Techniques for Effective Scientific Communication

If every doctor communicated like Paul Offit MD, TikTok wellness grifters would be unemployed by Christmas. WIRED sat him down to answer common vaccine questions — and it might be the clearest, most grounded piece of public-facing medical communication I’ve ever seen. I’ve followed Offit’s work for decades — but I’ve never heard him speak this plainly about common questions around vaccination. That matters. Because today ACIP is (still) debating whether to scrap the universal newborn dose of Hepatitis B vaccine for babies born to hepatitis-negative mothers — or delay that dose by months. Some of my favorite lines from the video: “𝗔𝗻𝗱 𝘄𝗵𝗶𝗹𝗲 𝗶𝘁’𝘀 𝘃𝗲𝗿𝘆 𝗲𝗮𝘀𝘆 𝘁𝗼 𝘀𝗰𝗮𝗿𝗲 𝗽𝗲𝗼𝗽𝗹𝗲, 𝗶𝘁’𝘀 𝗵𝗮𝗿𝗱 𝘁𝗼 𝘂𝗻𝘀𝗰𝗮𝗿𝗲 𝘁𝗵𝗲𝗺.” (That may be the single best summary of the entire vaccine misinformation era.) And when someone asks why babies get “so many shots,” he doesn’t spiral into jargon or defensiveness. He explains the whole point in one sentence: “𝗩𝗮𝗰𝗰𝗶𝗻𝗲𝘀 𝗮𝗿𝗲 𝗴𝗶𝘃𝗲𝗻 𝘁𝗼 𝗽𝗿𝗲𝘃𝗲𝗻𝘁 𝗱𝗶𝘀𝗲𝗮𝘀𝗲𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝘂𝘀𝗲 𝗰𝗵𝗶𝗹𝗱𝗿𝗲𝗻 𝘁𝗼 𝘀𝘂𝗳𝗳𝗲𝗿 𝗼𝗿 𝗯𝗲 𝗵𝗼𝘀𝗽𝗶𝘁𝗮𝗹𝗶𝘇𝗲𝗱 𝗼𝗿 𝗱𝗶𝗲.” BOOM. No drama. No spin. Just the truth clinicians sometimes forget to say out loud. This is what good communication looks like: clarity without condescension, empathy without indulgence and facts that actually land. If ACIP swings the wrong way — moving from a “safe by default” baseline to a “parent-choice roulette” at birth — we won’t just be trading a shot. We’ll be eroding decades of public-health trust and reopening the door to preventable chronic disease. If the birth-dose is delayed or abandoned, some of those newborns will turn up decades later with chronic HepB: cirrhosis, liver cancer, maybe needing transplant… and deaths in 2040s, 2050s, 2060s. Long after the current ACIP panel will be retired or dead. But the consequences won’t be. We keep talking about “restoring trust in medicine.” This is what it actually looks like. Full video below. Watch it if you talk to patients about vaccines — or if you just care what good medicine sounds like. https://lnkd.in/gMqWNY5t

Why do we still explain cancer the same way we did 20 years ago? In a world of 10-second attention spans and infinite scrolls, our medical messages still sound like patient leaflets from the ’90s. It’s time we stopped relying on jargon, fear, and bland diagrams—and started innovating how we talk about health. Because when a reel or a meme can make someone laugh and go for a checkup—that’s impact. I’m an oncologist. I work with science. But I speak in metaphors, memes, and middle-class family WhatsApp language. Not because it’s trendy—because it works. Healthcare needs communication that meets people where they are. Not where we wish they were. Let’s rethink, repackage, and rehumanize healthcare. Innovation isn’t just about machines—it’s about messaging. #HealthcareInnovation #CancerAwareness #MedicalCommunication

