing intake of RFs only; there are no specific goals for green and yellow foods. 
Participants assigned to Simplified tracking will receive a daily RF limit that ranges from 3-6 RFs per day and will 
track their RFs in a native Traffic Light Log app created for this study. They are not required to track their green 
and yellow foods but can do so if they choose. Participants will be able to see their current and historical dietary 
progress on the Eating page of the AGILE app, which will display RFs for the Simplified group and calories for the 
Standard group.  
 
Adaptive Activity Goals. Participants will be randomized to receive weekly adaptive or daily adaptive daily 
physical activity goals. In the weekly adaptive group, participants will receive a new daily activity goal at the 
beginning of each program week and the daily goal remains constant throughout the week. In the daily adaptive 
group, participants will receive a new daily activity goal at the beginning of each day. Participants will use their 
Fitbit activity trackers to track their “active minutes” (AM), which are equivalent to moderate-to-vigorous 
physical activity minutes. At the beginning of the program, participants will receive a daily AM goal of 10- 20 AM 
per day based on their baseline level of activity during the run-in period. After the first program week or day (for 
weekly and daily adaptive, respectively), AM goal adaptations will be driven by an algorithm that sets the new 
goal as the 4th highest day of AM (55th percentile) in the prior 9 days.39,54  

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Decision Points. Participants in this trial will be randomly assigned to fixed timing or adaptive timing. Fixed 
timing runs from a schedule that specifies the exact time (1-2 times per day) that the decision rules are run, 
though the times vary each day. In adaptive timing, the decision rules run hourly and participant data 
determines when the message should be sent (limited to 1-2 per day, mirroring the fixed schedule). In adaptive 
timing, messages can be delivered in closer proximity to when a behavior is completed (< 1 hour; to immediately 
reinforce goal achievement), or, if their usual behavior patterns suggest that receiving the message at the 
current time would not be ideal, the decision rules can continue to run and send a more appropriate message 
later in the day (e.g., not sending an activity reminder message at 9am if the participant does not usually 
exercise until after 7pm). This is done with additional variables in the adaptive timing decision rules that take 
into account participants’ usual behavioral patterns.   
 
Decision Rules. Participants will be randomly assigned to standard decision rules or adaptive decision rules. In 
standard, the decision rules include a limited set of variables representing behavioral progress from the current 
and prior day. In addition, participants are eligible to receive an interactive action planning tool if they are in a 2-
day lapse, meaning they have not met their goal the current or prior day. In adaptive decision rules, the rules 
mirror the fixed rules, with additional behavioral and contextual tailoring variables that allow for consideration 
of past progress on the given behavior, other behaviors, and recent weight change, such that a message about a 
different behavior can be sent if that might be more appropriate for the participant. Also, participants in 
adaptive decision rules are not eligible to receive an interactive action planning tool unless they are in a 
behavioral lapse of at least 4 days (compared to 2 in standard). These additional tailoring variables and 
adjustments are designed to provide flexibility in the messages that can be sent to participants. Rather than 
requiring that the system send a message about the behavior that was assigned for that day, the comprehensive 
rules allow the system to, when needed, send a message on another behavior that would be more appropriate. 
As an example, a fixed decision rule for eating may evaluate yesterday’s dietary goal achievement, the current 
day’s dietary tracking, and current dietary intake compared to their goal. If the participant has tracked nothing, 
they will receive a message prompting them to track their foods. In adaptive decision rules, the rules will also 
evaluate recent goal progress and weight change, such that a participant who regularly tracks their food intake 
and is losing weight would not receive this reminder message; instead the system would choose a message 
about a different behavior. However, these messages would be delivered if this pattern repeated, or if the 
weight trajectory was no longer favorable.   
 
Message Choice. Participants will be randomly assigned to choice or no choice, which differ in two ways. First, all 
messages have a like/dislike rating. In the choice group, participant like/dislike ratings change the probability 
that they will receive similar message types in the future based on their ratings. As described above, all 
messages were designed and coded based on the message type (feedback on outcome, feedback with a data 
point, directive action, nondirective action, encouragement/motivation, or social comparison). When a 
participant likes or dislikes a message, those data are used to increase or decrease, respectively, the probability 
that they will receive a similar message type for that given behavior in the future. In the no choice group all 
message types are equally likely to be chosen. Secondly, participants in the choice group are given more options 
and autonomy when completing the interactive action planning tools. In the no choice group, when an action 
planning tool is displayed on the Home page, the participant can select the ‘Take Action’ button, at which point 
they can view one available action planning activity. In the choice group, participants have two actions available, 
‘Take Action’ or ‘No Thanks.’ If they select ‘No Thanks,’ the app does not provide them with any activity or 
messaging. If they select ‘Take Action,’ they are given two action planning activity options and can choose 
between them.   
Study Population 

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Individuals will be eligible if they meet the following criteria: age 18-39; body mass index (BMI) of 25-45 kg/m2; 
English-speaking and writing; own a smartphone (iOS or Android) with a data and texting plan; and willing to be 
randomized to any levels of the factors. Exclusion criteria include being currently pregnant, pregnant within the 
past 6 months, or planning to become pregnant within the next 6 months; type 1 diabetes or receiving medical 
treatment for type 2 diabetes; a heart condition, chest pain, or other health problems that influence the ability 
to follow physical activity recommendations; lost 10 pounds or more in the past 6 months, history of weight loss 
surgery, or currently taking weight loss medications; report a past diagnosis of or receiving treatment for an 
eating disorder; hospitalization for depression or another psychiatric disorder in the past 12 months or history of 
bipolar or other psychotic disorder; another member of the household is a participant or staff member on this 
trial; currently participating in another weight loss, nutrition, or physical activity study or program. Individuals 
that reported joint problems, some prescription medications, or current treatment for hypertension or 
hyperlipidemia will be required to obtain written physician consent to participate (Appendix).   
The trial is registered on clinicaltrials.gov (NCT04922216) and was approved by the Institutional Review Board at 
the University of North Carolina at Chapel Hill on July 26, 2022.  
 
