Culture change and lessons learned from ten years in the VA centers of excellence in primary care education.

BACKGROUND: Team-based care is critical to achieving health care value while maximizing patient outcomes. Few descriptions exist of graduate-level team training interventions and practice models. Experience from the multisite, decade-long Veterans Affairs (VA) Centers of Excellence in Primary Care Education provides lessons for developing internal medicine training experiences in interprofessional clinical learning environments. METHODS: A review of multisite demonstration project transforming traditional silo-model training to interprofessional team-based primary care. Using iterative quality improvement approaches, sites evaluated curricula with learner, faculty and staff feedback. Learner- and patient-level outcomes and organizational culture change were examined using mixed methods, within and across sites. Participants included more than 1600 internal medicine, nurse practitioner, nursing, pharmacy, psychology, social work and physical therapy trainees. This took place in seven academic university-affiliated VA primary care clinics with patient centered medical home design RESULTS: Each site developed innovative design and curricula using common competencies of shared decision making, sustained relationships, performance improvement and interprofessional collaboration. Educational strategies included integrated didactics, workplace collaboration and reflection. Sites shared implementation best practices and outcomes. Cross-site evaluations of the impacts of these educational strategies indicated improvements in trainee clinical knowledge, team-based approaches to care and interest in primary care careers. Improved patient outcomes were seen in the quality of chronic disease management, reduction in polypharmacy, and reduced emergency department and hospitalizations. Evaluations of the culture of training environments demonstrated incorporation and persistence of interprofessional learning and collaboration. CONCLUSIONS: Aligning education and practice goals with cross-site collaboration created a robust interprofessional learning environment. Improved trainee/staff satisfaction and better patient care metrics supports use of this model to transform ambulatory care training. TRIAL REGISTRATION: This evaluation was categorized as an operation improvement activity by the Office of Academic Affairs based on Veterans Health Administration Handbook 1058.05, in which information generated is used for business operations and quality improvement (Title 38 Code of Federal Regulations Part 16 (38 CFR 16.102(l)). The overall project was subject to administrative oversight rather Human Subjects Institutional Review Board, as such informed consent was waived as part of the project implementation and evaluation.

Proxy use of patient portals on behalf of children: Federally Qualified Health Centers as a case study.

Objective: This study examined the proxy use of patient portals for children in a large Federally Qualified Health Centers (FQHC) network in Texas. Methods: We used de-identified individual-level data of patients, 0-18 years, who had 1+ visits between December 2018 and November 2020. Logistic regression was used to examine patient-, clinic-, and geographic-level factors associated with portal usage by an assumed proxy (i.e. parent or guardian). Results: The proxy portal usage rate increased from 28% in the pre-pandemic months (November 2018-February 2020) to 34% in the pandemic months (March-Nov 2020). Compared to patients 0-5 years, patients aged 6 to 18 years had lower odds of portal usage (6-10 OR: 0.77, p < 0.001; 11-14 OR: 0.62, p < 0.001; 15-18 OR: 0.51, p < 0.001). Minoritized groups had significantly lower odds of portal usage when compared to their non-Hispanic White counterparts (non-Hispanic Black OR: 0.78, p < 0.001; Hispanic OR 0.63, p < 0.001; Asian OR: 0.69, p < 0.001). Having one chronic condition was associated with portal usage (OR: 1.57, p < 0.001); however, there were no significant differences in portal usage between those with none or multiple chronic conditions. Portal usage also varied by service lines, with obstetrics and gynecology (OR: 1.84, p < 0.001) and behavioral health (OR 1.82, p < 0.001) having the highest odds of usage when compared to pediatrics. Having a telemedicine visit was the strongest predictor of portal usage (OR: 2.30, p < 0.001), while residence in zip codes with poor broadband internet access was associated with lower odds of portal usage (OR: 0.97, p < 0.001). Conclusion: While others have reported portal usage rates as high as 64% in pediatric settings, our analysis suggests proxy portal usage rates of 30% in pediatric FQHC settings, with race/ethnicity, age group, and chronic disease status being significant drivers of portal non-usage. These findings highlight the need for appropriate and responsive health information technology approaches for vulnerable populations receiving care in low-resource settings.

