Charge: Optimizing a Standalone Text Messaging-Based Weight Loss Intervention
Phase: NA
Conditions: Weight Loss, Obesity
Sponsor: Duke University

Charge: A Text Messaging-based Weight Loss Intervention
STUDY PROTOCOL,  INFORMED CONSENT
 & STATISTICAL ANALYSIS PLAN 
NCT03254940
Document date: January 21, 2021

STUDY PROTOCOL 

  
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Charge Full Research Protcocol 
Optimal iOTA (Charge): Optimizing a standalone text messaging-based weight loss intervention 
 
 
Overall study aim: This will be a 12-month experimental trial among 448 adults with obesity to 
determine which stand-alone text messaging intervention components produce a meaningful 
contribution to 6-month weight change. We operationalize meaningful text messaging 
components as those having an effect size of > .15, using the Pellegrini et al. definition.34 We 
will use the multiphase optimization strategy (MOST)1 to help us assemble multicomponent 
interventions comprised only of components that meaningfully affect our chosen outcomes.  
All participants will receive a core 6-month weight loss texting intervention (based on our 
iOTA approach) that includes tailored behavior change goals, interactive self-monitoring, 
automated feedback, and skills training. We will use a full factorial design to randomize 
participants to experimental conditions that reflect the texting intervention components: 
motivational messaging (self- vs 
expert-generated), texting frequency (daily vs weekly), reminders (one reminder v. multiple 
reminders), feedback type (summary score v. specific feedback) and comparison unit (to self v. 
to a group of people). The full factorial design is power efficient, logistically feasible (because 
we manipulate conditions using technology) and will allow us to examine the most important 
main and interaction effects among components. 
Our primary outcome will be absolute change in weight from baseline to 6 months. We 
will estimate the main effects and 10 pairwise interactions of each of the five components on the 
outcome at each follow-up time point using a linear mixed effects model. The model will include 
fixed effects for: time point (baseline, 3- or 6-months), component (motivational messaging, 
frequency, reminders, feedback type, and comparison unit), pairwise interactions of each 
component and the time-by-component and time-by-pairwise interactions.  
 
Background: More than 69% of U.S. adults are currently overweight or obese; 35% are 
obese.2,3 Obesity continues to increase for all men and for Black and Hispanic women.4 6 The 
rapid rise in severe obesity is especially troubling. Obesity heightens risk for hypertension, type 
2 diabetes, dyslipidemia, and insulin resistance.7 10 It also drives premature mortality and U.S. 
health system spending.11 13 Traditional behavioral weight loss treatments 
 usually including 
frequent interactions with a trained 
counselor and regular self-monitoring of diet/exercise 
 produces 7-10% weight loss after 6-12 
months.14,15 However, the intensive nature of these interventions constrains their widespread 
dissemination. We need innovative approaches to deliver effective weight loss interventions to 
Americans with obesity. 
We are interested in learning how to optimally design a standalone texting intervention 
that maximizes weight loss outcomes. Although there has been a proliferation of texting trials, 
none have been fully standalone (i.e., delivered entirely via texting). Standalone approaches 
have great population-level potential because they are low cost, highly scalable, and modular in 
nature. They can reach into broad, diverse, and geographically dispersed populations that do 
not have stable access to other approaches (e.g., counseling, web, email, video) frequently 
employed in mHealth weight loss trials. Efficacious texting approaches could also be employed 
in multicomponent treatments to enhance outcomes. If we could improve the outcomes of 
standalone texting interventions, we might make major population-level impact. However, it is 
challenging to move the science forward because texting intervention designs have varied 
considerably. This study is designed to remedy this omission. We will use the MOST framework 
to develop an optimized treatment package that will deliver the most effective 6-month 
standalone texting intervention for weight loss. 
 

  
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Experimental Trial Overview: We propose to conduct a 6-month full factorial trial with up to 
700 adults with obesity. All participants will receive a core 6-month weight loss texting 
intervention (based on our iOTA approach). Consistent with the MOST framework, we will 
randomize participants to one of 32 experimental conditions to test the intervention components 
we identified in phase 1. The components and their levels include: motivational messaging (self- 
vs expert-generated), texting frequency (daily vs weekly), reminders (one reminder v. multiple 
reminders), feedback type (summary score v. specific feedback) and comparison unit (to self v. 
to a group of people). We will collect follow-up measures at months 3, 6, and 12 months. 
 
Design rationale: Two considerations are important when choosing an experimental design for 
a MOST trial. First, it should allow us to estimate the independent effects of a component on our 
outcome. Second, it must be economical, in terms of its actual cost and utilization of resources.1 
We considered several designs and chose the full factorial design for this trial. 
Table 2 shows our experimental conditions. To estimate the main effect of texting 
frequency, we compare the mean of conditions with a weekly (conditions 1-16) to the mean of 
the conditions in which frequency is daily (conditions 17-32). Similarly, we compare the mean of 
conditions receiving self-generated motivational messages (1-8; 17-24) to those with expert-
generated motivational messages (9-16; 25-32) to examine the main effect of motivational 
messaging. A similar process is used to test interactions. 
Condition Frequency Motivational 
Messaging 
Reminders Feedback 
Type 
Comparison 
Unit 
1 
weekly 
Self-generated 
One 
Summary 
Score 
Self 
2 
weekly 
Self-generated 
One 
Summary 
Score 
Group 
3 
weekly 
Self-generated 
One 
Individual 
Goal 
Self 
4 
weekly 
Self-generated 
One 
Individual 
Goal 
Group 
5 
weekly 
Self-generated 
Multiple 
Summary 
Score 
Self 
6 
weekly 
Self-generated 
Multiple 
Summary 
Score 
Group 
7 
weekly 
Self-generated 
Multiple 
Individual 
Goal 
Self 
8 
Weekly 
Self-generated 
Multiple 
Individual 
Goal 
Group 
9 
Weekly 
Expert-generated 
One 
Summary 
Score 
Self 
10 
Weekly 
Expert-generated 
One 
Summary 
Score 
Group 
11 
Weekly 
Expert-generated 
One 
Individual 
Goal 
Self 
12 
Weekly 
Expert-generated 
One 
Individual 
Goal 
Group 
13 
Weekly 
Expert-generated 
Multiple 
Summary 
Score 
Self 
14 
Weekly 
Expert-generated 
Multiple 
Summary 
Score 
Group 

  
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15 
Weekly 
Expert-generated 
Multiple 
Individual 
Goal 
Self 
16 
Weekly 
Expert-generated 
Multiple 
Individual 
Goal 
Group 
17 
Daily 
Self-generated 
One 
Summary 
Score 
Self 
18 
Daily 
Self-generated 
One 
Summary 
Score 
Group 
19 
Daily 
Self-generated 
One 
Individual 
Goal 
Self 
20 
Daily 
Self-generated 
One 
Individual 
Goal 
Group 
21 
Daily 
Self-generated 
Multiple 
Summary 
Score 
Self 
22 
Daily 
Self-generated 
Multiple 
Summary 
Score 
Group 
23 
Daily 
Self-generated 
Multiple 
Individual 
Goal 
Self 
24 
Daily 
Self-generated 
Multiple 
Individual 
Goal 
Group 
25 
Daily 
Expert-generated 
One 
Summary 
Score 
Self 
26 
Daily 
Expert-generated 
One 
Summary 
Score 
Group 
27 
Daily 
Expert-generated 
One 
Individual 
Goal 
Self 
28 
Daily 
Expert-generated 
One 
Individual 
Goal 
Group 
29 
Daily 
Expert-generated 
Multiple 
Summary 
Score 
Self 
30 
Daily 
Expert-generated 
Multiple 
Summary 
Score 
Group 
31 
Daily 
Expert-generated 
Multiple 
Individual 
Goal 
Self 
32 
Daily 
Expert-generated 
Multiple 
Individual 
Goal 
Group 
 
 
Intervention design: At baseline, we will randomize participants to one of the 32 experimental 
conditions (see Table 2). Each participant will receive the core weight loss intervention, based 
on our iOTA approach. 
 
iOTA 
 the interactive obesity treatment approach (iOTA): iOTA is an approach that we 
developed and have used in several recent obesity treatment trials.43,55,56,58 iOTA creates an 
energy deficit sufficient to produce weight loss through the modification of routine obesogenic 
lifestyle behaviors.55,58 We designed iOTA specifically for delivery via mHealth channels, where 
sustained intervention engagement is critical. Individuals expect their mHealth experience to be 
straightforward, highly personalized, and minimally effortful. Accordingly, iOTA is straightforward 
and does not require expert knowledge or expensive resources. From the participant 
perspective, s/he simply takes a short survey and is immediately assigned a set of personally-

  
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tailored behavior change goals. Participants then use text messaging to self-monitor their 
adherence to these goals. They receive tailored feedback based on their progress, skills training 
videos and motivational texts. 
Behind the scenes, iOTA is sophisticated, but uses low cost, highly disseminable digital 
health technologies. It relies on a series of interconnected algorithms and content libraries. After 
participants take their initial surveys, our prescription algorithm assigns 4 tailored behavior 
change goals. The prescription algorithm prioritizes behaviors in highest need of change, those 
for which the participant has high self-efficacy and readiness, and those that achieve the 
intended caloric deficit. A feedback algorithm tailors feedback, selecting content from a vast 
feedback content library. From our skills training library, we send videos to assist behavior 
change efforts. Based on self-monitoring data, we can select motivational messages to support 
that can be easily disseminated. For this reason, several research groups are testing iOTA in a 
range of populations. 
 
