Increasing Social Support for Weight Loss Through the Use of Social Gaming and Points: The Mobile Intervention for Food and Exercise (mLIFE) Study
Phase: NA
Conditions: Overweight and Obesity, Type2 Diabetes
Sponsor: University of South Carolina

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Protocol and Statistical Analysis Plan 
 
Document Type: 
Study Protocol and Statistical Analysis Plan 
Document Date: 
July 24, 2023 
Organization’s Unique Protocol ID: 
Pro00109784 
Brief Title: 
The Mobile Lifestyle Intervention for Food and 
Exercise Study 
Acronym: 
mLIFE 
Study Type: 
Interventional 
Official Title: 
Increasing Social Support for Weight Loss 
Through the Use of Social Gaming and Points: The Mobile Intervention for Food and 
Exercise (mLIFE) Study 
NCT Number: 
NCT05176847 
NIH Grant/Contract Award Number:  
1R01DK129302 

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Protocol Synopsis 
Significance and rationale 
Overweight and obesity are linked to chronic diseases like type 2 diabetes 
mellitus (T2DM). Weight loss helps prevent and manage T2DM. Traditional group-
based behavioral treatment for weight loss includes self-monitoring, physical activity, 
weight, and regular group meetings. So- cial support also plays a crucial role in group-
based treatment, especially when it combines em- pathy, social support, and healthy 
competition. 
mHealth delivery offers advantages like cost-effectiveness and scalability. It also 
allows for inte- grating novel approaches to sustain motivation and engagement, such as 
social gaming to reward behaviors like self-monitoring and social support. Gamifying an 
mHealth behavioral weight loss intervention holds promise for promoting and sustaining 
social support, but research on its direct effects is limited. Despite commercial health 
apps using gamified approaches, no adult weight loss interventions have used gamified 
rewards or points, and no studies have evaluated the im- pact of reward type on desired 
outcomes. 
Pilot study main results 
To explore gamification’s role in promoting social support for weight loss, 
our team developed a mobile app that rewards social support through social gaming. 
The Social Pounds Off Digitally study, a three-month randomized weight loss 
intervention, delivered remote content via twice- weekly podcasts. Experimental 
group participants (n=26) lost more weight (-5.3 kg) than the standard app group 
(n=25; -2.2 kg; p=0.02). Total points earned predicted % weight loss (p=0.01). This 
diverse study sample (39% African American) represents one of the more inclu- sive 
digital weight loss intervention studies 
Study aims 
The goal of the present study is to examine the mLife intervention in a long-term 
study and to isolate the use of points to gamify the intervention in order to ensure that 
use of social gaming leads to improvements in social support and continued weight loss. 
 
Primary aims: 
Aim 1: Determine if the mLife app plus points intervention (mLife+points; 
points for provision and receipt of social support) produces significantly more weight 
loss at 12 months than the mLife without points (mLife) among 240 adults with 
overweight or obesity and ≥3 T2DM risk factors. 
Hypothesis aim 1: The mLife+points group will lose more weight than the mLife group. 
 
Aim 2: Examine the differences in social support provision and receipt 

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between groups at 12 months. 
Hypothesis aim 2: That the mLife+points group will have greater levels of social support 
provi- 
sion and receipt (both perceived and received) than the mLife. 
 
Secondary Aims 
Examine usage patterns over time (e.g., do points sustain engagement and promote 
weight loss maintenance?), potential mediators (e.g., engagement/self-monitoring) 
and moderators (demo- graphic factors such as sex, race, age), the usability and 
acceptability of the interventions and the association of social support provision/ 
receipt and psychosocial factors (e.g., motivation, enjoy- ment) with weight loss. 
Create and test predictive models that can be applied to future grant applications. 
 
Overview of Intervention 
This is a one-year remote intervention, randomized trial that will be conducted in 
two cohorts. Participants will be randomized to one of two groups: 1) mLIFE+points 
(n=120) or 2) mLIFE (n=120). Both groups will receive the same intervention, but in 
order to isolate the impact of points/social gaming, the mLIFE+points group will receive 
points for engaging in social support- related behaviors and the mLIFE will not. 
All participants will be asked to track all their meals daily via the mLIFE 
App, use a Fitbit to track their physical activity, and use a Fitbit scale to track their 
body weight. Also, all partici- pants will receive twice weekly podcasts and daily in-
app tip of the day (based on Social Cogni- tive Theory and modeled from the 
Diabetes Prevention Program). The mLIFE App will also en- courage and facilitate 
social support among participants. The intervention will last 12 months. 
 
Overview of assessments 
Potential participants will be directed to a study website to learn more about the 
study and com- plete a screening questionnaire. If they qualify, they’ll be invited to 
an orientation session where they’ll learn more and sign a consent form. Participants 
will then complete online surveys mea- suring psychosocial variables and diet, and 
anthropometric data will be collected. Those who complete all baseline assessments 
will be randomly assigned to either the mLIFE+points or mLIFE group using a 
computer program allocation sequence, stratified by sex and baseline BMI (to ensure 
equal distribution of sex and weight classes among the two groups). All participants 
will complete assessments at baseline, 6, and 12 months. The study will involve two 
cohorts, each with 120 participants, staggered by 12 months. 

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Trial registration 
The study was pre-registered on http://ClinicalTrials.gov (NCT05176847) by Dr. 
Gabrielle Turn- er-McGrievy (PI), Project coordinator (Dr. Carolina Delgado-Diaz) 
has access to the study dash- board as well. 
 
IRB Review and Approvals 
This study was initially approved by the University of South Carolina IRB on 
April 26th, 2021 (Pro00109784). 
 
Methods and Procedures 
Recruitment and Enrollment Plan 
Population 
The objective is to enroll a total of 240 participants (120 participants in Cohort 1 and 120 
partic- ipants in Cohort 2). Recruitment for Cohort 1 commenced in February 2022, while 
recruitment for Cohort 2 commenced in February 2023. 
 
Inclusion criteria 
Assessed through an online screening survey and/or a telephone screening 
conversation. 
• 
Be between the ages of 18-65 years 
• 
Have a Body Mass Index between 25- 49.9 kg/m2 
• 
Have at least 3 risk factors for type 2 diabetes identified by the NIDDK 
• 
Have an Android or iPhone and up-to-date mobile data plan 
• 
Not being pregnant or planning on becoming pregnant during the study, or 
breastfeeding 
• 
Not participating in another weight loss program 
• 
Be free of major health or psychiatric diseases, drug or alcohol dependency. 
 
Exclusion Criteria 
Assessed through an online screening survey and/or a telephone screening 
conversation. 
 Women that are pregnant, have been pregnant in the last 6 months, anticipate 
becoming pregnant in the next 24 months, or currently breastfeeding. 
Women who are pregnant should not be pursuing weight loss and should be 
under the direct care of a physician. Therefore, women who are pregnant or 

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who are anticipating they might be pregnant should not partici- pate in this 
study. If a woman becomes pregnant during the study, she will be advised to 
con- sult her care provider and will be dropped from the study. 
 Someone with an eating disorder (which will be screened with the Eating 
disorder Screen for Primary care [ESP]).17 If a participant has an eating 
disorder, they will be given the NIH brochure with information about eating 
disorders and contacts for help. 
 Currently participating in a weight loss program or taking weight loss 
medications. Partici- pants can be included in the study if they are trying to 
lose weight on their own, without any medication. 
 Individual recently lost a significant amount of weight (>10lbs in the last 6 
months). 
 Current use of medications that may significantly impact blood glucose 
(i.e.metformin, steroids) 
• 
Diagnosed with diabetes 
• 
FOR SECOND COHORT: Currently taking any of long term weight loss 
medications, 
in- 
cluding 
Bupropion-naltrexone 
(Contrave); 
Liraglutide 
(Saxenda); 
Orlistat 
(Xenical, 
Alli); 
Phentermine-topiramate 
(Qsymia); 
Semaglutide (Wegovy); Setmelanotide (Imcivree). 
 
Recruitment Strategies 
Participants were recruited nationwide, primarily via social media (Facebook and 
Instagram), television interviews, researchmatch.org, promotional materials (i.e., 
fliers and brochures), in- person targeted community outreach efforts (i.e. 
neighborhoods, churches, libraries, employers, recreation commissions, and 
coalitions). The recruitment process for the cohort 1 was launched on February 2022, 
and on February 2023 for the cohort 2. A waiting list was kept up to date dur- ing the 
intervention delivery of cohort 1. 
All advertising strategies included a brief description of the study with an 
invitation to inquire for more details. Those inquiring will be directed to the study 
website: www.mlifestudy.org. All potential participants will be prompted to 
complete the online eligibility screening administered via RedCap, using the public 
link of the online survey. 
 
Recruitment and Enrollment report 
Recruitment and enrollment (as well as retention) will be reported weekly during 
the recruitment timeframe using Consolidated Standards of Reporting Trials 
guidelines. Weekly data will be pulled from the RedCap recruitment projects using 
the reports feature. The project manager will be responsible for tracking potential 

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participants who contact the study office via phone or email. This involves reviewing 
the weekly information registered in the screening report from RedCap. Key metrics 
to track include the number of contacts, referral sources (e.g., social media, commu-
nity events), the number of individuals screened online and then by phone, the 
number of eligible participants, and the number of participants enrolled in the study. 
 
Training Plan 
All staff working on participant recruitment and retention, assessment, and/ 
or intervention are required to complete both Good Clinical Practices Training 
(available at: https://www.sbm.org/ training/good-clinical-practice-for-social-and-
behavioral-research-elearning-course), and Social and Behavioral Citi Training 
(available at: https://about.citiprogram.org/en/course/human-sub- jects-research-2/). 
Certificates for all personnel are uploaded to OneDrive/mLife Study/IRB/Citi 
training certificates, and kept up to date. 
The project coordinator sets reminders to personnel who are required to 
complete the refresher and update their certification. 
Any staff or students participating in the screening process must be trained by a 
Project coordina- tor. This training will include observation of phone screenings 
conducted by experienced staff and being observed by the Project Manager or 
experienced staff in conducting a phone screening. 
All training was conducted online, and recordings were available as part of 
the personnel training and refreshers. Tutorial videos are listed in the document for 
each section of the current document. 
 
Guidelines for Interacting with participants 
Maintain a Professional yet Friendly Tone: All online interactions, whether 
via email, text, or other digital platforms, should be conducted with a positive, 
approachable, and respectful tone. A friendly and warm manner helps participants 
feel at ease and ensures their willingness to contin- ue in the study. Even when 
conveying important or technical information, keep the language simple and clear to 
avoid confusion. 
 
