BACKGROUND:Dietary self-monitoring is central to effective personalized nutrition, providing critical data to inform tailored feedback and support behavior change. OBJECTIVES:To examine the impact of dietary self-monitoring adherence and the indirect effect of personalized scores to predict postprandial glycemic response (PPGR) on weight loss. METHODS:Post hoc analysis of the Personal Diet Study that investigated the impact of a machine algorithm-based diet that integrates clinical and microbiome features (Personalized) compared with a standard, low-fat diet (Standardized) on weight loss. All participants received behavioral counseling and were encouraged to self-monitor dietary intake via a smartphone application. Personalized received algorithm-based scores (1-5) on predicted PPGR to foods logged (PPGR score; 1-2 indicating optimal; 3-5 suboptimal). Dietary self-monitoring adherence was the percentage of days logging ≥50% of target calories, classified as high or low. PPGR score quality was calculated by the proportion of optimal predicted PPGR scores per day; defined as "high-PPGR quality" days when this exceeded the group average. Mediation analysis assessed whether PPGR quality mediated the relationship between dietary self-monitoring adherence and weight loss. RESULTS:Participants with high self-monitoring adherence lost an average of 4.2% of their baseline weight, compared with 1.9% among those with low adherence (P = 0.016). High self-monitoring adherence was associated with a greater likelihood of achieving ≥5% weight loss (adjusted odds ratio: 3.67; 95% confidence interval: 1.63, 8.50). Within Personalized, high-PPGR quality mediated 53.4% of the total effect of self-monitoring adherence on weight loss (P < 0.001). CONCLUSION:Consistent self-monitoring coupled with personalized feedback may significantly enhance weight loss in a precision nutrition approach. This trial was registered at https://clinicaltrials.gov/ as NCT03336411.

PURPOSE:Mobile health cardiac rehabilitation may improve access to care among older adults with ischemic heart disease, but engagement remains poorly understood. We analyzed weekly engagement data from the RESILIENT (Rehabilitation Using Mobile Health for Older Adults with Ischemic Heart Disease in the Home Setting) trial, a large, randomized trial of mobile health cardiac rehabilitation in older adults conducted in the United States. METHODS:Data from 298 intervention participants were analyzed. Weekly engagement was scored from 0 to 11 based on exercise entry (7 points), communication with exercise therapist (2 points), video viewing (1 point), and blood pressure measurement (1 point). Latent class analysis identified digital engagement phenotypes. Participant characteristics were compared, and multivariable logistic regression identified factors associated with phenotype membership. RESULTS:Median age was 71.0 years, 28% were women, 23% were non-White, and 62% were enrolled after elective percutaneous coronary intervention. Latent class analysis identified 3 phenotypes: persistently low (n = 81), intermediate declining (n = 93), and persistently high (n = 124). Participants with persistently low engagement were more likely to be non-White (48% vs 12% vs 15%, P < .001), Medicaid enrolled (22% vs 8% vs 7%, P = .001), have less than high school education (16% vs 4% vs 3%, P < .001), have frailty phenotype (28% vs 10% vs 7%, P < .001), and have a greater mean number of comorbidities (3.1 vs 3.0 vs 2.6; P = .012). After adjustment, non-White race and frailty remained independently associated with low engagement. Improvement in 6-minute walk test distance varied: 20.8 m (low), 29.7 m (intermediate), and 54.5 m (high) (P = .003). CONCLUSIONS:Three distinct digital engagement phenotypes emerged. Persistently low engagement was more common among non-White and frail participants, underscoring ongoing disparities despite efforts to overcome the digital divide.