Theoretical framework: All core iOTA intervention components are designed to target 
self-efficacy, which we selected from social cognitive theory (SCT),59,60 given its consistent 
association with weight loss outcomes.61 63 Bandura identified 4 primary factors64 that influence 
self-efficacy: mastery experiences, social modeling, social persuasion, and somatic and 
emotional reactions. These are noted in Table 3, along with details about the core iOTA 
intervention address each component. SCT also indicates that behavior change can be 
facilitated through a number of self-regulatory processes, including self-monitoring,65 67 goal 
setting,31,63 and social support.68,69 
The intervention will support these self-regulatory processes, further heightening self-
efficacy. Our conceptual framework integrates TAM and self-efficacy. The intervention will target 
self-efficacy. Our experimental components were selected to increase perceived usefulness and 
ease of use, with the goal of enhancing intervention engagement, given its importance in driving 
weight loss.16 
 
 
Obesogenic behavior change goals: Participants track 4 behavior change goals that 
produce an energy deficit sufficient to produce weight loss. At baseline, each participant will 
complete a short risk behavior assessment using a tablet computer. Our prescription algorithm 
assigns 4 goals that achieve the required energy deficit. We have a library containing over 35 
obesogenic behavior change goals that have been selected based on their: 1) empirical 
support; 2) population relevance; 3) ease of self-monitoring; and 4) concreteness. We will 
leverage the goal library that was deemed efficacious in our previous studies, Shape (Protocol 

  
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2938) and Track (Protocol B0033) (See Appendix F). During study startup, we will make efforts 
to identify population-relevant goals that might be missing from our library. 
 
Self-monitoring and tailored feedback: Regular self-monitoring is a robust predictor of 
weight loss, although adherence typically wanes over time.65,67,70 Disengagement likely results 
from usability limitations, cognitive complexity, and lack of immediate feedback. As a result, our 
trials have involved extensive testing to ensure that that our texting self-monitoring tools are 
engaging. Our text messaging system is fully automated, currently operational, uses open-
source technologies and is designed for scalability. 
Depending on their randomization status, we will contact participants either daily or 3 
times weekly. An outbound text requests self-monitoring data. Participants then text their self-
monitoring data. We immediately provide tailored, real-time feedback on participant's progress 
via text. Feedback considers both short- and long-term progress. We also provide skills training 
tips, tailored to a part
 A sample self-monitoring exchange can be found 
in Appendix G.  
 
Tailored skills training videos: We have skills training videos (2-5 min) for each of the 
goals in our library. For example, for those assigned a fast food reduction goal, we provide skills 
training materials on eating out, social eating, and lunch packing. We also have a larger library 
of general behavior change lessons (e.g., stimulus control, problem solving, social cues, stress 
management). Our materials include tailored narratives, and information about cost and 
community resources. We use expectancy priming throughout to heighten salience of 
materials.71 We will deliver adapted skills training videos that we have implemented with 
success in Track and send links to videos presented on responsive websites like a private 
channel on YouTube.com. 
 
 
Motivational messages: We will send motivational messages on 3 weekdays and 1 
weekend day. For participants randomized to the expert condition, we will send texts from our 
extensive library of motivational messages. Each is designed to enhance motivation for 
behavior change and heighten self-efficacy for the assigned set of behavior change goals. To 
prevent habituation, the messages do not repeat in 30-day cycles. 
Participants randomized to the self-generated condition will create text messages in two 
areas at baseline: reasons and competence for weight loss. The former will target autonomous 
self-regulation (i.e., change stems from within), while the latter targets efficacy for weight-related 
behavior change. We will send texts from these pools randomly. Every two weeks, we will give 
participants the opportunity to create new messages. We will do this for several reasons. First, 
participants may think of new messages as they engage in behavior change. Second, the 
creation and receipt of new messages may promote intervention engagement. Finally, crafting 
new messages can increase their sense of autonomy and competence. A sample motivational 
message from our library can be found in Appendix G.  
 
Study start-up: During the first 6 months of Year 1, we will adapt the goal library, skills training 
materials, message library and tailoring algorithms. We will draw from the library of intervention 
content that we have used in previous studies. We will adapt the iOTA sy
the experimental conditions. We will assess usability and test all systems prior to starting the 
trial. We have extensive experience with software engineering and will use the resources of the 
Duke Global Digital Health Science Center (led by Dr. Bennett). 
 
Pilot Testing: We will enroll up to 75 participants prior to the start of the large randomized trial 
to test the connections between our webpage, Qualtrics survey, texting platform and RedCap 
database. Participants will be enrolled similarly to our larger trial. We will place geographically 

  
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targeted advertisements via Facebook and Nextdoor. The inclusion and exclusion criteria will 
mirror that of our larger trial.  
 
Those who respond to study marketing will undergo preliminary eligibility screening via a 
Qualtrics eligibility survey linked to a website created for this study. If deemed eligible via the 
online screening, participants will be invited to complete the stu
and baseline surveys online via a Qualtrics survey. Those who complete all surveys will be 
randomized to one of the 32 intervention groups. Those participants will then receive 2-weeks of 
our text messaging intervention. Pilot participants will not have any in-person visits and there 
will be no 3,6, or 12 month follow-ups. Pilot study participants will receive a $10 Amazon gift 
card for their participation.  
 
In addition to our true pilot, the first 20 participants in our larger trial will be pilot-extension 
participants. These participants will complete all measures and in-person visits as all other 
participants, but their data will not be included in our study analysis. The rationale is that 
programming issues or bugs arise every time a new programming component (new goals, 
survey changes, software updates) is introduced. By having the pilot extension, we can catch 
these issues before they affect our intervention.  
 
 
Data collection: Research data will be collected from several sources. During the baseline visit 
and at subsequent follow-up visits at 3, 6 and 12 months, study staff will collect anthropometric 
data, including height and weight. Participants will complete a Qualtrics survey before coming to 
their baseline visits, as well as at 6-months to collect social, psychosocial, and health status 
data, including data on sociodemographics, physical activity, dietary patterns, self-efficacy, and 
depression. We will gather self-monitoring data via intervention text messages. In keeping with 
our practices on prior trials, only trained and certified research staff will obtain data according to 
detailed study protocols (described in the Data Safety Monitoring Plan). All research staff are 
required to have human subjects training. All gathered data will be used specifically for research 
purposes. 
 
As part of enrollment, participants will self-report baseline age, gender, race/ethnicity, 
health insurance, education, income, employment, health status, marital status, health 
literacy/numeracy,85 and smartphone/texting history via a Qualtrics survey.17 Additional 
measures by study aim are listed below in Table 4. 
 
Table 4: Outcome measures  
 
 
BL 
3 
6 
12 
Weight1 
x 
x 
x 
x 
Height1 
x 
 
 
 
REAP2 (Rapid Eating and Activity Assessment) 
x 
 
x 
 
Weight Control Strategies2 
x 
 
x 
 
GPAQ2 Physical Activity 
x 
 
x 
 
SF-122 Health Survey 
x 
 
x 
x 
Body Related Guilt and Shame  
x 
 
 
 
Weight Bias Internalization Scale 
x 
 
x 
 
Confusion, Order and Hubbub Scale 
x 
 
 
 
iOTA 
x 
 
 
 

  
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Intervention Engagement2a 
x 
x 
x 
x 
Non-use attrition2b 
x 
x 
x 
x 
System Usability Scale2 
 
x 
x 
 
Participant Preference2 
x 
 
x 
 
Intervention acceptability2 
 
 
x 
 
Weight loss treatment history2 
x 
 
x 
x 
Incentive paid in Amazon e-card $20/$
10* 
$25 
$25 
$30** 
 
1= in-person; 2= online via Qualtrics 
*$10 if ineligible at in-person visit 
** Participants who complete all 3 follow-up evaluation visits after baseline will be 
reimbursed an additional $15 amazon e-card at his/her 12-month visit. 
a The primary measure is self-monitoring episodes (texts received/requests successfully sent). 
We will also examine skills training video views (completed views/video links successfully sent) 
and changes in motivational message content (content changes/change requests successfully 
sent).  
b Defined as those who cease intervention participation, but do not drop out of the trial (i.e., they 
complete 6-month assessments). For each, we will define the week of nonuse as the week in 
which all intervention participation ceased, and the participant did not return to the intervention.  
 
Baseline Enrollment Survey: Participants who express interest in Charge will be asked to take a 
series of Qualtrics surveys before coming in for a baseline visit. First, participants will take a 
short eligibility screener. Eligible participants will go through the informed consent process via 
Qualtrics and to sign an electronic informed consent form. Participants who sign the informed 
consent will be asked to fill out baseline surveys and the iOTA goal assignment survey. This 
survey was tested prior to implementation via mTurk to ensure they are not burdensome (pilot 
testing was approved in previous amendments).  
 
Baseline Evaluation Visit: At the baseline evaluation visit, study staff will collect written informed 
consent, administer the motivational message survey (if applicable based on condition), and 
confirm participant eligibility. This will be followed by an individual orientation to the intervention. 
Participants will be reimbursed for their time at baseline visits. 
We will randomize participants at the baseline visit. Randomization sequences will be 
generated by a computer algorithm using a covariate adaptive randomization method, in which 
group assignment will be informed by the balance of race/ethnicity and gender in the previously 
assigned participants. This method minimizes imbalance between groups for these 
characteristics, even in a small sample where the risk of imbalance is high and when the exact 
composition of the sample is not known a priori. Due to the nature of the interventions, it will be 
difficult to completely blind staff collecting data to treatment assignment. However, we will 
ensure that different study staff collect follow-up data and we will take all possible steps to blind 
those data collection staff to treatment assignment. Outcomes will be analyzed blind to 
allocation status. 
 
Follow-up Data Collection: In addition to the baseline visit, trained study staff will also collect 
anthropometric data, specifically weight, at subsequent follow-up visits at 3, 6 and 12 months. 
Participants will complete a self-report survey at baseline and at 6-months to collect social, 
psychosocial, and health status data, including data on sociodemographics, physical activity, 
dietary patterns, self-efficacy, and depression. We will gather self-monitoring data via 

  
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intervention text messages. In keeping with our practices on prior trials, only trained and 
certified research staff will obtain data. 
 
2.   Subject Selection  
 
Inclusion Criteria: The study involves males and females aged 18-65 years who have English 
language proficiency, and a BMI above 25 kg/m2. Participants will own a smartphone and be 
willing to receive multiple text messages daily.  
 
