Development and Proof-of-Concept Trial of a Meaning- and Theory-based Physical Activity Intervention
Phase: NA
Conditions: Physical Inactivity
Sponsor: HealthPartners Institute

 
 
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Development and Proof-of-Concept Trial of a  
Meaning and Theory-Based Physical Activity Intervention  
 
NCT05332145 
Last IRB approval: 09/21/2022 
 
 

 
 
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Title: Development and Proof-of-Concept Trial of a Meaning and Theory-Based Physical Activity 
Intervention 
Grant Number: 1R21AG070161-01A1 
PI: Stephanie A Hooker, PhD MPH 
1. Summary  
Physical activity (PA) has numerous benefits, including reduced risk for chronic disease and cognitive 
impairment, improved mental health and well-being, and increased longevity. However, when measured 
objectively, only 5% of adults meet recommended PA guidelines of 150 min/week. Many interventions have 
been developed to increase PA among insufficiently active adults, yet the effects are modest, and many 
people return to inactive lifestyles after the intervention is completed.  
 
Meaning in life, the sense that one’s life matters, makes sense, and has purpose, has been shown to be a 
robust predictor of PA. To date, no PA interventions have thoughtfully incorporated meaning in life. A 
meaning-based approach is consistent with Self-Determination Theory (SDT), a theory of human 
motivation and behavior. The overall goal of this project is to systematically incorporate meaning in life and 
SDT principles into a web-based and text message intervention (Meaningful Activity Program [“MAP to 
Health”]) to increase PA among insufficiently active adults in midlife. The project will use Science of 
Behavior Change principles and the Obesity-Related Behavioral Intervention Trials (ORBIT) framework to 
conduct a Phase IIa proof-of-concept pilot study of MAP to Health.  
 
The study has two aims: (1) to develop and examine the acceptability of the technological and 
theoretical frameworks of MAP to Health and (2) to determine whether MAP to Health is related to 
changes in theoretically identified mechanisms of behavior change (meaning salience, basic 
psychological needs satisfaction, and internal motivation). In an exploratory aim, we will assess how 
the intervention and mechanisms of change are related to changes in PA. Participants will be adults in 
midlife (ages 40-64) who are insufficiently active, are interested in increasing PA, do not have 
contraindications to engaging in PA, and are patients in a large healthcare system in the Midwest.  
 
In Phase 1, we will develop the MAP to Health online web-based interview that will be used to explore what 
is particularly meaningful to participants, how PA is consistent with those goals, and what activities patients 
plan to engage in. Participants (N=12) will complete the interview and rate the ease of use, usefulness, 
intention to use, and theoretical fidelity of the intervention.  
 
In Phase 2, we will conduct a proof-of-concept pilot trial using a double-pretest single group design. 
Participants (N=35) will complete a 4-week pretest monitoring period and an 8-week pilot trial of the 
intervention, with assessments of SDT mechanisms and meaning salience at pretest (-4 weeks), baseline 
(0 weeks), midpoint (4 weeks) and posttest (8 weeks). In addition, participants will wear accelerometers to 
assess PA during the 12 weeks.  
 
2. Study Aims  
Aim 1 (Development): To assess the acceptability of underlying theoretical and technological frameworks 
of the web-based MAP to Health interview. 
H1a: Participants will rate the web-based interview as easy to use and useful and will report intentions 
to use the intervention.   
H1b: The web-based interview will solicit data necessary to program theory-based, personalized text 
messages for participants.  
Aim 2 (Proof-of-concept testing): To determine whether MAP to Health is related to changes in 
theoretically identified behavior change mechanisms. 
H2:   Participants will experience increases in the theoretically identified mechanisms of behavior 
change (i.e., meaning salience, internal motivation, and basic needs satisfaction) after receiving the 
MAP to Health intervention compared to a pre-test no intervention period. 

 
 
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Exploratory Aim: To assess whether the intervention and increases in the hypothesized behavior change 
mechanisms (meaning salience, internal motivation, and basic needs satisfaction) are associated with 
increases in PA compared to the pretest no intervention period.  
 
3. Background, Rationale, Significance  
A. Given its numerous benefits for physical and mental health, physical activity (PA) may be one of 
the most important behaviors for healthy aging. In particular, PA is known to be related to reduced risk 
of chronic disease, such as coronary heart disease and type 2 diabetes, improved mental health and well-
being, improved cognitive functioning (and lower risk of Alzheimer’s disease and other dementias), 
improved ability to engage in activities of daily living, and increased longevity.1,2 The evidence that PA is 
beneficial for health is so overwhelming that some have argued that nearly everyone could benefit from 
PA.3 However, 90% of US adults do not meet recommended guidelines of ≥150 minutes of moderate-
intensity PA per week (or 75 minutes of vigorous PA);4 when PA is objectively measured, this number rises 
to 95%.5  
 
B. Given the importance of engaging in regular PA for 
health, there has been considerable effort to develop 
interventions to increase PA, with modest results.6 
Interventions to increase PA generally demonstrate short-term 
success but not long-term maintenance7,8 and report varying 
attrition rates, with most participants dropping out in the first 6 
months.9,10 One potential explanation for this gap is the lack of 
systematic, mechanistic approaches to PA intervention 
development. In particular, despite the abundance of research 
examining theoretical psychosocial determinants of PA,11 
theory is often poorly applied to behavioral interventions.12 
Consequently, it is clear that new and innovative interventions 
focused on psychological mechanisms known to predict PA 
adoption and maintenance are desperately needed. 
 
C. The theory-based, mechanism-focused approach to the 
research proposed herein is aligned with the NIH Science 
of Behavior Change (SOBC) program and Stage I of behavioral intervention development. The 
SOBC emphasizes basic research grounded in theory to identify targeted mechanisms and assessment of 
the degree to which those targets are engaged and lead to behavior change. In the current study, we 
respond to the SOBC call for an experimental approach to behavior change by constructing an intervention 
aligned with theory and targeted mechanisms and testing theoretical validity of the intervention and its 
initial ability to change hypothesized mechanisms. The proposed study falls within Phase IIa (i.e., proof-of-
concept testing) as described in the Obesity-Related Behavioral Intervention Trials (ORBIT) Model for 
Developing Behavioral Treatments for Chronic Diseases.13 The ORBIT model parallels the widely accepted 
drug development model.14 In the proof-of-concept phase, the aim is to prove the concept that the 
intervention is effective at targeting theoretical mechanisms of change before advancing research to 
subsequent stages (efficacy and effectiveness trials). By employing SOBC and ORBIT frameworks, we will 
efficiently generate better understanding of the how and why of behavior change, enabling more precise 
future theory testing and development of effective interventions to increase PA.  
 
D. Self-Determination Theory (SDT)15 is a promising theory upon which to build innovative 
interventions to enhance long-term behavior change. SDT suggests that social environments that 
support the basic psychological needs of autonomy (feeling behavior is self-organized, accompanied by a 
sense of volition), relatedness (feeling connected to others), and competence (feeling capable of achieving 
goals) foster the internalization of motivation and facilitate behavior change. SDT posits that internally 
motivated behaviors are more likely to be maintained than behaviors that are extrinsically motivated. In 
SDT, motivation exists on a continuum from external regulation to internal regulation; research 
demonstrates that individuals who report more internally regulated motivation (i.e., motivated by 
Table 1. List of Abbreviations Used 
CESR 
Center for Evaluation and 
Survey Research 
EHR 
Electronic health record 
HP 
HealthPartners 
MI 
Motivational interviewing 
MAP 
Meaningful Activity Program 
MVPA 
Moderate-to-vigorous 
physical activity 
ORBIT Obesity-Related Behavioral 
Intervention Trials 
PA 
Physical activity 
SDT 
Self-determination Theory 
SOBC 
Science of Behavior Change 
TAM 
Technology Acceptance 
Model 

 
 
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congruence with the self or enjoyment) also engage in more in PA and experience more positive 
psychological outcomes of exercise participation.16-20 Exercise intervention research suggests that 
previously inactive exercise initiates experience a decrease in external regulations and an increase in more 
internalized motivations over time,21 and that more self-determined motivations are associated with greater 
exercise persistence.22 Three RCTs examining SDT-based interventions to increase PA23 using 
motivational interviewing (MI)24 frameworks demonstrated that increasing self-determined motivation 
increased PA.25 These interventions used 1:1 (e.g., physician and patient) or group interventions to deliver 
intervention content; to our knowledge, none of the SDT interventions have used ecological momentary 
interventions to deliver SDT-based messages to encourage PA. 
 
E. SDT interventions can be enhanced by integrating meaning salience. Meaning in life is the sense 
that one’s life matters, makes sense, and has purpose.26 Meaning and existential literatures explicate the 
basic human need to live a meaningful life. Research shows that people who engage in intrinsically 
meaningful life activities experience greater life satisfaction and well-being.27 Although previous SDT 
intervention studies23,28,29 assessed personal life goals and values, they did not deliberately integrate them 
with behavior change techniques or enhance awareness of meaning in life during the intervention. We 
hypothesize that meaning salience, or the extent to which individuals live with awareness of their sense of 
personal life meaning, is key to enhancing behavior change. This hypothesis is an implicit, but essentially 
ignored, aspect of SDT that suggests that integrating or directly linking new behaviors with important and 
salient aspects of meaning in life increases the likelihood of long-term maintenance of the new behaviors.30-
32 Moreover, Ryff and Singer33 suggest that individuals who live with awareness of a sense of meaning in 
life (i.e., meaning salience) may be more motivated to engage in healthier behaviors.34 Research supports 
this claim and observational findings show that greater meaning is related to greater engagement in PA.35-
39 Further, a recent meta-analysis40 found that possessing a high sense of meaning in life was associated 
with reduced risk for all-cause mortality and cardiovascular events. Additional evidence suggests that 
meaning is associated with improved health measured in a variety of ways, including subjective (e.g., self-
rated health) and objective (e.g., biomarkers) health indicators.41,42 Nevertheless, there are many reasons 
individuals fail to act in ways congruent with their sense of meaning, including the lure of short-term 
hedonic pleasures (e.g., watching a favorite TV show) and demanding environmental stimuli (e.g., 
peer/work pressure) that transfer their attention from what is meaningful toward what is immediate or 
comfortable. Thus, meaning salience is considered a state that can vary over the course of a day. We 
hypothesize that behaviors explicitly integrated within one’s life meaning are more likely to be maintained, 
particularly when the meaning salience is accentuated daily.  
 
