Behavioral Economic Approaches to Increase Physical Activity Among Patients With Elevated Risk for Cardiovascular Disease
Phase: NA
Conditions: Atherosclerotic Cardiovascular Disease
Sponsor: University of Pennsylvania

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CLINICAL PROTOCOL SYNOPSIS 
Protocol Title: Behavioral Economics Approaches to Increase Physical Activity Among Patients with 
Elevated Risk for Cardiovascular Disease (BE ACTIVE Study) 
Principal Investigators: Alexander Fanaroff, MD, MHS; Kevin Volpp, MD, PhD 
Date: 05/30/2024 
Outline 
1. Abstract 
2. Overall objectives 
3. Aims 
 
3.1 Primary outcome 
 
3.2 Secondary outcomes 
 
3.3 Exploratory outcomes 
4. Background 
5. Study design 
 
5.1 Design 
 
5.2 Study duration 
 
5.3 Target population 
 
5.4 Accrual 
 
5.5 Key inclusion criteria 
 
5.6 Key exclusion criteria 
6. Subject recruitment 
7. Subject compensation 
8. Study procedures 
 
8.1 Consent 
 
8.2 Procedures 
9. Analysis plan 
 
9.1 Power and sample size 
 
9.2 Comparative-effectiveness analysis 
 
9.3 Cost-effectiveness analysis 

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9.4 Process evaluation 
 
9.5 Safety analysis 
 
 

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1. Abstract 
Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality in the 
United States (US). Regular physical activity has been demonstrated to reduce the risk of ASCVD and is 
associated with a number of other health benefits. Yet, less than 50% of adults in the US achieve enough 
physical activity to actually obtain these benefits. Insights from behavioral economics have been shown to 
both better reflect the ‘predictable irrationality’ of humans and to be effective in designing interventions 
that achieve sustained improvements in health behavior. Our prior work has demonstrated that 
interventions using financial incentives and gamification can leverage principles from behavioral 
economics to increase physical activity during 3-month interventions and sustain effects in 3-month 
follow-up periods. These findings warrant further investigation of longer-term effects. In this study, we 
conduct a four-arm randomized, controlled trial to evaluate the effectiveness of using behavioral 
economic approaches including gamification, financial incentives, or both to increase physical activity 
among patients with elevated risk for atherosclerotic cardiovascular disease during a 12-month 
intervention with a 6-month follow-up.  
2. Overall objectives 
The objective of this study is to use a randomized, controlled trial to test the effectiveness of using 
gamification, financial incentives, or both to increase physical activity among patients with elevated risk 
for atherosclerotic cardiovascular disease. 
3. Aims 
 
3.1 Primary outcome 
The primary outcome is the change in mean daily steps counts from baseline to the 12-month intervention 
period, excluding the 8-week ramp-up phase. 
 
3.2 Secondary outcomes 
Secondary outcomes include change in mean daily steps from baseline to the post-intervention follow-up 
period, change in mean daily minutes of moderate-to-vigorous physical activity (MVPA) from baseline to 
the intervention period, and change in mean daily minutes of MVPA from baseline to the post-
intervention follow-up period. 
3.3 Exploratory outcomes 
We will explore the change in the proportion of participant-weeks that achieve the Centers for Disease 
Control and Prevention Recommendation of at least 150 minutes of MVPA per week from baseline to the 
intervention period and baseline to the follow-up period. 
4. Background 
Regular physical activity has been demonstrated to reduce the risk of ASCVD and is associated with a 
reduced risk of diabetes, hypertension, obesity, and mortality.1-6 Yet, less than 50% of adults in the US 
achieve enough physical activity to actually obtain these benefits.7   

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Behavioral economists have mapped out the ways in which people make predictable decision errors that 
often work against their own long-term self-interests.8,9 These insights are important to build into the 
design of interventions that are geared towards achieving sustained changes in behavior. Our prior work 
has demonstrated that interventions using financial incentives and gamification can leverage principles 
from behavioral economics to increase physical activity during 3-month interventions and sustain effects 
in 3-month follow-up periods.10-14 These findings indicate the potential of these approaches and the 
approaches developed provide a basis for testing the impact of these interventions on sustained behavior 
change over longer-term periods. 
5. Study design 
 