3. STUDY PROCEDURES  
 
Data Collection 
All study participants will complete objective weight measurements, two dietary recalls, and self-administered 
online surveys at baseline and 6 months (post-intervention). At 3 months, only psychosocial measures and 
medical events will be collected via online survey and telephone. Participants will receive $50, $25, and $75 for 
completing baseline, 3, and 6-month assessments, respectively. Online surveys will include measures of 
theoretical mediators, other psychosocial constructs, and process measures. We will send emails and texts 
prompting participants to complete assessments, with follow-up emails and phone calls to non-respondents, as 
necessary. Measures and timing are described below. 
 
Measures 
Where possible, we are measuring constructs using validated and recommended scales from the ADOPT Core 
Measures Project 58-60 (indicated below with ACM), an NIH-supported initiative to permit collaboration, pooling 
across obesity interventions, and to search for predictors of heterogeneity in response to treatment.  
 
Primary outcome (Weight): Weight will be objectively measured at the participant’s home at all time points. We 
will instruct participants to weigh themselves in light clothing, without shoes, on the wireless scales at each 
assessment time point. The participant will weigh themselves 3 times in succession to indicate the assessment 
weight on the date requested. A subset of participants local to our facilities (up to n=40) will be invited at 
baseline to complete in-person weight measurements to further validate smart scale weights with clinic weight. 
 
Other Anthropometric and Key Behavioral Mediators (collected at baseline, 3 months, and 6 months) 
• 
Height (Baseline only). Participants will self-report height using an item from the Behavioral Risk Factor 
Surveillance System (BRFSS), 61 adapted for the Health Information and National Trends Survey. 62 
• 
Dietary Intake (Baseline, 6 months). Changes in dietary intake will be assessed using the NCIs Automated 
Self-Administered 24-hour Recall (ASA-24). Participants will complete two self-reported recalls; one 
weekday and one weekend day. The 24 recall is a validated method of measuring diet. 63 Using two recalls 
permits adjustment of estimates for intraindividual variation and is superior to administering one recall.  

Page 14 of 30 
 
• 
Self-reported Physical Activity (ACM). Physical activity will be assessed with the Paffenbarger Physical 
Activity Questionnaire (PAQ) 56 which assesses leisure-time activity. The PAQ provides an estimate of 
minutes per week of moderate-to-vigorous intensity, and calories/week of light (5 kcal/min), medium (7.5 
kcal/min), and high (10 kcal/min) intensity activities. PAQ changes have been predictive of weight change. 
• 
Sedentary Activity (ACM). Given the increasing recognition of the effects of sedentary activity independent 
of physical activity, we will use the Sedentary Behavior Questionnaire from CARDIA/EARLY trials. 64 
 
Proposed Theoretical Mediators (collected at baseline, 3, and 6 months) 
• 
Autonomy Support (3 and 6 months only). We will adapt items from the Health Care Climate Questionnaire, 
which is a measure of how the participant perceives support from a healthcare provider, to measure 
autonomy support from the program.65 The scale includes 15 items rated on a scale of 1 (strongly disagree) 
to 7 (strongly agree) (e.g., “I feel that [the program] has provided me choices and options.”) 
• 
Competence for Diet and Physical Activity (ACM). The Perceived Competence for Scale includes 4 items that 
measure perceived competence for diet and 4 items for physical activity.66 Items are rated on a 7-point of 1 
(not at all true) to 7 (very true) (e.g., “I feel confident in my ability to maintain a healthy diet.”) 
• 
Relatedness (3 and 6 months only). Relatedness will be measured with 3 items adapted from the 8-item 
Relatedness subscale of the Basic Need Satisfaction at Work Scale.49,67 Examples include “The messages 
demonstrate caring about me as a person” and are scored on a Likert scale from 1 (strongly disagree) to 7 
(strongly agree). 
• 
Message Relevance (3 and 6 months only).  Perceived message relevance will be measured with two items 
used in our previous work 68 and adapted from previous studies of tailored messages. 45,69 Participants were 
asked to rate how strongly they disagree or agree with the statements about messages being “written 
personally for me” and “applied to my life.” Responses are on a 5-point scale from 1 (strongly disagree) to 5 
(strongly agree). 
• 
Treatment Self-Regulation (ACM). The Treatment Self-Regulation Questionnaire (TSRQ) will be used to 
assess autonomous and controlled motivation for making changes in diet (15 items) and physical activity (15 
items). 70 Examples item: “Because I feel that I want to take responsibility for my own health” answered on a 
scale of 1 (not at all true) to 7 (very true).  
 
Other Psychosocial and Behavioral Measures (collected at baseline, 3, and 6 months) 
• 
Quality of Life. All participants will complete the CDC Health-Related Quality of Life measure (referred to as 
“Healthy Days Measures”). 136 This 4-item questionnaire reliable, valid, and responsive to change.  
• 
Depression (ACM). Depressive symptoms have been associated with changes in weight, diet, and physical 
activity and will be assessed with the Center for Epidemiological Studies Depression Scale (CES-D). 137 
• 
Weight Control Strategies (ACM). Participants will be asked about frequency of use of 20 weight control 
strategies such as “ate only when I was hungry” with a scale used in the EARLY trials. 138  
• 
Hunger, Restraint, Disinhibition. The Three Factor Eating Questionnaire (TFEQ) is a 51-item self-report 
instrument assessing three factors of dietary restraint, disinhibition and hunger. 139 
• 
Perceived Stress (ACM). The Perceived Stress Scale is a 10-item measure that assesses stressful situations in 
the last month.140 
• 
Binge Eating (ACM). Participants will complete the revised Questionnaire on Eating and Weight Patterns 
(QEWP-5) to assess frequency of binge eating, loss of control, and compensatory behaviors. 141  
 
Process and Adherence Measures (collected over 6 months) 
• 
Dietary Monitoring. Objective self-monitoring of dietary intake will be assessed using data from the 
smartphone application food log (for simplified conditions) and Fitbit food log (for calorie conditions). 
• 
PA monitoring. Objective self-monitoring of PA will be assessed via the Fitbit tracker data. Using the Fitbit 
API, the study will collect data on the number of days the Fitbit was worn (steps > 500/day). 95 
• 
Self-weighing. Self-weighing habits will be objectively measured via the smart scales to calculate percent of 
days weighed, and average self-weighing days per week. 

