Faculty Bibliography

This study explores a novel, mixed qualitative method to deconstruct the diet of second-generation South Asian Americans (SAAs). Online interviews of 32 second-generation SAAs were conducted usingintegrated free-listing and mind-mapping. Ranked free-lists were aggregated to identify salient drivers, while connections made within mind-maps were analyzed using social network analysis (SNA) methods. Overall, 34 distinct drivers and 247 unique connections were identified. Taste, family, and health had the highest adjusted rankings, while health displayed the strongest network centrality. Interventions aimed at second-generation SAA dietary behaviors may benefit from family-based or multi-level interventions, which consider the complex, unique dietary norms identified.

Endowing meta-analytic results with a causal interpretation is challenging when there are differences in the distribution of effect modifiers among the populations underlying the included trials and the target population where the results of the meta-analysis will be applied. Recent work on transportability methods has described identifiability conditions under which the collection of randomized trials in a meta-analysis can be used to draw causal inferences about the target population. When the conditions hold, the methods enable estimation of causal quantities such as the average treatment effect and conditional average treatment effect in target populations that differ from the populations underlying the trial samples. The methods also facilitate comparison of treatments not directly compared in a head-to-head trial and assessment of comparative effectiveness within subgroups of the target population. We briefly describe these methods and present a worked example using individual participant data from three HIV prevention trials among adolescents in mental health care. We describe practical challenges in defining the target population, obtaining individual participant data from included trials and a sample of the target population, and addressing systematic missing data across datasets. When fully realized, methods for causally interpretable meta-analysis can provide decision-makers valid estimates of how treatments will work in target populations of substantive interest as well as in subgroups of these populations.

BACKGROUND:There is elevated prevalence of problem drinking among Russian women living with HIV and HCV co-infection. This paper describes the development and cultural adaptation of a multi-component alcohol reduction intervention incorporating a brief, computer-delivered module for Russian women living with HIV and HCV co-infection. METHODS:The format and content of the intervention were adapted to be linguistic-, cultural-, and gender-appropriate using the ADAPT-ITT framework. A computer-delivered module and brief clinician-delivered individual and telephone sessions were developed. RESULTS:We describe the theoretical foundations of the intervention, the cultural adaptation of the intervention, and overview the content of the intervention's multiple components. DISCUSSION:Interventions to reduce alcohol use that can be integrated within Russian HIV treatment centers are urgently needed. If efficacious, the culturally-adapted intervention offers the promise of a cost-effective, easily disseminated intervention approach for Russian women living with HIV/HCV co-infection engaging in problematic alcohol use.

INTRODUCTION/BACKGROUND:The COVID-19 pandemic has resulted in social isolation and reports of insomnia. However, reports of changes in sleep duration and associated factors are few. METHODS:Data were from an online survey of adults recruited via social media that included a question asking whether the respondent slept less or more after the onset of the pandemic. Analyses determined the association between changes in sleep duration and self reported sociodemographic and occupational information; beliefs about COVID-19; changes in sleep patterns; and responses pertaining to loneliness, anxiety, and depression. RESULTS:4.1-6.7) for sleeping less and anxiety. CONCLUSIONS:Changes in sleep duration since the start of the COVID-19 pandemic were highly prevalent among social media users and were associated with several sociodemographic factors and beliefs that COVID-19 would have adverse personal impacts. However, the strongest associations occurred with worse mental health suggesting that improvements may occur with better sleep.

There is a growing need to better capture comprehensive, nuanced, and multi-faceted qualitative data while also better engaging with participants in data collection, especially in virtual environments. This study describes the development of a novel 3-step approach to virtual mind-mapping that involves (1) ranked free-listing, (2) respondent-driven mind-mapping, and (3) interviewing to enhance both data collection and analysis of complex health behaviors. The method was employed in 32 virtual interviews as part of a study on eating behaviors among second-generation South Asian Americans. Participants noted the mind-mapping experience to be (1) helpful for visual learners, (2) helpful in elucidating new ideas and to structure thoughts, as well as (3) novel and interesting. They also noted some suggestions that included improving interpretability of visual data and avoiding repetition of certain discussion points. Data collection revealed the adaptability of the method, and the power of mind-maps to guide targeted, comprehensive discussions with participants.

