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BackgroundIn light of the scarcity of culturally tailored mobile health (mHealth) lifestyle interventions for African Americans, we designed and pilot tested the Fostering African-American Improvement in Total Health (FAITH!) App in a community-based participatory research partnership with African American churches to promote cardiovascular health and wellness in this population. ObjectiveThis report presents the results of a formative evaluation of the FAITH! App from participants in an intervention pilot study. MethodsWe included 2 semistructured focus groups (n=4 and n=5) to explore participants’ views on app functionality, utility, and satisfaction as well as its impact on healthy lifestyle change. Sessions were audio-recorded and transcribed verbatim, and qualitative data were analyzed by using general inductive analysis to generate themes. ResultsIn total, 6 overarching themes emerged among the 9 participants: overall impression, content usefulness, formatting, implementation, impact, and suggestions for improvement. Underpinning the themes was a high level of agreement that the intervention facilitated healthy behavioral change through cultural tailoring, multimedia education modules, and social networking. Suggestions for improvement were streamlining the app self-monitoring features, prompts to encourage app use, and personalization based on individuals’ cardiovascular risk. ConclusionsThis formative evaluation found that the FAITH! App had high reported satisfaction and impact on the health-promoting behaviors of African Americans, thereby improving their overall cardiovascular health. Further development and testing of the app among African Americans is warranted. Trial RegistrationClinicalTrials.gov NCT03084822; https://clinicaltrials.gov/ct2/show/NCT03084822.

BackgroundPrevious studies have reported older adults’ perceptions of using health monitors; however, no studies have examined the actual use of multiple health monitors for lifestyle changes over time among older adults with type 2 diabetes (T2D). ObjectiveThe primary aim of this study was to examine the actual use of multiple health monitors for lifestyle changes over 3 months among older adults with T2D. The secondary aim was to explore changes in caloric intake and physical activity (PA) over 3 months. MethodsThis was a single-group study lasting 3 months. The study sample included participants who were aged ≥65 years with a diagnosis of T2D. Participants were recruited through fliers posted at the Joslin Diabetes Center in Boston. Participants attended five 60-min, biweekly group sessions, which focused on self-monitoring, goal setting, self-regulation to achieve healthy eating and PA habits, and the development of problem-solving skills. Participants were provided with the Lose It! app to record daily food intake and devices such as a Fitbit Alta for monitoring PA, a Bluetooth-enabled blood glucose meter, and a Bluetooth-enabled digital scale. Descriptive statistics were used for analysis. ResultsOf the enrolled participants (N=9), the sample was white (8/9, 89%) and female (4/9, 44%), with a mean age of 76.4 years (SD 6.0; range 69-89 years), 15.7 years (SD 2.0) of education, 33.3 kg/m2 (SD 3.1) BMI, and 7.4% (SD 0.8) hemoglobin A1c. Over the 84 days of self-monitoring, the mean percentage of days using the Lose It!, Fitbit Alta, blood glucose meter, and scale were 82.7 (SD 17.6), 85.2 (SD 19.7), 65.3 (SD 30.1), and 53.0 (SD 34.5), respectively. From baseline to completion of the study, the mean daily calorie intake was 1459 (SD 661) at week 1, 1245 (SD 554) at week 11, and 1333 (SD 546) at week 12, whereas the mean daily step counts were 5618 (SD 3654) at week 1, 5792 (SD 3814) at week 11, and 4552 (SD 3616) at week 12. The mean percentage of weight loss from baseline was 4.92% (SD 0.25). The dose of oral hypoglycemic agents or insulin was reduced in 55.6% (5/9) of the participants. ConclusionsThe results from the pilot study are encouraging and suggest the need for a larger study to confirm the outcomes. In addition, a study design that includes a control group with educational sessions but without the integration of technology would offer additional insight to understand the value of mobile health in behavior changes and the health outcomes observed during this pilot study.

STUDY OBJECTIVES: This single-arm, mixed-methods, pilot study examined the feasibility and preliminary efficacy of an adapted version of the transdiagnostic intervention for sleep and circadian dysfunction (TranS-C) on multidimensional sleep health (MDSH) in a sample of adults with excess weight and suboptimal sleep health. METHODS: Participants received up to eight, weekly, remotely delivered, tailored TranS-C sessions. At pre- and post-intervention, the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and 7 days of Fitbit data were used to evaluate changes in sleep dimensions (regularity, alertness, timing, satisfaction, duration, and efficiency) and the composite MDSH score. Study feasibility examined recruitment, data collection, and intervention engagement (completion of core TranS-C sessions). Acceptability of the intervention was assessed with semi-structured interviews, which were analyzed using thematic analysis. RESULTS: From 85 referrals, 11 individuals were eligible, and 10 completed the study. All intervention participants completed the measures needed to calculate their composite MDSH score and completed the core intervention sessions. Themes from interviews support the interventions remote delivery approach, applicability of the information provided, and impact on self-reported health. The intervention resulted in a large improvement in the mean composite MDSH score (Cohens d = 1.17). Small-to-large effects were also observed for individual sleep health dimensions except for timing. CONCLUSIONS: Adapted TranS-C is acceptable for adults with excess weight and suboptimal sleep health and may be effective at improving short-term MDSH. With changes to recruitment methods, a larger study is feasible. Limitations include the small sample size and the lack of a control condition.