F. Midlife (ages 40-64) may be an important time to harness meaning and establish a healthy 
behavior pattern to improve health in later life. Evidence suggests that PA tends to decline as 
individuals age,43,44 even though engaging in health behaviors during this time may be more important than 
ever to prevent development of chronic disease and enhance healthy aging. Indeed, midlife PA levels are 
related to longer telomeres (a biological indicator of healthy aging) and improved cognition in old age.45,46 
Further, although midlife is a time when risk factors such as high blood pressure emerge,47 physical fitness 
in midlife is associated with delayed onset of chronic disease.48 However, midlife is also a time in human 
development when meaning becomes more salient.49 Thus, adults in midlife may be a particularly apropos 
group in which to test the hypothesis that pairing meaning with PA enhances PA engagement.  
 
G. Preliminary Studies 
Development of Colorado MAP (COMAP). Dr. Hooker and her colleagues systematically developed a 
smartphone intervention to increase PA in inactive healthy adults that was based on SDT and meaning and 
serves as the prototype for the present study.50 Focus groups of previously inactive adults provided 
feedback on the feasibility, utility, and usability of the COMAP app as well as general feedback regarding 
the initial interview, length of the program, and overall impressions. The team then modified the 
intervention based on the focus group feedback and recruited 10 inactive adults to participate in COMAP 
for 2 weeks. Participants gave feedback regarding their experience with COMAP and the response was 
overwhelmingly positive, with all participants reporting increased PA. Participants were particularly positive 
about the initial interview and personalized push notifications. Despite the initial success of the smart 
phone app, major challenges of using this platform include the need to develop multiple versions to reach a 

 
 
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wider audience (iOS and Android) and maintenance of the app(s) after development due to continual 
operating system updates. Thus, for this project, we chose to use a web platform plus text messages to be 
able to disseminate the intervention more easily. 
Observational studies of meaning and PA. Dr. Hooker led a study wherein 100 community members 
completed a self-report measure of meaning and then wore accelerometers for three consecutive days.37 
Meaning was significantly and positively related to total activity counts and self-reported PA, and it was 
marginally related to minutes of moderate-to-vigorous PA (MVPA). A second study, supported by the 
American Heart Association, examined the associations of SDT, meaning, and PA in a group of 160 
previously inactive adults starting new PA programs.51,52 Meaning was significantly and positively related to 
basic psychological needs satisfaction and internal motivation. Meaning, needs satisfaction, and internal 
motivation at baseline were significantly and positively related to PA at 4-weeks. In a second aim, 80 
participants recorded meaning salience, mood, and PA daily for 4 weeks. Meaning salience was 
significantly and positively associated with daily PA duration and intensity and a greater likelihood of 
attending the fitness center. 
 
4. Approach  
a. Study Design 
This study will use a pilot study design with two phases (see Figure 1). In Phase 1, an iterative, rapid 
development approach to assess intervention usability, acceptability, and intervention fidelity. In Phase 
2, we will use a double-pretest single group pilot study to assess the effects of the intervention on 
proposed intervention mechanisms and physical activity. 
 
i. Phase 1: Development of web-based MAP to Health Intervention 
Phase 1 consists of alpha and beta testing to examine the usability and acceptability of the 
technological and theoretical frameworks. During the first phase, the in-person interview designed 
during the COMAP pilot study will be translated into an interactive, web-based interview to determine 
how participants derive meaning and how that might be connected to reasons they want to be more 
physically active. Then, participants will be guided in setting small, realistic goals to be active in the 
next two weeks and will plan when they will be active.  
Phase 1. Development: Usability, acceptability, and intervention fidelity (N = 12) 
Phase 2. Intervention proof-of-concept testing (N = 35) 
Interview test: 
4 participants  
Interview test: 
4 participants  
Interview test: 
4 participants  
Review & 
Revise 
Week  
Pretest (-4) 
 
   Baseline (0)  
 
Midpoint (4) 
 
Posttest 
MAP to 
Health 
Interview 
SDT 
mechanisms 
Intervention 
activities 
Meaning 
salience  
 
Physical 
Activity 
Theory-based, personalized text messages 
Weekly goal setting 
Figure 1. Study design.  
3/week 
Continuous (Measured by ActiGraph) 
Review & 
Revise 
Basic needs  
& internal 
motivation 
Basic needs  
& internal 
motivation 
Basic needs  
& internal 
motivation 
Basic needs  
& internal 
motivation 
3/week 
3/week 
3/week 

 
 
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In Phase 1, we will use the Technology Acceptance 
Model (TAM; see Figure 2) as a framework for 
evaluation, as it has been widely used to examine the 
usability and acceptability of interventions using 
technology.53-57 Based on the Theory of Reasoned 
Action, the TAM proposes that attitudes about 
perceived ease of use and perceived usefulness 
predict intention to use the technology, which then 
predicts actual technology use. We will use the TAM 
framework to ensure that the technological interface is 
acceptable to participants prior to moving to a proof-of-
concept pilot trial. 
After internal testing of software fidelity, 12 patients will be recruited to test the interview to 
determine the acceptability and usability and whether the interview appropriately gathers information 
needed to program theory-based, personalized text messages (see Figure 1). Participants will 
complete an e-consent form, the web-based interview, and Phase 1 measures. 
After completing the measures, a list of text messages for that participant will be generated and 
displayed to the participant for review. Participants will review the text messages and rate the extent 
to which the messages are personalized to their sense of meaning and goals. Intervention 
modifications will be made iteratively; four participants will complete the web-based interview and 
review text messages. After each round of testing, the intervention will be modified to increase 
below-threshold ratings on the TAM constructs or intervention fidelity to theory. The process will 
repeat for at least three rounds, until the team is confident the interview is ready for preliminary 
testing in Phase 2. 
ii. Phase 2: Intervention Proof-of-Concept Testing 
Aim 2 will use a single-group, double pretest design to examine change in theoretical mechanisms 
prior to and during participation in MAP to Health (see Figure 1 for details). After completing the 
baseline measures, participants (N = 35) will begin the intervention by completing the web-based 
interview. For the next 8 weeks, they will receive personalized, theory-based text messages at times 
that they identify as opportune for PA, 2 times per day. After week 2, patients will receive a weekly 
link, via text message, to the calendar in the web-based application to set new goals for planned PA. 
At the four main assessments (pretest -4, baseline 0, midpoint 4, posttest 8), participants will 
complete SDT mechanism measures (needs satisfaction and internal motivation).  
Because meaning salience is a state, participants will be asked to report on meaning salience on 3 
random days during the same weeks. Participants will be given ActiGraph wGT3X-BT 
accelerometers to wear over the course of the 12 weeks; data will be automatically uploaded to the 
cloud and research staff will monitor wear compliance, reaching out to participants after 2 
consecutive days of no wear. At the end of the study, participants will rate the acceptability of the 
intervention using the same measures from Aim 1 and complete open-ended questions asking for 
qualitative feedback on intervention components and the use of accelerometers.  
b. Population 
i. Inclusion/Exclusion Criteria  
The eligibility criteria were chosen to identify a sample of insufficiently active midlife adults, without 
serious medical or psychiatric conditions, who are interested in increasing PA. Insufficiently active 
adults (individuals who engage in PA between 10 and 149 min/week)43 were chosen because they 
have indicated interest in engaging in PA but not yet made PA a regular habit. This group represents 
one quarter of adults43 who could use support to meet PA guidelines.  
Inclusion Criteria 
• 
Midlife (ages 40-64 at enrollment) 
• 
Able to read and understand English 
• 
Insufficiently active (engaging in ≥10 and ≤149 min of PA/week) 
• 
Intention to increase PA in the next 30 days 
MAP to 
Health 
Use 
Perceived 
Ease of 
Use 
Intention 
to Use 
Figure 2. Technology Acceptance Model. 
Perceived 
Usefulness 

 
 
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• 
Has consistent access to a smartphone with text-messaging capability 
• 
Able to access internet through phone or computer (to participate in intervention activities) 
 
Exclusion Criteria 
• 
Greater than minimal risk to starting a PA program (Physical Activity Readiness Questionnaire 
score > 0) 
• 
BMI ≥ 40 
• 
Currently pregnant 
• 
Has opted out of research 
• 
Diagnosis of metastatic cancer or cardiovascular disease 
• 
Residing in a nursing home or long-term care facility 
• 
Cognitive or psychiatric conditions that preclude completion of questionnaires, including dementia 
diagnosis 
• 
Diagnosis of severe psychiatric disorder (e.g., Bipolar Disorder, Schizophrenia) 
• 
Diagnosis of substance use disorder or AUDIT-C62 >7 
 