Objectives This quality improvement project evaluated trends in guideline-concordant statin prescription rates during implementation of an email-based nudge intervention among healthcare providers at a large FQHC network. Methods Eligible encounters included patients meeting UDS guideline criteria but not receiving treatment. On the morning of each eligible visit, providers received an email nudge. Providers were categorized as early adopters or non–early adopters, with early adopters defined as opening >50% of emails during this period. Outcomes included provider-level prescribing rates, and encounter-level prescribing stratified by email engagement. This study was designed, conducted, and reported in accordance with SQUIRE 2.0 guidelines. Results Seventy-five providers who received ≥5 nudges within the first three months were included in the early adopter analysis, and a total of 124 providers with 1,236 unique patient encounters were analyzed over 12 months for encounter-level prescribing rates. Guideline-concordant statin prescribing was modestly higher over time in both groups (early adopters: 85.6% to 89.2%, p < 0.001; non–early adopters: 83.3% to 89.4%, p < 0.001), with no significant evidence of differences between groups over the 1-year period (p = 0.734). At the encounter level, while successful prescribing occurred in 21.8% of visits when the email was opened prior to the encounter compared with 19.5% when it was not opened, this difference was not statistically significant (p = 0.442). Conclusion Guideline-concordant statin prescribing was modestly higher over the study period, though no differential association by email engagement was observed. Given that email nudges are scalable and low-cost, they have the potential to serve as useful adjunctive tools, however further research is needed in settings lacking EHR-integrated alerts or with lower baseline adherence.

Kaplan-Meier analysis of time to first all-cause readmission over 12 months among older adults with ischemic heart disease randomized to 3 months of mobile health cardiac rehabilitation (mHealth-CR) or usual care. There was no significant difference in time to first readmission between groups (log-rank P = 0.26).

ObjectivesTo develop and evaluate the Community Research Consulting Initiative (CRCI), a no-cost, student-led model designed to build bidirectional capacity between academic institutions and community-based organizations (CBOs) through research consulting and project-based assistance.Study designThis formative program evaluation examined the feasibility, acceptability, and preliminary outcomes of CRCI, which includes virtual Office Hours for short-term research consultation and Project-Based Assistance (PBA) for longer-term collaborations. The goal was to support CBOs with technical research needs while providing academic trainees with real-world experience.MethodsAcademic consultants (students, staff, faculty) were recruited through institutional listservs and outreach and completed an intake form outlining their expertise and learning goals. CBOs were engaged through Community Advisory Boards, faculty referrals, and existing networks. Consultants provided support via Zoom-based Office Hours and were matched with CBOs for PBA through a memorandum of understanding. Data collection included Zoom registration logs, post-session surveys, and follow-up communications. Quantitative data were analyzed descriptively, and qualitative feedback was reviewed thematically to inform implementation improvements.ResultsThirty-three consultants expressed interest; 21 participated in Office Hours or PBA projects, representing a range of NYU departments. Consultants sought practical experience applying academic skills in community settings. Fifty-one unique CBOs registered for 90 Office Hours slots, primarily serving racial/ethnic minority and at-risk populations in New York City. Grant writing and data analysis were the most frequently requested topics. Among 20 completed surveys, 95% of CBO respondents found sessions useful and relevant, citing take-home resources as especially beneficial. Six CBOs engaged in PBA projects involving survey design, data analysis, and program evaluation. Consultants appreciated the learning opportunity but highlighted challenges related to attendance, preparation time, and expectation setting.ConclusionCRCI demonstrates a feasible and replicable model for advancing equitable academic–community partnerships aligned with NIH priorities. The initiative supports community capacity building while fostering practical training for future leaders in community-engaged research. Broader implementation of CRCI-like models may enhance the sustainability and impact of academic–community collaborations.

