Multilevel mobile health approach to improve cardiovascular health in resource-limited communities with Step It Up: a randomised controlled trial protocol targeting physical activity

Design, rationale, and characterization of the mobile health based occupational cardiovascular risk intervention study (mHealth-OPEN study)

BACKGROUND

The substantial workforce and suboptimal cardiovascular health highlights the urgent need for workplace interventions. This ongoing cluster-randomized trial aims to evaluate the effectiveness, feasibility, and acceptability of a mobile health (mHealth) based comprehensive intervention program to improve cardiovascular health among employees.

METHODS AND RESULTS

We conducted a 1-year, 2-arm, parallel-group, cluster-randomized controlled multicenter trial involving 10,000 participants (aged 18-65, including 1,600 participants with high cardiovascular risk) across 20 workplaces. Workplaces were randomly assigned in a 1:1 ratio to either the intervention or control group. We established a mHealth based multifaceted cardiovascular risk management system that enables intelligent management. The intervention groups received a mHealth-based management with primary prevention inventions for all participants and additional cardiovascular risk interventions for participants with high cardiovascular risk via the system. The control groups received usual care. Primary outcomes included percentage changes in hypertension, diabetes, and dyslipidemia control rates among participants with high cardiovascular risk, and percentage changes in the rate of regular physical activity among all the participants, from baseline to 12-month follow-up. Secondary outcomes included changes in blood pressure, glucose, lipid, treatment adherence, behavioral factors, questionnaire scores, and incidence of major cardiovascular events. By now, baseline recruitment has been completed, with comparable characteristics between management and control groups.

CONCLUSIONS

This rigorous designed mHealth-based workplace intervention demonstrates potential for nationwide implementation, offering cardiovascular benefits for employees.

CLINICAL TRIAL REGISTRATION

www.chictr.org.cn. Identifier: ChiCTR2200066196.

The use of sequential multiple assignment randomized trials (SMARTs) in physical activity interventions: a systematic review

BACKGROUND

Physical activity (PA) is often the cornerstone in risk-reduction interventions for the prevention and treatment of many chronic health conditions. PA interventions are inherently multi-dimensional and complex in nature. Thus, study designs used in the evaluation of PA interventions must be adaptive to intervention components and individual capacities. A Sequential Multiple Assignment Randomised Trial (SMART) is a factorial design in a sequential setting used to build effective adaptive interventions. SMARTs represent a relatively new design for PA intervention research. This systematic review aims to examine the state-of-the-art of SMARTs used to develop PA interventions, with a focus on study characteristics, design, and analyses.

METHODS

PubMed, Embase, PsychINFO, CENTRAL, and CinAHL were systematically searched through May 2023 for studies wherein PA SMARTs were conducted. Methodological quality was assessed using the Cochrane Risk of Bias 2 Tool.

RESULTS

Twenty studies across a variety of populations - e.g., obesity, chronic pain, and cardiovascular conditions, were included. All PA SMARTs involved two decision stages, with the majority including two initial treatment options. PA interventions most commonly consisted of individual aerobic exercise with strategies such as goal setting, wearable technology, and motivational interviewing also used to promote PA. Variation was observed across tailoring variables and timing of tailoring variables. Non-response strategies primarily involved augmenting and switching treatment options, and for responders to continue with initial treatment options. For analyses, most sample size estimations and outcome analyses accounted for the SMART aims specified. Techniques such as linear mixed models, weighted regressions, and Q-learning regression were frequently used. Risk of bias was high across the majority of included studies.

CONCLUSIONS

Individual-based aerobic exercise interventions supported by behaviour change techniques and wearable sensing technology may play a key role in the future development of SMARTs addressing PA intervention development. Clearer rationale for the selection of tailoring variables, timing of tailoring variables, and included measures is essential to advance PA SMART designs. Collaborative efforts from researchers, clinicians, and patients are needed in order to bridge the gap between adaptive research designs and personalised treatment pathways observed in clinical practice.

Missing Data Statistics Provide Causal Insights into Data Loss in Diabetes Health Monitoring by Wearable Sensors

BACKGROUND

Data loss in wearable sensors is an inevitable problem that leads to misrepresentation during diabetes health monitoring. We systematically investigated missing wearable sensors data to get causal insight into the mechanisms leading to missing data.

METHODS

Two-week-long data from a continuous glucose monitor and a Fitbit activity tracker recording heart rate (HR) and step count in free-living patients with type 2 diabetes mellitus were used. The gap size distribution was fitted with a Planck distribution to test for missing not at random (MNAR) and a difference between distributions was tested with a Chi-squared test. Significant missing data dispersion over time was tested with the Kruskal-Wallis test and Dunn post hoc analysis.