Timeliness and Responsiveness: Respond to participants’ communications 
promptly, ideally within 24-48 hours. Acknowledge receipt of any participant 
submissions (e.g., completed sur- veys, questions, or concerns) to confirm their 
participation. If there will be a delay in responding, inform the participant in advance 
and apologize for any inconvenience caused. 

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Assure Participants’Confidentiality: Ensure that participants understand that any 
personal or sensitive information they share online will be treated with utmost 
confidentiality. Reassure them that their data will be anonymized for analysis, 
meaning their names will not be associated with any data used in the study. Clearly 
communicate that any documents containing personal infor- mation (e.g., consent 
forms) will be securely stored in accordance with privacy guidelines. Re- mind 
participants not to share sensitive health information over unsecured platforms (e.g., 
via text messages). Refrain from communicating with any participant using your 
personal email or phone line; instead, utilize the University’s resources. Do not 
discuss any participant’s medical records or private details with anyone outside the 
research setting. When conducting a call with a participant, ensure that you are in a 
private location where the information shared cannot be overheard or recorded by 
any external individuals. 
 
Be respectful and Sensitive: Respectful communication is key to maintaining a 
positive rapport. Always be mindful of the tone and choice of words. Since you are 
working with participant with overweight or obesity, ensure that all communications 
avoid comments or language that could be construed as judgmental or insensitive 
regarding body image, weight, or health. Avoid jokes, sar- casm, or casual remarks 
related to body image, and ensure all content is supportive and consider- ate. 
Show respect for their time by being punctual. Log in to all necessary platforms 
(RedCap, Signup Genius, OneDrive file) for contacting and tracking participants at 
least 5 minutes before meetings. This ensures you’re ready to initiate phone or 
Zoom calls without delays. If a follow- up is required, connect the participant with 
the project manager or research assistant. Maintain a professional appearance, 
demeanor, and speech at all times. 
 
Provide Clear Instructions and Information: When asking participants to 
complete tasks or sur- veys online, provide clear, concise, and easy-to-follow 
instructions. Ensure that links, access codes or attachments are easily accessible and 
functional. Allow participants enough time to re- view instructions and provide 
information on what is expected from them. If there are any up- coming tasks or 
deadlines, communicate them well in advance and more than once. All surveys 
should be programmed to have 2 reminders for completion in Redcap. 
 
Offer Technical Support: Be proactive in offering assistance for any 
technical issues that partici- pants may face with online tools or platforms. Provide 
clear instructions for troubleshooting and offer additional resources, such as the 
Fitbit user manual and FAQ sites for their devices. Ensure participants know how to 

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reach out if they encounter problems while participating in the study by clicking in 
the “help request” feature located in the dropdown menu of their mLife account. 
Also, advise them to save your email address and the study coordinator’s, Dr. 
Carolina Delgado: delgadoc@mailbox.sc.edu. 
 
Personalized Communication: Address participants by their preferred names 
to create a more personalized and friendly experience. When sending bulk messages, 
ensure that the message is addressed to them directly, and the content is tailored to 
the specific participant’s status in the study (e.g., reminders, next steps). Refrain 
from using the BCC feature in your email; use mail merge features in a word 
processor. Personalized communication enhances rapport and ensures that 
participants feel valued. 
 
Reassure and Encourage Participation: Regularly express gratitude to 
participants for their in- volvement in the study, emphasizing how much their 
participation is appreciated. Encourage open communication by reassuring 
participants that they can reach out at any time if they have questions or concerns. 
Ensure that participants feel confident and valued throughout their in- volvement in 
the study. 

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Study flow diagram. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Screening Process 
 
Steps to determine eligibility 
1. 
Potential participants are directed to the study’s website (www.mlifestudy.org/) to 
learn more information and complete a screening questionnaire. Phone numbers and 
e- mail addresses are included on all recruitment material. 
2. 
All screening processes is conducted using RedCap, project “mLife recruitment”. 
3. 
The project manager will access the record status dashboard and review one by one 
of the completed online screening surveys . Once the online screener is reviewed, 
the “verification form” will determine the eligibility of each individual (eligible, 
non-eli- gible, or uncertain). The verification form will be marked as complete if 
eligible or non-eligible and unverified if the eligibility is uncertain. 
4. 
The Project Manager will review each “unverified” verification form and consult 
with the PI as needed or add a note to gather additional information during the phone 
screening. Once the decision is made, the Project Manager will mark “complete” the 
verification form. All verification forms will be reviewed by the project manager and 
set as “complete”. The reasons participants are not eligible to enroll in the study are 
listed below and should be registered in the verification and enrollment forms. 
5. 
A notification and alert are set in RedCap to automatically send the invitation to 
sign up for a phone screening to all participants marked as “eligible” or “uncertain” 
in the “complete” verification forms. 
6. 
The phone screener should be conducted within a week of the online screener 
comple- tion date. RAs will use the phone screening form to conduct a phone call 
based on de- termining each person’s eligibility. Based on the information gathered 
from the partic- ipant, at the end of the phone screen, the RA will determine the 
participant’s eligibility and make either one of the following decisions: 
A. If the person is eligible, mark the phone screener as “complete” and invite them 
to sign up for an orientation meeting. 
B. If the person is ineligible, mark the phone screener as “complete” and inform 
them of their ineligibility. 
C. If the person’s eligibility is uncertain, mark the phone screener as “unverified” 
and inform them that the decision will be made soon. They will be contacted by 
the re- search manager. 
7. 
The project manager will access the record status dashboard and review one by one 
of the completed and unverified phone screeners. Once the phone screener is 
reviewed, the “enrollment” form will be used to inform of the individual’s eligibility. 
If the per- son is mark as eligible, the participant will immediately receive an email 
(welcome to the study letter), followed by a text message to confirm the date/time of 
the orientation meeting. Contrary, if the person is not eligible to participate, they 

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immediately receive an automatic email informing them of their ineligibility. If the 
criteria for no inclusion is either diabetes or an eating disorder, additional resources 
to help are provided. 
 
Orientation Session 
We intend to invite at least 155 individuals to the orientation session for a cohort of 120 
participants. This assumes a 20% attrition rate between invitation and baseline measurements. 
All par- ticipants must attend the virtual orientation session to receive study details and sign 
the consent form. Each session will be conducted via Zoom, lasting 1 hour. 
 
Schedule per cohort 
Cohort 1, May 2022 (total of 11 sessions) 
May 16, 2022; 10:30 – 11:30 a.m.; 5:30 - 6:30 p.m.; 7:30 - 8:30 p.m. 
May 17, 10:30 – 11:30 a.m.; 5:30 - 6:30 p.m.; 7:30 - 8:30 p.m. 
May 18, 10:30 – 11:30 a.m.; 5:30 - 6:30 p.m.; 7:30 - 8:30 p.m. 
May 19, 10:30 – 11:30 a.m.; 5:30 (makeup sessions) 
 
Cohort 2, May 2023 (total of 11 sessions) 
May 8, 10:30 – 11:30 a.m.; 5:30 - 6:30 p.m.; 7:30 - 8:30 p.m. 
May 9, 10:30 – 11:30 a.m.; 5:30 - 6:30 p.m.; 7:30 - 8:30 p.m. 
May 10, 10:30 – 11:30 a.m.; 5:30 - 6:30 p.m.; 7:30 - 8:30 p.m. 
May 11, 10:30 – 11:30 a.m.; 5:30 pm(makeup sessions) 
 
Prior to orientation procedures: 
1. Longitudinal project for each cohort is set up in RedCap (data collection). The first data 
col- lection instrument is the contact information form, which public link is shared at the 
begin- ning of the orientation meeting. This form will be used for attendance to the 
orientation, and it will determine the participant record ID number. A corresponding 
ASA-24 login has been assigned to each record. 
2. Two emails and then one phone/text message reminder of their scheduled orientation will 
be sent to all participants. The last email must include the Zoom link and a PDF copy of 
the study’s informed consent for participants to read prior to attending the meeting. 
3. A database with the list of the participants scheduled per session will be shared in 
OneDrive, and will be used for attendance tracking. 
4. All orientation materials (presentations, videos, databases, and forms) are stored in 
One- Drive, see below 

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Orientation Agenda 
1. Begin the Zoom meeting 5 minutes before the scheduled orientation time. Invite participants 
to join the room. During the opening video and chat, share the survey link to the contact 
infor- mation form 
2. Tracking of attendance 
3. Intro of the team using a video clip. 
4. Dr. Turner McGrievy, the principal investigator, delivers a welcome message. In this message, 
Dr. McGrievy provides a brief overview of USC, our research, the study’s goals, and 
introduces the concept of randomization and its potential impacts of dropouts. 
5. Show a video clip titled “A Day in the Life of the mLife Study” to introduce the study’s inter-
vention components. 
6. Research assistant informs participants that they will be divided into small groups, and a staff 
member will join each group. During the next 10 minutes, the group will engage in reflection 
and share their thoughts. 
7. Overview of mLife activities, assessments, and the overall timeline. Invite participants to join the 
breakout rooms for Q&A. 
8. Questions and answers session. Questions should be posted in the room’s chat, and the staff 
member in each small group will lead the session. Once all participants’ answers are addressed, 
they are invited to check their email for the link to their informed consent (IC). Participants 
who decide to participate should sign the form, and a verification window will be accepted 
before submitting. 
9. Explanation of the next steps: baseline assessment and training sessions. Each assessment 
component (survey, dietary recalls, physical activity, body weight, and anthropometric and 
blood pressure measurements) has a tutorial video that will be shared with participants as we 
request each component. 
10. Key items and dates. A journey 
 
Informed Consent 
Participants receive a pdf copy of the consent form prior to attending an orientation session to 
learn more about the study. Participants will be given a chance to ask questions at that time and will 
be asked to sign the consent as described in the orientation procedure. If participants would like 
more time, they may read it at a later time and, using the electronic format, they will sign it before 
they enroll in the study. The IRB approved the last version of the IC on 01-18-2022 is used. 

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Randomization Procedure 
Participants were randomized to a gamified (mLife+points) or non-gamified (mLife) version 
of the mLife mobile weight loss intervention where provision of social support was incentivized 
by providing points for engaging in social support activities (for the mLife+points group) or not 
re- ceiving points for social support activities (mLife group). 
Participants are randomly assigned once 50% of the baseline assessments are completed 
(either the baseline survey or the three dietary recalls). A computerized blocks system, 
stratified by race (Black, Other) and sex, is used to ensure equal distribution among groups 
within each co- hort. Brent Hutto generates a random list of two groups (0s = Standard, 1s = 
mLife) in blocks of 10 or 4. Separate blocks are created for women and men, as well as white 
and non-white partici- pants, this results in 15 blocks of 10 for non-white women, 30 blocks of 
10 for white women, 3 blocks of 5 for non-white men, and 5 blocks of 4 for white men. 
 
