Effects of Chronic Burden Across Multiple Domains and Experiences of Daily Stressors on Negative Affect.

BACKGROUND: Exposure to chronic psychological stress across multiple life domains (multi-domain chronic burden) is associated with poor health. This may be because multi-domain chronic burden influences daily-level emotional processes, though this hypothesis has not been thoroughly tested. PURPOSE: The current study tested whether (a) multi-domain chronic burden is associated with greater exposure to daily stressors and (b) multi-domain chronic burden compounds negative affect on days with stressors compared to stressor-free days. METHODS: The MIDUS Study (Wave II) and the National Study of Daily Experiences sub-study were conducted from 2004 to 2006 (N = 2,022). Participants reported on eight life domains of psychological stress used to create a multi-domain chronic burden summary score. For eight consecutive days, participants reported the daily occurrence of stressful events and daily negative affect. RESULTS: Participants with greater multi-domain chronic burden were significantly more likely to report daily stressors. There was also a significant interaction between multi-domain chronic burden and daily stressors on negative affect: participants with higher multi-domain chronic burden had greater negative affect on stressor days than stressor-free days compared to those with lower multi-domain chronic burden. CONCLUSION: Participants with higher multi-domain chronic burden were more likely to report daily stressors and there was a compounding effect of multi-domain chronic burden and daily stressors on negative affect. These results suggest that experiencing a greater amount of psychological stress across multiple life domains may make daily stressors more toxic for daily affect.

Psychophysiological correlates of systemic inflammation in black and white men.

Inflammation plays a critical role in the pathophysiology of cardiovascular disease (CVD) and levels of circulating inflammatory markers are associated with future CVD risk. However, the physiological mechanisms that control systemic levels of circulating inflammatory markers are not well understood. Here, we explore possible autonomic nervous system mechanisms by testing whether resting and stressor-evoked cardiovascular responses are associated with two markers of systemic inflammation: interleukin (IL)-6 and C-reactive protein (CRP). Subjects were 159 black and 129 white men (M=33.0years) who completed a laboratory protocol including an anger recall speech task. Electrocardiography and impedance cardiography data were collected during a resting baseline, the speech task, and a final recovery period. Hierarchical regressions tested whether resting or stressor-evoked levels of heart rate (HR), high-frequency heart rate variability (HF-HRV), pre-ejection period (PEP), and pulse transit time (PTT) were associated with CRP or IL-6. Higher resting HR was associated with higher CRP (ß=0.19, p=0.003) and IL-6 (ß=0.13, p<0.05). Similarly, shorter resting PTT was associated with higher CRP (ß=-0.21, p<0.001) and IL-6 (ß=-0.14, p=0.02). In addition, greater stressor-evoked decreases in HF-HRV were associated with higher CRP (ß=-0.14, p=0.01). Associations were independent of age, race, body mass index (BMI), smoking behavior, and socioeconomic status. Resting HF-HRV and PEP were also associated with CRP and IL-6, but associations were not significant after controlling for BMI and smoking behavior. These findings indicate that resting HR and PTT, as well stressor-evoked HF-HRV reactivity, are associated with systemic inflammation. Our results suggest that both tonic and stressor-evoked sympathetic and parasympathetic nervous system activity may contribute to regulation of systemic inflammation.

Sex differences in the association between stressor-evoked interleukin-6 reactivity and C-reactive protein.

Individuals differ consistently in the magnitude of their inflammatory responses to acute stressors, with females often showing larger responses than males. While the clinical significance of these individual differences remains unclear, it may be that greater inflammatory responses relate to increased systemic inflammation and thereby risk for chronic inflammatory disease. Here, we examined whether acute stressor-evoked interleukin (IL)-6 responses associate with resting levels of C-reactive protein (CRP), a marker of systemic inflammation, and whether this association differs by sex. Subjects were 57 healthy midlife adults (30-51years; 33% female; 68% white). Blood was drawn before and 30-min after two mental stress tasks: a multisource interference task and a Stroop color word task. Hierarchical regressions controlling for age, sex, race, and BMI tested whether stressor-evoked IL-6 responses were associated with resting CRP and whether this association differed by sex. Results indicated that sex and stressor-evoked IL-6 responses interacted to predict CRP (ΔR2=0.08, B=-1.33, ß=-0.39, p=0.02). In males, larger stressor-evoked IL-6 responses associated with higher CRP, whereas in females, stressor-evoked IL-6 responses showed a non-significant negative association with CRP. These findings indicate that inflammatory responses to acute stressors associate with resting levels of CRP; however, this association differs by sex. Previous literature suggests that there are sex differences in stressor-evoked IL-6 responses, but this is the first study to show sex differences in the relationship between acute inflammatory responses and systemic inflammation. The contribution of these sex differences to inflammatory disease risk warrants further investigation.