Introduction: Food insecurity affects 1.6 million New Yorkers and increases risk of cardiometabolic diseases. Traditional food assistance introduces barriers such as pantry stigma, lack of culturally centered foods, and raw ingredients requiring time and cooking skills. Food is Medicine (FIM) programs have emerged to address these gaps, yet few center on cultural relevance and community trust. Rethink Food, a non-profit organization in New York City (NYC), developed a FIM model that provides culturally tailored, nutritionally balanced hot meals at no cost. Meals are prepared by local restaurants and distributed through trusted community-based organizations (CBOs). Hypothesis: Implementation science examines how programs are adopted, adapted, and sustained in real-world settings. Assessing how Rethink Food’s model is implemented in Brooklyn, NYC will identify factors that support or hinder replicability and scalability in other urban settings. Methods: This implementation case study applied the Consolidated Framework for Implementation Research (CFIR) to guide qualitative data collection and analysis. We conducted semi-structured interviews with Rethink Food (n=2), partner CBOs (n=3), and restaurants (n=3). Deductive content analysis identified themes across CFIR domains relevant to partnerships, adaptation, and sustainability. Results: Strengths included mission alignment across partners to reduce food waste, provide culturally tailored meals, and support local restaurants. Complementary roles were key: Rethink Food provided funding and infrastructure; CBOs offered trusted spaces; and restaurants contributed culinary expertise and operational capacity. The model’s adaptability enabled tailoring across delivery settings (churches, mobile trucks) and populations. A custom program app streamlined meal scheduling, coordination, and feedback for iterative refinements. Barriers included the logistics of coordinating multiple partners and pressure from funders to reduce costs. Post-COVID declines in philanthropic funding threatened sustainability, though creative financing strategies (restaurant-led fundraising) showed promise. Conclusions: The Rethink Food model illustrates how restaurant-CBO partnerships can operationalize FIM principles by delivering culturally tailored meals to food insecure communities while supporting local food systems. This model offers a scalable, partnership-driven approach to advancing food security and cardiometabolic health through FIM.

BACKGROUND:Remote patient monitoring (RPM) and telehealth improve hypertension management but remain underutilized in resource-constrained settings. The Advancing Long-term Improvements in Hypertension Outcomes through a Team-based Care Approach (ALTA) intervention integrates RPM and virtual health coaching into routine care across a large urban FQHC network and has improved blood pressure outcomes. OBJECTIVE:Explore contextual and mechanistic factors shaping ALTA's implementation outcomes from the perspective of intervention deliverers. DESIGN:Following 1 year of ALTA implementation, we conducted a realist-informed qualitative evaluation to examine factors influencing intervention uptake using semi-structured interviews and focus groups conducted from September to November 2023. PARTICIPANTS:Practice leadership, clinicians, and staff. APPROACH:Participants were recruited through convenience sampling. Transcripts were analyzed using a stepwise deductive and inductive coding approach. Deductive codes were drawn from Proctor's taxonomy of implementation outcomes. Themes were developed using context-mechanism-outcome (C-M-O) configurations. KEY RESULTS:Analysis of 32 semi-structured interviews and four focus groups with a total of 46 intervention deliverers revealed five primary C-M-O-oriented themes: (1) Appropriateness, determined by perceptions of fit, drives acceptability. (2) Demanding workflows raise concerns around ALTA's additional burden, influencing perceptions of appropriateness. (3) Intervention challenges are mitigated by practice facilitation and team-based problem-solving, enhancing acceptability, feasibility, and fidelity. (4) Repeated exposure promotes workflow optimizations, fostering intervention penetration over time. (5) Staff desire insight into ALTA's impact, and communication about intervention progress increases motivation and buy-in. Five of Proctor's implementation outcomes emerged most prominently: appropriateness, acceptability, feasibility, fidelity, and penetration. Notably, these outcomes were interdependent, with one acting as an important contextual factor or mechanistic element for another. CONCLUSIONS:This evaluation highlights important contextual factors, mechanisms, and interconnected outcomes underlying implementation of ALTA. Shared understanding and peer learning, workflow optimization, and communication of outcomes with frontline staff improve reach, equity, and sustainability of RPM-enabled interventions for hypertension management in FQHCs. TRIAL REGISTRATION:ClinicalTrials.gov NCT03713515, date of registration: October 19, 2018, https://classic. CLINICALTRIALS:gov/ct2/show/NCT03713515.