ii. Sample size 
To identify potential participants, we will use electronic health records (EHRs) of patients from 
HealthPartners, Park Nicollet, and Stillwater Medical Group clinics who meet eligibility criteria. Then 
the Programmer Analyst will randomly select potential participants to recruit and screen. Recruitment 
samples will be stratified on sex and race/ethnicity; specifically, we will oversample racial and ethnic 
minorities to ensure adequate representation.  
Because some eligibility criteria are not available in EHR, potential participants will be further 
assessed for eligibility during the phone screening process. Estimating a 2-3% participation rate, we 
will pull a recruitment sample of 2250 patients: 250 in Phase 1 and 2,000 in Phase 2. 
For Phase 1, we will recruit up to 20 participants for usability testing. We anticipate that we will recruit 
a minimum of 12 participants, with three rounds of 4 participants. This sample size was chosen 
because it is the industry standard for this type of usability testing (~10 participants). We have 
included an additional 8 participants in case we need to conduct additional rounds of usability testing. 
For Phase 2, we will recruit up to 45 participants for the proof-of-concept pilot trial. Our power 
analysis indicates that a minimum of 35 participants is needed to detect a meaningful change in the 
hypothesized mediators (see Phase 1 Power Analysis for details). 
c. Data collection process 
i. Identifying Participants 
Potential participants will be identified EHRs by a Research Informatics Programmer Analyst. The 
Programmer Analyst will use available inclusion/exclusion criteria above to identify potentially eligible 
patients, stratify on sex and race/ethnicity, apply a random selection algorithm to that list, and check 
the research opt-out list. Once the list of potentially eligible participants has been narrowed to the 
appropriate sample size, the analyst will then pull demographics and contact information.  
For Phase 1, we may also offer the study to employees of HealthPartners who believe they meet the 
study inclusion exclusion/criteria.  
After Phase 1 is complete and the intervention is ready to move to Phase 2 proof-of-concept testing, 
another EHR recruitment batch will be gathered. Prior to starting the next recruitment batch, each 
newly generated list will be checked against the research opt-out list, and then reviewed to eliminate 
patients who have already had direct CESR staff contact (e.g., enrolled in the study, did not meet full 
eligibility criteria, opted out from further study contact).  
In Phase 2, we will partner with the HP Communications team to use social media and other 
communication strategies to advertise the study. Interested individuals will be directed to a self-
screening link in REDCap to see if they are eligible. If so, the CESR team will reach out to screen and 
confirm eligibility. 
ii. Recruitment 

 
 
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Recruitment, consent, and study assessments will be conducted by the Center for Evaluation and 
Survey Research (CESR) at HP. Patients in the recruitment sample will be sent a letter informing 
them of the research opportunity; CESR staff will make follow-up phone calls to conduct eligibility 
screening. In Phase 1, the recruitment process will be ‘batched’ to recruit patients on a rolling basis. 
For example, 4 patients will be recruited at a time for 3 consecutive rounds.  
CESR study staff will mail an introductory letter with study description and elements of informed 
consent to potential participants. The letter will include next steps for interested individuals to 
complete an online self-screener in REDCap or call CESR staff using a study-specific phone line for 
more information, opt out of further contact, or wait for a follow-up call from CESR staff. Up to three 
follow-up calls will be made. Call-management software will ensure that calls are made at different 
times of day and days of the week, including evenings and Saturdays, to maximize likelihood of 
contact.  
Upon successful contact, CESR staff will explain the study, gauge patient interest, complete eligibility 
screening, and collect required study participant information (i.e., cell phone number, email address). 
Participants who provide verbal consent for participation will be sent a study confirmation e-mail with 
a link to the MAP to Health web-based platform. For Phase 1, if participants have not completed the 
study within 2 business days, one reminder email will be sent. 
For Phase 1 only, we will also offer the study through email and huddle meetings to HealthPartners 
employees. Interested individuals can reach out to the study team via email to be screened and 
determine eligibility.  
In Phase 2, CESR staff will schedule participants for an initial study orientation visit with the project 
manager, either virtually (phone or Microsoft Teams) or in-person, based on the participants’ 
preference and in compliance with COVID-19 infection control guidelines. The CESR team will send a 
study confirmation e-mail with a link to the MAP to Health web-based platform, including details about 
how to register and complete the pre-test survey, and their scheduled study orientation visit. 
See Appendix A for Phase 1 recruitment materials. See Appendix D for Phase 2 recruitment 
materials. 
iii. Consent 
We are requesting a waiver of informed consent from the HealthPartners IRB to access patient data 
needed to determine potential eligibility and contact potential participants.  
During phone screening, participants will be given a description of the study activities and informed 
about the voluntary nature of the study. They will be given opportunities to ask questions before 
providing verbal consent to participate. After providing informed consent, staff will send study 
confirmation email to interested participants with instructions for study activities and link to the MAP to 
Health web-based platform, which will contain an e-consent form (both Phases). Participants will be 
required to consent to the study using the e-consent form before participating in any future study 
activities. 
iv. Data Sources 
HealthPartners Electronic Health Record (Epic/Clarity). EHR data will be extracted by the 
Programmer Analyst to identify a sample of potentially eligible HP patients to invite to participate. 
These data will include identifying information (name, address, phone number, email), demographic 
characteristics (sex, race, ethnicity, DOB), and clinical characteristics (diagnoses, vitals [BMI], visits).  
Self-Report Surveys and Screening Questionnaires. Self-report surveys and screening 
questionnaires will be stored in REDCap, a secure database management software. CESR staff will 
use REDCap to store data related to phone recruitment scripts, eligibility screening, and consent 
information. Participants will directly answer self-report survey questions in REDCap software that 
they receive through a link in a text message or email. 
MAP to Health Intervention Web-Based Platform. The web-based MAP to Health intervention is an 
interactive tool to guide participants through identifying reasons to engage in physical activity and 
scheduling those activities. As part of the intervention, participants will be prompted to respond to 
questions about physical activities, meaning, values, and barriers. This platform will be developed by 

 
 
9 
programmer from HPI’s Software & Engineering Team. These data will be collected and stored on a 
secure HPI server and will be used to generate personalized text-messages.  
ActiGraph Accelerometers. Participants in Phase 2 will wear ActiGraph accelerometers for 12 
weeks to monitor physical activity. These data will be uploaded directly to a cloud-based software 
provided from ActiGraph (CentrePoint) and accessed by our study team. The project manager will 
introduce the ActiGraphs and procedures to participants during the study orientation visit and will 
monitor use and remind participants to charge and wear the ActiGraphs throughout the study. 
 
v. Process steps for data acquisition  
Phase 1: 
1. Identifying Eligible Patients: 
Potential participants will be identified through either (1) HP EHR by a Research Informatics 
Programmer Analyst or (2) by advertisements among HP employees. For the first method, the 
Programmer Analyst will use the inclusion/exclusion list to determine potentially eligible 
participants. The Programmer Analyst will exclude participants who have opted out of research at 
this phase. For HP employee recruitment, we may offer the study through email or announce the 
availability of the study at Huddles.  
2. Recruitment & Screening: 
Potential participants identified through the EHR will be mailed a letter that describes the study 
and invites them to participate. Interested individuals will have the option to call the study team if 
they are interested, or they can wait for a phone call from CESR staff. For individuals who express 
interest from advertisements, they will reach out to study staff to schedule an eligibility screening 
call. For participants recruited through both sources, a CESR survey specialist will talk with 
potentially eligible participants via phone to screen for additional eligibility requirements. 
Specifically, they will ask questions about recent physical activity, interest in increasing activity, 
readiness for physical activity (Physical Activity Readiness Questionnaire), alcohol use (AUDIT-
C), consistent access to a phone with text-messaging capability, and access to internet (through 
phone or computer). If individuals are eligible, CESR staff will send participants a study 
confirmation email with a link to the web-based platform, which will contain an e-consent form. 
3. MAP to Health Web-Based Interview:  
Participants in Phase 1 will use the MAP to Health web-based platform to complete the MAP to 
Heath Interview, further described below in Section 4dii. See Appendix B: Phase 1 Intervention 
Tools for an outline of the interview.  
4. User Experience and Feedback: 
Immediately after completing the MAP to Health interview, participants will be directed to a 
REDCap survey to evaluate the usability and theoretical fidelity of the interview. They will also 
provide feedback using open-ended questions. See Appendix C: Phase 1 Survey Measures. 
5. Text Message Review and Ratings: 
After completing the measures rating the acceptability and theoretical fidelity of the interview, 
participants will review a list of generated text messages. They will rate the extent to which the 
messages are personalized to their sense of meaning and goals. See Appendix B: Phase 1 
Intervention Tools for templates of text messages. 
6. Incentives: 
The Project Manager will confirm that the participants have completed the web-based interview 
and survey measures. The Project Manager will send a $25 gift card to the participant as a thank 
you for their time. 
 
Phase 2: 

 
 
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1. Identifying Eligible Patients: 
Potential participants will be identified through HP EHR by a Research Informatics Programmer 
Analyst. The Programmer Analyst will use the inclusion/exclusion list to determine potentially 
eligible participants. The Programmer Analyst will exclude participants who have opted out of 
research as well as anyone who was involved in Phase 1. Additional recruitment may be 
conducted in collaboration with the HP Communications team through social media posts or press 
releases. 
2. Recruitment & Screening: 
Potential participants identified through the EHR will be mailed a letter that describes the study 
and invites them to participate. Interested individuals will have the option to complete an online 
screener to determine if they are eligible or call the study team if they are interested, or they can 
wait for a phone call from CESR staff. A CESR survey specialist will talk with potentially eligible 
participants via phone to screen for additional eligibility requirements. Specifically, they will ask 
questions about recent physical activity, interest in increasing activity, readiness for physical 
activity (Physical Activity Readiness Questionnaire), alcohol use (AUDIT-C), consistent access to 
a smartphone with text-messaging capability, and access to internet (through phone or computer). 
If individuals are eligible, CESR staff will schedule participants for a study orientation visit with the 
Project Manager and send them a study confirmation email with a link to the web-based platform, 
which will contain an e-consent form, and a detailed list of study activities. See Appendix D for 
Phase 2 recruitment materials. 
3. Outcome Assessments:  
Participants will complete survey measures at 4 time points: pre-test (-4 weeks), baseline (0 
weeks), midpoint (4 weeks), and posttest (8 weeks). To improve retention, we will send regular 
text and email reminders to complete study activities (up to 3 per assessment). If participants 
have not completed surveys after email and text prompts, the Project Manager may make one 
follow-up phone call to encourage completion. 
a. Pretest (-4 weeks): After reviewing the e-consent form, participants will complete the Pretest 
survey measures in REDCap through the MAP to Health web-based platform. Participants will 
complete measures of the hypothesized intervention mechanisms (basic psychological needs 
satisfaction and internal motivation) as well as demographic and physical activity history 
measures that will be used to describe the sample. During the study orientation visit, the 
Project Manager will confirm that participants have completed the Pretest survey and will mail 
participants the accelerometer. During the orientation visit, the Project Manager will review 
instructions for the accelerometer, including instructions on how to wear it, charge it, and 
ensure that the data are synced to the cloud-based data management software (CentrePoint). 
The Project Manager will follow-up with the participants within 2-3 business days by phone to 
ensure the participants received the accelerometer and understand how to use it. The Project 
Manager will monitor ActiGraph data collection and will contact to participants if data have not 
been uploaded for more than 2 consecutive days to encourage charging and/or wear. The 
Project Manager will schedule the remaining assessment surveys in REDCap for the 
participants. In the week following the Pretest surveys, participants will complete measures of 
meaning salience and mood on three random days (2 weekdays and 1 weekend day).  
b. Baseline (0 weeks): In the week leading up to baseline, participants will be sent the measures 
of meaning salience and mood on three random days (2 weekdays and 1 weekend day). They 
will be prompted to complete the baseline surveys that assess hypothesized mechanisms 
(basic needs satisfaction and internal motivation). Once the baseline survey measures are 
complete, the web-based platform will prompt participants to complete the MAP to Health 
web-based interview and start the intervention. 
c. Midpoint (4 weeks): In the week leading up to the midpoint assessment, participants will be 
prompted to complete the measures of meaning salience and mood on three random days (2 
weekdays and 1 weekend day). They will be prompted to complete the midpoint surveys that 
assess hypothesized mechanisms (basic needs satisfaction and internal motivation). 

