Applying the Health Belief Model to Characterize Racial/Ethnic Differences in Digital Conversations Related to Depression Pre– and Mid–COVID-19 (Preprint)

Abstract

\n BACKGROUND\n The prevalence of depression symptoms in the United States is >3 times higher mid–COVID-19 versus pre-pandemic. Racial/ethnic differences in mindsets around depression and the potential impact of the COVID-19 pandemic are not well characterized.\n \n \n OBJECTIVE\n To describe attitudes, mindsets, key drivers, and barriers related to depression pre– and mid–COVID-19 by race/ethnicity using digital conversations about depression mapped to health belief model (HBM) concepts.\n \n \n METHODS\n Advanced search, data extraction, and AI-powered tools were used to harvest, mine, and structure open-source digital conversations of US adults who engaged in conversations about depression pre– (February 1, 2019-February 29, 2020) and mid–COVID-19 pandemic (March 1, 2020-November 1, 2020) across the internet. Natural language processing, text analytics, and social data mining were used to categorize conversations that included a self-identifier into racial/ethnic groups. Conversations were mapped to HBM concepts (ie, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy). Results are descriptive in nature.\n \n \n RESULTS\n Of 2.9 and 1.3 million relevant digital conversations pre– and mid–COVID-19, race/ethnicity was determined among 1.8 million (62%) and 979,000 (75%) conversations pre– and mid–COVID-19, respectively. Pre–COVID-19, 1.3 million conversations about depression occurred among non-Hispanic Whites (NHW), 227,200 among Black Americans (BA), 189,200 among Hispanics, and 86,800 among Asian Americans (AS). Mid–COVID-19, 736,100 conversations about depression occurred among NHW, 131,800 among BA, 78,300 among Hispanics, and 32,800 among AS. Conversations among all racial/ethnic groups had a negative tone, which increased pre– to mid–COVID-19; finding support from others was seen as a benefit among most groups. Hispanics had the highest rate of any racial/ethnic group of conversations showing an avoidant mindset toward their depression. Conversations related to external barriers to seeking treatment (eg, stigma, lack of support, and lack of resources) were generally more prevalent among Hispanics, BA, and AS than among NHW. Being able to benefit others and building a support system were key drivers to seeking help or treatment for all racial/ethnic groups.\n \n \n CONCLUSIONS\n Applying concepts of the HBM to data on digital conversation about depression allowed organization of the most frequent themes by race/ethnicity. Individuals of all groups came online to discuss their depression. There were considerable racial/ethnic differences in drivers and barriers to seeking help and treatment for depression pre– and mid–COVID-19. Generally, COVID-19 has made conversations about depression more negative, and with frequent discussions of barriers to seeking care. These data highlight opportunities for culturally competent and targeted approaches to address areas amenable to change that might impact the ability of people to ask for or receive mental health help, such as the constructs that comprise the HBM.\n