Ascertainment of Minimal Clinically Important Differences in the Diabetes Distress Scale-17: A Secondary Analysis of a Randomized Clinical Trial.

Importance: The Diabetes Distress Scale-17 (DDS-17) is a common measure of diabetes distress. Despite its popularity, there are no agreed-on minimal clinically important difference (MCID) values for the DDS-17. Objective: To establish a distribution-based metric for MCID in the DDS-17 and its 4 subscale scores (interpersonal distress, physician distress, regimen distress, and emotional distress). Design, Setting, and Participants: This secondary analysis of a randomized clinical trial used baseline and postintervention data from a hybrid (implementation-effectiveness) trial evaluating Empowering Patients in Chronic Care (EPICC) vs an enhanced form of usual care (EUC). Participants included adults with uncontrolled type 2 diabetes (glycated hemoglobin A1c [HbA1c] level >8.0%) who received primary care during the prior year in participating Department of Veterans Affairs clinics across Illinois, Indiana, and Texas. Data collection was completed in November 2018, and data analysis was completed in June 2023. Interventions: Participants in EPICC attended 6 group sessions led by health care professionals based on collaborative goal-setting theory. EUC included diabetes education. Main Outcomes and Measures: The main outcome was distribution-based MCID values for the total DDS-17 and 4 DDS-17 subscales, calculated using the standard error of measurement. Baseline to postintervention changes in DDS-17 and its 4 subscale scores were grouped into 3 categories: improved, no change, and worsened. Multilevel logistic and linear regression models examined associations between treatment group and MCID change categories and whether improvement in HbA1c varied in association with MCID category. Results: A total of 248 individuals with complete DDS-17 data were included (mean [SD] age, 67.4 [8.3] years; 235 [94.76%] men), with 123 participants in the EPICC group and 125 participants in the EUC group. The MCID value for DDS-17 was 0.25 and MCID values for the 4 distress subscales were 0.38 for emotional and interpersonal distress and 0.39 for physician and regimen distress. Compared with EUC, more EPICC participants were in the MCID improvement category on DDS-17 (63 participants [51.22%] vs 40 participants [32.00%]; P = .003) and fewer EPICC participants were in the worsened category (20 participants [16.26%] vs 39 participants [31.20%]; P = .008). There was no direct association of DDS-17 MCID improvement (ß = -0.25; 95% CI, -0.59 to 0.10; P = .17) or worsening (ß = 0.18; 95% CI, -0.22 to 0.59; P = .38) with HbA1c levels among all participants. Conclusions and Relevance: In this secondary analysis of data from a randomized clinical trial, an MCID improvement or worsening of more than 0.25 on the DDS-17 was quantitatively significant and patients in the EPICC group were more likely to experience improvement than those in the EUC group. Trial Registration: ClinicalTrials.gov Identifier: NCT01876485.

Evaluating Predictors of Participation in Telephone-Based Social-Connectedness Interventions for Older Adults: A Dual Machine-Learning and Regression Approach.

Social isolation is a well-documented contributor to poor mental and physical health, and interventions promoting social connectedness have been associated with various health benefits. This study examined predictors of participation in a telephone-based social connectedness intervention for socially isolated older adults. Data were obtained from a social-connectedness intervention that paired college students with Houston-area, community-dwelling adults aged 65 years and older and enrolled in Medicare Advantage plans. We combined machine learning and regression techniques to identify significant predictors of program participation. The following machine-learning methods were implemented: (1) k-nearest neighbors, (2) decision tree and ensembles of decision trees, (3) gradient-boosted decision tree, and (4) random forest. The primary outcome was a binary flag indicating participation in the telephone-based social-connectedness intervention. The most predictive variables in the ML models, with scores corresponding to the 90th percentile or greater, were included in the regression analysis. The predictive ability of each model showed high discriminative power, with test accuracies greater than 95%. Our findings suggest that telephone-based social-connectedness interventions appeal to individuals with disabilities, depression, arthritis, and higher risk scores. scores. Recognizing features that predict participation in social-connectedness programs is the first step to increasing reach and fostering patient engagement.