“Our messaging is not working” Enrique Ortiz, a veteran conservationist and founding member of the Andes Amazon Fund, has spent decades translating the complexities of ecosystems into action. But in his recent commentary for Mongabay, he issues a striking critique—not of science itself, but of how it’s conveyed. “Facts are not the most important part,” Ortiz writes. “The current narrative needs a re-thinking.” That rethinking, he argues, begins not with more data, but with deeper insight into how people process information, make decisions, and respond emotionally to the world around them. Ortiz’s concern is not that people are unaware of climate change. In fact, the majority of the global population acknowledges it. But many remain unmoved, caught in a web of abstract language, ideological filters, and emotional distance. Scientific accuracy, while essential, often falters in the face of cognitive and cultural barriers. Ortiz points to the findings of cognitive scientists and neuroscientists: facts rarely shift belief systems. Instead, people gravitate toward stories, experiences, and social cues. “When facing uncertainty,” he notes, “humans make decisions that are satisfactory, rather than optimal.” This disconnect, Ortiz argues, is especially clear in environmental communication. Words like “rewilding,” “green,” or “ecological” may have once inspired clarity, but have since become muddled through overuse or conflicting interpretations. Worse, they sometimes trigger skepticism or backlash. In this fog of abstraction, the human connection is lost. What’s needed, Ortiz suggests, is a new narrative strategy—one that harnesses the emotional power of stories and speaks to how people actually think and feel. He draws from his own experience as an educator: while his lectures on plant-animal interactions faded from memory, it was the stories that lingered. This phenomenon, known as “narrative transportation,” isn’t mere sentimentality. It’s a neurological reality that helps ideas stick—and decisions shift. Rather than continuing to warn of catastrophe, Ortiz believes we should share stories of adaptation and resilience. From Andean farmers modifying how they grow quinoa and potatoes, to everyday consumers making environmentally conscious choices, these narratives offer agency and hope. They bridge divides and foster shared values. “Our messaging is not working,” Ortiz writes bluntly. “We need a revolution in narratives—and in how we tell them.” That revolution may begin not in the lab or the newsroom, but in the quiet space where empathy meets understanding—and where change can finally take root. 📰 His piece: https://lnkd.in/gmrWBcc5 📸 Hoatzin. My photo.

Smart people sound dumb when they try to sound smart. (and a Nobel Prize winner proved it). Richard Feynman was a late talker. Didn't say a word until he was three. His teachers thought he was slow. He went on to win the Nobel Prize in Physics. But here's what made him different: He could explain quantum physics to a five-year-old. While other professors hid behind jargon, Feynman exposed the truth—complexity is often a mask for shallow understanding. The research backs this up. From lectures, we remember 5%. From reading, 10%. From teaching others? 90%. So Feynman built his learning method around teaching. I've used it to master everything from investing to psychology. Here's how it works: First, study deeply. Attack your topic from every angle. Books, videos, conversations. Fill pages with notes. Then teach it simply. Find someone who knows nothing about it. Explain using only simple words. No jargon. No acronyms. Just clarity. Next, find the gaps. Where did you stumble? Where did you reach for fancy words? Those are your knowledge holes. Go back and fill them. Finally, refine and repeat. Turn your explanation into a story. Share it. Improve it. Now you truly understand. I've watched billion-dollar founders explain their business in one sentence. I've also watched people use 47 slides to say nothing. Guess which ones succeed. This week: Pick one thing you want to master. Give yourself a week to study. Then teach it to someone. You'll be shocked how much deeper your understanding becomes when you're forced to simplify.

“If you can’t be simple, you will be ignored.” That sentence is an oversimplification. I used it anyway. Not because the truth is simple, but because simplicity is the price of entry. In academia, we are trained to embrace nuance, caveats, and complexity. In public debate, especially around climate and energy, that instinct often works against us. Attention is scarce, timelines are short, and if experts refuse to offer clear answers, others will gladly fill the gap with simpler and often misleading ones. The title of my latest blog post is deliberately blunt. It’s the hook. What follows is the detail: an argument for thinking about communication as a ladder, where we lead with a clear takeaway and then layer in context, trade-offs, data, and uncertainty for those who want to go deeper. Simplifying is not dumbing down. It’s an act of translation. This comes with risks. Taking a position invites criticism. Being visible invites pushback. But in contested debates, silence and excessive caution are also positions, just ones that cede the ground to louder and less rigorous voices. If we want research to matter beyond the ivory tower, we need to learn to speak two languages at once: the rigorous language of the lab and the accessible language of the public square. Being right is not the same as being heard. https://lnkd.in/egnRHi8k