BackgroundMultilevel interventions targeting patients, providers, and health systems improve hypertension outcomes, but little is known about how well they are implemented in resource-limited settings. This study evaluated the implementation fidelity of ALTA, a multilevel approach for hypertension management, supported by practice facilitation, across six primary care practices in a Federally Qualified Health Center (FQHC).MethodsALTA included five components delivered by FQHC staff. At the practice level, staff: (1) identified medication non-adherence in patients with uncontrolled hypertension and (2) referred them to a centralized nurse-led virtual team with a home blood pressure (BP) monitor. The nurse-led team: (3) delivered monthly health coaching based on home BP readings; (4) completed documentation in the electronic health record (EHR); and (5) monitored patients' BP and goals. We used a multi-method approach to assess implementation fidelity (adherence, dose, quality, responsiveness, differentiation) guided by Proctor's Implementation Outcome's Framework. Data sources included a structured EHR-embedded tool, narrative reports, and interviews over 12 months. ALTA adaptations were tracked using the Framework for Reporting Adaptations and Modifications–Expanded.ResultsFrom 2022–2024, 124 staff across 6 FQHC sites implemented ALTA. Implementation adherence varied across sites. The identify component ranged from 49.0% to 57.9% across sites, while the refer component showed greater variability, ranging from 50.0% to 84.4%. Enrollment into health coaching also varied substantially, ranging from 20.8% to 88.5% across sites. The centralized nurse-led team delivered coaching to 91.4% of enrolled patients, completed all documentation, and conducted monitoring for 94.5%. Median implementation dose (patient exposure) was six coaching visits over 5.5 months, and 2.1 BP readings per week. Implementation quality was high, with comprehensive documentation of coaching visits. Six fidelity-consistent adaptations were made to improve feasibility, including simplifying the adherence screener and adding asynchronous training. Interviews (n = 46) highlighted the need for team support, ongoing practice facilitation, and feedback on patients' progress as factors affecting fidelity.ConclusionsImplementation fidelity varied across the ALTA components and participating sites, with the greatest variability observed in delivery of the site-level components of identify and refer. Centralized components delivered by the nurse-led team (coach, document, monitor) were delivered consistently with high fidelity. Contextual factors like staffing and patient engagement shaped implementation success.Clinical Trial RegistrationClinicalTrials.gov, NCT03713515.

BackgroundThe gut microbiome is implicated in obesity and type 2 diabetes (T2D), but how diet, body composition, glycemic status, and self-efficacy factors relate to the microbiome in high-risk individuals is not well characterized. The purpose of this post-hoc analysis is to examine the relationship between the gut microbiome and obesity-related metabolic factors, including body composition, resting energy expenditure (REE), and glycemic variability (GV).MethodsData for this post-hoc cross-sectional analysis were obtained from adults with prediabetes and obesity enrolled in The Personal Diet study, a 6-month behavioral weight loss study. Pre-intervention assessments (n = 95) included the collection of fecal microbiome profile, demographics, socioeconomic status, physical and metabolic characteristics [fat mass, fat free mass (FFM), continuous glucose monitoring–derived GV, REE], self-efficacy and dietary intake. Gut bacterial alpha diversity, beta diversity, and genus level abundances were associated with these host and lifestyle variables using multivariate regression, permutational multivariate analysis of variance, and correlation analyses.ResultsParticipants were a mean age of 58 years old, mostly female (75.8%), with a mean BMI of 34.6 kg/m2 and mean HbA1c of 5.7%. Higher FFM was associated with greater alpha diversity, whereas higher BMI was associated with lower diversity (p < 0.05). Dietary factors were the most consistent correlates of gut microbial beta diversity. At the genus level, associations were observed for sex, metformin use, BMI, protein intake, and REE. The Prevotella/Bacteroides ratio was positively associated with total energy, sugar, and carbohydrate intake (g/day) and negatively associated with monounsaturated fat intake (g/day). Glycemic measures and self-efficacy were not associated with any genera.ConclusionIn adults with prediabetes and obesity, the gut microbiome at baseline was most strongly associated with diet, with additional associations observed for body composition and selected host characteristics. These findings underscore diet as a key correlate of gut microbiome structure in a high-risk metabolic population and support further development of microbiome-informed precision nutrition strategies for obesity prevention and management.

