The languages of public health are complex and often politicized, making it difficult for public health practitioners to craft effective health messaging, build trust, and navigate funding opportunities. In the current climate—characterized by partisan politics, misinformation, skepticism, and heightened disparities, all intensified by the COVID-19 crisis—these tasks are particularly daunting. Moreover, the integration of artificial intelligence (AI) has precipitated changes in the public health vocabulary with growing concerns of algorithmic bias and data quality limitations. Given the potential to be either unifying or polarizing, the languages of public health matter as we seek to (re)build trust and advance public health.
Language shapes our world, how we speak, and how we think. Language often works unconsciously in the background of our minds, and it is a lens through which we see, interpret, and act in the world. As such, it also shapes health-seeking behaviors and policy (http://bit.ly/46cK42G). Differences in social position (e.g., being privileged or marginalized), as well as political lean, also shape language and worldviews across physical, social, and even digital spaces. Different understandings of technical terms can also lead to alarm and distrust, such as when the general US public interpreted epidemiological “surveillance” as a loss of privacy (https://bit.ly/46ed5Lj). Epidemiologists use this word in a specific way that is different from the colloquial meaning. Even if both epidemiologists and the general public are speaking in a common language (e.g., English), one’s background knowledge and life experiences are fundamental to making different associations and interpretations. In many ways, it may feel like another language altogether.
The language of public health consists of evolving terms to describe theoretical constructs, populations, organizations, therapies, and diseases. These terms are often driven by science, culture, geography, politics, history, and technology. We routinely use terms in our field that might seem intuitive yet miss the step of translating technical jargon into plain language. For example, at the peak of the COVID-19 pandemic, technical terms like “herd immunity” and “comorbidity” rapidly entered the public vernacular; however, the average person may not interpret these terms as they were intended in the field. Additionally, the term “herd” might be lost in translation, whereby the literal interpretation might lead people to think they were being compared with animals. On the other hand, a misguided attempt to oversimplify a nuanced topic may lead the audience to misinterpret the key message or inadvertently mischaracterize a subpopulation with potentially stigmatizing narratives. This lack of clear communication can result in a wide array of problems, from poor adherence to public health guidelines to the spread of misinformation. Furthermore, ineffective public health messaging intensifies stress, stigma, and cognitive bias, whereas a well-crafted public health message considers the audience while framing issues for action (https://bit.ly/47cajrc).
Accessible and inclusive language is required when considering the diverse health needs of populations and communities. Alarming disparities and trends associated with chronic conditions, mortality, and life expectancy all signal a need for equitable access to patient-centered care. Black, Indigenous, and People of Color; members of the lesbian, gay, bisexual, transgender, and questioning community; and people with disabilities are impacted by persistent systemic inequities and injustices that contribute to feelings of mistrust in health care systems. For those addressing health inequities and trust deficits, the delivery of socially and culturally appropriate care is strengthened with inclusive language and steps to mitigate health literacy or language barriers.
For those assessing and addressing disparities at the population level, data equity practices using equitable language reduce the risk of contributing to harmful narratives or perpetuating disinformation around health disparities. However, in scenarios where discourse exists because of political climate, it can be daunting to harmoniously navigate phrases that are agreeable with both politics and best practices. The navigation of evolving, polarizing, stigmatizing, or confusing terms is an ongoing exercise for those working to (re)build trust and advance health. However, the use of deliberative language in public health (https://bit.ly/49wT45n) and evolution of natural language processing in artificial intelligence (https://bit.ly/3MHLISY) are examples of how language can be leveraged in the pursuit of more equitable and healthier nation.
A cyclical relationship exists between bias and public health languages, and this is well demonstrated in policy. Often the use of culturally appropriate terms is considered “politically correct;” ironically, the terms favored in policy may not actually be the best choice of words to describe a concept or population. In late 2017, the US Centers for Disease Control and Prevention received instruction not to use seven words in its 2019 budget appropriation request: diversity, transgender, vulnerable, fetus, entitlement, evidence-based, and science-based (https://bit.ly/3QWVjHQ). After this request, many public health officials resisted this perceived attempt at censorship and effort to dehumanize marginalized populations. The potential exclusion of these seven words in the budget appropriation might have had serious funding and ethical implications.
The interconnected nature of public health and language has implications in our collective effort to advance health in the United States and on an international scale. Our research and practice are strengthened by our ability to effectively communicate and connect with our audience. By placing importance on the languages of public health, we are well-positioned to (re)build trust and serve the very public we aim to protect.
10. Years Ago
Ethical Issues in Conducting Research With Deaf Populations
[C]ultural naïvetë and lack of language fluency create a host of barriers and ethical dilemmas for many health researchers who work with minority, underserved, and vulnerable populations. Collaborating with underrepresented communities requires researchers to demonstrate creativity, mutual respect, flexibility, compassion, cultural competency, and patience in their work. . . . Few health researchers understand the cultural values held by the Deaf community or even know ASL [American Sign Language]. The lack of linguistic and cultural concordance places the population at high risk for poor research engagement and inaccessible informed-consent processes and research materials. This perpetuates a long-standing history of fear, mistrust, and frustration of deaf ASL users with biomedical researchers and their research studies.
From AJPH, December 2013, p. 2174
13. Years Ago
Community-Based Participatory Research to Improve Health Equity
[T]he third challenge [for translational research] is language, which includes incompatible discourse between the academy and the community, and the power of naming, which encompasses such commonly used terms as “institutionalization” or “collaborators.” These terms can unwittingly trigger resistance and historical memories of assimilationist policies or betrayal. . . . The use of language is closely tied to knowledge dominance, with [community-based participatory research] advocating changes in research discourse—that is, from “research subject” to “research participant,” or from “targeting community members” to “engaging community partners.” Ongoing dialogue with partners about discourse specific to local values remains critical; for example, the language of “institutionalizing” programs can bring up historical trauma from government, schools, or academic institutions that have caused damage in communities of color.
From AJPH, Supplement 1, 2010, p. S40
Biography
