The Hidden Half of the Message: Why Trial Design Matters More Than You Think

Several years ago, during a qualitative research session testing a visual aid for a new heart failure medication, a seasoned cardiologist made a comment that quietly—but powerfully—punctured a long-standing assumption in clinical messaging. I had just presented a message that our prior quantitative work had flagged as a top performer: a 25% relative reduction in the risk of hospitalization. He paused, nodded slowly, and then asked, “Were these patients NYHA Class II or Class III? And how many had preserved ejection fraction?”

That one question surfaced a core, often-overlooked truth: physicians often don’t just evaluate the outcome—they interrogate the path that led to it. Their clinical reasoning depends not only on the size of the effect, but on the credibility of the context. They’re constantly asking—whether out loud or internally—Do these data reflect the kinds of patients I actually treat? Even if the physician hasn't asked the question out loud, you can bet they are thinking it.

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What the Trial Showed vs. How the Trial Was Built

Pharma, biotech, and medtech companies pour enormous effort into generating headline results: the primary endpoint, the p-value, the topline efficacy. It’s not surprising—those numbers are critical for regulatory success, investor confidence, and market buzz. But when it comes to engaging physicians—the people who will actually decide whether to prescribe—a different kind of rigor often is required.

Physicians are scientists first. Many may not say it explicitly, especially within the context of a marketing research interview or focus group, but they are trained to look past the results to how those results were obtained. Medical school teaches them that industry-sponsored trials are designed to succeed. That doesn’t mean they don’t trust the data entirely—but it does mean they instinctively ask questions the glossy efficacy slides don’t answer. Questions like:

• Who exactly was included in the study?
• What were the exclusion criteria?
• How advanced was the disease in the patient population?
• How were prior treatments handled?
• Were there any confounding co-morbidities?

In many messaging studies, the implicit assumption is that the availability of data alone will drive prescribing. But this overlooks a fundamental aspect of physician thinking: they use heuristics informed by training, clinical experience, and a quiet skepticism of industry-sponsored research. They may not voice it explicitly, but in the background, their brains are asking:

• Do these results map to my patient population?
• Were the exclusion criteria too restrictive?
• Did they sidestep the “harder” patients—older, sicker, with more comorbidities?

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The Unspoken Skepticism

This skepticism doesn't always show up in the qualitative or quantitative readouts of message testing studies. That’s because the format often doesn't allow physicians the time to express these more structural concerns. When a doctor is evaluating a list of messages in a blinded or survey-based format, their feedback is often a surface-level reaction. But beneath that response is a subconscious evaluation: Does this data actually apply to my patients?

If the answer is “I’m not sure,” the credibility of even the most promising efficacy number begins to crumble.

One recent study we conducted illustrated this perfectly. In a quantitative survey, physicians ranked the efficacy message highly. But in follow-up interviews, many admitted they had lingering questions about how that number was achieved. They wanted to know more about the trial design, patient demographics, and baseline characteristics. In short, they were looking for reassurance that the data was translatable—that it would hold up in the messy, imperfect, comorbidity-laden real world.

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Trial Design as a Messaging Asset

Here’s the opportunity: the design of the trial—often buried in the appendix or hidden behind protocol language—is a messaging asset. In some cases, it’s more powerful than the efficacy data itself.

If your trial included patients with advanced disease, say so. If your inclusion criteria didn’t eliminate those with multiple chronic conditions, highlight it. If the average patient in your study looks like the patients a physician sees on a Wednesday morning—make that the story. The “real-world-ness” of your data can be a differentiator. But only if you tell that story clearly.

It’s not about overwhelming physicians with every detail of the protocol. It’s about surfacing the aspects of trial design that anticipate their skepticism—and answer the questions they haven’t yet asked out loud.

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How to Build Messaging That Resonates with the Clinical Mind

So how do we embed this thinking into our messaging strategy?

1. Distill design into messaging—not just data. Avoid dumping protocol details. Instead, create high-yield, poignant summaries that frame the results in terms of patient characteristics and trial realism.
2. Anticipate lateral skepticism. Even if physicians don’t vocalize it, assume they’re thinking about real-world applicability. Develop messaging that brings that layer to the surface.
3. Make design elements part of message testing. Don’t just test claims—test contextualizers. Statements like “40% of patients had at least two comorbidities” or “Average age was 72 with prior hospitalization” provide anchoring cues that enhance believability.
4. Build availability into your communications toolkit. Ensure field teams, MSLs, and digital channels are equipped to deliver trial design insights—not as an afterthought, but as part of the core narrative.

In an era where trust in data is hard-earned, the how matters as much as the what. Messaging should not simply present results; it should reconstruct the logic of the trial in a way that mirrors how physicians think—deeply, critically, and always in service of the patient in front of them.

After all, in a world saturated with data, belief still hinges on understanding.

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