Remote patient monitoring (RPM) has been shown to support adults with treated but uncontrolled hypertension (HTN) outside the clinic setting, yielding significant benefits in the treatment and control of blood pressure (BP). Despite its proven efficacy and recommendation as guideline-concordant care, adoption of RPM is suboptimal, particularly among marginalized populations, who face structural barriers to HTN control. A barrier to equitable adoption among marginalized populations is the lack of digital inclusivity in the design and deployment of RPM. Digitally inclusive tools consider factors such as affordability, access, digital literacy, and skills. To address this challenge, the authors describe a digitally inclusive model of RPM for HTN management within the Family Health Centers (FHCs) at NYU Langone, a federally qualified health center (FQHC) that serves more than 110,000 patients each year. The model uses protocols from the Target: BP initiative in combination with team-based care and digitally inclusive strategies to improve HTN control. Specifically, care teams work collaboratively to identify patients with uncontrolled HTN and order RPM using electronic health record-embedded clinical decision support; provide patients with free home BP monitors and training in accurate BP measurement; deliver language-concordant health coaching and optimize the antihypertensive regimen via a virtual high-risk clinic (VHRC); and monitor patient progress through shared communications. Patients also receive support from community health workers (CHWs) to address digital barriers and unmet social needs. The authors present utilization and preliminary outcome data of their model, involving 429 patients who were enrolled in RPM and the VHRC across five FHC practices between January 1, 2022, and December 31, 2023. Enrolled patients attended a mean of 4.9 (standard deviation [SD]: 0.5) visits with a nurse practitioner for medication adjustments and counseling; 5.7 (SD: 0.5) health coaching visits with a nurse; and 1 visit (SD: 0.2) with a CHW for digital and social needs over a mean of 5.7 months (SD: 0.8). Enrolled patients sent a mean number of 65 BP readings (SD: 96.4) over their period of participation. On average, enrolled patients exhibited a -13.5/-8.0 mmHg reduction from their enrollment date to the date that they were discharged from the VHRC (approximately 5.7 months). This is in comparison to a -0.5/+0.6 mmHg change in mean BP exhibited by patients with uncontrolled HTN not enrolled in the Advancing Long-term Improvements in Hypertension Outcomes through a Team-based Care Approach (ALTA) program and receiving care at the practices during the same period (n=2,843). Across the practices, BP control had also increased from the pre-ALTA baseline period (January 1, 2021, to December 31, 2021) of 68.44%-82.99%, by the end of December 31, 2023, among all patients with uncontrolled HTN. While the implementation of this digitally inclusive RPM model has shown success in a large FQHC that cares for a diverse population of patients, there remain digital inequity barriers that must be addressed at the policy level to ensure this efficacious approach reaches all patients.

INTRODUCTION:The impact of remote patient monitoring for hypertension on cardiovascular health remains ill defined. This study characterized the association between a remote patient monitoring, team-based hypertension intervention and cardiovascular health markers. METHODS:This retrospective, single-arm cohort study included patients with uncontrolled hypertension enrolled from February 2022 to July 2024 in the ALTA trial (clinicaltrials.gov NCT03713515) at 5 safety-net practices. The ALTA intervention involves remote patient monitoring supported by a virtual clinic managed by a nurse practitioner, a registered nurse, and a community health worker. Demographics, ALTA utilization, and cardiovascular health markers (blood pressure, lipids, glycemic indicators, BMI, and smoking history) at baseline and 12 months were collected. The 5 cardiovascular health markers were scored (0=poor, 1=intermediate, 2=ideal) and summed into a cardiovascular health score. The primary endpoint was a change in the 12-month cardiovascular health score among patients with a baseline score of ≤7. Secondary endpoints included changes in individual non-blood pressure markers among patients with baseline derangements. RESULTS:Among the 568 included patients (mean age: 56 years), most were female, non-Hispanic Black, and English-speaking individuals. Nurse practitioner visits were more common among females (p=0.04), with no other demographics predicting ALTA utilization. The cardiovascular health score improved from 4.5 to 5.2 (n=196, p<0.001), independent of ALTA utilization. Total cholesterol (n=86, p<0.001), low-density lipoprotein (n=128, p<0.001), and triglyceride levels (n=51, p=0.004) also improved. Hemoglobin A1c (n=195) dropped among patients with ≥1 nurse practitioner visit (p=0.02). Fasting glucose (n=135) and BMI (n=289) decreased in the highest tertile of nurse practitioner visits (p=0.03) and remote patient monitoring (p=0.02), respectively. Finally, 4 of 27 patients quit smoking. CONCLUSIONS:Remote patient monitoring with team-based support was associated with cardiovascular health improvements. However, benefits may depend on the intervention's utilization.