As participants complete 50% of the assessment, a blind staff member uses the demographic 
data report from RedCap to identify each participant by gender and race add the participant’s ID 
number to the next available spot on the blocks. The group alloca- tion will then be recorded in 
the RedCap project under the randomization form (randomization event). Participants will not 
be informed of their group assignment but will be provided with their choice of meeting times 
and days for the training session. On the day of randomization, par- ticipants will be contacted 
and asked to select the time and date they plan to attend. The group allocation will be revealed 
at the first group meeting, after all baseline assessments have been completed. Since the 
training sessions are scheduled by group, the randomization process must occur before inviting 
participants to the training meeting. 
 
Participant Status Updates 
The project manager is in charge of updating the participant status. The following procedure en-
sure efficient and effective updates of participant status, accurately documenting reasons for 
dropout. The steps described below are completed if a dropout occurs during the intervention 
timeframe. 
 
Initiating Status Update: 
Once a participant informs a team by using any of the retention strategies that they wish or 
need to drop out, the change of status protocol is activated. The staff member receiving the 
informa- tion immediately contacts the project manager via email, who is responsible for the 
following steps. 

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Communication Process 
The project manager reaches out to the participant via email or text message to schedule a 
phone call. The purpose of the call is to gather information from the participant about the 
reasons for their dropout, if they wish to share. The manager may also offer resources or 
alternatives if rele- vant. If the initial contact is incomplete, they will attempt a second and final 
contact with the par- ticipant via email in two weeks. If no response is received, the manager 
will consider the partici- pant to have “dropped out” due to personal reasons. If a change of 
status takes place it is docu- mented. 
 
Report 
The project manager reports any changes in the status of participants in the “participants status” 
form of the RedCap project. The report in the form includes documenting: 
- 
whether the withdrawal of the participant resulted from a decision by the participant or 
by the investigator (exclusion), and the reasons for the withdrawal, if known. 
- 
whether the withdrawal was from all components of the research study or just the 
primary interventional component (assessment only). 
- 
Note all communications and documentation in the notes section of the form, make sure it 
is complete, accurate, and contains all pertinent dates relating to events that resulted in the 
withdrawal of the participant, especially the date of withdrawal from your research study. 
Participant status definitions 
 
Status 
Definition 
Report 
Withdraw 
When a participant decides to withdraw from all 
com- ponents of a research study. The study’s 
Manager must discontinue research activities 
involving the partici- pant's participation such as: 
• 
Interacting or intervening with the 
participant in order to obtain data about for 
the research study. 
• 
Obtaining tracking data from FitBit, mLife app 
must be inactivated. 
Complete the 
form 
immediately. 
Inactivate mLife 
account 
Highlight 
partici- pant ID 
in the ASA24 
accounts 
file. 

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Excluded 
When a participant reports a change in their health 
Complete the 
sta- tus or if an exclusion criterion becomes apparent, 
form 
the study's manager must discontinue any research 
immediately. 
activi- ties involving the participant. The participant 
Inactivate mLife 
should be informed of this decision promptly. 
account 
Examples of exclu- sion criteria that may arise after 
Highlight 
randomization include pregnancy, the decision to take 
partici- pant ID 
weight loss medication, or the onset of a major health 
in the ASA24 
condition that prevents the participant from 
accounts file. 
complying with the intervention. 
Participants are made aware of these criteria at the ori- 
entation and training meetings to prevent any misunder- 
standings or disruptions during the study. 
Assessment 
Sometimes, a participant may wish to withdraw 
Complete the 
only 
from the primary interventional component of the 
form 
study but is still willing to participate in other 
immediately. 
research activities that are outlined in the IRB- 
Highlight 
approved protocol and in- formed consent 
partici- pant ID 
document. In such cases, these partici- pants will 
in the ASA24 
only be contacted for data collection at the follow- 
accounts file as 
up assessments. 
“AO”. 
Turn text and 
no- tifications 
from the APP 
off. 
Lost to 
Reported at the end of the trial for each of the 
Complete the 
follow- 
assess- ments. Participants who were enrolled in 
form after 
up 
the trial but  are  unavailable  during  follow-up 
incen- tives 
assessments. 
distribution. 
Inactive mLife 
account (do not 
remove the link 
to FitBit) 

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Completed 
Reported at the end of the trial: Participants who com- 
Complete the 
the study 
pleted the 12-month assessment with a body weight re- 
form after 
port. Individuals who participated in the 12-month as- 
incen- tives 
sessment but did not have an objective report of their 
distribution. 
body weight were determined as “Assessment Incom- 
Inactive mLife 
plete”. 
account (do not 
remove the link 
to FitBit) 

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Training Session 
This online training meeting launches the mLife intervention, equipping participants with skills 
to access and use the mLife app. Participants learn their group (mLife or mLife+), download 
the app, and link their Fitbit profile. Within the app, they edit their first name to match their 
pre- ferred username, keeping their last name and email unchanged. Other participants’ 
usernames display their chosen first name and the initial of their last name. Last names are not 
displayed for privacy. Sessions are limited to 1.5 hours. 
 
Schedule per cohort 
Cohort 1, June 2022 
June 28, 10:30 – 12:00M (Control group); 5:30 - 7:00PM (mLife+points group) 
June 29, 10:30 – 12:00M (mLife+points group); 5:30 - 7:00PM (Control group) 
June 30, 5:30 - 7:00PM (mLife+points group); 7:30 - 9:00PM (Control group) (makeup 
sessions) 
Cohort 2, July 2023 
July 5, 10:30 – 12:00M (Control group); 5:30 - 7:00PM (mLife+points 
group) July 6, 10:30 – 12:00M (mLife+points group); 5:30 - 7:00PM 
(Control group) 
July 7, 10:30 - 12:00M; 5:30 - 7:00PM (mLife+points group); 7:30 - 9:00PM (Control 
group) (makeup sessions) 
 
Prior to training meeting procedures 
 
1. 
All of the participant’s mLife accounts are created in a bulk upon completion of 
the randomization process. 
2. 
Signup genius is setup to invite participants for the training meeting. Two signup 
are required as the training meeting are different per group (social support 
gamification). 
3. 
Participants are contacted via automatic email sent from RedCap on the day they are 
randomized and accounts in the mLife application are created. The message 
includes the notification of the welcome to the study package shipping and the link 
to SignUp- Genius for the participant to book the training meeting. 
4. 
Approximately 1h prior to each session, an activation link to the mLife account will 
be sent from the mLife staff site. A database with the list of the participants 
scheduled per session will be shared in OneDrive (training meeting materials 
folder). It will be used for preparation and attendance purposes. 
5. 
An attendance form for the training session is included in the longitudinal project 
in RedCap for each cohort (training event). 

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Training Meeting Agenda & Notes for Study Personnel 
 
1. Only participants who have completed ALL components of the assessment are confirmed 
to attend the training meeting. 
2. Training meetings are conducted LIVE; the recording of screenshots and in-app tasks are 
used to conduct and time the meeting. 
3. The Principal Investigator opens up the session with a welcome back message and 
introduces the mLife team. 
4. Demo (live + screenshots) of activation of mLife account and link of Fitbit - participants 
to complete a task in-app (15 min). 
5. Q/A in breakout rooms. A staff member will be assigned to each group. At this point, 
participants will be allowed to share their screen. 
6. Demo of intervention components (live + screenshots of mLife app with comments related 
to the explanations) - include explanations of the graphs for self-monitoring (PA, BW, and 
Kcals), emphasis on the definitions and importance of each. 
7. Demo of diet logging (tutorial video). Participants complete one item/meal log. Reminder 
set as a text message at 8 p.m. (participants’ time zone) (10 min) 
8. Demo of tips of the day and podcasts access (live + screenshots). Participants "read" the 
available tip of the day. The first podcast should be available for them to listen to and 
mark as listened. 
9. Demo of Social support activities (tutorial video). Demo of outreach message. Partici-
pants write their first request for support and/or rate a response. They like someone's PA, 
diet logging, or BW. For the control group, review the checklist. For the +Points group, 
review the points system and leaderboard, emphasizing its importance in weight loss. 
10. Q/A in breakout rooms. A staff member will be assigned to each group. At this point, 
participants will be allowed to share their screen. 
11. Key items and dates. A journey 
Notes: 
• 
At the end of the meeting, ALL attendees must have their mLife account active and Fitbit 
devices synchronized to our site. A staff member will track this procedure via the mLife staff 
site. 
• 
Tutorial videos for each section of the app with a feedback survey (within the RedCap project 
/ training session event) will be shared with the participants via e-mail immediately after their 
meeting. 
• 
Three days after the training meeting, a handout with recommendations for physical activity 
and caloric intake limit will be sent to each participant via email. The cutoff points on 
baseline body weight for caloric intake limit (handout) are: 1500 kcal/day for participants 
weighing ≤248 lbs; 1800 kcal/day for participants weighing ≥ 249 lbs. 

