Science Communication and Misinformation
Misconceptions about science
For a layperson with lower health literacy or a non-scientific background, principles of research can be challenging to understand. Furthermore, with various sources from the Internet and its virtual forums, takeaways that reach the public through the media can be misleading. The next section addresses some common misconceptions that patients might have about science--for example, that masks cause illness--and suggestions on how to frame a response that is grounded in fundamental principles of the scientific method.
Q: Is science just an opinion?
A: Good science comes from well-defined research questions that arrive at objective facts, while opinions are beliefs or feelings that cannot be proven through the scientific method. However, as humans, researchers can have biases because of past experiences, assumptions, and goals. To minimize the effects of human bias, scientific research needs to be well-designed, which can involve double blinding (where neither researchers nor participants know who received experimental treatment) and randomization (the chance assignment of intervention or placebo). It is important to note, however, that the media can present biased interpretations of scientific facts and outcomes. Thus, it is helpful to read the scientific literature itself, known as the primary source.
Q: Why does scientific understanding seem to constantly evolve?
A: Knowledge is generated through iterations of the scientific method, which involves asking the right questions, using appropriate and robust methods, conducting detailed analyses, and publishing studies that can be reproduced. Thus, science is self-improving: it continuously changes and expands, and additional insights, different contexts, or new ways to analyze information can suggest new conclusions. Also, not all current practices in medicine are based on the highest levels of evidence (e.g. randomized controlled trials and meta-analyses), so more robust and recent research can challenge previously held assumptions that were made through expert consensus. This does not detract from the impact of scientific research. Rather, scientists work to get closer to the truth behind real-life phenomena.
Q: Why do different scientific models for COVID-19 produce such different predictions?
A: The results of models that try to forecast future COVID cases, hospitalizations, and deaths are often offered without context about underlying assumptions that are necessary to build them. For example, take the epidemiological models that suggest widely varying case and death numbers despite extrapolating from similar datasets. Even small variations in R0 or the percentage of community members adhering to physical distancing policies, can vastly affect model outcomes. Additionally, the farther into the future the model forecasts, the greater the degree of uncertainty and wider the range of inaccuracy. Finally, real-life responses to models, such as the implementation of social distancing policies or opening of economies, can cause a divergence from a model’s predictions--as the baseline assumptions have now changed.
Communicating data
Comprehending, interpreting, and communicating primary science literature can be overwhelming due to unfamiliar terms involving test statistics (e.g. sensitivity/specificity, positive/negative predictive values) and results (e.g. odds ratio, risk reductions). In this section, we offer suggestions on how to most effectively communicate about data.
Ask yourself if specific numbers might be helpful. In general, use numbers sparingly. If you are trying to motivate behavioral change or convey risk, a relative rather than absolute sense of scale may be sufficient. However, they may be helpful for concepts that require precision or when you are prompted for details.
Ask your patient if data would be helpful. Perhaps more importantly, consider your patient’s perspective. Based on your experience with them, are they an individual who is interested in interpreting the data, or do they prefer if you summarized? Oftentimes, you can directly ask about their style if you are not sure--it can help you discern how much and how best to convey data to them.
Avoid statistical jargon. Preferentially use qualitative descriptors, as they are more intuitive than fractions, statistics, and percentages. These descriptors can include terms such as “equally as likely” or “double as likely” to compare rates. In addition, describing probability as “one in four” rather than 25% is likely to be more informative. Try to translate test characteristics into more intuitive meaning--for instance, describe 60% sensitivity as a test that will have nearly as many false negatives (40%) as true positives (60%) and thus has a poor ability to accurately detect positive cases. Utilize analogies and comparisons to commonplace situations when applicable.
Use intuitive visual aids. Pie charts can help effectively illustrate fractions and line graphs can easily demonstrate trends, such as COVID-19 cases or deaths. However, if using illustrations from outside sources, try to assess whether it is based on robust data.
Navigating misinformation with patients
With patients increasingly spending time on the Internet and connecting with others through social media, they may receive medical information through not just traditional sources such as doctors but also from peers and online platforms. These technologies undoubtedly have positive effects, such as offering support networks for patients and providing more information to patients. But online platforms for knowledge can also be dangerous. When opinion pieces masquerade as fact, or when authors outright claim authority to “facts” that are in reality sown from prejudice or bias, the Internet can disseminate and propagate misinformation that can be harmful to medicine and society.
Misinformation has proliferated during the pandemic, ranging from unfounded statements about the origins of COVID-19 to spurious links between 5G and COVID-19. In this section on navigating misinformation, our aim is not to make you an expert on how to dismantle every false belief, but rather to provide communication tools that build off previously described frameworks to speak with patients about misinformation. Thus, we want to address: how do you, as a trainee or clinician, communicate effectively with someone whose beliefs about COVID-19 may be grounded in false information? How might you navigate gulfs between a wide scientific consensus and an individual’s beliefs? To illustrate this, we have included a table below on another divisive issue: childhood vaccinations, an area that taps into similar fears and concerns that patients may have.
Conversations on COVID vaccines
Vaccine hesitancy is a complex issue. Rampant misinformation, the novelty of these medications, and polarized discourse have all contributed to reluctance towards vaccine uptake. Longstanding medical racism is also inextricably linked with potential skepticism for BIPOC communities that have suffered disproportionately from COVID-19. From a medical perspective though, mass vaccination efforts sufficient to reach herd immunity are critical for addressing the pandemic. These differing perspectives have inevitably led to tensions and disagreement between healthcare providers and patients. However, while the vaccines themselves may be novel, many of the same principles previously covered in this module are relevant in such conversations with patients.
First, it is important to have the “facts” conversation. As in any disagreement, when speaking with a patient who holds a belief that diverges from general scientific understanding, it is important to explore the patient’s perspective. For example, where are they getting their information from? What evidence or principles are they using to support their conclusions? A patient who says that they do not wish to wear a mask in most settings could potentially expand on concerns about hypercapnia that they have seen in videos.
Intricately connected to the facts is the “feelings” conversation. Rather than making assumptions about patients’ intentions, we should consider probing those experiences. Also, by exploring our patients’ perspectives, we may be able to better manage our own initial emotions, evoke empathy, and have a more balanced, productive conversation that allows them to feel heard. The above patient with concerns about masks may come in expecting to be judged or not feel heard for harboring that view.
Finally, the “identity” conversation further explores patient priorities, and is key for creating common ground. As a provider, reflect on what deeper values or identities the patient holds. In the case of the patient who is reluctant to wear masks, anchoring recommendations on shared territory, such as concern for vulnerable family members or neighbors in the setting of COVID-19, may be more effective than listing specific numbers from recent studies.
From this framework of recognizing conversations on facts, feelings, and identity, healthcare providers can better validate and empathize with patient concerns while also providing clear recommendations and evidence for them. While this section focuses on communication with our patients, the strategies discussed also apply to other people in our life. As medical students, we will frequently field questions from friends and family that may seem uninformed or ignorant. We have a responsibility to probe further and address these misconceptions.
A strategy by which to structure this conversation is CASE. The steps are as follows:
Lastly, remember that while the goal is to help align a patient’s understanding with the greater scientific community’s consensus, the expectation is not necessarily to be able to change patients’ mind about a particular therapeutic that has been discredited or the value of wearing masks within the course of a single clinical interaction. Rather, it is important to continue to build and maintain the patient-physician relationship by making space for perspectives to be mutually heard.
Thought question:
Say that a patient you are seeing via telehealth makes a comment that masks don’t work and that social distancing measures are overblown. How might you respond?
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