Exclusion Criteria: Participants will be excluded from the study under the following conditions: 
prior or planned bariatric surgery; psychiatric hospitalization in past 12 months; pregnancy, 
nursing, or planned pregnancy; history of a cardiovascular event; history of an eating disorder; 
history of a condition (e.g., end stage renal disease, cancer, schizophrenia) or use of 
medications (e.g., lithium, steroids, anti-psychotics) that would affect weight measurement, for 
which weight loss is contraindicated, or might promote weight change; current participation in a 
weight loss trial and/or recent weight loss > 10%; investigator discretion for safety reasons. 
 
Sample size: We will recruit up to 700 males and females aged 18-65 years who have English 
language proficiency, and a BMI above 25 kg/m2. We will recruit a sample that is 30% male and 
40% racial/ethnic minority (similar to the demographics of Durham, N.C.). We will waitlist 
participants if needed in order to reach our target recruitment percentages for males and 
minorities.  
 Using the FactorialPowerPlan SAS Macro, developed by the Penn State Methodology Center, 
we computed the sample size needed for a full 25 factorial design.  We expect a minimal 
difference between groups, defined as an effect size of 0.15.34 With a standard deviation 
estimate from a recent weight loss trial90 of 5 kg, and a within-participant correlation of 0.9, this 
translates into a 0.75 kg difference in weight loss at 6 months between groups given an 
intervention component and those groups without the intervention component (main effects). 
We determined that a total sample size of 282 subjects would be required to achieve an overall 
power of 80% to detect a 0.75 kg difference in weight loss. We conservatively assume 30% 
dropout at 6 months, so we inflate the sample size to 403. To obtain an equal number of 
participants in each treatment combination (condition), we further inflate this sample size to up 
to 700, which is a final sample of 14 participants in each of the 32 conditions.   The main effects 
are then estimated with 224 participants receiving either level of each component. Likewise, 
pairwise interactions are based on comparisons of means for 224 participants who receive both 
or neither component compared to those who received only one. 
 
Recruitment: We will recruit participants using a multi-pronged strategy: 1) direct marketing; 2) 
local media; 3) social media, 4) snowball recruitment and; 5) community organizations. We have 
used these methods successfully in many of our 
experience with general recruitment and have consistently met our recruitment goals. Direct 
marketing has been particularly useful recently. In the CITY trial,57 recently conducted at Duke, 
40% of the 365 enrolled participants were recruited from direct marketing. Accordingly, we will 
mail postcards describing the study to potentially eligible households in the 3-county Research 
Triangle area. We will also advertise online, including the Duke Clinical Trials website, which 
 enrolled participants. For this study, we will also leverage our strong 
relationships to attract earned media placements. We have been successful attracting earned 
stories on television, radio, and in print media. These media mentions have consistently led to 
participant inquiries. We will also advertise in local newspapers (circulation: > 150,000), 
television, and radio. We will work with local websites and bloggers to advertise the study. We 
will also place geographically targeted advertisements via Facebook and Google. Our group is 

  
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also very active on Twitter (with both local and national followers); we will advertise the study 
and answer questions using the service. We maintain excellent relationships with several 
community organizations, including those that service high risk populations. This includes faith-
based organizations with whom we have worked on previous trials of mHealth weight loss 
interventions (e.g., Shape Plan) and a large, local historically Black university (North Carolina 
Central University). We have been particularly successful using endorsements from 
key community figures (e.g., college sports stars, church pastors, etc.). Of note, two of our most 
recent mHealth trials were conducted in a community health center system with more than 
42,000 patients that operates in 7 counties in central North Carolina. They have expressed 
continued interest in serving as a recruitment site. It is important for our sample to be diverse, 
particularly considering evidence that racial/ethnic minorities both experience the health effects 
of obesity at disproportionately high rates, and that use of text messaging in these groups is 
almost ubiquitous. 18 We will recruit a sample that is 30% male and 40% racial/ethnic minority 
(similar to the demographics of Durham, N.C.). We have extensive experience in this area. 
 
Screening, randomization and blinding: Those who respond to study marketing will undergo 
preliminary eligibility screening via a Qualtrics eligibility survey linked from our study website. As 
with our other trials, we will request a waiver of written consent to screen and consent 
participants by web. Those deemed potentially eligible will be invited to complete the study 
informed consent process and baseline surveys via a Qualtrics survey. Participants who 
complete the informed consent process and all surveys will be invited for an in-person visit. At 
the visit, study staff will collect written informed consent and confirm participant eligibility. Study 
surveys will eliminate or define medical terms, and use simple sentence structure and 
vocabulary. We have successfully used this approach in several studies. This will be followed by 
an individual orientation to the intervention.  
 
We will randomize participants at the baseline visit. Randomization sequences will be generated 
by a computer algorithm using a covariate adaptive randomization method, in which group 
assignment will be informed by the balance of race/ethnicity and gender in the previously 
assigned participants. This method minimizes imbalance between groups for these 
characteristics, even in a small sample where the risk of imbalance is high and when the exact 
composition of the sample is not known a priori. Due to the nature of the interventions, it will be 
difficult to completely blind staff collecting data to treatment assignment. However, we will 
ensure that different study staff collect follow-up data and we will take all possible steps to blind 
those data collection staff to treatment assignment. Outcomes will be analyzed blind to 
allocation status. 
 
Retention: Our team has an excellent record of retaining our trial participants. In Shape, we 
retained 96% of participants (in a profoundly socioeconomically disadvantaged population) at 
the 18-month 
follow-up. In our current study, Track, we also have a >90% 6-month retention rate in a 
medically vulnerable population. We will use strategies that have been successful in prior 
studies (e.g., contacting through multiple channels, incentivizing provision of changed contact 
information, birthday/holiday cards, using family contacts, text messaging and social media). To 
maximize retention, participants will receive reimbursements at each of the evaluation visits: 
baseline, 3, 6, and 12 months. Participants who come to all 3 follow-up visits (after baseline) will 
receive another $15. Home visits will be used when other contact strategies are exhausted. 
Despite our experience with participant retention, we have set a conservative floor of 70% 
retention at 6 months. We have exceeded this rate in all of our recent trials. 
 
Phase II 

  
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After enrollment is completed for the in-person cohort (Phase I), we will enroll up to 5000 
participants in a virtual cohort where there will be no in-person data collection. Participants will 
be recruited similarly to phase I, with 1) direct marketing; 2) community forums; 3) social media, 
4) snowball recruitment and; 5) community organizations. Those who respond to study 
advertisements will take an eligibility survey via Qualtrics, consent and complete a baseline 
questionnaire. Eligible participants will be randomized via Prompt and receive the same 6-
month iOTA-based intervention.  
Since phase II participants will not come in for in-person follow-up assessments, participants will 
send us picture of their feet on a scale, with the weight visible wearing only light clothing with 
empty pockets and no shoes at 3-, 6- and 12-months.  
 
 
3.  Risks and Benefits 
 
This is a minimal risk study, and thus we do not anticipate problems beyond our control that 
involve risks to subjects.      
 
Physical activity: Risks from increased physical activity will be minimized by: 1) recommending 
physical activity in line with national guidelines; 2) encouraging moderate activity; and 3) 
directing participants to their physicians when appropriate. If exercise-related symptoms are 
reported, we will advise participants to get clearance from their PCPs before they can restart 
physical activity. 
 
Participants will be counseled to change behaviors that will maintain or reduce weight. If 
individuals follow this advice and decide to change their health behaviors, there should be few 
risks or side effects. The materials and counseling will provide guidance on preventing and 
managing the side effects of health behavior change. 
 
Data confidentiality: We will use the standard operating procedures that have been used on our 
prior trials for survey conduct and data management. These procedures have been developed 
and used in many studies and we will adhere to these procedures for the proposed study. All 
paper files related to the study will be stored in a secure location at Duke University in a locked 
file cabinet accessible only to key study personnel. The privacy, security, and durability of 
accumulated personal health information are of paramount importance. Our existing practices 
physical access to computing resources (hard drives, servers, networking equipment) is secure, 
audited, and restricted to skilled personnel; virtual access (login and system administration) is 
encrypted, audited, and limited to skilled personnel; all databases are encrypted and access 
from the public Internet is precluded; all software and servers are reachable only via a virtual 
private network (VPN); and al
interface (API) and third-party software is encrypted using SSL. Personnel will have access to 
perform regular maintenance duties. However, this constituency is limited to senior system 
administrators and the director of the research group. 
 
Breach of confidentiality: All participant information collected in the context of this study, and 
even the fact that an individual is participating in the study, will be considered confidential. 
Confidentiality will be assured through several mechanisms. First, each participant will be 
assigned an anonymous study ID that will be used on all study forms. Second, all study forms 

  
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and paper records that contain participant information (e.g., address lists) will be kept in 
secured, locked areas or in encrypted databases. In addition, such materials, when in use, will 
be kept away from public scrutiny. Materials that need to be discarded will be destroyed. Third, 
access to all participant data and information will be restricted to authorized personnel. In the 
case of computerized study data, access to data will be password protected and staff members 
will be assigned individualized passwords that allow them access to only those elements of the 
data management system to which they are authorized. In addition, all study personnel will 
maintain certification with the Duke IRB that they have completed training in research ethics, 
which includes training on confidentiality. Finally, participants will not be identified by name in 
any reports or publications, nor will data be presented in such a way that the identity of 
individual participants can be inferred. 
 
All information obtained in the course of the study that identifies an individual will be treated as 
confidential in accordance with section 903C of the Public Health Service Act (42 U.S.C.299a-
1). We will strip all identifiers from analytic data sets after data merging and will keep all 
personal identifiers in a separate location from the analytic data. No individual participant will be 
identified in any reports from the study. Data storage will involve computer files that will be 
password protected and encrypted and will be accessible only to personnel who need to contact 
participants. 
 