The Effects of COVID-19 Lockdown on Social Connectedness and Psychological Distress in U.S. Adults with Chronic Diseases.

Lockdown measures enacted in 2020 to control the spread of COVID-19 led to increases in the prevalence of mental health problems. Due to their high-risk status, individuals with chronic diseases may be at increased risk and disproportionately adversely affected by the COVID-19 pandemic. The investigators examined associations between having a high-risk chronic condition, social connectedness, and general distress and COVID-19-specific distress among U.S. adults during the COVID-19 lockdown. Baseline measures of a longitudinal survey collected at the beginning of the pandemic (April to June 2020) were analyzed to identify factors associated with loss of social connectedness from pre- to post-lockdown. The associations between social connectedness and both general and COVID-19-specific psychological distress were adjusted for certain high-risk chronic illnesses and interaction effects. The sample available for analysis included 1354 subjects (262 high-risk chronic diseases and 1092 without chronic illness). Those reporting the loss of social connectedness were younger (median = 39 vs. 42) and more likely to be unemployed because of the pandemic (19.4% vs. 11.0%). Adjustment for interaction demonstrated a stronger negative association between social connectedness change and the psychosocial impact of COVID-19 for those with high-risk illness(es) (change in connectedness*chronic illness OR = 0.88, 95%CI: 0.79-0.98, p = 0.020). These findings inform our understanding of the distribution and intersection of responses to public health lockdown orders in the U.S. and build further evidence of the importance of social connectedness on psychological distress.

Rethinking access to care: A spatial-economic analysis of the potential impact of pharmacy closures in the United States.

Data chronicling the geo-locations of all 61,589 pharmacies in the U.S. (from the Homeland Infrastructure Foundation-Level Data (HIFLD) Open Data interface, updated on April 2018) across 215,836 census block groups were combined with Medically Underserved Areas (MUAs) information, and the Centers for Disease Control and Prevention's Social Vulnerability Index (CDC-SVI). Geospatial techniques were applied to calculate the distance between the center of each census block and the nearest pharmacy. We then modeled the expected additional travel distance if the nearest pharmacy to the center of a census block closed and estimated additional travel costs, CO2 emissions, and lost labor productivity costs associated with the additional travel. Our findings revealed that MUA residents have almost two times greater travel distances to pharmacies than non-MUAs (4,269 m (2.65 mi) vs. 2,388 m (1.48 mi)), and this disparity is exaggerated with pharmacy closures (107% increase in travel distance in MUAs vs. 75% increase in travel distance in non-MUAs). Similarly, individuals living in MUAs experience significantly greater average annual economic costs than non-MUAs ($34,834 ± $668 vs. $22,720 ± $326). Our findings suggest the need for additional regulations to ensure populations are not disproportionately affected by these closures and that there is a significant throughput with community stakeholders before any pharmacy decides to close.

Examining Black and Hispanic physicians and other healthcare providers' attitudes toward the COVID-19 vaccine.

