‘Gold Standard’ Science? How RFK Jr. and the Administration Measure Up

President Donald Trump and his health secretary, Robert F. Kennedy Jr., have repeatedly pledged that federal health policy will follow the "gold standard" of science. Many public-health experts say recent actions by the administration run counter to that promise — relying on preliminary studies, anecdotes or unproven theories to question established treatments and influence policy.

In a move that alarmed many scientists, the nation’s top public health agency revised language on its website in a way that appeared to contradict the scientific consensus that vaccines do not cause autism. The change drew sharp criticism across the public-health community.

Dr. Daniel Jernigan, who resigned from the Centers for Disease Control and Prevention in August, told reporters that Kennedy seems to be "going from evidence-based decision making to decision-based evidence making." That remark was one of several recent critiques of the administration’s approach to settled science.

In September, President Trump offered medical guidance that experts say was supported by little or no reliable evidence. Speaking directly to pregnant women and parents, he advised against taking acetaminophen (the active ingredient in Tylenol) and repeatedly revived a long-debunked link between vaccines and autism, describing his view as a personal hunch: "I have always had very strong feelings about autism and how it happened and where it came from," he said.

At a two-day meeting this fall, vaccine advisers selected by Kennedy questioned standard practice around vaccinating newborns against hepatitis B — a shot that has been shown to dramatically reduce disease and deaths. Pediatric infectious disease specialist Dr. Flor Munoz criticized those discussions, noting they relied largely on case reports and anecdotes rather than systematic evidence.

The administration’s skepticism has emerged amid the nation’s worst year for measles in more than three decades. Kennedy has cast doubt on the measles vaccine while promoting unproven treatments and suggesting that some unvaccinated children who died were "already sick." Scientists argue that such rhetoric conflicts with extensive data showing vaccines prevent severe illness and death.

What experts mean by the "gold standard"

When scientists refer to the "gold standard," they mean using the best available methods to answer a specific question — not one universal test that fits every situation.

Randomized clinical trials are often described as the most rigorous design because they assign participants randomly to treatment or control groups that are otherwise comparable. Many trials are "blinded," so neither participants nor researchers know who received which intervention, minimizing bias.

However, randomized trials aren't always possible or ethical. Jessica Steier, a public-health scientist, points out that conducting placebo-controlled vaccine trials can be unethical once a vaccine’s safety and effectiveness are well established: withholding a proven vaccine can harm participants.

When observational and real-world data matter

For questions about long-term effects or broadly applied behaviors, researchers often rely on observational studies that follow people over time without intervening. Observational work helped establish, for example, that fluoride reduces cavities; later laboratory studies explained how fluoride strengthens enamel. But observational studies generally show correlation rather than causation and can be confounded by factors such as the reason a medication was taken.

Real-world evidence — large-scale surveillance and data from health systems — complements trials by revealing rare side effects or confirming effectiveness across diverse populations. Vaccine surveillance systems can detect events as rare as one-in-a-million; to date, that monitoring has not shown a wave of chronic disease caused by vaccines. "If vaccines caused a wave of chronic disease, our safety systems — which can detect 1-in-a-million events — would have seen it. They haven’t," said Dr. Jake Scott, an infectious disease physician.

What credible science looks like

Publication alone does not equal transparency or reliability. High-quality research typically demonstrates several key features:

• The hypothesis and analysis plan are set before the study begins and are not changed midstream.
• Authors disclose conflicts of interest and funding sources.
• Work undergoes independent peer review by experts without a stake in the outcomes.
• Data, methods and statistical code are made available or clearly described so others can reproduce findings.
• Conclusions are supported by reliable, cited evidence and placed in the context of previous research.

Transparency allows science to correct itself. "That’s how science works," said Dr. Steven Woloshin of Dartmouth College, who has spent much of his career scrutinizing evidence behind health policy.

"Science isn’t about reaching certainty. It’s about trying to reduce uncertainty to the point where you can say, ‘I have good confidence that if we do X, we’ll see result Y.’ But there’s no guarantee." — Dr. Steven Woloshin

How to evaluate claims and studies

If you encounter a research paper, report, or a public official citing a study to justify a change in behavior or policy, consider these questions:

• Who conducted the research? What is their expertise, and are conflicts of interest disclosed?
• Who funded the work and who stands to benefit?
• Is the study published in a reputable, peer-reviewed journal?
• What precise question did the researchers ask, and were the comparison groups fair and appropriate?
• Is there a limitations section that explains what the study cannot prove or other potential biases?
• Do the findings align with the broader scientific consensus, or do they contradict a large body of high-quality evidence?

Ultimately, good policy and medical guidance should rest on rigorous methods, transparent reporting, and a balance of evidence types. Anecdotes and early studies can generate hypotheses, but decisions affecting large populations require reproducible, well-vetted science.