Page 15 of 30 
 
• 
Other Engagement Measures. We will examine app views as mean, median, and monthly percentage, to 
account for the skewing of app data. App views are similar to website logins, which have been associated 
with weight loss. 48,50,82,83 We will examine number of lessons accessed and feedback messages viewed. 
• 
Program Acceptability and Satisfaction. Participants will complete a post-treatment program evaluation 
about intervention perceptions and experiences, using questions from our previous studies.   
 
Other Measures (collected at baseline, 3, and 6 months, unless otherwise indicated) 
• 
Medical events and symptoms will be collected at 3 and 6 months in a scheduled telephone call.  Responses 
will be reviewed to determine if a Serious Adverse Events form is required.  
• 
Demographics. At baseline, standard demographic information will be collected 
• 
Medical history, Medication use. Self-report of both prescription and non-prescription medications. 
• 
Smoking, alcohol use. Smoking and alcohol use will be assessed at each time point. 
 
4. STATISTICAL CONSIDERATIONS  
 
Sample Size and Power  
We defined a 1-kg weight change as more than a minimal effect of any given component on overall weight loss. 
We estimated standard deviation based on a prior cell phone-delivered intervention for YAs that found a 
standard deviation of 6.9 kg for a weight change difference of 2.2 kg between groups;9 therefore, we 
conservatively estimated a standard deviation of 4 times our 1-kg weight change estimate. Assuming a type 1 
error rate of 5% and a standard deviation of 4 kg, reaching 80% power would require 505 total participants. 
Assuming a 17% attrition rate at 6 months based on our previous studies with YAs and rounding up to a whole 
number per condition results in a total of 608 participants needed. Thus, each of the two levels of each 
component will have 304 randomly assigned participants, with 19 participants in each of the 32 conditions.   
Statistical Analysis  
Aim 1 Analysis. To test for differences in weight change across time by the five intervention components, we will 
use mixed effects models on an intention-to-treat data set, with effects modeled as component × time 
interactions and the 6-month outcome as the primary endpoint. We will run separate models for (a) mean weight 
change and (b) the proportion of participants achieving 5% weight loss, the latter constituting a second-level 
decision-making criterion in cases where effects for mean weight change are equal. All higher-order interactions 
between components will also be modeled (e.g., adaptive physical activity goals × message choice × time 
interaction). The ability to test all higher-order interactions between intervention components, without reducing 
power, is a key advantage of the factorial experiment, as this is not possible in a traditional multi-component 
RCT. We will be using effect (-1,1) coding rather than dummy (0,1) coding, which keeps any covariances among 
main effects and interactions to a minimum. Once we have identified important effects in the initial set of 
models, we will establish parsimonious prediction models in which coefficients that do not contribute 
significantly to mean weight loss (or proportion achieving 5% weight loss) will be set to zero. 
 
Aim 2 Analysis. In Aim 2 we will conduct mediation analyses to test the relationships between the intervention 
components and hypothesized mediators, thus refining the underlying conceptual model. In contrast to 
mediation analyses conducted on data from an RCT, we will be able to fit models specifying which intervention 
component is mediated by each hypothesized mediator. For example, while we hypothesize that autonomy will 
mediate the relationship between the intervention component, message choice, and weight, it is possible that 
other mediators—e.g., relatedness—will explain this relationship. It is also possible that autonomy will mediate 
the relationship between other intervention components (e.g., decision points for message timing) and weight. 
This step will provide important information for improving our understanding of how the intervention 
components work and for revising our conceptual model. Mediators to be tested include the proximal theoretical 

Page 16 of 30 
 
mediators of component effects (self-regulation, competence, relatedness, relevance, and autonomy) and the 
more distal behavioral mediators (daily self-weighing, dietary intake, and physical activity). We will test the 
mediation effects for significance using the general approach described in MacKinnon. 
 
Aim 3 Exploratory Analyses. In Aim 3 we will conduct moderation analyses to test differential response to 
intervention components. The primary moderator to be tested is intervention engagement, which will include 
percentage of messages viewed, number of days of diet self-monitoring, number of days of physical activity 
tracking, number of days of self-weighing, and lessons viewed. Exploratory moderators will include gender, race 
and ethnicity, and initial BMI status. Results will provide important information for future research aimed at 
developing mobile interventions tailored and optimized for differing levels of engagement and subgroup 
membership. 
 
Handling Missing Data 
While every effort will be made to avoid missing data with proper tracking efforts, we do expect some missing 
data due to attrition and nonresponse. Under the MAR assumption, we will use the suite of multiple imputation 
tools in Stata (v.15 or greater) to (1) conduct a detailed analysis of the missing data, beginning with an 
examination of the number and proportion of missing values among the variables of interest; (2) identify 
potential auxiliary variables that are either correlated with a missing variable/(s) or are believed to be associated 
with missingness; (3) use MI IMPUTE, with at least 20 imputations, to derive the imputed data set; (4) rerun 
analyses on the imputed data set; and (5) verify the stability of MAR inference by conducting sensitivity analyses 
which modify the imputation step to accommodate potentially nonignorable missing-data mechanisms. This 
process will be followed separately for each estimation model (i.e., mean weight change from baseline to 6 
months, proportion achieving 5% weight loss).  
Strengths and Limitations.  
One limitation is the potential for contamination, as YAs may be connected to others via social media and learn 
about the study from common sources. This is mitigated by the fact that the intervention components of 
interest are uniquely tailored to individuals and the intervention is delivered via individual smartphones. 
Although participants will be limited to those with smartphone and internet access, prevalence of smartphone 
use is highest among young adults (96% of 18-29-year-olds, 92% of 30-49-year-olds), and the app will be 
available to iPhone and Android users, thereby extending generalizability. While our study requires extensive 
programming, our preliminary work, in which we have created complex algorithms and decision rules for 
multiple libraries of intervention messages (400+ for Nudge pilot, 1000+ for IMPACT study tailored feedback), 
demonstrates our ability to create infrastructure and content for this project. Our proposal has several strengths 
that outweigh its limitations. It targets an understudied population of YAs at risk for weight gain. Our work 
advances the science of JITAI development–answering key questions about adaptation and tailoring–and is 
guided by a conceptual model, which will further our understanding of how JITAI components and mobile 
interventions may operate via key theoretical mediators. We use ADOPT Core Measures to enable collaboration, 
data pooling, and identification of predictors of heterogeneity in treatment response. Moreover, our delivery via 
a smartphone app increases potential for widespread reach and adoption around the country. Our study builds 
upon our prior work focused on YAs and will be one of the first to systematically optimize a fully automated 
remotely delivered JITAI. Our work will elucidate appropriate and feasible mobile intervention strategies among 
YAs and holds promise for promoting weight loss among YAs that may decrease their risks for morbidity and 
mortality. 
5. SAFETY MANAGEMENT  
 