OBJECTIVES: Recognizing that the voice delivering the message is as important as the information being shared, we examined vaccine perceptions and willingness to encourage patients to obtain COVID-19 vaccinations among Black and Hispanic healthcare providers. METHODS: We conducted a cross-sectional, online survey of Black and Hispanic healthcare providers who were members of the National Medical Association (NMA), National Hispanic Medical Association (NHMA), and National Pharmaceutical Association (NPhA) between January 11 - March 3, 2021, shortly after emergency use authorization (EUA) for the Pfizer and Moderna COVID-19 vaccines. Three multivariable logistic regression models were used to determine factors associated with the willingness to encourage COVID-19 vaccination. RESULTS: The analytic sample consisted of 542 fully completed surveys. Pharmacists reported intent to take the vaccine (75.0% "as soon as you can" vs 91.4% for MD/DOs; p<0.001) and encouraged patients to get vaccinated (78.6% vs 91.0% for MD/DOs; p = 0.01). Providers in a suburban practice location were less likely to recommend vaccines to patients (OR=0.43, 95%CI: 0.22-0.87) and personal family (OR=0.45, 95%CI: 0.22-0.92) compared to those practicing in urban areas. Providers over age 45 were also more likely to report intent to take the vaccine themselves as soon as it was available (OR=3.72, 95%CI: 1.30-10.64). CONCLUSIONS: This is likely the first cross-sectional study in the United States demonstrating the substantial vaccine confidence among Black and Hispanic healthcare providers who serve minoritized communities that have borne the greatest risk of adverse COVID-related outcomes.

Engaging the Houston Community in Research: An Early Case Study of a Community Engagement Core in the University of Houston's HEALTH Center for Addictions Research and Cancer Prevention.

Objective: The National Institute on Minority Health and Health Disparities-funded U54 Research Center at the University of Houston addresses disparate racial/ethnic health outcomes related to cancer and substance abuse. Of its 4 cores, the Community Engagement Core involves the impacted community in affiliated research. Strategies include implementing community advisory boards, assisting with study design and execution, maintaining a social media presence, and publishing health-related videos for the community. We examine the early effectiveness of these strategies. Methods: Data collection included surveying investigators and community advisory board members and monitoring traffic to videos and social media posts. Results: On a Likert scale survey of investigators (4 = "agree" and 5 = "strongly agree"), the mean rating for a prompt expressing satisfaction with services received was 4.67 (SD = 0.52; N = 6). On a Likert scale survey of community advisory board members, the mean rating for a prompt expressing belief that feedback was taken seriously was 5.00 (SD = 0.00; N = 9). Conclusions: The Community Engagement Core is building trusting relationships between researchers and community members. We discuss lessons learned that may inform both our growth and others' efforts to implement community-engaged research.

Assessment of Unmet Health-Related Social Needs Among Patients With Mental Illness Enrolled in Medicare Advantage.

Importance: A large body of literature has found associations between unmet health-related social needs (HRSNs) and adverse mental health outcomes. A comparative analysis of the risks associated with HRSNs among patients with varying severity of mental illness and an assessment of how these risks compare with those of individuals without mental illness are needed. Objective: To examine the prevalence and risks of HRSNs among patients with serious and persistent mental illness (SPMI), patients with mental health diagnoses but no serious and persistent mental illness (non-SPMI), and patients with both SPMI and non-SPMI compared with individuals without mental illness. Design, Setting, and Participants: This retrospective cohort study used data from the Accountable Health Communities HRSN Screening Tool surveys, which target a nationally representative sample of Medicare Advantage members of a large payer (Humana Inc). The surveys were conducted between October 16, 2019, and February 29, 2020. Of the initial 329 008 eligible Medicare Advantage enrollees, 70 273 responded to the survey (21.4% response rate). Of those, 56 081 respondents (79.8%) had complete survey responses and were included in the final analytic sample. Main Outcomes and Measures: Outcomes of interest included 7 HRSNs (financial strain, food insecurity, housing instability, housing quality, severe loneliness, transportation problems, and utility affordability) based on responses to the survey. The major independent variable was the presence of mental illness up to 12 months preceding the date of survey completion. Codes indicating mental illness listed as the primary, principal, or secondary diagnoses of a patient's inpatient or outpatient medical claims data were identified, and participants were grouped into 4 cohorts: SPMI, non-SPMI, SPMI plus non-SPMI, and no mental illness. Results: Among 56 081 older adults, the mean (SD) age was 71.31 (8.59) years; 32 717 participants (58.3%) were female, and 43 498 (77.6%) were White. A total of 21 644 participants (38.6%) had at least 1 mental illness diagnosis in the past year, 30 262 (54.0%) had an HRSN, and 14 163 (25.3%) had both mental illness and an HRSN. Across all specific HRSNs, the odds of experiencing the respective HRSN was most substantial for those with SPMI plus non-SPMI vs those with only non-SPMI or SPMI. The HRSN with the largest risk differences among the study cohorts was severe loneliness; compared with the cohort without mental illness, the non-SPMI cohort had 2.07 times higher odds (95% CI, 1.84-2.32; P < .001), the SPMI cohort had 3.35 times higher odds (95% CI, 3.03-3.71; P < .001), and the SPMI plus non-SPMI cohort had 5.13 times higher odds (95% CI, 4.68-5.61; P < .001) of severe loneliness. Conclusions and Relevance: In this study, the increased risk of having HRSNs associated with SPMI, alone or in combination with non-SPMI, emphasizes the need for more targeted interventions to address social needs in this vulnerable population.

