To obtain our target sample (N=89), we leverage resources available to Emory investigators, including Georgia Clinical and Translational Science Institute, Research Match (registry of research volunteers), electronic mailings, announcements on social media sites, and fliers posted in the community. We are also recruiting from primary care practices affiliated with Emory Health care, with an aim to recruit a diverse sample that includes ≥25% men and ≥30% racial and ethnic minorities.

Individuals who respond to recruitment solicitations are directed to a web link that provides a brief overview of the study and eligibility criteria. Those who are eligible are guided to follow a link to complete 9 brief questionnaires which are outlined with their validation references in Table 1. For participant convenience, the questionnaires are administered via the REDCap (Research Electronic Data Capture; Vanderbilt University) platform so that they can be completed online in one or multiple sittings within 30 minutes. Data from the questionnaires are used for eligibility screening and will eventually allow us to examine the impact of sleep disturbance, health status, stress, and risk of depression on study outcomes. The eligibility criteria are embedded within the online surveys so that the data collection is terminated when a potential participant enters information that makes them ineligible (eg, history of stroke). Those who complete the REDCap questionnaires and remain eligible for the study are scheduled for a 20-minute phone interview, during which the Mediterranean Eating Pattern for Americans [22] screener and the PA questionnaire [20] are administered by an interviewer. Those who do not meet current PA guidelines (<150 min of MVPA per week) are scheduled for a 15-minute phone call to set up the technology that they will be using in the study.

Before the technology set-up phone call, we provide potential participants with email instructions on how to install Zoom (Zoom Video Communications; for assessments and coaching), Withings (weight, BP), and Fitbit (PA) apps. During the phone call, the study staff members verified the software installation and provided login credentials for the apps. Next, study staff members review the study procedures and those still interested in the study receive a copy of the informed consent to review and sign via REDCap. Those who consent are asked to complete the All of Us Research Program Lifestyle Survey as well as questionnaires assessing exercise self-efficacy [29], self-regulation [30], PA enjoyment [31], social support [32], and outcome expectancy [33] (Table 1). These validated questionnaires are frequently used to identify facilitators and barriers [29-33] that are known to influence PA and cardiovascular outcomes [38-41]. These questionnaires can be completed in REDCap within approximately 30 minutes and will be repeated at the 6-month follow-up visit. An optional Adverse Childhood Experiences questionnaire will be used to explore difficult childhood experiences that may impact variables of interest in the study. The participants will be asked by the study staff members to give their verbal consent to receive this questionnaire at the end of the study assessment.

Participants who meet all eligibility criteria during screening are scheduled for a baseline assessment via Zoom. Before the assessment, each participant will receive a package with all supplies including a Dry Blood Spot Kit, Fitbit Charge 5, ActiGraph GT3X, Withings Arm BP Monitor, Withings Scale, Perfect Waist Tape Measure, and Stretch Band. During the Zoom visit, the study staff members review the data in the PA readiness questionnaire (PAR-Q+) [21], to ensure that individuals who need primary care practitioner clearance obtain it before they are randomized to the intervention or attention control condition. We use the HIPAA (Health Insurance Portability and Accountability Act)-compliant online Fax (SRFax, Ziff Davis Inc) to send and receive faxes on behalf of participants.

The assessments commence with the study staff members reviewing the waist circumference self-measurement video and guidelines developed by the International Chair on Cardiometabolic Risk [42]. The staff members instruct the participants to go to a private location where they can measure their waist on bare skin using the Perfect Tape Measure. The participant shows the locked tape measure to staff members via the camera. There is evidence for strong correlation coefficients (0.8 to 0.9) between self and technician-measured waist circumference using this method [43-47]. Next, the staff members instruct the participant to wear light clothing and stand on the smart scale footpads with their bare feet to measure weight, percentage body fat, percentage body water, muscle, and BMI. The study team obtains these device-recorded measures via the Withings application programming interface (API) with the PATH platform.

We use the clinically validated Withings Arm BP Monitor for self-measurement of BP [48]. The smart monitor has a one-touch easy-to-read digital screen and a cuff that fits an arm circumference of 22-42 cm (larger cuffs available on request). Staff members will instruct the participant to apply the cuff on the bare left arm, then sit in a chair with both feet resting flat on the floor, with the back straight and supported. After 5 minutes of rest with the left arm resting on a flat surface at heart level, participants will be asked to turn on the BP machine and take 3 measurements at 1-minute intervals. The study team will immediately access the device-recorded BP via Withings API with the PATH platform. Participants with elevated BP (>130/80 mm Hg) will be referred to their primary care practitioner, with a request to update the study team if treatment is initiated. Those with severe hypertension (BP ≥180/110 mm Hg) will be asked to seek urgent medical attention before re-evaluation of their eligibility.