Users don't suck, but the information provided to them can. If your IFU reads like a legal contract, people won’t read it. Why? Because they’re confusing. Too wordy. Too complex. Too scattered. A great IFU should feel like having a clear-headed expert guiding you step by step. The user needs to know what to do, how to do it, and when to do it. Here's 20 recommendations/writing rules to improve your IFU↴ 1. Write procedures in short, identifiable steps, and in the correct order. 2. Before listing steps, tell the reader how many steps are in the procedure. 3. Limit each step to no more than three logically connected actions. 4. Make instructions for each action clear and definite. 5. Tell the user what to expect from an action. 6. Discuss common use errors and provide information to prevent and correct them. 7. Each step should fit on one page. 8. Avoid referring the user to another place in the manual (no cross-referencing). 9. Use as few words as possible to present an idea or describe an action. 10. Use no more than one clause in a sentence. 11. Write in a natural, conversational way. Avoid overly formal language. 12. Express ideas of similar content in similar form. 13. Users should be able to read instructions aloud easily. Avoid unnecessary parentheses. 14. Use the same term consistently for devices and their parts. 15. Use specific terms instead of vague descriptions. 16. Use active verbs rather than passive voice. 17. Use action verbs instead of nouns formed from verbs. 18. Avoid abbreviations or acronyms unless necessary. Define them when first used and stay consistent. 19. Use lay language instead of technical jargon, especially for medical devices intended for laypersons. 20. Define technical terms the first time they appear and keep definitions simple. Prioritize the user while ensuring MDR/IVDR compliance.

Excellent tips here illustrating how a subtle change in tone can have a massive influence upon how your message is received. 1) Acknowledge Delays with Gratitude "Sorry for the late reply…" "Thank you for your patience." 2) Respond Thoughtfully, Not Reactively "This is wrong." "I see your point. Have you considered [trying alternative]?" "Thank you for sharing this—I appreciate your insights." 3) Use Subject Lines That Get to the Point "Update" "Project X: Status Update & Next Steps" 4) Set the Tone with Your First Line "Hey, quick question…" "Hi [Name], I appreciate you. I wanted to ask about…" 5) Show Appreciation, Not Acknowledgment "Noted." "Thank you for sharing this—I appreciate your insights." 6) Frame Feedback Positively "This isn’t good enough." "This is a great start. Let’s refine [specific area] further." 7) Lead with Confidence "Maybe you could take a look…" "We need [specific task] completed by [specific date]." 8) Clarify Priorities Instead of Overloading "We need to do this ASAP!" "Let’s prioritize [specific task] first to meet our deadline." 9) Make Requests Easy to Process "Can you take a look at this?" "Can you review this and share your feedback by [date]?" 10) Be Clear About Next Steps "Let’s figure it out later." "Next steps: I’ll handle X, and you confirm Y by [deadline]." 11) Follow Up with Purpose, Not Pressure "Just checking in again!" "I wanted to follow up on this. Do you need any additional details from me?" 12) Avoid Passive-Aggressive Language "As I mentioned before…" "Just bringing this back in case it got missed."

Many amazing presenters fall into the trap of believing their data will speak for itself. But it never does… Our brains aren't spreadsheets, they're story processors. You may understand the importance of your data, but don't assume others do too. The truth is, data alone doesn't persuade…but the impact it has on your audience's lives does. Your job is to tell that story in your presentation. Here are a few steps to help transform your data into a story: 1. Formulate your Data Point of View. Your "DataPOV" is the big idea that all your data supports. It's not a finding; it's a clear recommendation based on what the data is telling you. Instead of "Our turnover rate increased 15% this quarter," your DataPOV might be "We need to invest $200K in management training because exit interviews show poor leadership is causing $1.2M in turnover costs." This becomes the north star for every slide, chart, and talking point. 2. Turn your DataPOV into a narrative arc. Build a complete story structure that moves from "what is" to "what could be." Open with current reality (supported by your data), build tension by showing what's at stake if nothing changes, then resolve with your recommended action. Every data point should advance this narrative, not just exist as isolated information. 3. Know your audience's decision-making role. Tailor your story based on whether your audience is a decision-maker, influencer, or implementer. Executives want clear implications and next steps. Match your storytelling pattern to their role and what you need from them. 4. Humanize your data. Behind every data point is a person with hopes, challenges, and aspirations. Instead of saying "60% of users requested this feature," share how specific individuals are struggling without it. The difference between being heard and being remembered comes down to this simple shift from stats to stories. Next time you're preparing to present data, ask yourself: "Is this just a data dump, or am I guiding my audience toward a new way of thinking?" #DataStorytelling #LeadershipCommunication #CommunicationSkills