 
 
11 
d. Posttest (8 weeks): In the week leading up to the posttest assessment, participants will be 
prompted to complete the measures of meaning salience and mood on three random days (2 
weekdays and 1 weekend day). They will be prompted to complete the posttest surveys that 
assess hypothesized mechanisms (basic needs satisfaction and internal motivation). 
Participants will provide feedback on intervention and study procedures using the measures 
from Phase 1 (usability and intervention fidelity). 
4. Exit Interview 
After Week 12, the Project Manager will call each participant to conduct an exit interview over the 
phone. The interview will consist of open-ended questions about the participant’s experience with 
the study. After the interview, the Project Manager will confirm that the participant has returned 
the accelerometer to the study or provide instruction on how to complete the return. 
5. Incentives 
Participants can receive up to $250 for their participation. Incentives will be paid out based on the 
activity schedule (see Appendix D: Phase 2 Activities and Incentives Schedule). Incentives 
will be distributed every 4 weeks. The Project Manager will upload the final incentive 
disbursement at the end of the study, prorated based on the return of the accelerometer. 
 
d. MAP to Health Intervention 
i. Intervention Overview 
The Meaningful Activity Program (MAP to Health) intervention is a theory-driven mobile health 
(mHealth) intervention that has the goal of helping adults in midlife increase physical activity. 
Specifically, MAP to Health uses theory (see Figure 3) and mHealth technology to increase meaning 
salience and support basic psychological needs (support autonomy in PA activities, encourage 
setting small goals to increase competence, and encouraging relatedness through promoting PA 
activities with important others), which will, in turn, enhance internal motivation to engage in PA. By 
explicitly addressing 
meaning, the 
intervention will overtly 
integrate PA with key 
life values, and 
therefore increase the 
likelihood that PA will 
become internally 
motivated and 
maintained. The 
intervention will be 
individualized by first having participants complete a web-based, interactive interview, using an MI 
framework, to explore what is particularly meaningful to them and how PA is consistent with those 
goals. After obtaining personalized information about meaning and PA goals, the web-based app will 
generate personalized messages that will be delivered as ecological momentary interventions to 
patients via text. A recent meta-analysis shows that text messages are an effective and flexible 
intervention strategy to increase PA.58 MAP to Health’s web-based interview plus text message 
modality (a) can flexibly deliver ecological momentary interventions to enhance meaning salience, (b) 
is resource-sparing, and (c) can be scaled up to a large audience without requiring interventionists or 
continued software maintenance (like smartphone apps). 
ii. Web-based Interview 
The intervention begins with a web-based interview that guides participants through a structured 
behavior change clinical interview. Participants will log in to a web-based portal with a unique login 
and password. The interactive interview will: (1) provide an overview of the program; (2) gather 
information about past physical activity experience; (3) provide a rationale for connecting physical 
activity to meaning; (4) guide participants through a life values assessment to rank values in order of 
meaningfulness and gather details about the top 3 most meaningful areas; (5) make the explicit 
Physical 
Activity 
MAP to 
Health 
Intervention 
Internal 
Motivation 
Meaning 
Salience 
Figure 3. Conceptual Model Integrating SDT and Meaning to Increase PA. 
Basic Psychological 
Needs Satisfaction 
Base 
SDT 
Model 

 
 
12 
connection between health and meaning; (6) identify how current behavior does not match with 
meaning or physical activity goals; (7) identify opportunity for physical activity; (8) guide participants in 
setting SMART goals for activity (Specific, Measurable, Attainable, Realistic, Timely); (9) elicit barriers 
and spur problem solving; and (10) summarize lessons learned and preview next steps. The initial 
interview will be designed to last 30 to 45 minutes. The information gathered from the interview will be 
used to program the personalized text messages (see next section). 
iii. Text Messages 
For 8 weeks after the initial interview, participants will receive text messages on their personal 
phones. The texts are designed to be delivered at times participants previously noted they will have 
an opportunity to be active (up to twice per day) and will incorporate personalized messages about 
meaning (e.g., For a person who derives meaning from work; “Good morning! Ready to go to the 
gym? Remember that being more active can help you take care of your health and be more efficient 
at work.”). These “just-in-time” messages will pair meaning with PA to (1) increase PA; (2) increase 
meaning salience; and (3) support basic psychological needs satisfaction to, in turn, internalize 
motivation to engage in PA.  
 
iv. Weekly Activity Scheduling 
Each week, participants will be prompted to log in to the web-based platform to update their physical 
activity schedule in the calendar for the coming week. Participants will have the option of carrying 
forward the previous week’s schedule and modifying it as they see fit. Weekly scheduling ensures 
that participants continue to actively plan for physical activity and that text messages are sent at 
appropriate times. 
 
e. Outcome and Variable Definitions 
i. Eligibility Screening 
1. EHR screening data. Data will be collected from the EHR to determine eligibility for a pool of 
potentially eligible individuals. This will include information on demographic characteristics (e.g., 
age, race, ethnicity, sex), most recent height and weight (BMI), diagnoses (e.g., cancer, 
cardiovascular disease, dementia, mental health and substance use disorders), and residential 
information (e.g., residing in a nursing home or long-term care facility). Individuals who are 
recruited through emails or huddle announcements will complete a self-report survey that will 
assess the same information. 
2. Self-reported Physical Activity. In the screening process, potentially eligible individuals will be 
asked to complete Godin’s Leisure Time Exercise Questionnaire (GLTEQ)59 to assess recent 
moderate to vigorous physical activity (MVPA). Individuals are asked to think about a typically 7-
day period (week) and how many times they exercise for more than 15 minutes per time for each 
type of activity (strenuous, moderate, or mild exercise). Individuals then estimate the total number 
of minutes per week they engage in each type of exercise. Individuals who exercise between 10 
and 90 minutes per week of MVPA (mild exercise does not count) will be eligible for this study. 
3. Intentions to be Physically Active. In the screening process, potentially eligible individuals will 
answer one question about intentions to increase physical activity: “Do you intend to increase 
your physical activity in the next 30 days?” Individual who answer “yes” will be eligible for this 
study. 
4. Physical Activity Readiness. The Physical Activity Readiness Questionnaire (PAR-Q)60 will be 
used to assess medical or physical contraindications to participate in physical activity. The PAR-Q 
has 6 questions that assess situations in which it may be unsafe to start a physical activity 
program without the supervision of a physician (e.g., Do you feel pain in your chest when you do 
physical activity?). If individuals answer “yes” to any one of the questions, they will not be eligible 
for the study. 
5. Alcohol Use Disorders Screening. The Alcohol Use Disorders Identification Test – Consumption 
(AUDIT-C)61 is a 3-item screener that assesses whether someone may be engaging in 
problematic alcohol use. Individuals answer the frequency and volume of alcohol that they 

 
 