RESULTS

Data from 77 subjects resulted in 73 cleaned glucose, 70 HR and 68 step count recordings. The glucose gap sizes followed a Planck distribution. HR and step count gap frequency differed significantly (p < 0.001), and the missing data were therefore MNAR. In glucose, more missing data were found in the night (23:00-01:00), and in step count, more at measurement days 6 and 7 (p < 0.001). In both cases, missing data were caused by insufficient frequency of data synchronization.

CONCLUSIONS

Our novel approach of investigating missing data statistics revealed the mechanisms for missing data in Fitbit and CGM data.

Effectiveness of a socioecological model-guided, smart device-based, self-management-oriented lifestyle intervention in community residents: protocol for a cluster-randomized controlled trial

BACKGROUND

Healthy lifestyles are crucial for preventing chronic diseases. Nonetheless, approximately 90% of Chinese community residents regularly engage in at least one unhealthy lifestyle. Mobile smart devices-based health interventions (mHealth) that incorporate theoretical frameworks regarding behavioral change in interaction with the environment may provide an appealing and cost-effective approach for promoting sustainable adaptations of healthier lifestyles. We designed a randomized controlled trial (RCT) to evaluate the effectiveness of a socioecological model-guided, smart device-based, and self-management-oriented lifestyles (3SLIFE) intervention, to promote healthy lifestyles among Chinese community residents.

METHODS

This two-arm, parallel, cluster-RCT with a 6-month intervention and 6-month follow-up period foresees to randomize a total of 20 communities/villages from 4 townships in a 1:1 ratio to either intervention or control. Within these communities, a total of at least 256 community residents will be enrolled. The experimental group will receive a multi-level intervention based on the socioecological model supplemented with a multi-dimensional empowerment approach. The control group will receive information only. The primary outcome is the reduction of modifiable unhealthy lifestyles at six months, including smoking, excess alcohol consumption, physical inactivity, unbalanced diet, and overweight/obesity. A reduction by one unhealthy behavior measured with the Healthy Lifestyle Index Score (HLIS) will be considered favorable. Secondary outcomes include reduction of specific unhealthy lifestyles at 3 months, 9 months, and 12 months, and mental health outcomes such as depression measured with PHQ-9, social outcomes such as social support measured with the modified Multidimensional Scale of Perceived Social Support, clinical outcomes such as obesity, and biomedical outcomes such as the development of gut microbiota. Data will be analyzed with mixed effects generalized linear models with family and link function determined by outcome distribution and accounting for clustering of participants in communities.

DISCUSSION

This study will provide evidence concerning the effect of a mHealth intervention that incorporates a behavioral change theoretical framework on cultivating and maintaining healthy lifestyles in community residents. The study will provide insights into research on and application of similar mHealth intervention strategies to promote healthy lifestyles in community populations and settings.

TRIAL REGISTRATION NUMBER

ChiCTR2300070575. Date of registration: April 17, 2023. https://www.chictr.org.cn/index.aspx .

Review of strategies to investigate low sample return rates in remote tobacco trials: A call to action for more user-centered design research

Remote collection of biomarkers of tobacco use in clinical trials poses significant challenges. A recent meta-analysis and scoping review of the smoking cessation literature indicated that sample return rates are low and that new methods are needed to investigate the underlying causes of these low rates. In this paper we conducted a narrative review and heuristic analysis of the different human factors approaches reported to evaluate and/or improve sample return rates among 31 smoking cessation studies recently identified in the literature. We created a heuristic metric (with scores from 0 to 4) to evaluate the level of elaboration or complexity of the user-centered design strategy reported by researchers. Our review of the literature identified five types of challenges typically encountered by researchers (in that order): usability and procedural, technical (device related), sample contamination (e.g., polytobacco), psychosocial factors (e.g., digital divide), and motivational factors. Our review of strategies indicated that 35% of the studies employed user-centered design methods with the remaining studies relying on informal methods. Among the studies that employed user-centered design methods, only 6% reached a level of 3 in our user-centered design heuristic metric. None of the studies reached the highest level of complexity (i.e., 4). This review examined these findings in the context of the larger literature, discussed the need to address the role of health equity factors more directly, and concluded with a call to action to increase the application and reporting of user-centered design strategies in biomarkers research.