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20 
 
Assessments 
Participants’ assessments will be conducted at baseline, 6, and 12 months of the intervention. 
The following table and cited references describe the surveys and measurements conducted at 
each time point: 
 
Instrument 
BL 
6 
mo 
12 
mo 
Demographic, social support and potential mediators/moderators 
Demographic and socioeconomic status 
Demographic variables 
X 
Socioeconomic status variables, use of nutrition assistance programs, environ- mental 
changes 
X 
X 
X 
Current medications 
X 
X 
X 
Social support provision, receipt and enjoyment 
Number of times a person completes a social support-related activity (SS provi- sion) 
X 
X 
Adapted Multidimensional Scale of Perceived Social Support Scale (MSPSS) – (SS 
perceived)1; 2 
X 
X 
Ratings each participant gives to the social support provided to the after they re- quest 
support (SS perceived) 
X 
X 
Total number of times other participants provided support to the individual (SS receipt) 
X 
X 
EGameFlow (enjoyment)3 
X 
X 
User engagement and user burden 
User Engagement Survey* (adaptation)4 
X 
X 
X 
User Burden Scale* (adaptation)5 
X 
X 
X 
Self-efficacy and -regulation and motivation 
Weight Efficacy Life-Style Questionnaire (WEL-Q)6 
X 
X 
X 
Treatment Self-Regulation Questionnaire (TSRQ)7 
X 
X 
X 
Potential drivers of weight loss 
NCI’s Automated Self-Administered 24-hour Dietary Recall (ASA24®) – 3 unannounced 
recalls – two weekdays, one weekend day)8; 9 
X 
X 
X 

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21 
 
Physical Activity (FitBit tracker) – minutes per week of MVPA (min:10h/d, 3 
valid days)10; 11 
X 
X 
X 
Exercise Vital Sign Questionnaire12; 13; 14 
X 
X 
X 
The Stanford Leisure-Time Activity Categorical Item (L-Cat), short version15; 16 
X 
X 
X 
Physiological and anthropometric measures 
Height (self-report) / weight (FitBit Aria Scale)17; 18 
X 
X 
X 
Hip and Waist circumference (self-report). 
X 
X 
X 
T2DM (Type 2 Diabetes Mellitus) risk factors (risk score 0 – 10) 
X 
X 
X 
Self-monitoring adherence and study compliance/responsiveness 
Monthly survey (self-monitoring) 
X 
X 
Adherence to FitBit devices usage (mLife app – rewards or points) 
X 
X 
Adherence to self-monitoring diet (mLife app - logging ≥2 eating occasions per 
day) 
X 
X 
Use of intervention components (mLife app - use of all intervention 
components) 
X 
X 
Factors that may affect compliance: differential dropouts and reasons to discon-
tinue the study 
X 
X 
Factors that may affect compliance: assessment of major life events 
X 
X 
 
ASSESSMENTS TABLE CITATIONS: 
1. 
ZIMET, G. D. et al. Psychometric characteristics of the Multidimensional Scale of Perceived Social 
Support. J Pers Assess, v. 55, n. 3-4, p. 610-7, 1990. ISSN 0022-3891. Disponível em: < https:// 
www.ncbi.nlm.nih.- gov/pubmed/2280326 >. 
2. 
SHUMAKER, S. C. et al. Psychometric Properties of the Multidimensional Scale of Perceived Social 
Support in Patients With Heart Failure. J Nurs Meas, v. 25, n. 1, p. 90-102, 04 01 2017. ISSN 1945-7049. 
Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/28395702 >. 
3. 
FONG-LING FU AND RONG-CHANG SU AND SHENG-CHIN, Y. EGameFlow: A scale to measure learn-
ers’ enjoyment of e-learning games. Computers & Education, v. 52, n. 1, p. 101-112, 2009. ISSN 
0360-1315. Disponível em: < https://www.sciencedirect.com/science/article/pii/S0360131508001024 >. 
4. 
PELLETIER, D. L. et al. Nutrition agenda setting, policy formulation and implementation: lessons from 
the Mainstreaming Nutrition Initiative. Health Policy Plan, v. 27, n. 1, p. 19-31, Jan 2012. ISSN 
1460-2237. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/21292709 >. 
5. 
SUH, H. et al. Developing and Validating the User Burden Scale: A Tool for Assessing User Burden in 
Computing Systems. Proceedings of the 2016 CHI Conference on Human Factors in Computing 
Systems. San Jose, California, USA: Association for Computing Machinery: 3988–3999 p. 2016. 
6. 
CLARK, M. M. et al. Self-efficacy in weight management. J Consult Clin Psychol, v. 59, n. 5, p. 
739-44, Oct 1991. ISSN 0022-006X. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/1955608 
7. 
LEVESQUE, C. S. et al. Validating the theoretical structure of the Treatment Self-Regulation 
Questionnaire (TSRQ) across three different health behaviors. Health Educ Res, v. 22, n. 5, p. 691-702, 
Oct 2007. ISSN 0268-1153. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/17138613 >. 
8. 
ANDERSON, K.; BURFORD, O.; EMMERTON, L. Mobile Health Apps to Facilitate Self-Care: A Qualita-
tive Study of User Experiences. PLOS ONE, v. 11, n. 5, p. e0156164, 2016. Disponível em: < https:// 
doi.org/ 10.1371/journal.pone.0156164 >. 

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9. 
TURNER-MCGRIEVY, G. M.; HALES, S. B.; BAUM, A. C. Transitioning to new child-care nutrition 
poli- cies: nutrient content of preschool menus differs by presence of vegetarian main entrée. J Acad Nutr 
Diet, v. 114, n. 1, p. 117-23, Jan 2014. ISSN 2212-2672. Disponível em: < https://www.ncbi.nlm.nih.gov/ 
pubmed/ 
24144990 >. 
10. 
YAO, J. et al. Number of daily measurements needed to estimate habitual step count levels using wrist-
worn trackers and smartphones in 212,048 adults. Sci Rep, v. 11, n. 1, p. 9633, 05 05 2021. ISSN 
2045-2322. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/33953288 >. 
11. 
LAWHUN COSTELLO, V. et al. Impact of the COVID-19 Pandemic on Objectively Measured Physical Ac-
tivity and Sedentary Behavior Among Overweight Young Adults: Yearlong Longitudinal Analysis. JMIR Pub-
lic Health Surveill, v. 7, n. 11, p. e28317, 11 24 2021. ISSN 2369-2960. Disponível em: < https:// 
www.ncbi.nlm.nih.gov/pubmed/34665759 >. 
12. 
QUILES, N. N.; MCCULLOUGH, A. K.; PIAO, L. Validity and Reliability of the Exercise Vital Sign 
Ques- tionnaire in an Ethnically Diverse Group: A Pilot Study. J Prim Care Community Health, v. 10, p. 
2150132719844062, 2019 Jan-Dec 2019. ISSN 2150-1327. Disponível em: < https:// 
www.ncbi.nlm.nih.gov/ pubmed/31044638 >. 
13. 
KUNTZ, J. L. et al. Validity of the Exercise Vital Sign Tool to Assess Physical Activity. Am J Prev Med, v. 
60, n. 6, p. 866-872, 06 2021. ISSN 1873-2607. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/ 
33781618 >. 
14. 
GOLIGHTLY, Y. M. et al. Physical Activity as a Vital Sign: A Systematic Review. Prev Chronic Dis, v. 14, 
p. E123, 11 30 2017. ISSN 1545-1151. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/29191260 >. 
15. 
KIERNAN, M. et al. The Stanford Leisure-Time Activity Categorical Item (L-Cat): a single categorical 
item sensitive to physical activity changes in overweight/obese women. Int J Obes (Lond), v. 37, n. 12, p. 
1597-602, Dec 2013. ISSN 1476-5497. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/23588625 >. 
16. 
ROSS, K. M.; LEAHEY, T. M.; KIERNAN, M. Validation of the Stanford Leisure-Time Activity Categorical 
Item (L-Cat) using armband activity monitor data. Obes Sci Pract, v. 4, n. 3, p. 276-282, Jun 2018. ISSN 
2055-2238. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/29951218 >. 
17. 
KRUKOWSKI, R. A.; ROSS, K. M. Measuring Weight with Electronic Scales in Clinical and Research 
Set- tings During the Coronavirus Disease 2019 Pandemic. Obesity (Silver Spring), v. 28, n. 7, p. 
1182-1183, 07 2020. ISSN 1930-739X. Disponível em: < https://www.ncbi.nlm.nih.gov/pubmed/ 
32339394> 
18.  ROSS, K. M.; WING, R. R. Concordance of In-Home "Smart" Scale Measurement with Body Weight 
Mea- sured In-Person. Obes Sci Pract, v. 2, n. 2, p. 224-248, Jun 2016. ISSN 2055-2238. Disponível em: < 
https:// www.ncbi.nlm.nih.gov/pubmed/27499884 >. 
 
 
Participants were informed about the timeframe for each assessment during the orientation 
session and two weeks before the 6- and 12-month assessments through emails and e-cards. At 
each assessment point, participants received detailed instructions for each component of the 
assessment. 
The order of the assessment request was in all time points, dietary recalls, survey, physical 
activi- ty and body weight. Protocols for each component of the assessment are described 
below. 
 
Dietary recalls 
Dietary intake data (24-hour recalls) were collected and analyzed using the Automated 
SelfAdministered 24-hour (ASA24) Dietary Assessment Tool, version 2020 for cohort 1 and 
2022 for cohort 2. Three unannounced dietary recalls were collected at each time-point. Invalid 
recalls (under 500kcals) were considered and participants were asked to complete another 
attempt. Total kcals for all valid recalls were averaged. A total of 5 weekdays and 5 weekend 
days are scheduled are each timepoints, thus enough makeup days are available for the 

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completion of the assessment. 
 
Steps to request a dietary recall 
1. Before the first recall date, the number of recalls completed and remaining per participant has 
to be determined. Data is exported from ASA24 research site “tracking feature”. If a partici-
pant has not enough recalls remaining (8 remaining at 6-mo assessment and 4 remaining at 
12- mo assessment), a new account must be assigned by highlighting the participant in the 
ac- counts Excel database located in OneDrive/mLife/Assessment Materials/Cohort/Dietary 
re- calls and pasting their identifying information on the last account available. 
2. Active participants in each cohort are identified at each assessment time-point (baseline 
and 12 weeks) by generating the “consort report” from RedCap. Desired participants are 
enrolled study participants, with a participant status “active” and who haven’t completed 
the required dietary recalls for that time-point. 
3. All databases generated for tracking each recall are securely stored in an Assessment 
Materials OneDrive folder per cohort. A folder within the Dietary Recalls section is labeled 
with the date of each recall. 
4. On the scheduled day, a recall request is emailed to the participant in the morning using Out-
look mail merge, which pulls participant information from the active participants 
spreadsheet. 
5. In the early afternoon of the recall date, a research assistant would examine the completion 
of the day using the ASA24 Researcher Site. They would then create a list of people to 
remind to complete the day’s recall on Excel utilizing the earlier created spreadsheet of 
participants who were contacted that day to complete a recall. The research assistant would 
then conduct re- minder phone calls using Google Voice. If not able to be reached by phone 
call, participants are texted. These contacts would be noted in the Reminder Call Excel 
Spreadsheet. After completing these phone calls, the research assistant would contact the 
faculty members asso- ciated with the recalls for the assessment time-point and update them 
on their contacts. The phone call and text message scripts are below. 
6. Participants are required to complete the recall before midnight Eastern time zone on the 
day that the recall was requested in order to be considered completed and valid. In addition, 
each participant’s recall had a threshold of 500 kcal to be considered valid. 
7. The following day, research coordinator imports to RedCap the kcal and date of the recall, 
and the participants who completed the prior day’s recall data. 

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24 
 
 
Survey 
A single survey is requested for completion at each time point. Configure RedCap’s 
Automated Survey Invitations (ASI) feature to automatically send the sur- vey link to the 
participant’s email. The customized email includes the unique survey link, a brief explanation of 
the survey’s purpose, and deadlines for completing the survey at each time point. Set the system 
to send the initial survey invitation email to the participant immediately after they sign the 
informed consent form (baseline or on the date of the 6- or 12-month assessment launch). 
Schedule two reminder emails: the first will be sent 3 days after the initial invitation, and the 
second will be sent 7 days later. 
Participants are requested to provide self-reported anthropometric measurements, such as 
hip and waist circumference and body weight, and physiological measurements, like blood 
pressure, at each time point. These measurements are reported in the “measurements” section of 
the survey instrument. Detailed instructions are provided below. 
 
