Early public health strategies to prevent the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the virus responsible for the coronavirus disease 2019 (COVID-19) in the United States primarily included non-pharmaceutical interventions (NPIs), as vaccines and therapeutic treatments were not yet available. Implementation of NPIs, primarily social distancing and mask-wearing, varied widely between communities within the U.S. due to variable government mandates, as well as differences in attitudes and opinions.
Though the type, timing, and duration of the orders varied greatly between jurisdictions, all of these public health orders called for behavioral changes and restrictions on personal movement, gatherings, and business activity.
Study: Effects of trust, risk perception, and health behavior on COVID-19 disease burden: Evidence from a multi-state US survey. Image Credit: r.classen / Shutterstock.com
Human behavior and response to these NPIs is the best way to assess their effectiveness.. Voluntary compliance with public health guidance and orders is affected by demographic factors, cognitive constructs, and social constructs. Health behavior theory and risk behavior models characterize the demographic factors related to risk perception and health-protective behaviors.
The basic understanding of viruses including the comprehension that they pose a serious threat and that individuals are susceptible to this threat is the most likely predictor of adoption and compliance with NPIs. Other cognitive constructs, like perceived severity, perceived susceptibility, and belief in the benefits of adopted behaviors are all associated with reduced COVID-19 risk behaviors and increased health-protective behaviors.
Another key in mapping the efficiency of NPIs and planning for further courses are influences from neighbors, friends, relatives, and extended families. Polarized political identity, in particular, is one factor that can lead to out-group distrust. Socio-economic barriers and age are also crucial in determining the perceived risks and impacts of viruses and affect the adoption of NPIs.
Studies have consistently shown less compliance with NPIs in rural areas, particularly among rural Americans identifying as conservative. However, these associations were less strong among older rural individuals. The lack of healthcare resources due to hospital closures, limited numbers of health professionals, and low critical-care capacity in rural communities pose additional risks in the face of a surge of patients with COVID-19.
In a recent study published on the preprint server medRxiv*, researchers analyze three socially and demographically diverse U.S. states including Idaho, Texas, and Vermont between October and November 2020 regarding the differences among rural and urban Americans in their attitudes towards, and the uptake of, NPIs. To advance health behavior theory, they tested various causal relationships between trust in public health guidance, health and economic risk perception, and resistance to pandemic behavioral changes using structural equation modeling.
Data for this research came from a sequential mixed-mode survey distributed to a disproportionate stratified sample of households in Idaho, Texas, and Vermont. The specific survey design, which employed both an online and a paper survey option, as well as English and Spanish translations, was selected. This type of approach was geared towards reaching communities that are typically harder to reach through purely online surveys including rural and elderly populations, individuals who lacked access to reliable internet connections, and non-English speakers.
The demographic variables were comprised of direct measures of five attributes. Political ideology was coded as an unordered factor with levels including liberal, moderate, conservative, libertarian, non-political, and others; moderate was designated as the reference level for statistical analyses. The remaining measures were recorded as Boolean variables measuring race (white = 1), gender (female = 1), age (over 64 years = 1), and geography (rural = 1)
A total of 1,034 responses were used to analyze whether these relationships were significantly different in rural populations. The best-fitting structural equation models showed that trust indirectly affected protective pandemic behaviors through both health and economic risk perceptions.
The researchers explored two different variations of this social cognitive model. The first assumed behavioral intention affects future disease burden, while the second assumed that observed disease burden affects behavioral intention. Political ideology was the only exogenous variable that significantly affected all aspects of the social cognitive model that including trust, risk perception, and behavioral intention.
While there is a direct negative effect associated with rurality on disease burden, likely due to the protective effect of low population density in the early pandemic waves, the researchers found a marginally significant, positive, and indirect effect of rurality on disease burden through decreased trust (p = 0.095). This trust deficit creates additional vulnerabilities to COVID-19 in rural communities that also have reduced healthcare capacity. Increasing trust by methods such as in-group messaging could potentially remove some of the disparities inferred by these models and increase NPI effectiveness.
Population surveys like the one utilized in the current study provide information on the cause(s) of non-adherence to any prevailing norm or intervention. Furthermore, such surveys can be vastly useful in planning and implementing better methods to ensure adherence, and in such cases, reduce the number of cases in a novel viral pandemic.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.