Faculty Bibliography

BACKGROUND:While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS:We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS:In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS:Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

IMPORTANCE/UNASSIGNED:Financial incentives for weight management may increase use of evidence-based strategies while addressing obesity-related economic disparities in low-income populations. OBJECTIVE/UNASSIGNED:To examine the effects of 2 financial incentive strategies developed using behavioral economic theory when added to provision of weight management resources. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:Three-group, randomized clinical trial conducted from November 2017 to May 2021 at 3 hospital-based clinics in New York City, New York, and Los Angeles, California. A total of 1280 adults with obesity living in low-income neighborhoods were invited to participate, and 668 were enrolled. INTERVENTIONS/UNASSIGNED:Participants were randomly assigned to goal-directed incentives, outcome-based incentives, or a resources-only group. The resources-only group participants were given a 1-year commercial weight-loss program membership, self-monitoring tools (digital scale, food journal, and physical activity monitor), health education, and monthly one-on-one check-in visits. The goal-directed group included resources and linked financial incentives to evidence-based weight-loss behaviors. The outcome-based arm included resources and linked financial incentives to percentage of weight loss. Participants in the incentive groups could earn up to $750. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Proportion of patients achieving 5% or greater weight loss at 6 months. RESULTS/UNASSIGNED:The mean (SD) age of the 668 participants enrolled was 47.7 (12.4) years; 541 (81.0%) were women, 485 (72.6%) were Hispanic, and 99 (14.8%) were Black. The mean (SD) weight at enrollment was 98.96 (20.54) kg, and the mean body mass index (calculated as weight in kilograms divided by height in meters squared) was 37.95 (6.55). At 6 months, the adjusted proportion of patients who lost at least 5% of baseline weight was 22.1% in the resources-only group, 39.0% in the goal-directed group, and 49.1% in the outcome-based incentive group (difference, 10.08 percentage points [95% CI, 1.31-18.85] for outcome based vs goal directed; difference, 27.03 percentage points [95% CI, 18.20-35.86] and 16.95 percentage points [95% CI, 8.18-25.72] for outcome based or goal directed vs resources only, respectively). However, mean percentage of weight loss was similar in the incentive arms. Mean earned incentives was $440.44 in the goal-directed group and $303.56 in the outcome-based group, but incentives did not improve financial well-being. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this randomized clinical trial, outcome-based and goal-directed financial incentives were similarly effective, and both strategies were more effective than providing resources only for clinically significant weight loss in low-income populations with obesity. Future studies should evaluate cost-effectiveness and long-term outcomes. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT03157713.

OBJECTIVE/BACKGROUND/OBJECTIVE:To examine the impact of prostate cancer (PCa) on sleep health for patients and caregivers. We hypothesized that sleep disturbances and poor sleep quality would be prevalent among patients with PCa and their caregivers. PATIENTS/METHODS/METHODS:A systematic literature search was conducted according to the Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines. To be eligible for this systematic review, studies had to include: (1) patients diagnosed with PCa and/or their caregivers; and (2) objective or subjective data on sleep. 2431 articles were identified from the search. After duplicates were removed, 1577 abstracts were screened for eligibility, and 315 underwent full-text review. RESULTS AND CONCLUSIONS/CONCLUSIONS:Overall, 83 articles met inclusion criteria and were included in the qualitative synthesis. The majority of papers included patients with PCa (98%), who varied widely in their treatment stage. Only 3 studies reported on sleep among caregivers of patients with PCa. Most studies were designed to address a different issue and examined sleep as a secondary endpoint. Commonly used instruments included the Insomnia Severity Index and European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaires (EORTC-QLQ). Overall, patients with PCa reported a variety of sleep issues, including insomnia and general sleep difficulties. Both physical and psychological barriers to sleep are reported in this population. There was common use of hypnotic medications, yet few studies of behavioral interventions to improve sleep for patients with PCa or their caregivers. Many different sleep issues are reported by patients with PCa and caregivers with diverse sleep measurement methods and surveys. Future research may develop consensus on validated sleep assessment tools for use in PCa clinical care and research to promote facilitate comparison of sleep across PCa treatment stages. Also, future research is needed on behavioral interventions to improve sleep among this population.