13 
typically drink on a scale from 0 to 4, with higher scores corresponding to greater frequency or 
volume of consumption. Items are summed for a total score. Individuals who score above the cut-
point (>7) will be ineligible for this study.62 
ii. Measures Used in Both Phase 1 and Phase 2 
1. Demographic questionnaire. Participants will complete self-report measures of demographic 
characteristics, including gender, age, race, ethnicity, marital status, employment status, 
education, and annual income. 
2. Technology Acceptance. Participants will answer 10 questions rating the extent to which they 
found the MAP to Health intervention easy to use (4 items) and useable (4-items) and their 
intentions to use the intervention in the future (2 items). Items were based on previous 
research53,57 and modified for the purposes of this study. Participants will rate each item on a 
scale from 1 (strongly disagree) to 5 (strongly agree). Items will be averaged within each subscale 
(ease of use, useability, and intentions to use). 
3. Intervention Fidelity to Theory. The Intervention Fidelity to Theory (IFT) questionnaire is a 14-item 
questionnaire that assesses the extent to which the MAP to Health intervention adheres to the 
theoretical foundations of supporting autonomy, competence, and relatedness and prompts 
meaning salience.50 Participants rate the extent they agree with each item on a scale from 1 
(strongly disagree) to 5 (strongly agree). Items will be averaged within each subscale for a total 
score. 
4. Intervention Acceptability and Feedback. In both phases, participants will be asked to respond to 
a series of open-ended questions asking about their experiences with the intervention (either the 
interview alone or the interview plus text messages) and the research process.  
iii. Measures Used in Phase 1 Only 
1. Text Message Acceptability. Participants will rate each one of a list of generated text messages 
(up to 14 messages) on whether they are a good fit for them (Yes/No). If participants say “No” to 
any message, they will be prompted to give feedback on how that message could be improved. 
iv. Measures Used in Phase 2 Only 
1. Physical Activity History. Physical activity history will be assessed at pre-test to describe the 
sample. Specifically, participants will be asked to note when they were last physically active, how 
many times they have stopped being active, and what were the reasons for stopping activity. 
2. Meaning Salience. Meaning salience is a primary outcome for Aim 2. The Meaning Awareness 
Scale (MAS) is a 6-item measure that assesses meaning salience.63 Participants rate the extent 
to which they were aware of meaning over the past day (e.g, “I was aware of the meaning in my 
life” on a 7-point Likert type scale ranging from 1 (rarely) to 7 (very often). Items are summed for a 
total score. Participants will complete the MAS on three random days during each of the four 
assessment periods and total scores will be averaged across those three days.  
3. Basic Psychological Needs Satisfaction. Basic needs satisfaction is a primary outcome for Aim 2. 
The Psychological Needs Satisfaction in Exercise Scale (PNSE)64 will be used to measure 
satisfaction of needs of autonomy (e.g., “I feel free to exercise in my own way”), competence 
(e.g., “I feel confident in my ability to perform exercises that personally challenge me”), and 
relatedness (e.g., “I feel attached to my exercise companions because they accept me for who I 
am”) in exercise contexts. The PNSE has 18-items that participants rate on a 6-point Likert-type 
scale ranging from 1 (false) to 6 (true). Items are averaged within and across the subscales for 
total scores. Previous research has demonstrated that the PNES has strong internal consistency 
reliability (αs ≥ .90), construct validity, and convergent validity.64 
4. Internal Motivation. Internal motivation is a primary outcome for Aim 2. Motivation internalization 
will be measured using the Behavioral Regulations in Exercise Questionnaire, version 4 (BREQ-
4).65-67 The 28-item BREQ-4 assesses motivations for exercise on the SDT continuum. There are 
7 subscales with 4 items each: amotivation (e.g., “I don’t see why I should have to exercise.”); 
external regulation (e.g., “I exercise because other people say I should.”); introjected regulation-
avoidance (e.g., “I feel guilty when I don’t exercise.”); introjected regulation – approach (e.g., “I 

 
 
14 
feel proud of myself when I persist.”); identified regulation (e.g., “It’s important to me to exercise 
regularly.”); integrated regulation (e.g., “I exercise because I value the benefits it gives me.”); and 
intrinsic motivation (e.g., “I exercise because it’s fun.”). The subscales will be combined using a 
bifurcation approach68 and scored into two subscales: autonomous and controlled motivation. 
Autonomous regulation will be the average of the intrinsic, integrated, and identified scales 
whereas controlled regulation will be the average of the external and introjected scales. The 
BREQ-2 has been shown to have good psychometric properties, including good internal 
consistency (αs range from .78 - .93).65,67 
5. Mood. Positive and negative mood will be measured using a positive and negative affect scale 
previously used in a study of daily meaning and daily mood.27 Eight items will measure positive 
affect (relaxed, proud, excited, appreciative, enthusiastic, happy, satisfied, and curious) and five 
items will measure negative affect (sluggish, afraid, sad, anxious, and angry). Participants will rate 
their mood using a 5-point Likert-type scale ranging from 1 (very slightly or not at all) to 5 
(extremely). Sums of the positive and negative affect scales have been shown to be positively 
correlated with their respective scales on the Positive and Negative Affect Schedule (PANAS)69 
(r= .55 - .57) and to have very high internal consistency (α = .97 - .98). Participants will complete 
the mood scale on three random days during each of the four assessment periods and total 
scores will be averaged across those three days. Mood will be a covariate for Aim 2. 
6. Psychological Well-Being. Psychological well-being will be assessed as an exploratory outcome. 
Well-being will be measured using two scales: The Subjective Vitality Scale (SVS)70 and The 
Satisfaction with Life Scale (SWLS).71 The 6-item SVS measures feeling active, alive, 
enthusiastic, and energetic (e.g., “I feel alive and vital”). Participants will rate the extent they 
generally feel this way on a 7-point Likert-type scale ranging from 1 (not at all true) to 7 (very 
true). Items will be summed for a total SVS score. Previous psychometric studies have 
demonstrated that the SVS correlates positively with other positive measures of well-being (e.g., 
self-esteem, self-actualization, satisfaction with life) and negatively with poor psychological well-
being (e.g., depression, anxiety, psychopathology), and was internally consistent (α = .84-.86).70 
On the SWLS, participants will rate their agreement with five statements on a 7-point Likert scale 
ranging from 1 (strongly disagree) to 7 (strongly agree). Responses will be summed so that higher 
scores correspond with greater satisfaction with life. Diener and colleagues71 conducted a 
thorough assessment of the SWLS’s reliability and validity. Previous assessments of reliability 
indicated that this measure is internally consistent (α = .87) and had good two-month temporal 
stability (r = .82). Evidence for construct validity indicates that the SWLS correlated positively with 
other measures of subjective well-being and negatively correlated with measures of personality 
psychopathology. Evidence for criterion validity indicates that the measure correlated highly with 
interviewer’s rating of the individual’s satisfaction with life.71  
7. Text Message Acceptability. Participants will rate the extent to which the text messages reflected 
what they found meaningful to them and their plans for physical activity. They will also report on 
the acceptability of the timing and frequency of the text messages at the end of the study. 
Participants will rate the extent to which they agree with each statement on a scale from 1 
(strongly disagree) to 5 (strongly agree). Item responses will be analyzed separately. 
8. Physical Activity. Participants will be given ActiGraph wGT3X-BT accelerometers72 to wear over 
the course of the 12 weeks; data will be automatically uploaded to the cloud (using CentrePoint 
software). Participants will be asked to wear the accelerometer on their non-dominant wrists 
during waking hours. Accelerometers will measure total activity counts and minutes of MVPA over 
a 7-day period at 6-months after the index visit. A valid assessment week will consist of four 
monitored days (at least one weekend day and three weekdays), each with 10 hours minimum 
wear time (determined by the best currently available wear-time algorithms.73 Data will be 
analyzed in 60-second epochs; epochs with at least 2020 activity counts per minute will be 
classified as MVPA and summed per week for each participant. The weekly sum of minutes of 
MVPA will be the primary measure for the exploratory aim. For the purposes of this study, weekly 
summaries of physical activity (MVPA) at each of the four assessment time points will be used for 
the main exploratory analyses. Research staff will monitor wear compliance, reaching out to 
participants after 2 consecutive days of no wear. 

 
 
15 
f. Statistical Analysis Plan  
Aim 1 Analysis. Descriptive statistics will be used to examine the ratings of TAM constructs (perceived 
ease of use, perceived usefulness, and intention to use) and intervention theory fidelity. Average 
ratings will be considered sufficient to move to the second phase if the mean reaches the threshold of 
satisfactory agreement for each construct (i.e., M ≥ 4 on a 5-point Likert-type scale with 4 
corresponding to “Agree”).  
Aim 2 Analysis. The goal of Aim 2 is to determine whether the intervention satisfactorily impacts the 
hypothesized theoretical mechanisms. As an exploratory outcome, we will also assess PA. Participant 
ratings of meaning salience (average of 3 measures across the week), basic psychological needs 
satisfaction, and internal motivation will each be compared across four time points (weeks -4, 0, 4, 8) 
using multilevel linear modeling with time points nested within participants to control for repeated 
measures variance. A fixed time effect will estimate participant ratings at each time point relative to 
baseline, and a series of linear contrasts will test our hypotheses about the pattern of change in ratings 
over time. Without intervention, we do not expect to see change in hypothesized mechanisms so that a 
week -4 vs. week 0 contrast will be close to zero. Following intervention implementation, however, we 
expect participants to report increases in the theoretical mechanisms so that contrasts comparing 
weeks 4 and 8 to baseline will each be positive. Furthermore, we expect to see the greatest change in 
the first 4 weeks post-intervention so that a week 8 vs. week 4 contrast will be close to zero.  
Exploratory Aim Analysis. In exploratory analyses, we will use this same approach as Aim 2 to 
examine changes in PA and whether the hypothesized mechanisms are related to PA over time (i.e., 
pre-intervention, early intervention, and late intervention stages). First, we will examine whether the 
difference in PA slope during the active intervention phase (week 0 to week 8) is significantly greater 
than the change observed during the pre-intervention phase. Additionally, we will examine whether 
changes in hypothesized mechanisms (meaning salience, needs satisfaction, and internal motivation) 
from week 0 to week 4 are associated with changes in PA from week 0 to week 8 using growth curve 
modeling. Although this pilot study will not be powered to determine statistical significance, the effect 
sizes will be calculated to assess the extent to which the intervention is impacting the hypothesized 
mechanisms. 
g. Power analysis 
Aim 2 Power. In this pilot, the aim is not to determine statistical significance but rather to assess 
whether MAP to Health is likely to increase the hypothesized mediators enough to elicit meaningful 
change in PA (Cohen’s d ≥ 0.30). Based on our previous observational study,52 the strength of the 
observed relationships in Figure 1 are expected to be β = .55 (needs satisfaction to internal motivation), 
β = .30 (internal motivation to PA), β = .16 (needs satisfaction to meaning salience), and β = .10 
(meaning salience to PA). Therefore, if half of the total intervention effect (d = .30/2 = .15) is mediated 
through the pathways in Figure 1, then the intervention will need to increase both needs satisfaction 
(estimated β = .50) and meaning salience (estimated β = .60) by d > 0.55. The remaining d ≈ 0.15 of 
the total effect would be represented as a direct effect on PA and could be obtained at least in part via 
unmeasured mediators. If the week -4 vs. week 0 comparison yields a difference of approximately 0, 
the week 4 vs. week 0 comparison is similar in power to a paired t-test. A paired t-test with a sample 
size of N = 35 is powered (0.80, α = 0.05) to detect differences of d ≥ 0.49. As such, the planned 
analyses may be sufficiently powered to detect meaningful within-person changes in the hypothesized 
mediators.   
 