Evaluating a New Digital App-Based Program for Heart Health: Feasibility and Acceptability Pilot Study.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the United States, affecting a significant proportion of adults. Digital health lifestyle change programs have emerged as a promising method of CVD prevention, offering benefits such as on-demand support, lower cost, and increased scalability. Prior research has shown the effectiveness of digital health interventions in reducing negative CVD outcomes. This pilot study focuses on the Lark Heart Health program, a fully digital artificial intelligence (AI)-powered smartphone app, providing synchronous CVD risk counseling, educational content, and personalized coaching. OBJECTIVE: This pilot study evaluated the feasibility and acceptability of a fully digital AI-powered lifestyle change program called Lark Heart Health. Primary analyses assessed (1) participant satisfaction, (2) engagement with the program, and (3) the submission of health screeners. Secondary analyses were conducted to evaluate weight loss outcomes, given that a major focus of the Heart Health program is weight management. METHODS: This study enrolled 509 participants in the 90-day real-world single-arm pilot study of the Heart Health app. Participants engaged with the app by participating in coaching conversations, logging meals, tracking weight, and completing educational lessons. The study outcomes included participant satisfaction, app engagement, the completion of screeners, and weight loss. RESULTS: On average, Heart Health study participants were aged 60.9 (SD 10.3; range 40-75) years, with average BMI indicating class I obesity. Of the 509 participants, 489 (96.1%) stayed enrolled until the end of the study (dropout rate: 3.9%). Study retention, based on providing a weight measurement during month 3, was 80% (407/509; 95% CI 76.2%-83.4%). Participant satisfaction scores indicated high satisfaction with the overall app experience, with an average score of ≥4 out of 5 for all satisfaction indicators. Participants also showed high engagement with the app, with 83.4% (408/489; 95% CI 80.1%-86.7%) of the sample engaging in ≥5 coaching conversations in month 3. The results indicated that participants were successfully able to submit health screeners within the app, with 90% (440/489; 95% CI 87%-92.5%) submitting all 3 screeners measured in the study. Finally, secondary analyses showed that participants lost weight during the program, with analyses showing an average weight nadir of 3.8% (SD 2.9%; 95% CI 3.5%-4.1%). CONCLUSIONS: The study results indicate that participants in this study were satisfied with their experience using the Heart Health app, highly engaged with the app features, and willing and able to complete health screening surveys in the app. These acceptability and feasibility results provide a key first step in the process of evidence generation for a new AI-powered digital program for heart health. Future work can expand these results to test outcomes with a commercial version of the Heart Health app in a diverse real-world sample.

Weight loss and modeled cost savings in a digital diabetes prevention program.