Blood samples for measurement of adipokines (tumor necrosis factor alpha [TNF-α], monocyte chemoattractant protein 1 [MCP-1], interleukin [IL]-1 beta [IL-1β], and IL-6, leptin, and adiponectin) and lipids (low-density lipoprotein [LDL], high-density lipoprotein [HDL], and total cholesterol) are collected via volumetric absorptive microsampling approach using Mitra dry blood spot kits [49]. Study staff members supervise participants collecting the fingerstick sample following the steps outlined in the sample collection tutorial [50]. The samples are mailed by each participant to the laboratory using the included return address. Once at the laboratory, the samples are stored at –80^o C and will be processed at the end of the study using established protocols for analysis [51].

At the end of the baseline assessment, the staff members will instruct participants to wear the ActiGraph GT3X on their waist and Fitbit on their wrist to monitor PA for a 7-day run-in period. The run-in period will help potential participants appreciate study expectations and will provide objective data on baseline MVPA. Individuals will need to wear the Fitbit and ActiGraph GT3X for ≥10 hours on ≥4 days to be eligible in the study [52].

After the successful completion of the run-in period, nonblinded staff members randomize eligible participants with equal allocation (1:1) to either the PATH intervention or the attention control arm using the REDCap randomization software. Group assignments are generated via a REDCap stratified randomization scheme to achieve a balance between the treatment and control groups regarding age (18-45, 46-64, and ≥65 years), sex (male or female), and race (White or racial and ethnic minorities). The Randomization scheme was developed by the study statistician. After randomization, a study staff member meets with each participant on Zoom to orient them to their randomized group resources. If blinded staff members inadvertently become unblinded, the incident will be noted in the study’s log, and they will not conduct end-of-study assessments on the participant. Participants in both groups are instructed to wear Fitbit on their nondominant hand during the study using a 24-hour wear protocol.

After randomization, study staff members schedule a Zoom meeting with each control group participant where they are guided to use their tracker and Be Active Your Way Guide [19]. They also schedule a check-in meeting with them every 2 weeks, with the intention to keep the contact between the groups as similar as possible.

During the twice per month meetings with intervention and control groups, the participants receive early morning reminders to empty their bladder and step on the scale before meeting with the study staff members who supervise BP measurements on Zoom. These data are used to monitor trends in BP, weight, and body composition during the study period. Both the intervention and control arms receive an email with a brief PDF addressing 1 diet component every 4 weeks. The diet information is also available to them as modules on the PATH platform (control group access on PATH is limited to the nutritional resources). At the end of the 6-month study assessments, both control and intervention group participants are given the option to continue using the PATH platform at their convenience without any interaction with the coaches.

Effectiveness of the PATH Fresher algorithm will be indicated by its ability to analyze PATH users’ data, spin up new browser sessions in the background to activate the YouTube recommender system, and select new workouts like those highly rated (≥3.5/5 stars) by study users. At the end of the study, the coaches will vet the new workouts recommended by the PATH fresher algorithm. The acceptance of ≥50% of the top twenty recommended workouts for inclusion in PATH will indicate the effectiveness of the PATH fresher algorithm. The systems usability survey [37] will be completed by participants to survey satisfaction with the PATH platform.

The resources will be curated from an extensive library of standard behavioral treatment content previously developed and validated by the SMARTER study team [57,58]. Their acceptability will be indicated by 70% of the participants rating the materials as helpful via a researcher-developed end-of-study survey (Multimedia Appendix 1).

The efficacy of PATH in enhancing adherence to PA guidelines will be evaluated at 6 months using MVPA data collected using the Actigraph GT3X device [59] worn on the waist for 7 days at 6 months. Adherence to PA guidelines will be defined as achieving ≥150 minutes of MVPA per week. Percent change in adherence will be calculated as follows: ([postintervention MVPA–baseline MVPA]/recommended MVPA×100). Between-group differences in % change in adherence and the proportion of individuals who attain the recommended MVPA will be evaluated. Established and novel methods will be used to process ActiGraph data which will be considered valid if ≥4 days with ≥10 hours of wear time are measured [59]. ActiGraph GT3X nonwear time was defined using the Choi wear time validation algorithm [60]. Fitbit valid data were indicated by ≥4 days with ≥500 steps per day as recommended by Thorndike et al [61] and Bizhanova et al [62]. Sustained PA engagement will be evaluated via Active Zone Minutes data collected via Fitbit Charge 5 and will be analyzed via the adherence strategy described above. Validation studies suggest that Fitbit is ideally suited for long-term self-monitoring of PA due to its user-friendliness and extensive use in RCTs [63].

Cardiovascular outcomes will be indicated by change from baseline to end of 6-month study post intervention in CVD risk score calculated using the 2013 Atherosclerotic Cardiovascular Disease Risk Calculator [35]. The algorithm provides sex- and race-specific estimates for the first CVD events. The scores range from 0% to 100% with higher scores representing poor cardiovascular health status. The composite risk factors included in the algorithm are age, total and HDL cholesterol, systolic blood pressure (including treated or untreated status), diabetes, and current smoking status. These will be measured using the protocols outlined under baseline assessment. The main outcome will be between-group differences in risk score change from baseline. We will use the same strategy to evaluate changes in independent risk factors for CVD (secondary outcomes): waist circumference, weight, BP, Life’s Essential 8, hemoglobin A_1c (HbA_1c), adiponectin, and lipids (total, low-density lipoprotein, and HDL cholesterol).