h. Strengths and Limitations 
This study has several strengths, including building off a previously developed prototype intervention 
that used a psychometric approach to intervention development (COMAP), using a systematic 
approach to developing and testing the intervention (using the ORBIT and SOBC models), and building 
off a solid base of observational and interventional research based on SDT and meaning. Further, we 
have a strong interdisciplinary team with the resources to carry out the proposed work.  
The study is designed as a proof-of-concept pilot trial. Participants will serve as their own controls 
instead of being compared to a no-intervention control group and our sample size is small. These 
design choices were made to ensure the intervention was related to changes in the hypothesized 

 
 
16 
mechanisms; however, we will be limited in our abilities to state that the intervention was related to 
changes in physical activity. 
There are two potential biases that we will be sure to address during the project. First, in longitudinal 
studies, there is always data loss due to participants not completing assessments. To reduce data loss, 
we will use multiple reminders to encourage participants to complete follow-up assessments (up to 3 
reminders per assessment). Further, we will provide compensation for participants to complete each of 
the assessments to encourage continued participation. Finally, multilevel modeling allows for use of all 
available data, so participants will not be completely dropped from analysis if they miss any of the 
assessments.  
Second, objectively measured PA using accelerometers has the advantage over self-report PA in 
reducing measurement bias.74 However, it also requires that participants’ wear the devices and can be 
subject to data loss due to hardware malfunction. Participants will be encouraged to wear devices on 
their wrist during daytime hours and data will be uploaded to a cloud-based data management system. 
Research staff will call participants and remind them to wear or charge the device if needed. 
6. Setting/Environment/Organizational feasibility  
This study will be conducted at HealthPartners Institute (HPI). HPI is a particularly appropriate setting 
because we have the research infrastructure and staffing capacity to build the MAP to Health intervention 
(SET team), serve hundreds of thousands of midlife adults who may benefit from this intervention in care 
group and health plans, and have experience designing and evaluating technological innovations. During 
the development of this proposal, we sought the support of the health plan’s Health Promotion department 
(Joel Spoonheim, leader) in the potential of integrating MAP to Health in the Be Well offerings should it be 
funded. We will continue to engage the Health Promotion team to ensure we are developing an intervention 
that will fit with their product offerings. 
7. Risks and Benefits  
a. Potential Risks  
In terms of procedures, measurements, and data collection methods, this is a low risk study. Many 
adults attempt to start physical activity programs on their own every year; this study would not impose a 
specific plan or program for activity but would rather capitalize on participants’ motivation to change and 
encourage free choice of activities. As with any physical activity, there is a slight risk that participants 
could get injured during the study. A second risk is the risk of loss of confidentiality. HealthPartners 
Institute has procedures to ensure that confidentiality will always be protected and that potential risks 
are systematically minimized. 
b. Potential Benefits 
There are no direct benefits to participating in this research study to the participant. As a result of 
participating in the proof-of-concept trial, some participants may increase physical activity, which has 
been shown to have many health benefits. The major benefit of this study is the knowledge gained 
about how the intervention impacts the hypothesized mechanisms of behavior change and physical 
activity. 
c. Protection Against Risks  
To reduce risks of injuries as a result of engaging in physical activity, we will encourage participants to 
engage in activities that are consistent with their current levels of physical fitness and to rest when 
needed. 
To reduce the risk of breach of confidentiality, we will access and employ only the minimally necessary 
EHR data to identify and screen potentially eligible participants and to contact them for recruitment. We 
will maintain the confidentiality of all study data by assigning an arbitrary and unique subject 
identification number to each participant. We will maintain study data on computerized databases on 
username- and password-protected file servers at HPI to which only staff and researchers involved in 
the study will have access. No participant data will be individually identified or released to anyone other 
than the study investigators without specific written permission from the study participant. All 
procedures will be reviewed in advance, approved, and monitored on an ongoing basis by the 
HealthPartners IRB. 

 
 
17 
 
8. Data Confidentiality and Privacy  
The study team has extensive experience in health services research and clinical research with human 
subjects, with procedures to safeguard privacy and personal information. Data will be retained in secure 
storage following the completion of the study in accordance with Minnesota and federal law. We guard 
against the potential for breach of subject confidentiality through a multi-layered system of data protection 
policies, processes, staff training, software safeguards and physical security measures for both paper and 
electronic data involved in research. 
The following measures will be taken to protect subjects from the risk of breach of confidentiality:  
1. All data collected in the study will be identified by using an arbitrary and unique study ID number to 
each patient.  
2. A file containing a link between the study ID and individually identifying information will be maintained 
by a study team programmer.  
3. A crosswalk table linking the study ID to a patient identity will be destroyed within 6 months after the 
linked databases needed to complete study analyses are completed.  
4. All electronic study data will be maintained in a computerized database residing on a username- and 
password-protected fileserver to which only the study team members will have access.  
5. All study-related paper documents containing individually identifiable information will be maintained in 
locked file cabinets. 
To protect the confidentiality of any clinic or organization employee participating in a survey, we will not 
allow anyone outside of the research team to know the identity of those respondents. All of the protection 
to electronic data sources, described above, also apply to survey collection. 
9. Timeline: Key Milestones 
Phase 1: Development 
Oct – Dec 2021:  Intervention Development      
Finalize MAP to Health online assessment 
Develop text messages 
Develop outcome surveys 
Determine process for ActiGraph delivery & set up and monitoring 
Oct 2021 – Jan 2022:  Programming 
Programming for MAP to Health online assessment 
Build REDCap survey for usability testing  
Build CESR Recruitment REDCap  
Develop modality for sending surveys  
Feb – Apr 2022:  Recruitment & Usability testing  
 
Phase 2: Proof-of-Concept Trial 
Feb – Apr 2022:  Intervention Modifications 
Revise text messages 
Revise MAP to Health online assessment 
Revise survey measures 
 
Feb – Jun 2022:  Programming  
Updates and modifications 
 
Jun – Nov 2022:  Intervention Delivery 
Recruitment (rolling) 
Participant Outreach (start up and reminders) 

 
 
18 
Survey Data Collection  
ActiGraph data collection (using CentrePoint cloud-based software) 
 
Analysis & Dissemination                                                          
Dec 2022 – May 2023 
Data preparation & cleaning 
Data analysis 
Manuscript preparation 
 
10. Dissemination/Sharing Results/Integration and Impact  
A. Reporting on ClinicalTrials.gov 
Upon funding, we will register our study protocol with ClinicalTrials.gov in accordance with NIH policy 
no later than 21 calendar days after enrollment of the first participant. We will enter study results no 
later than one year after the trial’s primary completion date. All participant consent forms will include 
specific language indicating that the study information will be registered with ClinicalTrials.gov, 
including the final results. The HealthPartners Institute, as part of internal policy and in compliance with 
federal regulations, registers all of its clinical trials on ClinicalTrials.gov. 
B. Disseminating and implementing the results of this research in other settings 
Regular physical activity is a key behavior for healthy aging and wellbeing. In the Healthy People 2030 
goals, physical activity was named a leading health indicator, and increasing the proportion of adults 
who are engaging in physical activity is a core objective. Despite significant efforts to increase the 
proportion of physically active adults, the high rates of insufficient physical activity have not improved. 
MAP to Health is a resource-sparing, theory-based intervention for encouraging regular physical 
activity. The intervention harnesses a person’s personal sense of meaning in life to increase internal 
motivation to engage in regular physical activity, with the goal of increasing the likelihood that physical 
activity will become a part of that person’s regular routine. The proposed study will further develop and 
provide proof-of-concept testing for the intervention; if successful, we will seek additional funding for a 
Phase III efficacy trial to compare MAP to Health to a physical activity reminder intervention.  
To ensure that the intervention can be easily disseminated within our system, we will work closely with 
the HealthPartners Health Promotion department, who maintains and offers several digital health 
promotion products to HealthPartners insurance members. We will meet with their development team 
prior to, during, and after intervention development to make sure the product we develop could be 
integrated within their health promotion package.  
Because MAP to Health is an entirely digital product, it has the potential to be widely disseminated and 
offered to individuals across the country. There is no staffing requirement beyond regular maintenance 
of the digital tools. We will be open to discussing implementation of the intervention in other health 
systems and health plans as part of their health promotion packages. We posit that taking a systematic 
approach to behavioral intervention development will increase the probability of intervention success 
and will facilitate the likelihood that the final product will be useful to adults attempting to increase their 
physical activity. 
Beyond these considerations, we will also promote dissemination by communicating results of this 
study in many ways, including through publications in peer-reviewed professional journals, 
communications in lay and professional media, and presentations to patients, clinicians, and health 
care leaders. In addition, we are willing to engage in any dissemination activities that may be suggested 
by the funding agency during or after the project period. 
Our preliminary communication strategy for dissemination includes the following components: 
• 
Communicate findings internally to leaders of the HealthPartners medical group and HealthPartners 
insurance plan 
• 
Communicate findings to other health systems that collaborate with HealthPartners on research and 
care improvement initiatives (e.g., Health Care Systems Research Network) 

 
 
19 
• 
Publish study methods and results in peer-reviewed journals 
• 
Present findings at scientific and professional meetings 
The research team will evaluate the success of the dissemination plan iteratively in a long-term 
partnership with NIH, end users, dissemination partners, and stakeholders. 
C. Disseminating study results to study participants after completion of analyses 
Participants who are interested in learning the results of the study will indicate so on their baseline 
study questionnaire. Our team will develop a one-page description of the results of the study in lay 
language, with information about study publications, that will be distributed to participants in their 
preferred mode (e.g., via email or mail). We will work closely with the HealthPartners Communications 
team to include information about study results in HealthPartners publications that are sent to staff, 
physicians, patients, and members.  
 