Background: Participation in the National Diabetes Prevention Program (DPP) can improve individual health through reduced risk of type 2 diabetes and save the healthcare system substantial medical costs associated with a diagnosis of type 2 diabetes and its associated complications. There is less evidence of outcomes and cost savings associated with a fully digital delivery of the DPP. Methods: This study assessed 13,593 members who provided an initial digital weight and subsequently achieved various weight loss and engagement outcomes during their participation in a digital DPP. Analyzed data included both complete observations and missing observations imputed using maximum likelihood estimation. Findings include members' behavioral correlates of weight loss and a literature-based cost-savings estimate associated with achieving three mutually exclusive weight loss or engagement benchmarks: ≥5% weight loss, >2% but <5% weight loss, and completion of ≥4 educational lessons. Results: 11,976 members (88%) provided a weight after 2 months of participation, enabling calculation of their weight nadir. Considering complete data, 97% of members maintained or lost weight. Using the imputed data for these calculations, 32.0% of members achieved ≥5%, 32.4% achieved >2% but <5%, 32.0% maintained ±2%, and 3.6% gained weight. Members who lost the most weight achieved their weight nadir furthest into the program (mean day = 189, SE = 1.4) and had the longest active engagement (mean days = 268, SE = 1.4), particularly compared to members who gained weight (mean nadir day = 119, SE = 3.7; active engagement mean days = 199, SE = 4.9) (both p ≤ 0.0001). Modeled 1-year cost-savings estimates ranged from $11,229,160 to $12,960,875. Conclusions: Members of a fully digital DPP achieved clinical and engagement outcomes during their participation in the program that confer important health benefits and cost savings.

Weight Loss in a Digital Diabetes Prevention Program for People in Health Professional Shortage and Rural Areas.

Individuals with prediabetes living in hard-to-reach and underserved areas experience barriers to accessing traditional in-person preventive health services. The National Diabetes Prevention Program (DPP) is a preventive health care program designed to reduce the risk of developing type 2 diabetes. Although there have been increasing numbers of remote DPPs accessible, there are little data on the clinical outcomes of digital DPPs for members living in hard-to-reach and underserved areas. This study assessed whether living in a designated Health Professional Shortage Area (HPSA) and a rural versus urban area impacted the weight loss of N = 7266 members of a fully digital program called Lark DPP. Secondary analyses included between-group comparisons of program retention and member characteristics, demographics, and socioeconomics. Percent weight loss did not differ by HPSA (P = 0.16) or rural/urban status (P = 0.15), despite greater potential barriers for members residing in HPSAs (eg, highest starting body mass index, lowest income, lowest education). Mean percent weight loss for members residing in an HPSA and rural area was mean (M) = 4.75%, standard error (SE) = 0.09; for members in a non-HPSA, rural area M = 4.96%, SE = 0.16; for members in an HPSA, urban area M = 4.55%, SE = 0.13; and for members in a non-HPSA, urban area M = 4.77%, SE = 0.13. Members of a fully digital DPP achieved weight loss that did not differ by HPSA or urban/rural designation. Fully digital programs offer a solution to reduce the risk of type 2 diabetes in areas where residents may not otherwise have access to diabetes prevention services.

Predictors of program interest in a digital health pilot study for heart health.

Digital health programs can play a key role in supporting lifestyle changes to prevent and reduce cardiovascular disease (CVD) risk. A key concern for new programs is understanding who is interested in participating. Thus, the primary objective of this study was to utilize electronic health records (EHR) to predict interest in a digital health app called Lark Heart Health. Because prior studies indicate that males are less likely to utilize prevention-focused digital health programs, secondary analyses assessed sex differences in recruitment and enrollment. Data were drawn from an ongoing pilot study of the Heart Health program, which provides digital health behavior coaching and surveys for CVD prevention. EHR data were used to predict whether potential program participants who received a study recruitment email showed interest in the program by "clicking through" on the email to learn more. Primary objective analyses used backward elimination regression and eXtreme Gradient Boost modeling. Recruitment emails were sent to 8,649 patients with available EHR data; 1,092 showed interest (i.e., clicked through) and 345 chose to participate in the study. EHR variables that predicted higher odds of showing interest were higher body mass index (BMI), fewer elevated lab values, lower HbA1c, non-smoking status, and identifying as White. Secondary objective analyses showed that, males and females showed similar program interest and were equally represented throughout recruitment and enrollment. In summary, BMI, elevated lab values, HbA1c, smoking status, and race emerged as key predictors of program interest; conversely, sex, age, CVD history, history of chronic health issues, and medication use did not predict program interest. We also found no sex differences in the recruitment and enrollment process for this program. These insights can aid in refining digital health tools to best serve those interested, as well as highlight groups who may benefit from behavioral intervention tools promoted by additional recruitment efforts tailored to their interest.

Engagement in Digital Health App-Based Prevention Programs Is Associated With Weight Loss Among Adults Age 65.