Data safety management in this trial is intended to achieve 4 objectives: 1) to minimize the occurrence of 
adverse effects, especially those related to the intervention; 2) to effectively manage adverse events as they 
relate to the study; 3) to identify when the interventions should be suspended because of concerns for 

Page 17 of 30 
 
participant safety; and 4) to determine when interventions may be resumed after having been suspended. The 
Principal Investigator (Tate) will have primary responsibility for the safety of participants as it relates to the 
study protocol, which must be approved by the UNC IRB prior to study initiation. In addition, the North Carolina 
Translational and Clinical Sciences (TraCS) Institute Data Safety Monitoring Board (DSMB) is responsible for 
reviewing data from clinical trials approved by the UNC Biomedical IRB. Because the risks to subjects 
participating in this phase of this study are expected to be low, we do not anticipate the need for a formal Data 
Safety Monitoring Board.  The research team will provide continuous monitoring of participant safety and 
periodic reporting to the IRB as required, including any Unanticipated Problems/Severe Adverse Events that may 
have occurred during the study. If risk or complexity is significant, the UNC Office of Human Research Ethics may 
require additional reporting or alternative data and safety monitoring. Data safety and monitoring activities 
continue until all participants have completed treatment and until all participants have been followed to the 
point at which study related adverse events would likely no longer be encountered. 
 
Participant Safety 
The risks to human subjects in this study, including psychological and physical risks, are judged to be minimal. 
The anticipated benefits are great, insofar as the results will be used to determine if mobile-delivered behavior 
change strategies are effective for obesity risk reduction in a sample of young adults.  
Psychological Risks: We expect risk of harm, including psychosocial and emotional distress or breach of 
confidentiality, as a result of this study to be rare or infrequent. Most communication during the intervention 
period will take place via telephone, the smartphone app, direct emails, or text messages—to deliver 
intervention components, conduct assessments, or remind participants to complete questionnaires. We do not 
anticipate any risks of harm as a result of these communications. As part of the intervention, participants may 
be asked about personal factors related to their diet, physical activity, and weight. Participants are not required 
to share this information and can elect not to share sensitive and confidential information with the study. 
Participants will be encouraged to contact the Principal Investigator if they feel they have incurred any 
emotional distress as a result of study participation. As this is a voluntary study, a participant is free to exit at 
any point if discomfort should occur. Individuals scoring >16 on the Center for Epidemiological Studies 
Depression Scale (CES-D) at baseline, 3-, or 6-month assessments (indicating levels of depressive symptoms that 
might benefit from follow up with a health care provider) will be given a letter explaining the survey and 
providing information and referral to resources (Appendix). 
Physical Risks: There are no major physical risks associated with the weight loss intervention or data collection. 
There may be some risk to increasing physical activity, including, but not limited to, injuries to the muscles, 
ligaments, tendons and joints of the body. Other risks include abnormal blood pressure, fainting, dizziness, 
disorders of heart rhythm, exacerbation of exercise-induced asthma symptoms, and very rare instances of heart 
attack, stroke, or even death. Although increasing physical activity can have great benefits, participants may also 
experience some general fatigue, sore muscles or joints from exercising. Because several studies indicate that 
walking is the preferred exercise type for most adult populations, the study focuses on encouraging moderate-
intensity walking. To help ensure safety, the study will follow guidelines and safety recommendations for 
physical activity set forth by the American College of Sports Medicine. Educational materials during the course of 
the intervention will educate participants on exercise safety and inform them of precautions in starting an 
exercise program and how to manage increasing amounts of exercise. Messages will encourage participants to 
start at a reasonable frequency and intensity of exercise based on their current level and to increase their 
exercise gradually. The informed consent will also clearly communicate the potential physical risks related to 
starting an exercise program and increasing physical activity. Participation is fully voluntary, and we will ask 
participants to report any problems to the study researchers. There is a rare, but possible, risk of extreme 
dieting in this intervention. However, the intervention recommendations are geared toward simplified dietary 
changes and should be of very low risk. The greatest concerns are that participants may engage in unsafe dietary 
practices, lose weight more quickly or to lower levels than recommended, or develop untoward psychological 

