The U.S. Centers for Disease Control and Prevention (CDC) reportedly has plans to perform a large study on a “possible connection” between vaccines and autism—a topic of interest to Robert F. Kennedy Jr., Secretary of Health and Human Services, despite plenty of research showing no such connection exists.
During his Senate confirmation hearings, Kennedy was asked by Republican senator and physician Bill Cassidy about his views on vaccines and autism. “Will you reassure mothers unequivocally and without qualification that the measles and the hepatitis B vaccines do not cause autism?” Cassidy asked.
“If the data is there, I will absolutely do that,” Kennedy replied.
Of course, the data is there—in abundance. There is ample scientific evidence that vaccines do not cause autism. Yet Kennedy and those who discount this research claim that it is either flawed or insufficient to disprove a possible link. That raises the question: could more “data” change their minds?
If a lack of “good data” is truly driving people to avoid vaccines, it would be important to know, exactly, what new data could possibly change minds. Considering that most parents are probably not reading and appraising scientific studies themselves (either because they’re busy or because scientific studies are not really written for general audiences), this question is best asked to the high-profile vaccine skeptics in which some parents have placed their trust and whose opinions are taken seriously by millions of Americans.
Now, if high-profile vaccine skeptics were to lead their own study, it may be hard for the mainstream scientific community or most Americans to trust its results. Similarly, if experienced researchers who’ve previously advocated for vaccines were to conduct a new study, vaccine skeptics would likely dismiss the results as flawed, insufficient, or biased—as they have already for many existing studies.
Bias, or the perception of it, can paralyze the pursuit of scientific truth.
If the CDC embarks on its study of vaccines and autism, is there any way that its findings could be considered reliable by all?
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One strategy is an adversarial collaboration, a process pioneered by the late Nobel laureate in economics Daniel Kahneman. He popularized adversarial collaboration as an alternative to “angry science.” Simply put, adversarial collaboration is where those with opposing viewpoints perform research together to arrive at conclusions in a mutually agreeable way.
According to the University of Pennsylvania’s Adversarial Collaboration Project, the process is helpful when those with clashing views have “become entrenched” and research has “become politicized.”
Both sides must make three key commitments:
- They will both make good faith efforts to understand and fairly characterize the opposing viewpoint
- Before performing any research, they will work together to design a study and framework for interpretation—in advance—that both sides agree would have the potential to change their minds
- Both sides will stick to their pre-specified plan and publish the results together, regardless of the study’s outcomes.
Advocates of adversarial collaborations point to benefits like avoiding errors and oversights, putting a check on biases researchers may have, and advancing science faster than if opposing groups were to continue work in their respective silos. Specifying a plan up front and sticking to it—a method routinely used in the conduct of clinical trials—helps ensure analyses aren’t changed and results aren’t interpreted in a biased manner if one side isn’t happy with the study’s findings.
This has worked in the past. There are a number of examples of the method’s success when research has produced conflicting results, particularly in the field of behavioral science—such as research into how short term memory works, gender bias in academia, and even the link between happiness and income, when researchers who had separately published conflicting results teamed up to better hone the relationship between these two factors.
While performing a well-executed adversarial collaboration at the national level is easier said than done, if the National Institutes of Health and CDC want to perform additional research on vaccines and autism, there’s no reason the strategy couldn’t be applied—the stakes are certainly high enough. But both parties must take the process seriously and stick to their commitments. That means agreeing up front on what kinds of data will be collected, the specific methods that will be used to analyze the data, and what processes will be followed if disagreements in data interpretation occur. The end result—a study published by both vaccine skeptics and proponents—might just make for more productive public discourse surrounding vaccine policy.
If, however, advocates on either side of this issue aren’t willing to engage in an adversarial collaboration, it should call the seriousness of their concerns into question. If a vaccine skeptic says the current evidence is insufficient to prove vaccines are safe, shouldn’t they be able to tell us what evidence would be scientifically sufficient? And if vaccine proponents want to increase vaccination rates, shouldn’t they be willing to take steps to address mistrust in the scientific community—a known driver of vaccine hesitancy—even if they view the research as redundant?
If successful and productive, an adversarial collaboration on vaccines could serve as a model for addressing other politicized issues in public health and science-informed policy more broadly. For researchers, engaging with those who have lost trust in the scientific community—in good faith and without condescension—is one way to start rebuilding that trust. At the same time, if critics of the mainstream scientific community won’t engage to address their own concerns, it suggests that, perhaps, their dissatisfaction is with what the science has been telling us—and not the quality or quantity of the research.
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