Re-Framing the Digital Divide during COVID-19: A Study of Bhutanese Refugees in the U.S

Background: Pervasive social and structural inequities in the United States (U.S.) have propagated health disparities experienced by underserved populations, especially immigrants and refugees. During COVID-19, health-related disparities were further exacerbated by the physical gap that separates populations from access to digital services including the internet, referred to as “digital divide” and limited digital literacy among underserved immigrant and refugee communities. While the rapid expansion of telehealth and tele-mental health services in the U.S. helped contain COVID-19 during the pandemic, telehealth-services disproportionately impacted immigrants and refugees with limited access to digital technologies. Focusing on the Bhutanese refugee population, our study aimed to examine the correlates between sociocultural and sociodemographic factors, access to internet, utilization of telehealth services and COVID-19 information seeking behavior.

Methods: This study is a part of a larger mixed-methods research project conducted between July 2021 and January 2022 using a community based participatory research (CBPR) approach that assessed the digital divide to bridge gap in digital technology access and utilization among Bhutanese refugee population in a mid-western U.S. region. Our study was guided by digital health equity for refugee well-being and inclusion framework based on the overarching concepts of social determinants of health and access to digital technology model.

Quantitative data was collected through a cross-sectional community survey (N=495) administered using in-person (59.2%) and web-based (40.8%) mediums using convenience and respondent-driven sampling methods. Data analysis followed a multinominal logistic regression (MNLR) for each outcome (telehealth, tele-counseling and COVID-19 information seeking) using a block entry approach. Block 1 included education as a predictor; Block 2 added sociocultural variables (years of arrival in the U.S, use of traditional healer, English language comprehension, and spoken English proficiency); Block 3 added sociodemographic variables (sex and age), and finally Block 4 added SES/socioenvironmental factors (annual household income and internet use at home).

Results: Findings showed that most participants had daily access to internet at home (85.98%); had at least high school and above education (65.0%); and had an annual income below $50,000 (76.20%). Telehealth service utilization rates were low, where 72.7% of the participants never used telehealth services, including digital mental health services. We found increased odds of telehealth use based on educational attainment, English language comprehension, and higher income. Frequently seeking COVID-19 information was found to have increased odds with high school education (AOR:6.8 [95%CI:1.7-26.8]) and some college and higher education degree (AOR:16.8 [95%CI:3.4-83.9]) when compared to no formal education or less than high school education.

Conclusion: Efforts to increase digital literacy in underserved communities must go beyond physical access and connectivity and consider the role of cultural factors. Understanding the history of the inequalities that compound and complicate the digital divide is critical to the development of programs and tools that will support marginalized populations, and in particular, marginalized populations as they define access to health-related information around unanticipated events and crises. We argue for the reframing of the understanding of digital divide beyond access to internet to deeper social, structural, and psychological inequities behind the inequality of access.