5.1 Design 
This is a four-arm, randomized, controlled trial to test the effectiveness of gamification, financial 
incentives, or both to increase physical activity among individuals with a 10-year ASCVD risk score of 
7.5% or higher. There will be a 2-week run-in period to obtain baseline measures of physical activity, 
followed by a 12-month intervention period and then a 6-month follow-up period. 
Participants will use the Penn Way to Health research technology platform to provide informed consent 
and complete eligibility surveys. Eligible patients will be mailed a wearable activity tracker that captures 
data on daily steps counts and minutes of MVPA. They will be asked to use the device for two weeks to 
get accustomed to it.  During this period, we will use a protocol from prior work to estimate a baseline 
step count using the second week of data. The first week of data will be ignored to diminish the tendency 
for use of devices in week 1 of receiving a new device to be significantly higher than what might be 
observed at steady state. To prevent risk of mismeasurement, we will ignore any daily values less than 
1000 steps because evidence indicates these values are unlikely to represent capture of actual activity.15,16 
At least four days of data must be available during that second week to estimate baseline measures; 
otherwise the period will be extended. In prior work, we typically have 6 to 7 days of data from more than 
90% of participants.12 Participants who do not complete this run-in phase will not be randomized into the 
trial. Participants will also complete a series of validated surveys including risk preferences 
(DOSPERT),17 social support (Medical Outcomes Study),18 personality (Big Five) and health-related 
quality of life (EQ-5D).19-21 See table in Section 8.2 for full list of surveys and timing 
--Goal Setting-- 
Once baseline measures have been established, participants will be contacted to choose their goals using 
an approach we have found to work well in previous studies. They will be given their baseline step count 
and asked to select a step goal increase of 33%, 40%, 50% or choose a custom goal as long as it is at least 
1500 steps greater than baseline. We have used this approach in the past because it gives participants the 
options of setting their own goal but also steers people to choose one of the options provided, any of 
which would be terrific from the standpoint of increasing physical activity. Leaving it completely open-
ended risks having participants either pick goals that are ‘too easy’ or not likely to be attainable. In prior 
work, we find that on average participants chose ambitious goals and more than half selected a 50% step 
increase. 
 

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--Randomization— 
Participants that have established baseline measures and finished goal selection will be randomly assigned 
to control or one of the three interventions using a 1:2:2:2 allocation and stratifying on baseline step count 
(< 4000 steps, 4000 – 7000 steps, > 7000 steps) using an electronic number generator through the Way to 
Health research technology platform.  We do this because it preferentially increases power for 
comparison between the different intervention arms, as the differences between intervention arms are 
likely to be smaller than the difference between the intervention arms and control.  
--Study Arms— 
All participants will be asked to use the wearable device during the day and at night to measure activity. 
Each participant will primarily receive study communications by text message. Interventions by study 
arm will vary as follows: 
--Arm 1: Control— 
During the intervention and follow-up periods, participants in this arm will receive a daily text message 
stating whether or not they achieved their step goal on the prior day. 
--Arm 2: Gamification intervention— 
Participants in this arm will be entered into a game designed to leverage insights from behavioral 
economics to address predictable barriers to behavior change during the 12-month intervention period. 
This approach is based on our successful pilot work in this area. We will use an 8-week ramp-up period in 
which daily goals are increased gradually from baseline to targets, as this was found to achieve sustained 
behavior change in previous work. For example, if the baseline number of steps per day is 5,000 steps and 
the goal number of steps chosen is 7,400. In week 1 the goal would be 5,300, in week 2 the goal would be 
5,600 up through the 8 week period. We have found that the rate of goal attainment is high using this 
gradual approach rather than encouraging the participant to go from 5,000 to 7,400 steps immediately.  
The components of the gamification intervention are as follows: 
1) Pre-commitment: First, each participant signs a pre-commitment contract agreeing to try their best to 
achieve their daily step goal. Pre-commitment has been demonstrated to help motivate behavior change.33-
34 
2) Points: At the start of each week, the participant will receive 70 points (10 for each day that week). 
Points are endowed rather than given after goal achievement to leverage loss aversion – a concept from 
prospect theory that reveals that individuals are more motivated by losses than gains.29,35 Each day the 
participant is informed of their step count. If the step goal was achieved, he or she retains their points.  
However, each day the goal is not met, they are informed that they lost 10 points. Points are replenished 
at the start of the week to leverage the “fresh start effect” – the concept that individuals are more 
motivated for aspirational behavior around temporal landmarks such as the start of the week.84 
3) Levels: At the end of the week, if the participant has 40 points or more, he or she will advance one 
level. The levels include: blue (lowest), bronze, silver, gold, platinum (highest). If he or she has less than 
40 points, he or she will drop down one level at the end of the week. This creates a sense of achievable 