Purpose:Hypertension (HTN) is common and represents a major modifiable risk factor for ischemic heart disease in older adults. While home blood pressure monitoring (HBPM) is important in HTN management, patterns of HBPM engagement in older adults undergoing mobile health cardiac rehabilitation (mHealth-CR) are unknown. We aimed to identify patterns of adherence to HBPM in a cohort of older adults undergoing mHealth-CR to optimize HBPM use in the future.Methods:We used interim data from the ongoing Rehabilitation using Mobile Health for Older Adults with Ischemic Heart Disease in the Home Setting (RESILIENT) randomized trial, in which intervention arm participants (adults >= 65 years with ischemic heart disease) were instructed to monitor blood pressure (BP) at least weekly. Engagement groups were determined by latent class analysis and compared using ANOVA or Chi-Square tests. Longitudinal mixed effect modeling determined the associations between weekly HBPM and baseline covariates including uncontrolled HTN, obesity, diabetes, depression, alcohol, and tobacco use.Results:Of the 111 participants, the mean age was 71.9 +/- 5.6 years, and 83% had HTN. Over the 12-week study, mean HBPM engagement was 2.3 +/- 2.3 d/wk. We observed 3 distinct patterns of engagement: high engagement (22%), gradual decline (10%), and sustained baseline engagement (68%). HBPM adherence decreased in two of the engagement groups over time. Of the covariates tested, only depression was associated with weekly HBPM after adjusting for relevant covariates (OR 9.09, P = .03).Conclusions:In this older adult cohort undergoing mHealth-CR, we found three main engagement groups with declining engagement over time in two of the three groups. These patterns can inform future mHealth-CR interventions.

Social determinants of health (SDoH), health care use, and cardiovascular disease (CVD) risk perception are understudied among men who identify as Black and Hispanic. In this study we sought to describe these factors among a cohort of urban-residing Black men, participants in a community-engaged trial on hypertension prevention. We focused on presenting intermediary SDoH, including material circumstances, health behaviors, and psychosocial factors, which allow for a more robust understanding of health inequities but are underexplored. We analyzed baseline trial data (N=430) and compared subgroups (44% of participants self-identified as having Hispanic ethnicity and a Black racial identity). Average age was 38 years, with mean blood pressure of 129/83 mmHg. Hispanic Black (HB) men reported higher unemployment (21.4% versus 11.1%, P=.02) and more housing instability (28.7% versus 18.6%, P=.01) than did non-Hispanic Black (NHB) men. Overall, HB men reported worse household conditions compared with NHB men. Approximately half of both groups reported high stress, 45% (HB) and 51% (NHB), respectively. Both groups had low perception of personal CVD risk and underutilized health care. Hispanic Black men were less likely to have a primary care provider than were NHB men (17.6% versus 29.3%, P<.001). Non-Hispanic Black men reported lower physical activity than did HB men (median, 2655 vs 2547 metabolic equivalent minutes/week, P=.03). Recognizing heterogeneity among Black populations, including in social drivers of CVD disparities, will allow for more precision in designing CVD health promotion interventions. Findings also suggest that perception of personal CVD risk and health care utilization may be important targets for CVD prevention in Black men.