Designing For Things You Can't See. Microbes aren't easy brand assets to work with. You can't photograph them and you can't point at them. One bad headline has taught most people to associate them with illness, contamination, or something they should scrub harder. Not ideal when the job is building trust around something meant to support human and planetary health. Most people can't picture their microbiome, but they can decide in three seconds whether a pack looks credible. That gap shapes how they read the science and the brand behind it. That's the starting point for anyone designing in this space. Push too far into clinical cues and everything turns cold. Drift too far into lifestyle and the credibility drops out. Neither survives in a category built on evidence, consistency, and long‑term use. The language doesn't help. Strains, metabolites, pathways, gut–brain axis. All accurate, none inviting. The challenge isn't simplifying the science, but organising it so people can grasp what matters without wading through terminology. Packaging has to make sense of an ecosystem no one can see. And because the science is still unfamiliar to most people, the visual defaults carry even more weight. The work converges visually, even as the propositions diverge. Different strains, claims, and applications sit behind packs that resolve in almost the same way. You register the category before the brand. That's the space Seed has worked in for years, and it shaped the brief. As the range grew, they partnered with MOUTHWASH Studio to evolve the identity without losing clarity. The focus stayed on structure rather than surface. With Dinamo, the studio developed Seed Sans, a variable typeface that shifts between precision and expression without tipping into either. The form of Seed's DS‑01 product fed into the type design. Capsules, dots, and symbols sit inside the character set, letting scientific ideas appear within the text instead of around it. The colour system expanded in the same way. Seed's green remained the anchor, joined by tones drawn from Darwin's Nomenclature of Colour, giving the system range without losing its centre. Growth curves under a microscope informed how the system moves, echoing the cycles Seed works with. But movement only matters if the system holds its shape everywhere it shows up. All of this sits inside a framework built to adapt. The brand speaks differently to customers, clinicians, and retail buyers while still holding together across platforms and markets. Taken together, the work points to a broader shift. Seed's evolution shows where this category is settling. Systems that can carry complexity without defaulting to the same visual shortcuts. Work that stays legible as the science expands instead of smoothing into tone. Designing for microbes is less about showing the unseen and more about deciding what earns trust, holds together, and survives first contact with a shelf. 📷MOUTHWASH Studio

Health systems must release test results to patients immediately. Yet, lacking context, patients often cannot fully interpret their results alone. A key challenge is that results like pathology reports contain complex medical terminology and are not written for patients. A newly published JAMA study sought to determine whether supplementing traditional reports with plain language explanations helps patients better understand their results. [doi:10.1001/jama.2024.25461] The investigators randomized 2238 adult males to receive the same hypothetical clinical vignette along with either: (1) a patient-centered pathology report (PCPR); (2) a standard university pathology report; or (3) a standard VA report. They found that patients who received the patient-centered report were far more likely to appropriately identify the report’s prostate cancer diagnosis (93% vs. 39% and 56%; P < .001) and severity (93% vs. 41% and 36% P < .001). [see table] The authors recommend that “Hospital systems should consider including PCPRs with standard pathology reports to improve patient understanding.” My take: EHRs both empower and overwhelm us with information. Practicing physicians like me fear our patients will read – and misinterpret – their test results before we have a chance to discuss them. This study showed the value of pathologists spending a few minutes adding a plain-language, patient-centered report to supplement the standard (medical-language) report. Of course, few pathologists have the time to do this for each specimen they read. What’s so exciting is that Gen AI can do this in seconds. And these same principles (and opportunities) extend beyond pathology reports to other test results, including imaging studies, procedure reports, and even lab tests. Though it may not be as glamorous as AI diagnosis or even ambient documentation, translating medical text/jargon into patient-friendly language may be one of AI's most pragmatic, attainable, and impactful uses today.