Evaluating a contact tracing course: How universities can develop the public health workforce.

OBJECTIVES: To describe the participants of a university-based COVID-19 contact tracing course and determine whether the course changed knowledge, attitudes, and intention to participate in contact tracing. PARTICIPANTS: Faculty, staff, and students were eligible. METHODS: Surveys evaluated the impact of the course on participant intentions to engage in contact tracing. Logistic regression identified characteristics associated with increased likelihood of participating in contact tracing. RESULTS: Nearly 800 individuals participated, of whom 26.2% identified as Hispanic/Latino and 14.0% as Black. Nearly half (48.8%) planned to conduct contact tracing. While attitudes did not change, knowledge improved (67.9% vs. 93.8% scores on assessments; p < 0.001). Younger participants and Black individuals were more more likely to be confident that they would participate in contact tracing. CONCLUSIONS: Course completion was associated with increased knowledge. Participants were racially and ethnically diverse, highlighting how universities can partner with health departments to develop workforces that reflect local communities.

Comparison of Collaborative Goal Setting With Enhanced Education for Managing Diabetes-Associated Distress and Hemoglobin A1c Levels: A Randomized Clinical Trial.

Importance: Type 2 diabetes is a prevalent and morbid condition. Poor engagement with self-management can contribute to diabetes-associated distress and hinder diabetes control. Objective: To evaluate the implementation and effectiveness of Empowering Patients in Chronic Care (EPICC), an evidence-based intervention to improve diabetes-associated distress and hemoglobin A1c (HbA1c) levels after the intervention and after 6-month maintenance. Design, Setting, and Participants: This hybrid (implementation-effectiveness) randomized clinical trial was performed in Veterans Affairs clinics across Illinois, Indiana, and Texas from July 1, 2015, to June 30, 2017. Participants included adults with uncontrolled type 2 diabetes (HbA1c level >8.0%) who received primary care during the prior year in participating clinics. Data collection was completed on November 30, 2018, and data analysis was completed on June 30, 2020. All analyses were based on intention to treat. Interventions: Participants in EPICC attended 6 group sessions based on a collaborative goal-setting theory led by health care professionals. Clinicians conducted individual motivational interviewing sessions after each group. Usual care was enhanced (EUC) with diabetes education. Main Outcomes and Measures: The primary outcome consisted of changes in HbA1c levels after the intervention and during maintenance. Secondary outcomes included the Diabetes Distress Scale (DDS), Morisky Medication Adherence Scale, and Lorig Self-efficacy Scale. Secondary implementation outcomes included reach, adoption, and implementation (number of sessions attended per patient). Results: A total of 280 participants with type 2 diabetes (mean [SD] age, 67.2 [8.4] years; 264 men [94.3]; 134 non-Hispanic White individuals [47.9%]) were equally randomized to EPICC or EUC. Participants receiving EPICC had significant postintervention improvements in HbA1c levels (F1, 252 = 9.12, Cohen d = 0.36 [95% CI, 0.12-0.59]; P = .003) and DDS (F1, 245 = 9.06, Cohen d = 0.37 [95% CI, 0.13-0.60]; P = .003) compared with EUC. During maintenance, differences between the EUC and EPICC groups remained significant for DDS score (F1, 245 = 8.94, Cohen d = 0.36 [95% CI, 0.12-0.59]; P = .003) but not for HbA1c levels (F1, 252 = 0.29, Cohen d = 0.06 [95% CI, -0.17 to 0.30]; P = .60). Improvements in DDS scores were modest. There were no differences between EPICC and EUC in improvements after intervention or maintenance for either adherence or self-efficacy. Among all 4002 eligible patients, 280 (7.0%) enrolled in the study (reach). Each clinic conducted all planned EPICC sessions and cohorts (100% adoption). The EPICC group participants attended a mean (SD) of 4.34 (1.98) sessions, with 54 (38.6%) receiving all 6 sessions. Conclusions and Relevance: A patient-empowerment approach using longitudinal collaborative goal setting and motivational interviewing is feasible in primary care. Improvements in HbA1c levels after the intervention were not sustained after maintenance. Modest improvements in diabetes-associated distress after the intervention were sustained after maintenance. Innovations to expand reach (eg, telemedicine-enabled shared appointments) and sustainability are needed. Trial Registration: ClinicalTrials.gov Identifier: NCT01876485.