 

 
 
20 
11. References 
1. 
Piercy KL, Troiano RP, Ballard RM, et al. The physical activity guidelines for Americans. JAMA. 
2018;320(19):2020-2028. 
2. 
Rhodes RE, Janssen I, Bredin SSD, Warburton DER, Bauman A. Physical activity: Health impact, 
prevalence, correlates and interventions. Psychol Health. 2017;32(8):942-975. 
3. 
Warburton DER, Bredin SSD. Reflections on physical activity and health: What should we recommend? 
Canadian Journal of Cardiology. 2016;32:495-504. 
4. 
Tucker JM, Welk GJ, Beyler NK. Physical activity in U.S. adults: Compliance with Physical Activity 
Guidelines for Americans. American Journal of Preventive Medicine. 2011;40(4):454-461. 
5. 
Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United 
States measured by accelerometer. Medicine & Science in Sports & Exercise. 2008;40(1):181-188. 
6. 
Conn VS, Hafdahl AR, Mehr DR. Interventions to increase physical activity among healthy adults: Meta-
analysis of outcomes. American Journal of Public Health. 2011;101(4):751-758. 
7. 
Marcus BH, Dubbert PM, Forsyth LH, et al. Physical activity behavior change: Issues in adoption and 
maintenance. Health Psychology. 2000;19(1). 
8. 
Marcus B, Owen N, Forsyth L, Cavill N, Fridinger F. Physical activity interventions using mass media, 
print media, and information technology. American Journal of Preventive Medicine. 1998;15(4):362-
378. 
9. 
Schmidt JA, Gruman C, King MB, Wolfson LI. Attrition in an exercise intervention: a comparison of early 
and later dropouts. Journal of the American Geriatrics Society. 2000;48(8):952-960. 
10. 
Linke SE, Gallo LC, Norman GJ. Attrition and adherence rates of sustained vs. intermittent exercise 
interventions. Ann Behav Med. 2011;42(2):197-209. 
11. 
Amireault S, Godin G, Vézina-Im L-A. Determinants of physical activity maintenance: a systematic 
review and meta-analyses. Health Psychology Review. 2013;7(1):55-91. 
12. 
Prestwich A, Sniehotta FF, Whittington C, Dombrowski SU, Rogers L, Michie S. Does theory influence 
the effectiveness of health behavior interventions? Meta-analysis. Health Psychol. 2014;33(5):465-474. 
13. 
Czajkowski SM, Powell LH, Adler N, et al. From ideas to efficacy: The ORBIT model for developing 
behavioral treatments for chronic diseases. Health psychology : official journal of the Division of Health 
Psychology, American Psychological Association. 2015;34(10):971-982. 
14. 
Turner JR. New drug development: An introduction to clinical trials. 2nd ed. ed. New York, NY: 
Springer; 2010. 
15. 
Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social 
development, and well-being. Am Psychol. 2000;55(1):68-78. 
16. 
Ingledew DK, Markland D. The role of motives in exercise participation. Psychol Health. 
2008;23(7):807-828. 
17. 
Sebire SJ, Standage M, Vansteenkiste M. Examining intrinsic versus extrinsic exercise goals: cognitive, 
affective, and behavioral outcomes. J Sport Exerc Psychol. 2009;31(2):189-210. 
18. 
Standage M, Sebire SJ, Loney T. Does exercise motivation predict engagement in objectively assessed 
bouts of moderate-intensity exercise? A self-determination theory perspective. J Sport Exerc Psychol. 
2008;30(4):337-352. 
19. 
Wilson PM, Rodgers WM, Fraser SN, Murray TC. Relationships between exercise regulations and 
motivational consequences in university students. Res Q Exerc Sport. 2004;75(1):81-91. 
20. 
Zafeiridou MP, Sarafi VD, Vlachopoulos SP. The mediating role of exercise identity in the relationship 
of exercise motivational regulations with strenuous, moderate and mild exercise. J Sports Med Phys 
Fitness. 2014;54(6):816-827. 
21. 
Rodgers WM, Hall CR, Duncan LR, Pearson E, Milne MI. Becoming a regular exerciser: Examining 
change in behavioural regulations among exercise initiates. Psychol Sport Exerc. 2010;11(5):378-386. 
22. 
Hagger M, Chatzisarantis N. Self-determination theory and the psychology of exercise. Int Rev Sport 
Exerc Psychol. 2008;1(1):79-103. 
23. 
Fortier MS, Hogg W, O'Sullivan TL, et al. The physical activity counselling (PAC) randomized controlled 
trial: rationale, methods, and interventions. Applied physiology, nutrition, and metabolism = Physiologie 
appliquee, nutrition et metabolisme. 2007;32(6):1170-1185. 
24. 
Miller WR, Rollnick S. Motivational Interviewing: Helping People Change. 3rd ed. New York, NY: 
Guilford Press; 2013. 
25. 
Fortier MS, Hogg W, O'Sullivan TL, et al. Impact of integrating a physical activity counsellor into the 
primary health care team: physical activity and health outcomes of the Physical Activity Counselling 

 
 
21 
randomized controlled trial. Applied physiology, nutrition, and metabolism = Physiologie appliquee, 
nutrition et metabolisme. 2011;36(4):503-514. 
26. 
George LS, Park CL. Meaning in life as comprehension, purpose, and mattering: Toward integration 
and new research questions. Review of General Psychology. 2016;20(3):205-220. 
27. 
Steger MF, Kashdan TB, Oishi S. Being good by doing good: Daily eudaimonic activity and well-being. 
Journal of Research in Personality. 2008;42(1):22-42. 
28. 
Jolly K, Duda JL, Daley A, et al. Evaluation of a standard provision versus an autonomy promotive 
exercise referral programme: rationale and study design. BMC Public Health. 2009;9(1):176. 
29. 
Silva MN, Markland D, Minderico CS, et al. A randomized controlled trial to evaluate self-determination 
theory for exercise adherence and weight control: rationale and intervention description. BMC Public 
Health. 2008;8(1):234. 
30. 
Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social 
development, and well-being. American Psychologist. 2000;55(1):68-78. 
31. 
Deci EL, Ryan RM. The "what" and "why of goal pursuits: Human needs and the self-determination of 
behavior. Psychological Inquiry. 2000;11:227-268. 
32. 
Hadden BW, Smith CV. I Gotta Say, Today Was a Good (and Meaningful) Day: Daily Meaning in Life 
as a Potential Basic Psychological Need. Journal of Happiness Studies. 2019;20(1):185-202. 
33. 
Ryff CD, Singer B. The contours of positive human health. Psychol Inq. 1998;9(1):1-28. 
34. 
Hooker SA, Masters KS, Park CL. A meaningful life is a healthy life: A conceptual model linking 
meaning and meaning salience to health. Review of General Psychology. 2018;22(1):11-24. 
35. 
Holahan CK, Holahan CJ, Suzuki R. Purposiveness, physical activity, and perceived health in cardiac 
patients. Disabil Rehabil. 2008;30(23):1772-1778. 
36. 
Holahan CK, Suzuki R. Motivational factors in health promoting behavior in later aging. Activities, 
Adaptation & Aging. 2006;30(1):47-60. 
37. 
Hooker SA, Masters KS. Purpose in life is associated with physical activity measured by accelerometer. 
J Health Psychol. 2014. 
38. 
Ruuskanen J, Ruoppila I. Physical activity and psychological well-being among people aged 65 to 84 
years. Age Ageing. 1995;24(4):292-296. 
39. 
Takkinen S, Suutama T, Ruoppila I. More meaning by exercising? Physical activity as a predictor of a 
sense of meaning in life and of self-rated health and functioning in old age. J Aging Phys Act. 
2001;9(2):128-141. 
40. 
Cohen R, Bavishi C, Rozanski A. Purpose in Life and its Relationship to All-Cause Mortality and 
Cardiovascular Events: A Meta-Analysis. Circulation. 2015;131(Suppl 1):A52-A52. 
41. 
Czekierda K, Banik A, Park CL, Luszczynska A. Meaning in life and physical health: Systematic review 
and meta-analysis. Health Psychology Review. 2017;11(4):387-418. 
42. 
Steptoe A, Fancourt D. Leading a meaningful life at older ages and its relationship with social 
engagement, prosperity, health, biology, and time use. Proc Natl Acad Sci U S A. 2019;116(4):1207-
1212. 
43. 
Adabonyan I, Loustalot F, Kruger J, Carlson SA, Fulton JE. Prevalence of highly active adults--
Behavioral Risk Factor Surveillance System, 2007. Prev Med. 2010;51(2):139-143. 
44. 
Watson KB. Physical inactivity among adults aged 50 years and older—United States, 2014. MMWR 
Morbidity and mortality weekly report. 2016;65. 
45. 
Savela S, Saijonmaa O, Strandberg TE, et al. Physical activity in midlife and telomere length measured 
in old age. Exp Gerontol. 2013;48(1):81-84. 
46. 
Chang M, Jonsson PV, Snaedal J, et al. The effect of midlife physical activity on cognitive function 
among older adults: AGES--Reykjavik Study. J Gerontol A Biol Sci Med Sci. 2010;65(12):1369-1374. 
47. 
Wang C, Yuan Y, Zheng M, et al. Association of Age of Onset of Hypertension With Cardiovascular 
Diseases and Mortality. J Am Coll Cardiol. 2020;75(23):2921-2930. 
48. 
Willis BL, Gao A, Leonard D, Defina LF, Berry JD. Midlife fitness and the development of chronic 
conditions in later life. Archives of internal medicine. 2012;172(17):1333-1340. 
49. 
Steger MF, Oishi S, Kashdan TB. Meaning in life across the life span: Levels and correlates of meaning 
in life from emerging adulthood to older adulthood. The Journal of Positive Psychology. 2009;4(1):43-
52. 
50. 
Masters KS, Ross KM, Hooker SA, Wooldridge JS. A psychometric approach to theory-based behavior 
change intervention development: Example from the Colorado Meaning-Activity Project. Annals of 
Behavioral Medicine. 2018;52(6):463-473. 