Life Course Cardiovascular Health: Risk Factors, Outcomes, and Interventions

Since it was first defined by the American Heart Association in 2010, cardiovascular health (CVH) has been extensively studied across the life course. In this review, we present the current literature examining early life predictors of CVH, the later life outcomes of child CVH, and the relatively few interventions which have specifically addressed how to preserve and promote CVH across populations. We find that research on CVH has demonstrated that prenatal and childhood exposures are consistently associated with CVH trajectories from childhood through adulthood. CVH measured at any point in life is strongly predictive of future cardiovascular disease, dementia, cancer, and mortality as well as a variety of other health outcomes. This speaks to the importance of intervening early to prevent the loss of optimal CVH and the accumulation of cardiovascular risk. Interventions to improve CVH are not common but those that have been published most often address multiple modifiable risk factors among individuals within the community. Relatively few interventions have been focused on improving the construct of CVH in children. Future research is needed that will be both effective, scalable, and sustainable. Technology including digital platforms as well as implementation science will play key roles in achieving this vision. In addition, community engagement at all stages of this research is critical. Lastly, prevention strategies that are tailored to the individual and their context may help us achieve the promise of personalized prevention and help promote ideal CVH in childhood and across the life course.

Improving representativeness in trials: a call to action from the Global Cardiovascular Clinical Trialists Forum

Participants enrolled in cardiovascular disease (CVD) randomized controlled trials are not often representative of the population living with the disease. Older adults, children, women, Black, Indigenous and People of Color, and people living in low- and middle-income countries are typically under-enrolled in trials relative to disease distribution. Treatment effect estimates of CVD therapies have been largely derived from trial evidence generated in White men without complex comorbidities, limiting the generalizability of evidence. This review highlights barriers and facilitators of trial enrollment, temporal trends, and the rationale for representativeness. It proposes strategies to increase representativeness in CVD trials, including trial designs that minimize the research burden on participants, inclusive recruitment practices and eligibility criteria, diversification of clinical trial leadership, and research capacity-building in under-represented regions. Implementation of such strategies could generate better and more generalizable evidence to reduce knowledge gaps and position the cardiovascular trial enterprise as a vehicle to counter existing healthcare inequalities.

Geospatial Analysis of Neighborhood Environmental Stress in Relation to Biological Markers of Cardiovascular Health and Health Behaviors in Women: Protocol for a Pilot Study

Background

Innovative analyses of cardiovascular (CV) risk markers and health behaviors linked to neighborhood stressors are essential to further elucidate the mechanisms by which adverse neighborhood social conditions lead to poor CV outcomes. We propose to objectively measure physical activity (PA), sedentary behavior, and neighborhood stress using accelerometers, GPS, and real-time perceived ecological momentary assessment via smartphone apps and to link these to biological measures in a sample of White and African American women in Washington, DC, neighborhoods.

Objective

The primary aim of this study is to test the hypothesis that living in adverse neighborhood social conditions is associated with higher stress-related neural activity among 60 healthy women living in high or low socioeconomic status neighborhoods in Washington, DC. Sub-aim 1 of this study is to test the hypothesis that the association is moderated by objectively measured PA using an accelerometer. A secondary objective is to test the hypothesis that residing in adverse neighborhood social environment conditions is related to differences in vascular function. Sub-aim 2 of this study is to test the hypothesis that the association is moderated by objectively measured PA. The third aim of this study is to test the hypothesis that adverse neighborhood social environment conditions are related to differences in immune system activation.

Methods

The proposed study will be cross-sectional, with a sample of at least 60 women (30 healthy White women and 30 healthy Black women) from Wards 3 and 5 in Washington, DC. A sample of the women (n=30) will be recruited from high-income areas in Ward 3 from census tracts within a 15% of Ward 3’s range for median household income. The other participants (n=30) will be recruited from low-income areas in Wards 5 from census tracts within a 15% of Ward 5’s range for median household income. Finally, participants from Wards 3 and 5 will be matched based on age, race, and BMI. Participants will wear a GPS unit and accelerometer and report their stress and mood in real time using a smartphone. We will then examine the associations between GPS-derived neighborhood variables, stress-related neural activity measures, and adverse biological markers.

Results

The National Institutes of Health Institutional Review Board has approved this study. Recruitment will begin in the summer of 2021.

Conclusions

Findings from this research could inform the development of multilevel behavioral interventions and policies to better manage environmental factors that promote immune system activation or psychosocial stress while concurrently working to increase PA, thereby influencing CV health.

International Registered Report Identifier (IRRID)

PRR1-10.2196/29191