Examining longitudinal disparities in COVID-19 prevalence in the U.S.: a county level growth rate perspective.

Background: The objectives of the present study are to understand the longitudinal variability in COVID-19 reported cases at the county level and to associate the observed rates of infection with the adoption and lifting of stay-home orders.Materials and Methods: The study uses the trajectory of the pandemic in a county and controls for social and economic risk factors, physical environment, and health behaviors to elucidate the social determinants contributing to the observed rates of infection.Results and conclusion: Results indicated that counties with higher percentages of young individuals, racial and ethnic minorities and, higher population densities experienced greater difficulty suppressing transmission.Except for Education and the Gini Index, all factors were influential on the rate of COVID-19 spread before and after stay-home orders. However, after lifting the orders, six of the factors were not influential on the rate of spread; these included: African-Americans, Population Density, Single Parent Households, Average Daily PM2.5, HIV Prevalence Rate, and Home Ownership. It was concluded that different factors from the ones controlling the initial spread of COVID-19 are at play after stay-home orders are lifted.KEY MESSAGESObserved rates of COVID-19 infection at the County level in the U.S. are not directly associated with adoption and lifting of stay-home orders.Disadvantages in sociodemographic determinants negatively influence the rate of COVID-19 spread.Counties with more young individuals, racial and ethnic minorities, and higher population densities have greater difficulty suppressing transmission.

Leveraging Public-Private Partnerships During COVID-19: Providing Virtual Field Opportunities for Student Learners and Addressing Social Isolation in Older Adults.

While preventive and management measures are important to mitigate the spread of COVID-19, strategies like social distancing can have devastating effects on older adults who are already at risk for social isolation and loneliness. In response, two Colleges of Health Professions (Social Work and Nursing) at a large public University leveraged a partnership with a national health and wellbeing company to address social isolation and loneliness in Houston area older adults during the COVID-19 pandemic. This intergenerational linkage initiative involved 707 older adults and 177 graduate social work and nursing students. This study describes the process of developing a virtual educational opportunity for students while also meeting the needs of vulnerable older adults in Houston, the third largest, and one of the most diverse cities in the U.S. Findings include student/learner outcomes, as well as self-reported improvements in loneliness scores, and unhealthy physical and mental health days among enrolled older adults.

An evidence-based, structured, expert approach to selecting essential indicators of primary care quality.