BACKGROUND:In the United States, approximately 11% of households were food insecure prior to the COVID-19 pandemic. The present study aims to describe the prevalence of food insecurity among adults and households with children living in the United States during the pandemic. METHODS:This study utilized social media as a recruitment platform to administer an original online survey on demographics and COVID-related food insecurity. The survey was disseminated through an advertisement campaign on Facebook and affiliated platforms. Food insecurity was assessed with a validated six-item United States Department of Agriculture (USDA) Household Food Security Survey Module, which was used to create a six-point numerical food security score, where a higher score indicates lower food security. Individual-level participant demographic information was also collected. Logistic regressions (low/very-low compared with high/marginal food security) were performed to generate adjusted odds ratios (AOR) and 95%CIs for food insecurity and select demographic characteristics. RESULTS:Advertisements reached 250,701 individuals and resulted in 5,606 complete surveys. Overall, 14.7% of participants self-identified as having low or very low food security in their households, with higher prevalence (17.5%) among households with children. Unemployment (AOR:1.76, 95%CI:1.09-2.80), high school or lower education (AOR:2.25, 95%CI:1.29-3.90), and low income (AOR[$30,000-$50,000]:5.87, 95%CI:3.35-10.37; AOR[< $30,000]:10.61, 95%CI:5.50-20.80) were associated with higher odds of food insecurity in multivariable models among households with children (and the whole sample). CONCLUSIONS:These data indicate exacerbation of food insecurity during the pandemic. The study will be instrumental in guiding additional research and time-sensitive interventions targeted towards vulnerable food insecure subgroups.

South Asian immigrants confront a growing non-communicable disease burden, a significant issue in countries such as the USA. While efforts have slowly begun to address South Asian migrant health, second-generation communities remain underserved and understudied despite facing many of the same non-communicable disease concerns. The aim of this commentary is to highlight unique health disparities contributing to the current South Asian migrant health status and identify pathways for further formative research needed to inform subsequent development, implementation, and evaluation of health interventions targeting this community. Extant peer-reviewed literature addressing second-generation South Asian health issues was used to identify key research pathways needed to address existing gaps. Specifically, we call for (a) enhancing targeted surveillance and recruitment in research and (b) collecting data to help characterize behavioral and cultural patterns that may contribute to disease onset and progression. Expanding research on second-generation South Asian migrant health may help to develop tailored and targeted interventions.

Aim/UNASSIGNED:Given the need for data to inform public health messaging to mitigate the COVID-19 pandemic, this national survey sought to assess the state of COVID-19-related knowledge, beliefs, mental health, substance use changes, and behaviors among a sample of U.S. adults. Subject and methods/UNASSIGNED:In the period March 20-30, 2020, we collected data on COVID-19-related knowledge, awareness and adoption of preventive practices, depression and anxiety (Patient Health Questionnaire-4), stress (Impact of Event Scale-6), pessimism, and tobacco and alcohol use. Differences between age groups (18-39 years, 40-59 years and ≥ 60 years) were tested using Pearson's chi-squared tests or ANOVAs; associations between drinking and smoking and depression, anxiety, and stress were tested using adjusted logistic regression models. Results/UNASSIGNED: < 0.001) and smoking (AOR = 1.75; 95% CI = 1.31, 2.33). Conclusions/UNASSIGNED:In spite of high knowledge levels, important gaps were identified. High prevalence of poor mental health outcomes and associated increases in drinking and smoking warrant ongoing risk communications tailoring to effectively disseminate information and expanding psychosocial services, particularly via telehealth, to mitigate the negative mental health impact of COVID-19. Supplementary Information/UNASSIGNED:The online version contains supplementary material available at 10.1007/s10389-021-01564-4.