Study surveys, including the online eligibility screen, will be administered using Qualtrics. We 
will deliver separate surveys to participants in order to minimize drop off and maximize 
participant security. Each participant will be asked to fill out one survey with his or her name and 
contact information; participants will thereafter use only study ID or a unique link when 
completing surveys. At various timepoints throughout data collection and after, we will download 
survey data from Qualtrics for analyses. Data sets will be de-identified before being 
downloaded. Data will be downloaded using the Qualtrics export feature. Data will be 
-
protected. A copy of the raw de-identified data set and/or the results of the analyses will be 
uploaded to a Box sensitive folder. When the study biostatistician is ready to analyze the data in 
SAS, a statistical analysis program. She will upload the de-identified data, and SAS will store a 
copy locally to work from. This data set will be deleted from SAS after analyses are completed.  
 
In order to send and receive text messages, we will use a software engine designed by Duke 
software engineers, called Prompt. Prompt uses Twilio, Heroku, and Amazon S3. Prompt will 
receive self-monitoring data that participants send via text message. The data will be 
automatically analyzed each week according to algorithms we embed. Study staff will log into a 
password-protected database using multi-factor authentication to view and edit participant 
information. We will use Twilio to send text messages to participants each week. We delete data 
from Twilio at least every 2 weeks. We will use Heroku to process data for the engine. We will 
use Amazon S3 to store data; data will be encrypted when it is stored. If these companies or 
their business partners disclose data, it may no longer be covered under the Duke privacy 
protections. Text messaging does not provide a completely secure and confidential means of 
communication. Participants will be made aware of these risks as well as those that are inherent 
in using text messaging during the informed consent process. We have used these processes 
on several previous studies conducted in this population.  
 
Potential Benefits: Potential benefits for study participants include improved lifestyle, lower 
weight and blood pressure and consequent reduction in cardiovascular risk. An additional 
benefit for some participants may be personal satisfaction in being part of a study that may have 
major public health implications for the community. No benefit from participation can be 

  
Protocol renewal approved by Duke Campus IRB:  7/21/2021 
 
Page 12  
guaranteed. Potential benefits to others include the possibility that this research will lead to the 
dissemination of an intervention that can help maintain weight, with consequent reduction in the 
risks associated with diagnoses of diabetes, high cholesterol, and hypertension. The minimal 
health risks to participants listed above are offset by the potential benefits to them and to 
society. 
 
4. 
  Confidentiality 
 
In the present study, we will collect identifying demographic information including: names, 
addresses, telephone numbers, email addresses, age, gender, race/ethnicity, health insurance, 
education, income, employment, health status, and marital status. We will use the standard 
operating procedures that have been used on our prior trials for survey conduct and data 
management. All paper files related to the study will be stored in a secure location at Duke 
University in a locked file cabinet accessible only to key study personnel. The privacy, security, 
and durability of accumulated personal health information are of paramount importance. 
Physical access to computing resources (hard drives, servers, networking equipment) is secure, 
audited, and restricted to skilled personnel; virtual access (login and system administration) is 
encrypted, audited, and limited to skilled personnel; all databases are encrypted and access 
from the public Internet is precluded; all software and servers are reachable via a password-
protected database that is enabled with multifactor authentication; and all communication 
(API) and third-party software is 
encrypted using SSL. Personnel must have access to these databases to perform regular 
maintenance duties. However, this constituency is limited to senior system administrators and 
the director of the research group. 
 
Strategies for protecting electronic PHI: Screening, outcome measures (height, weight, 
sociodemographics) and surveys will be entered into Qualtrics and Redcap. We will also enter 
some participant information (phone number, study group, and behavioral goals) into a software 
engine developed by Duke software engineers. Prompt is developed on Heroku, a managed 
container system for data. We will use Heroku to process data analytics. All web-transmitted 
data are encrypted using a protocol called Transport Layer Security (TLS) or Secure Sockets 
Layer (SSL). This type of security is most often used for web sites that are doing eCommerce 
(selling products/services over the Internet). The reason for the increased security is to protect 
the privacy of visitors/customers and transmission of personal, confidential, financial or billing 
information over the Internet. We will also password protect study data on Prompt and use 
multifactor authentication processes. As described above, physical access to computing 
resources (hard drives, servers, networking equipment) is secure, audited, and restricted to 
skilled personnel; virtual access (login and system administration) is encrypted, audited, and 
limited to skilled personnel; all databases are encrypted and access from the public Internet is 
 
(API) and third-party software is encrypted using SSL. Only research staff who have received 
CITI Certification and are listed on the Duke University Institutional Review Board protocol will 
have access to the study database. Information in the database will not be shared with anyone 
outside the research team. On the study consent form (Appendix A), we inform participants that 
we do collect identifying information and that we take all appropriate measures to minimize the 
risk of unintentional breach of confidentiality. 
 
The information generated by this study will be kept for seven years after the date of last 
publication. Then it will be destroyed by shredding the paper copies and by securely deleting the 
computer files. 
 

  
Protocol renewal approved by Duke Campus IRB:  7/21/2021 
 
Page 13  
Data management will take place under the supervision of Dr. Bennett. Our group has 
developed extensive quality assurance procedures, including on-going quality control checks. 
 
 
Some participants will choose to be reimbursed with an electronic Amazon gift card.  
Participants who choose this method of compensation will be asked to provide their email 
address, so we can email the gift card to them.  Their email address will be stored in a 
password-protected, encrypted study database. They will not need to provide their social 
security numbers.  
 
After data analysis, we plan to disseminate the results of the study via journal publications and 
presentations.  
 
We will not collect information about illegal activities. Further, we do not expect that participants 
will reveal information subject to reporting because our coaches are instructed to maintain close 
adherence to a protocol that involves discussing only behavior change efforts related to diet and 
exercise.   
 
5.  Compensation 
 
Participants will be reimbursed in the form of an electronic Amazon gift card for their time at 
each of the evaluation visits: baseline, 3, 6, and 12 months (20,25,25,30 respectively). If a 
participant is determined to be ineligible at the time of the screening baseline visit, s/he will be 
compensated $10 amazon e-card for his or her time. Participants who complete all 3 follow-up 
evaluation visits after baseline will be reimbursed an additional $15 amazon e-card at his/her 
12-month visit. 
 
 

  
Protocol renewal approved by Duke Campus IRB:  7/21/2021 
 
Page 14  
If a participant does not wish to provide their social security or tax identification number, they 
can be reimbursed using an electronic Amazon gift card for each visit.  Participants who choose 
this method of compensation will be asked to provide their email address, so we can email the 
gift card to them.  Their email address will be stored in a password-protected, encrypted study 
database.  
 
6.  Informed Consent 
 
Please see the consent form attached (Appendix A). 
 
7.   Deception 
 
Deception will not be used in the present study. 
 
8.  Debriefing 
 
We do not anticipate a need for debriefing. 
 
9.  References  
 
1. Collins LM, Baker TB, Mermelstein RJ, et al. The multiphase optimization strategy for 
engineering effective tobacco use interventions. Ann Behav Med. 2011;41(2):208-226. 
2. Ogden CL, Carroll MD, Flegal KM. Prevalence of obesity in the United States. JAMA. 
2014;312(2):189- 190. 
3. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution 
of body mass index among US adults, 1999-2010. JAMA. 2012;307(5):491-497. 
4. Yang L, Colditz GA. Prevalence of Overweight and Obesity in the United States, 2007-2012. 
JAMA Intern Med. 2015. doi:10.1001/jamainternmed.2015.2405. 
5. Ogden CL, Lamb MM, Carroll MD, Flegal KM. Obesity and socioeconomic status in adults: 
United States, 2005-2008. NCHS Data Brief. 2010;(50):1-8. 
6. Chow EA, Foster H, Gonzalez V, McIver L. The Disparate Impact of Diabetes on 
Racial/Ethnic Minority Populations. Clin Diabetes. 2012;30(3):130-133. 
7. Rodriguez F, Ferdinand KC. Hypertension in minority populations: new guidelines and 
emerging concepts. Adv Chronic Kidney Dis. 2015;22(2):145-153. 
8. Befort CA, Nazir N, Perri MG. Prevalence of obesity among adults from rural and urban areas 
of the United States: findings from NHANES (2005-2008). J Rural Health. 
2012;28(4):392-397. 
9. Jensen MD, Ryan DH, Apovian CM, et al. 2013 AHA/ACC/TOS guideline for the 
management of overweight and obesity in adults: a report of the American College of 
Cardiology/American Heart Association Task Force on Practice Guidelines and The 
Obesity Society. J Am Coll Cardiol. 2014;63(25 Pt B):2985-3023. 
10. Mokdad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes, and obesity-
related health risk factors, 2001. JAMA. 2003;289(1):76-79. 
11. Finkelstein EA, Brown DS, Wrage LA, Allaire BT, Hoerger TJ. Individual and aggregate 
years-of-life-lost associated with overweight and obesity. Obesity. 2010;18(2):333-339. 
12. Fontaine KR, Redden DT, Wang C, Westfall AO, Allison DB. Years of life lost due to obesity. 
JAMA. 2003;289(2):187-193. 
13. Han X, Stevens J, Truesdale KP, et al. Body mass index at early adulthood, subsequent 
weight change and cancer incidence and mortality. Int J Cancer. 2014;135(12):2900-
2909. 
14. Wadden TA, Stunkard AJ. Handbook of Obesity Treatment. Guilford Press; 2002. 