Background: Digital health programs have been shown to be feasible and effective for the prevention of chronic diseases such as diabetes. Contrary to expectations, findings also suggest that older adults have higher levels of engagement with digital health programs than younger adults. However, there is a paucity of research examining outcomes among older adults in digital health programs and whether higher engagement is related to better outcomes. Methods: We examined weight loss outcomes for 538 users aged 65 and older participating in one of two app-based prevention programs called the Diabetes Prevention Program and the Prevention Program, respectively. Both programs were available on a single artificial intelligence (AI)-powered digital health platform and shared a common goal of weight loss. We also examined the relationship between key engagement metrics (i.e., conversing with the AI-powered coach, weigh-ins, and initiating educational lessons early in the program) and weight loss outcomes. Results: The average weight loss of all enrollees having a weight measurement after after the 9th week was 4.51%, and the average weight loss of the Diabetes Prevention Program enrollees meeting a minimum engagement level was 8.56%. Greater weight loss was associated with a greater number of days with AI-powered coaching conversations (p = 0.03), more weigh-ins (p = 0.00), and early educational lesson initiation (p = 0.02). Conclusions: Digital health programs powered by AI offer a promising solution for health management among older adults. The results show positive health outcomes using app-based prevention programs, and all three engagement metrics were independently associated with weight loss.

Reach of a Fully Digital Diabetes Prevention Program in Health Professional Shortage Areas.

The National Diabetes Prevention Program (NDPP) offers lifestyle change education to adults at risk for diabetes across the United States, but its reach is curbed due, in part, to limitations of traditional in-person programs. Diabetes Prevention Programs (DPPs) that are fully digital may increase reach by overcoming these barriers. The aim of this research was to examine the reach of Lark's DPP, a fully digital artificial-intelligence-powered DPP. This study assessed geographic features and demographic characteristics of a sample of Lark DPP commercial health plan members with complete data (N = 16,327) and compared several demographic features with a large composite sample of members from DPPs across the nation (NDPP; N = 143,489) and a National Health Interview Survey (NHIS) sample of prediabetic adults in the United States (NHIS; N = 2118). Examination of the Lark DPP sample revealed that 24.4% of members lived in rural areas, 30.8% lived in whole county health professional shortage areas, and only 7.6% of members lived in a zip code with an in-person DPP. When comparing the Lark sample with the NDPP and NHIS samples, Lark DPP enrollees tended to be younger and have a higher body mass index (BMI) (p's < 0.001). Lark provides convenient access to a DPP for individuals living in hard-to-reach areas who may face barriers to participating in in-person or telephonic DPPs or who prefer a digital program. Compared with the NDPP sample, Lark is also reaching younger and higher BMI users, who are traditionally difficult to enroll and have a high need for intervention.

Relationships Between Blood Pressure Reduction, Weight Loss, and Engagement in a Digital App-Based Hypertension Care Program: Observational Study.