Page 18 of 30 
 
reactions. However, prior weight loss studies indicate that participants in these programs increase their use of 
healthy weight control practices and decrease their use of unhealthy practices.  
Risk to privacy and/or confidentiality. We expect a breach of confidentiality to be rare or infrequent. Most 
communication during the study period will take place via telephone, direct emails, text messages, or through 
the smartphone app—either to deliver questions, conduct assessments, or remind participants to complete 
questionnaires. We do not anticipate any risks of harm as a result of these communications; however, there is 
always a possibility that their scale data, tracker data, or activity in the app will be intercepted.  
Adequacy of Protection Against Risks  
a. Informed Consent and Assent  
Recruitment and Informed Consent: Several different efforts will be used to recruit potential participants and 
obtain informed consent from those eligible participants. The research team is responsible for assuring that the 
UNC IRB has approved the study protocol and has reviewed and approved the informed consent document. 
Written approval must be obtained from the IRB before the study can begin. Once an individual has been 
deemed potentially eligible to participate through online and telephone screening, study staff will provide more 
study details and describe the concept of random assignment, the 32 study conditions, and assessment 
procedures over the telephone. Individuals who remain interested will receive an email directing them to a 
unique and secure REDCap link to an online informed consent. After clicking on the link, they will be directed 
through a series of screens that present the informed consent document. The online informed consent records 
will be retained, and recruitment of participants will be done by adhering to HIPAA regulations. Accrual reports 
will list enrolled participants and excluded participants throughout the stages of the research. This routine 
monitoring allows for early identification and resolution of potential problems during the recruitment phase. 
The anticipated recruitment duration is 30 months. All key personnel have attended the required courses on 
human subject protection and HIPAA regulations, and certificates of IRB training completion are on file with the 
University of North Carolina.  
b. Protections Against Risk  
Protections against Psychological Risks: As noted above, participants are not required to share this information 
and can elect not to share sensitive and confidential information with the study. Participants will be encouraged 
to contact the Principal Investigator if they feel they have incurred any emotional distress as a result of study 
participation. As this is a voluntary study, a participant is free to exit at any point if discomfort should occur. 
Individuals scoring >16 on the Center for Epidemiological Studies Depression Scale (CES-D) at baseline, 3- or 6-
month assessments (indicating levels of depressive symptoms that might benefit from follow up with a health 
care provider) will be given a letter explaining the survey and providing information and referral to resources 
(Appendix).  
Protections against Physical Risks: To ensure medical readiness to begin physical activity, participants will 
complete a physical activity readiness questionnaire (PAR-Q). The PAR-Q assesses for the following medical 
conditions: heart problems, chest pains, faintness or dizzy spells, high blood pressure, bone or joint problems 
such as arthritis that has been or could be aggravated by exercise, prescription medication use, and other 
medical reasons why exercise would not be advisable. Participants endorsing yes to any items 1-4 on the PAR-Q 
(experience of heart problems, frequent chest pains, faintness or dizziness, bone or joint problems) will be 
excluded from the study. We also will monitor any major musculoskeletal problems that develop during the 
intervention (e.g. broken bones) using a medical events questionnaire at 3 and 6 months and will determine 
whether these appear related to our study. Participants who develop musculoskeletal problems or other health 
problems that may affect safe participation will be instructed to stop exercising until the problem resolves and 
their physician approves resumption of physical activity.  
All participants will be advised about safe weight loss practices including dietary change and increasing physical 
activity at their initial study visit. Participants will be advised to gradually increase their physical activity and to 

Page 19 of 30 
 
use walking as a primary form of activity and will be taught that the appropriate rate of weight loss is 1 to 2 
pounds per week. In addition, we will carefully monitor changes in weight during our trial. We will collect 
information at each assessment timepoint on hospitalizations for any psychiatric problem, including depression 
and eating disorders. We will track weight changes using smart scale weights and will identify any individual who 
loses more than 20% of their body weight, has a BMI ≤ 18.5 kg/m2 at any point during the program, or loses 
more than 15 pounds in any month during the trial. We will have a telephone call with these participants within 
2 weeks, discuss our concerns with them, and make referrals if appropriate. If there is no improvement in 
weight status, the participant will be unable to continue to participate in the intervention.  
Protections to Ensure Confidentiality of Participants: All data records related to a participant’s involvement in 
this research study will be stored in a locked file cabinet and/or in encrypted files on servers that adhere to the 
University policy on storage and transmission of sensitive data. Participant identity on these records will be 
indicated by an ID number, and the information linking these numbers with participant identity will be kept 
separate from the research records. In addition, all research databases will have password-controlled access, 
and this will be controlled by critical staff. Participants will be encouraged to contact the Principal Investigators if 
they feel they have incurred any emotional distress as a result of study participation. As this is a voluntary study, 
a participant is free to exit at any point if discomfort should occur.  
The Fitbit API will be used to access data from the participant’s scale, activity tracker, and Fitbit app. During the 
consent process, participants will consent for the data from their specific device IDs to be accessed by our study. 
They will need to enter their Fitbit username and password during the app setup process to allow Fitbit data to 
be sent to our study server. The study smartphone app uses a Standard OAuth 2.0 security model for logging in 
to Fitbit. The study uses temporary access tokens that are stored only on the user's device and is not stored on 
our servers. Therefore, Fitbit usernames and passwords will not be stored in any way with this study. Instead, 
the weight and tracker data will be connected to participants by their unique study ID that they will also enter 
during the app setup process. Data are transmitted on secure servers that adhere to University policy on 
Sensitive Data. The risk of breach of confidentiality over the Fitbit websites will be partly subject to each 
individual’s comfort in sharing information in their individual profile. To further minimize the risk of breach of 
confidentiality, all participant activities on the Fitbit websites will be voluntary. Consent forms will also clearly 
communicate the risk of this type of disclosure to participants.  
Removal of Patients from Protocol. Participants will be removed from the protocol should they experience 
greater than minimal risk as detailed above. Participants will be reminded that their participation is voluntary 
and that they may withdraw from the study at any time without consequence by contacting the Principal 
Investigator. In addition, we expect that pregnancies will occur. We will stop all intervention activities for 
anyone who becomes pregnant.  
 
Potential Benefits of the Proposed Research to Research Participants and Others  
Intervention participants are expected to improve dietary behaviors, physical activity, and may lose modest to 
clinically significant amounts of weight, ultimately reducing their risk of developing type 2 diabetes, 
cardiovascular disease, and other chronic diseases. In addition, the results of this study could be used to develop 
an optimized weight loss intervention to be tested in a similar population and, if effective, could be 
generalizable to a larger population of young adults. If successful, an automated program that uses a 
smartphone and other relatively low-cost digital technologies that is optimized for effective treatment 
components could be disseminated in a larger-scale program, thus benefiting a greater number of young 
adults.   
Importance of the Knowledge to be Gained   
There are currently few trials that have used a strictly mobile weight loss intervention that have resulted in 
clinically significant weight loss in young adults. Should this trial prove effective, it will have great public health 
relevance, as young adulthood is a critical period for excessive weight gain that is associated with future 

Page 20 of 30 
 
comorbidities, including type 2 diabetes, hypertension, and cardiovascular disease. Results from this trial have 
the potential to lead a new generation of scalable, low-cost technology-based intervention strategies that could 
significantly enhance the adoption of healthy behaviors and prevent or treat overweight and obesity. The risks 
to study participants are minimal, whereas the potential benefits for improved health are significant.  
 