  
Protocol renewal approved by Duke Campus IRB:  7/21/2021 
 
Page 15  
15. Osei-Assibey G, Kyrou I, Adi Y, Kumar S, Matyka K. Dietary and lifestyle interventions for 
weight management in adults from minority ethnic/non-White groups: a systematic 
review. Obes Rev. 2010;11(11):769-776. 
16. Bennett GG, Glasgow RE. The delivery of public health interventions via the Internet: 
actualizing their potential. Annu Rev Public Health. 2009;30:273-292. 
17. Smith A. US Smartphone Use in 2015. Pew Research Center. 2015. 
18. Smith A. Smartphone Ownership 2013. 2013. 
http://pewinternet.org/Reports/2013/Smartphone- 
Ownership-2013/Findings.aspx. 
31. Strecher V. Internet methods for delivering behavioral and health-related interventions 
(eHealth). Annu Rev Clin Psychol. 2007;3:53-76. 
34. Pellegrini CA, Hoffman SA, Collins LM, Spring B. Optimization of remotely delivered 
intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-
IN study protocol. Contemp Clin Trials. 2014;38(2):251-259. 
43. Bennett GG, Foley P, Levine E, et al. Behavioral treatment for weight gain prevention 
among black women in primary care practice: a randomized clinical trial. JAMA Intern 
Med. 2013;173(19):1770-1777. 
53. Chakraborty B, Collins LM, Strecher VJ, Murphy SA. Developing multicomponent 
interventions using fractional factorial designs. Stat Med. 2009;28(21):2687-2708. 
55. Bennett GG, Herring SJ, Puleo E, Stein EK, Emmons KM, Gillman MW. Web-based weight 
loss in primary care: a randomized controlled trial. Obesity. 2010;18(2):308-313. 
56. Bennett GG, Warner ET, Glasgow RE, et al. Obesity treatment for socioeconomically 
disadvantaged patients in primary care practice. Arch Intern Med. 2012;172(7):565-574. 
57. Batch BC, Tyson C, Bagwell J, et al. Weight loss intervention for young adults using mobile 
technology: design and rationale of a randomized controlled trial - Cell Phone 
Intervention for You (CITY). Contemp Clin Trials. 2014;37:333-341. 
58. Greaney ML, Quintiliani LM, Warner ET, et al. Weight Management Among Patients at 
Management. 2009;5(5):222-228. 
59. Bandura A. Self-Efficacy: The Exercise of Control. Macmillan; 1997. 
60. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 
1977;84(2):191-215. 
61. Linde JA, Rothman AJ, Baldwin AS, Jeffery RW. The impact of self-efficacy on behavior 
change and weight change among overweight participants in a weight loss trial. Health 
Psychol. 2006;25(3):282. 
62. Richman RM, Loughnan GT, Droulers AM, Steinbeck KS, Caterson ID. Self-efficacy in 
relation to eating behaviour among obese and non-obese women. Int J Obes Relat 
Metab Disord. 2001;25(6):907-913. 
 
63. Elfhag K, Rossner S. Who succeeds in maintaining weight loss? A conceptual review of 
factors associated with weight loss maintenance and weight regain. Obes Rev. 
2005;6(1):67-85. 
64. Bandura A. Health promotion from the perspective of social cognitive theory. Psychol 
Health. 
1998;13(4):623-649. 
65. Levitsky DA, Garay J, Nausbaum M, Neighbors L, Dellavalle DM. Monitoring weight daily 
blocks the freshman weight gain: a model for combating the epidemic of obesity. Int J 
Obes 2006;30(6):1003-1010. 
66. Klem ML, Wing RR, McGuire MT, Seagle HM, Hill JO. A descriptive study of individuals 
successful at long-term maintenance of substantial weight loss. Am J Clin Nutr. 
1997;66(2):239-246. 

  
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Page 16  
67. Boutelle KN, Kirschenbaum DS, Baker RC, Mitchell ME. How can obese weight controllers 
minimize weight gain during the high risk holiday season? By self-monitoring very 
consistently. Health Psychol. 1999;18(4):364-368. 
68. Stolley MR, Fitzgibbon ML, Schiffer L, et al. Obesity reduction black intervention trial 
(ORBIT): six-month results. Obesity. 2009;17(1):100-106. 
69. Wing RR, Jeffery RW. Benefits of recruiting participants with friends and increasing social 
support for weight loss and maintenance. J Consult Clin Psychol. 1999;67(1):132-138. 
70. Hardeman W, Griffin S, Johnston M, Kinmonth AL, Wareham NJ. Interventions to prevent 
weight gain: a systematic review of psychological models and behaviour change 
methods. Int J Obes Relat Metab Disord. 2000;24(2):131-143. 
85. Weiss BD, Mays MZ, Martz W, et al. Quick assessment of literacy in primary care: the 
newest vital sign. The Annals of Family Medicine. 2005;3(6):514-522. 
90. Svetkey LP, Batch BC, Lin PH, et al. Cell phone intervention for you (CITY): A randomized, 
controlled trial of behavioral weight loss intervention for young adults using mobile 
technology. Obesity (Silver Spring). 2015;23(11):2133-2141. 
 
10. Appendices  
 
 
A. Informed Consent 
B. Baseline Survey 
C. iOTA Survey 
D. Web-based Eligibility Screen 
E. Recruitment Postcard 
E.1. Recruitment Radio Spot 
F. IRB Personal Data Disclosure Form 
G. iOTA Goal Library 
H. Sample text messages from Charge 
I. 
Phase II Welcome Email 
J. Full Protocol 
 
 
 
 

INFORMED CONSENT

 
Effective: December 22, 2015 
 
Page 17 of 123 
Appendix A 
Duke University 
Informed Consent form for participation in Charge 
(Online Consent for Online Baseline Survey and In-Person Consent for Baseline Visit) 
 
 
What is Charge? 
 
 Charge is a research study. Researchers at Duke University are doing this study. The goal 
of the study is to find the best way to use text messaging to help men and women lose 
weight and take care of their health. 
  
 Charge is open to men and women who are between 18 and 65 years old. To be eligible 
for the study, we will weigh you and take your height. Your weight and height must be in 
a certain range to be eligible for the study. 
 
 To be eligible for this study, you must have a smartphone and be willing to send and 
receive text messages. 
  
 A total of up to 700 patients will be invited to take part in this study. 
 
 
What is the reason for this form? 
 
 We are inviting you to join Charge 
 
 This consent form explains the study and your part in it.  
 
 Please read the form carefully. Feel free to ask any questions at any time about the study. 
 
 If you decide to take part in the study, you are a volunteer. You can join the study now 
and stop later if you change your mind.  
 
 You may quit the study at any time.  
 
What will happen if you join the study? 
 
 If you decide to join, your participation will last 12 months.  
 
 We will ask you to take a 30-
personal information, like your age, gender, race/ethnicity, education, and marital status. 
Once you finish the survey, our staff will call you to schedule a time come to our study 
office for a baseline visit. This visit should take 30 minutes. We will take your height and 
weight at the visit to confirm your eligibility.  
 

 
18 
 
 Using a computer, all participants in this study will be randomly placed into one of 32 
experimental groups. While group assignment is random, the computer will make sure 
We will tell you which group 
you are in at your baseline visit. Depending on 
fill out another short survey.  
 
 We will ask you some questions about certain behaviors like what you eat and how much 
walking you do.  
 
 We will ask you to change some of these behaviors to help you maintain or lose weight.  
 
 We will ask you to monitor these behaviors by answering our questions. The study will 
will answer these questions by using the buttons on your phone.  
 
 
 
 You will receive information about your health via short videos we will send you by SMS. 
 
 You will also have 20-minute follow-up visits for weight measurements at:  
o 3 months 
o 6 months 
o 12 months 
 
 We will send you surveys before the follow-up visits at 3 months, 6 months and 12-months 
via a text message link.  
 
 
What are the risks or discomforts of the study?  
 
 The study will help you follow general health guidelines from the National Institutes of 
Health. The activities we ask you to do (such as walking more, eating healthy) have very 
little risk to your body. 
 
 
 We may ask you to get more exercise as part of this study. You will mostly be asked to 
do activities (like walking) that usually do not cause injuries. However, sometimes 
injuries like muscle strains and sprains can happen. We will talk with you about ways to 
not get hurt. 
 
 Most people do not have problems when they get more physical activity. We may only 
recommend that you do some brisk walking and this is consistent with public health 
guidelines. If you have any pain from exercise, we would want you to see a doctor right 
away. 

 
19 
 
 
 If you become pregnant, we will ask you to leave the study. Changes in diet and weight 
may not be healthy for a baby during pregnancy. 
 
 If study investigators think you should not continue in the study for health reasons, we 
will ask you to leave the study. 
 
o There is a potential risk of loss of confidentiality of the information you send us 
via text message. Text messaging is not a completely secure method of 
communication. Every effort will be made to keep your information confidential; 
however, this cannot be guaranteed.  
 You can refuse to take part in any part of the study. You can also refuse to answer any 
questions that make you uncomfortable. You can drop out of the study at any time, and 
your relationship with your health care professionals will stay the same. Your health 
insurance benefits will not change. 
 
What are the benefits of taking part in the study? 
 
 We cannot promise that you will you will lose weight while participating in our study 
but, by taking part, we hope that you will learn ways to be healthy. 
 
 Participation in the study helps us learn more about ways to keep men and women in your 
community healthy. 
 
Will I be paid for taking part in Charge? 
 
 You will receive reimbursements for your time at each of your study visits, including 
baseline, 3-, 6-, and 12-months in the form of an amazon e-card. Amounts will vary from 
$10 - $45.  
 
 If you quit the study or become ineligible for the study for any reason, you will be paid 
for your participation to that point. 
 
How will my privacy be protected?  
 
 Every effort will be made to keep your information private; however, this cannot be 
guaranteed. The information we gather from you (name, address, phone number, etc) will 
be kept in databases on password-protected computers at Duke and we will use code 
numbers on data collected. The information we collect will be used only for this study. 
Only study staff approved by the Duke Institutional Review Board (IRB) will be able to 
see your information.  None of your data will ever be sent to third parties except as 
described in this consent form, with your permission, or as may be required by law. We 
will only report information about the whole study group, not about individual people. 
 
 

 
20 
 
 
 We realize that no data security system is completely safe, but we will take all 
appropriate measures to minimize the risk of violating your privacy. 
 
 Many applications on your phone and email services you commonly use work with text 
messaging and cloud-based companies to send and receive information. In order to send 
you send text messages, we use Twilio, Heroku, and Amazon S3. These companies 
encrypt your information on their servers, but no system is completely safe.  If these 
companies decide to share these data, it may no longer be covered under the privacy 
protections.  
 
 When we interview you, we will speak to you in a private space.  
 