ImportanceAmong older adults with ischemic heart disease, participation in traditional ambulatory cardiac rehabilitation (CR) remains low. While mobile health CR (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments to technology use may limit uptake, and efficacy data are currently lacking.ObjectiveTo test whether mHealth-CR improves functional capacity in older adults.Design, Setting, and ParticipantsThe RESILIENT phase 2, multicenter, randomized clinical trial recruited patients aged 65 years or older with ischemic heart disease (defined as a hospital visit for myocardial infarction or coronary revascularization) from 5 academic hospitals in New York, Connecticut, and Massachusetts between January 9, 2020, and April 22, 2024.InterventionParticipants were randomized 3:1 to mHealth-CR or usual care. mHealth-CR consisted of commercially available software delivered on a tablet computer, coupled with remote monitoring and weekly exercise therapist telephone calls, delivered over a 3-month duration. As RESILIENT was a trial conducted in a routine care setting to inform decision-making, participants in both arms were also allowed to receive traditional CR at their cardiologist’s discretion.Main Outcomes and MeasuresThe primary outcome was change from baseline to 3 months in functional capacity, measured by 6-minute walk distance (6MWD). Secondary outcomes were health status (12-Item Short Form Health Survey [SF-12]), residual angina, and impairment in activities of daily living.ResultsA total of 400 participants (median age, 71.0 years [range, 65.0-91.0 years]; 291 [72.8%] male) were randomized to mHealth-CR (n = 298) or usual care (n = 102) and included in the intention-to-treat analysis. Of those, 356 participants (89.0%) returned in person for 6MWD assessment at 3 months. For the primary outcome, there was no adjusted difference in 6MWD between participants receiving mHealth-CR vs usual care (15.6 m; 95% CI, −0.3 to 31.5 m; P = .06). Among subgroups, there was an improvement in 6MWD among women (36.6 m; 95% CI, 8.7-64.4 m). There were no differences in any secondary outcomes between groups (eg, adjusted difference in SF-12 physical component scores at 3 months: −1.9 points; 95% CI, −3.9 to 0.2 points). Based on inverse propensity score weighting, there was no effect of mHealth-CR on 6MWD among those who did not attend traditional CR (25.7 m; 95% CI, −8.7 to 60.2 m).Conclusions and RelevanceIn this randomized clinical trial of mHealth-CR vs usual care, mHealth-CR did not significantly increase 6MWD or result in improvements in secondary outcomes. The findings suggest the older adult population may require more age-tailored mHealth strategies to effectively improve outcomes.Trial RegistrationClinicalTrials.gov Identifier: NCT03978130

Importance:Among older adults with ischemic heart disease, participation in traditional ambulatory cardiac rehabilitation (CR) remains low. While mobile health CR (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments to technology use may limit uptake, and efficacy data are currently lacking. Objective:To test whether mHealth-CR improves functional capacity in older adults. Design, Setting, and Participants:The RESILIENT phase 2, multicenter, randomized clinical trial recruited patients aged 65 years or older with ischemic heart disease (defined as a hospital visit for myocardial infarction or coronary revascularization) from 5 academic hospitals in New York, Connecticut, and Massachusetts between January 9, 2020, and April 22, 2024. Intervention:Participants were randomized 3:1 to mHealth-CR or usual care. mHealth-CR consisted of commercially available software delivered on a tablet computer, coupled with remote monitoring and weekly exercise therapist telephone calls, delivered over a 3-month duration. As RESILIENT was a trial conducted in a routine care setting to inform decision-making, participants in both arms were also allowed to receive traditional CR at their cardiologist's discretion. Main Outcomes and Measures:The primary outcome was change from baseline to 3 months in functional capacity, measured by 6-minute walk distance (6MWD). Secondary outcomes were health status (12-Item Short Form Health Survey [SF-12]), residual angina, and impairment in activities of daily living. Results:A total of 400 participants (median age, 71.0 years [range, 65.0-91.0 years]; 291 [72.8%] male) were randomized to mHealth-CR (n = 298) or usual care (n = 102) and included in the intention-to-treat analysis. Of those, 356 participants (89.0%) returned in person for 6MWD assessment at 3 months. For the primary outcome, there was no adjusted difference in 6MWD between participants receiving mHealth-CR vs usual care (15.6 m; 95% CI, -0.3 to 31.5 m; P = .06). Among subgroups, there was an improvement in 6MWD among women (36.6 m; 95% CI, 8.7-64.4 m). There were no differences in any secondary outcomes between groups (eg, adjusted difference in SF-12 physical component scores at 3 months: -1.9 points; 95% CI, -3.9 to 0.2 points). Based on inverse propensity score weighting, there was no effect of mHealth-CR on 6MWD among those who did not attend traditional CR (25.7 m; 95% CI, -8.7 to 60.2 m). Conclusions and Relevance:In this randomized clinical trial of mHealth-CR vs usual care, mHealth-CR did not significantly increase 6MWD or result in improvements in secondary outcomes. The findings suggest the older adult population may require more age-tailored mHealth strategies to effectively improve outcomes. Trial Registration:ClinicalTrials.gov Identifier: NCT03978130.