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goals (goal gradients)37 and uses loss aversion to help motivate ongoing efforts to not lose status. Each 
participant begins the intervention in the silver level. By starting them in the middle, the higher levels 
seem within reach and they will feel a sense of loss from dropping down a level in the first week if they 
don’t achieve 40 points; this may motivate them to initiate greater activity. Every 8 weeks, we will reach 
out to individuals that are stuck in lower levels of blue or bronze and restart them back at silver.  This 
allows for another “fresh start” and creates a new endowment effect as someone who is already at the 
bottom would otherwise not be able to drop down further and experience loss aversion. At the same time, 
we will also inquire if he or she would like to adjust their step goal as long as they are within the range of 
a 33% to 50% increase. In previous studies, we’ve found that some individuals set overly ambitious goals 
at the start of the intervention and that for participants who have trouble achieving their initial goals, we 
can re-engage them if goals are reset to a more reasonable level. 
4) Supportive sponsor: Each participant will select a family member or friend of their choice who will 
serve as a supportive sponsor. This person will receive a weekly email with the participant’s progress 
including accumulated points, level in the game, and average step count. This supportive sponsor will 
help to enhance social incentives to motivate the individual towards his or her goal.31 We will encourage 
participants to select someone with whom he or she comes into frequent contact and is close to such as a 
partner, family member, or friend that they see often.  Prior to starting in the study, we will conduct a 
three-way phone call with the participant and their supportive sponsor. We will provide an overview of 
study procedures for their arm assignment, and then prompt the participant and supportive sponsor to 
discuss ways in which they can help the participant meet their step goals. At least 3 goals will be decided 
upon during the conversation, and if needed, we will provide suggestions for supporting the participant. 
The goals that are decided upon will be entered into a survey by study staff, and will be included in 
weekly emails to the supportive sponsor. Every 8 weeks, we will reach out to the participant and 
supportive sponsor if the participant is stuck in lower levels of blue or bronze to determine if changes 
should be made to the original support goals.  
5) Prize: At the end of the intervention period, participants in the platinum or gold levels will receive a 
trophy to recognize their achievement. While this is a nominal incentive of very low monetary value, it 
represents a culmination of participant effort, creates a sense of something to work towards while in the 
game, and conveys a sense of “status” to participants that achieve it. 
During the follow-up period, participants in this arm will continue to receive a daily text message stating 
whether or not they achieved their step goal on the prior day. 
 
--Arm 3: Financial incentive intervention— 
Participants in this arm are informed that each week $14 is placed in a virtual account for them. Each day 
the participant is informed of their step count on the prior day. If the step goal was achieved, the balance 
remains.  Each day the goal is not achieved, the participant is informed that $2 was taken away. We will 
use an 8-week ramp-up period in which daily goals are increased gradually from baseline to targets, as 
this was found to achieve sustained behavior change in previous work. 