Hip and waist circumference 
A tape measure is sent to the participants for hip and waist circumference measurements. 
The participant will be instructed to measure waist circumference at the iliac crest, and hip 
circumfer- ence will be measured at the maximum protuberance of the buttocks. Two 
measurements will be taken and should be within 4mm of one another. If they are not, a third 
measurement will be re- quested in the survey/ 
 
Written tips: 
• 
Stand up straight and breathe out. Use the tape provided for the study. 
• 
Measure the distance around the smallest part of your waist, just above your belly 
button. This is your waist circumference. 
• 
Then measure the distance around the largest part of your hips - the widest part of 
your buttocks. This is your hip circumference. 
• 
The accuracy of waist and hip circumference measurements depends on: 
◦ 
The tightness of the measuring tape. The tape should be snug around the body, 
but not pulled so tight that it is constricting. 
◦ 
The correct positioning of the tape around the body (horizontal). 
• 
Complete two measures of both waist and hip circumference and report below as 
indicat- ed. If the difference between the two is greater than 1cm, please repeat the 
process a 3rd time. 
• 
Report your measurements in centimeters (cm). 
. 

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25 
 
Blood pressure 
Participants self-report blood pressure: a recent reading taken at a local pharmacy or at home 
will be recommended. Measurement should be taken after a five-minute rest period, with a 
digital blood pressure cuff. A minimum of 2 readings will be taken, and the average of those 
readings will be reported. If there is a >5 mmHg difference between the first and second 
readings, addi- tional (one or two) readings will be obtained, and the average of these readings 
will be used. 
 
The following instructions will be provided to the participants: 
Sit quietly for at least 5 minutes before testing. 
Don't smoke, drink caffeine or alcohol, or exercise within 30 minutes prior to testing. 
Empty your bladder. 
Sit up straight in a firm, hard-backed chair that supports your back. 
Don't sit or lie on a sofa or bed. 
Place feet flat on the floor with legs uncrossed. 
Your arm should be supported on a flat surface, such as the chair arm or a table. 
The upper arm should be at heart level. 
Place the cuff on your upper arm above the bend in your elbow. 
See your monitor's instructions for an illustration or ask for a demonstration at your doctor's 
office. 
Don't place the cuff over clothing. 
Take at least two readings and record the average result. 
Take two readings one minute apart. 
Record your readings and upload a picture of the device showing the numbers. 
 
Body-weight 
Body weight is determined objectively and self-reported, with units for assessment 
reported in pounds (lb). The self-reported body weight is one of the first questions in the “health 
status” sur- vey. 
For the objective measure, participants receive instructions on how to use the provided 
Fitbit Aria Air scale, which syncs data to the Fitbit app. If the scale does not properly sync to 
their Fit- bit app, participants are asked to take a picture of the scale's display and upload it to 
the instru- ment for data verification (self-reported, verified). 
At the beginning of the trial, the first synchronized body weight reading is recorded as 
baseline. The body weight at 6 months and 12 months is determined as the last reading at 
weeks 26 and 52, respectively. The objective measure of body weight data is extracted from 
Fitbit and is pulled to the mLife site, from where it is exported to a CSV file. The body weight 
and date are then im- ported to RedCap at the assessment event using the “Body Weight 
(Fitbit)” instrument. Import- ing the body weight data marks the instrument as “complete,” so it 

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26 
 
is not requested again from the participant. However, if no body weight data is reported for a 
participant at the end of the as- sessment period, they receive a link to either report their body 
weight directly to the form “Body Weight (Fitbit)” or to manually enter it into their Fitbit 
profile. In either case, they are prompted to upload a picture of the scale. 
Participants follow the instructions below to get their body weight reading. These 
instructions are included in the RedCap instrument for the participant. 
• 
Use Aria Air while barefoot. 
• 
Make sure your feet are dry before weighing yourself. 
• 
Place Aria Air on a hard, flat surface during use. 
• 
Balance your weight evenly between both feet when you stand on the scale. 
• 
Weigh yourself at the same time each day to see consistent trends. Your weight 
naturally varies over the course of the day. 
 
Outreach Plan to Address Technical Issues with Participants’ Scales 
Assessment Preparation: 
Before each assessment point, review the weekly data to identify participants whose scales 
haven’t synchronized (no body weight reading in the mLife account) for more than three weeks. 
 
Participant Contact: 
Reach out to the identified participants to inquire about any technical problems they may be ex-
periencing, particularly with setting up their scales. 
 
Technical Assistance: 
Schedule a video call with the participant to provide them with assistance in setting up their 
scale, if necessary. Share the tips to use Fitbit scales listed below 
 
Tips/Links for Fitbit Assistance 
Below, are options to explore regarding your Fitbit device. 
• 
Fitbit Support Line: call 24 hours a day (877) 623-4997 
• 
Fitbit Live Chat: 24 hours a day. 
Fitbit.com > scroll all the way down, click “Product Help” > click “GET SUP-
PORT” under “Let’s Talk” 
• 
Fitbit Community: Search for info/questions among other Fitbit users 
Fitbit.com > scroll all the way down, click “Community” > search anything in the 
search bar regarding your device, also feel free to explore the page for guidance 
• 
Twitter: @FITBITSUPPORT 
Give this account a follow on twitter and direct message the account with any 
questions you may have 
• 
Trouble with Bluetooth pairing? 
There is a small black circle button on the back of your scale. Press and hold that 

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27 
 
button for one minute until the screen flashes “otA” then your scale has been re-
set. Once your scale is reset, try and repair your device to your app. 
Some participants have also found that restarting their phones help debug any 
Bluetooth troubles. 
• 
Need to change the weight units to lb? 
Tap the small black circle button on the back of your scale to switch your weight 
unit. 
Escalation to Fitbit Customer Service: 
If the research team is unable to resolve the issue during the video call, contact Fitbit customer 
service on behalf of the participant. Follow up with Fitbit to ensure that the problem is resolved 
promptly. Document the case number in the tracking database. 
Device Replacement: 
If Fitbit fails to offer a solution, arrange for a replacement device to be sent to the participant. 
Follow the procedure for Distributing mLIFE Study Kits. Each step of the process is tracked 
and documented in a database created for each assessment time point per cohort, located in 
OneDrive/mLife/Retention/Cx_202x. 
 
Physical activity 
A FitBit Versa 2 tracker will be used to objectively assess and monitor minutes per week of 
mod- erate to vigorous-intensity physical activity (MVPA). During the orientation, the 
participants are instructed to wear the tracker at least 10 h daily, during asleep and awake time. 
Fitbit uses a pro- prietary algorithm to determine activity levels, which are defined as vigorous, 
moderate, light, or sedentary and activity intensity—active zone minutes (time spent in the fat 
burn, cardio, or peak heart-rate zones), the number of steps per day, and resting heart rate will 
be pulled from the Fit- Bit public API to the mLife App. For data analysis, participants’ data is 
considered valid if they had a wear time of ≥600 minutes per day. 
The average of three valid days within a week during the assessment period is imported to 
Red- Cap at the assessment event using the “Physical Activity (Fitbit)” instrument. Baseline 
data was reported for Week 0, and 6-month and 12-month assessments were reported for Weeks 
26 and 52, respectively. When data for the week of intervention is unavailable, data from two 
weeks before or the week after the time point cutoff is considered for assessment. 
Additionally, self-reported physical activity was assessed using the Exercise Vital Sign 
Questionnaire and the Stanford Leisure-Time Activity Categorical Item (L-Cat), both of which were 
included as questions within the “health status questionnaire of the survey. 
 
Procedure for Distributing mLIFE Study Kits 
The mLIFE Study kits, which include a Fitbit Versa2, Fitbit Aria Air Scale, and non-
elastic measuring tape, are distributed to participants who have completed at least the initial 
survey or three dietary recalls. These devices are critical for tracking physical activity, weight, 

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28 
 
and conduct the hip and waist circumference measures at each time point. 
All devices are bought in bulk and kitting services are hired to receive the orders of the 
Fitbit devices and tapes and to create and label each kit box. USC Post office provides the 
shipping services to the participants. Once the shipped to a participant, an email containing 
the tracking number is sent to the participant. A designated study assistant monitors the 
tracking progress to ensure timely delivery. Upon receipt of the kit, a courtesy phone call is 
scheduled to confirm successful delivery and to ensure the participant understands the setup 
and usage instructions for the devices. If required, a video call is scheduled to assist with 
the device setup. 
The kits includes a welcome letter which provides step-by-step guidance on creating a 
Fitbit account, syncing devices, and verifying the account. Participants are instructed to sync 
their devices at least once every 5 days and upload a picture of the scale's display for data 
verification. Additionally, a training session is scheduled to guide participants through linking 
their Fitbit account to the mLIFE app, ensuring smooth device usage and data synchronization. 
All kit distribution is tracked in the study’s OneDrive/Retention/Cx_202_. 
During the courtesy call, the RA reminds the participants of the following: 
 
1. 
Create a FitBit profile on the website (no app). When linking the profile to the 
mLife app, permission to access FitBit physical activity data will be asked. 
2. 
Wear Versa 2 on your non-dominant wrist. When not exercising, wear it a finger’s width 
above your wrist bone. During workouts, wear it higher for a better fit. Frequent 
bending of the wrist during exercises like bike riding or weight lifting could interfere 
with the heart-rate signal if the watch is lower. 
3. 
Wear the Fitbit device on top of your wrist, ensuring the back is in contact with 
your skin. 
4. 
Follow the manufacturer’s instructions for cleaning and caring for the device. 
 