Despite the popularity of commercially available wearable activity monitors (WAMs), there is a paucity of consistent methodology for analyzing large amounts of accelerometer data from these devices. This multimethod study aimed to inform appropriate Fitbit wear thresholds for physical activity (PA) outcomes assessment in a sample of 616 low-income, majority Latina patients with obesity enrolled in a behavioral weight-loss intervention. Secondly, this study aimed to understand intervention participants' barriers to Fitbit use. We applied a heart rate (HR) criterion (≥10 h/day) and a step count (SC) criterion (≥1000 steps/day) to 100 days of continuous activity monitor data. We examined the prevalence of valid wear and PA outcomes between analytic subgroups of participants who met the HR criterion, SC criterion, or both. We undertook qualitative analysis of research staff notes and participant interviews to explore barriers to valid Fitbit data collection. Overall, one in three participants did not meet the SC criterion for valid wear in Weeks 1 and 13; however, we found the SC criterion to be more inclusive of participants who did not use a smartphone than the HR criterion. Older age, higher body mass index (BMI), barriers to smartphone use, device storage issues, and negative emotional responses to WAM-based self-monitoring may predict higher proportions of invalid WAM data in weight-loss intervention research.

Objectives/UNASSIGNED:The aim of this study was to test the mediating role of perceived discrimination and stress on associations between perceived neighborhood social environment (PNSE) and TV viewing. Methods/UNASSIGNED:Baseline data were used for 4716 participants (mean age = 55.1 y; 63.4% female) in the Jackson Heart Study (JHS), a large prospective cohort study of African Americans in Jackson, Mississippi. One binary TV viewing outcome was created: ≥4 h/day versus <4 h/day. PNSE variables included neighborhood violence, problems (higher value = more violence/problems), and social cohesion (higher value = more cohesion). Mediators included perceived lifetime discrimination, daily discrimination, and chronic stress (higher value = greater discrimination/stress). Multivariable regression was used with bootstrap-generated 95% bias-corrected confidence intervals (BC CIs) to test for mediation adjusting for demographics, health-related and psychosocial factors, and population density. Results/UNASSIGNED: = 1.01, 1.10, respectively). Daily discrimination was neither directly nor indirectly associated with TV viewing. Conclusions/UNASSIGNED:Each PNSE variable was indirectly associated with TV viewing via lifetime discrimination and perceived stress, but not with daily discrimination among JHS participants. Unexpected directionality of mediating effects of lifetime discrimination and chronic stress should be replicated in future studies. Further research is also needed to pinpoint effective community efforts and physical environmental policies (e.g., installing bright street lights, community policing) to reduce adverse neighborhood conditions and psychosocial factors, and decrease TV viewing and subsequent cardiovascular disease risk.

INTRODUCTION/BACKGROUND:). Clinical guidelines recommend multicomponent lifestyle programmes to promote modest, clinically significant body mass (BM) loss. Primary care providers (PCPs) often lack time to counsel and refer patients to intensive programmes (≥6 sessions over 3 months). Using peer coaches to deliver obesity counselling in primary care may increase patient motivation, promote behavioural change and address the specific needs of veterans. We describe the rationale and design of a cluster-randomised controlled trial to test the efficacy of the Peer-Assisted Lifestyle (PAL) intervention compared with enhanced usual care (EUC) to improve BM loss, clinical and behavioural outcomes (aim 1); identify BM-loss predictors (aim 2); and increase PCP counselling (aim 3). METHODS AND ANALYSIS/UNASSIGNED:We are recruiting 461 veterans aged 18-69 years with obesity or overweight with an obesity-associated condition under the care of a PCP at the Brooklyn campus of the Veterans Affairs NY Harbor Healthcare System. To deliver counselling, PAL uses in-person and telephone-based peer support, a tablet-delivered goal-setting tool and PCP training. Patients in the EUC arm receive non-tailored healthy living handouts. In-person data collection occurs at baseline, month 6 and month 12 for patients in both arms. Repeated measures modelling based on mixed models will compare mean BM loss (primary outcome) between study arms. ETHICS AND DISSEMINATION/UNASSIGNED:The protocol has been approved by the Institutional Review Board and the Research and Development Committee at the VA NY Harbor Health Systems (#01607). We will disseminate the results via peer-reviewed publications, conference presentations and meetings with stakeholders. TRIAL REGISTRATION NUMBER/BACKGROUND:NCT03163264; Pre-results.