Given our repeated measures study design, we anticipate some participant attrition. To ensure sufficient sample size with complete assessment through 6-months follow-up, we plan to enroll 88 participants (44 per treatment group) retaining at least 76 participants (38 per treatment group) assuming a 14% attrition through the 6-month follow-up based on attrition rates observed in the literature [64]. When estimating within-group changes to describe the effect of PATH on study outcomes using either proportions or means, with at least 38 participants per treatment group (76 total), we would have at least 80% power to detect small-to-medium effect sizes for the efficacy of the PATH intervention. For PA, this corresponds to a mean difference of 20 minutes of MVPA or 13.3% absolute change in terms of adherence to PA guidelines. For CVD risk factors, linear contrasts from either linear or generalized linear mixed modeling will be specified and estimated to compare the treatment groups on the 6-month change in CVD risk scores and risk factors at test wise (Bonferroni-adjusted) significance level of .05.

Data will be analyzed using SAS (version 9.4; SAS Institute) to conduct exploratory data analyses for data screening, including missing data assessment, as well as repeated measures modeling, and modeling of attrition. Mplus (version 8.8; Muthén and Muthén) will be used for mediational analyses to explore possible mechanisms of action of the PATH intervention. Data will first be carefully screened with the results of these preliminary analyses informing the final analysis strategies to be applied to address study aims and exploratory analyses. Although hypotheses are stated as directional, hypothesis testing will be nondirectional with the significance level set to .05 and CI estimation at 95%. The randomness of missing data will be investigated using information on participant characteristics to help discern patterns in the missing data, identify possible missing data mechanisms, and inform strategies to handle missing data. If data are not missing at random, we will apply multiple imputations and 2 extreme case scenarios (worst or best case) to address missing data. If nonrandom missingness is suspected, we will use selection or pattern mixture modeling to explore the sensitivity of results to the assumed missing data patterns.

An intent-to-treat (ITT) approach will be used to test the efficacy of the PATH intervention on the distal outcome of adherence to the PA guidelines over time. Since key study end points are assessed at multiple time points, repeated measures modeling (eg, linear or generalized linear mixed modeling methods and or marginal modeling using generalized estimating equations as appropriate, both assuming a normal error structure) will be used to test the efficacy of the PATH intervention on the measures of adherence to the PA guidelines over time (baseline [0 months], and 6 months [long-term] follow-up). To test the hypothesis that the PATH intervention group will have greater adherence to PA guidelines compared with the attention control group, linear contrasts will be specified and estimated to compare adherence to PA guidelines between the treatment groups at 6 months relative to baseline values, respectively. The test wise significance level will be set to .05 (Bonferroni-adjusted). Point and interval (95% CIs) estimates based on linear contrasts will also be computed as both unstandardized and standardized effect sizes of the efficacy of the PATH intervention.

A similar repeated measures modeling approach as outlined above will be used to evaluate the efficacy of the PATH intervention compared with the attention control condition on CVD risk factors including CVD risk score, weight, BP, waist circumference, HbA_1c, and lipids at 6-month follow-up. These measures of CVD risk are either interval or ratio scaled, and a normal error structure (or following a suitable data transformation) will be assumed when modeling. As necessary, generalized linear mixed modeling assuming a binomial error will be applied to model CVD risk factors dichotomized based on clinically meaningful cut points. To test the hypothesis that the PATH intervention group will have a greater reduction in CVD risk score versus the control group, linear contrasts will be specified and estimated to compare the treatment groups on the change in CVD risk scores at 6-months follow-up relative to baseline values at a test wise significance level of .05 and CI estimation at 95%.

All technologies to be used in this study, including the AWS web hosting platform, PATH website, Twilio, SR Fax, ActiGraph GT3X, Fitbit, and Withings apps were reviewed and approved by Emory University’s Enterprise Information Security Team. The entire data collection infrastructure, including the REDCap and PATH platforms, were tested by the study team before it was deployed for data collection. Data will be stored on a password-protected computer with access limited to the staff members who monitor participants’ adherence and safety, and the data management team. Access to the master list of participant names and ID numbers will be limited to the staff members who conduct the screening and intervention procedures as they need to interact with these individuals on a name basis. The staff members who do not interact with participants are blinded to name and treatment assignment. The primary outcomes will be shared in scientific conferences and peer-reviewed publications. Investigators seeking to use the deidentified data will sign a data user agreement with Emory University.

A data safety and monitoring plan will be implemented to ensure the safety of all participants involved in the study and to ensure the validity and integrity of the collected data. The PI and biostatistician (in conjunction with the project coordinators and staff members), will be responsible for the execution of this plan under the oversight of a safety officer and the institutional review board (IRB). The safety officer will act in an advisory capacity to the PI and the National Institutes of Health program director. All adverse events will be documented in REDCap and reported in publications. Major adverse events will be reported to IRB following established protocols. To posttrial care or compensation for harm will be provided. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) checklist is provided in Multimedia Appendix 2.