 We will destroy copies of all personal health information and other study information 
seven years after the date of last publication. 
 
 Since you will receive an electronic Amazon gift card, we will collect your email 
address, so we can email you the Amazon gift card.  We will keep this 
information in a password-protected, encrypted study database. This information 
will also be shared with Duke accounting, but this information will not be 
connected to your data.  
 
 
 
Will the study pay if there is an injury?  
 
 If you get hurt from taking part in this study, you should contact Jamiyla Bolton (919-
613-5456), after contacting a health professional (like first aid, your primary care 
provider, or emergency treatment). However, the study will not pay for the treatment. 
Your health insurance may be billed for the cost. 
 
Where can I get more information? 
For questions about your rights as a research participant, please call: 
Chair 
Duke University 
Institutional Review Board 
(919) 684-3030 
 
For questions about the study, please call:  
Jamiyla Bolton, MS 
Project Director 
Duke University 
(919) 684-1953 
 
What does my signature on this page mean? 
  

 
21 
 
 Your signature means that: 
o You have read this form 
o You have been given an opportunity to ask questions. 
o You agree to join the study 
 
 
[For written consent only, not Qualtrics consent] 
 
________________________ has been informed of the nature and purpose of the procedures 
described above, including any risks involved with participation in the study.  He or she has been 
given time to ask any questions, and these questions have been answered to the best of the 
investigator's ability. A signed copy of this consent form will be made available to the subject. 
 
 
________________________________Research Assistant  
___________________Date 
 
 
I have been told about this research study and its possible benefits, risks, and discomforts. I agree 
to take part in this research as a subject. I know that I am free to change my mind and quit this 
project at any time.  
 
 
_________________________________Participant              
_________________ Date 
 
 
 
 
Charge study: consent form phase II 
 
 
What is Charge? 
 
 Charge is a research study. Researchers at Duke University are doing this study. The goal 
of the study is to find the best way to use text messaging to help men and women lose 
weight and take care of their health. 
  
 Charge is open to men and women who are between 18 and 65 years old. To be eligible 
for the study, you will be asked to report your weight and height. Your weight and height 
must be in a certain range to be eligible for the study. 
 
 To be eligible for this study, you must have a smartphone and be willing to send and 
receive text messages. 
  
 Up to 5000 participants will be invited to take part in this study. 
 
 

 
22 
 
What is the reason for this form? 
 
 We are inviting you to join Charge. 
 
 This consent form explains the study and your part in it.  
 
 Please read the form carefully. Feel free to ask any questions at any time about the study. 
 
 If you decide to take part in the study, you are a volunteer. You can join the study now 
and stop later if you change your mind.  
 
 You may quit the study at any time.  
 
 
What will happen if you join the study? 
 
 If you decide to join, your participation will last 12 months.  
 
 We will ask you to take a 30-
personal information, like your age, gender, race/ethnicity, education, and marital status.  
 
 Once you finish the survey, a computer, all participants in this study will be randomly 
placed into one of 32 experimental groups. While group assignment is random, the 
will tell y
asked to fill out another short survey.  
 
 We will ask you some questions about certain behaviors like what you eat and how much 
walking you do.  
 
 We will ask you to change some of these behaviors to help you maintain or lose weight.  
 
 We will ask you to monitor these behaviors by answering our questions. The study will 
different number of text messages 
will answer these questions by using the buttons on your phone.  
 
 You will receive information about your health via short videos we will send you by 
SMS. 
 
 You may also be asked to complete 3 more follow-up surveys for weight measurements 
at:  
 
o 3 months 
o 6 months 

 
23 
 
o 12 months 
 
 If you are asked to complete follow-up surveys, we will send you links to these online via 
an email link.  
 
 
What are the risks or discomforts of the study?  
 
 The study will help you follow general health guidelines from the National Institutes of 
Health. The activities we ask you to do (such as walking more, eating healthy) have very 
little risk to your body. 
 
 We may ask you to get more exercise as part of this study. You will mostly be asked to 
do activities (like walking) that usually do not cause injuries. However, sometimes 
injuries like muscle strains and sprains can happen. We will talk with you about ways to 
not get hurt. 
 
 Most people do not have problems when they get more physical activity. We may only 
recommend that you do some brisk walking and this is consistent with public health 
guidelines. If you have any pain from exercise, we would want you to see a doctor right 
away. 
 
 If you become pregnant, we will ask you to leave the study. Changes in diet and weight 
may not be healthy for a baby during pregnancy. 
 
 If study investigators think you should not continue in the study for health reasons, we 
will ask you to leave the study. 
 
o There is a potential risk of loss of confidentiality of the information you send us 
via text message. Text messaging is not a completely secure method of 
communication. Every effort will be made to keep your information confidential; 
however, this cannot be guaranteed.  
 You can refuse to take part in any part of the study. You can also refuse to answer any 
questions that make you uncomfortable. You can drop out of the study at any time, and 
your relationship with your health care professionals will stay the same. Your health 
insurance benefits will not change. 
 
What are the benefits of taking part in the study? 
 
 We cannot promise that you will you will lose weight while participating in our study 
but, by taking part, we hope that you will learn ways to be healthy. 
 
 Participation in the study helps us learn more about ways to keep men and women in your 
community healthy. 

 
24 
 
 
 
How will my privacy be protected?  
 
 Every effort will be made to keep your information private; however, this cannot be 
guaranteed. The identifiable information we gather from you (name, address, phone 
number, etc) will be kept in secure online servers and databases on password-protected 
computers at Duke and we will use code numbers on data collected. The information we 
collect will be used only for this study. Only study staff approved by the Duke 
Institutional Review Board (IRB) will be able to see your identifiable information.  None 
of your data will ever be sent to third parties except as described in this consent form, 
with your permission, or as may be required by law. We will only report information 
about the whole study group, not about individual people. 
 
 We realize that no data security system is completely safe, but we will take all 
appropriate measures to minimize the risk of violating your privacy. 
 
 Many applications on your phone and email services you commonly use work with text 
messaging and cloud-based companies to send and receive information. In order to send 
you text messages, we use Twilio, Heroku, and Amazon S3. These companies encrypt 
your information on their servers, but no system is completely safe.  If these companies 
decide to share these data, it may no longer be covered under the privacy protections.  
 
 We will destroy copies of all personal health information and other study information 
seven years after the date of last publication. 
 
 
Will the study pay if there is an injury?  
 
 If you get hurt from taking part in this study, you should contact Jamiyla Bolton (919-
613-5456), after contacting a health professional (like first aid, your primary care 
provider, or emergency treatment). However, the study will not pay for the treatment. 
Your health insurance may be billed for the cost. 
 
Where can I get more information? 
For questions about your rights as a research participant, please call: 
Chair 
Duke University 
Institutional Review Board 
(919) 684-3030 
 
 
For questions about the study, please call:  
Jamiyla Bolton, MS 
Project Director 
Duke University 

 
25 
 
(919) 684-1953 
 
 
What does my signature on this page mean? 
  
 Your signature means that: 
o You have read this form 
o You have been given an opportunity to ask questions. 
o You agree to join the study 
 
I have been told about this research study and its possible benefits, risks, and discomforts. I agree 
to take part in this research as a participant. I know that I am free to change my mind and quit 
this project at any time.  
 
 
 
________________________________ 
 
 
 
___________________ 
Participant 
 
 
 
 
 
 
 
Date 
 
 
 
 
Duke University 
Informed Consent form for participation in Charge Pilot 
(Online Consent) 
 
 
What is Charge? 
 
 Charge is a research study. Researchers at Duke University are doing this study. 
The goal of the study is to find the best way to use text messaging to help men 
and women lose weight and take care of their health.  
 
 This portion of Charge is a pilot study. A pilot study is used to make sure all study 
parts are working as they should before we enroll participants in a larger study. 
  
 Charge is open to men and women who are between 18 and 65 years old. To be 
eligible for the study, we will weigh you and take your height. Your weight and 
height must be in a certain range to be eligible for the study. 
 
 To be eligible for this study, you must have a smartphone and be willing to send 
and receive text messages. 
  
 Up to 75 patients will be invited to take part in this study. 
 
 

 
26 
 
What is the reason for this form? 
 
 We are inviting you to join Charge 
 
 This consent form explains the study and your part in it.  
 
 Please read the form carefully. Feel free to ask any questions at any time about 
the study. 
 
 If you decide to take part in the study, you are a volunteer. You can join the study 
now and stop later if you change your mind.  
 
 You may quit the study at any time.  
 
What will happen if you join the study? 
 
 If you decide to join, your participation will last 2 weeks.  
 
 Using a computer, all participants in this study will be randomly placed into one of 
32 experimental groups. While group assignment is random, the computer will 
/ethnicity and gender are balanced. We will tell 
you which group you in after you fill out your initial surveys. Depending on what 
 
 
 We will ask you some questions about certain behaviors like what you eat and 
how much walking you do.  
 
 We will ask you to change some of these behaviors to help you maintain or lose 
weight.  
 
 We will ask you to monitor these behaviors by answering our questions. The 
study will text you on your cell phone. These texts will come from a computer and 
phone.  
 
 You will receive information about your health via short videos we will send you by 
SMS. 
 
What are the risks or discomforts of the study?  
 
 The study will help you follow general health guidelines from the National 
Institutes of Health. The activities we ask you to do (such as walking more, eating 
healthy) have very little risk to your body. 
 

 
27 
 
 If study investigators think you should not continue in the study for health 
reasons, we will ask you to leave the study. 
 
o There is a potential risk of loss of confidentiality of the information you 
send us via text message. Text messaging is not a completely secure 
method of communication. Every effort will be made to keep your 
information confidential; however, this cannot be guaranteed.  
 You can refuse to take part in any part of the study. You can also refuse to 
answer any questions that make you uncomfortable. You can drop out of the 
study at any time, and your relationship with your health care professionals will 
stay the same. Your health insurance benefits will not change. 
 
What are the benefits of taking part in the study? 
 