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During the follow-up period, participants in this arm will continue to receive a daily text message stating 
whether or not they achieved their step goal on the prior day. 
 
--Arm 4: Gamification + Financial Incentive intervention— 
Participants in this arm will receive both of the interventions described in arms 3 and 4 above. 
 
5.2 Study duration 
This study is anticipated to take up to 5 years to complete. Each participant will be enrolled in a 12-month 
intervention and 6-month follow-up period.  
 
5.3 Target population 
Adult patients at the University of Pennsylvania Health System with an ASCVD 10-year risk score of 
7.5% or greater, or existing ASCVD. 
 
5.4 Accrual 
We will enroll and randomize 1050 participants over a two-year period.  
5.5 Key inclusion criteria 
Participants will be eligible if they: 1) are age 18 years or older; 2) have a 10-year ASCVD risk score of 
7.5% or greater (including those with existing ASCVD); 3) are able to provide informed consent. 
 
5.6 Key exclusion criteria 
Participants will be excluded if they: 1) are already participating in another physical activity study; 2) an 
18-month physical activity program is infeasible (e.g. metastatic cancer; unable to ambulate or provide 
informed consent) or unsafe (currently pregnant or told by a physician not to exercise); 3) they do not 
have a device (e.g. smartphone, tablet, or computer) to transmit data from the wearable activity tracker; 4) 
baseline step count is 7,500 or greater; 5) they do not have a primary care physician in the University of 
Pennsylvania Health System.   
6. Subject recruitment 
Participants will be recruited from the University of Pennsylvania Health System (UPHS) which consists 
of five large hospitals including the Hospital of the University of Pennsylvania, Penn Presbyterian 
Medical Center, Pennsylvania Hospital, Chester County Hospital, and Lancaster General Hospital. There 
are more than 60 primary care practice clinics affiliated with UPHS throughout Pennsylvania and New 
Jersey. Target population: The UPHS population includes patients of mixed socioeconomic status with a 
high rate of ASCVD. Based on initial evaluation, there are more than 100,000 patients at UPHS who meet 
criteria for with a 10-year ASCVD ≥ 7.5% or clinical ASCVD. This will provide an ample population 
from which to perform the proposed clinical trial given that we typically are able to recruit about 30% of 
eligible health system patients for our studies and the target sample size is 1,050 or about 1% of the 
eligible population. 

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Potentially eligible patients will be identified using data from the electronic health record and Penn Data 
Store, the health system’s clinical data warehouse. They will be invited to participate either by e-mail or 
mail letters. Study coordinators will conduct follow-up phone calls to further assess interest and answer 
questions related to the study. In the initial invitation, patients will have the ability to opt out from any 
further communications. Interested patients will be instructed to visit the study website on the Way to 
Health research technology platform to learn more about the study, create an account, provide informed 
consent, and complete initial baseline and eligibility surveys.  
7. Subject compensation 
All participants will receive $30 for enrolling in the study, $30 for completing the 6-month assessment, 
$40 for completing the 12-month assessment, and $50 for completing the 18-month assessment.  Each 
participant will receive a ClinCard, and payments will be uploaded to their card after assessments are 
completed. 
 
8. Study procedures 
 
8.1 Consent 
Upon recruitment, individuals who are interested in learning more about the study will be directed to the 
Way to Health web portal. We will follow an IRB-approved approach taken by many studies using the 
Way to Health platform to obtaining informed consent. Upon reaching the portal, potential participants 
will be asked to create an account and will then be informed of the details of the study, including its 
objectives, duration, requirements, and financial payments.  The Way to Health portal will then take 
interested participants through an online informed consent. The consent document will be divided into 
sections and potential participants will have to click a button to advance through each section. This is to 
help ensure that participants read the consent form thoroughly by breaking down the form into 
manageable blocks of text. Each section will have a button allowing the user to contact a researcher via 
email or by telephone if they have questions about the consent form. Successive screens will explain the 
voluntary nature of the study, the risks and benefits of participation, alternatives to participation, and that 
participants can withdraw from the study at any time. On the final consent screen, potential participants 
who click a clearly delineated button stating that they agree to participate in the study will be considered 
to have consented to enroll. Participants will be provided with details regarding how to contact the 
research team via email or phone at any time if they subsequently wish to withdraw from the study. This 
contact information will remain easily accessible via the participants’ individual Way to Health web 
portal dashboards throughout the study.   
 