BackgroundEngagement with self-monitoring of blood pressure (BP) declines, on average, over time but may vary substantially by individual.ObjectivesWe aimed to describe different 1-year patterns (groups) of self-monitoring of BP behaviors, identify predictors of those groups, and examine the association of self-monitoring of BP groups with BP levels over time.MethodsWe analyzed device-recorded BP measurements collected by the Health eHeart Study-an ongoing prospective eCohort study-from participants with a wireless consumer-purchased device that transmitted date- and time-stamped BP data to the study through a full 12 months of observation starting from the first day they used the device. Participants received no instruction on device use. We applied clustering analysis to identify 1-year self-monitoring, of BP patterns.ResultsParticipants had a mean age of 52 years and were male and White. Using clustering algorithms, we found that a model with three groups fit the data well: persistent daily use (9.1% of participants), persistent weekly use (21.2%), and sporadic use only (69.7%). Persistent daily use was more common among older participants who had higher Week 1 self-monitoring of BP frequency and was associated with lower BP levels than the persistent weekly use or sporadic use groups throughout the year.ConclusionWe identified three distinct self-monitoring of BP groups, with nearly 10% sustaining a daily use pattern associated with lower BP levels.

Self-weighing may promote attainment and maintenance of healthy weight; however, the natural temporal patterns and factors associated with self-weighing behavior are unclear. The aims of this secondary analysis were to (1) identify distinct temporal patterns of self-weighing behaviors; (2) explore factors associated with temporal self-weighing patterns; and (3) examine differences in percent weight changes by patterns of self-weighing over time. We analyzed electronically collected self-weighing data from the Health eHeart Study, an ongoing longitudinal research study coordinated by the University of California, San Francisco. We selected participants with at least 12 months of data since the day of first use of a WiFi- or Bluetooth-enabled digital scale. The sample (N = 1041) was predominantly male (77.5%) and White (89.9%), with a mean age of 46.5 ± 12.3 years and a mean BMI of 28.3 ± 5.9 kg/m2 at entry. Using group-based trajectory modeling, six distinct temporal patterns of self-weighing were identified: non-users (n = 120, 11.5%), weekly users (n = 189, 18.2%), rapid decliners (n = 109, 10.5%), increasing users (n = 160, 15.4%), slow decliners (n = 182, 17.5%), and persistent daily users (n = 281, 27.0%). Individuals who were older, female, or self-weighed 6-7 days/week at week 1 were more likely to follow the self-weighing pattern of persistent daily users. Predicted self-weighing trajectory group membership was significantly associated with weight change over time (p

Adding feedback messages (FB) to self-monitoring (SM) may reinforce behavior change. However, socio-environmental conditions (e.g., limited access to parks or low walkability) may limit one's ability to respond to FB focused on physical activity (PA). In this analysis, we hypothesized that high neighborhood walkability will positively modify the treatment effect of FB on PA, and residents of high walkability neighborhoods will achieve higher PA levels at 12 months than those in low walkability neighborhoods. The study is a secondary analysis of a 12-month behavioral weight-loss trial. Adults with overweight/obesity were randomized to SM + FB (n = 251) or SM alone (n = 251). SM + FB group received smartphone pop-up messages thrice/week tailored to their PA SM data. The assessment included neighborhood walkability via Walk Score (low [<50] vs. high [≥50]), moderate to vigorous PA (MVPA) and step count via Fitbit Charge 2™, and weight via smart scale. We report adjusted linear regression coefficients (b) with standard errors (SE). The analysis included participants who were primarily white, female, and with obesity. In adjusted models, neighborhood walkability did not moderate the effect of treatment assignment on log-transformed (ln) MVPA or steps count over 12 months. The SM + FB group had greater lnMVPA than the SM group, but lnMVPA and steps were similar between walkability groups. There were no significant interactions for group and time or group, time, and walkability. These findings suggest that adding FB to SM had a small but significant positive impact on PA over 12 months, but neighborhood walkability did not moderate the treatment effect of FB on PA. [ABSTRACT FROM AUTHOR]

Cardiovascular disease risk factor control as primary prevention in patients with type 2 diabetes mellitus has changed substantially in the past few years. The purpose of this scientific statement is to review the current literature and key clinical trials pertaining to blood pressure and blood glucose control, cholesterol management, aspirin therapy, and lifestyle modification. We present a synthesis of the recent literature, new guidelines, and clinical targets, including screening for kidney and subclinical cardiovascular disease for the contemporary management of patients with type 2 diabetes mellitus.