 We cannot promise that you will you will lose weight while participating in our 
study but, by taking part, we hope that you will learn ways to be healthy. 
 
 Participation in the study helps us learn more about ways to keep men and 
women in your community healthy. 
 
 
Will I be paid for taking part in Charge? 
 
 You will receive a $10 Amazon gift card for participation.   
 
 If you quit the study or become ineligible for the study for any reason, you will be 
paid for your participation to that point. 
 
How will my privacy be protected?  
 
 Every effort will be made to keep your information private; however, this cannot 
be guaranteed. The information we gather from you (name, address, phone 
number, etc) will be kept in databases on password-protected computers at Duke 
and we will use code numbers on data collected. The information we collect will 
be used only for this study. Only study staff approved by the Duke Institutional 
Review Board (IRB) will be able to see your information.  None of your data will 
ever be sent to third parties except as described in this consent form, with your 
permission, or as may be required by law. We will only report information about 
the whole study group, not about individual people. 
 
 We realize that no data security system is completely safe, but we will take all 
appropriate measures to minimize the risk of violating your privacy. 
 
 Many applications on your phone and email services you commonly use work 
with text messaging and cloud-based companies to send and receive 

 
28 
 
information. In order to send you send text messages, we use Twilio, Heroku, 
and Amazon S3. These companies encrypt your information on their servers, but 
no system is completely safe.  If these companies decide to share these data, it 
may no longer be covered under the privacy protections.  
 
 We will destroy copies of all personal health information and other study 
information seven years after the date of last publication. 
 
 Since you will receive an electronic Amazon gift card, we will collect your email 
address, so we can email you the Amazon gift card.  We will keep this 
information in a password-protected, encrypted study database. This information 
will also be shared with Duke accounting, but this information will not be 
connected to your data.  
 
Will the study pay if there is an injury?  
 
 If you get hurt from taking part in this study, you should contact Jamiyla Bolton 
(919-613-5456), after contacting a health professional (like first aid, your primary 
care provider, or emergency treatment). However, the study will not pay for the 
treatment. Your health insurance may be billed for the cost. 
 
Where can I get more information? 
For questions about your rights as a research participant, please call: 
Chair 
Duke University 
Institutional Review Board 
(919) 684-3030 
 
For questions about the study, please call:  
Jamiyla Bolton, MS 
Project Director 
Duke University 
(919) 684-1953 
 
What does my electronic signature on this page mean? 
  
 Your signature means that: 
o You have read this form 
o You have been given an opportunity to ask questions. 
o You agree to join the study 
 
I have been told about this research study and its possible benefits, risks, and 
discomforts. I agree to take part in this research as a subject. I know that I am free to 
change my mind and quit this project at any time.  
 
 

STATISTICAL ANALYSIS PLAN (SAP)

 
Page 1 
 
1 Study Overview 
Background/Introduction:  
1.1 Study Aims 
• 
Determine the effect of each of the five intervention components on absolute weight change from baseline 
to 6 months. 
• 
Assemble a multicomponent treatment package including the comparator level of components with 
standardized main effect sizes of ≥ 0.7 kg.  Otherwise, include the default level, unless interactions of ≥ 0.7 
kg are present that would cause us to include the comparator level. 
2 Study Population 
2.1 Inclusion Criteria 
• 
English language proficiency 
• 
BMI above 25 kg/m2 
• 
Own a smartphone 
• 
Be willing to receive multiple text messages daily. 
• 
We aimed to recruit a sample that is 30% male and 40% racial/ethnic minorities. 
2.2 Exclusion Criteria 
• 
Exclusion criteria include the following conditions: prior or planned bariatric surgery; psychiatric 
hospitalization in past 12 months; pregnancy, nursing, or planned pregnancy; history of a cardiovascular 
event; history of an eating disorder; history of a condition (e.g., end stage renal disease, cancer, 
schizophrenia) or use of medications (e.g., lithium, steroids, anti-psychotics) that would affect weight 
measurement, for which weight loss is contraindicated, or might promote weight change; current 
participation in a weight loss trial and/or recent weight loss > 10%, and; investigator discretion for safety 
reasons. 
 
2.3 Sample size 
Sample size: We plan to recruite 448 males and females aged 18-65 years who have English language 
proficiency, and a BMI between 25-40 kg/m2. We plan to recruit a sample that is 30% male and 40% 
racial/ethnic minority. 
 
 Using the FactorialPowerPlan SAS Macro,1 we computed the sample size needed for a full 2x2x2x2x2 factorial 
design.  We expect a minimal difference between groups, defined as an effect size of 0.15.2 With a standard 
deviation estimate from a recent weight loss trial3 of 5 kg, and a within-participant correlation of 0.9, this 
translates into a 0.75 kg difference in weight loss at 6 months between groups given the comparison level of the 
intervention component and those groups with the default level of the intervention component (main effects). 
We determined that a total sample size of 282 subjects would be required to achieve an overall power of 80% 
to detect a 0.75 kg difference in weight loss. We conservatively assume 30% dropout at 6 months, so we inflate 
the sample size to 403. To obtain an equal number of participants in each treatment combination (condition), 
we further inflate this sample size to 448, which is a final sample of 14 participants in each of the 32 conditions. 
The main effects are then estimated with 224 participants receiving either level of each component. Likewise, 
pairwise interactions are based on comparisons of means for 224 participants who receive both or neither 
component compared to those who received only one. 
2.4 Data Acquisition 
 

 
Page 2 
Fill in all relevant information: 
Study design 
Factorial trial 
Data source/how the data were 
collected 
Primary data collection from participants in 
North Carolina 
Contact information for team member 
responsible for data 
collection/acquisition 
Sandy Askew 
sandy.askew@duke.edu 
Date or version (if downloaded, provide 
date) 
October 21, 2019 
Data transfer method and date 
Transferred from Box to CRU drive on 
November 11, 2019 
Where dataset is stored 
A shared Box folder called “Charge Data 
Cleaning” 
 
 
3 Outcomes, Exposures, and Additional Variables of Interest 
3.1 Primary Outcome(s) 
• 
The primary outcome is absolute change in weight from baseline to 6 months.  Weight is measured in 
duplicate by trained, certified staff. 
3.2 Secondary Outcome(s) 
• 
Absolute change in weight from baseline to 12 months. 
 
3.3 Other variables of interest. 
• 
Absolute change in weight from baseline to 3 months.  Will be included for statistical modeling purposes. 
• 
Engagement:  
 
3.4 
Primary predictors 
The primary predictors are the five text messaging intervention components listed in the table below.  
Detailed descriptions of these components are provided in Appendix A. 
 
Intervention component Default Level 
Comparator Level 
Motivational Messages 
Expert generated 
Self-generated 
Texting frequency 
Weekly 
Daily 
Reminders 
One 
Multiple 
Feedback 
Individual goal 
Summary Score 
Performance comparison 
Self 
Others (group) 
 
 
 

 
Page 3 
4 Statistical Analysis Plan 
 
Notes: Participants in the full-length pilot will be included in the main analysis, since they ended up 
being recruited right about when the full trial started, and were not actually used to fix bugs in the 
program.  In the primary analysis, those whose data is collected outside of the study window will be 
treated as missing for that time point.  Sensitivity analyses will be performed including such data. 
 
For each of the five components, participants’ weights and demographics will be summarized by 
levels of the component.  Continuous variables will be summarized using means, standard deviations, 
medians, quartiles, and ranges, and categorical variables will be summarized using counts and 
percentages. 
 
The primary outcome is absolute change in weight from baseline to 6 months.  We will estimate the 
main effects of each intervention component on the primary outcome and of all pairwise interactions 
of those components at each follow-up time point using a linear mixed effects model.  In order to 
estimate effects on weight change, the model will include as outcomes absolute weight at baseline and 
each follow-up time point. The model will include fixed effects for: time point (3 months, and 6 
months, and 12 months), the time-by-component and time-by-pairwise up to five-way interactions, 
and gender (the variable by which the randomization was stratified).  We do not include the effects of 
the components at baseline.  This constrains the baseline comparisons to be equal, which is 
appropriate in a randomized trial and increases power.4,5  The model will allow us to estimate weight 
change and percentage weight change at the interim time point (month 3) and final follow-up time 
point (month 12), but the main estimate of interest will be the five treatment indicators by month 6 
interaction.   
 
After examining the model, we will assemble a multicomponent intervention package.  If a component 
has a main effect on weight loss at 6 months greater than or equal to 0.7 kg (1.5 lbs), and no significant 
interaction with another component, then the superior level of the component will be retained for the 
intervention package.  Otherwise, if there is no significant main effect or interaction, the default 
(reference) level of the component will be retained.  We will reconsider inclusions based on the 
presence of large (effect ≥ 0.7 kg) interactions.  This decision making is based on the approach 
outlined in Collins et al.6  Although the secondary outcome of 12-month weight will not be used in the 
primary decision-making process, we may reconsider our inclusions if there is a large change in effect 
between 6 months and 12 months. 
 
Given the factorial design, we will use effect coding, rather than dummy coding, for analyzing the 
effects of the intervention components.7  If the sample size is equal per condition, all of the tests of 
main effects and interactions are uncorrelated—that is, the main effect of a condition is the same even 
if other treatment conditions and interactions are included in the statistical model.  Even with unequal 
sample sizes across conditions (as may occur with differential dropout by condition), if the imbalance 
is minor, the correlations between effects should be small.8 
 
Missing outcome data due to dropout or missing intermediate visits is expected to be at most 
30%. Since the mixed model will be fit using a full maximum likelihood method, we will be able to 
account for predictors of missingness in the model in order to obtain valid estimates of the main 
component effects, thanks to the property that the response can be missing at random (MAR) as 
defined by Little and Rubin.9 In practice, we will compare baseline characteristics of completers and 
non-completers. If we find that any covariates predict missingness, we will adjust for these variables 
in the model in order to obtain valid estimates. 
 
In addition, we will examine gender as a potential moderator, where those who answered “non-
binary” will be excluded from the analysis, given the extremely small numbers of participants who 

 
Page 4 
answered this way.  We acknowledge that we are not powered to detect moderators, but these results 
may be used to guide future studies. 
 