6. DATA COLLECTION AND MANAGEMENT  
 
The rigorous system used for participant tracking, data collection, management, and quality control procedures 
for our previous projects (SNAP: U01HL090864; IMPACT: R01CA204965) will be modified for this study. All data 
will be entered using the REDCap computer-assisted program that has built-in validation checks for range, data 
type, and completeness. All measurements will undergo consistency and outlier checks, compared with raw 
data, and edited as required. REDCap includes detailed audit logs that document any database changes, and we 
will document protocols for cleaning data. 
 
Participants will provide physical data (objective weight and self-reported height), self-reported questionnaire 
data online, and self-reported physical activity data over the telephone specifically for research purposes. All 
self-report online data will be collected using secure REDCap surveys. A subset of participants local to the UNC 
clinic will have objective height and weight data taken in the clinic in order to validate home scale weights. Food 
log data from the study smartphone application will be transmitted to study servers, and weight and activity 
data from Fitbit be will transmitted to study servers. Identifiable information collected in online surveys will 
include the participant’s name, address, phone numbers, and date of birth.  
Risk to privacy and/or confidentiality 
We expect a breach of confidentiality to be rare or infrequent. Most communication during the study period will 
take place via telephone, direct emails, text messages, or through the smartphone app—either to deliver 
questions, conduct assessments, or remind participants to complete questionnaires. We do not anticipate any 
risks of harm as a result of these communications; however, there is always a possibility that their scale data, 
tracker data, or activity in the app will be intercepted.  
 
7. RECRUITMENT, CONSENT, AND RETENTION STRATEGY 
 
Recruitment 
Young adults will be recruited using a multi-pronged approach including: 1) postings on social media including 
Facebook, Instagram, and Twitter; 2) emails through listservs comprised of the target audience; 3) 
advertisements on select media accessed by young adults, including television, radio, Spotify.  
Using Facebook, Instagram, and other social media to recruit has been shown to be an efficient and cost-
effective manner of recruiting diverse participant samples, both in the literature and in our prior research, 
including our pilot study. We will purchase advertisements and “Boosted Posts” with recruitment information 
about the study that will link to the recruitment website and online screening survey. The ads and posts will be 
targeted specifically to reach adults between the ages of 18 and 39 that live in the United States and can also be 
targeted specifically to reach only men and minorities, if needed. We have used similar strategies to recruit 599 
young adults in the Chapel Hill, NC and Providence, RI area for a weight gain prevention study (NIH 
R01HL090864) as well as recruitment of participants across a larger geographic area (U.S.) for a mobile-delivered 
physical activity promotion trial among 280 young adult cancer survivors (NIH R01CA204965). 

Page 21 of 30 
 
All recruitment efforts will direct participants to a study website with a more detailed description of the 
research study and FAQs about participating in research. Interested individuals will click through to a REDCap 
web screening survey to determine initial eligibility. Those who are preliminarily eligible will be contacted by 
trained study staff and will undergo additional phone screening. Following an approach we have used in the 
past, eligible and interested individuals will receive an email directing them to a unique REDCap link to an online 
informed consent. After providing consent, participants will be instructed on procedures for 1) completing one 
weekday and one weekend self-reported 24-hour dietary recall, 2) completing baseline online questionnaires, 
and 3) completing their baseline weight measurement using a Bluetooth-connected scale. The Fitbit scale and 
activity tracker will be mailed to the participant. After completion of baseline assessments, the participant will 
be randomized to one level of each of the 5 factors, or one of the 32 conditions (Table 1). The participant will be 
scheduled for a one-on-one telephone/videochat session during which they will be informed of condition 
assignments, assisted with downloading of the study smartphone app, and questions about getting started will 
be answered.  
Inclusion of Women and Minorities 
All individuals will be eligible for enrollment independent of sex/gender and race/ethnicity. As women are 
generally over-represented in weight control studies, we do not anticipate having inadequate representation by 
women. To be able to test for differences in the treatment effect by sex/gender, we may need to specifically 
target recruitment of men. Our research group has had success in recruiting higher percentages of men by using 
pictures of men in Facebook/social media advertisements, and by using terms such as “wellness” and “health” 
instead of “weight loss.” Therefore, we will use these strategies to increase our recruitment of men if we are 
under our targets. 
We will specifically aim to recruit participants representing a wide variety of racial/ethnic backgrounds. In past 
studies, we have successfully recruited minority populations through direct mailings to targeted heads of 
households, identification of minority groups through social media platforms and community groups, and 
tailored recruitment materials. In the pilot Nudge study (N = 52), we recruited a sample, almost entirely through 
Facebook, that was 34.6% minority (17.3% Black or African American, 7.7% multiple races, 5.8% Asian, 3.8% 
other; 5.8% Hispanic or Latino). For the current trial we will aim to recruit at least 30% non-white participants, 
with specific emphasis on black and Hispanic populations, given the burden of overweight in these groups. 
Because we will be opening recruitment to eligible individuals across the United States, we anticipate that with a 
targeted recruitment plan we will be able to meet goals for inclusion of minorities. 
Initially, no groups will be excluded or limited based on sex/gender, race, and or/ethnicity. However, if the 
enrollment targets for minority participants are proceeding slower than expected compared to white 
participants, we may limit enrollment of white participants in order to raise the percentage of minority 
participants closer to our targets.  
Retention 
Participant retention strategies have been used effectively in our other studies. A systematic protocol will be 
followed to minimize dropouts. Top priority will be for assessment visits. At baseline, names and addresses of 
several friends and family members who can be contacted are obtained for use if we lose touch with the 
participant. The study provides incentives for completing the follow-up assessments to offset any time costs and 
to promote retention ($50 for completing the baseline assessment, $25 for the abbreviated 3-month 
assessment, and $75 for completing the 6-month assessment). For each assessment visit, we will send 
participants an email that will include a link to online questionnaires with an expected completion date as well 
as a scheduled date and time to step on their scale. Missed weights and/or questionnaires will be immediately 
followed up by phone and rescheduled.  