 
Study Intervention 
The intervention design promoted weight loss and weight-loss maintenance by focusing on diet 
and PA behaviors and facilitating social support, grounded in theoretical perspectives such as 
supportive action, appraisal, and relationships, as well social support provision and receipt. 
The mLife intervention consisted of 5 main components: daily tracking of 1) diet, 2) PA, and 3) 
body weight; 4) podcasts and tips of the day; and 5) gamification of social support activities. As 
mentioned above, participants were provided a Fitbit watch and scale for PA and body weight 
tracking, with all intervention components implemented remotely through the mLife app 
(cohort 2 tracked diet outside of the app). Both groups will be instructed to follow the same 

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29 
 
dietary (re- duced energy diet) and PA recommendations (progressed up to a goal of 150 
minutes of moder- ate or 75 minutes of vigorous activity/week). These recommendations will be 
provided via hand- out at the orientation and reinforced in the podcasts. The figure below 
displays images of the mLife app components. 
 
 
mLife intervention components delivered via the mLife app: 
a. diet, physical activity (PA), and weight tracking; b. leaderboard and points tracker; c. tips of the day; d. newsfeed; e. social support requests 

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30 
 
App Development and Use 
A progressive web application, incorporating improved features from the pilot Social POD app, 
delivered the mLife weight loss program. It integrated the NutritionIX Database via API for diet 
logging. For cohort 2, Participants used FitBit devices to track activity and weight, and the API 
displayed Fitbit data. 
Based on Cohort 1 feedback, two adjustments were made for Cohort 2. Participants were 
initially limited to one response to peer support requests, but this hindered social interactions, 
so unlimit- ed responses were allowed. The in-app graph displayed only “active minutes” per 
day, but the FitBit app emphasized “active zone minutes,” so the mLife app adjusted to display 
both. 
Cohort 2 also made an adjustment based on Cohort 1 feedback. Participants expressed 
dissatis- faction with the in-app diet tracking feature’s lack of recipe building and barcode 
scanning. So, Cohort 2 logged their diet in the Fitbit app, and the data was synchronized to the 
mLife app. 
Participants and staff member accessed the mLife application from the study’s website, 
under the login menu: https://mlifestudy.org/study/guest/login Participants access their account 
using the Email provided during the orientation, contact information form in RedCap project. 
IT team assist with any account issues or data display concerns through the help request RedCap 
project, as detailed under retention strategies. 
 
Intervention components procedures 
 
Both groups will receive the same intervention, but to isolate the impact of points/social gaming, the 
mLIFE+points group will receive points for engaging in social support-related behaviors, and the 
mLIFE will not. The intervention components and points system is displayed below. 
 
Intervention Components 
Points 
Podcasts (within the app): 
Nutrition and exercise information 
N/A* 
Audio diary 
N/A 
Goal setting 
N/A 
mLIFE app: 
Self-regulation features 
Diet, PA**, and weight tracking app components 
N/A 
App notifications at specific times to remind participants to self-monitor 
N/A 

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31 
 
Newsfeed of activity listing when someone self-monitored diet, PA, and weight; 
downloaded a podcast or read a tip of the day; or requested social support on a topic. 
N/A 
Leaderboard and Points tracker 
N/A 
Social support features 
Thumbs Up that someone tracked their diet for the day (posted to newsfeed) 
1 
Thumbs Up a notification that someone logged 30 min of PA for the day (posted to 
newsfeed) 
1 
Thumbs Up a notification that someone logged their weight for the day (posted to 
newsfeed) 
1 
Thumbs Up a notification that someone listened to a podcast or read a tip of the day 
(posted to newsfeed) 
1 
Sending someone an encouraging message when they have not logged on (choice of 3 
pre-populated messages or ability write their own message) 
1 
Sending out a request for help on a specific topic related to diet or PA 
1 
Responding to a request for help 
1 
Thanking someone for a thumbs up or response to a request for help (participants will 
also rate how supported they felt for each response they receive) 
1 
Total max points possible per day: 
8 
 
Within the study’s app, the participants can monitor their physical activity data from the FitBit 
tracker, log their food and engage in social support activities. FitBit app is used for body weight 
saving and in cohort 2 only, Fitbit nutrition feature is used for diet logging. The procedures for 
the 5 components are described below 
 
Diet tracking. 
Both groups were instructed to follow the same dietary (reduced energy diet) recommendations, 
which were provided via e-handout at the beginning of the study and reinforced in the podcasts. 
Participants were asked to enter all food and drink items consumed daily into the mLife app and 
were instructed to select the best match listed within the dietary database. Recently consumed 
foods were programmed to be ‘remembered’ within each participant’s search history for ease of 
use. Participants were able to view their individual diet log and daily total kilocalorie intake 
within the mLife app. 
 
Physical activity tracking 
Participants wore wrist-worn Fitbit Versa2 to self-monitor their physical activity (PA). The Fitbit 
synced PA data (steps, sedentary, lightly active, fairly active, and very active categories) to the 

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mLife app for self-monitoring. Heart rate data (number of minutes in heart rate zones) was also 
displayed in the mLife app. Participants wore the Fitbit daily and didn’t modify the default heart 
rate zone. 
 
PA data was displayed in the mLife app in two ways: total minutes of moderate to vigorous PA 
and total number of ‘active zone’ minutes. Fitbit used the term ‘active minutes’ to denote 
minutes spent performing MVPA (>10 consecutive minutes) calculated by METs. Activities at 
or above about 3 METs count towards active minutes. ‘Active zone minutes’ denote time spent 
in light to near maximal heart-rate zones (fat burn to peak). Participants earned 2 active zone 
minutes for each minute spent in the vigorous and near maximal heart rate zone (cardio and 
peak zones). 
 
Body weight tracking. 
Participants received an Aria Air Fitbit scale and were asked to weigh themselves daily for regu-
lar feedback. Fitbit scales synced to the mLife app via Bluetooth and the Fitbit app, allowing 
par- ticipants to view weight graphs and track changes over time. 
 
Remote content delivery via podcasts and tips of the day. 
Remote intervention content was delivered through podcasts and tips of the day. Designed 
using the Diabetes Prevention Program and Social Cognitive Theory. New podcasts are 
released every Monday and Thursday morning for the first 6 months, then once weekly for the 
second half of the intervention. Podcasts were 10-15 minutes long and tracked in the mLife 
app. On podcast release days, participants received a notification for a tip of the day. 
Podcasts for the first 6 months structure: 
1. introduction 
2. audio diary of person discussing their weight loss efforts 
3. nutrition/exercise information 
4. continuing soap opera 
5. a goal-setting activity. 
 
Podcasts for months 7-12 structure: 
1. introduction 
2. nutrition/exercise information 
3. scripted audio interviews or audio diary of person discussing their weight loss experiences 
4. a goal-setting activity. 

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Social support activities and gamification 
The mLife app offered eight social support activities to engage users and test gamification. 
It au- tomatically posted newsfeed when users logged meals, exercised, tracked weight, or 
listened to podcasts. Users could “like” posts and request support from peers by commenting or 
asking questions. Peers could comment and respond to support requests, and users received 
notifications when peers offered support.Refer to the graph below that shows the gamified 
social actions with- in the application id and point value for the leaderboard. 
 
 
Participants are also prompted to send supportive messages to inactive peers. When 
inactive for more than 24 hours, an outreach request is posted in the newsfeed: “(username) 
hasn’t been active for more than a day. Please send them an encouraging message to return.” 
Participants can choose a pre-written message or create a custom message and send it via text. 
Pre-written messages are created using Social Cognitive Theory to target social support, self-
efficacy, and out- come expectations regarding self-monitoring behavior. Once an outreach 
message is sent, the request is closed. 
Participants earn up to 8 points per day for social support interactions. They can provide 
support as many times as desired, with a maximum of 1 point per activity. The mLife+Points 
group views the 8 activities, their daily points, and an overall leaderboard that resets monthly to 
boost motivation. The mLife group is unable to see the points earned; they have daily 
checklists. However, the mLife app calculates points for objective comparison between groups. 
Posting a “request for support” comment or question in the app’s newsfeed allows mLife 
peers to comment and respond. Initially, participants could only post one response to peer 
requests to control moderation, but this limited social interactions, so unlimited responses were 
allowed at the 8 weeks data inspection. See the comment replies example graph below. 

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All participants’ social interactions are posted in the newsfeed. 
Participant Retention 
Our retention and adherence strategies will target the following main areas: 
Intervention 
1. mLife incorporated several in-app features to support participant activity monitoring and app 
usage. Inactive participants, defined as those who haven’t logged in for three consecutive 
days or more, are displayed on the Management Page dashboard. On the third day of each 
mLife week intervention, designated research assistants contact inactive participants via 
phone call or email. This outreach process underwent several reviews and modifications to 
enhance retention efforts and ensure accurate intervention progress reporting to participants. 
2. During the intervention, participants were able to submit a form within the mLife app to re-
quest technical assistance from the mLife staff. This form was collected and tracked via 
Red- Cap. An RA is assigned to derive each request to a staff member to provide assistance 
to the participants. 
3. The research team stays in contact with participants by sending birthday and holiday cards 
during the study. Mid-way through the study, participants were mailed a postcard reminding 
them of the importance of engaging in the mLife app. 
4. Monthly surveys were administered to collect participant feedback regarding changes in 
medication, health status, life events, and satisfaction with the mLife app and intervention 
components. The distribution, tracking and data report is conducted via the RedCap projects. 
5. Monthly e-newsletters are sent to all enrolled and active participants. To retain and motivate 
members of the mLife+Points group, the top three individuals on the leaderboard for the 

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month are included in these newsletters. The newsletter is sent to each participant via email 
as confirmation of completing the monthly survey. For those participants who did not 
respond to the survey, an email is sent via email. 
 
Assessment 
Participants are provided with a $50 Amazon gift card incentive for completion of all 
assessment measures at 6 months and again at 12 months. The breakdown of the incentive was 
based on the completion of each component of the assessment as follows: survey and 
measurements $10, body weight $15, dietary recalls $15, and 3 valid days of physical activity 
assessment $10. The incentives are sent directly from Amazon to the participant’s email. The 
project Manager uses the Assessment Tracking Report from the RedCap project to determine 
completion of each component. 
 
Adherence 
We use the intervention monitoring RedCap project to track adherence to each of the 
intervention components. Dietary intake will be assessed using 24-hour recall data at 0, 6, and 
12 months. In addition, we will use the data obtained from objectively self-monitored 
participant diet data. This approach assesses the degree to how each participant has met a priori 
energy limits and distribu- tion adherence criteria. Overall adherence to intervention delivery 
will also be assessed by collected data in the mLife application. Process data will be collected 
before, during, and after the intervention. 
Study Compliance 
In an effort to maximize adherence to the protocol and minimize noncompliance, training on the 
study protocol, weekly review of the aggregated data, and routine communication with the team 
has been put in place to help minimizing protocol deviations. However, the Project Manager 
oversees all recruitment, randomization and assessment procedures, keep IRB approval up to 
date, and confirm each participant is using the provided devices properly and syncs with the cor-
responding app based on group allocation. 
The project manager monitors each of the aspects and maintains a log of all protocol deviations 
(OneDrive > mLife study > Administrative > Protocol Deviations Log. All deviations should 
then be reported to the DSMO. 
Protocol deviations include, but are not limited to the following: 
• 
Randomization of an ineligible participant 
• 
Failure to obtain Informed Consent 
• 
Failure to keep IRB approval up to date 
• 
Wrong app version downloaded by a participant 
• 
Outcome measurement not performed 

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36 
 
Data Collection, Storage and Management 
For the mLife study, Dr. Carolina Delgado-Diaz served as Data manager by completing the fol-
lowing tasks before, during and after the completion of the trial. 
 