BACKGROUND: Home blood pressure (BP) monitoring is recommended for people with hypertension; however, meta-analyses have demonstrated that BP improvements are related to additional coaching support in combination with self-monitoring, with little or no effect of self-monitoring alone. High-contact coaching requires substantial resources and may be difficult to deliver via human coaching models. OBJECTIVE: This observational study assessed changes in BP and body weight following participation in a fully digital program called Lark Hypertension Care with coaching powered by artificial intelligence (AI). METHODS: Participants (N=864) had a baseline systolic BP (SBP) ≥120 mm Hg, provided their baseline body weight, and had reached at least their third month in the program. The primary outcome was the change in SBP at 3 and 6 months, with secondary outcomes of change in body weight and associations of changes in SBP and body weight with participant demographics, characteristics, and program engagement. RESULTS: By month 3, there was a significant drop of -5.4 mm Hg (95% CI -6.5 to -4.3; P<.001) in mean SBP from baseline. BP did not change significantly (ie, the SBP drop maintained) from 3 to 6 months for participants who provided readings at both time points (P=.49). Half of the participants achieved a clinically meaningful drop of ≥5 mm Hg by month 3 (178/349, 51.0%) and month 6 (98/199, 49.2%). The magnitude of the drop depended on starting SBP. Participants classified as hypertension stage 2 had the largest mean drop in SBP of -12.4 mm Hg (SE 1.2 mm Hg) by month 3 and -13.0 mm Hg (SE 1.6 mm Hg) by month 6; participants classified as hypertension stage 1 lowered by -5.2 mm Hg (SE 0.8) mm Hg by month 3 and -7.3 mm Hg (SE 1.3 mm Hg) by month 6; participants classified as elevated lowered by -1.1 mm Hg (SE 0.7 mm Hg) by month 3 but did not drop by month 6. Starting SBP (ß=.11; P<.001), percent weight change (ß=-.36; P=.02), and initial BMI (ß=-.56; P<.001) were significantly associated with the likelihood of lowering SBP ≥5 mm Hg by month 3. Percent weight change acted as a mediator of the relationship between program engagement and drop in SBP. The bootstrapped unstandardized indirect effect was -0.0024 (95% CI -0.0052 to 0; P=.002). CONCLUSIONS: A hypertension care program with coaching powered by AI was associated with a clinically meaningful reduction in SBP following 3 and 6 months of program participation. Percent weight change was significantly associated with the likelihood of achieving a ≥5 mm Hg drop in SBP. An AI-powered solution may offer a scalable approach to helping individuals with hypertension achieve clinically meaningful reductions in their BP and associated risk of cardiovascular disease and other serious adverse outcomes via healthy lifestyle changes such as weight loss.

Discovering Engagement Personas in a Digital Diabetes Prevention Program.

Digital health technologies are shaping the future of preventive health care. We present a quantitative approach for discovering and characterizing engagement personas: longitudinal engagement patterns in a fully digital diabetes prevention program. We used a two-step approach to discovering engagement personas among n = 1613 users: (1) A univariate clustering method using two unsupervised k-means clustering algorithms on app- and program-feature use separately and (2) A bivariate clustering method that involved comparing cluster labels for each member across app- and program-feature univariate clusters. The univariate analyses revealed five app-feature clusters and four program-feature clusters. The bivariate analysis revealed five unique combinations of these clusters, called engagement personas, which represented 76% of users. These engagement personas differed in both member demographics and weight loss. Exploring engagement personas is beneficial to inform strategies for personalizing the program experience and optimizing engagement in a variety of digital health interventions.

Dual impedance cardiography: An inexpensive and reliable method to assess arterial stiffness.

Pulse wave velocity (PWV) is a common measure of arterial stiffness. Non-invasive methods to measure PWV are widely used in biomedical studies of aging and cardiovascular disease, but they are rarely used in psychophysiology. Barriers to wider use include the prohibitive costs of specialized equipment and need for trained technicians (e.g., ultrasonographers). Here, we describe an impedance cardiography method to measure PWV. By this method, impedance signals are dually collected from the thorax and calf. Combined with ensemble averaging of vascular signals, this dual impedance cardiography (d-ICG) method allows for the measurement of aortic flow onset and the arrival time of peripheral pulse waveforms to compute PWV. In a community sample of adults (aged 19-78 years), PWV measured with d-ICG exhibited a strong positive correlation with age. Moreover, age-specific mean PWV values were within the normative reference intervals established by large scale studies using other techniques. PWV derived from d-ICG exhibited high test-retest reliability across several days, as well as excellent inter-rater reliability. Last, PWV exhibited expected associations with known cardiovascular disease risk factors and indicators of autonomic cardiovascular control. d-ICG is an inexpensive and reliable method to assess arterial stiffness.

Best practices for stress measurement: How to measure psychological stress in health research.

Despite the strong evidence linking psychological stress to disease risk, health researchers often fail to include psychological stress in models of health. One reason for this is the incorrect perception that the construct of psychological stress is too vague and broad to accurately measure. This article describes best practices in stress measurement, detailing which dimensions of stressor exposures and stress responses to capture, and how. We describe when to use psychological versus physiological indicators of stress. It is crucial that researchers across disciplines utilize the latest methods for measuring and describing psychological stress in order to build a cumulative science.

Perceived discrimination and cardiovascular health disparities: a multisystem review and health neuroscience perspective.