BACKGROUND: The purpose of this article is to illustrate the application of an evidence-based, structured performance measurement methodology to identify, prioritize, and (when appropriate) generate new measures of health care quality, using primary care as a case example. Primary health care is central to the health care system and health of the American public; thus, ensuring high quality is essential. Due to its complexity, ensuring high-quality primary care requires measurement frameworks that can assess the quality of the infrastructure, workforce configurations, and processes available. This paper describes the use of the Productivity Measurement and Enhancement System (ProMES) to compile a targeted set of such measures, prioritized according to their contribution and value to primary care. METHODS: We adapted ProMES to select and rank existing primary care measures according to value to the primary care clinic. Nine subject matter experts (SMEs) consisting of clinicians, hospital leaders and national policymakers participated in facilitated expert elicitation sessions to identify objectives of performance, corresponding measures, and priority rankings. RESULTS: The SMEs identified three fundamental objectives: access, patient-health care team partnerships, and technical quality. The SMEs also selected sixteen performance indicators from the 44 pre-vetted, currently existing measures from three different data sources for primary care. One indicator, Team 2-Day Post Discharge Contact Ratio, was selected as an indicator of both team partnerships and technical quality. Indicators were prioritized according to value using the contingency functions developed by the SMEs. CONCLUSION: Our article provides an actionable guide to applying ProMES, which can be adapted to the needs of various industries, including measure selection and modification from existing data sources, and proposing new measures. Future work should address both logistical considerations (e.g., data capture, common data/programming language) and lingering measurement challenges, such as operationalizating measures to be meaningful and interpretable across health care settings.

Correlates of Social Isolation Among Community-Dwelling Older Adults During the COVID-19 Pandemic.

Background: The past year has severely curtailed social interactions among older adults given their high rates of COVID-19 morbidity and mortality. This study examined social, behavioral, and medical correlates of social isolation among community-dwelling older adults during the COVID-19 pandemic and stratified findings to explore unique differences in two typically neglected populations, African American and Hispanic older adults. Methods: Working with community-based organizations and senior living centers, the research team administered a survey to older adults 55 years of age and older (n = 575). The survey assessed COVID-19 prevention behaviors, medical conditions, and lived experiences, including feelings of social isolation, in the target population. Responses to a previously validated social isolation question informed a dichotomous social isolation dependent variable. Multivariable logistic regression was used to adjust for sociodemographic characteristics, medical conditions, unmet caregiving needs, and COVID-19 prevention behaviors. Results from the regression model were stratified by race/ethnicity to examine correlates of social isolation in African American and Hispanic older adults, separately. Results: Overall, female sex and a higher level of education were also positively associated with social isolation (OR = 2.46, p = 0.04; OR = 5.49, p = 0.02) while having insurance exhibited an inverse relationship (OR = 0.25, p = 0.03). Unmet caregiving needs were strongly associated with social isolation (OR = 6.41, p < 0.001) as was having any chronic conditions (OR = 2.99, p = 0.02). Diabetes was the single strongest chronic condition predictor of social isolation. Among minority older adults, a different pattern emerged. For Hispanic older adults, language, unmet caregiving needs, and social distancing were strongly associated with social isolation; while unmet caregiving needs, having 1+ chronic conditions and adhering to social distancing guidelines were significant predictors in African American older adults. Conclusion: These findings suggest that social isolation affects older adults in a myriad of ways and support the need for culturally sensitive initiatives to mitigate the effect of social isolation in these vulnerable populations.

Overcoming COVID-19 Vaccine Hesitancy: Insights from an Online Population-Based Survey in the United States.