Data manager duties: 
• 
Data Collection and Entry: Ensure accurate and timely data collection and entry from 
all trial sites, maintaining data integrity and quality. 
• 
Database Design and Maintenance: Develop and maintain the clinical trial 
database, ensuring it is user-friendly and meets all project requirements. 
• 
Data Cleaning and Validation: Conduct regular data cleaning and validation processes 
to identify and resolve discrepancies, ensuring data consistency and reliability. 
• 
Data Security and Confidentiality: Implement and enforce data security and 
confidentiality protocols to protect sensitive information in compliance with 
regulatory standards. 
• 
Monitoring and Reporting: Monitor data collection activities, generating regular 
reports and summaries for the research team and regulatory parties. 
• 
Training and Support: Provide training and support to clinical trial staff on data 
management systems and protocols. 
• 
Regulatory Compliance: Ensure all data management activities comply with 
relevant regulatory and ethical guidelines, such as the IRB and GCP. 
• 
Liaison with IT and Researchers: Work closely with IT professionals for 
system enhancements and PI and co-investigators for data preparation and 
analysis. 
 
All data related to the mLife study, including but not limited to surveys, attendance to online 
meetings, informed consent forms, surveys, physical activity, diet and body weight data, 
adherence to intervention and release of newsletters is captured using the following systems: 
• 
OneDrive: This cloud storage system is used for maintaining a copy of the mLife 
study data. Once data is collected in any other platform, it is transferred and stored in 
the corresponding folder. This serves as a backup storage solution and allows easy 
access to data for authorized staff members. 
• 
ASA24: ASA24 is used for capturing self-reported dietary data. All diet-related data 
will be stored in this tool, and a backup is kept in the mLife OneDrive. 
• 
mLife Server (Hosted in the ASPH): This is the primary server where all 
study intervention-related data is initially captured and stored. 
• 
RedCap: This is a secure, web-based data collection tool specifically used for 
distribution of orientation materials, capture of informed consent, distribution and 
collection of assessment surveys, and tracking mLife study data. This is the 
primary platform for all implementation of the study’s procedures. 

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The institutional cloud storage service, is used as repository for the mLife study. Undergraduate 
research assistants (RAs) are granted access to specific folders based on their tasks by the 
project manager. The project manager, the principal investigator (PI), the research assistant 
(staff mem- ber), and graduate assistants have full access to the main folder. All information 
related to the mLife study, including drafts and working documents, must be stored and 
accessed using the University credentials. 
 
Plan for Data Quality Control Procedures 
The PI and the project manager will review all data collection forms and surveys on 
an ongoing basis for data completeness and accuracy as well as protocol compliance. Any 
ambiguity in the response to a question will be brought to the attention of the Project 
Manager for clarification. If the Project Manager is unsure how to resolve the issue, the matter 
will be brought to the attention of the Principal Investigator. 
The Project Manager will 
maintain a log so that future occurrences of problems will be handled in the same manner. 
Further, these issues will be discussed during project meetings to ensure that data resolution is 
handled consistently. 
The data entry system (RedCap) requires a login identification and password in order to 
gain access to the data. Where appropriate, validation and range rules are applied to the actual 
entry field. Data found to be inconsistent after the verification has been run will be compared 
to original questionnaires and recorded values to resolve any discrepancies. 
 
Data Safety Monitoring Responsibilities 
The entire team for this project will meet at least monthly in the first year in order to coordinate 
planning of the study and oversee recruitment efforts. Staff, graduate assistants, and the PI will meet 
weekly. In addition, weekly individual meetings with the PI and project coordinator will occur to 
ensure recruitment efforts are yielding our target goals and weekly meetings with the PI and the 
nutrition interventionist will occur in order to ensure intervention content is being devel- oped/ 
collected in a timely manner. The project coordinator will oversee the monthly reports to the DSMB 
that detail recruitment efforts and enrollment demographics. Sub-committees for each aim will also 
be formed. All sub-committees will be led by PI Turner-McGrievy. Sub-committees for Aim 1 will 
include Drs. Wilcox and Valafar; Aim 2 will include Drs. Monroe and Valafar. 
Progress reports, including participant recruitment, retention/attrition, and adverse events (AEs), will 
be provided to the DSMB semi-annually. An Annual Report will be compiled and will include a list 
and summary of AEs, whether AE rates are consistent with pre-study assumptions, reason for 

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dropouts from the study, whether all participants met entry criteria, whether continuation of the study 
is justified on the basis that additional data are needed to accomplish the stated aims of the study, 
and conditions whereby the study might be terminated prematurely. 
The Annual Report will be sent to the DSMB and will be forwarded to the USC IRB and NIH. The 
USC IRB will review progress of this study on an annual basis. The PI will also send copies of 
signed recommendations and comments from the DSMB to the NIH Program Officer within 1 
month of each monitoring review. 
 
Statistical Design and Power 
I. The below statistical plan justifies the proposed sample size based on appropriate study 
assumptions, as well as our plans for evaluation of the primary outcomes by race/ethnicity and sex, 
including all relevant data that assess whether the trial includes adequate numbers for valid analyses 
of subgroups. Below we also justify the adequacy of power to analyze subgroups of participants: 
 
Aims 1 and 2 
We are powering our study to detect differences in weight loss at one year between those 
randomized to mLife+points and mLife groups (Aim 1) and differences in social support provision 
and receipt at one year between groups (Aim 2). For Aim 1 power, we used an F-test on the 
interaction between time (two levels) and treatment arm (two levels) in a two-way ANOVA with 
repeated measurements. We assumed conservatively a small effect size (Cohen’s d = 0.1). 
Moreover, we used our NETworks pilot work, which collected weight loss outcomes at one year,1 to 
determine the intra-cluster correlation (ICC) which is the correlation of weight between times within 
individuals. The pilot study estimate of the ICC was 0.9 but 2e judged that this estimate may be too 
optimistic and lead to an inadequately low sample size (see Table 5). Therefore, we used a more 
conservative ICC = 0.7. In summary, we calculated that to achieve 95% power (alpha = 0.05) for 
Aim 1 assuming a small effect size (Cohen’s d = 0.1) and ICC equal to 0.7, we need a sample size 
equal to 200. Further, we assumed an attrition rate of 15-20% and increased the sample size to 240. 
Thus, we aim to recruit a total of 240 participants (~120 per cohort), with the initial randomization 
assigning 120 to mLife+points and 120 to mLife. This sample size will also give us abundant power 
for the study in Aim 2. Based on our Social POD pilot work, we are powering Aim 2 from both 
differences in overall app usage (Social POD 50.7 ± 25.0 days and standard 34.4 ± 25.8 days out of 
a possible 84 days)2 and points earned (representing social support provision). Social POD pilot 
participants earned a mean of 202±105 points/participant.3 We are assuming a difference of 50 
points between groups with a SD of 105. Therefore, with the sample size chosen for Aim 1, our 

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power for Aim 2 will be 99% for app usage and 95% for points earned. 
The sample size for our study has been chosen to ensure sufficient statistical power to detect 
differences in weight loss at one year after baseline between those randomized to mLife+points and 
mLife groups (Aim 1) and differences in social support provision and receipt and at one year 
between groups (Aim 2). 
 
Sample size according to F-test 
Because our main outcomes will be measured at 12 months, we are using pilot work that collected 
weight loss outcomes at one year. Based on our pilot data (NETworks trial as this provides 12-month 
outcomes for weight), as well as several other one-year mHealth intervention studies,4-7 we 
calculated the sample size necessary to achieve 95% power (alpha = 0.05) for Aim 1 assuming a 
small effect size (Cohen’s d = 0.1) and an intra-cluster correlation (ICC) equal to 0.7. The sample 
size estimate was 200. For this calculation, we used an F-test on the interaction between time (two 
levels) and treatment arm (two levels) in a two-way ANOVA with repeated measurements (RM-
ANOVA). We used a more conservative value of the ICC as compared to the actual estimate from 
the NETworks trial data (ICC = 0.9), as the latter would have resulted in a much smaller sample size 
(for a larger ICC, the residual sum of squares decreases, therefore precision increases and sample 
size decreases. The opposite is true when the test is strictly between subjects). Further, we assumed 
an attrition rate between 15 and 20%, and increased the sample size to 240. Thus, we aim to recruit a 
total of 240 participants (~120 per cohort), with the initial randomization assigning 120 to 
SocialPOD+points and 120 to SocialPOD-points. 
Based on pilot study for overall app usage (Social POD 50.7 ± 25.0 days and standard 34.4 ± 25.8 
days out of a possible 84 days)2 and points earned (mean of 202±105 points/participant with 
estimated 50 point difference between groups),3 our power for Aim 2 will be 99% for app usage and 
95% for points earned based on our sample size from Aim 1. 
We plan to use a random-effects (RE) model which is mathematically equivalent to repeated-
measures-ANOVA.8 However, in the presence of loss to follow-up, RE models can handle responses 
that are missing at random. RE models can be adjusted for additional covariates if needed (though 
the randomization procedure should make this unnecessary). RE models provide additional 
information about the variance of the random effects which is valuable for understanding 
heterogeneity of responses and assessing the intra-cluster correlation (ICC). 
 
Analysis Plan 
I. Below details how the outcomes will address the hypotheses being tested: 

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We have two main hypotheses in this study. We are examining our outcomes among 240 adults with 
overweight or obesity and ≥3 T2DM risk factors.9 
Hypothesis 1: That the SocialPOD+points group will lose significantly more weight than the 
SocialPOD-points group. 
Hypothesis 2: That the SocialPOD+points group will have greater objectively measured levels of 
social support provision and receipt than the SocialPOD- group 
 
In order to ensure that each of these hypotheses can be addressed we must measure the following 
outcomes: 
Objective body weight assessments 
Objective assessment of social support provision and receipt via the app 
Type 2 diabetes risk factors (assessed at baseline, 6 months, and 12 months): body weight, body 
circumference measures, and blood pressure 
Demographic data (race/ethnic group and sex) 
These outcomes will help us examine how weight loss and social support provision and receipt may 
differ between groups. 
 