There are distinct racial disparities in cardiovascular disease (CVD) risk, with Black individuals at much greater risk than White individuals. Although many factors contribute to these disparities, recent attention has focused on the role of discrimination as a stress-related factor that contributes to racial disparities in CVD. As such, it is important to understand the mechanisms by which discrimination might affect CVD. Recent studies have examined these mechanisms by focusing on neurobiological mediators of CVD risk. Given this increase in studies, a systematic review of perceived discrimination and neurobiological mediators of CVD risk is warranted. Our review uses a multisystem approach to review studies on the relationship between perceived discrimination and (1) cardiovascular responses to stress, (2) hypothalamic-pituitary-adrenocortical axis function, and (3) the immune system, as well as (4) the brain systems thought to regulate these parameters of peripheral physiology. In addition to summarizing existing evidence, our review integrates these findings into a conceptual model describing multidirectional pathways linking perceived discrimination with a CVD risk.

Early life socioeconomic status associates with interleukin-6 responses to acute laboratory stress in adulthood.

It is proposed that environmental exposures in early life influence immune programming. Specifically, socioeconomic disadvantage is thought to program an immune phenotype that is prone to inflammation and associated with increased risk for inflammatory disease later in life. Existing literature shows an inverse association of early childhood socioeconomic status (SES) with adult levels of systemic inflammation. Here, we extend that literature to examine whether early childhood SES also relates to the magnitude of inflammatory response to acute psychological stress in adulthood. Healthy volunteers (N = 110; 40-58 years; 59% female; 90% white) performed a laboratory stress protocol, with blood samples drawn at the end of a 30-min baseline, a 5-min speech task, and a 30-min recovery to assess interleukin (IL)-6 stress responses. An early childhood SES index was derived from reports of parental home and vehicle ownership, and number of bedrooms per child in the home across ages 1-2, 3-4, and 5-6. Regressions adjusted for current age, sex, race, and BMI showed that lower SES at age 1-2 was associated with larger IL-6 stress responses in adulthood (ΔR2 = 0.05, ß = -0.24, p = .03). This association was independent of adult SES and task-evoked affective responses. No association was found between SES at ages 3-4 or 5-6 and IL-6 responses. These results provide initial evidence for a link between disadvantage in the first 2 years of life and heightened inflammatory response to stress in adulthood; this link may contribute to the increased disease risk that accompanies being raised in disadvantaged socioeconomic circumstances.

Business vs After-Hours Use of an Artificial Intelligence-Powered Digital Health Platform Among Insured Patients.

This cross-sectional study assesses usage patterns of an AI-powered patient digital health platform.

Low heart rate variability and cancer-related fatigue in breast cancer survivors.

Cancer-related fatigue is a common and often long lasting symptom for many breast cancer survivors. Fatigued survivors show evidence of elevated inflammation, but the physiological mechanisms driving inflammatory activity have not been determined. Alterations in the autonomic nervous system, and particularly parasympathetic nervous system activity, are a plausible, yet understudied contributor to cancer-related fatigue. The goal of this study was to replicate one previous study showing an association between lower parasympathetic activity and higher fatigue in breast cancer survivors (Fagundes et al., 2011), and to examine whether inflammation mediates this association. Study participants were drawn from two samples and included 84 women originally diagnosed with early stage breast cancer prior to age 50. Participants completed questionnaires, provided blood samples for determination of interleukin (IL)-6 and C-reactive protein (CRP), and underwent electrocardiography (ECG) assessment for evaluation of resting heart rate variability (HRV), a measure of parasympathetic activity. Results showed that lower HRV was associated with higher fatigue (p<.05), as predicted. In bivariate analyses, HRV was also correlated with circulating concentrations of IL-6 and CRP. However, path analyses did not support inflammation as a mediator of the association between HRV and fatigue; instead, associations among these variables appeared to be driven by age and BMI. These findings identify HRV as a potential contributor to cancer-related fatigue, but suggest that inflammation does not mediate this association in younger, healthy breast cancer survivors who are several years post-treatment. The autonomic nervous system merits additional attention in research on the etiology of cancer-related fatigue.