Page 22 of 30 
 
In addition to our assessment retention protocol, participants who complete all three assessments will be able 
to keep their Fitbit and scale at the end of the study, which we will believe will also encourage retention to 
assessment measures. In addition, regardless of condition assignments, the study smartphone application is 
designed to enhance engagement by sending notifications one or several times per day, including reminders to 
use the app or self-monitor, among other behavior change techniques. This method of prompting engagement 
will also serve to remind participants of their participation in the study, and thus will serve as cues for 
completing study assessments. We will review participant engagement weekly and will use structured protocols 
for promoting engagement with the intention of also promoting retention. 
8. PLANS FOR PUBLICATION 
 
 
As Principal Investigator of this grant application and clinical trial, Dr. Tate will comply with the clinical trial 
information dissemination expectations of the NIH policy to register and submit summary results at 
ClinicalTrials.gov. Karen Hatley, Project Manager, will be responsible for handling ClinicalTrials.gov requirements 
for this project under the Dr. Tate's oversight. Consistent with the terms and conditions of NIH funding, we will 
ensure the submission and updating of registration and results information for this clinical trial in the 
timeframes established by the Final Rule. Registration and results reporting in ClinicalTrials.gov will be 
completed within the following timeframes:   
• 
Registration of the trial at ClinicalTrials.gov no later than 21 days after enrolling the first participant  
• 
All submitted information will be updated at least once a year.  
• 
Any apparent errors, deficiencies, and/or inconsistencies identified by NIH as part of the quality control 
review process and any other errors identified will be addressed by the responsible party.  
• 
Corrections to submitted information will be made within 15 days for registration information and 25 days 
for results information.  
• 
Trial results will be submitted no later than one year after the primary completion date.  
Informed Consent Documents for the clinical trial will include a specific statement relating to posting of clinical 
trial information at ClinicalTrials.gov. The UNC IRB has template language explaining that the study will be 
posted on ClinicalTrials.gov that investigators are required to include in the consent document for the trial.  
As PI, Dr. Tate will work closely with the UNC-CH Office of Clinical Trials (OCT), which serves as the university’s 
internal PRS. The OCT has responsibility for ensuring that clinical trial registration and reporting occurs in 
compliance with NIH policies. The OCT has support staff to facilitate the process of registration and results 
reporting to ClinicalTrials.gov, and our team will work closely with them to register this trial and to submit 
summary results to the website in a timely manner, in keeping within the required timeframes. Once data 
collection is complete, our research team will work to prepare and submit trial results no later than one year 
after the primary completion date.  
 
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Page 27 of 30 
 
 
APPENDIX 
 
Table 1. Experimental conditions in the 25 factorial trial  
Condition 
Core 
Diet Self-
Monitoring 
Approach 
Adaptive 
Activity 
Goals 
Decision 
Points for 
Message 
Timing 
Decision 
Rules for 
Message 
Content 
Message 
Choice 
1 
Yes 
Standard 
Daily 
Fixed 
Standard 
No 
2 
Yes 
Standard 
Daily 
Fixed 
Standard 
Yes 
3 
Yes 
Standard 
Daily 
Fixed 
Adaptive 
No 
4 
Yes 
Standard 
Daily 
Fixed 
Adaptive 
Yes 
5 
Yes 
Standard 
Daily 
Adaptive 
Standard 
No 
6 
Yes 
Standard 
Daily 
Adaptive 
Standard 
Yes 
7 
Yes 
Standard 
Daily 
Adaptive 
Adaptive 
No 
8 
Yes 
Standard 
Daily 
Adaptive 
Adaptive 
Yes 
9 
Yes 
Standard 
Weekly 
Fixed 
Standard 
No 
10 
Yes 
Standard 
Weekly 
Fixed 
Standard 
Yes 
11 
Yes 
Standard 
Weekly 
Fixed 
Adaptive 
No 
12 
Yes 
Standard 
Weekly 
Fixed 
Adaptive 
Yes 
13 
Yes 
Standard 
Weekly 
Adaptive 
Standard 
No 
14 
Yes 
Standard 
Weekly 
Adaptive 
Standard 
Yes 
15 
Yes 
Standard 
Weekly 
Adaptive 
Adaptive 
No 
16 
Yes 
Standard 
Weekly 
Adaptive 
Adaptive 
Yes 
17 
Yes 
Simplified 
Daily 
Fixed 
Standard 
No 
18 
Yes 
Simplified 
Daily 
Fixed 
Standard 
Yes 
19 
Yes 
Simplified 
Daily 
Fixed 
Adaptive 
No 
20 
Yes 
Simplified 
Daily 
Fixed 
Adaptive 
Yes 
21 
Yes 
Simplified 
Daily 
Adaptive 
Standard 
No 
22 
Yes 
Simplified 
Daily 
Adaptive 
Standard 
Yes 
23 
Yes 
Simplified 
Daily 
Adaptive 
Adaptive 
No 
24 
Yes 
Simplified 
Daily 
Adaptive 
Adaptive 
Yes 
25 
Yes 
Simplified 
Weekly 
Fixed 
Standard 
No 
26 
Yes 
Simplified 
Weekly 
Fixed 
Standard 
Yes 
27 
Yes 
Simplified 
Weekly 
Fixed 
Adaptive 
No 
28 
Yes 
Simplified 
Weekly 
Fixed 
Adaptive 
Yes 
29 
Yes 
Simplified 
Weekly 
Adaptive 
Standard 
No 
30 
Yes 
Simplified 
Weekly 
Adaptive 
Standard 
Yes 
31 
Yes 
Simplified 
Weekly 
Adaptive 
Adaptive 
No 
32 
Yes 
Simplified 
Weekly 
Adaptive 
Adaptive 
Yes 
 
 
 

Page 28 of 30 
 
 
Weight Research 
1700 Martin Luther King Jr. Blvd, Room 136   T 919.966.5852 
Chapel Hill, NC 27599-7294                                  F 919.966.7827 
Date: 
 
  
 
Dear 
, 
 
Thank you for being a participant in the AGILE study! We take seriously our obligation to protect the health and 
confidentiality of all participants in our research study. You are receiving this letter because the responses you gave to 
questions on the Moods Questionnaire indicate that you may be feeling down and if this feeling lasts for any length of 
time it may indicate symptoms of depression. These survey results provide important information about symptoms, but 
only your physician can diagnose actual depression. Consider talking with your doctor about your symptoms, or use the 
resources below to get more information or identify a qualified provider. These results do not prevent you from 
participating in AGILE, but we want to make you aware of these results so that you can make an informed decision about 
seeing a physician or other provider to get checked. 
 
