Cognitive and emotional factors related to COVID-19 among high-risk ethnically diverse adults at the onset of the New York City outbreak: A cross-sectional survey.

A cross-sectional survey was conducted among high-risk, racially/ethnically diverse adults at the point in time when New York City (NYC) became the COVID-19 pandemic's global epicenter. The study objective was to assess the threat and coping appraisals (cognitive factors known to correspond with people's willingness to adopt behaviorally focused interventions) and levels of distress, anxiety, and intolerance for uncertainty (emotional factors). Survey respondents were recruited in April 2020 using an online survey with unpaid recruitment on the GetHealthyHeights.org community-oriented website. We also recruited participants that engaged in previous research studies to gain survey responses from community members at higher risk for COVID-19 complications due to comorbidities compared to the general population. Analysis was performed to test for differences in survey responses by comorbidities, age, race, ethnicity, and employment status. Results show that the devastating effects of the pandemic appear to have uniquely impacted minority respondents, who reported significantly higher levels of anxiety and were significantly more likely to report having little control over whether they will get COVID-19 compared with White/non-Hispanic respondents. Minority respondents also had significantly higher mean scores on the behaviorally focused dimension of the intolerance of uncertainty (IU) scale, which measures avoidance and paralysis in the face of uncertainty. In multivariate analysis, IU predicted anxiety levels, and this association was not mediated by cognitive factors (threat and coping appraisals). By conducting this survey early in the pandemic, our study uniquely evaluated cognitive and emotional factors among a racially/ethnically diverse group of NYC residents during the height of the COVID-19 pandemic. Our findings suggest the need to acknowledge the disparities that appear to exist in pandemic response and for culturally tailored messaging and interventions. Few studies have reported differences by race and ethnicity during pandemic exposure. Therefore, further research on factors that may influence pandemic response among minority populations is needed.

A randomized controlled trial of generic and localized MedlinePlus-based information resources for hard-to-reach urban Hispanic community.

OBJECTIVE: To determine if the Conexion digital localized health information resource about diabetes and depression could increase patient activation among Hispanic low-income adults. MATERIALS AND METHODS: A nonblinded randomized controlled trial was conducted (NCT03984929). Participants at least 18 years old living in Washington Heights/Inwood, New York, were recruited from the community between July 2019 and August 2020 and randomized 1:1 to either the intervention group (localization of MedlinePlus resources customized with community components) or the control group (no localized community components). The primary outcome, patient activation, and secondary outcomes, knowledge, self-efficacy, and behavior change, were collected through surveys at 1-month follow-up. RESULTS: Of the 134 participants recruited, 50.7% (n = 68) completed the 1-month follow-up. We found no statistically significant differences in the sociodemographic and baseline characteristics between those who missed the 1-month survey and those who completed it. No significant differences were observed in patient activation at 1-month. However, patient activation among all participants (n = 68) significantly increased (P = .048). Statistically significant improvements were also found in self-efficacy (P < .03). In multivariate analysis, birth country outside the United States and higher self-rated attachment to the community emerged as significant predictors of higher patient activation scores. DISCUSSION: While the trial did not detect significant differences between groups, all participants demonstrated increased patient activation scores and improved secondary outcomes. While other factors may have contributed to this increase, our study suggests that access to carefully selected high-quality health information materials delivered digitally in the context of a community may result in improvements comparable to localized content in a hard-to-reach urban Hispanic population. CONCLUSIONS: Our study highlights the potential of making carefully selected digital information accessible to hard-to-reach communities.

Patient and Clinician Decision Support to Increase Genetic Counseling for Hereditary Breast and Ovarian Cancer Syndrome in Primary Care: A Cluster Randomized Clinical Trial.

Importance: To promote the identification of women carrying BRCA1/2 variants, the US Preventive Services Task Force recommends that primary care clinicians screen asymptomatic women for an increased risk of carrying a BRCA1/2 variant risk. Objective: To examine the effects of patient and clinician decision support about BRCA1/2 genetic testing compared with standard education alone. Design, Setting, and Participants: This clustered randomized clinical trial was conducted at an academic medical center including 67 clinicians (unit of randomization) and 187 patients. Patient eligibility criteria included women aged 21 to 75 years with no history of breast or ovarian cancer, no prior genetic counseling or testing for hereditary breast and ovarian cancer syndrome (HBOC), and meeting family history criteria for BRCA1/2 genetic testing. Interventions: RealRisks decision aid for patients and the Breast Cancer Risk Navigation Tool decision support for clinicians. Patients scheduled a visit with their clinician within 6 months of enrollment. Main Outcomes and Measures: The primary end point was genetic counseling uptake at 6 months. Secondary outcomes were genetic testing uptake at 6 and 24 months, decision-making measures (perceived breast cancer risk, breast cancer worry, genetic testing knowledge, decision conflict) based upon patient surveys administered at baseline, 1 month, postclinic visit, and 6 months. Results: From December 2018 to February 2020, 187 evaluable patients (101 in the intervention group, 86 in the control group) were enrolled (mean [SD] age: 40.7 [13.2] years; 88 Hispanic patients [46.6%]; 15 non-Hispanic Black patients [8.1%]; 72 non-Hispanic White patients [38.9%]; 35 patients [18.9%] with high school education or less) and 164 (87.8%) completed the trial. There was no significant difference in genetic counseling uptake at 6 months between the intervention group (20 patients [19.8%]) and control group (10 patients [11.6%]; difference, 8.2 percentage points; OR, 1.88 [95% CI, 0.82-4.30]; P = .14). Genetic testing uptake within 6 months was also statistically nonsignificant (13 patients [12.9%] in the intervention group vs 7 patients [8.1%] in the control group; P = .31). At 24 months, genetic testing uptake was 31 patients (30.7%) in intervention vs 18 patients (20.9%) in control (P = .14). Comparing decision-making measures between groups at baseline to 6 months, there were significant decreases in perceived breast cancer risk and in breast cancer worry (standard mean differences = -0.48 and -0.40, respectively). Conclusions and Relevance: This randomized clinical trial did not find a significant increase in genetic counseling uptake among patients who received patient and clinician decision support vs those who received standard education, although more than one-third of the ethnically diverse women enrolled in the intervention underwent genetic counseling. These findings suggest that the main advantage for these high-risk women is the ability to opt for screening and preventive services to decrease their cancer risk. Trial Registration: ClinicalTrials.gov Identifier: NCT03470402.

Extraction of Electronic Health Record Data using Fast Healthcare Interoperability Resources for Automated Breast Cancer Risk Assessment.

Women at high risk for breast cancer may benefit from enhanced screening and risk-reduction strategies. However, limited time during clinical encounters is one barrier to routine breast cancer risk assessment. We evaluated if electronic health record (EHR) data downloaded using Fast Healthcare Interoperability Resources (FHIR) is sufficient for breast cancer risk calculation in our decision support tools, RealRisks and BNAV. We accessed EHR data using FHIR for six patient advocates, and downloaded and parsed XML documents. We searched for relevant clinical variables, and evaluated if data was sufficient to calculate risk using validated models (Gail, Breast Cancer Screening Consortium [BCSC], BRCAPRO). While only one advocate had sufficient EHR data to calculate risk using the BCSC model only, we identified variables including age, race/ethnicity, mammographic density, and prior breast biopsy in most advocates. EHR data from FHIR could be incorporated into automated breast cancer risk calculation in clinical decision support tools.