Background. The Mobility and Vitality Lifestyle Program (MOVE UP) is a behavioral weight-management intervention for improving mobility among community-dwelling older adults. We examined program factors that affect implementation outcomes and participant-level health outcomes. Methods. The MOVE UP program was implemented in the greater Pittsburgh area from January 2015 to June 2019 to improve lower extremity performance in community-dwelling older adults who were overweight or obese. Thirty-two sessions were delivered over 13 months. All sessions were designed to be 1-hour in length, on-site, group-based, and led by trained and supported community health workers (CHWs). Participants completed weekly Lifestyle Logs for self-monitoring of body weight, diet, and physical activity. We evaluated the MOVE UP program using the RE-AIM framework, and collected quantitative data at baseline, 5-, 9-, and 13-months. Multilevel linear regression models assessed the impacts of program factors (site, CHW, and participant characteristics) on implementation outcomes and participant-level health outcomes. Results. Twenty-two CHWs delivered MOVE UP program to 303 participants in 26 cohorts. Participants were similar to the target source population in weight but differed in some demographic characteristics. The program was effective for weight loss and lower extremity function in both intervention and maintenance periods (p s <.01), with an independent effect for Lifestyle Logs submission but not session attendance. Discussion. CHWs were able to deliver a multi-component weight loss intervention effectively in community settings. CHW and site characteristics had independent impacts on participants' adherence. Lifestyle Log submission may be a more potent measure of adherence in weight loss interventions than attendance. [ABSTRACT FROM AUTHOR]

The diet quality of US adults is poor and cross-sectional analyses suggest self-perception of healthful dietary intake may be overestimated. This analysis assessed the concordance between calculated and perceived diet quality and changes in diet quality among adults seeking weight loss and enrolled in a 12-month randomized behavioral trial. Healthy Eating Index-2015 diet quality (HEI) was calculated from self-administered 24-hour recalls. Perceived diet quality (PDQ) was measured on a 100-point scale. Higher scores indicate better diet quality. Concordance was assessed using the concordance correlation coefficient and Bland-Altman plots. The one hundred and five participants with complete dietary data were mostly female and white. There was good agreement between HEI and PDQ scores at 12 months for less than a third of participants. Most of the disagreement arose from PDQ scores being higher than HEI scores. Even fewer participants had good agreement between HEI changes and PDQ changes. Participants perceived greater improvement in diet quality than indicated by HEI score changes. Concordance was low at 12 months and for change in diet quality. Despite the diet quality of adults seeking weight loss being suboptimal and not improving, many perceived their diet quality and diet quality improvements as better than calculated. Future studies might explore the effect of misperceptions on weight loss outcomes. [ABSTRACT FROM AUTHOR]

African American (AA) churches are valuable partners in implementing health promotion programming (HPP) to combat health disparities. The study purpose was to evaluate AA church characteristics associated with enrollment into the FAITH! (Fostering African American Improvement in Total Health) Trial, a community-based, cluster randomized controlled trial (RCT) of a mobile health intervention for cardiovascular health promotion among AA churches. Churches located in Minneapolis-St. Paul and Rochester, Minnesota were invited to complete an electronic screening survey and follow-up telephone interview including the PREACH (Predicting Readiness to Engage African American Churches in Health) tool to assess church characteristics and infrastructure for HPP. The primary outcome was church enrollment in the FAITH! Trial. Key predictors included overall PREACH scores and its subscales (Personnel, Physical Structure, Faith-based Approach, Funding), congregation size, and mean congregation member age. Of the 26 churches screened, 16 (61.5%) enrolled in the trial. The enrolled churches had higher overall mean PREACH scores (36.1 vs. 30.2) and subscales for Personnel (8.8 vs. 5.6), Faith-based Approach (11.0 vs. 9.6), and Funding (7.3 vs. 4.8) compared with non-enrolled churches; all differences were not statistically significant due to small sample size. Twelve (75.0%) of the enrolled churches had >75 members versus six (60.0%) of the non-enrolled churches. Twelve (80.0%) of the enrolled churches had an average congregation member age ≤54 years versus six (67.0%) of the non-enrolled churches. AA churches enrolling into a community-based RCT reported greater infrastructure for HPP, larger congregations, and members of younger age. These characteristics may be helpful to consider among researchers partnering with AA churches for HPP studies. [ABSTRACT FROM AUTHOR]