COVID-19 Knowledge and Prevention Behaviors in Rural Zambia: A Qualitative Application of the Information-Motivation-Behavioral Skills Model

Abstract

ABSTRACT. In early 2020, the Zambian Ministry of Health instituted prevention guidelines to limit spread of COVID-19. We assessed community knowledge, motivations, behavioral skills, and perceived community adherence to prevention behaviors (i.e., hand hygiene, mask wearing, social distancing, and limiting gatherings). Within a cluster-randomized controlled trial in four rural districts, in November 2020 and May 2021, we conducted in-depth interviews with health center staff (N = 19) and community-based volunteers (N = 34) and focus group discussions with community members (N = 281). A content analysis was conducted in Nvivo v12. Data were interpreted using the Information-Motivation-Behavioral Skills Model. Generally, respondents showed good knowledge of COVID-19 symptoms, spread, and high-risk activities, with some gaps. Prevention behavior performance was driven by personal and social factors. Respondents described institutional settings (e.g., clinics and church) having higher levels of perceived adherence due to stronger enforcement measures and clear leadership. Conversely, informal community settings (e.g., weddings, funerals, football matches) lacked similar social and leadership expectations for adherence and had lower perceived levels of adherence. These settings often involved higher emotions (excitement or grief), and many involved alcohol use, resulting in community members “forgetting” guidelines. Doubt about disease existence or need for precautions persisted among some community members and drove non-adherence more generally. Although COVID-19 information successfully penetrated these very remote rural communities, more targeted messaging may address persistent COVID-19 doubt and misinformation. Engaging local leaders in religious, civic, and traditional leadership positions could improve community behaviors without adding additional monitoring duties on an already overburdened, resource-limited health system.