III. Below describes our plans for interim and final analyses and methods for handling missing 
data: 
 
Aims 1 and 2 
Data from all study measures will undergo initial data cleaning to identify potential outliers, 
determine distributions of variables, assess normality, and enumerate loss to follow-up and other 
missing data. Descriptive statistics at baseline will be compared between treatment groups to 
evaluate the success of randomization. Analyzing changes in weight between groups at year one 
(Primary Aims 1 ): For Aim 1, the two levels of the treatment effect will be assignment to 
SocialPOD+points vs. SocialPOD-points, and the entire study sample will be included. Primary Aim 
1will be addressed using a repeated-measures mixed model with maximum likelihood estimation as 
provided by PROC MIXED in the SAS® system. Under the assumption that missing data are missing 
at random, mixed models provide unbiased estimates. These will be adjusted using robust 
computation of standard errors if non-normality is detected. These models will be estimated 
applying an intent-to-treat principle. Models for each primary aim are of the same form, with the 
difference of the groups being compared. Models will examine weight at baseline and at 12 months 
with a two-level time effect, two-level treatment effect, and two-way interaction between time and 
treatment. The repeated-measures model will contain time, treatment, time-by-treatment interactions, 
and any covariates associated with weight loss. Models will be adjusted for changes in PA (via 

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41 
 
accelerometers). If the time-by-treatment interaction in a model is significant at the 0.05 level, this 
will be interpreted as a significant weight-loss effect for one treatment relative to the other. 
Analyzing differences in social support provision and receipt between groups (Aim 2): For Aim 2, 
the model will regress support provided (total points earned) and social support received (mean of 
ratings of support provided to the individual over the 12 months) on treatment group, adjusted for 
the same covariates used in Aim 1. 
 
IV. Below details various types of bias and how our study aims to avoid them. 
 
Type of Bias 
How to Avoid 
Pre-trial bias 
Flawed study design 
We have a clearly defined risk and outcome and are using 
objective or validated methods. Standard operating procedures 
will be developed for data collection and assessors will be 
blinded to random assignment. 
Selection bias 
We will select participants using rigorous criteria to avoid 
confounding results. Participants will originate from the same 
general population. Because this is a well-designed, prospective 
stud, selection bias should be avoided as outcome is unknown at 
time of enrollment. 
Channeling bias 
We will assign participants to study cohorts using rigorous 
criteria, stratifying by sex and race. 
Bias during trial 
Interventionist bias 
All study personnel interactions with participants will be 
standardized. As part of our treatment fidelity process, 
interactions with participants (e-mails, phone calls, etc.) will be 
regularly assessed and monitored to assure equal treatment 
among groups. 
Recall bias 
We will use objective data sources whenever possible. While 
surveys and the dietary recalls will rely on memory, these 
measures are currently the gold-standard way to assess these 
outcomes. 
Transfer bias 
We will carefully design plan for lost-to-follow-up participants 
prior to the start of the study. This will include number of 
contacts required after a participant does not attend classes or 
assessment visits. 

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Outcome 
Misclassification 
We are using objective validated measures to assess all primary 
outcomes. 
Bias after trial 
Citation bias 
Our trial will be registered with clinicaltrials.gov prior to study 
recruitment for cohort 1. We will heck registries for similar 
unpublished or in-progress trials prior to publication. 
Confounding 
Known confounders will be controlled during data analysis 
(such as medications). Unknown confounders will be controlled 
with randomization. 
* Adapted from Pannucci CJ, Wilkins EG. Plast Reconstr Surg. 2010 Aug; 126(2): 619–625. 
 
V. Consideration of relevant biological variables 
Of primary interest in the present study will be examining differences in outcomes by sex and age. 
Previous research has demonstrated that men lose more weight than women in behavioral weight 
loss interventions, but there is no indication that different weight loss strategies should be used.10 
There is evidence that men may interact with technology, including health-related mobile 
technology, differently than women. For example, a study examining gender differences in usage of 
a physical activity app found that enjoyment and goal-setting were more important for women than 
men but that men more often shared their results and used the live tracking function in the app.11 
Other research has found that men feel that mobile phone usage is more appropriate across a variety 
of social situations than women.12 In addition, those under 50 (and particularly those under 30) tend 
to have higher rates of smartphone ownership than those over 50.13 Based on these findings, we aim 
to conduct sub-analyses examining the impact of sex and age on social support provision and receipt 
and weight loss. We have been successful recruiting both men and AA participants in our previous 
studies and being situated in South Carolina and housing this work within the Prevention Research 
Center (where the current main research project is among AA churches in SC) will ensure we can 
consider both of these relevant biological variables. Our models will also control for other factors 
that could impact outcomes, including age, BMI, SES, baseline lab values, and medication use. 
 
A. Below details out approach to data management and validation, including our data 
management system, methods of data entry and cleaning, and event tracking and logistics 
Ms. Mary Wilson, Project Manager, and Dr. Brie Turner-McGrievy, study PI, will develop and 
maintain the computerized data management system for this study. Use of the data management 
system will be restricted to only those persons having access authority. 

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Participant surveys 
Participants will complete all surveys electronically using a secured online platform. Electronic data 
will be imported into the study’s database. Any paper documents, like attendance sheets, will be 
entered in the tracking database and stored in a locked filing cabinet. This study will use the IRB-
approved OneDrive for storage of online files. 
 
Local Tracking Application 
An online tracking database will be used to track study participants. This local application will 
allow the study personnel to input demographic, contact information, form & visit tracking, and 
other data about individual participants. Access to the local application will be restricted by use of 
individual username and passwords. 
The tracking database will have three primary forms: 
Screening Forms – This form is used to track attempts to reach participants who completed an online 
screening form. 
Measurement Tracking – This form tracks all measurement activities, including scheduled and 
actual dates of all measurement visits; location of measurement visits; return of accelerometers; 
distribution of incentives; completion of the three ASA24 dietary recalls; and participant status and 
status changes. 
Intervention Tracking – This form has subforms that are used to record randomization assignment; 
participant-level tracking for the intervention groups. 
 
Below is a screenshot of the tracking application we are currently using in our NIH R01 study: 
 
B. Methods for monitoring the quality and consistency of the intervention and data collection 
The intervention quality and consistency will be monitored with our treatment fidelity plan (see our 
Process Evaluation Plan in the Recruitment and Retention section of this grant). For the quality and 
consistency of data collection, our plan includes the following: 
Trained assessors who are blinded to study assignment: All assessors will go through rigorous 
training in order to know how to accurately assess height, weight, blood pressure, and other 
physiological outcomes. 
Training participants on survey data: All participants will be trained on how to complete 
questionnaires and dietary recalls to ensure accurate data. Participants will complete the baseline 
questionnaire and the first dietary recall in person in order to ensure participants can have questions 
answered about the process. Missing answers on the electronic surveys will be highlighted for 
participants to complete. 

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44 
 
Electronic entry of survey and dietary data: All participants will enter the data for surveys and 
recalls directly themselves to avoid data entry issues common with paper surveys. 
All data entered or imported into the database will be double checked: Once data has been 
double verified in the database, there is a purple check box that personnel will select to indicate the 
verification has occurred: 
 
 
C. Policies and methods for ensuring blinding of study results 
While participants and interventionists cannot be blinded to study assignment, all assessors (lab and 
measurement personnel) will be blinded to assignment. In addition, the study statistician will be 
blinded to participant identification during the randomization process and will also be blinded to 
group assignment (random numbers will be used to delineate which of the 2 groups a participant has 
been randomized to) for statistical analysis. 
 
D. Data confidentiality and subject privacy 
The database will be stored on a University managed data server with daily backups to tape drives. 
Staff will not keep copies of databases on thumb drives of portable external drives (unless they 
remain at USC and are locked). Survey data will remain in locked filing cabinets in the project 
manager’s office. Other than the database, no other documents will contain identifiable information. 
All surveys and lab assessments will only use participant ID number 
 
E. Data Reports generated by the project will be: 
De-identified Data Safety reports for the PI (monthly) and the Data Safety and Monitoring Board 
(quarterly) 
Publications authored by project team members based on research performed in this project 
Data from experiments 

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References 
 
1. 
Monroe CM GM, Larsen CA, West DS. Feasibility and efficacy of a novel technology-based 
approach to harness social networks for weight loss: NETworks pilot randomized controlled 
trial. Obesity Science and Practice. In press. 
2. 
Hales S, Turner-McGrievy GM, Wilcox S, et al. Social Networks for Improving Healthy Weight 
Loss Behaviors for Overweight and Obese Adults: A Randomized Clinical Trial of the Social 
Pounds Off Digitally (Social POD) Mobile App. International Journal of Medical Informatics. 
2016;94:81-90. 
3. 
Hales S, Turner-McGrievy GM, Wilcox S, et al. Trading pounds for points: Engagement and 
weight loss in a mobile health intervention. DIGITAL HEALTH. 2017;3:2055207617702252. 
4. 
Allen JK, Stephens J, Patel A. Technology-Assisted Weight Management Interventions: 
Systematic Review of Clinical Trials. Telemedicine Journal and e-Health. 
2014;20(12):1103-1120. 
5. 
Haapala I, Barengo NC, Biggs S, Surakka L, Manninen P. Weight loss by mobile phone: a 1-
year effectiveness study. Public Health Nutr. 2009:1-10. 
6. 
Lyzwinski L. A Systematic Review and Meta-Analysis of Mobile Devices and Weight Loss 
with an Intervention Content Analysis. Journal of Personalized Medicine. 2014;4(3):311. 
7. 
Khokhar B, Jones J, Ronksley PE, Armstrong MJ, Caird J, Rabi D. Effectiveness of mobile 
electronic devices in weight loss among overweight and obese populations: a systematic review 
and meta-analysis. BMC Obesity. 2014;1(1):22. 
8. 
Venables WN, Ripley BD. Modern applied statistics with S-PLUS. Springer Science & 
Business Media; 2013. 
9. 
Risk Factors for Type 2 Diabetes. https://www.niddk.nih.gov/health-information/diabetes/ 
overview/risk-factors-type-2-diabetes. 
10. 
Williams RL, Wood LG, Collins CE, Callister R. Effectiveness of weight loss interventions – is 
there a difference between men and women: a systematic review. Obesity Reviews. 
2015;16(2):171-186. 
11. 
Klenk S, Reifegerste D, Renatus R. Gender differences in gratifications from fitness app use 
and implications for health interventions. Mobile Media & Communication. In press. 
12. 
Forgays DK, Hyman I, Schreiber J. Texting everywhere for everything: Gender and age 
differences in cell phone etiquette and use. Computers in Human Behavior. 2014;31:314-321. 
13. 
Pew Research Center. Mobile Fact Sheet. https://www.pewresearch.org/internet/fact-sheet/ 
mobile/. 2019.