8.2 Procedures 
After providing informed consent, participants will complete an online questionnaire to confirm eligibility 
and complete the study surveys. Eligible participants will be mailed a wearable activity tracking device to 
wear for about two weeks to collect a baseline step count.   
Participants will select step goals and then be randomly assigned as described in the Study Design 
section. 

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Surveys and interviews will be conducted as outlined in the Table: 
 
Once the study is completed and the results are published, study staff will reach out to all participants via 
email to disseminate the findings of the study.  
 
9. Analysis Plan 
 
9.1 Power and sample size 
Physical activity has been demonstrated to have a direct dose relationship with reduction in the risk of 
cardiovascular disease and events, with even small increases significantly lowering risk.6,22-25 We use 
1000 steps as our threshold for powering statistical significance, which for the average person is about 
half a mile and takes about 10 minutes of MVPA.26 Based on our prior work,10-14 we estimate a standard 
deviation in the primary outcome of 2500 steps. This study has been powered for six comparisons 
Area
Name
# 
Questions Baseline
6 
Months
12 
Months
18 
Months Validation Study
Screening Survey
NA
X
Baseline 
(demographics)
NA
X
Cardiovascular 
history/Weight/Meds
NA
X
X
X
X
Health status
EQ-5D-5L and 
EQ-VAS
6
X
X
X
X
Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada 
M, Scalone L, Swinburn P, Busschbach J. 
Measurement properties of the EQ-5D-5L compared to 
the EQ-5D-3L across eight patient groups: a multi-
country study. Qual Life Res. 2013;22(7): 1717-1727.
Exercise self-efficacy
Self-Efficacy 
for Exercise 
Behaviors
12
X
X
X
X
Sallis JF, Pinski RB, Grossman RM, Patterson TL, 
Nader, PR. The development of self-efficacy scales for 
health-related diet and exercise behaviors. Health 
Education Research. 1998;3:283-292.
Sleep
Pittsburg Sleep 
Quality 
Assessment
9
X
X
X
X
Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer 
DJ. The Pittsburgh Sleep Quality Index: A new 
instrument for psychiatric practice and research. 
Psychiatry Research. 1989;28:193-213
Mood
PHQ9
9
X
X
X
X
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity 
of a brief depression severity measure. J Gen Intern 
Med. 2001;16(9):606-613.
Social Support
MOS Social 
Support
19
X
X
X
X
Sherbourne CD, Stewart AL. The MOS social support 
survey. Soc Sci Med. 1991;32(6):705-714.
Risk Preferences
DOSPERT
30
X
Blais A, Weber EU. A domain-specific risk-taking 
(DOSPERT) scale for adult populations. Judgement 
and Decision Making. 2006;1(1):33-47.
Personality
Big Five
44
X
John OP, Srivastava S. The Big-Five trait taxonomy: 
History, measurement, and
theoretical perspectives. In L. A. Pervin & O. P. John 
(Eds.), Handbook of personality: Theory
and research. New York: Guilford Press. 1999;2: 
102–138.
Grit
Grit Scale
10
X
Duckworth AL, Quinn PD. Development and validation 
of the short grit scale (grit-s). J Pers Assess. 
2009;91(2):166-174. 
Qualitative survey
NA
X
X
Interviews
X

10 
 
between arms using a common cutoff for the test statistics that ensures the familywise error rate is at most 
0.05.  This is the approach suggested in Follmann et al.27 and it generalized Tukey’s Honest Significant 
Differences approach for an unbalanced design.  We estimate that a sample of 1050 participants allocated 
in a 1:2:2:2 distribution (150 in control and 300 in each intervention arm), will ensure 93% power to 
detect a 1000 step difference between each intervention arm and control, with a standard deviation of 
2500 steps and an 8-minute difference in MVPA assuming a standard deviation of 20 minutes.  This 
calculation assumes a 10% dropout rate. We estimate that we will have at least 85% power to detect a 
750-step difference with a standard deviation of 2500 steps and a 6-minute difference in MVPA with a 
standard deviation of 20 minutes.  
 