Engagement data will be summarized and displayed in a table. 
 
 
 

 
Page 5 
5 Table shells and proposed figures 
Potential format of table 1 (from Piper et al.10): 
 
 
Table 2. Potential format of regression results table (from Piper et al.) 
 
Another example of showing effects: 

 
Page 6 
 
 
 
 
 

 
Page 7 
6 References 
 
1. 
Dziak J, Collins L, Wagner A. FactorialPowerPlan SAS macro suite users’ guide. 2013. 
2. 
Pellegrini CA, Hoffman SA, Collins LM, Spring B. Optimization of remotely delivered intensive 
lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol. 
Contemp Clin Trials. 2014;38(2):251-259. 
3. 
Svetkey LP, Batch BC, Lin PH, et al. Cell phone intervention for you (CITY): A randomized, 
controlled trial of behavioral weight loss intervention for young adults using mobile technology. 
Obesity. 2015;23(11):2133-2141. 
4. 
Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis. 2nd ed. Hoboken, N.J.: Wiley; 
2011. 
5. 
Lu K. On Efficiency of Constrained Longitudinal Data Analysis Versus Longitudinal Analysis of 
Covariance. Biometrics. 2010;66(3):891-896. 
6. 
Collins LM, Trail JB, Kugler KC, Baker TB, Piper ME, Mermelstein RJ. Evaluating individual 
intervention components: making decisions based on the results of a factorial screening experiment. 
Transl Behav Med. 2014;4(3):238-251. 
7. 
Kugler KC, Trail JB, Dziak JJ, Collins LM. Effect coding versus dummy coding in analysis of data 
from factorial experiments. The Methodology Center, The Pennsylvania State University. 2012. 
8. 
Collins LM, Dziak JJ, Kugler KC, Trail JB. Factorial experiments: efficient tools for evaluation of 
intervention components. Am J Prev Med. 2014;47(4):498-504. 
9. 
Little RJA, Rubin DB. Statistical analysis with missing data. New York: Wiley; 1987. 
10. 
Piper ME, Fiore MC, Smith SS, et al. Identifying effective intervention components for smoking 
cessation: a factorial screening experiment. Addiction. 2016;111(1):129-141. 
 
 

 
Page 8 
7 Appendix A 
 
Motivational messaging (self- vs expert-generated) 
 
Self: As part of Charge, we’d like you to write some motivational messages to yourself. These messages will 
help you stay positive and encouraged. Your next step to get started is to write yourself a few messages to get 
you started. We will text these to you a few times a week.  
 
Expert-generated: As part of Charge, we’ll be sending you motivational text messages a few times a week. 
These messages were written by people who are experts in helping people lose weight, and are meant to help 
you stay positive and encouraged.  
 
Texting frequency (daily vs weekly) 
 
Daily: Every day, we will text you to ask how you did yesterday with each of your 4 Charge goals. The text will 
look like this: “Yesterday, did you: eat any red zone foods, drink any sugary drinks, eat 5+ fruits and vegetables, 
eat any sweet snacks?” 
You will reply to this message with your answers to each yes/no question - like this: 
“y, y, y, n” 
After we get your reply, we’ll send you personalized feedback and some tips/ideas about how to reach your 
goals. Taking a few seconds to reply to us every day helps us keep track of your progress over time – by doing 
that, we can give you the most personalized and helpful feedback. 
 
Weekly: Every week, we will text you to ask how you did with each of your 4 Charge goals. The text will look like 
this: “Last week, how many days did you: eat any red zone foods, drink any sugary drinks, eat 5+ fruits and 
vegetables, eat any sweet snacks?” 
You will reply to this message with your answers to each yes/no question - like this: 
“2, 3, 2, 1” 
After we get your reply, we’ll send you personalized feedback and some tips/ideas about how to reach your 
goals. Taking a few seconds to reply to us every week helps us keep track of your progress over time - by doing 
that, we can give you the most personalized and helpful feedback. 
 
Reminders (one vs multiple) 
 
One: If you don’t reply to the first text we send you each [day/week], we will text you one more time to remind you 
to track your progress. We recommend replying to the first text we send you, so you get it out of the way!  
 
Multiple: If you don’t reply to the first text we send you each [day/week], we will text you a few more times over 
the [day/week] to remind you to track your progress. We recommend replying to the first text we send you, so 
you get it out of the way! 
 
Feedback type (summary score vs individual goal) 
 
Summary score: When we send you feedback every [day/week] we will send one number, an overall score, 
that considers how you’re doing on all of your goals. 
 
Individual goal: When we send you feedback every [day/week], we will give you feedback on specific goals. 
You may not get feedback on how you’re doing on every one of your goals individually, but we’ll send you smart 
feedback based on how you’re doing over time.   
 
Comparison unit (self vs group) 
 

 
Page 9 
Self: The feedback we send you each [day/week] will take into account how you’ve been doing. The more 
[days/weeks] you track your goals, the better our feedback will be. For example, we may say “You’ve been 
getting better at meeting all your goals!” or “Looks like your progress is slowing on each of your goals”.  
 
Group: The feedback we send you each [day/week] will take into account how you’ve been doing compared to 
other people in Charge. For example, we may say, “Only a quarter of Charge participants are doing better than 
you are” or “Your scores have placed you in the top 10% of program participants”.  
 
 
Condition 
Frequency 
Motivational 
Messaging 
Reminders 
Feedback Type 
Comparison Unit 
1 
Weekly 
Self-generated 
One 
Summary Score 
Self 
2 
Weekly 
Self-generated 
One 
Summary Score 
Group 
3 
Weekly 
Self-generated 
One 
Individual Goal 
Self 
4 
Weekly 
Self-generated 
One 
Individual Goal 
Group 
5 
Weekly 
Self-generated 
Multiple 
Summary Score 
Self 
6 
Weekly 
Self-generated 
Multiple 
Summary Score 
Group 
7 
Weekly 
Self-generated 
Multiple 
Individual Goal 
Self 
8 
Weekly 
Self-generated 
Multiple 
Individual Goal 
Group 
9 
Weekly 
Expert-generated 
One 
Summary Score 
Self 
10 
Weekly 
Expert-generated 
One 
Summary Score 
Group 
11 
Weekly 
Expert-generated 
One 
Individual Goal 
Self 
12 
Weekly 
Expert-generated 
One 
Individual Goal 
Group 
13 
Weekly 
Expert-generated 
Multiple 
Summary Score 
Self 
14 
Weekly 
Expert-generated 
Multiple 
Summary Score 
Group 
15 
Weekly 
Expert-generated 
Multiple 
Individual Goal 
Self 
16 
Weekly 
Expert-generated 
Multiple 
Individual Goal 
Group 
17 
Daily 
Self-generated 
One 
Summary Score 
Self 
18 
Daily 
Self-generated 
One 
Summary Score 
Group 
19 
Daily 
Self-generated 
One 
Individual Goal 
Self 
20 
Daily 
Self-generated 
One 
Individual Goal 
Group 
21 
Daily 
Self-generated 
Multiple 
Summary Score 
Self 
22 
Daily 
Self-generated 
Multiple 
Summary Score 
Group 
23 
Daily 
Self-generated 
Multiple 
Individual Goal 
Self 
24 
Daily 
Self-generated 
Multiple 
Individual Goal 
Group 
25 
Daily 
Expert-generated 
One 
Summary Score 
Self 
26 
Daily 
Expert-generated 
One 
Summary Score 
Group 
27 
Daily 
Expert-generated 
One 
Individual Goal 
Self 
28 
Daily 
Expert-generated 
One 
Individual Goal 
Group 
29 
Daily 
Expert-generated 
Multiple 
Summary Score 
Self 
30 
Daily 
Expert-generated 
Multiple 
Summary Score 
Group 
31 
Daily 
Expert-generated 
Multiple 
Individual Goal 
Self 
32 
Daily 
Expert-generated 
Multiple 
Individual Goal 
Group 
 
8 Appendix B 
 
*Description of Track: Track was a 12-month weight loss intervention delivered between 2013-
2015 that utilized the iOTA framework. Similar to Charge, participants (n= 175 in the intervention 
arm) were asked to change 4 weight-related behaviors at a time and to report their progress via 
text message (or automated phone calls) every week. In Track, each participant was assigned 4 
goals to track at a time, in 8 week cycles. So some people tracked sugary drinks for the first Cycle 
(weeks 1-8) and some people tracked it in a different cycle, later in the study. We have self-

 
Page 10 
monitoring data for 175 participants for 1 year on the same goals as we are assigning in Charge. 
Track participants were patients at Piedmont Health with obesity and at least 1 obesity-related co-
morbidity.  
 
In the summary score + group comparison condition (in both self-monitoring conditions), we’ll 
calculate an average score across all 4 goals a participant is tracking each day or week.  
 
We will create a score from the *same 4 goals* as the participant has using the *mean score of 
each goal* for all participants who tracked it the same cycle week as the participant. This would 
mean we could include everyone who ever tracked “No Sugary Drinks” - whether they track it in 
Cycle 1, 3, or 5. We’d match the score to their cycle week - so if a Charge participant is in the 4th 
week of Cycle 2, they’d be compared to Track participants who ever tracked “No Sugary Drinks” in 
the 4th week of any cycle. 
 
We will calculate the following variables to use as referent data: 
For the people who get a summary score: 
a. 
Average summary score for each week (All participants, all goals) 
b. 
% of people who get each summary score for each week 
c. 
Mode for each summary score each week 
d. 
Median for each summary score for each week 
 
For people who get feedback on specific goals: 
a) the average score for each goal each week 
b) The percent of people who got each score for each goal each week 
c)  the mode for each individual goal each week 
d) the median for each goal score for each week. 
This allows us to analyze the data differently to provide feedback variety - we can tell 
people their percentile (you’re in the top 10%!) or how they’re doing compared to most 
other people, or how they are doing compared to the group’s average. 
 

 
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