This study sought to identify individual-level determinants of COVID-19 vaccine hesitancy based on the Health Belief Model (HBM) and Theory of Planned Behavior (TPB). An online population-based survey was distributed in English and Spanish. Data were derived from 1208 U.S. adults (52% female; 38.7% minorities), 43.5% of whom reported vaccine hesitancy. Multivariable analysis revealed that unemployed individuals were more likely (OR = 1.78, 95% CI: 1.16-2.73, p = 0.009) and married (OR = 0.57, 95% CI: 0.39-0.81, p = 0.002) and higher income individuals (OR = 0.52, 95% CI 0.32-0.84, p = 0.008) were less likely to be hesitant. Individuals with greater perceived susceptibility to COVID-19 (OR = 0.82, 95% CI: 0.71-0.94, p = 0.006), who perceived vaccination as being convenient (OR = 0.86, 95% CI: 0.74-1.00, p = 0.047), and who afforded greater importance to cues to action from government (OR = 0.84, 95% CI: 0.74-0.95, p = 0.005), public health (OR = 0.70, 95% CI: 0.59-0.82, p < 0.001), and healthcare experts (OR = 0.59, 95% CI: 0.50-0.69, p < 0.001) were also less likely to be hesitant. Findings suggest that HBM and TPB constructs may be useful in informing strategies to improve COVID-19 vaccine uptake. Specifically, framing appeals based on perceptions of COVID-19 susceptibility, making vaccination convenient, and rebuilding trust through unified cues to action may help to overcome vaccine hesitancy.

Sociodemographic and Health Belief Model Factors Associated with Nonadherence to COVID-19 Mitigation Strategies in the United States.

BACKGROUND AND PURPOSE: Virus mitigation strategies such as adhering to stay-at-home orders, practicing social distancing, and engaging in personal protective behaviors are central to slowing the spread of COVID-19. This population-based cohort study sought to identify sociodemographic characteristics and Health Belief Model factors that are associated with nonadherence to COVID-19 mitigation strategies with the goal of informing public health messaging campaigns. METHODS: An online population-based survey was distributed via social media over an 8-week period from April 13, 2020, to June 8, 2020. RESULTS: Data were derived from 2,222 adults (57% female; 40% racial/ethnic minorities). Univariate analyses revealed that men, younger aged (18-30 years) and unmarried adults, and noncollege educated individuals had lower levels of perceived threat, control, and knowledge about COVID-19 (p ≤ .001). Multivariable linear regression models further revealed that male gender was significantly associated with reporting lower levels of adherence to COVID-19 mitigation strategies (p < .001), and that higher levels of perceived threat, perceived control, and knowledge about how to keep oneself and others safe from COVID-19 were significantly associated with reporting higher levels of adherence to COVID-19 mitigation strategies (p < .01). CONCLUSIONS: Findings suggest that public health appeals that target men, emphasize individual risk, and provide clear, consistent guidance on what individuals can do to decrease their risk for COVID-19 may be effective in motivating increased mitigation adherence.

Individual-Level Determinants of Lifestyle Behavioral Changes during COVID-19 Lockdown in the United States: Results of an Online Survey.

This study examined individual-level determinants of self-reported changes in healthy (diet and physical activity) and addictive (alcohol use, smoking, and vaping) lifestyle behaviors during the initial COVID-19 lockdown period in the USA. A national online survey was administered between May and June 2020 that targeted a representative U.S. sample and yielded data from 1276 respondents, including 58% male and 50% racial/ethnic minorities. We used univariate and multivariable linear regression models to examine the associations of sociodemographic, mental health, and behavioral determinants with self-reported changes in lifestyle behaviors. Some study participants reported increases in healthy lifestyle behaviors since the pandemic (i.e., 36% increased healthy eating behaviors, and 33% increased physical activity). However, they also reported increases in addictive lifestyle behaviors including alcohol use (40%), tobacco use (41%), and vaping (46%). With regard to individual-level determinants, individuals who reported adhering to social distancing guidelines were also more likely to report increases in healthy lifestyle behaviors (ß = 0.12, 95% CI 0.04 to 0.21). Conversely, women (ß = -0.37, 95% CI -0.62 to -0.12), and unemployed individuals (ß = -0.33, 95% CI -0.64 to -0.02) were less likely to report increases in healthy lifestyle behaviors. In addition, individuals reporting anxiety were more likely to report increases in addictive behaviors (ß = 0.26, 95% CI 0.09 to 0.43). Taken together, these findings suggest that women and unemployed individuals may benefit from interventions targeting diet and physical activity, and that individuals reporting anxiety may benefit from interventions targeting smoking and alcohol cessation to address lifestyle changes during the pandemic.