9.2 Comparative-effectiveness analysis 
Prior to analyses, we will produce data summaries to assess data quality, examine data distribution, and 
randomization success. All analyses will be performed using intention-to-treat. Data can be missing for 
any day if the participant did not use the activity tracking device or did not upload data. For the main 
analysis we will use multiple imputation for step values that are missing or less than 1000 steps. We will 
perform five sets of imputations and results will be combined using Rubin’s standard rules.28 We will 
perform sensitivity analyses to assess the robustness of the findings using only collected data with and 
without step values less than 1000 steps. Since minutes of MVPA are derived from step counts, this 
process should address missing data for MVPA as well.   
Similar to prior work,12 the primary analysis will fit linear mixed effect regression models to evaluate 
changes in physical activity outcomes measures (primary and secondary outcomes) adjusting for each 
participant’s baseline measure, time using calendar month fixed effects, participant random effects, and 
accounting for repeated measures. Secondary analyses will fit linear mixed effect regression models 
adjusted for other variables of interest such as participant demographic characteristics and cardiovascular 
history. Exploratory analyses will fit logistic mixed effect regression models to evaluate the proportion of 
weeks that CDC guidelines for physical activity were achieved. 
We will perform subgroup analyses using available participant sociodemographic characteristics 
including age, sex, race/ethnicity, education, and income level. We will also conduct subgroup analyses 
using differences in baseline measures such as baseline step count and atherosclerotic cardiovascular 
disease (ASCVD) 10-year risk score. If differences in outcomes exist, we will fit a fully adjusted model 
that includes these covariates and interaction terms with the treatment arms to evaluate for statistical 
significance. 
 
9.3 Cost-effectiveness analysis 
To compare the cost-effectiveness of each intervention compared to control, we will follow 
recommendations from the Second Panel on Cost-Effectiveness in Health and Medicine.29,30 Based on the 
Panel’s recommendations, we will use two perspectives: a health care sector perspective and a societal 
perspective. Our primary analysis will use differences between each intervention and control in measures 
of physical activity (steps and minutes of MVPA), and in health-related quality of life measured by the 
EQ-5D,19-21 as the outcome measures. We will explore using a simulation model to translate changes in 
these measures into quality-adjusted life-years (QALYs) over a longer period.31-34 

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The costs incurred from a health care sector perspective include costs for the Way to Health research 
technology platform, staff, wearable devices, data storage, and financial incentives. Outcomes will be 
summarized in the form of incremental cost-effectiveness ratios (ICERs) that show the difference in costs 
between two arms of the trial (e.g., the gamification and control arms) divided by the difference in 
outcome (e.g., step count).  Deterministic (1-way and multi-way) and probabilistic sensitivity analyses 
will be conducted to determine the key drivers behind the cost-effectiveness ratios. 
The additional costs incurred by a societal perspective include the time participants spend on the 
intervention and physical activity itself and out-of-pocket costs related to the intervention such as clothing 
for exercise. Participants will be surveyed at the end of the study to capture these measures. These 
additional costs will be captured within the ICERs. 
 