 
 
22 
51. 
Hooker SA, Masters KS. Daily meaning salience and physical activity in previously inactive exercise 
initiates. Health Psychology. 2018;37(4):344-354. 
52. 
Hooker SA, Masters KS, Ranby KW. Integrating meaning in life and self-determination theory to predict 
physical activity adoption in previously inactive exercise initiates enrolled in a randomized trial. 
Psychology of Sport and Exercise. 2020;49:101704. 
53. 
Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information 
Technology. MIS Quarterly. 1989;13(3):319. 
54. 
Davis FD, Bagozzi RP, Warshaw PR. User Acceptance of Computer Technology: A Comparison of 
Two Theoretical Models. Management Science. 1989;35(8):982-1003. 
55. 
Schepers J, Wetzels M. A meta-analysis of the technology acceptance model: Investigating subjective 
norm and moderation effects. Information & Management. 2007;44(1):90-103. 
56. 
Devito Dabbs A, Song MK, Hawkins R, et al. An intervention fidelity framework for technology-based 
behavioral interventions. Nurs Res. 2011;60(5):340-347. 
57. 
Venkatesh V, Bala H. Technology acceptance model 3 and a research agenda on interventions. 
Decision Sciences. 2008;39(2):273-315. 
58. 
Smith DM, Duque L, Huffman JC, Healy BC, Celano CM. Text Message Interventions for Physical 
Activity: A Systematic Review and Meta-Analysis. Am J Prev Med. 2019. 
59. 
Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl 
Sport Sci. 1985;10:141-146. 
60. 
Thomas S, Reading J, Shephard RJ. Revision of the Physical Activity Readiness Questionnaire (PAR-
Q). Can J Spt Sci. 1992;17(4):338-345. 
61. 
Bradley KA, DeBenedetti AF, Volk RJ, Williams EC, Frank D, Kivlahan DR. AUDIT-C as a brief screen 
for alcohol misuse in primary care. Alcohol Clin Exp Res. 2007;31(7):1208-1217. 
62. 
Khadjesari Z, White IR, McCambridge J, et al. Validation of the AUDIT-C in adults seeking help with 
their drinking online. Addiction science & clinical practice. 2017;12(1):2-2. 
63. 
Vagnini KM, Hooker SA, Masters KS. The Meaning Awareness Scale (MAS): Assessing Salience of 
Meaning in Life. In:2021. 
64. 
Wilson PM, Rogers WT, Rodgers WM, Wild TC. The Psychological Need Satisfaction in Exercise 
Scale. Journal of Sport & Exercise Psychology. 2006;28:231-251. 
65. 
Markland D, Tobin V. A modification to the behavioural regulation in exercise questionnaire to include 
an assessment of amotivation. Journal of Sport & Exercise Psychology. 2004;26:131-196. 
66. 
Mullan E, Markland D, Ingledew DK. A graded conceptualization of self-determination in the regulation 
of exercise behavior: Development of a measure using confirmatory factor analytic procedures. 
Personality and Individual Differences. 1997;23:745-752. 
67. 
Wilson PM, Rodgers WM, Loitz CC, Scime G. "It's who I am...really!" The importance of integrated 
regulation in exercise contexts. Journal of Applied Biobehavioral Research. 2006;11(2):79-104. 
68. 
Wilson PM, Sabiston CM, Mack DE, Blanchard CM. On the nature and function of scoring protocols 
used in exercise motivation research: An empirical study of the behavioral regulation in exercise 
questionnarie. Psychology of Sport and Exercise. 2012;13:614-622. 
69. 
Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative 
affect: the PANAS scales. Journal of personality and social psychology. 1988;54(6):1063. 
70. 
Ryan RM, Frederick C. On energy, personality, and health: Subjective vitality as a dynamic reflection of 
well-being. Journal of Personality. 1997;65(3):529-565. 
71. 
Diener E, Emmons RA, Larsen RJ, Griffin S. The satisfaction with life scale. Journal of Personality 
Assessment. 1985;49(1):71-75. 
72. 
Clevenger KA, Pfeiffer KA, Montoye AHK. Cross-generational comparability of hip- and wrist-worn 
ActiGraph GT3X+, wGT3X-BT, and GT9X accelerometers during free-living in adults. J Sports Sci. 
2020:1-9. 
73. 
Ahmadi MN, Nathan N, Sutherland R, Wolfenden L, Trost SG. Non-wear or sleep? Evaluation of five 
non-wear detection algorithms for raw accelerometer data. Journal of sports sciences. 2020;38(4):399-
404. 
74. 
Burchartz A, Anedda B, Auerswald T, et al. Assessing physical behavior through accelerometry – State 
of the science, best practices and future directions. Psychology of Sport and Exercise. 2020;49:101703. 
 
 

 
 
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Appendix A: Phase 1 recruitment materials 
MAP to Health Phase 1 recruitment letter v1.0 
MAP to Health Phase 1 recruitment email to HPI employees v1.0 
MAP to Health Phase 1 phone scripts v1.0 
Screening Questionnaire v1.0 
Screening Questionnaire_HPI employees v1.0 
MAP to Health Phase 1 FAQs v1.0 
MAP to Health Phase 1 confirmation and reminder emails v1.0 
MAP to Health Phase 1 e-consent v1.0 
MAP to Health Phase 1 thank you message 
 
Appendix B: Phase 1 Intervention Tools 
Map to Health online assessment v1.0 
Map to Health example messages 
 
Appendix C: Survey Measures 
Phase 1 Measures v1.0 
Phase 2 Measures v1.0 
 
Appendix D: Phase 2 recruitment materials 
Phase 2 Activities and Incentives Schedule v1.0 
 
 
 
 
 

 
 
24 
Consent to Participate in a Research Study  
 
Title of Study: Development and Proof-of-Concept Trial 
 of a Meaning and Theory-Based Physical Activity Intervention  
“MAP to Health” 
 
We are inviting you to take to be part of a research study. We have developed an online program called “MAP to 
Health,” which is designed to help people be more physically active. The program takes place over 12-weeks during 
which you will be asked to track your physical activity, complete online survey measures, participate in the MAP to 
Health program (including the initial assessment, weekly scheduling of activities, and receive text messages) and provide 
feedback on study activities. 
 
Please review the information below and ask any questions before you decide if you want to participate.  
 
Why is this study being done?  
Physical activity has many benefits, including reducing the risks for certain medical conditions, improved mental health 
and well-being, and living longer. However, many adults are unable to regularly meet the recommended activity of 150 
minutes per week. This study aims to support people who want to increase their physical activity by offering an online 
program to enhance motivation, assist with planning, and offer encouraging text message reminders.  
 
What will I be asked to do? 
If you choose to participate in this study, you will be asked to complete the following activities: 
 
• 
Complete online survey measures 4 times (every 4 weeks). These surveys should take between 15-30 minutes. 
During each of these 4 weeks, you will also be asked to do short surveys on your mood 3 times (12 short surveys 
total; < 5 minutes each). 
 
• 
Wear an accelerometer to track your activity for the duration of the study. As part of this, we will have you 
download an app on your phone to sync the accelerometer to the database. You will be asked to regularly 
charge and sync the accelerometer. 
 
• 
After 4 weeks, you will start the MAP to Health program. As part of this program, you will: 
o Complete the MAP to Health online assessment. This assessment takes 20-30 minutes. In this 
assessment, you’ll be asked questions about the types of physical activity you enjoy and the things you 
find meaningful in your life.  
o Schedule physical activities each week (8 weeks total) using the activity scheduler. This should take 
about 5-10 minutes a week. 
o Receive personalized text messages designed to increase your motivation for activity. These messages 
are based on your initial assessment and scheduled at times based on your activity calendar. Text 
messaging rates may apply. 
 

 
 
25 
• 
After finishing the intervention, provide feedback on your study experience in an exit interview. This interview 
will be 15-20 minutes long. 
 
You will be eligible to receive up to $250 for your participation. The total you receive depends on how many study 
activities you complete. 
 
Can being in this study help me? 
Physical activity has many known benefits, including improving energy and mood, reducing risks for chronic diseases, 
and helping people live longer. The aim of this program being tested in this study is to increase physical activity among 
participants. However, these benefits are not guaranteed as part of your participation. This study will help us learn if this 
program could be helpful for future participants.  
 
What are the risks? 
There are minimal risks to participating in this study. There is a risk of injury as individuals participate in exercise. 
However, you will not be asked to participate in any specific exercise activities as part of this research study. You may 
also feel some fatigue from completing the online assessment and study measures. However, you can do them at your 
own pace and take breaks if needed. 
 
How is my information protected? 
Survey responses will be stored on a secure web server with access limited to study staff. The following groups may 
inspect these records: National Institutes of Health, the HealthPartners Institutional Review Board, the United States 
Food and Drug Administration (FDA), or other applicable regulatory authorities.  
 
Any information that can identify you will be removed before analysis. The results of the study may be published. Your 
name or other personal information will never be used. 
 
Do I have to participate? 
Your participation is voluntary. Your decision whether or not to participate will not affect your regular medical care or 
health care benefits in any way. At any point if you decide that you do not want to participate, please call 952-967-5389.  
  
What if I have questions or problems? 
The researcher (“Principal Investigator”) conducting this study is Stephanie Hooker, PhD, MPH. You may ask any 
questions you have by contacting her at 952-967-5056 or emailing Stephanie.A.Hooker@HealthPartners.Com.  
 
If you have questions about your rights as a research participant, you may contact the HealthPartners Institutional 
Review Board (IRB) via phone at 952-967-5025 or by mail at 8170 33rd Avenue South, Mail Stop 21112R, Bloomington, 
MN 55440-1524. Refer to study A20-287.  
 
Statement of Consent: 
 I have read the consent form and I understand:   
 
• 
What I am being asked to do, and  

 
 
26 
• 
The risks and benefits of participating in this research 
 
I understand that clicking the "submit" button indicates:    
 
• 
I have read this consent form,   
• 
I have no outstanding questions, and  
 
• 
I am agreeing to participate.   
 
You may print or retain a copy of this consent for your records. 
▢ 
I consent.  [Skip to End of Survey if not checked] 
 
 
▢ 
(Optional) I would like to receive a copy of the study results when the study is complete.