If you are interested in learning more about the symptoms, causes and/or treatment of depression, you may find it 
helpful to take a look at the following online resources: 
 
• The National Institute of Mental Health has a page dedicated to the topic of depression 
(http://www.nimh.nih.gov/health/topics/depression/index.shtml). On this page, you can find more 
information about depression, signs and symptoms of depression, information about treatment, and 
how to locate service providers near you. 
• NC Health Info (https://www.nchealthinfo.org/) is a joint project of UNC-Chapel Hill and the National 
Library of Medicine that allows users to find local health resources in North Carolina. In the upper right 
box labeled Quick Start, you will find pull-down menus for both “Topic” and “Location.” If you choose 
“Depression” from the Topic menu and either your home county or city, you will be shown a list of 
websites that specifically address mental health providers that work in your area. 
• The North Carolina Psychologists Association’s website (http://www.ncpsychology.org/) has information 
available under the “General Public” tab. In this area, you will find a list of Frequently Asked Questions 
along with a tool that can help you find a licensed psychologist near you. 
• Mental Health America offers a screening tool (https://screening.mhanational.org/screening-tools/ 
depression/) whose results you can share with a health care provider. On this site, you can find 
information about depression and locate some local resources that can provide referrals to 
professionals, services or support groups in your area. 
• Contact your Human Resources Director or Benefits Coordinator at your workplace to inquire about a 
depression-related Employee Assistance Program. 
 
If you have any questions, please email the AGILE research team at agilestudy@unc.edu or call us at (919) 966-5852, and 
we will return your call within 24 hours during regular business days. 
 
Sincerely, 
Deborah Tate, PhD 
Principal Investigator 
 
 

Page 29 of 30 
 
 
 
PHYSICIAN CONSENT TO PARTICIPATE IN A DIET AND EXERCISE  
PROGRAM AT UNC-CHAPEL HILL 
 
 
TO: 
 
RETURN TO: 
 
Physician’s Name 
 
Karen Hatley, MPH, RD 
 
 
UNC Weight Research Program 
 
 
Lineberger Comprehensive Cancer Center 
 
 
1700 Martin Luther King Jr. Blvd., CB 7294 
 
Address 
Chapel Hill, NC 27514 
 
 
 
 
 
Telephone: (919) 966-5853 
 
City 
State 
Zip 
FAX:          (919) 843-6663 
Email:        agilestudy@unc.edu 
 
 
 
 
(          ) 
 
 
Telephone Number 
  
 
Your patient ______________________________ has asked to participate in a weight loss program conducted 
by the University of North Carolina at Chapel Hill that is specifically designed for young adults to help them 
adopt healthier eating and activity habits and learn effective ways to manage their weight.  
 
The 6-month program is delivered using a study smartphone app and digital health tools. All participants will 
receive a standard program using the study smartphone app, which will have weekly lessons and feedback on 
progress. Each participant will receive a combination of tools to help them keep track of their diet and meet diet 
and physical activity goals. The combination of tools will vary the method of dietary monitoring, physical 
activity goals, and personalization of study messages in the app for each study participant. 
 
 All participants will receive the following intervention: 
1. A diet program that will reduce calories and involves dietary monitoring on a smartphone app. 
2. A physical activity program that will be primarily home-based.  The exercise will gradually be progressed to 
150 – 300 minutes per week (depending on starting activity levels) with activities akin to brisk walking.   
3. Behavioral modification techniques for changing eating and exercise behaviors. 
4. Digital tools including a smartphone app, Bluetooth-connected digital scale, and Fitbit activity tracker. 
 
Please indicate below if this program seems appropriate for your patient or if you see any 
contraindications for his/her participation (please check the appropriate box below). 
 
I know of no contraindications to this patient participating in any of the above components of the 
program. 
 
I feel that this program would not be appropriate for this patient for the following reason(s): 
 
_______________________________________________________________________________________ 
 
_______________________________________________________________________________________ 
 
 
 
 
Signature of Physician 
 

Page 30 of 30 
 
 
Inclusion Criteria: 
1. Age 18-39. 
2. Body Mass Index (BMI) of 25-45 kg/m2. 
3. English-speaking, reading, and writing. 
4. Own a smartphone with a data and texting plan. 
5. Willing to wear a Fitbit activity tracker and to be randomized to any levels of the factors. 
 
Exclusion Criteria: 
1.  Type 1 diabetes or currently receiving medical treatment for Type 2 diabetes. 
2. Other health problems which may influence the ability to walk for physical activity or be associated with 
unintentional weight change, including cancer treatment within the past 5 years or tuberculosis. 
3. Report a heart condition, chest pain during periods of activity or rest, or loss of consciousness on the 
Physical Activity Readiness Questionnaire (PAR-Q; items 1-4). 
4. Lost 10 or more pounds (and kept it off) in the last 6 months. 
5. Currently taking weight loss medications. 
6. Report a past diagnosis of or receiving treatment for a DSM-IV-TR eating disorder (anorexia nervosa or 
bulimia nervosa). 
7. Currently pregnant, pregnant within the past 6 months, or planning to become pregnant within the next 6 
months. 
8. Hospitalization for depression or other psychiatric disorder within the past 12 months. History of 
psychotic disorder or bipolar disorder. 
9. Another member of the household is a participant or staff member on this trial. 
10. Currently participating in a weight loss, nutrition or physical activity study or program or other study 
that would interfere with this study. 
No exclusion criteria shall be based on race, ethnicity, or gender.