9.4 Process evaluation 
In order to understand how our interventions were implemented and received by participants, we will 
conduct a mixed-methods process evaluation.35 All participants will be asked to complete an end-of-study 
fixed response questionnaire measuring their satisfaction with the wearable device, research technology 
platform, and intervention design. They will also complete a series of validated surveys including MOS 
Social Support Survey,18  and the EQ-5D health-related quality of life survey.19-21 to explore changes in 
participant characteristics associated with strong or poor performance. All questionnaires and surveys will 
be administered electronically via the Way to Health portal. 
We will conduct semi-structured qualitative interviews with study participants purposefully selected by 
performance. In each arm, we will split the participants into two groups based on performance above and 
below the mean of that arm. We will randomly invite up to 10 participants from each of the two groups to 
complete a 30-minute telephone interview (up to 80 total participants across all 4 arms, or until we reach 
saturation in each group). We will provide $50 for participating in the interview.  
Interviews will be conducted by a trained research assistant using a semi-structured interview guide 
informed by the theoretical domains framework (TDF).36,37 The TDF provides a lens through which to 
view the cognitive, affective, social and environmental influences on behavior in relation to the 
implementation of complex interventions to improve health.38 It includes 14 domains: knowledge, skills, 
social role and identity, beliefs about capabilities, optimism, reinforcement, intentions, goals, decision 
processes, environmental context and resources, social influences, emotion and behavioral regulation. We 
will create open-ended interview questions informed by these domains. The guide will also include 
questions on the following topics: (1) factors motivating participation in the study, (2) prior experiences 
with trying to increase physical activity, (3) perceptions of the intervention including its impact on his or 
her performance and perceived risks and benefits. Participants will be asked to describe aspects of each 
intervention element that helped them to achieve their physical activity goals and aspects that did not. The 
interview guide will also elicit information about intervention burden as well as suggestions for 
improvement in intervention design. The interview guide will be developed, refined and piloted prior to 
the trial launching. 
Interviews will be audio recorded and professionally transcribed. Transcripts will be uploaded to 
qualitative data analysis software (e.g. NVivo) for management and coding. Two trained coders will 
perform the coding, in close collaboration with the study PIs. We will utilize a mixed inductive-deductive 

12 
 
approach to analysis.39 We will begin by reading through a subset of transcripts from respondents in both 
performance levels to generate our preliminary coding framework. We will create two types of codes in 
this phase of analysis: (1) descriptive codes based on our interview guide and factors previously identified 
in the literature and (2) interpretive codes that emerge from the data. 
Once the coding framework has been created and discussed with the study team, the coders will read 
through the interview transcripts line by line and apply codes to the data. The coding framework will be 
open to expansion and refinement throughout analysis, should the coders come upon novel salient themes. 
Intercoder reliability will be assessed every fifth transcript.  We will calculate a coefficient of reliability 
(the ratio of coding agreements to the total number of coding decisions) for one selected interview 
document.40 A coefficient of greater than 0.95 will be our cut off for proceeding with the coding. If our 
coefficient is less than 0.95, we will review the discrepancies, refine code definitions and reeducate the 
coders to ensure reliability. Once the entire data set has been coded, we will perform cross-code searches 
and explore variation in themes across respondents by performance on the intervention and by 
sociodemographic characteristics to identify higher-order patterns. 
 
9.5 Safety analysis 
Participants will be asked to report any study-related injuries or hospitalizations. These will be reviewed 
with the Principal Investigator and the patient will be contacted if there is a risk to continuing in the trial. 
We will constitute a DSMB comprised of 3 experts with one being a statistical expert, another an expert 
in physical activity, and a third being someone who is experienced in leading trials of behavioral 
interventions. As per NIH guidelines we are not naming anyone now so as not to preclude reviewers from 
their academic institutions. All adverse events will be reported to the IRB and DSMB. We will also ask 
participants to report study-related injuries, falls, emergency department visits, and hospitalization on the 
12-month and 18-month surveys. We will evaluate these data in a blinded fashion after 25%, 50%, 75%, 
and 100% of participants complete the intervention and follow-up periods. This plan will be reviewed 
with the DSMB and modified as necessary prior to participant enrollment. Our plan will be to have 
milestone-driven meetings with the DSMB likely approximately every six months. 
 
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